Effect of a Single Platinum Atom within a Small Metal Oxide Cluster: Reaction of DMMP with Size-Selected Pt1Zr2O7 Supported on HOPG.

Chemical warfare agents (CWAs) are a persistent threat facing civilians and military personnel across the modern geopolitical landscape. The development of the next generation of protective and sensing materials stands to benefit from an improved fundamental understanding of the interaction of CWA molecules with the active components of such candidate materials. The use of model systems in well-controlled environments offers a route to glean such information and has been applied here to investigate the fundamental interaction of a nerve agent simulant molecule, dimethyl methylphosphonate (DMMP), with a small cluster model of a single atom catalyst (SAC) active site. The cluster models, Pt1Zr2O7, were prepared by depositing mass-selected cluster anions synthesized in the gas phase onto a 100 K highly oriented pyrolytic graphite (HOPG) substrate surface prepared in ultra-high vacuum (UHV) at sub-monolayer coverage. Upon deposition, the cluster anions lost their charge to the electrically conductive surface to yield free-standing neutral clusters. The HOPG-supported clusters were characterized by X-ray photoelectron spectroscopy (XPS) to determine the oxidation states and chemical environment of the metal atoms present within the clusters. The reactivity of the clusters with DMMP was investigated via temperature-programmed desorption/reaction (TPD/R) and XPS experiments in which the clusters were exposed to DMMP and incrementally heated to higher temperatures. In contrast to two other HOPG-supported clusters, (ZrO2)3 and Pt1Ti2O7, recently investigated in our laboratory, Pt1Zr2O7 decomposed DMMP to primarily evolve a methane species, which was completely absent for the other clusters.

Ultrasmall Cluster Model for Investigating Single Atom Catalysis: Dehydrogenation of 1-Propanamine by Size-Selected Pt1Zr2O7 Clusters Supported on HOPG.

The selective dehydrogenation of hydrocarbons and their functionalized derivatives is a promising pathway in the realization of endothermic fuel systems for powering important technologies such as hypersonic aircraft. The recent surge in interest in single atom catalysts (SACs) over the past decade offers the opportunity to achieve the ultimate levels of selectivity through the subnanoscale design tailoring of novel catalysts. Experimental techniques capable of investigating the fundamental nature of the active sites of novel SACs in well-controlled model studies offer the chance to reveal promising insights. We report here an approach to accomplish this through the soft landing of mass-selected, ultrasmall metal oxide cluster ions, in which a single noble metal atom bound to a metal oxide moiety serves as a model SAC active site. This method allows the preparation of model catalysts in which monodispersed neutral SAC model active sites are decorated across an inert electrically conductive support at submonolayer surface coverage, in this case, Pt1Zr2O7 clusters supported on highly oriented pyrolytic graphite (HOPG). The results contained herein show the characterization of the Pt1Zr2O7/HOPG model catalyst by X-ray photoelectron spectroscopy (XPS), along with an investigation of its reactivity toward the functionalized hydrocarbon molecule, 1-propanamine. Through temperature-programmed desorption/reaction (TPD/R) experiments it was shown that Pt1Zr2O7/HOPG decomposes 1-propanamine exclusively into propionitrile and H2, which desorb at 425 and 550 K, respectively. Conversely, clusters without the single platinum atom, that is, Zr2O7/HOPG, exhibited no reactivity toward 1-propanamine. Hence, the single platinum atom in Pt1Zr2O7/HOPG was found to play a critical role in the observed reactivity.

A machine learning analysis of COVID-19 mental health data.

In late December 2019, the novel coronavirus (Sars-Cov-2) and the resulting disease COVID-19 were first identified in Wuhan China. The disease slipped through containment measures, with the first known case in the United States being identified on January 20th, 2020. In this paper, we utilize survey data from the Inter-university Consortium for Political and Social Research and apply several statistical and machine learning models and techniques such as Decision Trees, Multinomial Logistic Regression, Naive Bayes, k-Nearest Neighbors, Support Vector Machines, Neural Networks, Random Forests, Gradient Tree Boosting, XGBoost, CatBoost, LightGBM, Synthetic Minority Oversampling, and Chi-Squared Test to analyze the impacts the COVID-19 pandemic has had on the mental health of frontline workers in the United States. Through the interpretation of the many models applied to the mental health survey data, we have concluded that the most important factor in predicting the mental health decline of a frontline worker is the healthcare role the individual is in (Nurse, Emergency Room Staff, Surgeon, etc.), followed by the amount of sleep the individual has had in the last week, the amount of COVID-19 related news an individual has consumed on average in a day, the age of the worker, and the usage of alcohol and cannabis.

Effectiveness of training methods for delivery of evidence-based psychotherapies: a systematic review.

BACKGROUND: Extensive efforts have been made to train mental health providers in evidence-based psychotherapies (EBPs); there is increasing attention focused on the methods through which providers are trained to deliver EBPs. Evaluating EBP training methods is an important step in determining which methods are most effective in increasing provider skill and improving client outcomes. METHODS: We searched MEDLINE (Ovid) and PsycINFO for randomized controlled trials published from 1990 through June 2019 that evaluated EBP training methods to determine the effectiveness of EBP training modalities on implementation (provider and cost) and client outcomes. Eligible studies (N = 28) were evaluated for risk of bias, and the overall strength of evidence was assessed for each outcome. Data was extracted by a single investigator and confirmed by a second; risk of bias and strength of evidence were independently rated by two investigators and determined by consensus. RESULTS: Overall, EBP training improved short-term provider satisfaction, EBP knowledge, and adherence compared to no training or self-study of training materials (low to moderate strength of evidence). Training in an EBP did not increase treatment adoption compared to no training or self-study. No specific active EBP training modality was found to consistently increase provider EBP knowledge, skill acquisition/adherence, competence, adoption, or satisfaction compared to another active training modality. Findings were mixed regarding the additive benefit of post-training consultation on these outcomes. No studies evaluated changes in provider outcomes with regards to training costs and few studies reported on client outcomes. LIMITATIONS: The majority of included studies had a moderate risk of bias and strength of evidence for the outcomes of interest was generally low or insufficient. Few studies reported effect sizes. The ability to identify the most effective EBP training methods was limited by low strength of evidence for the outcomes of interest and substantial heterogeneity among studies. CONCLUSIONS: EBP training may have increased short-term provider satisfaction, EBP knowledge, and adherence though not adoption. Evidence was insufficient on training costs and client outcomes. Future research is needed on EBP training methods, implementation, sustainability, client outcomes, and costs to ensure efforts to train providers in EBPs are effective, efficient, and durable. TRIAL REGISTRATION: The protocol for this review is registered in PROSPERO (CRD42018093381).

Sleep Patterns and Problems Among Army National Guard Soldiers.

Introduction: Adequate sleep plays an integral role in the physical and mental health of individuals, while simultaneously influencing their cognitive and work performance. Having recognized this, the U.S. Army has focused efforts on improving soldiers' healthy sleep behaviors. This study examines the extent to which mental health, alcohol use, and certain sleep hygiene behaviors predict sleep problems within an Army National Guard sample (N = 438). Materials and Methods: This manuscript is part of a larger study approved through the Minneapolis Veterans Affairs Medical Center Institutional Review Board. Mailed surveys were sent to Minnesota Army National Guard soldiers collecting data on sleep hygiene behaviors, mental health symptoms (post-traumatic stress disorder and depression), and alcohol use. Predictors of sleep problems were evaluated with ordinary least squares multiple linear regression analyses, regressing Insomnia Severity Index total scores on demographic variables, post-traumatic stress disorder (PTSD), depression, alcohol use, sleep hygiene factors (routine and consumption activity; both derived from exploratory factor analysis), and technology use (multiple device use and use before bed). Results: Overall, the majority of participants did not endorse high levels of sleep impairment, while 16.4% screened positive for moderate or even severe levels of clinical insomnia. Bivariate correlations demonstrated that sleep problems were correlated with PTSD symptoms (r = 0.41, p < 0.001), depression (r = 0.49, p < 0.001), Sleep Hygiene Routine (r = -0.34, p < 0.001), and more frequent use of multiple devices before bed (r = 0.15, p = 0.002). The overall regression model predicting sleep problems was significant (R2 = 0.35, adj R2 = 0.34, F[8,408] = 27.58, p < 0.001). Independent predictors of sleep problems included gender (B = 0.99, ß = 0.09, t = 2.10, p = 0.036), PTSD (B = 0.89, ß = 0.22, t = 4.86, p < 0.001), depression (B = 1.53, ß = 0.20, t = 7.56, p < 0.001), and Sleep Hygiene Routine (B = -0.88, ß = -0.23, t = -5.473, p < 0.001). Alcohol use, Sleep Hygiene Consumption, and technology use did not emerge as independent predictors. Conclusion: Although most soldiers denied sleep problems, a sizeable minority met screening criteria for clinical insomnia. Greater numbers of sleep-related complaints were related to psychological distress including depressive and PTSD symptoms, while adherence to a bedtime routine (Sleep Hygiene Routine) showed an inverse relationship. Alcohol use and sleep hygiene consumption activities were not predictive of sleep problems, suggesting that different sleep hygiene behaviors have differential relationships with sleep problems. Screening and intervention for specific sleep problems may be helpful even very early in Army National Guard service members' careers. Particular focus may be needed for those showing signs of emotional distress, such as PTSD or depression. Future research examining the impact of individual sleep hygiene components is warranted.

Workplace social support in job satisfaction among veterans with posttraumatic stress symptoms: A preliminary correlational study.

For Veterans managing PTSD symptoms, returning to vocational functioning is often challenging; identifying modifiable variables that can contribute to positive vocational adjustment is critical to improved vocational rehabilitation services. Workplace social support has proven to be important in vocational adjustment in both general population and vocational rehabilitation samples, but this area of inquiry has received little attention among Veterans with PTSD symptoms. In this small correlational study, employed Veterans (N = 63) presenting for outpatient PTSD treatment at a VA Health Care System completed surveys assessing demographic variables, PTSD symptoms, workplace social support, and job satisfaction. Workplace social support contributed to the prediction of job satisfaction. It is of note that workplace social support predicted a larger proportion of the variance in employment satisfaction than PTSD symptoms. Further research on workplace social support as a vocational rehabilitation resource for Veterans with PTSD is indicated.