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An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures. Related Article: Gabriel Marineau-Plante, Frank Juvenal, Adam Langlois, Daniel Fortin, Armand Soldera, Pierre D. Harvey|2018|Chem.Commun.|54|976|doi:10.1039/C7CC09503A

A Data Guide for this study is available as a web page and for download. The National Longitudinal Study of Adolescent to Adult Health (Add Health), 1994-2008 [Public Use] is a longitudinal study of a nationally representative sample of U.S. adolescents in grades 7 through 12 during the 1994-1995 school year. The Add Health cohort was followed into young adulthood with four in-home interviews, the most recent conducted in 2008 when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents' social, economic, psychological, and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships. Add Health Wave I data collection took place between September 1994 and December 1995, and included both an in-school questionnaire and in-home interview. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12, and gathered information on social and demographic characteristics of adolescent respondents, education and occupation of parents, household structure, expectations for the future, self-esteem, health status, risk behaviors, friendships, and school-year extracurricular activities. All students listed on a sample school's roster were eligible for selection into the core in-home interview sample. In-home interviews included topics such as health status, health-facility utilization, nutrition, peer networks, decision-making processes, family composition and dynamics, educational aspirations and expectations, employment experience, romantic and sexual partnerships, substance use, and criminal activities. A parent, preferably the resident mother, of each adolescent respondent interviewed in Wave I was also asked to complete an interviewer-assisted questionnaire covering topics such as inheritable health conditions, marriages and marriage-like relationships, neighborhood characteristics, involvement in volunteer, civic, and school activities, health-affecting behaviors, education and employment, household income and economic assistance, parent-adolescent communication and interaction, parent's familiarity with the adolescent's friends and friends' parents. Add Health data collection recommenced for Wave II from April to August 1996, and included almost 15,000 follow-up in-home interviews with adolescents from Wave I. Interview questions were generally similar to Wave I, but also included questions about sun exposure and more detailed nutrition questions. Respondents were asked to report their height and weight during the course of the interview, and were also weighed and measured by the interviewer. From August 2001 to April 2002, Wave III data were collected through in-home interviews with 15,170 Wave I respondents (now 18 to 26 years old), as well as interviews with their partners. Respondents were administered survey questions designed to obtain information about family, relationships, sexual experiences, childbearing, and educational histories, labor force involvement, civic participation, religion and spirituality, mental health, health insurance, illness, delinquency and violence, gambling, substance abuse, and involvement with the criminal justice system. High School Transcript Release Forms were also collected at Wave III, and these data comprise the Education Data component of the Add Health study. Wave IV in-home interviews were conducted in 2008 and 2009 when the original Wave I respondents were 24 to 32 years old. Longitudinal survey data were collected on the social, economic, psychological, and health circumstances of respondents, as well as longitudinal geographic data. Survey questions were expanded on educational transitions, economic status and financial resources and strains, sleep patterns and sleep quality, eating habits and nutrition, illnesses and medications, physical activities, emotional content and quality of current or most recent romantic/cohabiting/marriage relationships, and maltreatment during childhood by caregivers. Dates and circumstances of key life events occurring in young adulthood were also recorded, including a complete marriage and cohabitation history, full pregnancy and fertility histories from both men and women, an educational history of dates of degrees and school attendance, contact with the criminal justice system, military service, and various employment events, including the date of first and current jobs, with respective information on occupation, industry, wages, hours, and benefits. Finally, physical measurements and biospecimens were also collected at Wave IV, and included anthropometric measures of weight, height and waist circumference, cardiovascular measures such as systolic blood pressure, diastolic blood pressure, and pulse, metabolic measures from dried blood spots assayed for lipids, glucose, and glycosylated hemoglobin (HbA1c), measures of inflammation and immune function, including High sensitivity C-reactive protein (hsCRP) and Epstein-Barr virus (EBV). Datasets: DS0: Study-Level Files DS1: Wave I: In-Home Questionnaire, Public Use Sample DS2: Wave I: Public Use Contextual Database DS3: Wave I: Network Variables DS4: Wave I: Public Use Grand Sample Weights DS5: Wave II: In-Home Questionnaire, Public Use Sample DS6: Wave II: Public Use Contextual Database DS7: Wave II: Public Use Grand Sample Weights DS8: Wave III: In-Home Questionnaire, Public Use Sample DS9: Wave III: In-Home Questionnaire, Public Use Sample (Section 17: Relationships) DS10: Wave III: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancies) DS11: Wave III: In-Home Questionnaire, Public Use Sample (Section 19: Relationships in Detail) DS12: Wave III: In-Home Questionnaire, Public Use Sample (Section 22: Completed Pregnancies) DS13: Wave III: In-Home Questionnaire, Public Use Sample (Section 23: Current Pregnancies) DS14: Wave III: In-Home Questionnaire, Public Use Sample (Section 24: Live Births) DS15: Wave III: In-Home Questionnaire, Public Use Sample (Section 25: Children and Parenting) DS16: Wave III: Public Use Education Data DS17: Wave III: Public Use Graduation Data DS18: Wave III: Public Use Education Data Weights DS19: Wave III: Add Health School Weights DS20: Wave III: Peabody Picture Vocabulary Test (PVT), Public Use DS21: Wave III: Public In-Home Weights DS22: Wave IV: In-Home Questionnaire, Public Use Sample DS23: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16B: Relationships) DS24: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16C: Relationships) DS25: Wave IV: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancy Table) DS26: Wave IV: In-Home Questionnaire, Public Use Sample (Section 19: Live Births) DS27: Wave IV: In-Home Questionnaire, Public Use Sample (Section 20A: Children and Parenting) DS28: Wave IV: Biomarkers, Measures of Inflammation and Immune Function DS29: Wave IV: Biomarkers, Measures of Glucose Homeostasis DS30: Wave IV: Biomarkers, Lipids DS31: Wave IV: Public Use Weights Wave I: The Stage 1 in-school sample was a stratified, random sample of all high schools in the United States. A school was eligible for the sample if it included an 11th grade and had a minimum enrollment of 30 students. A feeder school -- a school that sent graduates to the high school and that included a 7th grade -- was also recruited from the community. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12. The Stage 2 in-home sample of 27,000 adolescents consisted of a core sample from each community, plus selected special over samples. Eligibility for over samples was determined by an adolescent's responses on the in-school questionnaire. Adolescents could qualify for more than one sample.; Wave II: The Wave II in-home interview surveyed almost 15,000 of the same students one year after Wave I.; Wave III: The in-home Wave III sample consists of over 15,000 Wave I respondents who could be located and re-interviewed six years later.; Wave IV: All original Wave I in-home respondents were eligible for in-home interviews at Wave IV. At Wave IV, the Add Health sample was dispersed across the nation with respondents living in all 50 states. Administrators were able to locate 92.5% of the Wave IV sample and interviewed 80.3% of eligible sample members. ; For additional information on sampling, including detailed information on special oversamples, please see the Add Health Study Design page. Add Health was developed in response to a mandate from the U.S. Congress to fund a study of adolescent health. Waves I and II focused on the forces that may influence adolescents' health and risk behaviors, including personal traits, families, friendships, romantic relationships, peer groups, schools, neighborhoods, and communities. As participants aged into adulthood, the scientific goals of the study expanded and evolved. Wave III explored adolescent experiences and behaviors related to decisions, behavior, and health outcomes in the transition to adulthood. Wave IV expanded to examine developmental and health trajectories across the life course of adolescence into young adulthood, using an integrative study design which combined social, behavioral, and biomedical measures data collection. Response Rates: Response rates for each wave were as follows: Wave I: 79 percent; Wave II: 88.6 percent; Wave III: 77.4 percent; Wave IV: 80.3 percent; Adolescents in grades 7 through 12 during the 1994-1995 school year. Respondents were geographically located in the United States. audio computer-assisted self interview (ACASI) computer-assisted personal interview (CAPI) computer-assisted self interview (CASI) paper and pencil interview (PAPI) face-to-face interview

Fig 2 (heatmap) data files and R codeData and R code needed to create Fig 2 in Hargreaves et al (2015) J Evol Biol. One data file for each of the 6 figure panels. Each file contains evolved D across the range in each of 500 generations of stable climate followed by 1000 generations of climate change.Fig 2 (heatmap).zipFig 3 (D lines) data and R codeData and R code needed to create Fig 3 in Hargreaves et al (2015) J Evol Biol. One data file for each of the 6 models shown. Each file contains evolved D across the range after 500 generations of stable climate and after 1000 generations of climate change, averaged across 10 runs per cost per model.Fig 3 (D lines).zipFig 4 (delta.D) data and R codeData and R code needed to create Fig 4 in Hargreaves et al (2015) J Evol Biol. One data file for each of the 4 models (ie figure rows) shown. Each file contains evolved D across the range after 500 generations of stable climate and after 1000 generations of climate change for 30 runs per model.Fig 4 (delta.D).zipFig 6 (D vs density) data and R codeData and R code needed to create Fig 6 in Hargreaves et al (2015) J Evol Biol. Two data files (one for evolved D and one for density) for each of 2 model runs, one with dispersal (dispersal distance =1 as normal) and one run without dispersal (dispersal distance =0).Fig 6 (D vs density).zipAppendix S1 data and R code for each figureData and R code needed to create figures in Appendix S1 in Hargreaves et al (2015) J Evol Biol. All figures remake Fig 3 while varying one parameter. Fig S1.1 shows murate = .005; Fig S1.2 shows avshift = .01, .05, .2; Fig. S1.3 shows K=10; Fig. S1.4 shows effect of eliminating kin selection by randomizing individuals within columns before each dispersal event. For each figure there is 1 data file per model. Each data file contains evolved D across the range after 500 generations of stable climate and after 1000 generations of climate change, for 10 runs per cost.Appendix S1.zipModel code Matlab fileCode to run the model simulations.rangeshift (for dryad).mFig 5 (extinction threshold) Matlab codeMatlab code to run the simulations necessary to determine the relationship between the speed of climate change (avshift) and probability of extinction.rangeshift_thresh (for dryad).m Dispersal ability will largely determine whether species track their climatic niches during climate change, a process especially important for populations at contracting (low-latitude/low-elevation) range limits that otherwise risk extinction. We investigate whether dispersal evolution at contracting range limits is facilitated by two processes that potentially enable edge populations to experience and adjust to the effects of climate deterioration before they cause extinction: (i) climate-induced fitness declines towards range limits and (ii) local adaptation to a shifting climate gradient. We simulate a species distributed continuously along a temperature gradient using a spatially explicit, individual-based model. We compare range-wide dispersal evolution during climate stability vs. directional climate change, with uniform fitness vs. fitness that declines towards range limits (RLs), and for a single climate genotype vs. multiple genotypes locally adapted to temperature. During climate stability, dispersal decreased towards RLs when fitness was uniform, but increased when fitness declined towards RLs, due to highly dispersive genotypes maintaining sink populations at RLs, increased kin selection in smaller populations, and an emergent fitness asymmetry that favoured dispersal in low-quality habitat. However, this initial dispersal advantage at low-fitness RLs did not facilitate climate tracking, as it was outweighed by an increased probability of extinction. Locally adapted genotypes benefited from staying close to their climate optima; this selected against dispersal under stable climates but for increased dispersal throughout shifting ranges, compared to cases without local adaptation. Dispersal increased at expanding RLs in most scenarios, but only increased at the range centre and contracting RLs given local adaptation to climate.

Detail of the construction of the matrices of phylogenetic distances used for the species in the two experiments.

DESY-HERA. Measurement of event shape distributions (THRUST and SPHERICITY)and the energy flow distributions of hadronic events produced diffractively in collisions of 27.5 GeV positrons with 820 GeV protons. The events are characterised by having a large rapidity gap between the recoil-proton system and the produced hadronic system. Diffractive events are defined as those with a recoil-proton of momentum & gt; 97% of the initial proton momentum. The data was collected during the 1997 running period with an integrated luminosity of 13.8 +- 0.3 pb-1. Atleast 4 stable particles in the final state were required.. Numerical values supplied by R. Wichmann. Average squared transverse momentum of particles measured in the hadron c.m. frame as a function of the Feynman XL = PL/PLMAX.

File format: NetCDFSimulated/analyzed periods: 1989-2010 (current) and 2079-2100 (future)The repository for the analysis code is attached.Entry scripts for the figures are:- figure1, 4: src/lake_effect_snow/hles_cc/plot_monthly_histograms_cc_and_domain.py- figure2(partially lake ice fraction), figure3: src/lake_effect_snow/hles_cc_validation/validate_hles_and_related_params_biases_and_obs.py- figure5: src/lake_effect_snow/hles_cc/plot_cc_2d_all_variables_for_all_periods_001.py- figure6: src/lake_effect_snow/hles_cc/hles_tt_and_pr_correlations_mean_ice_fraction.py- cold_air.m for part of Fig. 2 and hles_intensity.m for Fig. 7 The dataset contains Heavy Lake Effect Snowfall (HLES) and related parameters from GEM outputs (RCP8.5, 10 km horizontal resolution, Laurentian Great Lakes region, driven by CanESM2 at the boundaries) and observation datasets. Observation data included are: interpolated to the model grid Daymet 2m air temperature and total precipitation, CIS-NIC ice concentration observations, and REA-Interim near-surface winds.

Additional file 1. Geographical, genetic, and kinetic parameter information for hybrids.