An Algorithmic Framework for Fairness Elicitation

We consider settings in which the right notion of fairness is not captured by simple mathematical definitions (such as equality of error rates across groups), but might be more complex and nuanced and thus require elicitation from individual or collective stakeholders. We introduce a framework in which pairs of individuals can be identified as requiring (approximately) equal treatment under a learned model, or requiring ordered treatment such as "applicant Alice should be at least as likely to receive a loan as applicant Bob". We provide a provably convergent and oracle efficient algorithm for learning the most accurate model subject to the elicited fairness constraints, and prove generalization bounds for both accuracy and fairness. This algorithm can also combine the elicited constraints with traditional statistical fairness notions, thus "correcting" or modifying the latter by the former. We report preliminary findings of a behavioral study of our framework using human-subject fairness constraints elicited on the COMPAS criminal recidivism dataset

Meat Intake and the Dose of Vitamin B3 - Nicotinamide:Cause of the Causes of Disease Transitions, Health Divides, and Health Futures?

Meat and vitamin B 3 – nicotinamide – intake was high during hunter-gatherer times. Intake then fell and variances increased during and after the Neolithic agricultural revolution. Health, height, and IQ deteriorated. Low dietary doses are buffered by ‘welcoming’ gut symbionts and tuberculosis that can supply nicotinamide, but this co-evolved homeostatic metagenomic strategy risks dysbioses and impaired resistance to pathogens. Vitamin B 3 deficiency may now be common among the poor billions on a low-meat diet. Disease transitions to non-communicable inflammatory disorders (but longer lives) may be driven by positive ‘meat transitions’. High doses of nicotinamide lead to reduced regulatory T cells and immune intolerance. Loss of no longer needed symbiotic ‘old friends’ compounds immunological over-reactivity to cause allergic and auto-immune diseases. Inhibition of nicotinamide adenine dinucleotide consumers and loss of methyl groups or production of toxins may cause cancers, metabolic toxicity, or neurodegeneration. An optimal dosage of vitamin B 3 could lead to better health, but such a preventive approach needs more equitable meat distribution. Some people may require personalised doses depending on genetic make-up or, temporarily, when under stress

Active learning in psychiatry education: current practices and future perspectives

Over the past few decades medical education has seen increased interest in the use of active learning formats to engage learners and promote knowledge application over knowledge acquisition. The field of psychiatry, in particular, has pioneered a host of novel active-learning paradigms. These have contributed to our understanding of the role of andragogy along the continuum of medical education, from undergraduate to continuing medical education. In an effort to frame the successes and failures of various attempts at integrating active learning into healthcare curricula, a group of educators from the A. B. Baker Section on Neurological Education from the American Academy of Neurology reviewed the state of the field in its partner field of medical neuroscience. Herein we provide a narrative review of the literature, outlining the basis for implementing active learning, the novel formats that have been used, and the lessons learned from qualitative and quantitative analysis of the research that has been done to date. While preparation time seems to present the greatest obstacle to acceptance from learners and educators, there is generally positive reception to the new educational formats. Additionally, most assessments of trainee performance have suggested non-inferiority (if not superiority); however, occasional mixed findings point to a need for better assessments of the type of learning that these new formats engender: knowledge application rather than acquisition. Moreover, this field is relatively nascent and, in order to ascertain how best to integrate active learning into psychiatry education, a framework for quantitative outcome assessments is needed going forward

Emerging SARS-CoV-2 Variants: A Review of Its Mutations, Its Implications and Vaccine Efficacy

The widespread increase in multiple severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variants is causing a significant health concern in the United States and worldwide. These variants exhibit increased transmissibility, cause more severe disease, exhibit evasive immune properties, impair neutralization by antibodies from vaccinated individuals or convalescence sera, and reinfection. The Centers for Disease Control and Prevention (CDC) has classified SARS-CoV-2 variants into variants of interest, variants of concern, and variants of high consequence. Currently, four variants of concern (B.1.1.7, B.1.351, P.1, and B.1.617.2) and several variants of interests (B.1.526, B.1.525, and P.2) are characterized and are essential for close monitoring. In this review, we discuss the different SARS-CoV-2 variants, emphasizing variants of concern circulating the world and highlight the various mutations and how these mutations affect the characteristics of the virus. In addition, we discuss the most common vaccines and the various studies concerning the efficacy of these vaccines against different variants of concern

Spectroscopic Differentiation and Chromatographic Separation of Regioisomeric Indole Aldehydes: Synthetic Cannabinoids Precursors

The compounds in this study are the six regioisomeric 2-, 3-, 4-, 5-, 6- and 7-formyl indoles and the corresponding six regioisomeric N-n-pentylindole aldehydes. These compounds can serve as precursor chemicals and synthetic intermediates for a number of synthetic cannabinoid drugs. These two sets (the six regioisomeric indole aldehydes as well as the six regioisomeric pentylindole aldehydes) each have identical elemental compositions and differ in the position of attachment of the aldehyde group on the indole ring. The electron ionization mass spectra for the indole aldehydes were essentially identical. However, the vapor phase infrared spectra showed differences in the absorption frequencies for the NH and carbonyl groups based on intramolecular interactions. The associated NH absorption band occurs as low as 3467 cm−1 while the free band is as high as 3517 cm−1. The aldehyde carbonyl band for the indole aldehydes varies from 1713 cm−1 to 1686 cm−1. Substitution of the aldehyde group on the pyrrole ring for the N-n-pentylindole aldehydes yields lower carbonyl absorption bands. The EI mass spectra for the pentylindole aldehydes are identical with little information for differentiation among these six regioisomeric compounds. The six compounds were separated on a capillary column using gas chromatography and the elution order appears to be related to the steric crowding of the indole ring substituents. Graphical abstrac

Habitat structure mediates vulnerability to climate change through its effects on thermoregulatory behavior

Tropical ectotherms are thought to be especially vulnerable to climate change because they are thermal specialists, having evolved in aseasonal thermal environments. However, even within the tropics, habitat structure can influence opportunities for behavioral thermoregulation. Open (and edge) habitats likely promote more effective thermoregulation due to the high spatial heterogeneity of the thermal landscape, while forests are thermally homogenous and may constrain opportunities for behavioral buffering of environmental temperatures. Nevertheless, the ways in which behavior and physiology interact at local scales to influence the response to climate change are rarely investigated. We examined the thermal ecology and physiology of two lizard species that occupy distinct environments in the tropics. The brown anole lizard (Anolis sagrei) lives along forest edges in The Bahamas, whereas the Panamanian slender anole (Anolis apletophallus) lives under the canopy of mature forests in Panama. We combined detailed estimates of environmental variation, thermoregulatory behavior, and physiology to model the vulnerability of each of these species. Our projections suggest that forest-dwelling slender anoles will experience severely reduced locomotor performance, activity time, and energy budgets as the climate warms over the coming century. Conversely, the forest-edge dwelling brown anoles may use behavioral compensation in the face of warming, maintaining population viability for many decades. Our results indicate that local habitat variation, through its effects on behavior and physiology, is a major determinant of vulnerability to climate change. When attempting to predict the impacts of climate change on a given population, broad-scale characteristics such as latitude may have limited predictive power.This Neel_Anole_Biotropica_readme.txt file was generated on 2021-03-29 by Lauren Neel GENERAL INFORMATION 1. Title of manuscript: Habitat structure mediates vulnerability to climate change through its effects on thermoregulatory behavior 2. Author Information A. Lead Author Contact Information Name: Lauren Neel Institution: Arizona State University Address: Tempe, AZ, USA Email: [email protected] B. Associate or Co-investigator Contact Information Name: Mike Logan Institution: University Nevada - Reno Address: Reno, NV, USA Email: [email protected] 3. Date of data collection (single date, range, approximate date): Please see Table S1 in the manuscript for this detailed information. 4. Geographic location of data collection: 1. Great Exuma, The Bahamas 2. Gamboa, Panama 5. Information about funding sources that supported the collection of the data: Our methods were approved by the Smithsonian Tropical Research Institute Institutional Animal Care and Use Committee (protocol 2017-0308-2020-A5), Harvard University Institutional Animal Care and Use Committee (protocol 26-11), MiAmbiente research permit SE/A-37-19, and the BEST commission research permit. Funding for this project was provided by a USAID Global Development Research Fellowship awarded to L. Neel, a STRI-ASU Collaborative Initiative Research Grant awarded to L. Neel and M. Logan, a Smithsonian Institution Biodiversity Genomics Postdoctoral Fellowship awarded to M. Logan, a Smithsonian Tropical Research Institute Earl S. Tupper Postdoctoral Fellowship awarded to M. Logan, a NERC studentship (NE/L002485/1) awarded to D. Nicholson, a Smithsonian Pre-Doctoral Fellowship awarded to D. Nicholson, a STRI Short-Term Fellowship awarded to A. Chung, Georgia Southern University Graduate Student Organization Professional Development grants awarded to A. Chung and J. Curlis, American Museum of Natural History Theodore Roosevelt grants awarded to A. Chung and J. Curlis, and a John Templeton Foundation grant awarded to J. Losos (the opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation). The authors thank Lil Camacho, Adriana Bilgray, Paola Gomez, and Raineldo Urriola for administrative support at STRI. SHARING/ACCESS INFORMATION 1. Licenses/restrictions placed on the data: n/a 2. Links to publications that cite or use the data: n/a 3. Links to other publicly accessible locations of the data: n/a 4. Links/relationships to ancillary data sets: n/a 5. Was data derived from another source? no DATA & FILE OVERVIEW 1. File List: "2017-2018 Panama and Bahamas CTmin UVT.csv" - file containing thermal tolerance data "activity_time_model_panama.xlsx" - file containing modeled body temperature data for Panama, generated using regression equation from present day body temperature (Tb) and operative temperature (Te) data. Body temps modeled for a 3C warming event occurring over 100 years. Activity is assumed to be possible whenever Tb is below upper voluntary temperatures. "activity_time_model_bahamas.xlsx" - file containing modeled body temperature data for The Bahamas, generated using regression equation from present day body temperature (Tb) and operative temperature (Te) data. Body temps modeled for a 3C warming event occurring over 100 years. Activity is assumed to be possible whenever Tb is below upper voluntary temperatures. "Anole Mainland Tb.csv" - field active body temperature data "combined mainland data sheet.csv" - file containing Tb and Te when captured, thermal tolerance, field data, mass, svl "combined mainland Tpref.csv" - file containing more detailed thermal preference data "metabolism.csv" - file containing lizard sex, mass, oxygen consumed, trial temperature, and calculated Q10 values "MR modeling panama.xlsx" - file containing modeled body temperature data and oxygen consumption for 3C warming event, assuming current relationship between metabolism and temperature in Panama "MR modeling bahamas.xlsx" - file containing modeled body temperature data and oxygen consumption for 3C warming event, assuming current relationship between metabolism and temperature in The Bahamas "Sprint projection panama.xlsx" - file containing modeled body temperature data and sprint speeds for 3C warming event, assuming current relationship between locomotor performance and temperature in Panama "Sprint projection bahamas.xlsx" - file containing modeled body temperature data and sprint speeds for 3C warming event, assuming current relationship between locomotor performance and temperature in The Bahamas "sprint_thermal_sensitivity.csv" - file containing thermal sensitivity of locomotor performance data "TbTe_andmass.xlsx" - file containing lizard mass, Tb when caught, and average Te when caught. Regression equation from Tb plotted as function of Te retained to incorporate thermoregulation when modeling body temperatures under 3C warming scenario. "Hourly_Te.xlsx" - file containing summary hourly operative environmental data "daily_nightly_summary_Te.xlsx" - daily and nightly summary operative environmental data "monthly weather station data bahamas.xlsx" - monthly weather station air temperature data in the Bahamas "monthly weather station data panama.xlsx" - monthly weather station air temperature data in Panama 2. Relationship between files, if important: n/a 3. Additional related data collected that was not included in the current data package: no 4. Are there multiple versions of the dataset? no A. If yes, name of file(s) that was updated: i. Why was the file updated? ii. When was the file updated? METHODOLOGICAL INFORMATION 1. Description of methods used for collection/generation of data: Please read the full materials and methods section of our manuscript for this detailed information. 2. Methods for processing the data: Please read the full materials and methods section of our manuscript for this detailed information. 3. Instrument- or software-specific information needed to interpret the data: Model comparisons were conducted with the MUMIN package in R version 3.6.2 (R Core Team 2020). 4. Standards and calibration information, if appropriate: n/a 5. Environmental/experimental conditions: n/a 6. Describe any quality-assurance procedures performed on the data: n/a 7. People involved with sample collection, processing, analysis and/or submission: all authors were involved with some combination of these items. DATA-SPECIFIC INFORMATION FOR: [2017-2018 Panama and Bahamas CTmin UVT.csv] 1. Number of variables: 4 2. Number of cases/rows: 1909 3. Variable List: Country - population of individual sampled Year - year data collected Ctmin - critical thermal minima (C) UVT - upper voluntary temperature (C) 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [activity_time_model_panama.xlsx] 1. Number of variables: 4 2. Number of cases/rows: 82 3. Variable List: Hours active - total number annual hours where predicted Tb was within preferred thermal range (CTmin - UVT) Year - year data modeled Daily hours - total number daily hours where predicted Tb was within preferred thermal range (CTmin - UVT) % annual hours - percentage of annual hours where predicted Tb within preferred thermal range 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [activity_time_model_bahamas.xlsx] 1. Number of variables: 4 2. Number of cases/rows: 82 3. Variable List: Hours active - total number annual hours where predicted Tb was within preferred thermal range (CTmin - UVT) Year - year data modeled Daily hours - total number daily hours where predicted Tb was within preferred thermal range (CTmin - UVT) % annual hours - percentage of annual hours where predicted Tb within preferred thermal range 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [Anole Mainland Tb.csv] 1. Number of variables: 4 2. Number of cases/rows: 1426 3. Variable List: Lizard ID - Lizard identifier Date capture - date sampled Capture_site - population Tb - field active body temperature (C) 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [combined mainland data sheet.csv] 1. Number of variables: 11 2. Number of cases/rows: 2013 3. Variable List: Lizard ID - Lizard identifier Country - population of individual sampled Year - year data collected Timecaptured - time animal captured Tb - field active body temp (C) Te - average operative temperature (C) at time lizard caught CTmin - lower thermal limit (C) UVT - upper voluntary thermal limit (C) Sex - sex m/f Mass_g - mass (g) SVL_mm - Snout vent length (mm) 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [combined mainland Tpref.csv] 1. Number of variables: 17 2. Number of cases/rows: 120 3. Variable List: Country - population of individual sampled Trial date - date of trial Time trial began - trial start time Lizard ID - Lizard identifier Mass - mass (g) SVL_mm - Snout vent length (mm) Sex - sex m/f Tpref_mean - mean thermal preference (C) Tpref_median - median thermal preference (C) Tpref_min - min thermal preference (C) Tpref_max - max thermal preference (C) Tpref_range - range of thermal preference (C) Tpref_StdDev - standard deviation of preferred temps (C) Tpref_25thq - 25th quartile of thermal preference (C) Tpref_75thq - 25th quartile of thermal preference (C) IQR - interquartile range (C) TC # - thermocouple number 4. Missing data codes: N/a - means data type were not collected from that individual. ? - means data weren't collected for unknown reasons. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [metabolism.csv] 1. Number of variables: 9 2. Number of cases/rows: 145 3. Variable List: Lizard - Lizard identifier Country - population of individual sampled Year - year data collected Sex - sex m/f Mass - mass (g) Total o2 consumed per hourly - total hourly oxygen consumed Temp - trial temperature (C) Q10 - calculated Q10 value LH - low/high temp.. used to code in stats 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [MR modeling bahamas.xlsx] 1. Number of variables: 7 2. Number of cases/rows: 82 3. Variable List: Te - average annual operative temperature incorporating 3C uniform warming scenario occurring through century's end Year - year Predicted Tb - predicted body temperature (C) given operative temperature under warming scenario, adjusted to incorporate thermoregulation (via function from Tb Te regression) Predicted VO2 - predicted oxygen consumption (ml O2/ gram animal / time ) using current relationship between metabolism and temperature EE - annual energy expenditure (kilocalorie/hour) EE - annual energy expenditure (kilojoule/hour) EE annual - annual energy expenditure assuming animal is active 12 hr/day 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [MR modeling panama.xlsx] 1. Number of variables: 7 2. Number of cases/rows: 82 3. Variable List: Te - average annual operative temperature incorporating 3C uniform warming scenario occurring through century's end Year - year Predicted Tb - predicted body temperature (C) given operative temperature under warming scenario, adjusted to incorporate thermoregulation (via function from Tb Te regression) Predicted VO2 - predicted oxygen consumption (ml O2/ gram animal / time ) using current relationship between metabolism and temperature EE - annual energy expenditure (kilocalorie/hour) EE - annual energy expenditure (kilojoule/hour) EE annual - annual energy expenditure assuming animal is active 12 hr/day 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [Sprint projection bahamas.xlsx] 1. Number of variables: 3 2. Number of cases/rows: 82 3. Variable List: Year - year Predicted Tb - predicted body temperature (C) given operative temperature under warming scenario, adjusted to incorporate thermoregulation (via function from Tb Te regression) Predicted relative performance - predicted relative locomotor performance (meter/second) using current relationship between locomotion and temperature 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [Sprint projection panama.xlsx] 1. Number of variables: 3 2. Number of cases/rows: 82 3. Variable List: Year - year Predicted Tb - predicted body temperature (C) given operative temperature under warming scenario, adjusted to incorporate thermoregulation (via function from Tb Te regression) Predicted relative performance - predicted relative locomotor performance (meter/second) using current relationship between locomotion and temperature 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [Sprint_thermal_sensitivity.xlsx] 1. Number of variables: 6 2. Number of cases/rows: 65 3. Variable List: Lizard # - Lizard identifier Topt - thermal optima for locomotor performance (C) Pmax - maximum locomotor performance (m/s) Mass - mass (g) Country - population of individual sampled 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [TbTe_andmass.csv] 1. Number of variables: 8 2. Number of cases/rows: 692 3. Variable List: Lizard ID - Lizard identifier Time - time lizard sampled Date - date lizard sampled Mass - mass (g) of lizard Tb - field active body temperature (C) Te - operative environmental temperature (C) at time lizard caught #OTMS averaged - the number of operative temperature models that went in to averaged Te value Country - population of individual sampled 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [Hourly_Te.xlsx] 1. Number of variables: 5 2. Number of cases/rows: 25 3. Variable List: Site - location Hour - hour data collected Temp median - median operative temperature (C) Se - standard error of operative temperature 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [daily_nightly_summary_Te.xlsx] 1. Number of variables: 3 2. Number of cases/rows: 178 3. Variable List: Te - operative temperature (C) Category - min/max/mean Country - country sampled 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [monthly weather station data bahamas.xlsx] 1. Number of variables: 3 2. Number of cases/rows: 178 3. Variable List: Date - date temp taken Temp - weather station air temp (C) Month - month data sampled 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/a DATA-SPECIFIC INFORMATION FOR: [monthly weather station data panama.xlsx] 1. Number of variables: 3 2. Number of cases/rows: 178 3. Variable List: Date - date temp taken Temp - weather station air temp (C) Month - month data sampled 4. Missing data codes: N/a - means data type were not collected from that individual. 5. Specialized formats or other abbreviations used: N/aPlease see the methods section of the published manuscrip

Climate anomalies and competition reduce establishment success during island colonization

Abstract: Understanding the factors that facilitate or constrain establishment of populations in novel environments is crucial for conservation biology and the study of adaptive radiation. Important questions include: (1) Does the timing of colonization relative to stochastic events, such as climatic perturbations, impact the probability of successful establishment? (2) To what extent does community context (e.g., the presence of competitors) change the probability of establishment? (3) How do sources of intrapopulation variance, such as sex differences, affect success at an individual level during the process of establishment? Answers to these questions are rarely pursued in a field‐experimental context or on the same time scales (months to years) as the processes of colonization and establishment. We introduced slender anole lizards (Anolis apletophallus) to eight islands in the Panama Canal and tracked them over multiple generations to investigate the factors that mediate establishment success. All islands were warmer than the mainland (ancestral) environment, and some islands had a native competitor. We transplanted half of these populations only 4 months before the onset of a severe regional drought and the other half 2 years (two generations) before the drought. We found that successful establishment depended on both the intensity of interspecific competition and the timing of colonization relative to the drought. The islands that were colonized shortly before the drought went functionally extinct by the second generation, and regardless of time before the drought, the populations on islands with interspecific competition declined continuously over the study period. Furthermore, the effect of the competitor interacted with sex, with males suffering, and females benefitting, from the presence of a native competitor. Our results reveal that community context and the timing of colonization relative to climactic events can combine to determine establishment success and that these factors can generate opposite effects on males and females