Recent publications
This paper studies the role of privatization and subsidization policies as trade strategies in a single multinational market where private and public firms of different nationalities interact. It finds out when a country subsidizes its industry the rival country would have the incentive to retaliate by adopting a subsidization regime to prevent a free riders’ situation from happening when it moves to liberalize the market. However this step does not eliminate the free rider problem governments are facing in this market when they privatize their public firms unilaterally.
Prior research has found inconsistent results regarding gender differences in confidence and metacognitive ability. Different studies have shown that men are either more or less confident and have either higher or lower metacognitive abilities than women. However, this research has generally not used well-controlled tasks or used performance-independent measures of metacognitive ability. Here, we test for gender differences in performance, confidence, and metacognitive ability using data from 10 studies from the Confidence Database (total N = 1,887, total number of trials = 633,168). We find an absence of strong gender differences in performance and no gender differences in either confidence or metacognitive ability. These results were further confirmed by meta-analyses of the 10 datasets. These findings show that it is unlikely that gender has a strong effect on metacognitive evaluation in low-level perceptual decision-making and suggest that previously observed gender differences in confidence and metacognition are likely domain-specific.
A new biomimetic model complex of the active site of acireductone dioxygenase (ARD) was synthesized and crystallographically characterized ([Ni(II)(N-(ethyl-N’Me2)(Py)(2-t-ButPhOH))(OTf)]-1). 1 displays carbon-carbon oxidative cleavage activity in the presence of O2...
Fermentation of pectin-rich biomass by Saccharomyces cerevisiae can produce bioethanol as a fuel replacement to combat carbon dioxide emissions from the combustion of fossil fuels. Saccharomyces cerevisiae UCDFST 09-448 produces its own pectinase enzymes potentially eliminating the need for commercial pectinases during fermentation. This research assessed growth, pectinase activity, and fermentative activity of S. cerevisiae UCDFST 09-448 and compared its performance to an industrial yeast strain, S. cerevisiae XR122N. Saccharomyces cerevisiae UCDFST 09-448’s growth was inhibited by osmotic stress (xylose concentrations above 1 M), ethanol concentrations greater than 5% v/v, and temperatures outside of 30°C–37°C. However, S. cerevisiae UCDFST 09-448 was able to consistently grow in an industrial pH range (3–6). It was able to metabolize glucose, sucrose, and fructose but was unable to metabolize arabinose, xylose, and galacturonic acid. The pectinase enzyme produced by S. cerevisiae UCDFST 09-448 was active under typical fermentation conditions (35°C–37°C, pH 5.0). Regardless of S. cerevisiae UCDFST 09-448’s limitations when compared to S. cerevisiae XR122N in 15% w/v peach fermentations, S. cerevisiae UCDFST 09-448 was still able to achieve maximum ethanol yields in the absence of commercial pectinases (44.7 ± 3.1 g/L). Under the same conditions, S. cerevisiae XR122N produced 39.5 ± 3.1 g/L ethanol. While S. cerevisiae UCDFST 09-448 may not currently be optimized for industrial fermentations, it is a step toward a consolidated bioprocessing approach to fermentation of pectin-rich biomass.
One-Sentence Summary
Saccharomyces cerevisiae UCDFST 09-448 demonstrates the potential to ferment pectin-rich biomass as part of a consolidated bioprocess, but is sensitive to industrial stressors.
Ontologies and terminologies serve as the backbone of knowledge representation in biomedical domains, facilitating data integration, interoperability, and semantic understanding across diverse applications. However, the quality assurance and enrichment of these resources remain an ongoing challenge due to the dynamic nature of biomedical knowledge. In this editorial, we provide an introductory summary of seven articles included in this special supplement issue for quality assurance and enrichment of biological and biomedical ontologies and terminologies. These articles span a spectrum of topics, such as development of automated quality assessment frameworks for Resource Description Framework (RDF) resources, identification of missing concepts in SNOMED CT through logical definitions, and developing a COVID interface terminology to enable automatic annotations of COVID-19 related Electronic Health Records (EHRs). Collectively, these contributions underscore the ongoing efforts to improve the accuracy, consistency, and interoperability of biomedical ontologies and terminologies, thus advancing their pivotal role in healthcare and biomedical research.
The modern era of running shoes began in the 1960s with the introduction of simple polymer midsole foams, and it ended in the late 2010s with the introduction of advanced footwear technology (AFT). AFT is characterized by highly compliant, resilient, and lightweight foams with embedded, rigid, longitudinal architecture. This footwear complex improves a runner’s efficiency, and it introduced a step change in running performance. Purpose : This review serves to examine the current state of knowledge around AFT—what it is and what we know about its ingredients, what benefits it confers to runners, and what may or may not mediate that benefit. We also discuss the emerging science around AFT being introduced to track-racing spikes and how it is currently regulated in sporting contexts. Conclusions : AFT has changed running as a sport. The construction of AFT is grossly understood, but the nature of the interacting elements is not. The magnitude of the enhancement of a runner’s economy and performance has been characterized and modeled, but the nuanced factors that mediate those responses have not. With these knowns and unknowns, we conclude the review by providing a collection of best practices for footwear researchers, advice for runners interested in AFT, and a list of pertinent items for further investigation.
Prenatal stress is hypothesized to contribute to the development of schizophrenia. Lee and colleagues determined that prenatal stress in rats decreases levels of Dpysl2, which is found to be inactivated in schizophrenic patients. UNC-33 , the homolog to Dpysl2 in C. elegans , is important for axonal outgrowth and synapse formation. Herein, we study the effects of antipsychotic drugs on developing C.elegans exposed to stress through high temperatures. Results indicate that the unc-33 promoter was not impacted by antipsychotic drug treatment, but the lifespan was decreased.
Social media analyses have become increasingly popular among health care researchers. Social media continues to grow its user base and, when analyzed, offers unique insight into health problems. The process of obtaining data for social media analyses varies greatly and involves ethical considerations. Data extraction is often facilitated by software tools, some of which are open source, while others are costly and therefore not accessible to all researchers. The use of software for data extraction is accompanied by additional challenges related to the uniqueness of social media data. Thus, this paper serves as a tutorial for a simple method of extracting social media data that is accessible to novice health care researchers and public health professionals who are interested in pursuing social media research. The discussed methods were used to extract data from Facebook for a study of maternal perspectives on sudden unexpected infant death.
Purpose:
Determine the effects of advanced footwear technology (AFT) in track spikes and road-racing shoes on running economy (RE).
Methods:
Four racing shoes (3 AFT and 1 control) and 3 track spikes (2 AFT and 1 control) were tested in 9 male distance runners on 2 visits. Shoes were tested in a random sequence over 5-minute trials on visit 1 (7 trials at 16 km·h-1; 5-min rest between trials) and in the reverse/mirrored order on visit 2. Metabolic data were collected and averaged across visits.
Results:
There were significant differences across footwear conditions for oxygen consumption (F = 13.046; P < .001) and energy expenditure (F = 14.710; P < .001). Oxygen consumption (in milliliters per kilogram per minute) in both the first AFT spike (49.1 [1.7]; P < .001; dz = 2.1) and the other AFT spike (49.3 [1.7]; P < .001; dz = 1.7) was significantly lower than the control spike (50.2 [1.6]), which represented a 2.1% (1.0%) and 1.8% (1.0%) improvement in RE, respectively, for the AFT spikes. When comparing the subjects' most economic shoe by oxygen consumption (49.0 [1.5]) against their most economic spike (49.0 [1.8]), there were no statistical differences (P = .82). Similar statistical conclusions were made when comparing energy expenditure (in watts per kilogram).
Conclusions:
AFT track spikes improved RE ∼2% relative to a traditional spike. Despite their heavier mass, AFT shoes resulted in similar RE as AFT spikes. This could make the AFT shoe an attractive option for longer track races, particularly in National Collegiate Athletic Association and high school athletics, where there are no stack-height rules.
Given the history of discrimination and increased mental health risks surrounding LGBTQIA+ service members, group counseling is a practical approach for practitioners to mitigate effects in a therapeutic setting. This article synthesizes the Positive Relational Couples Therapy (PRCT) model, incorporating concepts of the Multicultural and Social Justice Counseling Competencies (MSJCC), Relational-Cultural Theory (RCT), the PERMA model, and Gottman's Method Couples Therapy as a group process to provide a conceptual framework. An outline of the PRCT model and case illustration are provided for practitioners for group counseling with LGBTQIA+ military couples. Practical group considerations and implications for this work are discussed.
Photochemical modeling outputs showing high ozone concentrations over the Gulf of Mexico and Galveston Bay during ozone episodes in the Houston-Galveston-Brazoria (HGB) region have not been previously verified using in-situ observations. Such data was collected systematically, for the first time, from July-October 2021 from three boats deployed for the Galveston Offshore Ozone Observations (GO3) and Tracking Aerosol Convection Interactions ExpeRiment - Air Quality (TRACER-AQ) field campaigns. A pontoon boat and a commercial vessel operated in Galveston Bay, while another commercial vessel operated in the Gulf of Mexico offshore of Galveston. All three boats had continuously operating sampling systems that included ozone analyzers and weather stations, and the two boats operating in Galveston Bay had a ceilometer. The sampling systems operated autonomously on the two commercial boats as they traveled their daily routes. Thirty-seven ozonesondes were launched over water on forecast high ozone days in Galveston Bay and the Gulf of Mexico. During the campaigns, multiple periods of ozone exceeding 100 ppbv were observed over water in Galveston Bay and the Gulf of Mexico. These events included previously identified conditions for high ozone events in the HGB region, such as the bay/sea breeze recirculation and post-frontal environments, as well as a localized coastal high ozone event after the passing of a tropical system (Hurricane Nicholas) that was not well forecast.
Predicting nurse turnover is a growing challenge within the healthcare sector, profoundly impacting healthcare quality and the nursing profession. This study employs the Synthetic Minority Over-sampling Technique (SMOTE) to address class imbalance issues in the 2018 National Sample Survey of Registered Nurses dataset and predict nurse turnover using machine learning algorithms. Four machine learning algorithms, namely logistic regression, random forests, decision tree, and extreme gradient boosting, were applied to the SMOTE-enhanced dataset. The data were split into 80% training and 20% validation sets. Eighteen carefully selected variables from the database served as predictive features, and the machine learning model identified age, working hours, electric health record/electronic medical record, individual income, and job type as important features concerning nurse turnover. The study includes a performance comparison based on accuracy, precision, recall (sensitivity), F1-score, and AUC. In summary, the results demonstrate that SMOTE-enhanced random forests exhibit the most robust predictive power in the classical approach (with all 18 predictive variables) and an optimized approach (utilizing eight key predictive variables). Extreme gradient boosting, decision tree, and logistic regression follow in performance. Notably, age emerges as the most influential factor in nurse turnover, with working hours, electric health record/electronic medical record usability, individual income, and region also playing significant roles. This research offers valuable insights for healthcare researchers and stakeholders, aiding in selecting suitable machine learning algorithms for nurse turnover prediction.
The US Supreme Court has required that death penalty procedures narrow the class of persons eligible for a death sentence. Through the selection requirement, juries must use mitigating and aggravating evidence jointly to determine if a defendant is one of the worst of the worst, resulting in a sentence of life without parole or death. This study analyzed capital trial transcripts from the punishment phase to assess the type and amount of mitigating and aggravating evidence presented to jurors in cases resulting in life without parole and death. The main assumption of the research was that cases resulting in life without the possibility of parole (LWOP) would reveal patterns in the types of evidence presented and differing patterns in cases where the jury handed down a sentence of death. The study qualitatively examined the trial transcripts from the punishment phase of 18 capital murders (nine resulting in LWOP and nine in death). The extra‐legal factors from each LWOP case were matched to a death case to eliminate sentencing discrepancies based on jurisdiction, race of defendant or victim, aggravator, age etc. The results found no consistent patterns of evidence presented in cases resulting life without parole and some relevant patterns in sentences resulting in death.
Disclosure: E.N. Hilz: None. C. Schnurer: None. S. Bhamidipati: None. L. Thompson: None. E. Morales-Ledesma: None. A.C. Gore: None.
Polychlorinated biphenyls (PCBs) are a weakly estrogenic class of ubiquitous environmental EDCs that affect a range of sex-specific neuroendocrine and reproductive outcomes. Furthermore, these effects can extend intergenerationally via epigenetic changes carried down the germline. In humans, PCBs are associated with sexually dimorphic and hormone sensitive neurobehavioral disorders including attention deficit hyperactivity disorder (ADHD) and mood disorders such as depression; however, little preclinical work has modeled these cognitive changes in rats and none has determined if they extend intergenerationally via endocrine-mediated changes to the brain dopamine system. In the current work, three generations of male and female Sprague-Dawley rats were exposed to the PCB mixture Aroclor 1221 (A1221) at different life stages: as adults; through perinatal exposure via mother's diet; or preconceptionally, as the germ cells within the exposed fetus. Adults of each generation underwent a battery of behavioral tasks to assess attentional phenotype, cognitive flexibility, and affect as measured by attentional set-shifting, conditioned orienting, and sucrose preference tests. These outcomes were correlated with both serum estradiol concentrations and dopamine cell quantity in the midbrain. Results revealed that A1221 treatment had sex- and generation-specific effects: in adult-exposed females, decreased conditioned orienting suggested a hyporesponsive attentional phenotype; in males, preconceptional exposure reduced cognitive flexibility via impaired attentional set-shifting. All rats showed a strong preference for sucrose solution; however, A1221 treatment decreased the total amount of sucrose solution consumed (indicating anhedonia) regardless of sex or timing of exposure. Dopamine cell numbers were inversely affected by A1221 between the sexes: decreased in females and increased in males, which correlates well with the cognitive changes observed. Relationships among estradiol concentration, cognitive changes, and dopamine cell quantity will be ascertained using a multilevel model that accounts for endocrine-mediated disruptions at the brain, body, and behavioral levels. These data show that the PCB mixture A1221 impairs different aspects of cognitive behavior between the sexes depending on timing of exposure, while having a broader effect of increased anhedonia, in a manner potentially mediated by hypo- or hyper-availability of midbrain dopamine and serum estradiol. Supported by RO1 ES029464.
Presentation: Thursday, June 15, 2023
Human-driven environmental changes shape ecological communities from local to global scales. Within cities, landscape-scale patterns and processes and species characteristics generally drive local-scale wildlife diversity. However, cities differ in their structure, species pools, geographies and histories, calling into question the extent to which these drivers of wildlife diversity are predictive at continental scales. In partnership with the Urban Wildlife Information Network, we used occurrence data from 725 sites located across 20 North American cities and a multi-city, multi-species occupancy modelling approach to evaluate the effects of ecoregional characteristics and mammal species traits on the urbanization–diversity relationship. Among 37 native terrestrial mammal species, regional environmental characteristics and species traits influenced within-city effects of urbanization on species occupancy and community composition. Species occupancy and diversity were most negatively related to urbanization in the warmer, less vegetated cities. Additionally, larger-bodied species were most negatively impacted by urbanization across North America. Our results suggest that shifting climate conditions could worsen the effects of urbanization on native wildlife communities, such that conservation strategies should seek to mitigate the combined effects of a warming and urbanizing world.
Background
Brazilian immigrants are becoming a more visible minority and, although different from other Latinos (in a linguistic, cultural, historical, and ethnic sense), are usually either counted as Latinos, not included in the Latino samples or simply overlooked in research studies. It is essential to understand the stress and pressures they undergo and appreciate their singular perspective and culturally-infused experiences to meet their needs and improve their mental healthcare and quality of life in the United States.
Aim
The aim of this review is to understand and describe the experience of Brazilian immigrants in the U.S., related to mental health, assessing what studies have addressed and what is still needing to be researched.
Method
We carried out an integrative review of peer-reviewed articles published between 2011 and 2022 using PychInfo, PubMed, and Proquest, addressing mental health of Brazilian immigrants in the United States.
Results
A total of 10 articles were included revealing the interest of a variety of fields and uncovering three themes: (1) mental healthcare needs (especially warmth and understanding of culture), (2) common sources of support and stress in the community and work, and (3) Socioeconomic aspects related to their mental health, including discrimination, work-life balance, neighborhood cohesion, and acculturation.
Conclusions
Results may be useful to practitioners, researchers, and policy makers, who should be attentive to client’s familiarity with the English language, their sources of support, spirituality, specific Brazilian traits, their feeling of ‘being invisible’, life in community, and their previous experiences with healthcare in Brazil.
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