Context Identifying key spatio–temporal periods of an organism's activity is an important focus of many ecological studies. Bat activity, as assessed by passive acoustic monitoring, can be extremely variable and currently there exists no agreed-upon method for identifying periods of high activity. Aims We proposed a new application for the space–time scan statistic (SaTScan) as an objective technique for identifying peak periods of bat activity. We aimed to test the validity of SaTScan as a method for identifying peaks in bat activity and demonstrate its use for assessing species-specific temporal patterns of activity. Methods To evaluate the effectiveness of SaTScan for detecting peaks in activity, we compared SaTScan to peaks identified with percentile thresholds. We evaluated peaks in activity across three scales: within nights; among nights at a site; and among sites. We applied SaTScan to demonstrate analysis of species-specific activity as further use of this technique. Key results SaTScan was effective at identifying peak time periods that included the majority of the high activity minutes. Timing of peaks of activity was most consistent for Myotis lucifugus during swarming and Lasiurus borealis during migration. All other activity for five species at three sites was indicative of foraging activity, with peaks in the first 5h after sunset. Conclusions SaTScan can be a valuable tool for quickly identifying peaks in acoustic activity of bats, with an objective, replicable and statistically sound method that can be applied at many temporal and spatial scales. Implications This tool has the potential for many more applications in ecology. Beyond acoustic analyses of bat activity, this technique could easily identify peaks in a research or management context, such as study activity among habitats, commercial developments or years at a single site.
In: Alcohol and alcoholism: the international journal of the Medical Council on Alcoholism (MCA) and the journal of the European Society for Biomedical Research on Alcoholism (ESBRA), Band 42, Heft 1, S. 42-48
Chapter Outlines -- Section 1: What is an Urban Bat? Morphological, Physiological, Behavioural and Genetic Adaptations -- Chapter 1: Physiological adaptation of bats to urban areas -- Chapter 2: Genetic impoverishment and species endangerment in the Anthropocene -- Chapter 3: Behavioral preadaptation of molossid bats to urban environments -- Chapter 4: The ecology of bats and their parasites in relation to urbanisation -- Chapter 5: Effect of urbanization on the social and mating system of bats -- Section 2: How do Bats Inhabit Urban Environments? Uses of Artificial Roosts, the Aerospace, and Green Spaces -- Chapter 6: Roost selection by urban bats -- Chapter 7: Bat boxes as roosting habitat in cities – 'thinking outside the box' -- Chapter 8: Woah, living in the air! Aerial habitats and aeroconservation for urban bats -- Chapter 9: What traits of greenspace in urban environments influence bat abundance and diversity? -- Chapter 10: Urban bats living in the city of Recife, Brazil -- Section 3: How do Bats and Humans Interact in Urban Environments? Human Perceptions, Public Health, and Ecosystem Services of Bats -- Chapter 11: Human dimension of bats in the city -- Chapter 12: Public health /conflicts between humans and bats -- Chapter 13: Ecosystem services of bats in urban habitats -- Chapter 14: The big picture, and moving forward with urban bat research, management, and conservation.
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Background Surgery is the main modality of cure for solid cancers and was prioritised to continue during COVID-19 outbreaks. This study aimed to identify immediate areas for system strengthening by comparing the delivery of elective cancer surgery during the COVID-19 pandemic in periods of lockdown versus light restriction. Methods This international, prospective, cohort study enrolled 20 006 adult (≥18 years) patients from 466 hospitals in 61 countries with 15 cancer types, who had a decision for curative surgery during the COVID-19 pandemic and were followed up until the point of surgery or cessation of follow-up (Aug 31, 2020). Average national Oxford COVID-19 Stringency Index scores were calculated to define the government response to COVID-19 for each patient for the period they awaited surgery, and classified into light restrictions (index 60). The primary outcome was the non-operation rate (defined as the proportion of patients who did not undergo planned surgery). Cox proportional-hazards regression models were used to explore the associations between lockdowns and non-operation. Intervals from diagnosis to surgery were compared across COVID-19 government response index groups. This study was registered at ClinicalTrials.gov, NCT04384926. Findings Of eligible patients awaiting surgery, 2003 (10·0%) of 20 006 did not receive surgery after a median follow-up of 23 weeks (IQR 16–30), all of whom had a COVID-19-related reason given for non-operation. Light restrictions were associated with a 0·6% non-operation rate (26 of 4521), moderate lockdowns with a 5·5% rate (201 of 3646; adjusted hazard ratio [HR] 0·81, 95% CI 0·77–0·84; p<0·0001), and full lockdowns with a 15·0% rate (1775 of 11 827; HR 0·51, 0·50–0·53; p<0·0001). In sensitivity analyses, including adjustment for SARS-CoV-2 case notification rates, moderate lockdowns (HR 0·84, 95% CI 0·80–0·88; p<0·001), and full lockdowns (0·57, 0·54–0·60; p<0·001), remained independently associated with non-operation. Surgery beyond 12 weeks from diagnosis in patients without neoadjuvant therapy increased during lockdowns (374 [9·1%] of 4521 in light restrictions, 317 [10·4%] of 3646 in moderate lockdowns, 2001 [23·8%] of 11 827 in full lockdowns), although there were no differences in resectability rates observed with longer delays. Interpretation Cancer surgery systems worldwide were fragile to lockdowns, with one in seven patients who were in regions with full lockdowns not undergoing planned surgery and experiencing longer preoperative delays. Although short-term oncological outcomes were not compromised in those selected for surgery, delays and non-operations might lead to long-term reductions in survival. During current and future periods of societal restriction, the resilience of elective surgery systems requires strengthening, which might include protected elective surgical pathways and long-term investment in surge capacity for acute care during public health emergencies to protect elective staff and services. Funding National Institute for Health Research Global Health Research Unit, Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, Medtronic, Sarcoma UK, The Urology Foundation, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research.
Background Surgery is the main modality of cure for solid cancers and was prioritised to continue during COVID-19 outbreaks. This study aimed to identify immediate areas for system strengthening by comparing the delivery of elective cancer surgery during the COVID-19 pandemic in periods of lockdown versus light restriction. Methods This international, prospective, cohort study enrolled 20 006 adult (≥18 years) patients from 466 hospitals in 61 countries with 15 cancer types, who had a decision for curative surgery during the COVID-19 pandemic and were followed up until the point of surgery or cessation of follow-up (Aug 31, 2020). Average national Oxford COVID-19 Stringency Index scores were calculated to define the government response to COVID-19 for each patient for the period they awaited surgery, and classified into light restrictions (index 60). The primary outcome was the non-operation rate (defined as the proportion of patients who did not undergo planned surgery). Cox proportional-hazards regression models were used to explore the associations between lockdowns and non-operation. Intervals from diagnosis to surgery were compared across COVID-19 government response index groups. This study was registered at ClinicalTrials.gov, NCT04384926. Findings Of eligible patients awaiting surgery, 2003 (10·0%) of 20 006 did not receive surgery after a median follow-up of 23 weeks (IQR 16–30), all of whom had a COVID-19-related reason given for non-operation. Light restrictions were associated with a 0·6% non-operation rate (26 of 4521), moderate lockdowns with a 5·5% rate (201 of 3646; adjusted hazard ratio [HR] 0·81, 95% CI 0·77–0·84; p<0·0001), and full lockdowns with a 15·0% rate (1775 of 11 827; HR 0·51, 0·50–0·53; p<0·0001). In sensitivity analyses, including adjustment for SARS-CoV-2 case notification rates, moderate lockdowns (HR 0·84, 95% CI 0·80–0·88; p<0·001), and full lockdowns (0·57, 0·54–0·60; p<0·001), remained independently associated with non-operation. Surgery beyond 12 weeks from diagnosis in patients without neoadjuvant therapy increased during lockdowns (374 [9·1%] of 4521 in light restrictions, 317 [10·4%] of 3646 in moderate lockdowns, 2001 [23·8%] of 11827 in full lockdowns), although there were no differences in resectability rates observed with longer delays. Interpretation Cancer surgery systems worldwide were fragile to lockdowns, with one in seven patients who were in regions with full lockdowns not undergoing planned surgery and experiencing longer preoperative delays. Although short-term oncological outcomes were not compromised in those selected for surgery, delays and non-operations might lead to long-term reductions in survival. During current and future periods of societal restriction, the resilience of elective surgery systems requires strengthening, which might include protected elective surgical pathways and long- term investment in surge capacity for acute care during public health emergencies to protect elective staff and services. Funding National Institute for Health Research Global Health Research Unit, Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, Medtronic, Sarcoma UK, The Urology Foundation, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research.
ANPCyT, Argentina ; YerPhI, Armenia ; ARC, Australia ; BMWFW, Austria ; FWF, Austria ; ANAS, Azerbaijan ; SSTC, Belarus ; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ; Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) ; NSERC, Canada ; NRC, Canada ; CFI, Canada ; CERN ; CONICYT, Chile ; CAS, China ; MOST, China ; NSFC, China ; COLCIENCIAS, Colombia ; MSMT CR, Czech Republic ; MPO CR, Czech Republic ; VSC CR, Czech Republic ; DNRF, Denmark ; DNSRC, Denmark ; IN2P3-CNRS, CEA-DRF/IRFU, France ; SRNSFG, Georgia ; BMBF, Germany ; HGF, Germany ; MPG, Germany ; GSRT, Greece ; RGC, Hong Kong SAR, China ; ISF, Israel ; Benoziyo Center, Israel ; INFN, Italy ; MEXT, Japan ; JSPS, Japan ; CNRST, Morocco ; NWO, Netherlands ; RCN, Norway ; MNiSW, Poland ; NCN, Poland ; FCT, Portugal ; MNE/IFA, Romania ; MES of Russia, Russian Federation ; NRC KI, Russian Federation ; JINR ; MESTD, Serbia ; MSSR, Slovakia ; ARRS, Slovenia ; MIZS, Slovenia ; DST/NRF, South Africa ; MINECO, Spain ; SRC, Sweden ; Wallenberg Foundation, Sweden ; SERI, Switzerland ; SNSF, Switzerland ; Canton of Bern, Switzerland ; MOST, Taiwan ; TAEK, Turkey ; STFC, United Kingdom ; DOE, United States of America ; NSF, United States of America ; BCKDF, Canada ; CANARIE, Canada ; CRC, Canada ; Compute Canada, Canada ; COST, European Union ; ERC, European Union ; ERDF, European Union ; Horizon 2020, European Union ; Marie Sk lodowska-Curie Actions, European Union ; Investissements d' Avenir Labex and Idex, ANR, France ; DFG, Germany ; AvH Foundation, Germany ; Greek NSRF, Greece ; BSF-NSF, Israel ; GIF, Israel ; CERCA Programme Generalitat de Catalunya, Spain ; Royal Society, United Kingdom ; Leverhulme Trust, United Kingdom ; BMBWF (Austria) ; FWF (Austria) ; FNRS (Belgium) ; FWO (Belgium) ; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) ; Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) ; FAPERGS (Brazil) ; MES (Bulgaria) ; CAS (China) ; MoST (China) ; NSFC (China) ; COLCIENCIAS (Colombia) ; MSES (Croatia) ; CSF (Croatia) ; RPF (Cyprus) ; SENESCYT (Ecuador) ; MoER (Estonia) ; ERC IUT (Estonia) ; ERDF (Estonia) ; Academy of Finland (Finland) ; MEC (Finland) ; HIP (Finland) ; CEA (France) ; CNRS/IN2P3 (France) ; BMBF (Germany) ; DFG (Germany) ; HGF (Germany) ; GSRT (Greece) ; NKFIA (Hungary) ; DAE (India) ; DST (India) ; IPM (Iran) ; SFI (Ireland) ; INFN (Italy) ; MSIP (Republic of Korea) ; NRF (Republic of Korea) ; MES (Latvia) ; LAS (Lithuania) ; MOE (Malaysia) ; UM (Malaysia) ; BUAP (Mexico) ; CINVESTAV (Mexico) ; CONACYT (Mexico) ; LNS (Mexico) ; SEP (Mexico) ; UASLP-FAI (Mexico) ; MOS (Montenegro) ; MBIE (New Zealand) ; PAEC (Pakistan) ; MSHE (Poland) ; NSC (Poland) ; FCT (Portugal) ; JINR (Dubna) ; MON (Russia) ; RosAtom (Russia) ; RAS (Russia) ; RFBR (Russia) ; NRC KI (Russia) ; MESTD (Serbia) ; SEIDI (Spain) ; CPAN (Spain) ; PCTI (Spain) ; FEDER (Spain) ; MOSTR (Sri Lanka) ; MST (Taipei) ; ThEPCenter (Thailand) ; IPST (Thailand) ; STAR (Thailand) ; NSTDA (Thailand) ; TAEK (Turkey) ; NASU (Ukraine) ; SFFR (Ukraine) ; STFC (United Kingdom ; DOE (U.S.A.) ; NSF (U.S.A.) ; Marie-Curie programme ; Horizon 2020 Grant (European Union) ; Leventis Foundation ; A.P. Sloan Foundation ; Alexander von Humboldt Foundation ; Belgian Federal Science Policy Office ; Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium) ; Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium) ; F.R.S.-FNRS (Belgium) ; Beijing Municipal Science & Technology Commission ; Ministry of Education, Youth and Sports (MEYS) of the Czech Republic ; Hungarian Academy of Sciences (Hungary) ; New National Excellence Program UNKP (Hungary) ; Council of Science and Industrial Research, India ; HOMING PLUS programme of the Foundation for Polish Science ; European Union, Regional Development Fund ; Mobility Plus programme of the Ministry of Science and Higher Education ; National Science Center (Poland) ; National Priorities Research Program by Qatar National Research Fund ; Programa Estatal de Fomento de la Investigacion Cientfica y Tecnica de Excelencia Maria de Maeztu ; Programa Severo Ochoa del Principado de Asturias ; EU-ESF ; Greek NSRF ; Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University (Thailand) ; Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand) ; Welch Foundation ; Weston Havens Foundation (U.S.A.) ; Canton of Geneva, Switzerland ; Herakleitos programme ; Thales programme ; Aristeia programme ; European Research Council (European Union) ; Horizon 2020 Grant (European Union): 675440 ; FWO (Belgium): 30820817 ; Beijing Municipal Science & Technology Commission: Z181100004218003 ; NKFIA (Hungary): 123842 ; NKFIA (Hungary): 123959 ; NKFIA (Hungary): 124845 ; NKFIA (Hungary): 124850 ; NKFIA (Hungary): 125105 ; National Science Center (Poland): Harmonia 2014/14/M/ST2/00428 ; National Science Center (Poland): Opus 2014/13/B/ST2/02543 ; National Science Center (Poland): 2014/15/B/ST2/03998 ; National Science Center (Poland): 2015/19/B/ST2/02861 ; National Science Center (Poland): Sonata-bis 2012/07/E/ST2/01406 ; Programa Estatal de Fomento de la Investigacion Cientfica y Tecnica de Excelencia Maria de Maeztu: MDM-2015-0509 ; Welch Foundation: C-1845 ; This paper presents the combinations of single-top-quark production cross-section measurements by the ATLAS and CMS Collaborations, using data from LHC proton-proton collisions at = 7 and 8 TeV corresponding to integrated luminosities of 1.17 to 5.1 fb(-1) at = 7 TeV and 12.2 to 20.3 fb(-1) at = 8 TeV. These combinations are performed per centre-of-mass energy and for each production mode: t-channel, tW, and s-channel. The combined t-channel cross-sections are 67.5 +/- 5.7 pb and 87.7 +/- 5.8 pb at = 7 and 8 TeV respectively. The combined tW cross-sections are 16.3 +/- 4.1 pb and 23.1 +/- 3.6 pb at = 7 and 8 TeV respectively. For the s-channel cross-section, the combination yields 4.9 +/- 1.4 pb at = 8 TeV. The square of the magnitude of the CKM matrix element V-tb multiplied by a form factor f(LV) is determined for each production mode and centre-of-mass energy, using the ratio of the measured cross-section to its theoretical prediction. It is assumed that the top-quark-related CKM matrix elements obey the relation |V-td|, |V-ts| « |V-tb|. All the |f(LV)V(tb)|(2) determinations, extracted from individual ratios at = 7 and 8 TeV, are combined, resulting in |f(LV)V(tb)| = 1.02 +/- 0.04 (meas.) +/- 0.02 (theo.). All combined measurements are consistent with their corresponding Standard Model predictions.
