Designing a Heat Sink for Lithium-ion Battery Packs in Electric Vehicles

This report addresses the concepts and implementation of fluid cooled heat sink designs for an electric or hybrid vehicle battery. To determine the battery’s temperature and heat flux profile, testing was performed by measuring these values at multiple locations on a lithium-ion pouch battery using heat flux sensors and thermocouples during the charge and discharge cycles of the battery. Once the data was collected and analyzed, trendlines were fit to the heat flux data then used to create equations for the heat flux profile during the discharging stage. Each equation represented a specific region on the battery geometry. Four heat sink designs were modeled in COMSOL Multiphysics to optimize cooling. The third model concept (Model 3) was chosen as the best model because it cooled the battery to the lowest temperature with the lowest pressure drop

Tracking icebergs with time-lapse photography and sparse optical flow, LeConte Bay, Alaska, 2016–2017

We present a workflow to track icebergs in proglacial fjords using oblique time-lapse photos and the Lucas-Kanade optical flow algorithm. We employ the workflow at LeConte Bay, Alaska, where we ran five time-lapse cameras between April 2016 and September 2017, capturing more than 400 000 photos at frame rates of 0.5–4.0 min−1. Hourly to daily average velocity fields in map coordinates illustrate dynamic currents in the bay, with dominant downfjord velocities (exceeding 0.5 m s−1 intermittently) and several eddies. Comparisons with simultaneous Acoustic Doppler Current Profiler (ADCP) measurements yield best agreement for the uppermost ADCP levels (∼ 12 m and above), in line with prevalent small icebergs that trace near-surface currents. Tracking results from multiple cameras compare favorably, although cameras with lower frame rates (0.5 min−1) tend to underestimate high flow speeds. Tests to determine requisite temporal and spatial image resolution confirm the importance of high image frame rates, while spatial resolution is of secondary importance. Application of our procedure to other fjords will be successful if iceberg concentrations are high enough and if the camera frame rates are sufficiently rapid (at least 1 min−1 for conditions similar to LeConte Bay).This work was funded by the U.S. National Science Foundation (OPP-1503910, OPP-1504288, OPP-1504521 and OPP-1504191).Ye

Coding of sexual assault by emergency physicians: A nationally representative study

INTRODUCTION: Sexual assault is a public health problem that affects many Americans and has multiple long-lasting effects on victims. Medical evaluation after sexual assault frequently occurs in the emergency department, and documentation of the visit plays a significant role in decisions regarding prosecution and outcomes of legal cases against perpetrators. The American College of Emergency Physicians recommends coding such visits as sexual assault rather than adding modifiers such as alleged. METHODS: This study reviews factors associated with coding of visits as sexual assault compared to suspected sexual assault using the 2016 Nationwide Emergency Department Sample. RESULTS: Younger age, female gender, a larger number of procedure codes, urban hospital location, and lack of concurrent alcohol use are associated with coding for confirmed sexual assault. CONCLUSION: Implications of this coding are discussed

Cyberbullying and Sleep Disturbance Among Early Adolescents in the U.S.

ObjectiveTo determine the association between cyberbullying (victimization and perpetration) and sleep disturbance among a demographically diverse sample of 10-14-year-old early adolescents.MethodsWe analyzed cross-sectional data from the Adolescent Brain Cognitive Development (ABCD) Study (Year 2, 2018-2020) of early adolescents (10-14 years) in the US. Modified Poisson regression analyses examined the association between cyberbullying and self-reported and caregiver-reported sleep disturbance measures.ResultsIn a sample of 9,443 adolescents (mean age 12.0 years, 47.9% female, 47.8% white), 5.1% reported cyberbullying victimization, and 0.5% reported cyberbullying perpetration in the past 12 months. Cyberbullying victimization in the past 12 months was associated with adolescent-reported trouble falling/staying asleep (risk ratio [RR] 1.87, 95% confidence interval [CI] 1.57, 2.21) and caregiver-reported overall sleep disturbance of the adolescent (RR: 1.16 95% CI 1.00, 1.33), in models adjusting for sociodemographic factors and screen time. Cyberbullying perpetration in the past 12 months was associated with trouble falling/staying asleep (RR 1.95, 95% CI 1.21, 3.15) and caregiver-reported overall sleep disturbance of the adolescent (RR: 1.49, 95% CI 1.00, 2.22).ConclusionsCyberbullying victimization and perpetration are associated with sleep disturbance in early adolescence. Digital media education and counseling for adolescents, parents, teachers, and clinicians could focus on guidance to prevent cyberbullying and support healthy sleep behavior for early adolescents

Bedtime screen use behaviors and sleep outcomes: Findings from the Adolescent Brain Cognitive Development (ABCD) Study

ObjectivesTo determine associations between bedtime screen time behaviors and sleep outcomes in a national study of early adolescents.MethodsWe analyzed cross-sectional data from 10,280 early adolescents aged 10-14 (48.8% female) in the Adolescent Brain Cognitive Development Study (Year 2, 2018-2020). Regression analyses examined the association between self-reported bedtime screen use and self- and caregiver-reported sleep measures, including sleep disturbance symptoms, controlling for sex, race/ethnicity, household income, parent education, depression, data collection period (pre- vs. during COVID-19 pandemic), and study site.ResultsOverall, 16% of adolescents had at least some trouble falling or staying asleep in the past 2 weeks and 28% had overall sleep disturbance, based on caregiver reports. Adolescents who had a television or an Internet-connected electronic device in the bedroom had a greater risk of having trouble falling or staying asleep (adjusted risk ratio 1.27, 95% CI 1.12-1.44) and overall sleep disturbance (adjusted risk ratio 1.15, 95% CI 1.06-1.25). Adolescents who left their phone ringer activated overnight had more trouble falling/staying asleep and greater overall sleep disturbance compared to those who turned off their cell phones at bedtime. Streaming movies, playing video games, listening to music, talking/texting on the phone, and using social media or chat rooms were all associated with trouble falling/staying asleep and sleep disturbance.ConclusionsSeveral bedtime screen use behaviors are associated with sleep disturbances in early adolescents. The study's findings can inform guidance for specific bedtime screen behaviors among early adolescents

The Association Between Adverse Childhood Experiences (ACEs), Bullying Victimization, and Internalizing and Externalizing Problems Among Early Adolescents: Examining Cumulative and Interactive Associations

Both adverse childhood experiences (ACEs) and bullying victimization are linked with mental health problems in adolescents. However, little is known about the overlap between the two factors and how this impacts adolescent mental health problems (i.e., internalizing and externalizing problems). The current study analyzed data from 8,085 participants (47.7% female; 44.1% racial/ethnic minority) in the Adolescent Brain Cognitive Development (ABCD) study, baseline (2016–2018, ages 9–10 years) to Year 2. Regression analyses were used to estimate associations between ACEs, bullying victimization and mental health problems, respectively, adjusting for sex, race/ethnicity, country of birth, household income, parental education, and study site. The findings showed that both ACEs and bullying victimization were independently associated with higher internalizing and higher externalizing problems. However, no significant interaction was found between ACEs and bullying victimization. Overall, the results align with the cumulative risk model of adversity, linking cumulative ACEs and bullying victimization to internalizing and externalizing problems in early adolescents

Screen time, problematic screen use, and eating disorder symptoms among early adolescents: findings from the Adolescent Brain Cognitive Development (ABCD) Study

PurposeEmerging research evidence suggests positive relationships between higher screen time and eating disorders. However, few studies have examined the prospective associations between screen use and eating disorder symptoms in early adolescents and how problematic screen use may contribute to symptom development.MethodsWe analyzed prospective cohort data from the Adolescent Brain Cognitive Development (ABCD) Study (N = 10,246, 2016-2020, ages 9-14). Logistic regression analyses were used to estimate the longitudinal associations between baseline self-reported screen time and eating disorder symptoms in year two. Logistic regression analyses were also used to estimate cross-sectional associations between problematic screen use in year two (either problematic social media or mobile phone use) and eating disorder symptoms in year two. Eating disorder symptoms based on the Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS-5) included fear of weight gain, self-worth tied to weight, engaging in compensatory behaviors, binge eating, and distress with binge eating.ResultsEach additional hour of total screen time and social media use was associated with higher odds of fear of weight gain, self-worth tied to weight, compensatory behaviors to prevent weight gain, binge eating, and distress with binge eating two years later (odds ratio [OR] 1.05-1.55). Both problematic social media and mobile phone use were associated with higher odds of all eating disorder symptoms (OR 1.26-1.82).ConclusionsFindings suggest greater total screen time, social media use, and problematic screen use are associated with more eating disorder symptoms in early adolescence. Clinicians should consider assessing for problem screen use and, when high, screen for disordered eating.Level of evidenceLevel III: Evidence obtained from well-designed cohort or case-control analytic studies

Assessing longitudinal housing status using Electronic Health Record data: a comparison of natural language processing, structured data, and patient-reported history

IntroductionMeasuring long-term housing outcomes is important for evaluating the impacts of services for individuals with homeless experience. However, assessing long-term housing status using traditional methods is challenging. The Veterans Affairs (VA) Electronic Health Record (EHR) provides detailed data for a large population of patients with homeless experiences and contains several indicators of housing instability, including structured data elements (e.g., diagnosis codes) and free-text clinical narratives. However, the validity of each of these data elements for measuring housing stability over time is not well-studied.MethodsWe compared VA EHR indicators of housing instability, including information extracted from clinical notes using natural language processing (NLP), with patient-reported housing outcomes in a cohort of homeless-experienced Veterans.ResultsNLP achieved higher sensitivity and specificity than standard diagnosis codes for detecting episodes of unstable housing. Other structured data elements in the VA EHR showed promising performance, particularly when combined with NLP.DiscussionEvaluation efforts and research studies assessing longitudinal housing outcomes should incorporate multiple data sources of documentation to achieve optimal performance

Comprehensive Evaluation of the 5XFAD Mouse Model for Preclinical Testing Applications: A MODEL-AD Study.

The ability to investigate therapeutic interventions in animal models of neurodegenerative diseases depends on extensive characterization of the model(s) being used. There are numerous models that have been generated to study Alzheimer\u27s disease (AD) and the underlying pathogenesis of the disease. While transgenic models have been instrumental in understanding AD mechanisms and risk factors, they are limited in the degree of characteristics displayed in comparison with AD in humans, and the full spectrum of AD effects has yet to be recapitulated in a single mouse model. The Model Organism Development and Evaluation for Late-Onset Alzheimer\u27s Disease (MODEL-AD) consortium was assembled by the National Institute on Aging (NIA) to develop more robust animal models of AD with increased relevance to human disease, standardize the characterization of AD mouse models, improve preclinical testing in animals, and establish clinically relevant AD biomarkers, among other aims toward enhancing the translational value of AD models in clinical drug design and treatment development. Here we have conducted a detailed characterization of the 5XFAD mouse, including transcriptomics, electroencephalogram

Comprehensive Evaluation of the 5XFAD Mouse Model for Preclinical Testing Applications: A MODEL-AD Study.

The ability to investigate therapeutic interventions in animal models of neurodegenerative diseases depends on extensive characterization of the model(s) being used. There are numerous models that have been generated to study Alzheimer\u27s disease (AD) and the underlying pathogenesis of the disease. While transgenic models have been instrumental in understanding AD mechanisms and risk factors, they are limited in the degree of characteristics displayed in comparison with AD in humans, and the full spectrum of AD effects has yet to be recapitulated in a single mouse model. The Model Organism Development and Evaluation for Late-Onset Alzheimer\u27s Disease (MODEL-AD) consortium was assembled by the National Institute on Aging (NIA) to develop more robust animal models of AD with increased relevance to human disease, standardize the characterization of AD mouse models, improve preclinical testing in animals, and establish clinically relevant AD biomarkers, among other aims toward enhancing the translational value of AD models in clinical drug design and treatment development. Here we have conducted a detailed characterization of the 5XFAD mouse, including transcriptomics, electroencephalogram