Motivation to Participate: Understanding Students\u27 Reasons for Participating as a Help in Growing a Youth Group

Why do high school students participate in church activities? The question has been asked and answered abstractly and anecdotally for years. Still, no one working in church ministry with high school students really understands what motivates those who participate regularly in church youth group activities to do so. It seems that understanding these motivations would be a rather high priority considering what seems to be increasing disinterest in church among contemporary high schoolers

Motivation to Participate: Understanding Students\u27 Reasons for Participating as a Help in Growing a Youth Group

Why do high school students participate in church activities? The question has been asked and answered abstractly and anecdotally for years. Still, no one working in church ministry with high school students really understands what motivates those who participate regularly in church youth group activities to do so. It seems that understanding these motivations would be a rather high priority considering what seems to be increasing disinterest in church among contemporary high schoolers

Minimal cross-recombination between wild-type and loxP511 sites in vivo facilitates truncating both ends of large DNA inserts in pBACe3.6 and related vectors

Contrary to several earlier reports, we find that cross-recombination between wild-type and the mutant loxP511 sites is <0.5% of that between two wild-type sites if Cre protein is expressed by phage P1 during an infection. The finding enabled us to develop a procedure to truncate DNA progressively from both ends of large genomic inserts flanked by these two loxP sites in pBACe3.6 and related vectors with transposons carrying either a wild-type or a loxP511 sequence. Newly constructed loxP511 transposons contained either a kanamycin resistance gene or no marker. Insert DNA ends in deletions were sequenced with primers unique to each transposon-end remaining after the respective recombination. End-sequencing 223 deletions confirmed that the low level of cross-recombination, observed between those sites during the P1 transductions, does not complicate the procedure: truncations from the unintended end of genomic inserts did not occur. Multiple BACs pooled together could also be processed in a single tube to make end-deletions. This deletion technology, utilizing the very minimal cross-recombination between the mutant and wild-type loxP sites of most BAC clones in the public domain and a heterologous one inserted as a transposon, should facilitate functionally mapping long-range gene regulatory sequences and help to isolate genes with defined functional boundaries in numerous projects including those of therapeutic interest

MR446: Profiles of Sixteen Eastern Maine Fishing Communities

In the United States, a number of legal mandates require social impact assessments of proposed federal fisheries management and other actions. However, too often there are insufficient data with which to conduct social impact assessments for fisheries management, in part because these data are expensive and time consuming to collect and social science for SIAs is typically underfunded. To address this lack of data, these authors profiled 16 fish­ing communities in eastern Maine (Vinalhaven, Stonington, Bar Harbor, Northeast Harbor, Southwest Harbor, Bass Harbor, Swan’s Island, Steuben, Winter Harbor, Gouldsboro, Milbridge, Jonesport, Beals, Bucks Harbor, Lubec, and Eastport), focusing on the communities in eastern Maine currently or historically engaged in the New England groundfish fishery. The profiles are based on a rapid assessment to document the current infrastructure and updated with social, economic, and demographic data available from the 2010 U.S. Census and with 2011 state and federal license data.https://digitalcommons.library.umaine.edu/aes_miscreports/1026/thumbnail.jp

SP701-A-Growing and Harvesting Switchgrass for Ethanol Production in Tennessee

Switchgrass is a warm-season perennial grass native to North America. The plant can reach heights up to 10 feet with an extensive root system. Once established, switchgrass well-managed for biomass should have a productive life of 10-20 years. Within the stand, switchgrass is an extremely strong competitor. However, it is not considered an invasive plant. Switchgrass adapts well to a variety of soil and climatic conditions. It is most productive on moderately well to well-drained soils of medium fertility and a soil pH at 5.0 or above. The high cellulosic content of switchgrass makes it a favorable feedstock for ethanol production. It is anticipated that switchgrass can yield sufficient biomass to produce approximately 500 gallons of ethanol per acre. While the Tennessee Biofuels Initiative includes a demonstration plant to make ethanol from switchgrass, the market for switchgrass as an energy crop remains limited. Producers will likely need to be located within 30 to 50 miles of a cellulosic ethanol plant. Producing switchgrass for energy generally occurs under some form of contractual arrangement with the end-user. To reap potential benefits from using switchgrass for cellulosic ethanol production, the system of production must be profitable for farmers and energy producers, as well as cost effective for consumers

Cervical, Anal and Oral HPV in an Adolescent Inner-City Health Clinic Providing Free Vaccinations

Published human papillomavirus (HPV) vaccine trials indicate efficacy is strongest for those naive to the vaccine-types. However, few high-risk young women have been followed and cervical HPV has been the predominant outcome measure.We collected cervical and anal swabs, as well as oral rinse specimens from 645 sexually active inner-city young females attending a large adolescent health-clinic in New York City that offers free care and HPV vaccination. Specimens were tested for HPV-DNA using a MY09/MY11-PCR system. Type-specific prevalence of HPV at each anatomic site was compared for individuals by vaccination dose using generalized estimating equation logistic regression models.The majority of subjects reported being of non-Caucasian (92%) and/or Hispanic ethnicity (61%). Median age was 18 years (range:14-20). All had practiced vaginal sex, a third (33%) practiced anal sex, and most (77%) had also engaged in oral sex. At enrollment, 21% had not received the vaccine and 51% had received three doses. Prevalent HPV infection at enrollment was detected in 54% of cervical, 42% of anal and 20% of oral specimens, with vaccine types present in 7%, 6% and 1% of specimens, respectively. Comparing prevalence for vaccine types, the detection of HPV in the cervix of vaccinated compared to unvaccinated adolescents was significantly reduced: HPV6/11 (odds ratio [OR] = 0.19, 95%CI:0.06-0.75), HPV16 (OR = 0.31, 95%CI:0.11-0.88) and HPV18 (OR = 0.14, 95%CI:0.03-0.75). For anal HPV, the risk of detecting vaccine types HPV6/11 (OR = 0.27, 95%CI:0.10-0.72) and HPV18(OR = 0.12, 95%CI:0.01-1.16) were significantly reduced for vaccinated adolescents however, the risk for HPV16 was not significantly decreased (OR = 0.63, 95%CI:0.18-2.20).HPV Prevalence is extremely high in inner-city female adolescents. Administration of the HPV vaccine reduced the risk for cervical HPV; however continued follow-up is required to assess the protection for HPV at all sites in young women with high exposure

Simplicity in Visual Representation: A Semiotic Approach

Simplicity, as an ideal in the design of visual representations, has not received systematic attention. High-level guidelines are too general, and low-level guidelines too ad hoc, too numerous, and too often incompatible, to serve in a particular design situation. This paper reviews notions of visual simplicity in the literature within the analytical framework provided by Charles Morris' communication model, specifically, his trichotomy of communication levels—the syntactic, the semantic, and the pragmatic. Simplicity is ultimate ly shown to entail the adjudication of incompatibilities both within, and between, levels.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68281/2/10.1177_105065198700100103.pd

A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015–2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM2.5, PM10, PMC (coarse fraction of PM), NO2, SO2, NOx, CO, O3 and the total gaseous oxidant (OX = NO2 + O3) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015–2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO2 and NOx concentrations and peoples’ mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO2 and between 30% and 40% in mean PM2.5 concentrations over 2020 full lockdown compared to the same period in 2015–2019. However, PM2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO2/CO ratio). Some Chinese cities showed similar increases in PM2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O3 concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO2 anomalies were negative for 2020 compared to 2015–2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO2/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO2 decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO2 + O3) showed that primary NO2 emissions at urban locations were greater than the O3 production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO2 and O3 concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.Peer reviewedFinal Published versio

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015–2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM2.5, PM10, PMC (coarse fraction of PM), NO2, SO2, NOx, CO, O3 and the total gaseous oxidant (OX = NO2 + O3) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015–2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO2 and NOx concentrations and peoples’ mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO2 and between 30% and 40% in mean PM2.5 concentrations over 2020 full lockdown compared to the same period in 2015–2019. However, PM2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO2/CO ratio). Some Chinese cities showed similar increases in PM2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O3 concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO2 anomalies were negative for 2020 compared to 2015–2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO2/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO2 decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO2 + O3) showed that primary NO2 emissions at urban locations were greater than the O3 production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO2 and O3 concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.World Meteorological Organization Global Atmospheric Watch programme is gratefully acknowledged for initiating and coordinating this study and for supporting this publication. We acknowledge the following projects for supporting the analysis contained in this article: Air Pollution and Human Health for an Indian Megacity project PROMOTE funded by UK NERC and the Indian MOES, Grant reference number NE/P016391/1; Regarding project funding from the European Commission, the sole responsibility of this publication lies with the authors. The European Commission is not responsible for any use that may be made of the information contained therein. This project has received funding from the European Commission’s Horizon 2020 research and innovation program under grant agreement No 874990 (EMERGE project). European Regional Development Fund (project MOBTT42) under the Mobilitas Pluss programme; Estonian Research Council (project PRG714); Estonian Research Infrastructures Roadmap project Estonian Environmental Observatory (KKOBS, project 2014-2020.4.01.20-0281). European network for observing our changing planet project (ERAPLANET, grant agreement no. 689443) under the European Union’s Horizon 2020 research and innovation program, Estonian Ministry of Sciences projects (grant nos. P180021, P180274), and the Estonian Research Infrastructures Roadmap project Estonian Environmental Observatory (3.2.0304.11-0395). Eastern Mediterranean and Middle East—Climate and Atmosphere Research (EMME-CARE) project, which has received funding from the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement no. 856612) and the Government of Cyprus. INAR acknowledges support by the Russian government (grant number 14.W03.31.0002), the Ministry of Science and Higher Education of the Russian Federation (agreement 14.W0331.0006), and the Russian Ministry of Education and Science (14.W03.31.0008). We are grateful to to the following agencies for providing access to data used in our analysis: A.M. Obukhov Institute of Atmospheric Physics Russian Academy of Sciences; Agenzia Regionale per la Protezione dell’Ambiente della Campania (ARPAC); Air Quality and Climate Change, Parks and Environment (MetroVancouver, Government of British Columbia); Air Quality Monitoring & Reporting, Nova Scotia Environment (Government of Nova Scotia); Air Quality Monitoring Network (SIMAT) and Emission Inventory, Mexico City Environment Secretariat (SEDEMA); Airparif (owner & provider of the Paris air pollution data); ARPA Lazio, Italy; ARPA Lombardia, Italy; Association Agr´e´ee de Surveillance de la Qualit´e de l’Air en ˆIle-de- France AIRPARIF / Atmo-France; Bavarian Environment Agency, Germany; Berlin Senatsverwaltung für Umwelt, Verkehr und Klimaschutz, Germany; California Air Resources Board; Central Pollution Control Board (CPCB), India; CETESB: Companhia Ambiental do Estado de S˜ao Paulo, Brazil. China National Environmental Monitoring Centre; Chandigarh Pollution Control Committee (CPCC), India. DCMR Rijnmond Environmental Service, the Netherlands. Department of Labour Inspection, Cyprus; Department of Natural Resources Management and Environmental Protection of Moscow. Environment and Climate Change Canada; Environmental Monitoring and Science Division Alberta Environment and Parks (Government of Alberta); Environmental Protection Authority Victoria (Melbourne, Victoria, Australia); Estonian Environmental Research Centre (EERC); Estonian University of Life Sciences, SMEAR Estonia; European Regional Development Fund (project MOBTT42) under the Mobilitas Pluss programme; Finnish Meteorological Institute; Helsinki Region Environmental Services Authority; Haryana Pollution Control Board (HSPCB), IndiaLondon Air Quality Network (LAQN) and the Automatic Urban and Rural Network (AURN) supported by the Department of Environment, Food and Rural Affairs, UK Government; Madrid Municipality; Met Office Integrated Data Archive System (MIDAS); Meteorological Service of Canada; Minist`ere de l’Environnement et de la Lutte contre les changements climatiques (Gouvernement du Qu´ebec); Ministry of Environment and Energy, Greece; Ministry of the Environment (Chile) and National Weather Service (DMC); Moscow State Budgetary Environmental Institution MOSECOMONITORING. Municipal Department of the Environment SMAC, Brazil; Municipality of Madrid public open data service; National institute of environmental research, Korea; National Meteorology and Hydrology Service (SENAMHI), Peru; New York State Department of Environmental Conservation; NSW Department of Planning, Industry and Environment; Ontario Ministry of the Environment, Conservation and Parks, Canada; Public Health Service of Amsterdam (GGD), the Netherlands. Punjab Pollution Control Board (PPCB), India. R´eseau de surveillance de la qualit´e de l’air (RSQA) (Montr´eal); Rosgydromet. Mosecomonitoring, Institute of Atmospheric Physics, Russia; Russian Foundation for Basic Research (project 20–05–00254) SAFAR-IITM-MoES, India; S˜ao Paulo State Environmental Protection Agency, CETESB; Secretaria de Ambiente, DMQ, Ecuador; Secretaría Distrital de Ambiente, Bogot´a, Colombia. Secretaria Municipal de Meio Ambiente Rio de Janeiro; Mexico City Atmospheric Monitoring System (SIMAT); Mexico City Secretariat of Environment, Secretaría del Medio Ambiente (SEDEMA); SLB-analys, Sweden; SMEAR Estonia station and Estonian University of Life Sciences (EULS); SMEAR stations data and Finnish Center of Excellence; South African Weather Service and Department of Environment, Forestry and Fisheries through SAAQIS; Spanish Ministry for the Ecological Transition and the Demographic Challenge (MITECO); University of Helsinki, Finland; University of Tartu, Tahkuse air monitoring station; Weather Station of the Institute of Astronomy, Geophysics and Atmospheric Science of the University of S˜ao Paulo; West Bengal Pollution Control Board (WBPCB).http://www.elsevier.com/locate/envintam2023Geography, Geoinformatics and Meteorolog