Brief for Respondents. Tyson Foods, Inc. v. Bouaphakeo, 136 S.Ct. 1036 (2016) (No. 14-1146), 2015 WL 5634431

QUESTIONS PRESENTED 1. Whether, in this class and collective action for wage-and-hour violations arising out of an employer\u27s failure properly to compensate employees for time spent donning and doffing protective equipment and walking between sites where work was performed, the district court abused its discretion in granting certification where plaintiffs proceeded to prove the amount of work they did using individual timesheet evidence and representative proof concerning donning, doffing, and walking times in accordance with Anderson v. Mt. Clemens Pottery Co., 328 U.S. 680 (1946). 2. Whether a class or collective action may be certified when it contains members who may not have been injured

Hash Functions for Episodic Recognition and Retrieval

Episodic memory systems for artificially intelligent agents must cope with an ever-growing episodic memory store. This paper presents an approach for minimizing the size of the store by using specialized hash functions to convert each memory into a relatively short binary code. A set of desiderata for such hash functions are presented including locale sensitivity and reversibility. The paper then introduces multiple approaches for such functions and compares their effectiveness

Linkage Quality Assessment for Anonymously linked Administrative Data.

Introduction Linked datasets are important resources for research, but linkage errors can lead to incorrect results. For data security and privacy concerns, when linkage of personal identifiers is performed anonymously, it is difficult to assess the quality of the linked dataset. We describe the method used to perform linkage quality. Objectives and Approach We explored how to check the quality of linkages while preserving the privacy of individuals. We also adopted an approach that minimized time and burden on data providers involved in physical verification using randomly-generated appropriate sample sizes. To validate these linkages, data providers were given random samples of 50 unique records from both linked and unlinked individuals across two other Government programs. Data providers were asked to look at the records associated with those individuals in their original datasets. Three types of linkage results were validated: cross-program linkages, cross-program non-linkages, and within-program linkages. Proportions of false-matches and missed-matches were estimated. Results Twenty data providers checked their samples with two other programs which gave us a sample of 2000 individuals. The linkage process, based on anonymized personal identifiers, resulted in high true positive and high true negative rates. Agreement between human judges and the linkage software was strong. Results of this exercise and other linkage validation examinations provided confidence in the accuracy of the linkage process. With false matches occurring approximately only 3% of the time and virtually no missed-matches occurring, no adjustments were deemed necessary. Although linkage rates were reassuring, the sample sizes used for comparison were small, so it is expected that there would be significant variation associated with this 3% estimate; caution is advised in its use. Conclusion/Implications Proportions of false-matches and missed-matches determine linkage quality which is the base for research when linkages are performed anonymously. A low proportion of false-matches and an absence of missed-matches was an indication of robust linkages

Using Ai-Generated Suggestions From ChatGPT to Optimize Clinical Decision Support

OBJECTIVE: To determine if ChatGPT can generate useful suggestions for improving clinical decision support (CDS) logic and to assess noninferiority compared to human-generated suggestions. METHODS: We supplied summaries of CDS logic to ChatGPT, an artificial intelligence (AI) tool for question answering that uses a large language model, and asked it to generate suggestions. We asked human clinician reviewers to review the AI-generated suggestions as well as human-generated suggestions for improving the same CDS alerts, and rate the suggestions for their usefulness, acceptance, relevance, understanding, workflow, bias, inversion, and redundancy. RESULTS: Five clinicians analyzed 36 AI-generated suggestions and 29 human-generated suggestions for 7 alerts. Of the 20 suggestions that scored highest in the survey, 9 were generated by ChatGPT. The suggestions generated by AI were found to offer unique perspectives and were evaluated as highly understandable and relevant, with moderate usefulness, low acceptance, bias, inversion, redundancy. CONCLUSION: AI-generated suggestions could be an important complementary part of optimizing CDS alerts, can identify potential improvements to alert logic and support their implementation, and may even be able to assist experts in formulating their own suggestions for CDS improvement. ChatGPT shows great potential for using large language models and reinforcement learning from human feedback to improve CDS alert logic and potentially other medical areas involving complex, clinical logic, a key step in the development of an advanced learning health system

Cloud System Evolution in the Trades (CSET): Following the Evolution of Boundary Layer Cloud Systems with the NSFNCAR GV

The Cloud System Evolution in the Trades (CSET) study was designed to describe and explain the evolution of the boundary layer aerosol, cloud, and thermodynamic structures along trajectories within the North Pacific trade winds. The study centered on seven round trips of the National Science FoundationNational Center for Atmospheric Research (NSFNCAR) Gulfstream V (GV) between Sacramento, California, and Kona, Hawaii, between 7 July and 9 August 2015. The CSET observing strategy was to sample aerosol, cloud, and boundary layer properties upwind from the transition zone over the North Pacific and to resample these areas two days later. Global Forecast System forecast trajectories were used to plan the outbound flight to Hawaii with updated forecast trajectories setting the return flight plan two days later. Two key elements of the CSET observing system were the newly developed High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Cloud Radar (HCR) and the high-spectral-resolution lidar (HSRL). Together they provided unprecedented characterizations of aerosol, cloud, and precipitation structures that were combined with in situ measurements of aerosol, cloud, precipitation, and turbulence properties. The cloud systems sampled included solid stratocumulus infused with smoke from Canadian wildfires, mesoscale cloudprecipitation complexes, and patches of shallow cumuli in very clean environments. Ultraclean layers observed frequently near the top of the boundary layer were often associated with shallow, optically thin, layered veil clouds. The extensive aerosol, cloud, drizzle, and boundary layer sampling made over open areas of the northeast Pacific along 2-day trajectories during CSET will be an invaluable resource for modeling studies of boundary layer cloud system evolution and its governing physical processes

Modification by N-acetyltransferase 1 genotype on the association between dietary heterocyclic amines and colon cancer in a multiethnic study

Colorectal cancer incidence is greater among African Americans, compared to whites in the U.S., and may be due in part to differences in diet, genetic variation at metabolic loci, and/or the joint effect of diet and genetic susceptibility. We examined whether our previously reported associations between meat-derived heterocyclic amine (HCA) intake and colon cancer were modified by N-acetyltransferase 1 (NAT1) or 2 (NAT2) genotypes and whether there were differences by race

Project ACHIEVE – Using Implementation Research to Guide the Evaluation of Transitional Care Effectiveness

Background: Poorly managed hospital discharges and care transitions between health care facilities can cause poor outcomes for both patients and their caregivers. Unfortunately, the usual approach to health care delivery does not support continuity and coordination across the settings of hospital, doctors’ offices, home or nursing homes. Though complex efforts with multiple components can improve patient outcomes and reduce 30-day readmissions, research has not identified which components are necessary. Also we do not know how delivery of core components may need to be adjusted based on patient, caregiver, setting or characteristics of the community, or how system redesign can be accelerated. Methods/design: Project ACHIEVE focuses on diverse Medicare populations such as individuals with multiple chronic diseases, patients with low health literacy/numeracy and limited English proficiency, racial and ethnic minority groups, low-income groups, residents of rural areas, and individuals with disabilities. During the first phase, we will use focus groups to identify the transitional care outcomes and components that matter most to patients and caregivers to inform development and validation of assessment instruments. During the second phase, we will evaluate the comparative effectiveness of multi-component care transitions programs occurring across the U.S. Using a mixed-methods approach for this evaluation, we will study historical (retrospective) and current and future (prospective) groups of patients, caregivers and providers using site visits, surveys, and clinical and claims data. In this natural experiment observational study, we use a fractional factorial study design to specify comparators and estimate the individual and combined effects of key transitional care components. Discussion: Our study will determine which evidence-based transitional care components and/or clusters most effectively produce patient and caregiver desired outcomes overall and among diverse patient and caregiver populations in different healthcare settings. Using the results, we will develop concrete, actionable recommendations regarding how best to implement these strategies. Finally, this work will provide tools for hospitals, community-based organizations, patients, caregivers, clinicians and other stakeholders to help them make informed decisions about which strategies are most effective and how best to implement them in their communities. Trial registration: Registered as NCT02354482 on clinicaltrials.gov on 1/29/201

Genetic versus Rearing-Environment Effects on Phenotype: Hatchery and Natural Rearing Effects on Hatchery- and Wild-Born Coho Salmon

With the current trends in climate and fisheries, well-designed mitigative strategies for conserving fish stocks may become increasingly necessary. The poor post-release survival of hatchery-reared Pacific salmon indicates that salmon enhancement programs require assessment. The objective of this study was to determine the relative roles that genotype and rearing environment play in the phenotypic expression of young salmon, including their survival, growth, physiology, swimming endurance, predator avoidance and migratory behaviour. Wild- and hatchery-born coho salmon adults (Oncorhynchus kisutch) returning to the Chehalis River in British Columbia, Canada, were crossed to create pure hatchery, pure wild, and hybrid offspring. A proportion of the progeny from each cross was reared in a traditional hatchery environment, whereas the remaining fry were reared naturally in a contained side channel. The resulting phenotypic differences between replicates, between rearing environments, and between cross types were compared. While there were few phenotypic differences noted between genetic groups reared in the same habitat, rearing environment played a significant role in smolt size, survival, swimming endurance, predator avoidance and migratory behaviour. The lack of any observed genetic differences between wild- and hatchery-born salmon may be due to the long-term mixing of these genotypes from hatchery introgression into wild populations, or conversely, due to strong selection in nature—capable of maintaining highly fit genotypes whether or not fish have experienced part of their life history under cultured conditions

Impact of Acute Intermittent Exercise on Natural Killer Cells in Breast Cancer Survivors

BACKGROUND: Current research examining the effect of exercise on immune responses in cancer survivors is limited. OBJECTIVE: The aim of this pilot study was to examine the effect of 1 bout of intermittent exercise on natural killer (NK) cell numbers in breast cancer survivors. METHODS: A total of 9 women with stage I to III invasive breast cancer who were 3 to 6 months posttreatment and 9 sedentary women without a history of cancer completed 10 three-minute intervals of aerobic exercise on the cycle ergometer at 60% of VO2peak (peak oxygen uptake). Whole blood samples were taken pre-exercise, immediately postexercise, and at 2 hours and 24 hours postexercise. NK cell counts were assessed using flow cytometry. RESULTS: In both groups, NK cell counts significantly increased immediately postexercise compared with pre-exercise (P = .004-.008) and returned to near pre-exercise levels during recovery (P = .129-.547). Absolute NK cell counts were significantly lower in breast cancer survivors immediately postexercise when compared with controls (P = .046). CONCLUSIONS: The breast cancer survivor group exhibited NK cell responses to 30 minutes of moderate-intensity intermittent aerobic exercise that were comparable with that in the group of physically similar women without a history of cancer. Immune changes related to cancer treatments may be related to the lower absolute NK cell counts observed in the breast cancer survivor group. Although the results of this study are preliminary in nature, they suggest that this type of exercise does not disrupt this aspect of innate immunity in recent breast cancer survivors, thereby supporting current exercise recommendations for this population