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In Hidden Depths, Professor Penny Spikins explores how our emotional connections have shaped human ancestry. Focusing on three key transitions in human origins, Professor Spikins explains how the emotional capacities of our early ancestors evolved in response to ecological changes, much like similar changes in other social mammals. For each transition, dedicated chapters examine evolutionary pressures, responses in changes in human emotional capacities and the archaeological evidence for human social behaviours. Starting from our earliest origins, in Part One, Professor Spikins explores how after two million years ago, movement of human ancestors into a new ecological niche drove new types of collaboration, including care for vulnerable members of the group. Emotional adaptations lead to cognitive changes, as new connections based on compassion, generosity, trust and inclusion also changed our relationship to material things. Part Two explores a later key transition in human emotional capacities occurring after 300,000 years ago. At this time changes in social tolerance allowed ancestors of our own species to further reach out beyond their local group and care about distant allies, making human communities resilient to environmental changes. An increasingly close relationship to animals, and even to cherished possessions, appeared at this time, and can be explained through new human vulnerabilities and ways of seeking comfort and belonging. Lastly, Part Three focuses on the contrasts in emotional dispositions arising between ourselves and our close cousins, the Neanderthals. Neanderthals are revealed as equally caring yet emotionally different humans, who might, if things had been different, have been in our place today. This new narrative breaks away from traditional views of human evolution as exceptional or as a linear progression towards a more perfect form. Instead, our evolutionary history is situated within similar processes occurring in other mammals, and explained as one in which emotions, rather than 'intellect', were key to our evolutionary journey. Moreover, changes in emotional capacities and dispositions are seen as part of differing pathways each bringing strengths, weaknesses and compromises. These hidden depths provide an explanation for many of the emotional sensitivities and vulnerabilities which continue to influence our world today.

In Hidden Depths, Professor Penny Spikins explores how our emotional connections have shaped human ancestry.
Focusing on three key transitions in human origins, Professor Spikins explains how the emotional capacities of our early ancestors evolved in response to ecological changes, much like similar changes in other social mammals. For each transition, dedicated chapters examine evolutionary pressures, responses in changes in human emotional capacities and the archaeological evidence for human social behaviours.
Starting from our earliest origins, in Part One, Professor Spikins explores how after two million years ago, movement of human ancestors into a new ecological niche drove new types of collaboration, including care for vulnerable members of the group. Emotional adaptations lead to cognitive changes, as new connections based on compassion, generosity, trust and inclusion also changed our relationship to material things. Part Two explores a later key transition in human emotional capacities occurring after 300,000 years ago. At this time changes in social tolerance allowed ancestors of our own species to further reach out beyond their local group and care about distant allies, making human communities resilient to environmental changes. An increasingly close relationship to animals, and even to cherished possessions, appeared at this time, and can be explained through new human vulnerabilities and ways of seeking comfort and belonging. Lastly, Part Three focuses on the contrasts in emotional dispositions arising between ourselves and our close cousins, the Neanderthals. Neanderthals are revealed as equally caring yet emotionally different humans, who might, if things had been different, have been in our place today.
This new narrative breaks away from traditional views of human evolution as exceptional or as a linear progression towards a more perfect form. Instead, our evolutionary history is situated within similar processes occurring in other mammals, and explained as one in which emotions, rather than 'intellect', were key to our evolutionary journey. Moreover, changes in emotional capacities and dispositions are seen as part of differing pathways each bringing strengths, weaknesses and compromises. These hidden depths provide an explanation for many of the emotional sensitivities and vulnerabilities which continue to influence our world today.

U.S. forces launched a third strike against Iran-linked groups on Sunday, the latest in an increasingly destructive series of exchanges that have cast a new light on the continued U.S. troop presence in the Middle East. American aircraft struck a weapons storage facility and command-and-control center used by Iran-backed groups in Syria, according to officials. "Within the last two hours, the U.S. has taken precision defensive strikes against two sites in Syria," an official told ABC News. The two structures were located near the eastern Syrian cities of Mayadin and Abu Kamal, according to statements issued on Sunday by the Department of Defense and U.S. Central Command (CENTOM). "The President has no higher priority than the safety of U.S. personnel, and he directed today's action to make clear that the United States will defend itself, its personnel, and its interests," Defense Secretary Lloyd Austin said in a statement. Up to seven "Iranian proxy fighters" were killed at one of the two locations struck by U.S. warplanes, according to Jennifer Griffin, chief national security correspondent for Fox News, citing a senior defense official. This is the third such strike since October 26, reflecting a continued effort by the U.S. to retaliate against Iran-linked groups that the White House says are responsible for a spate of ongoing rocket and drone attacks against U.S. military personnel in Iraq and Syria. The U.S. sent forces including two carrier strike groups headlined by the USS Gerald R. Ford Carrier and USS Dwight D. Eisenhower, squadrons consisting of F-15E Strike Eagle aircraft and A-10 close-air-support (CAS), and the USS Bataan Amphibious Ready Group to the region following the October 7 Hamas attacks on Israel and subsequent outbreak of war in Gaza. High-ranking officers including a Marine three-star general were reportedly sent to help advise Israeli leadership as it proceeds with its campaign and another 2,000 U.S. personnel were ordered to prepare to deploy last month. Iranian leaders have unsurprisingly taken a strong policy stance in favor of Hamas, though the full extent of their foreknowledge of and support for the October 7 attack remains unclear. Reports citing U.S. intelligence findings suggest that senior Iranian officials were surprised by the attack, undermining or at least heavily complicating claims of direct Iranian involvement. Nevertheless, Tehran has been accused of mobilizing its robust network of regional proxies to launch scores of attacks against American personnel and infrastructure. U.S. assets have been attacked at least 52 times by Iran-linked groups since October 17, according to officials. A total of fifty-six service members have been injured according to numbers provided by the Pentagon, with over two dozen suffering traumatic brain injuries. Washington has responded to these attacks with a mix of warnings by top officials, which have gone wholly unheeded, and retaliatory strikes. The Sunday strikes came shortly on the heels of airstrikes conducted by two F-15 fighter jets against Iran-linked facilities in Syria earlier last week. These two latest rounds of U.S. strikes come just two weeks after a similar spate of operations targeting facilities in eastern Syria that officials say were "used by Iran's Islamic Revolutionary Guard Corps (IRGC) and affiliated groups." The strikes on October 26, which the Pentagon said were not related to "the ongoing conflict between Israel and Hamas," were partly intended to deter Iran from coordinating further attacks on U.S. personnel. Yet attacks on American troops have not only continued but intensified in recent weeks, with Iran-backed militants reportedly assaulting U.S. bases with drones carrying even larger payloads.Growing risks to American service members and concerns that these continued exchanges could trigger a direct military confrontation between the U.S. and Iran have spurred new perspectives on the costs and benefits of the continued military presence in the Middle East. The 2,500 and 900 troops in Iraq and Syria, respectively, are ostensibly there to prevent the resurgence of the Islamic State, but the rationale behind this presence has come under scrutiny. "If a U.S. ground presence in Iraq and Syria were absolutely necessary to achieve a core U.S. security interest, then perhaps these risks would be tolerable. But this is hardly the case," Defense Priorities (DEFP) fellow Daniel DePetris wrote in a release on November 9. "ISIS lost its territorial caliphate more than four years ago and is now relegated to a low-grade, rural insurgency that local actors can contain. The U.S. military presence is not only unnecessary, but also a dangerous tripwire for a wider war." The continued deployments put service members at constant risk, especially in the context of heightened regional tensions stemming from the Israel-Hamas war, and serve neither clear nor achievable policy aims, argued Justin Logan, the Cato Institute's director of defense and foreign policy studies."Attacks on U.S. troops in Iraq and Syria will no doubt continue—the solution is to remove U.S. forces which remain as targets only because they're within range of these local militias," said a DEFP explainer published earlier this month, suggesting that U.S. troops in stationed within striking distance of local militants be redeployed to better-defended positions in the Middle-East. American troops have reportedly been attacked a staggering four times within less than a day of Sunday's airstrike, sending the clearest signal yet that retaliatory strikes have not had their intended deterring effect. As the Gaza crisis roils on, the dangers confronting U.S. troops — and, with them, calls to reconsider the tools and goals of American power projection in the Middle East—will likely intensify.

학위논문(석사)--서울대학교 대학원 :국제대학원 국제학과(국제지역학전공),2019. 8. Song, Jiyeoun. ; 초록 운송 비용의 절감과 정보에 대한 용이한 접근은 사람들이 한 곳에서 다른 곳으로 이동하는 경향을 증가시켜 개발 도상국에서 선진국에 이르기까지 국제적인 국제 이주 경향을 증폭시켰다. 아프리카는 이주민이 주로 공급되는 지역 중 하나이다. 해당 지역 사회는 세계에서 가장 많은 이동을 보이고 있다. 경제, 정치, 기후문제 및 분쟁에서 벗어나 경제적 번영과 정치적 안정을 찾아 주로 유럽으로 이주한다. 수십 년 동안 많은 연구자들이 이주의 파급 효과로 인해 해당 국가에게 사회 경제적 안정성에 유해한 현상을 강조하면서 이주가 두뇌 유출과 연관 되어왔다. 그러나 이러한 비관적인 견해는 이민자들이 출생국에 기여하는 낙관적인 요소를 고려하면 출생국의 발전에 기여한 것을 알 수 있다. 예를 들어 송금 및 외국인 직접 투자와 같은 재정적 기여는 경제 성장과 모국의 산업 변형을 저해하는 유동성의 희소성을 해결하는 데 중요한 역할을 한다. 외국인 직접 투자 (FDI)에 관한 한, 많은 학자들은 이주자와 정확하게 이주하는 나라가 외국인 직접 투자의 유입 국가에 긍정적 인 영향을 미친다고 주장하면서 이주와 외국인 투자의 긍정적인 상관 관계를 증명 하였다. 비록 관련되었지만 대부분이 아시아 국가들을 대상으로 한 기존 연구들은 아프리카 국가들, 정확하게는 사하라 이남 국가들을, 고려하지 않은 연구였다. 본 연구의 목표는 중앙아프리카 경제 공동체(CEMAC) 지역의 국가인 카메룬의 상황을 평가하기 위해 상대적 질적 방법론을 사용하여이 기존연구의 한계로 인해 채우지 못한 공백을 채우는 것이다. 수집 된 데이터를 분석 한 결과, 해당 경제공동체에서 카메룬이 이민자의 주요 공급자인 것으로 나타났고 이러한 이유로 경제적 공동체의 다른 회원국에 비해 외국인직접투자를 우선으로 수령하는 국가로 예측하였다. 그러나 양적 관측에서, 즉 CEMAC에서 FDI의 분포와 결과적으로 하위 지역의 FDI의 주요 추진 요인을 이해하기위한 회귀 분석의 사용 했을시 전혀 다른 결과가 나왔다. 결론적으로, 아시아와 같은 세계의 다른 지역과 달리 해당 지역의 투자자들이 천연 자원에 관심을 갖게됨에 따라 외국으로의 이민이 FDI의 동인이되지 못한다는 것이 드러났다. ; Abstract The reduction of transportation cost and the easy access to information have increased the propensity of people to move from one place to another thus amplifying the global international migration trend, generally from developing to developed countries. Africa appears among the main providers of migrants as its community is one of the most mobile in the world. Running away from economic, political, climatic and security struggles, they mainly migrate to Europe thanks to its economic prosperity and political stability. For many decades migration has been assimilated to brain drain by many researchers presenting the phenomenon as harmful for the socioeconomic stability of sending countries. But this pessimistic view has given the way to a more optimistic consideration that gives credit to migrants and migration as contributors to the development of sending country. Their financial contributions, for instance remittances and Foreign Direct Investments, play a key role in solving liquidity scarcity that hampers the economic growth and the industrial transformation of home country. As far as FDI is concerned, many scholars have concluded on a positive correlation between migration and FDI arguing that migrants and precisely tertiary migrant do influence positively attraction of Foreign Direct Investment in Sending country. Though pertinent, these studies, mostly directed towards Asian countries, omitted to include African countries and precisely sub-Saharan countries. The aim of this work is to fill this vacuum using comparative qualitative methodology to assess the situation in Cameroon among countries of the CEMAC sub-region. From the analysis of the collected data, it appears that Cameroon in the sub Region is the main provider of migrants, suggesting therefore that it would be the first recipient of FDI among its peers of the economic community. But the results obtained from the quantitative observation proved otherwise, implying thus the use of another method, namely regression analysis, to understand the distribution of FDI in CEMAC and consequently the main drivers of FDI in the sub-Region. It emerged finally that, unlike in other regions of the globe like Asia; migrant stock is not a driver of FDI as investors in the regional are interested by natural resources. ; Table of content Graphs and tables iv List of abbreviations v Chapter 1. INTRODUCTION 1 1.1 Background of the study 1 1.2 Statement of the problem 2 1.3 Objective of the study 3 1.4 Research question 3 1.5 Hypothesis 3 1.6 Significance of the study 4 1.7 Organization of the study 4 Chapter 2. Literature review 6 2.1 Explanation of key terms 6 2.2 Related literature 7 Chapter 3. CAMEROON FACING THE CHALLENGE OF INTERNATIONAL MIGRATION: THE STATE OF PLAY 12 3.1 Introduction 12 3.2 Overview of Cameroonian emigration 12 3.3 Factors of migration 14 3.4 Profile of Cameroonian emigrants in Africa 14 3.5 Cameroon intellectual elite in developed countries: tertiary migrants 15 3.6 Major destinations of Cameroon tertiary emigrants 16 3.7 Cameroon in CEMAC: comparison of tertiary migrant stocks 17 Chapter 4. MIGRATION POSSIBLE TRIGGER OF FOREIGN DIRECT INVESTMENT 21 4.1 Introduction 21 4.2 Allocation of FDI to Cameroon 21 4.3 The nexus Migration-FDI rooted in social construction 21 4.4 FDI and Migration stock: the share of Cameroon in CEMAC 22 Chapter 5. EMPIRICAL ANALYSIS: THE EFFECTS OF MIGRATION ON FDI INFLOW 28 5.1 Introduction 28 5.2 The approach 28 5.3 Data 29 5.4 Procedure 30 5.5 The variables object of our study 31 5.5.1 Dependent variable 31 5.5.2 Independent variables 31 5.6 Results 32 5.7 Explanation of the non correlation of migrants and tertiary migrants 36 5.7.1 The exclusion of naturalized citizens 36 5.7.2 Migrant networks as pressure groups 37 Chapter 6. CONCLUSION 39 초록 45 Acknowledgements 46 ; Master

A university campus is not only a complex of living, education and auxiliary facilities. It is a certain style of life. It is developed to fulfill a certain task: knowledge preservation and generation.The system of preservation and processing of the society's knowledge has functions similar to the nervous system. The stronger the society's scientific and academic network is, the more intellectual, advanced, diverse and flexible is the society's response to extrinsic stimuli. The nervous system of present day states is similar to the nervous system of insects – with ganglions and different sense organs.A university campus is an elaborate complex of "sense organs" (research laboratories) and "ganglions" (theoretic groups, seminars etc.). The nervous tissue is the most delicate and volatile of all tissues in the organism. Under nutritional deficiency, too strong or too light external effects, the nervous system fails. Its signals malfunction, and either neuralgia or anesthesia occurs. If disorders in the nervous system become more serious, they can lead to a complete paralysis.A university campus is to provide comfortable working conditions for scientists – preservers and generators of knowledge. Comfort is a special thing for them. The level of material needs among campus residents is usually not very high. Their food, clothing and housing requirements are rather modest. Certainly, the sense of security is necessary – any violation in the campus is very painful, like touching a naked nerve. But the most important and vital thing in the campus is a constant and intense flow of all kinds of information.The Internet, libraries, scientific conferences, symposiums and forums are necessary to the campus as the breath of life. It makes dying gasps without it. At the same time, all these "adventures of a thought" are outwardly almost undistinguished. Intensively thinking people look lazy and even inert. A true brainwork is not intension of the Thinker by Roden, but relaxation and meditative calm. (Isn't it the reason why mental workers seem to be idlers in the eyes of administrators?.)In the Late Medieval and Renaissance eras, first universities adopted from monasteries the practice of creating the forms of life comfortable for the society's "nervous system". It is difficult to add something crucially new to this millenarian experience. Therefore, modern campuses (or modern elements of old campuses) are built on the same principles as in the 13th century.Cambridge, one of the oldest university complexes in Europe, can serve as a fine example of an effectively organized campus. Its image is less aristocratic and more applicable than the image of its eternal competitor – Oxford. But they are organized almost equally. Their financial and political independence protects them from economical fluctuations and governmental crises, like a skull protects brain from strokes and cold. The campuses' interior is traditional, comfortable and calm. Their intellectual life is full of intense flows of new knowledge.What is the life like in the Cambridge campus? The article "On the English Land, on Another Planet… Interview with a resident of Cambridge" by Ekaterina Antipina contains an interview from the first person. ; Университетский кампус – это не просто комплекс жилых, учебных и вспомогательных строений. Кампус – это определенный образ жизни. Он формируется для выполнения вполне определенной задачи – сохранения и производства знаний. Система хранения и обработки знаний социума по своим функциям аналогична нервной системе организма.Чем мощнее научно-университетская сеть в сообществе, тем оно «умнее», технологичнее, разнообразнее и гибче в своих реакциях на внешние стимулы. Нервная система современных государств устроена аналогично нервной системе насекомых – с узлами (ганглиями) и разнообразными органами чувств.Университетский кампус это сложный комплекс «органов чувств» (исследовательских лабораторий) и «ганглий» (теоретических групп, семинаров и так далее). Нервная ткань – самая нежная и капризная из всех тканей организма. При недостатке питания, чересчур сильных или наоборот, слишком слабых воздействиях извне нервная система отказывает. Ее сигналы искажаются, возникают либо невралгии, либо анестезии. Если же нарушения в работе нервной системы станут еще серьезнее, то недалеко и до полного паралича.Университетский кампус призван обеспечить комфортные условия для работы ученых – хранителей и производителей знаний. Комфорт для этих людей составляет понятие особое. Как правило, уровень материальных потребностей у обитателей кампуса невысок. В требованиях к еде, одежде, жилище житель кампуса очень неприхотлив.Разумеется, необходимо чувство безопасности – любое насилие в кампусе, как прикосновение к обнаженному нерву, очень болезненно. Но самое важное, жизненно необходимое в кампусе – это постоянный, мощный поток информации во всех возможных видах. Интернет, библиотеки, научные конференции, симпозиумы и прочие форумы необходимы кампусу как воздух. Без них он задыхается и умирает. При этом внешне, для постороннего наблюдателя, все эти «приключения мысли» почти незаметны. Напряженно мыслящие люди выглядят какими-то ленивыми, даже вялыми. Настоящая работа мысли – это не напряжение, как у роденовского «Мыслителя», а расслабленность и медитативный покой. (Может быть, поэтому работники умственного труда в глазах администраторов иногда выглядят просто бездельниками?.)В позднем Средневековье и в эпоху Ренессанса первые университеты переняли у монастырей опыт создания укладов жизни, комфортных для «нервной системы» социума. К этому тысячелетнему опыту трудно добавить что-то принципиально новое, поэтому современные кампусы (или современные элементы старых кампусов) строятся по тем же принципам, что и в тринадцатом веке.Один из старейших университетских комплексов Европы – Кембридж представляет собой замечательный пример и образец эффективно устроенного кампуса. Его имидж менее аристократичный и более прикладной, чем у вечного соперника – Оксфорда. Но устроены оба почти одинаково. Финансовая и политическая независимость защищает их от экономических колебаний и правительственных кризисов, как череп укрывает головной мозг от ударов и холода. Внутреннее пространство кампусов традиционно, уютно и спокойно. Интеллектуальная жизнь их насыщена мощными потоками новых знаний.Каково жить в кампусе Кембриджа? Интервью от первого лица – в статье Екатерины Антипиной «На английской стороне, на чужой планете. Разговор с резидентом Кембриджа».

El trasplante de órganos es considerado uno de los avances más significativos de la medicina moderna y es un procedimiento cada vez más exitoso en términos de supervivencia de los pacientes, siendo actualmente la mejor opción de tratamiento para los pacientes con innumerables patologías. El proceso de donación es insuficiente para cubrir las necesidades de trasplante de la población, por lo tanto, se hace necesario el desarrollo de nuevas estrategias para fortalecer la experiencia y efectividad de los programas existentes. La falta de conocimiento de los profesionales de la salud, su percepción y actitud hacia temas relacionados con el proceso de donación, pueden convertirlos en facilitadores o barreras para la identificación de potenciales donantes. Por esta razón, los recursos disponibles, las actitudes hacia la donación, la legislación y conocimiento de los procesos involucrados en la donación de tejidos y órganos son críticos. Dada la influencia de los profesionales de salud se definen los objetivos de este proyecto de tesis: determinar cuál es el conocimiento y las habilidades de los profesionales de la salud encargados de los trasplantes de órganos y de tejidos en la regional 1, evaluados mediante una herramienta educativa para contribuir a mejorar un programa eficiente de Donación de Órganos y tejidos y así mismo, fijar recomendaciones en aras de aumentar las tasas de donación, con especial énfasis en la actividad hospitalaria en el país. METODOLOGIA Se realizó un estudio basado en el análisis de la evaluación de conocimientos del proceso donación- trasplante de órganos y tejidos en el personal de salud participante en la herramienta educativa llamada "Curso taller primer respondiente del potencial donante de órganos y tejidos". Este curso incluía un formato evaluativo que fue diligenciado de manera anónima por los participantes antes y después de recibir el contenido del curso. El estudio se desarrolló en personal de la Salud de IPS pertenecientes a la Regional I, de la Red Nacional de donación y trasplantes de órganos y tejidos. Con el fin de evidenciar si existen diferencias en el conocimiento de los participantes del curso antes y después de asistir al mismo, se utilizó la prueba de McNemar (p< 0.05). RESULTADOS Entre julio del 2011 y junio del 2012, se realizó el "Curso taller primer respondiente del potencial donante de órganos y tejidos" y se obtuvieron 303 encuestados incluidos médicos, enfermeras y auxiliares de enfermería. Al inicio del curso las respuestas acertadas con relación a legislación, selección del donante, muerte encefálica y mantenimiento del donante estuvieron alrededor del 50%. No fue posible detectar la profesión que pudiese generar riesgo en la detección del donante y los procesos asociados. Posterior al curso, el 72% de las preguntas se respondieron de manera correcta, lo que representa un incremento estadísticamente significativo. Este cambio evidenció significancia estadística al usar la prueba de McNemar y arrojar un valor de p=0.00. .DISCUSIÓN El personal de salud participante en el curso taller proveniente de unidades involucradas como generadoras de donantes muestra un déficit de conocimientos del proceso donación trasplantes lo que puede convertirlos en limitantes para dicho proceso ; Organ transplantation is considered one of the most significant advances in modern medicine and is a successful procedure in terms of patients survival, being nowadays the best treatment option for patients with many pathologies. The donation process is insufficient to cover the transplantation needs of population, therefore, is necessary the development of new strategies to strengthen the experience and effectiveness of existing programs. The lack of knowledge of health professionals, their perception and attitude towards topics related with the donation process, could turn them into facilitators or barriers for potential donors identification. For this reason, the available sources, attitude towards donation, legislation and knowledge of involved processes in tissue and organ donation are critic. Given the influence of health professionals the objectives of this project are defined: determine which is the knowledge and skills of health professionals in charge of organ and tissue transplantation in the REGIONAL 1, assessed through an educative tool to contribute to the improvement of an efficient program of Organ and Tissue Donation and in that way, establish recommendations to increase donation rates, with an special focus in health centre's activities in the country. Methodology There was an study performed based on the analysis of knowledge evaluation in the organ and tissue donation-transplantation process with participant health staff in the educative tool called ¨Curso taller primer respondiente del potencial donante de organos y tejidos¨ (¨Workshop course first respondent of organ and tissue potential donor¨). This course included an evaluative format that was filled in anonymously by participants before and after receiving the course's content. The study was developed in IPS health staff who belong to the REGIONAL I, of National's organ and tissue donation and transplantation network. In order to evidence if there are differences in course participant's knowledge before and after assisting to it, we used McNemar's test. Results Between july-2011 and june-2012, the ¨Workshop course first respondent of organ and tissue potential donor¨ was completed and there were 303 respondents doctors, nurses and nurse assistants included. At the beginning of the course answers were accretive related to legislation, donor selection, brain death and donor maintenance were around 50%. It wasn't possible to determine the profession that could generate risk i donor detection and associated processes. After the course, 72% of the questions were answered correctly, which represents an statistically significant increase. This change shows statistic significance using McNemar's test and provide a value of: p=0.00. Discussion The health staff participating in the workshop course coming from involved units donor generators, show a knowledge shortfall regarding the donation transplantation process, which could turn them into barriers for the process

Actual importance of study. At the beginning of the 2020s developed world countries and countries which are the leaders of world economic development faced up the challenges of radical structural reformation of social production (from industry to service system) which is based on digitalization. Digital technologies in world science and business practice are considered essential part of a complex technological phenomenon like 'Industry 4.0'. Digitalization should cover development of all business processes and management processes at micro-, meso- and microlevels, processes of social production management at national and world economy levels. In general, in the 21st century world is shifting rapidly to the strategies of digital technologies application. The countries which introduce these strategies will gain guaranteed competitive advantages: from reducing production costs and improved quality of goods and services to developing new sales market and making guaranteed super-profits. The countries which stand aside from digitalization processes are at risk of being among the outsiders of socio-economic development. Such problem statement highlights the actual importance of determining the directions, trends and strategic priorities of social production digitalization. This issue is really crucial for all world countries, including Ukraine which is in midst of profound structural reformation of all national production system. Problem statement. Digital economy shapes the ground for 'Industry 4.0', information, It technologies and large databases become the key technologies. The main asset of 'Industry 4.0' is information, the major tool of production is cyberphysical systems that lead to formation the single unified highly productive environmental system of collecting, analyzing and applying data to production and other processes. Cyberphysical systems provides 'smart machines' (productive machines, tools and equipment which are programmed) integration via their connection to the Internet, or creation special network, 'Industrial Internet' (IIoT) which is regarded as a productive analogue of 'Internet of Things' (IoT) that is focused on the consumers. 'Internet of Things' can be connected with 'smart factories' which use 'Industrial Internet' to adjust production processes quickly turning into account the changes in costs and availability of resources as well as demand for production made. One of the most essential tasks for current economics and researchers of systems and processes of organization future maintenance of world production is to determine the main strategic priorities of social production digitalization. Analysis of latest studies and publications. Valuable contribution to the study of the core and directions of strategic priorities concerning social production digitalization was made by such foreign scientists as the Canadian researcher Tapscott D [1], foreigners Sun, L., Zhao, L [2], Mcdowell, M. [3] and others. Yet, the study of issues concerning social production digitalization are mainly done by the team of authors as such issues are complicated and multihierarchical. Furthermore, the problem of social production digitalization is closely linked to the transition to sustainable development, which is reflected in the works by Ukrainian scholars like Khrapkin V., Ustimenko V., Kudrin O., Sagirov A. and others in the monograph "Determinants of sustainable economy development" [4]. The edition of the first in Ukraine inter-disciplinary textbook on Internet economy by a group of scientists like Tatomyr I., Kvasniy L., Poyda S. and others [5] should also be mentioned. But the challenges of social production digitalization are constantly focused on by theoretical scientists, analytics and practitioners of these processes. Determining unexplored parts of general problem. Defining strategic priorities of social production digitalization requires clear understanding of prospective spheres of their application, economic advantages and risks which mass transition of social production from traditional (industrial and post-industrial)to digital technologies bear. A new system of technological equipment (production digitalization, Internet-economy, technology 'Industry 4.0', NBIC- technologies and circular economy) has a number of economic advantages for commodity producers and countries, as well as leads to dramatical changes in the whole social security system, changes at labour market and reformation the integral system of social relations in the society. Tasks and objectives of the study. The objective of the study is to highlight the core and define the main strategic priorities of social production digitalization, as they cause the process of radical structural reformation of industrial production, services and social spheres of national economy of world countries and world economy in general. To achieve the objective set in the article the following tasks are determined and solved: - to define the main priorities of digital technologies development, which is radically modify all social production business processes; - to study the essence and the role of circular economy for transition to sustainable development taken EU countries as an example; - to identify the strategic priorities of robotization of production processes and priority spheres of industrial and service robots application; - to define the role of NBIC-technologies in the process of social production structural reformation and its transition to new digital technologies in the 21st century. Method and methodology of the study. While studying strategic priorities of social production digitalization theoretical and empirical methods of study are used, such as historical and logical, analysis and synthesis, abstract and specific, casual (cause-and-effect) ones. All of them helped to keep the track of digital technologies evolution and its impact on structural reformation of social production. Synergetic approach, method of expert estimates and casual methods are applied to ground system influence of digital technologies, 'Industry 4.0' and their materialization as 'circular economy' on the whole complicated and multihierarchical system of social production in general. Basic material (the results of the study). Digital economy, i.e. economy where it is virtual but not material or physical assets and transactions are of the greatest value, institutional environment in which business processes as well as all managerial processes are developed on the basis of digital computer technologies and information and communication technologies (ICT), lies as the ground for social production digitalization. ICT sphere involves production of electronic equipment, computing, hardware,.software and services. It also provides various information sevices. Information Technology serves as a material basis for digital economy and digital technologies development. Among the basic digital technologies the following ones play the profound role: technology 'Blockchain', 3D priniting, unmanned aerial vehicles and flying drones, virtual reality (VR). Augmented reality (AR), Internet of Things (IoT), Industrial Internet of Things (IIoT), Internet of Value (IoV) which is founded on IT and blockchain technology, Internet of Everything (IoE), Artificial Intelligence (AI), neuron networks and robots. These basic digital technologies in business processes and management practices are applied in synergy, complexity and system but not in a single way. System combination of digital technologies gives maximal economic effect from their practical application in all spheres of social production-from industry to all kinds of services. For instance, in education digital technologies promote illustrating and virtual supplement of study materials; in tourism trade they promote engagement of virtual guides, transport and logistics security of tourist routes, virtual adverts and trips arrangements, virtual guidebooks, virtual demonstration of services and IT brochures and leaflets. Digital technologies radically change gambling and show businesses, in particular, they provide virtual games with 'being there' effect. Digital technologies drastically modify the retail trade sphere, advertisement and publishing, management and marketing, as well as provide a lot of opportunities for collecting unbiased data concerning changes in market conditions in real time. Digital technologies lie as the basis for 'circular economy', whose essence rests with non-linear, secondary, circular use of all existing natural and material resources to provide the production and consumption without loss of quality and availability of goods and services developed on the grounds of innovations, IT-technology application and 'Industry 4.0'. Among priorities of circular economy potential applications the following ones should be mentioned: municipal services, solid household wastes management and their recycling, mass transition to smart houses and smart towns, circular agriculture development, circular and renewable energy, The potential of circular economy fully and equally corresponds to the demands for energy efficiency and rational consumption of limited natural resources, so it is widely applied in EU countries while transiting to sustainable development. In the 21st century processes of social production robotization draw the maximal attention of the society. There is a division between industrial and service robots which combine artificial intelligence and other various digital technologies in synergy. Industrial robots are widely used in production, including automotive industry, processing industry, energetic, construction sectors and agriculture Services are applied in all other spheres and sectors of national and world economies –from military-industrial complex (for instance, for mining and demining the areas, military drones) to robots-cleaners (robots-vacuum cleaners), robots-taxis, robots engaged in health care service and served as nurses (provide the ill person with water, tidy up, bring meals). Social production robotization is proceeding apace. According to "World Robotic Report 2020", within 2014 – 2019 the total quantity of industrial robots increased by 85 %. By 2020 in the world the share of robots in the sphere of automated industrial production had comprised 34 %, in electronics – 25%, in metallurgy – 10 %. These indicators are constantly growing which results in structural reformation of the whole system of economic and industrial processes, radical changes in world labour market and the social sphere of world economy in general. Alongside with generally recognized types of digital technologies and robotization processes, an innovation segment of digital economy – NBIC – technologies (Nanotechnology, Biotechnology, Information technology, Cognitive Science) are rapidly spread. Among the priorities of NBIC-technologies development the special place belongs to interaction between information and cognitive technologies. As a material basis for its synergy in NBIC-technologies creation of neuron networks, artificial intelligence, artificial cyber brain for robots are applied. It is estimated as one of the most prospective and important achievements of digital economy which determines basic, innovational vector of social production structural reformations in the 21st century. The sphere of results application. International economic relations and world economy, development of competitive strategies of national and social production digitalization of world economy in general. Conclusions. Digital technologies radically change all spheres of social production and social life, including business and managerial processes at all levels. Digital technologies are constantly developing and modifying, that promotes emergence of new spheres and new business activities and management. 21st century witnessed establishing digital economy, smart economy, circular economy, green economy and other various arrangements of social production which are based on digital technologies. Social production digitalization and innovative digital technologies promotes business with flexible systems of arrangement and management, production and sales grounded on processing large Big Data permanently, on the basis of online monitoring in real time. Grounded on digital technologies business in real time mode processes a massive Big Data and on their results makes smart decisions in all business spheres and business processes management. Radical shifts in social production digitalization provides businesses of the states which in practice introduce digital technologies with significant competitive advantages - from decrease in goods and services production cost to targeted meeting of specific needs of consumers. Whereas, rapid introduction of digital technologies in the countries-leaders of world economic development results in a set of system socio-economic and socio-political challenges, including the following: crucial reformatting the world labour market and rise in mass unemployment, shift from traditional export developing countries' specialization, breakups of traditional production networks being in force since the end of the 20th century, so called 'chains of additional value shaping', breakups of traditional cooperation links among world countries and shaping the new ones based on 'Industry 4.0' and 'Industrial Internet'. Socio-economic and political consequences of radical structural reformation of all spheres in national and world economy in the 21st century, undoubtedly, will be stipulated with the processes of social production digitalization. It will require further systemic and fundamental scientific studies on this complicated and multi hierarchical process.

Researchers increasingly use meta-analysis to synthesize the results of several studies in order to estimate a common effect. When the outcome variable is continuous, standard meta-analytic approaches assume that the primary studies report the sample mean and standard deviation of the outcome. However, when the outcome is skewed, authors sometimes summarize the data by reporting the sample median and one or both of (i) the minimum and maximum values and (ii) the first and third quartiles, but do not report the mean or standard deviation. To include these studies in meta-analysis, several methods have been developed to estimate the sample mean and standard deviation from the reported summary data. A major limitation of these widely used methods is that they assume that the outcome distribution is normal, which is unlikely to be tenable for studies reporting medians. We propose two novel approaches to estimate the sample mean and standard deviation when data are suspected to be non-normal. Our simulation results and empirical assessments show that the proposed methods often perform better than the existing methods when applied to non-normal data. ; anadian Institutes of Health Research (CIHR) KRS-134297 Fonds de recherche du Quebec -Sante (FRQS) Canadian Institutes of Health Research (CIHR) Canadian Institutes of Health Research (CIHR) FRQS Masters Training Awards Vanier Canada Graduate Scholarship FRQS Postdoctoral Training Fellowship Research Institute of the McGill University Health Centre G.R. Caverhill Fellowship from the Faculty of Medicine, McGill University Cumming School of Medicine, University of Calgary Alberta Health Services through the Calgary Health Trust Hotchkiss Brain Institute Senior Health Scholar award from Alberta Innovates Health Solutions Health Research Council of New Zealand Lundbeck International Tehran University of Medical Sciences M-288 Department of Education, National Institute on Disability and Rehabilitation Research, Spinal Cord Injury Model Systems: University of Washington H133N060033 Baylor College of Medicine H133N060003 University of Michigan System H133N060032 National Health and Medical Research Council of Australia 1002160 Safe Work Australia Australian Research Council FT130101444 European Foundation for Study of Diabetes Chinese Diabetes Society Lilly Foundation Asia Diabetes Foundation Liao Wun Yuk Diabetes Memorial Fund United States National Institute of Mental Health (NIMH) grant 5F30MH096664 United States Department of Health & Human Services National Institutes of Health (NIH) - USA United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH Fogarty International Center (FIC) United States Department of Health & Human Services National Institutes of Health (NIH) - USA National Cancer Center United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Heart Lung & Blood Institute (NHLBI) NIH Office of Research for Women's Health through the Fogarty Global Health Fellows Program Consortium 1R25TW00934001 American Recovery and Reinvestment Act United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of Mental Health (NIMH) R24MH071604 / R34 MH072925/ K02 MH65919 / P30 DK50456 / R24 MH56858 / RO1 MH073687 /RO1-MH069666 / R34MH084673 /R24 MH071604 United States Department of Health & Human Services Centers for Disease Control & Prevention - USA R49 CE002093 St Anne's Community Services, Leeds, UK US National Center for Medical Rehabilitation Research RO1 HD39415 Federal Ministry of Education & Research (BMBF) 01GY1150 United States Department of Health & Human Services National Institutes of Health (NIH) - USA T37 MD001449 / T32 GM07356 Ohio Board of Regents Research and Development Administration Office, University of Macau MYRG2015-00109-FSS Federal Ministry of Education & Research (BMBF) 01 GD 9802/4 ; 01 GD 0101 Federation of German Pension Insurance Institute Federal Ministry of Education & Research (BMBF) Perpetual Trustees Flora and Frank Leith Charitable Trust Jack Brockhoff Foundation Grosvenor Settlement Sunshine Foundation Danks Trust Canadian Institutes of Health Research (CIHR) FRN 83518 Scleroderma Society of Canada Scleroderma Society of Ontario Scleroderma Society of Saskatchewan Sclerodermie Quebec Cure Scleroderma Foundation Inova Diagnostics Inc Euroimmun FRQS Canadian Arthritis Network Lady Davis Institute of Medical Research of the Jewish General Hospital, Montreal, QC FRQS Senior Investigator Award National Strategic Reference Framework European Union (EU) Greek Ministry of Education, Lifelong Learning and Religious Affairs (ARISTEIA-ABREVIATE) 1259 Ministry of Health, Labour and Welfare, Japan UK National Institute for Health Research under its Programme Grants for Applied Research Programme RP-PG-0606-1142 Canada Research Chair in Neurological Health Services Research AIHS Population Health Investigator Award National Health and Medical Research Council of Australia 1088313 Netherlands Organization for Health Research and Development 945-03-047 National Health Research Institutes - Taiwan NHRI-EX97-9706PI Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand 49086 Reitoria de Pesquisa da Universidade de Sao Paulo 09.1.01689.17.7 Banco Santander 10.1.01232.17.9 Pfizer medical faculty of the University of Heidelberg, Germany 121/2000 Research University Grant Scheme from Universiti Putra Malaysia, Malaysia Postgraduate Research Student Support Accounts of the University of Auckland, New Zealand National Program for Centers of Excellence (PRONEX/FAPERGS/CNPq, Brazil) Pfizer US Pharmaceutical Inc. PQ-CNPq-2 301321/2016-7 Belgian Ministry of Public Health and Social Affairs Pfizer Ministry of Health, Italy UK National Health Service Lothian Neuro-Oncology Endowment Fund Universiti Sains Malaysia United States Department of Health & Human Services United States Health Resources & Service Administration (HRSA) R40MC07840 United States Department of Health & Human Services Agency for Healthcare Research & Quality R36 HS018246 United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Center for Research Resources (NCRR) TL1 RR024135 University of Melbourne Hunter Medical Research Institute Innovatiefonds Zorgverzekeraars Netherlands Organization for Health Research and Development (ZonMw) Mental Health Program 100.003.005 100.002.021 Academic Medical Center/University of Amsterdam Fund for Innovation and Competitiveness of the Chilean Ministry of Economy, Development and Tourism, through the Millennium Scientific Initiative IS130005 US Department of Veteran Affairs US Department of Veteran Affairs United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Heart Lung & Blood Institute (NHLBI) R01 HL079235 American Federation for Ageing Research Robert Wood Johnson Foundation (RWJF) Ischemia Research and Education Foundation

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. Acknowledgements: We especially thank all volunteers who participated in our study. This study made use of data generated by the 'Genome of the Netherlands' project, which is funded by the Netherlands Organization for Scientific Research (grant no. 184021007). The data were made available as a Rainbow Project of BBMRI-NL. Samples were contributed by LifeLines (http://lifelines.nl/lifelines-research/general), the Leiden Longevity Study (http://www.healthy-ageing.nl; http://www.langleven.net), the Netherlands Twin Registry (NTR: http://www.tweelingenregister.org), the Rotterdam studies (http://www.erasmus-epidemiology.nl/rotterdamstudy) and the Genetic Research in Isolated Populations programme (http://www.epib.nl/research/geneticepi/research.html#gip). The sequencing was carried out in collaboration with the Beijing Institute for Genomics (BGI). Cardiovascular Health Study: This CHS research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, HHSN268200960009C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086; and NHLBI grants HL080295, HL087652, HL105756 and HL103612 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through AG023629 from the National Institute on Aging (NIA). A full list of CHS investigators and institutions can be found at http://www.chs-nhlbi.org/pi.htm. The CROATIA cohorts would like to acknowledge the invaluable contributions of the recruitment teams in Vis, Korcula and Split (including those from the Institute of Anthropological Research in Zagreb and the Croatian Centre for Global Health at the University of Split), the administrative teams in Croatia and Edinburgh and the people of Vis, Korcula and Split. SNP genotyping was performed at the Wellcome Trust Clinical Research Facility in Edinburgh for CROATIA-Vis, by Helmholtz Zentrum München, GmbH, Neuherberg, Germany for CROATIA-Korcula and by AROS Applied Biotechnology, Aarhus, Denmark for CROATIA-Split. They would also like to thank Jared O'Connell for performing the pre-phasing for all cohorts before imputation. The ERF study as a part of EuroSPAN (European Special Populations Research Network) was supported by European Commission FP-6 STRP grant number 018947 (LSHG-CT-2006-01947) and also received funding from the European Community's Seventh Framework Programme (FP7/2007-2013)/grant agreement HEALTH-F4-2007-201413 by the European Commission under the programme 'Quality of Life and Management of the Living Resources' of 5th Framework Programme (no. QLG2-CT-2002-01254). High-throughput analysis of the ERF data was supported by joint grant from the Netherlands Organisation for Scientific Research and the Russian Foundation for Basic Research (NWO-RFBR 047.017.043). This research was financially supported by BBMRI-NL, a Research Infrastructure financed by the Dutch government (NWO 184.021.007). Statistical analyses for the ERF study were carried out on the Genetic Cluster Computer (http://www.geneticcluster.org), which is financially supported by the Netherlands Scientific Organization (NWO 480-05-003 PI: Posthuma) along with a supplement from the Dutch Brain Foundation and the VU University Amsterdam. We are grateful to all study participants and their relatives, general practitioners and neurologists for their contributions and to P. Veraart for her help in genealogy, J. Vergeer for the supervision of the laboratory work and P. Snijders for his help in data collection. The FamHS is funded by a NHLBI grant 5R01HL08770003, and NIDDK grants 5R01DK06833603 and 5R01DK07568102. The Framingham Heart Study SHARe Project for GWAS scan was supported by the NHLBI Framingham Heart Study (Contract No. N01-HC-25195) and its contract with Affymetrix Inc for genotyping services (Contract No. N02-HL-6-4278). DNA isolation and biochemistry were partly supported by NHLBI HL-54776. A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at the Boston University School of Medicine and Boston Medical Center. We are grateful to Han Chen for conducting the 1000G imputation. The Family Heart Study was supported by the by grants R01-HL-087700 and R01-HL-088215 from the National Heart, Lung, and Blood Institute (NHLBI). We would like to acknowledge the invaluable contributions of the families who took part in the Generation Scotland: Scottish Family Health Study, the general practitioners and Scottish School of Primary Care for their help in recruiting them, and the whole Generation Scotland team, which includes academic researchers, IT staff, laboratory technicians, statisticians and research managers. SNP genotyping was performed at the Wellcome Trust Clinical Research Facility in Edinburgh. GS:SFHS is funded by the Scottish Executive Health Department, Chief Scientist Office, grant number CZD/16/6. SNP genotyping was funded by the Medical Research Council, United Kingdom. We wish to acknowledge the services of the LifeLines Cohort Study, the contributing research centres delivering data to LifeLines and all the study participants. MESA Whites and the MESA SHARe project are conducted and supported by contracts N01-HC-95159 through N01-HC-95169 and RR-024156 from the NHLBI. Funding for MESA SHARe genotyping was provided by NHLBI Contract N02.HL.6.4278. MESA Family is conducted and supported in collaboration with MESA investigators; support is provided by grants and contracts R01HL071051, R01HL071205, R01HL071250, R01HL071251, R01HL071252, R01HL071258 and R01HL071259. We thank the participants of the MESA study, the Coordinating Center, MESA investigators and study staff for their valuable contributions. A full list of participating MESA investigators and institutions can be found at http://www.mesa-nhlbi.org. Netherland Twin Register (NTR) and Netherlands Study of Depression and Anxiety (NESDA): Funding was obtained from the Netherlands Organization for Scientific Research (NWO) and MagW/ZonMW grants Middelgroot-911-09-032, Spinozapremie 56-464-14192, Geestkracht programme of the Netherlands Organization for Health Research and Development (Zon-MW, grant number 10-000-1002), Center for Medical Systems Biology (CSMB, NWO Genomics), NBIC/BioAssist/RK(2008.024), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL, 184.021.007), VU University's Institute for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam (NCA); the European Science Foundation (ESF, EU/QLRT-2001-01254), the European Community's Seventh Framework Program (FP7/2007-2013), ENGAGE (HEALTH-F4-2007-201413); the European Science Council (ERC Advanced, 230374); and the European Research Council (ERC-284167). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health, Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the Avera Institute, Sioux Falls, South Dakota (USA) and the National Institutes of Health (NIH R01 HD042157-01A1, MH081802, Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995). PREVEND genetics is supported by the Dutch Kidney Foundation (Grant E033), the EU project grant GENECURE (FP-6 LSHM CT 2006 037697), the National Institutes of Health (grant 2R01LM010098), The Netherlands Organisation for Health Research and Development (NWO-Groot grant 175.010.2007.006, NWO VENI grant 916.761.70, ZonMw grant 90.700.441) and the Dutch Inter University Cardiology Institute Netherlands (ICIN). The PROSPER study was supported by an investigator-initiated grant obtained from Bristol-Myers Squibb. J.W.J is an Established Clinical Investigator of the Netherlands Heart Foundation (grant 2001 D 032). Genotyping was supported by the seventh framework programme of the European commission (grant 223004) and by the Netherlands Genomics Initiative (Netherlands Consortium for Healthy Aging grant 050-060-810). The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII) and the Municipality of Rotterdam. We are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. The generation and management of GWAS genotype data for the Rotterdam Study is supported by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012). This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) project no. 050-060-810. We thank Pascal Arp, Mila Jhamai, Marijn Verkerk, Lizbeth Herrera and Marjolein Peters for their help in creating the GWAS database. ; Peer reviewed ; Publisher PDF

Issue 47 of Publicaciones brings excellent news for this research journal: from October 2017 it is included in the prestigious Scopus database. This achievement has been made possible by two factors: on the one hand, all the work done by previous editors-in- chief of Publicaciones, the Editorial Board, the Advisory Board, the peer reviewers, the Administration and Services staff of the Melilla university campus, the various interns the journal has had, and our sponsors, the Department of Education, Youth and Sport of the Autonomous City of Melilla and the Office of the Vice-Rector for Research and Knowledge Transfer of the University of Granada. On the other hand, the new strategy of internationali- sation and visibility on social media that the journal has been following since July 2016 has also made an important contribution. During the past year, Publicaciones has been presented in higher education institutions in China (Shanghai International Studies University and Peking University) and Mexico (Autonomous University of Yucatán and Centre for Teaching and Research of the Ministry of Education of the Yucatán State Government), and it will continue on this path of interna- tionalisation over the next few years. It has also established collaboration agreements with a number of institutions and international education networks to publish special issues. As for its presence on social media, work has been done on search engine optimisation (SEO) and networks, web traffic monitoring, updating the Google Scholar Citations profile and creating a new Facebook profile. All this is gradually building a process of national and international growth and expan- sion for the journal, which will continue seeking to be included in new document collections and databases and to increase its quality factors and indicators. Turning now to the content of this issue, number 47, it begins with a study on the use of information and communication technologies (video tutorials), improving the educa- tional process and effective inclusion of students with different interests. This is followed by a literature review on democratic citizenship and cultural diversity. Next comes an empirical article on development and validation of the School Adjustment Questionnaire (SAQ), using statistical homogeneity, factorial and internal and external validity analy- sis. Fourth, there is a study carried out at the University of Cienfuegos (Cuba) on the use of responsibility value by a sample of physical education teachers in higher education. The fifth article addresses the psychological and physiological response to listening to music, through galvanic skin response (GSR), alpha brain waves (ABW) and heart rate (HR). The issue concludes with a pilot study on improving entrepreneurial competence in secondary education. As in previous issues, the team would like to take this opportunity to express its grati- tude to the authors of the articles published, to those who have helped carry out the various tasks needed to make it possible to publish this issue number 47, and to the institutions that sponsor its publication. ; El número 47 de la revista Publicaciones trae consigo una excelente noticia para esta publicación científica: desde octubre de 2017, la revista está incluida en la prestigiosa base de datos Scopus. Este logro ha sido posible gracias a dos factores, por un lado, a todo el trabajo hecho por los anteriores directores de Publicaciones; el Consejo de Redacción; el Consejo Asesor; los evaluadores; el Personal de Administración y Servicios del Campus Universitario de Melilla; las diferentes becarias que ha tenido la revista; y nuestros patrocinadores, la Consejería de Educación, Juventud y Deportes de la Ciudad Autónoma de Melilla y el Vicerrectorado de Investigación y Transferencia de la Universidad de Granada. Por otro lado, ha coadyuvado también la nueva estrategia de internacionalización y visibilidad en redes digitales que la revista sigue desde julio de 2016. Durante el último año, la revista se ha presentado en instituciones de educación superior de China (Shanghai International Studies University y Peking University) y México (Universidad Autónoma de Yucatán y Centro de Docencia e Investigación de la Secretaría de Educación del Gobierno del Estado de Yucatán), y continuará con esta senda de internacionalización durante los próximos años. Además, ha establecido acuerdos de colaboración con diferentes institucio- nes y redes internacionales de educación, para la publicación de monográficos. En cuanto a su presencia en redes digitales, se han llevado a cabo labores de posiciona- miento en motores de búsqueda (SEO) y redes, seguimiento del tráfico web, actualización del perfil de Google Scholar Citations y creación de un nuevo perfil en Facebook. Todo lo anterior va construyendo un crecimiento y expansión sostenidos de alcance nacional e internacional para la revista, que seguirá tratando de incorporarse a nuevos fondos y bases documentales y de incrementar sus índices y evidencias de calidad. En cuanto a los contenidos del número 47, éste comienza con un trabajo sobre el uso de las tecnologías de la información y la comunicación (vídeo-tutoriales), la mejora del proceso educativo y la inclusión efectiva de alumnos con diferentes intereses. A continua- ción, aparece un estudio de revisión de la literatura sobre ciudadanía democrática y diver- sidad cultural. Seguidamente, se muestra un artículo empírico sobre desarrollo y validación del Cuestionario de Adaptación al Centro (CAC), mediante análisis estadístico de homoge- neidad, factorial y validez interna y externa. En cuarto lugar, aparece un estudio realizado en la Universidad de Cienfuegos (Cuba) sobre el uso del valor responsabilidad por parte de una muestra de docentes de educación física en educación superior. El quinto trabajo aborda la respuesta psicofisiológica ante la escucha musical, mediante la respuesta galvánica de la piel- rgp, onda cerebral alfa-oca y frecuencia cardíaca-fc. Cierra este número un estudio piloto sobre la mejora de la competencia emprendedora en educación secundaria. Como en los anteriores números, el equipo de personas vinculado a la gestión de Publicaciones expresa aquí su agradecimiento a los autores de los artículos publicados, a los colaboradores en las diferentes tareas necesarias para hacer posible la edición de este número 47, y a las instituciones que patrocinan su publicación. ; Le numéro 47 de la revue Publicaciones s'accompagne d'une excellente nouvelle pour cette publication scientifique : depuis octobre 2017, la revue figure dans la prestigieuse base de données Scopus. Cela a été possible grâce à deux facteurs : d'une part, le travail réalisé par les anciens directeurs de la publication, le conseil de rédaction, le conseil consultatif, les évaluateurs, le personnel d'administration et de services du Campus universitaire de Melilla, les différentes stagiaires ayant travaillé avec nous, ainsi que nos parraineurs : la Direction de l'éducation, de la jeunesse et des sports de la ville autonome de Melilla et le Vice-rectorat pour la recherche et le transfert de l'Université de Grenade. Par ailleurs, la nouvelle stratégie d'internationalisation et de visibilité dans les réseaux numériques adoptée par la revue depuis juillet 2016 a également contribué à ce succès. Durant l'année écoulée, la revue a été présentée dans des établissements d'enseignement supé- rieur de Chine (Shanghai International Studies University et Peking University) et du Mexique (Universidad Autónoma de Yucatán et Centre d'enseignement et de recherche du Secrétariat à l'éducationduGouvernementdel'ÉtatduYucatán)etpoursuivracettedémarched'internationalisation lors des années à venir. De plus, elle a conclu des accords de collaboration avec diverses institutions et réseaux internationaux d'éducation pour la publication de monographies. Quant à sa présence dans les réseaux numériques, elle a été renforcée par des activités de référencement sur les moteurs de recherche (SEO) et les réseaux, le suivi du trafic web, l'actualisation du profil Google Scholar Citations et la création d'un nouveau profil Facebook. Tout cela favorise une croissance et une expansion soutenues à l'échelle nationale et internationale pour la revue, qui envisage de poursuivre ses efforts pour intégrer de nouveaux fonds et bases documentaires et augmenter ses indices et ses attestations de qualité. Quant au contenu du numéro 47, celui-ci commence par un article sur l'utilisation des technologies de l'information et de la communication (tutoriels vidéo), l'amélioration du processus éducatif et l'inclusion effective d'élèves ayant divers centres d'intérêt. Il est suivi par une revue de littérature sur la citoyenneté démocratique et la diversité culturelle. Un article empirique est ensuite consacré au développement et à la validation du questionnaire d'adaptation à l'établissement sur la base d'une analyse statistique d'homogénéité, factorie- lle et de validité interne et externe. Le quatrième volet est une étude réalisée à l'Université de Cienfuegos (Cuba) sur l'utilisation de la valeur responsabilité par un échantillon d'enseignants de l'éducation supérieure. Le cinquième article aborde la réponse psychophysiologique à l'écoute musicale, via la réponse galvanique de la peau (RGP), l'onde cérébrale alpha (OCA) et la fréquence cardiaque (FC). Ce numéro se termine par une étude pilote sur l'amélioration des compétences entrepreneuriales dans l'enseignement secondaire. Comme dans les numéros précédents, l'équipe chargée de la gestion des publications tient à adresser ses remerciements aux auteurs des articles publiés, aux personnes ayant colla- boré aux différentes activités ayant permis de publier ce numéro 47 ainsi qu'aux institutions qui ont parrainé la publication.

Sarajevo's contested position at the intersection of geopolitical 'tectonic plates' – situated between Rome and Byzantium, Austro-Hungarian and Ottoman Empires, the Western and Eastern Bloc, de-colonization and re-colonization – resulted in both fertile periods of exchange and moments of devastating conflicts. This inbetweenness has contributed to the (dis)continuous cityscape, characterized by a diversity of spatial productions and radical urban transformations. Therefore, Sarajevo represents an urban laboratory for social and spatial transformation processes. The ETHZ/UTT 'Urban Toolbox' provided a cross-scalar methodological approach for examining the physical typology, program, and actors of Sarajevo's urbanism, spanning from spatial and stakeholder analyses synthesized through critical mapping to the identification of strategic scenarios and the use of digital media. This dissertation zooms both in and out on three time periods between 1945 and 2014, defined by three distinct revolutionary moments. The central theme of this project is the examination of the transformative processes with the focus on the district of Marijin Dvor in New Sarajevo. Previously a peripheral zone, it became a central operational laboratory of the new Sarajevo to test the effects of major geopolitical shifts on the 'heart' and 'brain' of the city. While investigating multiple spatial crystallization points, one building epitomized the correlation between geopolitical power and space – the Museum of the Revolution – a living symbol of the three periods of construction, destruction and fragmentation. The proclamation of Tito's communist revolution in 1945 and the establishment of a socialist Yugoslav federation, created pressing spatial demands for the new urban proletariat. The industrialization and rural-urban migration gave birth to the city's first strategic urbanistic model, enabled by proclaiming the collectivization of land as a common good. The City Planning Institute developed the first General Urban Plan (GUP-Generalni Urbanistički Plan) in 1961. This large-scale urban planning instrument was enabled by the Yugoslav decentralized model of self-management that also included the 'Mjesne Zajednice' (MZs), the local communities. These new societal postulates were decisive for the construction of the flagship project for Sarajevo and its nucleus, Marijin Dvor, as a cultural, educational and industrial hub of BiH, one of Yugoslavia's most ethnically diverse and rural regions. Architects and urbanists were tasked with planning, designing and building a New Sarajevo as a socialist utopia. Buildings, such as the Museum of the Revolution, were constructed as monuments to celebrate both the victory of the partisans over Nazi Germany and the new state design ideology: functionalist modernism. The construction of Marijin Dvor was catalyzed by the Winter Olympic Games, hosted by Sarajevo in 1984 as a result of Yugoslavia's non-aligned foreign policy and the city's status as 'terra neutral`. Later in 1992, as socialist Yugoslavia began to crumble after the geopolitical vacuum of post-1989 Europe, Marijin Dvor became the site of the fruitless peace protests. The city was put under military siege and New Sarajevo was divided along a frontline. Under wartime conditions, the urban utopia was de-urbanized. The collapse of urban infrastructure and the destruction of the human habitat, characterized in Bogdan Bogdanović's description of urbicide, reached its peak in Sarajevo. During this period, Marijin Dvor went through a radical transformation: public spaces became graveyards or urban-agricultural zones for survival. The Museum of the Revolution found itself at the frontline and was bombed as the symbol of a common Yugoslav past. Nevertheless, in acts of popular resistance, destroyed buildings became temporary art spaces. Derelict parks turned into agricultural zones. This attracted a wave of global solidarity as intellectuals visited Sarajevo, including the architect Lebbeus Woods, and formed a vital part of the antiwar movement, analyzing the destruction and proposing both small adaptations and radical post-war reconstruction visions. However, these visions did not adhere to the post-socialist and post-war realities of the newly ethnically divided Sarajevo resulting from the 1995 Dayton Peace Agreement. Common properties had been converted into state ones, which were then auctioned off in a massive privatization wave. These policies fell in line with the country's market liberalization. Within these new realities, MZs maintained the same level of legal status, but under the extreme pressure by neoliberal urban development. New economic and urban mechanisms led to aggressive development driven by investments from across the geopolitical spectrum, which disregarded already destroyed public space in favor of monocultures of generic commercial architecture. Marijin Dvor became a high-density node of real estate speculations and a symbol of socio-economic segregation and spatial fragmentation. The refugia of public space were found in administrative grey-zones of the post-war constitutional changes. Politically contaminated and left out of the legal system and with a new name and no program as a consequence, the Historical Museum, once the Museum of the Revolution, became a host to civic engagements, inviting citizens to figure as curators. This new system and its accompanying urban model revealed ruptures in 2014, symbolized through violent mass protests of the so-called 'Bosnian Spring'. Impoverished and unemployed, Sarajevans turned their anger and desperation against the city's governmental buildings. The dissertation includes 'Reactivate Sarajevo', an activist experiment of spatial agency that connects theory and practice by engaging in-situ. Influenced by both the pioneers of reflective practice, Donald Schön and Kurt Lewin, and the ETHZ/UTT concept of the activist architect, 'Reactivate Sarajevo' exposes the dissertation's work-in-progress to the public. This discourse was initiated through the organization of expert symposia, stakeholder workshops and open discussions with the general public. The production of discourse, curation of performances and reflection of these actions mutually nurtured the theoretical chapters. These acts spawned critical mapping and alternative design concepts, presented through an interactive digital platform, as well as a strategy of inversion to represent Sarajevo and Bosnia and Herzegovina in 2016 at the International Architecture Biennale in Venice for the first time in the country's history. The exhibition showcased not only critical research, but also alternative design concepts amplifying civic action as a basis for the integrated and inclusive development of Marijin Dvor. The insights were then transferred back to Sarajevo back via the 'Balkan route' and the exhibition was installed in the Historical Museum. The Experiment contributed to the creation of a network of formal and informal partnerships locally and laid the groundwork for a future urban design and planning project concerning the future planning of Marijin Dvor and Sarajevo. This approach of action research resonated throughout the Balkans and other regions through workshops, lectures and consultancies and formed the basis for the extrapolation and application of the insights to other cities.

Importance: Alzheimer disease (AD) is the leading cause of death in individuals with Down syndrome (DS). Previous studies have suggested that the APOE ɛ4 allele plays a role in the risk and age at onset of dementia in DS; however, data on in vivo biomarkers remain scarce. Objective: To investigate the association of the APOE ɛ4 allele with clinical and multimodal biomarkers of AD in adults with DS. Design, setting, and participants: This dual-center cohort study recruited adults with DS in Barcelona, Spain, and in Cambridge, UK, between June 1, 2009, and February 28, 2020. Included individuals had been genotyped for APOE and had at least 1 clinical or AD biomarker measurement; 2 individuals were excluded because of the absence of trisomy 21. Participants were either APOE ɛ4 allele carriers or noncarriers. Main outcomes and measures: Participants underwent a neurological and neuropsychological assessment. A subset of participants had biomarker measurements: Aβ1-42, Aβ1-40, phosphorylated tau 181 (pTau181) and neurofilament light chain (NfL) in cerebrospinal fluid (CSF), pTau181, and NfL in plasma; amyloid positron emission tomography (PET); fluorine 18-labeled-fluorodeoxyglucose PET; and/or magnetic resonance imaging. Age at symptom onset was compared between APOE ɛ4 allele carriers and noncarriers, and within-group local regression models were used to compare the association of biomarkers with age. Voxelwise analyses were performed to assess topographical differences in gray matter metabolism and volume. Results: Of the 464 adults with DS included in the study, 97 (20.9%) were APOE ɛ4 allele carriers and 367 (79.1%) were noncarriers. No differences between the 2 groups were found by age (median [interquartile range], 45.9 [36.4-50.2] years vs 43.7 [34.9-50.2] years; P = .56) or sex (51 male carriers [52.6%] vs 199 male noncarriers [54.2%]). APOE ɛ4 allele carriers compared with noncarriers presented with AD symptoms at a younger age (mean [SD] age, 50.7 [4.4] years vs 52.7 [5.8] years; P = .02) and showed earlier cognitive decline. Locally estimated scatterplot smoothing curves further showed between-group differences in biomarker trajectories with age as reflected by nonoverlapping CIs. Specifically, carriers showed lower levels of the CSF Aβ1-42 to Aβ1-40 ratio until age 40 years, earlier increases in amyloid PET and plasma pTau181, and earlier loss of cortical metabolism and hippocampal volume. No differences were found in NfL biomarkers or CSF total tau and pTau181. Voxelwise analyses showed lower metabolism in subcortical and parieto-occipital structures and lower medial temporal volume in APOE ɛ4 allele carriers. Conclusions and relevance: In this study, the APOE ɛ4 allele was associated with earlier clinical and biomarker changes of AD in DS. These results provide insights into the mechanisms by which APOE increases the risk of AD, emphasizing the importance of APOE genotype for future clinical trials in DS. ; This study was funded in part by the Fondo de Investigaciones Sanitario; Instituto de Salud Carlos III (grants PI14/01126 and PI17/01019 to Dr Fortea, grants PI13/01532 and PI16/01825 to Dr Blesa, grant PI18/00335 to Dr Carmona-Iragui, grants PI18/00435 and INT19/00016 to Dr Alcolea, grant PI18/00327 to Dr Belbin, and grants PI14/1561 and PI17/01896 to Dr Lleó); Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED) Program 1, Alzheimer Disease (Dr Lleó) and SIGNAL study, which was partly jointly funded by Fondo Europeo de Desarrollo Regional, Unión Europea, and Una Manera de Hacer Europa; National Institutes of Health (NIH; grants 1R01AG056850-01A1, R21AG056974, and R01AG061566 to Dr Fortea); Departament de Salut de la Generalitat de Catalunya, Pla Estratègic de Recerca i Innovació en Salut (grant SLT002/16/00408 to Dr Lleó); Fundació La Marató de TV3 (grant 20141210 to Dr Fortea and grant 044412 to Dr Blesa); Fundació Catalana Síndrome de Down and Fundació Víctor Grífols i Lucas (Dr Fortea); Generalitat de Catalunya (grant SLT006/17/00119 to Dr Fortea, grant SLT006/17/95 to Dr Vilaplana, and grant SLT006/17/00125 to Dr Alcolea); Fundació Bancaria La Caixa to Dr Blesa; NIHR Cambridge Biomedical Research Centre; NIHR Collaborations in Leadership for Applied Health Research and Care (CLAHRC) for the East of England; NIHR Cambridge Dementia Biomedical Research Unit; Down Syndrome Association; and the Health Foundation. Dr Bejanin was supported by a Juan de la Cierva Incorporación grant (IJCI-2017-32609) from the Spanish Ministry of Economy and Competitiveness and by a Miguel Servet I grant (CP20/00038) from the Carlos III Health Institute. Dr Iulita was supported by the Jérôme Lejeune Foundation and Sisley D'Ornano Foundations. Dr Estellés was supported by grant CM19/00017 from Pío del Río Hortega. Dr Padilla was supported as a Sara Borrell Postdoctoral Fellow (CD20/00133) at the Carlos III Health Institute. Dr Illán-Gala was supported by a Juan Rodés contract (JR21-00018) and the Pilot Award for Global Brain Health Leaders (GBHI ALZ UK-21-720973). Dr Belbin was supported by a Miguel Servet II grant (CP18/00011). Dr Osorio was supported by grants R01AG056031, R01AG056531, R01AG066870, and R21AG067549 from the NIH and grant 98480 from the Medical Research Council. Dr Lehmann was supported by grants from the Programme Hospitalier de Recherche Clinique National program, grant NeuroMET2 #18HLT09 from the European Union (EU) European Metrology Programme for Innovation and Research, and the Marie Skłodowska-Curie grant agreement 860197 from the EU Horizon 2020 research and innovation programme. Dr Holland was supported by CLAHRC for the East of England at Cambridgeshire and Peterborough NHS Foundation Trust. Dr Zetterberg was supported by grant 2018-02532 from the Swedish Research Council; grant 681712 from the European Research Council; grant ALFGBG-720931 from the Swedish State Support for Clinical Research; grant 201809-2016862 from the Alzheimer Drug Discovery Foundation (ADDF); grants ADSF-21-831376-C, ADSF-21-831381-C, and ADSF-21-831377-C from the Alzheimer's Strategic Fund and the Alzheimer's Association; Olav Thon Foundation; Erling-Persson Family Foundation; grant FO2019-0228 from the Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden; the Marie Skłodowska-Curie grant agreement 860197 from the EU Horizon 2020 research and innovation programme; and the UK Dementia Research Institute at UCL. Dr Blennow was supported by grant 2017-00915 from the Swedish Research Council; grant RDAPB-201809-2016615 from the ADDF; grant AF-742881 from the Swedish Alzheimer Foundation; grant FO2017-0243 from Hjärnfonden, Sweden, the Swedish state under the agreement between the Swedish government and the County Councils; grant ALFGBG-715986 from the ALF agreement; and grant JPND2019-466-236 from the EU Joint Program for Neurodegenerative Disorders. Dr Zaman was supported by CLAHRC for the East of England at Cambridgeshire and Peterborough NHS Foundation Trust and grant 98480 from the Medical Research Council. Dr Fortea was supported by grants from the Jérome Lejeune Foundation.

The research activity carried out during the three years of the PhD course attended, at the Engineering Department of the University of Palermo, was aimed at the identification of an alternative predictive model able to solve the traditional building thermal balance in a simple but reliable way, speeding up any first phase of energy planning. Nowadays, worldwide directives aimed at reducing energy consumptions and environmental impacts have focused the attention of the scientific community on improving energy efficiency in the building sector. The reduction of energy consumption and CO2 emissions for heating and cooling needs of buildings is an important challenge for the European Union, because the buildings sector contributes up to 36% of the global CO2 emissions [1] and up to 40% of total primary energy consumptions [2]. Despite the ambitious goals set by the Energy Performance of Buildings Directive (EPBD) at the European level [1], which states that, by 2020, all new buildings and existing buildings undergoing major refurbishments will have to be Nearly Zero Energy Buildings (NZEB) [3,4], the critical challenge remains the improvement of the efficiency when upgrading the existing building stock to standards of the NZEB level [5]. The improvement of the energy efficiency of buildings and their operational energy usage should be estimated early in the design phase to guarantee a reduction in energy consumption, so buildings can be as sustainable as possible [6]. While a newly constructed NZEB can employ the "state of the art" of available efficient technologies and design practices, the optimization of existing buildings requires better efforts [7]. One way or the other, the identification of the best energy retrofit actions or the choice of a better technological solution to plan a building is not so simple. It has become one of the main objectives of several research studies, which require deep knowledge in the field of the building energy balance. The building thermal balance includes all sources and sinks of energy, as well as all energy that flows through its envelope. More in detail, the energy demand in buildings depends on the combination of several parameters, such as climate, envelope features, occupant behaviour and intended use. Indeed, the assessment of building energy performance requires substantial input data describing structures, environmental conditions [8], thermo-physical properties of the envelope, geometry, control strategies, and several other parameters. From the first design phases designers and researchers, which are trying to respect the prescriptions of the EPBD directive and to simultaneously ensure the thermal comfort of the occupants, must optimize all possible aspects that represent the key points in the building energy balance. As will be shown in Chapter A, the literature offers highly numerous complex and simplified resolution approaches [9]. Some are based on knowledge of the building thermal balance and on the resolution of physical equations; others are based on cumulated building data and on implementations of forecast models developed by machine-learning techniques [10]. Several numerical approaches are most widespread; these have undergone testing and implementing in specialised software tools such as DOE-2 [11], Energy Plus [12], TRNSYS [13] and ESP-r [14]. Such building modelling software can be employed in several ways on different scales; they can be simplified [15,16] or detailed comprehensively by different methods and numerical approaches [17]. Nevertheless, they are often characterised by a lack of a common language, which constitutes an obstacle for making a suitable choice. It is often more convenient to accelerate the building thermal needs evaluation and use the simplified methods and models. For example, a steady state approach for the evaluation of thermal loads is characterised by a good level of accuracy and low computational costs. However, its main limitation is that some phenomenon, such as the thermal inertia of the building envelope/structure, may be completely neglected. On the other hand, the choice of a more complex solution, such as the dynamic approach, uses very elaborate physical functions to evaluate the energy consumption of buildings. Although these dynamic simulation tools are effective and accurate, they have some practical difficulties such as collecting detailed building data and/or evaluating the proper boundary conditions. The use of these tools normally requires an expert user and a careful calibration of the model and do not provide a generalised response for a group of buildings with the same simulation, because they support a specific answer to a specific problem. Meanwhile the lack of precise input can lead to low-accuracy simulation. Anyway, in all cases it is necessary to be an expert user to implement, solve and evaluate the results, and these phases are not fast and not always immediately provide the correct evaluation, conducting the user to restart the entire procedure. In the field of energy planning, in order to identify energy efficiency actions aimed at a particular context, could be more convenient to speed up the preliminary assessment phase resorting to a simplified model that allows the evaluation of thermal energy demand with a good level of accuracy and without excessive computational cost or user expertise. The aim of this research, conducted during the three years of the PhD studies, is based on the idea of overcoming the limits previously indicated developing a reliable and a simple building energy tool or an evaluation model capable of helping an unskilled user at least in the first evaluation phase. To achieve this purpose, the first part of the research was characterised of an in-depth study of the sector bibliography with the analysis of the most widespread and used methods aimed at solving the thermal balance of buildings. After a brief distinction of the analysed methods in White, Black and Grey Box category, it was possible to highlight the strengths and weaknesses of each one [9]. Based on the analysis of this study, some alternative methods have been investigated. In detail, the idea was to investigate several Black-Box approaches; mainly used to deduce prediction models from a relevant database. This category does not require any information about physical phenomena but are based on a function deduced only by means of sample data connected to each other and which describes the behaviour of a specific system. Therefore, it is fundamental the presence of a suitable and well-set database that characterise the problem, so that the output data are strongly related to one or more input data. The completely absence of this information and the great difficulty in finding data, has led to the creation of a basic energy database which, under certain hypotheses, is representative of a specific building stock. For this reason, in the first step of this research was developed a generic building energy database that in a reliable way, and underlining the main features of the thermal balance, issues information about the energy performances. In detail, two energy building databases representative of a non-residential building-stock located in the European and Italian territory have been created. Starting from a well-known and calibrated Base-Case dynamic model, which simulates the actual behaviour of a non-residential building located in Palermo, it was created an Ideal Building representative of a new non-residential building designed with high energy performances in accordance whit the highest standard requirements of the European Community. Taking into consideration the differences existing in the regulations and technical standards about the building energy performance of various European countries, several detailed dynamic simulation models were developed. Moreover, to consider different climatic characteristics, different locations were evaluated for each country or thermal zone which represent the hottest, the coolest and the mildest climate. The shape factor of buildings, which represents the ratio between the total of the loss surfaces to the gross heated volume of a building, was varied from 0.24 to 0.90. To develop a representative database where the data that identify the building conditions are the inputs of the model linked to an output that describes the energy performances it was decided to develop a parametric simulation. In detail different transmittance values, boundary conditions, construction materials, and energy carriers were chosen and employed to model representative building stocks of European and Italian cities for different climatic zones, weather conditions, and shape factor; all details and the main features are described in Chapter B. These two databases were used to investigated three alternative methods to solve the building thermal balance; these are: • Multi Linear Regression (MLR): identification of some simple correlations that uses well known parameters in every energy diagnosis [18–20]; • Buckingham Method (BM): definition of dimensionless numbers that synthetically describe the relationships between the main characteristic parameters of the thermal balance [21]; and • Artificial Neural Network (ANN): Application of a specific Artificial Intelligence (AI) to determine the thermal needs of a [22] building. These methods, belonging to the Black-Box category, permit solving a complex problem easier with respect to the White-Box methods because they do not require any information about physical phenomena and expert user skills. Only a small amount of data on well-known parameters that represent the thermal balance of a building is required. The first analysed alternative method was the MLR, described in Chapter C. This approach allowed to develop a simple model that guarantees a quick evaluation of building energy needs [19] and is often used as a predictive tool. It is reliable and, at the same time, easy to use even for a non-expert user since an in-depth knowledge in the use phase is not needed, and computational costs are low. Moreover, the presence of an accurate input analysis guarantees greater speed and simplicity in the data collection phase [23]. The basis for this model is the linear regression among the variables to forecast and two or more explanatory variables. The feasibility and reliability of MLR models is demonstrated by the publication of the main achieved results in international journals. At first, the MLR method was applied on a dataset that considered heating energy consumptions for three configurations of non-residential buildings located in seven European countries. In this way, it was developed a specific equation for each country and three equations that describe each climatic region identified by a cluster analysis; these results were published in [19]. In a second work [18], it was applied the same methodology to a set of data referring to buildings located in the Italian peninsula. In this case, three building analysed configurations, in accordance to Italian legislative requirements regarding the construction of high energy performance buildings, have been employed. The achievement of the generalised results along with a high level of reliability it was achieved by diversifying each individual model according to its climate zone. It was provided an equation for each climate zone along with a unique equation applicable to the entire peninsula, obviously with different degrees of reliability. An improved version of the latest work concerning the Italian case study appeared in the paper published in [20]. The revised model provided an ability to predict the energy needs for both heating and cooling. Furthermore, to simplify the data retrieval phase that is required for the use of the developed MLR tool, an input selection analysis based on the Pearson coefficient has been performed. In this way the explanatory variables, needful for an optimal identification of thermal loads, have been identified. Finally, a comprehensive statistical analysis of errors ensured high reliability. The second analysed alternative method represents an innovative approach in developing a flexible and efficient tool in the building energy forecast framework. This tool predicts the energy performance of a building based some dimensionless parameters implemented through the application of the Buckingham theorem. A detailed description of the methodology and results is discussed in the Chapter D and is also published in [21]. The Buckingham theorem represents a key theorem of the dimensional analysis since it is able to define the dimensionless parameters representing the building balance [24]. These parameters define the relationships between the descriptive variables and the fundamental dimensions. Such a dimensional analysis guarantees that the relationship between physical quantities remains valid, even if there is a variation of the magnitudes of the base units of measurement [25]. The dimensional analysis represents a good model to simplify a problem by means of the dimensional homogeneity and, therefore, the consequent reduction in the number of variables. Therefore, this model works well with different applications such as forecasting, planning, control, diagnostics and monitoring in different sectors. The application of the BM for predicting the energy performance of buildings determined nine ad hoc dimensionless numbers. The identification of a set of criteria and a critical analysis of the results allowed to immediately determine thought the dimensionless numbers and without using any software tool, the heating energy demand with a reliability of over 90%. Furthermore, the validation of the proposed methodology was carried out by comparing the heating energy demand that was calculated by a detailed and accurate dynamic simulation. The last Black-Box examined model was the application of Artificial Neural Networks. The ANNs are the most widely used data mining models, characterised by one of the highest levels of accuracy with respect to other methods but generally have higher computational costs in the developing phase [26]. The design of a neural network, inspired by the behaviour of the human brain, involves the large number of suitably connected nodes (neurons) that, upon applications of simple mathematical operations, influence the learning ability of the network itself [27]. Also in this case, as described in Chapter E, this methodology was applied at the two different energy databases. In [22], the ANN was used to predict the demand for thermal energy linked to the winter climatization of non-residential buildings located in European context, while in another work under review, the ANN was used to determine the heating and cooling energy demand of a representative Italian building stock. The validation of the ANNs was carried out by using a set of data corresponding to 15% of the initial set which were not used to train the ANNs. The obtained good results (determination coefficient values higher than 0.95 and Mean Absolute Percentage Error lower than 10%) show the suitability of the calculation model based on the use of adaptive systems for the evaluation of energy performance of buildings. Simultaneously, a deep analysis of the investigated problem, underlines how to determine the thermal behaviour of a building trough Black-Box models, particular attention must be paid to the choice of an accurate climate database that along with thermophysical characteristics, strongly influence the thermal behaviour of a building [9]. In detail, to develop a predictive model of thermal needs, it is also necessary to pay close attention to the climate aspects. In the literature, many studies use the degree day (DD) to predict building energy demand, but this assessment, through the use of a climatic index, is correct only if its determination is a function of the same weather data used for the model implementation. Otherwise, the predictive model is generally affected by a greater evaluation error; all these aspects are deeply discussed analysing a specific Italian case study in Chapter F, and the main results are published in [8]. The results achieved during the three years of PhD research, make it possible to affirm that each model can be used to solve thermal building balance by knowing merely a few parameters representative of the analysed problem. Nonetheless, some questions may be asked: Which of these models can be identified as the most efficient solution? Is it possible to compare the performances of these models? Is it possible to choose the most efficient model based on some specific phase in the evaluation? To attempt to answer these questions, during the research period it was decided to compare the three selected alternative models by applying a Multi Criteria Analysis (MCA), that explicitly evaluates multiple criteria in decision-making. It is a useful decision support tool to apply to many complex decisions by choosing among several alternatives. The idea rising thanks to the scientific collaboration with the VGTU University of Vilnius, Lithuanian, in the person of Prof. A. Kaklauskas and Prof. L. Tupènaitè, experts in the field of multi-criteria analysis. At the first time a multi-criteria procedure was applied to determine the most efficient alternative model among some resolution procedures of a building's energy balance. This application required extra effort in defining the criteria and identifying a team of experts. To apply the MCA, it was necessary to identify the salient phases of the evaluation procedure to explain the most sensitive criteria for acquiring conscious, truthful answers that only a pool of experts in the field can provide. Details of this work were carried out during the period of one-month research in Vilnius, from April to May 2019, where it was possible to improve the application of the Multiple Criteria Complex Proportional Evaluation (COPRAS) method for identifying the most efficient predictive tool to evaluate building thermal needs. These results are collected in Chapter G and the main results are explained in a paper under review in the Journal "Energy" from September. The identification of the most efficient alternative model to solve the building energy balance through the application of a specific MCA, allowed to deepen the identified methodology and improve research. In particular, the most efficient alternative resolution model was the subject of the research that took place during the research period at the RWTH in Aachen University, Germany with Prof. M. Traverso, Head of the INaB Department, from September 2018 to March 2019. The experience in the field of LCA and the possibility of identifying the environmental impacts linked to the building system, has led the research to investigate neural networks for a dual and simultaneous environmental-energy analysis. The results confirm that the application of ANNs is a good alternative model for solving the energy and environmental balance of a building and for ensuring the development of reliable decision support tools that can be used by non-expert users. ANNs can be improved by upgrading the training database and choosing the network structure and learning algorithm. The results of this research are collected in Chapter H and published in [28].

BACKGROUND: The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. RESULTS: Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. CONCLUSION: We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens. ; The work of IF was funded, in part, by the National Science Foundation award DBI-1458359. The work of CSG and AJL was funded, in part, by the National Science Foundation award DBI-1458390 and GBMF 4552 from the Gordon and Betty Moore Foundation. The work of DAH and KAL was funded, in part, by the National Science Foundation award DBI-1458390, National Institutes of Health NIGMS P20 GM113132, and the Cystic Fibrosis Foundation CFRDP STANTO19R0. The work of AP, HY, AR, and MT was funded by BBSRC grants BB/K004131/1, BB/F00964X/1 and BB/M025047/1, Consejo Nacional de Ciencia y Tecnología Paraguay (CONACyT) grants 14-INV-088 and PINV15-315, and NSF Advances in BioInformatics grant 1660648. The work of JC was partially supported by an NIH grant (R01GM093123) and two NSF grants (DBI 1759934 and IIS1763246). ACM acknowledges the support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy - EXC 2155 "RESIST" - Project ID 39087428. DK acknowledges the support from the National Institutes of Health (R01GM123055) and the National Science Foundation (DMS1614777, CMMI1825941). PB acknowledges the support from the National Institutes of Health (R01GM60595). GB and BZK acknowledge the support from the National Science Foundation (NSF 1458390) and NIH DP1MH110234. FS was funded by the ERC StG 757700 "HYPER-INSIGHT" and by the Spanish Ministry of Science, Innovation and Universities grant BFU2017-89833-P. FS further acknowledges the funding from the Severo Ochoa award to the IRB Barcelona. TS was funded by the Centre of Excellence project "BioProspecting of Adriatic Sea", co-financed by the Croatian Government and the European Regional Development Fund (KK.01.1.1.01.0002). The work of SK was funded by ATT Tieto käyttöön grant and Academy of Finland. JB and HM acknowledge the support of the University of Turku, the Academy of Finland and CSC – IT Center for Science Ltd. TB and SM were funded by the NIH awards UL1 TR002319 and U24 TR002306. The work of CZ and ZW was funded by the National Institutes of Health R15GM120650 to ZW and start-up funding from the University of Miami to ZW. The work of PWR was supported by the National Cancer Institute of the National Institutes of Health under Award Number U01CA198942. PR acknowledges NSF grant DBI-1458477. PT acknowledges the support from Helsinki Institute for Life Sciences. The work of AJM was funded by the Academy of Finland (No. 292589). The work of FZ and WT was funded by the National Natural Science Foundation of China (31671367, 31471245, 91631301) and the National Key Research and Development Program of China (2016YFC1000505, 2017YFC0908402]. CS acknowledges the support by the Italian Ministry of Education, University and Research (MIUR) PRIN 2017 project 2017483NH8. SZ is supported by the National Natural Science Foundation of China (No. 61872094 and No. 61572139) and Shanghai Municipal Science and Technology Major Project (No. 2017SHZDZX01). PLF and RLH were supported by the National Institutes of Health NIH R35-GM128637 and R00-GM097033. JG, DTJ, CW, DC, and RF were supported by the UK Biotechnology and Biological Sciences Research Council (BB/N019431/1, BB/L020505/1, and BB/L002817/1) and Elsevier. The work of YZ and CZ was funded in part by the National Institutes of Health award GM083107, GM116960, and AI134678; the National Science Foundation award DBI1564756; and the Extreme Science and Engineering Discovery Environment (XSEDE) award MCB160101 and MCB160124. The work of BG, VP, RD, NS, and NV was funded by the Ministry of Education, Science and Technological Development of the Republic of Serbia, Project No. 173001. The work of YWL, WHL, and JMC was funded by the Taiwan Ministry of Science and Technology (106-2221-E-004-011-MY2). YWL, WHL, and JMC further acknowledge the support from "the Human Project from Mind, Brain and Learning" of the NCCU Higher Education Sprout Project by the Taiwan Ministry of Education and the National Center for High-performance Computing for computer time and facilities. The work of IK and AB was funded by Montana State University and NSF Advances in Biological Informatics program through grant number 0965768. BR, TG, and JR are supported by the Bavarian Ministry for Education through funding to the TUM. The work of RB, VG, MB, and DCEK was supported by the Simons Foundation, NIH NINDS grant number 1R21NS103831-01 and NSF award number DMR-1420073. CJJ acknowledges the funding from a University of Illinois at Chicago (UIC) Cancer Center award, a UIC College of Liberal Arts and Sciences Faculty Award, and a UIC International Development Award. The work of ML was funded by Yad Hanadiv (grant number 9660 /2019). The work of OL and IN was funded by the National Institute of General Medical Science of the National Institute of Health through GM066099 and GM079656. Research Supporting Plan (PSR) of University of Milan number PSR2018-DIP-010-MFRAS. AWV acknowledges the funding from the BBSRC (CASE studentship BB/M015009/1). CD acknowledges the support from the Swiss National Science Foundation (150654). CO and MJM are supported by the EMBL-European Bioinformatics Institute core funds and the CAFA BBSRC BB/N004876/1. GG is supported by CAFA BBSRC BB/N004876/1. SCET acknowledges funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 778247 (IDPfun) and from COST Action BM1405 (NGP-net). SEB was supported by NIH/NIGMS grant R01 GM071749. The work of MLT, JMR, and JMF was supported by the National Human Genome Research Institute of the National of Health, grant numbers U41 HG007234. The work of JMF and JMR was also supported by INB Grant (PT17/0009/0001 - ISCIII-SGEFI / ERDF). VA acknowledges the funding from TUBITAK EEEAG-116E930. RCA acknowledges the funding from KanSil 2016K121540. GV acknowledges the funding from Università degli Studi di Milano - Project "Discovering Patterns in Multi-Dimensional Data" and Project "Machine Learning and Big Data Analysis for Bioinformatics". SZ is supported by the National Natural Science Foundation of China (No. 61872094 and No. 61572139) and Shanghai Municipal Science and Technology Major Project (No. 2017SHZDZX01). RY and SY are supported by the 111 Project (NO. B18015), the key project of Shanghai Science & Technology (No. 16JC1420402), Shanghai Municipal Science and Technology Major Project (No. 2018SHZDZX01), and ZJLab. ST was supported by project Ribes Network POR-FESR 3S4H (No. TOPP-ALFREVE18-01) and PRID/SID of University of Padova (No. TOPP-SID19-01). CZ and ZW were supported by the NIGMS grant R15GM120650 to ZW and start-up funding from the University of Miami to ZW. The work of MK and RH was supported by the funding from King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. URF/1/3454-01-01 and URF/1/3790-01-01. The work of SDM is funded, in part, by NSF award DBI-1458443 ; Sí

BACKGROUND: The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. RESULTS: Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. CONCLUSION: We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens. ; The work of IF was funded, in part, by the National Science Foundation award DBI-1458359. The work of CSG and AJL was funded, in part, by the National Science Foundation award DBI-1458390 and GBMF 4552 from the Gordon and Betty Moore Foundation. The work of DAH and KAL was funded, in part, by the National Science Foundation award DBI-1458390, National Institutes of Health NIGMS P20 GM113132, and the Cystic Fibrosis Foundation CFRDP STANTO19R0. The work of AP, HY, AR, and MT was funded by BBSRC grants BB/K004131/1, BB/F00964X/1 and BB/M025047/1, Consejo Nacional de Ciencia y Tecnologia Paraguay (CONACyT) grants 14-INV-088 and PINV15-315, and NSF Advances in BioInformatics grant 1660648. The work of JC was partially supported by an NIH grant (R01GM093123) and two NSF grants (DBI 1759934 and IIS1763246). ACM acknowledges the support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy -EXC 2155 "RESIST" - Project ID 39087428. DK acknowledges the support from the National Institutes of Health (R01GM123055) and the National Science Foundation (DMS1614777, CMMI1825941). PB acknowledges the support from the National Institutes of Health (R01GM60595). GB and BZK acknowledge the support from the National Science Foundation (NSF 1458390) and NIH DP1MH110234. FS was funded by the ERC StG 757700 "HYPER-INSIGHT" and by the Spanish Ministry of Science, Innovation and Universities grant BFU2017-89833-P. FS further acknowledges the funding from the Severo Ochoa award to the IRB Barcelona. TS was funded by the Centre of Excellence project "BioProspecting of Adriatic Sea", co-financed by the Croatian Government and the European Regional Development Fund (KK.01.1.1.01.0002). The work of SK was funded by ATT Tieto kayttoon grant and Academy of Finland. JB and HM acknowledge the support of the University of Turku, the Academy of Finland and CSC -IT Center for Science Ltd. TB and SM were funded by the NIH awards UL1 TR002319 and U24 TR002306. The work of CZ and ZW was funded by the National Institutes of Health R15GM120650 to ZW and start-up funding from the University of Miami to ZW. The work of PWR was supported by the National Cancer Institute of the National Institutes of Health under Award Number U01CA198942. PR acknowledges NSF grant DBI-1458477. PT acknowledges the support from Helsinki Institute for Life Sciences. The work of AJM was funded by the Academy of Finland (No. 292589). The work of FZ and WT was funded by the National Natural Science Foundation of China (31671367, 31471245, 91631301) and the National Key Research and Development Program of China (2016YFC1000505, 2017YFC0908402]. CS acknowledges the support by the Italian Ministry of Education, University and Research (MIUR) PRIN 2017 project 2017483NH8. SZ is supported by the National Natural Science Foundation of China (No. 61872094 and No. 61572139) and Shanghai Municipal Science and Technology Major Project (No. 2017SHZDZX01). PLF and RLH were supported by the National Institutes of Health NIH R35-GM128637 and R00-GM097033. JG, DTJ, CW, DC, and RF were supported by the UK Biotechnology and Biological Sciences Research Council (BB/N019431/1, BB/L020505/1, and BB/L002817/1) and Elsevier. The work of YZ and CZ was funded in part by the National Institutes of Health award GM083107, GM116960, and AI134678; the National Science Foundation award DBI1564756; and the Extreme Science and Engineering Discovery Environment (XSEDE) award MCB160101 and MCB160124. The work of BG, VP, RD, NS, and NV was funded by the Ministry of Education, Science and Technological Development of the Republic of Serbia, Project No. 173001. The work of YWL, WHL, and JMC was funded by the Taiwan Ministry of Science and Technology (106-2221-E-004-011-MY2). YWL, WHL, and JMC further acknowledge the support from "the Human Project from Mind, Brain and Learning" of the NCCU Higher Education Sprout Project by the Taiwan Ministry of Education and the National Center for High-performance Computing for computer time and facilities. The work of IK and AB was funded by Montana State University and NSF Advances in Biological Informatics program through grant number 0965768. BR, TG, and JR are supported by the Bavarian Ministry for Education through funding to the TUM. The work of RB, VG, MB, and DCEK was supported by the Simons Foundation, NIH NINDS grant number 1R21NS103831-01 and NSF award number DMR-1420073. CJJ acknowledges the funding from a University of Illinois at Chicago (UIC) Cancer Center award, a UIC College of Liberal Arts and Sciences Faculty Award, and a UIC International Development Award. The work of ML was funded by Yad Hanadiv (grant number 9660/2019). The work of OL and IN was funded by the National Institute of General Medical Science of the National Institute of Health through GM066099 and GM079656. Research Supporting Plan (PSR) of University of Milan number PSR2018-DIP-010-MFRAS. AWV acknowledges the funding from the BBSRC (CASE studentship BB/M015009/1). CD acknowledges the support from the Swiss National Science Foundation (150654). CO and MJM are supported by the EMBL-European Bioinformatics Institute core funds and the CAFA BBSRC BB/N004876/1. GG is supported by CAFA BBSRC BB/N004876/1. SCET acknowledges funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 778247 (IDPfun) and from COST Action BM1405 (NGP-net). SEB was supported by NIH/NIGMS grant R01 GM071749. The work of MLT, JMR, and JMF was supported by the National Human Genome Research Institute of the National of Health, grant numbers U41 HG007234. The work of JMF and JMR was also supported by INB Grant (PT17/0009/0001 - ISCIII-SGEFI/ERDF). VA acknowledges the funding from TUBITAK EEEAG-116E930. RCA acknowledges the funding from KanSil 2016K121540. GV acknowledges the funding from Universita degli Studi di Milano - Project "Discovering Patterns in Multi-Dimensional Data" and Project "Machine Learning and Big Data Analysis for Bioinformatics". SZ is supported by the National Natural Science Foundation of China (No. 61872094 and No. 61572139) and Shanghai Municipal Science and Technology Major Project (No. 2017SHZDZX01). RY and SY are supported by the 111 Project (NO. B18015), the key project of Shanghai Science & Technology (No. 16JC1420402), Shanghai Municipal Science and Technology Major Project (No. 2018SHZDZX01), and ZJLab. ST was supported by project Ribes Network POR-FESR 3S4H (No. TOPP-ALFREVE18-01) and PRID/SID of University of Padova (No. TOPP-SID19-01). CZ and ZW were supported by the NIGMS grant R15GM120650 to ZW and start-up funding from the University of Miami to ZW. The work of MK and RH was supported by the funding from King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. URF/1/3454-01-01 and URF/1/3790-01-01. The work of SDM is funded, in part, by NSF award DBI-1458443. ; Sí