Suchergebnisse

Los currículos son progresivamente relevantes para educar futuros ciudadanos activos. En este contexto, se vuelve fundamental explorar la relación entre las directrices curriculares y cómo la educación ciudadana es efectivamente alcanzada por los estudiantes en países Latinoamericanos. Por ello este artículo tiene por objetivo evaluar comparativamente la visión institucional expresada en cada currículum y las perspectivas de los estudiantes sobre asuntos ciudadanos. El análisis factorial exploratorio y el análisis estadístico descriptivo currícular se basan en dos fuentes valiosas y complementarias, respectivamente: El Estudio Internacional de Educación Cívica y Ciudadana (ICCS) y el Sistema Regional de Competencias de Ciudadanía (Sredecc). Luego de una comparación sistemática de ambas fuentes este estudio revela que varios aspectos curriculares son coherentes con las actitudes y creencias de los estudiantes, y sugiere pautas para mejorar y expandir la educación ciudadana en América Latina, considerando la importancia de esta para la formación de una ciudadanía activa. ; 1. Introduction. -Democracy and citizenship education. -Curriculum and citizenship education. -Latin American political context. -2. Data and research methods. -3. Results. -4.Discussion and conclusions. -References

By the 1980s, UK government research laboratories were an often quirky but always essential part of the state sector. In one of the most radical experiments in the organization and management of scientific research attempted in the UK, successive Conservative governments sought to reform these laboratories by applying the market-based solution of 'New Public Management'. Scrutinising Science explores and critiques that reform process by examining the laboratories' new organizational forms, the new visions of what science is for implicit in the reform agenda and the new forms of scientific knowledge production that have arisen as a consequence.

Cover -- Series Page -- Title Page -- Copyright Page -- Contents -- List of contributors -- Preface -- 1 Statistical aspects of ARCH and stochastic volatility -- 1.1 Introduction -- 1.2 ARCH -- 1.3 Stochastic volatility -- 1.4 Multivariate models -- 1.5 Option pricing with changing volatility -- 1.6 Continuous-time models -- 1.7 Concluding remarks -- 1.8 Appendix -- 1.9 Computing and data sources -- Acknowledgements -- References -- 2 Likelihood-based inference for cointegration of some nonstationary time series -- 2.1 Introduction -- 2.2 Granger's representation theorem -- 2.3 Purchasing power parity: an illustrative example -- 2.4 Formulation of the reduced-form error correction model and various hypotheses on the cointegrating relations -- 2.5 Estimation of cointegrating relations and calculation of test statistics -- 2.6 The empirical example continued -- 2.7 Asymptotic theory -- 2.8 Conclusion -- Acknowledgements -- References -- 3 Forecasting in macro-economics -- 3.1 Introduction -- 3.2 A framework for economic forecasting -- 3.3 Alternative methods of forecasting -- 3.4 The economic system and forecasting models -- 3.5 Measuring forecast accuracy -- 3.6 A taxonomy of forecast errors -- 3.7 Parameter constancy -- 3.8 Parameter non-constancy -- 3.9 Intercept corrections -- 3.10 Conclusions -- Acknowledgements -- References -- 4 Longitudinal panel data: an overview of current methodology -- 4.1 Introduction -- 4.2 General formulation -- 4.3 The GEE approach to longitudinal data analysis -- 4.4 Likelihood-based approaches to longitudinal data analysis -- 4.5 Estimation with incomplete data -- 4.6 Example: childhood obesity -- 4.7 Random effects models -- 4.8 Discussion -- Acknowledgements -- References -- 5 Pricing by no arbitrage -- 5.1 Introduction -- 5.2 Notation -- 5.3 The 'no arbitrage' condition.

Bioscience has recently undergone a series of knowledge-based and technological revolutions. A critical consequence has been increasing recognition of the need to invest in infrastructure. Good access to data (and samples) from multiple studies is axiomatic to the value of this infrastructure. Access must be streamlined, secure, and based upon transparent and 'fair' decision making. It must be clear who has created and who has used which data. Ethico-legal policies and guidelines, which reflect dominant local cultural and societal norms, must take account of the increasingly global nature of bioscience research. A robust data infrastructure must also be attentive to the translational aims and social impact of its knowledge generation. In order to maintain the trust of its constituency – the general public as well as professional, political, commercial stakeholders – it must develop mechanisms to take account of all of these perspectives. These considerations form the basis of an emerging data economy. Building on extant achievements and pursuing the ideas outlined here could revolutionise the way we use and manage large-scale data. They have critical implications for biomedical and public health research communities and will be of central relevance for healthcare managers and policy makers, governments and industry. However, if the major challenges are to be met we must continue to invest,both nationally and internationally, in developing the cooperative infrastructures that provide a complementary foil to competitive resourcing mechanisms that drive hypothesis-driven science.

Biobanks can have a pivotal role in elucidating disease etiology, translation, and advancing public health. However, meeting these challenges hinges on a critical shift in the way science is conducted and requires biobank harmonization. There is growing recognition that a common strategy is imperative to develop biobanking globally and effectively. To help guide this strategy, we articulate key principles, goals, and priorities underpinning a roadmap for global biobanking to accelerate health science, patient care, and public health. The need to manage and share very large amounts of data has driven innovations on many fronts. Although technological solutions are allowing biobanks to reach new levels of integration, increasingly powerful data-collection tools, analytical techniques, and the results they generate raise new ethical and legal issues and challenges, necessitating a reconsideration of previous policies, practices, and ethical norms. These manifold advances and the investments that support them are also fueling opportunities for biobanks to ultimately become integral parts of health-care systems in many countries. International harmonization to increase interoperability and sustainability are two strategic priorities for biobanking. Tackling these issues requires an environment favorably inclined toward scientific funding and equipped to address socio-ethical challenges. Cooperation and collaboration must extend beyond systems to enable the exchange of data and samples to strategic alliances between many organizations, including governmental bodies, funding agencies, public and private science enterprises, and other stakeholders, including patients. A common vision is required and we articulate the essential basis of such a vision herein. ; Jennifer R Harris . Lyle J Palmer . et al.

Recent research efforts have progressively shifted towards preventative psychiatry and prognostic identification of individuals before disease onset. We describe the development of a serum biomarker test for the identification of individuals at risk of developing schizophrenia based on multiplex immunoassay profiling analysis of 957 serum samples. First, we conducted a meta-analysis of five independent cohorts of 127 first-onset drug-naive schizophrenia patients and 204 controls. Using least absolute shrinkage and selection operator regression, we identified an optimal panel of 26 biomarkers that best discriminated patients and controls. Next, we successfully validated this biomarker panel using two independent validation cohorts of 93 patients and 88 controls, which yielded an area under the curve (AUC) of 0.97 (0.95-1.00) for schizophrenia detection. Finally, we tested its predictive performance for identifying patients before onset of psychosis using two cohorts of 445 pre-onset or at-risk individuals. The predictive performance achieved by the panel was excellent for identifying USA military personnel (AUC: 0.90 (0.86-0.95)) and help-seeking prodromal individuals (AUC: 0.82 (0.71-0.93)) who developed schizophrenia up to 2 years after baseline sampling. The performance increased further using the latter cohort following the incorporation of CAARMS (Comprehensive Assessment of At-Risk Mental State) positive subscale symptom scores into the model (AUC: 0.90 (0.82-0.98)). The current findings may represent the first successful step towards a test that could address the clinical need for early intervention in psychiatry. Further developments of a combined molecular/symptom-based test will aid clinicians in the identification of vulnerable patients early in the disease process, allowing more effective therapeutic intervention before overt disease onset.

Recent research efforts have progressively shifted towards preventative psychiatry and prognostic identification of individuals before disease onset. We describe the development of a serum biomarker test for the identification of individuals at risk of developing schizophrenia based on multiplex immunoassay profiling analysis of 957 serum samples. First, we conducted a meta-analysis of five independent cohorts of 127 first-onset drug-naive schizophrenia patients and 204 controls. Using least absolute shrinkage and selection operator regression, we identified an optimal panel of 26 biomarkers that best discriminated patients and controls. Next, we successfully validated this biomarker panel using two independent validation cohorts of 93 patients and 88 controls, which yielded an area under the curve (AUC) of 0.97 (0.95–1.00) for schizophrenia detection. Finally, we tested its predictive performance for identifying patients before onset of psychosis using two cohorts of 445 pre-onset or at-risk individuals. The predictive performance achieved by the panel was excellent for identifying USA military personnel (AUC: 0.90 (0.86–0.95)) and help-seeking prodromal individuals (AUC: 0.82 (0.71–0.93)) who developed schizophrenia up to 2 years after baseline sampling. The performance increased further using the latter cohort following the incorporation of CAARMS (Comprehensive Assessment of At-Risk Mental State) positive subscale symptom scores into the model (AUC: 0.90 (0.82–0.98)). The current findings may represent the first successful step towards a test that could address the clinical need for early intervention in psychiatry. Further developments of a combined molecular/symptom-based test will aid clinicians in the identification of vulnerable patients early in the disease process, allowing more effective therapeutic intervention before overt disease onset.

Recent research efforts have progressively shifted towards preventative psychiatry and prognostic identification of individuals before disease onset. We describe the development of a serum biomarker test for the identification of individuals at risk of developing schizophrenia based on multiplex immunoassay profiling analysis of 957 serum samples. First, we conducted a meta-analysis of five independent cohorts of 127 first-onset drug-naive schizophrenia patients and 204 controls. Using least absolute shrinkage and selection operator regression, we identified an optimal panel of 26 biomarkers that best discriminated patients and controls. Next, we successfully validated this biomarker panel using two independent validation cohorts of 93 patients and 88 controls, which yielded an area under the curve (AUC) of 0.97 (0.95-1.00) for schizophrenia detection. Finally, we tested its predictive performance for identifying patients before onset of psychosis using two cohorts of 445 pre-onset or at-risk individuals. The predictive performance achieved by the panel was excellent for identifying USA military personnel (AUC: 0.90 (0.86-0.95)) and help-seeking prodromal individuals (AUC: 0.82 (0.71-0.93)) who developed schizophrenia up to 2 years after baseline sampling. The performance increased further using the latter cohort following the incorporation of CAARMS (Comprehensive Assessment of At-Risk Mental State) positive subscale symptom scores into the model (AUC: 0.90 (0.82-0.98)). The current findings may represent the first successful step towards a test that could address the clinical need for early intervention in psychiatry. Further developments of a combined molecular/symptom-based test will aid clinicians in the identification of vulnerable patients early in the disease process, allowing more effective therapeutic intervention before overt disease onset.

Aims. The Seeds Of Life In Space IRAM/NOEMA large program aims at studying a set of crucial complex organic molecules in a sample of sources with a well-known physical structure that covers the various phases of solar-type star formation. One representative object of the transition from the prestellar core to the protostar phases has been observed toward the very low luminosity object (VeLLO) L1521F. This type of source is important to study to link prestellar cores and Class 0 sources and also to constrain the chemical evolution during the process of star formation. Methods. Two frequency windows (81.6-82.6 GHz and 96.65-97.65 GHz) were used to observe the emission from several complex organics toward the L1521F VeLLO. These setups cover transitions of ketene (H2CCO), propyne (CH3CCH), formamide (NH2CHO), methoxy (CH3O), methanol (CH3OH), dimethyl ether (CH3OCH3), and methyl formate (HCOOCH3). Results. Only two transitions of methanol (A+, E2) have been detected in the narrow window centered at 96.7 GHz (with an upper limit on E1) in a very compact emission blob (∼7″ corresponding to ∼1000 au) toward the northeast of the L1521F protostar. The CS 2-1 transition is also detected within theWideX bandwidth. Consistently with what has been found in prestellar cores, the methanol emission appears ∼1000 au away from the dust peak. The location of the methanol blob coincides with one of the filaments that have previously been reported in the literature. The excitation temperature of the gas inferred from methanol is (10 ± 2) K, while the H2 gas density (estimated from the detected CS 2-1 emission and previous CS 5-4 ALMA observations) is a factor >25 higher than the density in the surrounding environment (n(H2) ≥ 107 cm-3). Conclusions. Based on its compactness, low excitation temperature, and high gas density, we suggest that the methanol emission detected with NOEMA is (i) either a cold and dense shock-induced blob that formed recently (≤ a few hundred years) by infalling gas or (ii) a cold and dense fragment that may just have been formed as a result of the intense gas dynamics within the L1521F VeLLO system. © 2020 C. Favre et al. ; Russian Science Foundation, RSF: 18–12–00351 ; Australian Education International, Australian Government, AEI: MDM-2017-0737 ; Agence Nationale de la Recherche, ANR: ANR-15-IDEX-02 ; European Research Council, ERC ; Horizon 2020 Framework Programme, H2020: 741002 ; Ministerio de Economía y Competitividad, MINECO: AYA2016-79006-P ; European Regional Development Fund, FEDER: ESP2017-86582-C4-1-R ; Acknowledgements. We thank our referee, Dr. Kazuki Tokuda, (i) for his fruitful comments that have improved the quality of our paper and (ii) for sharing his continuum emission map. This work is supported by the French National Research Agency in the framework of the Investissements d'Avenir program (ANR-15-IDEX-02), through the funding of the "Origin of Life" project of the Univ. Grenoble-Alpes. C.F., C.V. and C.C. acknowledge the funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme, for the Project The Dawn of Organic Chemistry (DOC), grant agreement No 741002. I.J.-S. has received partial support from the Spanish FEDER (project number ESP2017-86582-C4-1-R), and State Research Agency (AEI) through project number MDM-2017-0737 Unidad de Excelencia María de Maeztu–Centro de Astrobiología (INTA-CSIC). A.P. acknowledges the financial support of the Russian Science Foundation project 18–12–00351. A.C.-T acknowledges support from MINECO project AYA2016-79006-P.