George Mason University
  • Fairfax, VA, United States
Recent publications
Background Cardiovascular risk factors (CVRF) and executive function difficulties increase during later-life and are associated with depression symptoms among non-autistic older people. These associations, however, have not yet been explored among middle-aged and older autistic people. Methods Using data collected via Simons Foundation Powering Autism Research (SPARK), Research Match, we examined the frequency of CVRF, and associations between CVRF, executive function and depression symptoms in 387 middle-aged and older autistic people (aged 40–83 years). Results Autistic adults reported high rates of CVRF (two, 28.9%; three or more, 23.2%). Rates of high cholesterol and obesity were greater among middle-aged and older autistic adults compared to the general population. CVRF, age, and emotion regulation (but not inhibitory control), were significantly associated with depression symptoms in middle-aged and older autistic adults. Conclusions CVRF occur at high rates in middle-aged and older autistic adults, and it is important that healthcare providers monitor risk factors in order to implement preventative strategies. CVRF are associated with depressive symptoms among middle-aged and older autistic adults, but may not be as important as difficulties with emotion regulation.
Police‐initiated pedestrian stops have been one of the most widely used crime prevention tactics in modern policing. Proponents have long considered police stops to be an indispensable component of crime prevention efforts, with many holding them responsible for the significant reductions in violent crime observed across major US cities in recent decades. Critics, however, have taken issue with the overuse of pedestrian stops, linking them to worsening mental and physical health, attitudes toward the police, and elevated delinquent behavior for individuals directly subject to them. To date, there has been no systematic review or meta‐analysis on the effects of these interventions on crime and individual‐level outcomes. To synthesize the existing evaluation research regarding the impact of police‐initiated pedestrian stops on crime and disorder, mental and physical health, individual attitudes toward the police, self‐reported crime/delinquency, violence in police‐citizen encounters, and police misbehavior. We used the Global Policing Database, a repository of all experimental and quasi‐experimental evaluations of policing interventions conducted since 1950, to search for published and unpublished evaluations of pedestrian stop interventions through December of 2019. This overarching search was supplemented by additional searches of academic databases, gray literature sources, and correspondence with subject‐matter experts to capture eligible studies through December 2021. Eligibility was limited to studies that included a treatment group of people or places experiencing pedestrian stops and a control group of people or places not experiencing pedestrian stops (or experiencing a lower dosage of pedestrian stops). Studies were required to use an experimental or quasi‐experimental design and evaluate the intervention using an outcome of area‐level crime and disorder, mental or physical health, individual or community‐level attitudes toward the police, or self‐reported crime/delinquency. We adopted standard methodological procedures expected by the Campbell Collaboration. Eligible studies were grouped by conceptually similar outcomes and then analyzed separately using random effects models with restricted maximum likelihood estimation. Treatment effects were represented using relative incident rate ratios, odds ratios, and Hedges' g effect sizes, depending on the unit of analysis and outcome measure. We also conducted sensitivity analyses for several outcome measures using robust variance estimation, with standard errors clustered by each unique study/sample. Risk of bias was assessed using items adapted from the Cochrane randomized and non‐randomized risk of bias tools. Our systematic search strategies identified 40 eligible studies corresponding to 58 effect sizes across six outcome groupings, representing 90,904 people and 20,876 places. Police‐initiated pedestrian stop interventions were associated with a statistically significant 13% (95% confidence interval [CI]: −16%, −9%, p < 0.001) reduction in crime for treatment areas relative to control areas. These interventions also led to a diffusion of crime control benefits, with a statistically significant 7% (95% CI: −9%, −4%, p < 0.001) reduction in crime for treatment displacement areas relative to control areas. However, pedestrian stops were also associated with a broad range of negative individual‐level effects. Individuals experiencing police stops were associated with a statistically significant 46% (95% CI: 24%, 72%, p < 0.001) increase in the odds of a mental health issue and a 36% (95% CI: 14%, 62%, p < 0.001) increase in the odds of a physical health issue, relative to control. Individuals experiencing police stops also reported significantly more negative attitudes toward the police (g = −0.38, 95% CI: −0.59, −0.17, p < 0.001) and significantly higher levels of self‐reported crime/delinquency (g = 0.30, 95% CI: 0.12, 0.48, p < 0.001), equating to changes of 18.6% and 15%, respectively. No eligible studies were identified measuring violence in police‐citizen encounters or officer misbehavior. While eligible studies were often considered to be at moderate to high risk of bias toward control groups, no significant differences based on methodological rigor were observed. Moderator analyses also indicated that the negative individual‐level effects of pedestrian stops may be more pronounced for youth, and that significant differences in effect sizes may exist between US and European studies. However, these moderator analyses were limited by a small number of studies in each comparison, and we were unable to compare the effects of police stops across racial groupings. While our findings point to favorable effects of pedestrian stop interventions on place‐based crime and displacement outcomes, evidence of negative individual‐level effects makes it difficult to recommend the use of these tactics over alternative policing interventions. Recent systematic reviews of hot spots policing and problem‐oriented policing approaches indicate a more robust evidence‐base and generally larger crime reduction effects than those presented here, often without the associated backfire effects on individual health, attitudes, and behavior. Future research should examine whether police agencies can mitigate the negative effects of pedestrian stops through a focus on officer behavior during these encounters.
Ecosystem decay is responsible for biodiversity declines following forest fragmentation, as initially abundant species may become rare, or experience delayed local extinctions. However, the underlying mechanisms behind the delayed local extinction of certain species following fragmentation are unknown. Species declines may be attributed to an inadequate number of breeding adults required to replace the population or decreased juvenile survival rate due to reduced recruitment or increased nest predation pressures. This study uses 10 years of avian banding data, five years before and four years after fragment isolation, at the Biological Dynamics of Forest Fragments Project near Manaus, Brazil, to investigate the breeding activity hypothesis which predicts that there is less breeding activity and fewer young after relative to before fragment isolation. We found support for the breeding activity hypothesis in both insectivorous and frugivorous birds (effect sizes 0.45 and 0.53, respectively), and in birds with open cup, and enclosed nesting strategies (effect sizes 0.56 and 0.44, respectively) such that on average there were more breeding birds in fragments before isolation relative to after fragment isolation. In addition, a larger proportion of birds in the community were actively breeding before fragment isolation relative to after fragment isolation. Unexpectedly, there was no significant decrease in the number of young birds after fragment isolation, although sample sizes for young were very small, potentially from sustained immigration of young birds to fragments after isolation. Together, these results provide some of the strongest evidence to date that avian breeding activity decreases in response to fragment isolation, which could be a fundamental mechanism that leads to ecosystem decay. This article is protected by copyright. All rights reserved.
The structures of regional economies play a critical role in determining both a region’s productivity and its resilience to shocks. We extend previous work on the regional occupation and skills structure by analyzing the effect of a region’s industry structure. We operationalize the concept of economic structure by constructing a network of interdependent economic components, employing ecological techniques of co-occurrence analysis to infer interactions between industries. For each U.S. metropolitan statistical area, we create an aggregate measure of economic tightness that captures the degree of interconnectedness among a region’s industries. We find that industry tightness, which we find is partly driven by rare industry pairs, is positively correlated with a region’s economic productivity, negatively correlated with a region’s change in productivity following the Great Recession. This study contributes to an understanding of the tradeoff between productivity and resilience, which is intended to help policy makers that face similar real-world tradeoffs.
The recent shift from predominantly hardware-based systems in complex settings to systems that heavily leverage non-deterministic artificial intelligence (AI) reasoning means that typical systems engineering processes must also adapt, especially when humans are direct or indirect users. Systems with embedded AI rely on probabilistic reasoning, which can fail in unexpected ways, and any overestimation of AI capabilities can result in systems with latent functionality gaps. This is especially true when humans oversee such systems, and such oversight has the potential to be deadly, but there is little-to-no consensus on how such system should be tested to ensure they can gracefully fail. To this end, this work outlines a roadmap for emerging research areas for complex human-centric systems with embedded AI. Fourteen new functional and tasks requirement considerations are proposed that highlight the interconnectedness between uncertainty and AI, as well as the role humans might need to play in the supervision and secure operation of such systems. In addition, 11 new and modified non-functional requirements, i.e., “ilities,” are provided and two new “ilities,” auditability and passive vulnerability, are also introduced. Ten problem areas with AI test, evaluation, verification and validation are noted, along with the need to determine reasonable risk estimates and acceptable thresholds for system performance. Lastly, multidisciplinary teams are needed for the design of effective and safe systems with embedded AI, and a new AI maintenance workforce should be developed for quality assurance of both underlying data and models.
Because of the world's dependence on fossil fuels, climate change and air pollution are profoundly harming both human and planetary health. Fortunately, climate solutions are also health solutions, and they present both local and global opportunities to foster cleaner, healthier, and safer communities. In this review, we briefly discuss the human health harms of climate change, climate and health solutions, and provide a thorough synthesis of social science research on climate and health communication. Through our review, we found that social science research provides an evidence-based foundation for messaging strategies that can build public and political will for climate and health solutions. Specifically, messages that convey the health harms of climate change and highlight the health benefits of climate solutions may be especially effective in building this public and political will. We also found that health professionals are trusted sources of information about climate change, and many have shown interest in engaging with the public and policymakers about the health relevance of climate change and clean energy. Together, the alignment between message strategies and the interest of highly trusted messengers strongly suggests the potential of health students and health professionals to create the conditions necessary to address climate change as a public health imperative. Therefore, our review serves as a resource for those interested in communicating about climate change and health and suggests that social scientists can continue to support practitioners with research and advice on the most effective communication strategies.
Reliable neutron star mass measurements are key to determining the equation of state of cold nuclear matter, but such measurements are rare. Black widows and redbacks are compact binaries consisting of millisecond pulsars and semi-degenerate companion stars. Spectroscopy of the optically bright companions can determine their radial velocities, providing inclination-dependent pulsar mass estimates. Although inclinations can be inferred from subtle features in optical light curves, such estimates may be systematically biased due to incomplete heating models and poorly understood variability. Using data from the Fermi Large Area Telescope, we have searched for gamma-ray eclipses from 49 spider systems, discovering significant eclipses in 7 systems, including the prototypical black widow PSR B1957+20. Gamma-ray eclipses require direct occultation of the pulsar by the companion, and so the detection, or significant exclusion, of a gamma-ray eclipse strictly limits the binary inclination angle, providing new robust, model-independent pulsar mass constraints. For PSR B1957+20, the eclipse implies a much lighter pulsar (1.81 ± 0.07 solar masses) than inferred from optical light curve modelling. A few missing photons in Fermi Gamma-ray Space Telescope observations lead to robust neutron star mass measurements in eclipsing millisecond pulsar binaries, ruling out an ultra-massive pulsar in the original Black Widow system.
RNA sequencing (RNA‐Seq) is popular for measuring gene expression in non‐model organisms, including wild populations. While RNA‐Seq can detect gene expression variation among wild‐caught individuals and yield important insights into biological function, sampling methods may influence gene expression estimates. We examined the influence of multiple technical variables on estimated gene expression in a non‐model fish, the westslope cutthroat trout (Oncorhynchus clarkii lewisi), using two RNA‐Seq library types: 3’ RNA‐Seq (QuantSeq) and whole mRNA‐Seq (NEB). We evaluated effects of dip netting versus electrofishing, and of harvesting tissue immediately versus 5 minutes after euthanasia on estimated gene expression in blood, gill, and muscle. We found no significant differences in gene expression between sampling methods or tissue collection times with either library type. When library types were compared using the same blood samples, 58% of genes detected by both NEB and QuantSeq showed significantly different expression between library types, and NEB detected 31% more genes than QuantSeq. Although QuantSeq and NEB recovered different numbers of genes and expression levels, there were no differences in gene expression between sampling methods and tissue harvesting time for either library type. Our study suggests that researchers can safely rely on different fish sampling strategies in the field. In addition, while QuantSeq is more cost effective, NEB detects more expressed genes. Therefore, when it is crucial to detect as many genes as possible (especially low expressed genes), when alternative splicing is of interest, or when working with an organism lacking good genomic resources, whole mRNA‐Seq is more powerful.
Robert (Bob) Keith Wayne lost his battle with cancer in his home on 26 December 2022 with his wife, Dr. Blaire Van Valkenburgh, by his side. This essay, written by his former graduate students, highlights the foundation that survives Bob and our vision of continuing his efforts in building a future for endangered species.
Skin cancer is one of the primary causes of death globally, and experts diagnose it by visual inspection, which can be inaccurate. The need for developing a computer-aided method to aid dermatologists in diagnosing skin cancer is highlighted by the fact that early identification can lower the number of deaths caused by skin malignancies. Among computer-aided techniques, deep learning is the most popular for identifying cancer from skin lesion images. Due to their power-efficient behavior, spiking neural networks are attractive deep neural networks for hardware implementation. We employed deep spiking neural networks using the surrogate gradient descent method to classify 3670 melanoma and 3323 non-melanoma images from the ISIC 2019 dataset. We achieved an accuracy of 89.57% and an F1 score of 90.07% using the proposed spiking VGG-13 model, which is higher than the VGG-13 and AlexNet using less trainable parameters.
For more than a decade, the notion of attack surface has been used to define the set of vulnerable assets that an adversary may exploit to penetrate a system, and various metrics have been developed to quantify the extent of a system's attack surface. However, most approaches to tackle this problem have failed to consider the complex interdependencies that exist between the many components of a distributed system, its vulnerabilities, and its configuration parameters. In our work, building upon previous research on vulnerability metrics and on graphical models to capture such interdependencies, we propose a novel approach to evaluate the potential risk associated with exposed vulnerabilities by studying how the effect of each vulnerability exploit propagates through chains of dependencies. Our analysis goes beyond the scope of traditional attack surface metrics, and considers the depth and implications of potential attacks, leading to the definition of a new family of metrics, which we refer to as attack volume metrics. We present experimental results illustrating how the proposed metric scales for graphs of realistic sizes, and illustrate its application to real‐world testbeds.
Using an organization design lens, we explore how key characteristics of both task systems and their associated resources may benefit firms. We unpack task system interdependencies by studying the interaction of decentralization and complexity, examining resource fungibility and resource slack, and exploring their joint alignment. Our context is the scheduled U.S. passenger airline industry over two decades. Results show that firm performance improves when (1) task system decentralization and complexity are aligned, either more or less of both; (2) having both resource fungibility and resource slack, not simply more of one or the other; and (3) aligning less decentralized and less complex task systems with fungible and available resources. Our findings underscore the importance of holistically managing tasks and resources to minimize bottlenecks within organizations. Eliminating bottlenecks can help firms improve performance. Our study focuses on two types of bottlenecks—task system bottlenecks stemming from the design of activities and resource bottlenecks, created when necessary resources are already in use or available resources are not applicable. Our results show that firms benefit when task system properties of decentralization and complexity are aligned and when firms’ resources are both fungible and available; these characteristics also reinforce each other. Thus, managers should be aware of both task system properties and resource characteristics to avoid bottlenecks, so that the tasks to which the resources are applied can be completed. In addition, managers should ensure to have available and fungible resources at their disposal, especially when organizations have a centralized and less complex design.
Recruiting racially minoritized principals is one suggested strategy to increase the racial diversity of teachers, who would then better match their increasingly racially diverse students. However, focusing solely on race ignores the salience of race-gender intersectionality in principal-teacher relations. Using three waves of nationally representative, cross-sectional data with school and year fixed effects, we compared similar teachers in the same school who are and are not race-gender congruent with their principal. We found that better discretionary workplace benefits were concentrated among Black teachers with Black principals, especially Black male teachers with Black male principals, who reported workplace supports almost half a standard deviation higher than did similar non-Black female teachers in their school. Male teachers earned up to $2,890 more supplemental income with male, racially congruent principals; female teachers earned up to $1,050 less with female, racially congruent principals. However, teacher turnover was not consistently responsive to race-gender congruence.
As biobanks become increasingly popular, access to genotypic and phenotypic data continues to increase in the form of precomputed summary statistics (PCSS). Widespread accessibility of PCSS alleviates many issues related to biobank data, including that of data privacy and confidentiality, as well as high computational costs. However, questions remain about how to maximally leverage PCSS for downstream statistical analyses. Here we present a novel method for testing the association of an arbitrary number of single nucleotide variants (SNVs) on a linear combination of phenotypes after adjusting for covariates for common multimarker tests (e.g., SKAT, SKAT‐O) without access to individual patient‐level data (IPD). We validate exact formulas for each method, and demonstrate their accuracy through simulation studies and an application to fatty acid phenotypic data from the Framingham Heart Study.
We investigate whether Minority Owned/Controlled Banks (MDIs) perform better or worse than Non-Minority Banks (NMDIs) in terms of lower profit rates and higher risk. MDIs and NMDIs are compared using a propensity score matching (PSM) methodology. We also compare the performance when their headquarters are in the same census tract. In contrast to previous and earlier studies, the empirical results indicate that MDIs exhibit no signs of under- or over-performance vis-à-vis NMDIs. Moreover, we find no statistically significant difference between the four sub-categories of MDIs (Black, Asian, Hispanic, and Native American) and NMDIs regarding either profitability or riskiness. Robustness checks using zip code and city-level data effectively confirm these results.
We characterize the daytime sky quality in terms of its brightness, cloud coverage and main weather variables at the Carlos Ulrico Cesco stationof the Felix Aguilar Astronomical Observatory (OAFA), located in El Leoncito national park, San Juan, Argentina. We have collected more than 15 years of daily observations from the auxiliary sky brightness detectors of the Mirror Coronagraph for Argentina (MICA, in operations from 1997 to 2012), including daily observing reports. We additionally present data from two meteorological stations that operated at the site from 2000 to 2020. We determine the main statistical properties and seasonal variability of daytime sky brightness, clear sky timefraction (CSTF), precipitable water vapor (WV), temperature, humidity and wind speed, which are relevant for solar and particularly coronal observations. Our results confirm that El Leoncito is an excellent place to perform daytimeastronomical observations. We measure a median sky brightness of 15.8 ppm, estimated at 526.0 ± 1 nm and 6 solar radii from the solar disk center; a median CSTF of 0.7; and a median WV below 6 mm. These values, and those of other relevant weather variables, are comparable to the levels found among the best astronomical observing sites in the world. Due to the extended period of time analyzed and high sampling frequency, the novel data and results presented in this report contribute to the analysis and interpretation of historical sky brightness data, and are of great value for the future planning of daytime astronomical instrumentation at El Leoncito.
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12,621 members
Donald Seto
  • Bioinformatics and Computational Biology Program, School of Systems Biology
Gary Kreps
  • Department of Communication
Dale Scott Rothman
  • Department of Computational and Data Sciences
Michelle Harris-Love
  • Department of Rehabilitation Science
Viviana Maggioni
  • Department of Civil, Environmental and Infrastructure Engineering
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