Social Determinants of Health and Their Impact on Mental Health and Substance Misuse

Health and wellbeing are shaped by many factors beyond healthcare and behavioral choices, including conditions that make up our social, economic, and physical environments. These factors are often referred to as social determinants of health (SDoHs). SDoHs not only affect our physical health, but they also can have an impact on a person’s mental wellbeing and substance use. These social determinants of health can be grouped into five major categories: 1. Neighborhood and built environment 2. Health and healthcare 3. Social and community context 4. Education 5. Economic stability To address SDoHs effectively, a “health in all policies” approach that integrates health considerations into policymaking across sectors is essential

Progress in the development of an electronic nose using arrays of chemically sensitive carbon black-polymer resistors

Response data were collected for a carbon black-polymer composite electronic nose array during exposure to homologous series of alkanes and alcohols. At a fixed partial pressure of odorant in the vapor phase, the mean response intensity of the electronic nose signals varied significantly for members of each series of odorants. However, the mean response intensity of the electronic nose detectors, and the response intensity of the most strongly-driven set of electronic nose detectors, was essentially constant for members of a chemically homologous odorant series when the concentration of each odorant in the gas phase was maintained at a constant fraction of the odorant's vapor pressure. Because the thermodynamic activity of an odorant at equilibrium in a sorbent phase is equal to the partial pressure of the odorant in the gas phase divided by the vapor pressure of the odorant, and because the activity coefficients are similar within these homologous series of odorants for sorption of the vapors into specific polymer films, the data imply that the trends in detector response can be understood based on the thermodynamic tendency to establish a relatively constant concentration of sorbed odorant into each of the polymeric films of the electronic nose at a constant fraction of the odorant's vapor pressure. This phenomenon provides a natural mechanism for enhanced sensitivity to low vapor pressure compounds, like TNT, in the presence of high vapor pressure analytes, such as diesel fuel. In a related study to evaluate the target recognition properties of the electronic nose, a statistical metric based on the magnitudes and standard deviations along Euclidean projections of clustered array response data, was utilized to facilitate an evaluation of the performance of detector arrays in various vapor classification tasks. This approach allowed quantification of the ability of a fourteen-element array of carbon black-insulating polymer composite chemiresistors to distinguish between members of a set of nineteen solvent vapors, some of which vary widely in chemical properties (e.g. methanol and benzene) and others of which are very similar (e.g. n-pentane and n-heptane). The data also facilitated evaluation of questions such as array performance as a function of the number of detectors in the system

Psychological Safety and Norm Clarity in Software Engineering Teams

In the software engineering industry today, companies primarily conduct their work in teams. To increase organizational productivity, it is thus crucial to know the factors that affect team effectiveness. Two team-related concepts that have gained prominence lately are psychological safety and team norms. Still, few studies exist that explore these in a software engineering context. Therefore, with the aim of extending the knowledge of these concepts, we examined if psychological safety and team norm clarity associate positively with software developers' self-assessed team performance and job satisfaction, two important elements of effectiveness. We collected industry survey data from practitioners (N = 217) in 38 development teams working for five different organizations. The result of multiple linear regression analyses indicates that both psychological safety and team norm clarity predict team members' self-assessed performance and job satisfaction. The findings also suggest that clarity of norms is a stronger (30\% and 71\% stronger, respectively) predictor than psychological safety. This research highlights the need to examine, in more detail, the relationship between social norms and software development. The findings of this study could serve as an empirical baseline for such, future work.Comment: Submitted to CHASE'201

Opal web services for biomedical applications

Biomedical applications have become increasingly complex, and they often require large-scale high-performance computing resources with a large number of processors and memory. The complexity of application deployment and the advances in cluster, grid and cloud computing require new modes of support for biomedical research. Scientific Software as a Service (sSaaS) enables scalable and transparent access to biomedical applications through simple standards-based Web interfaces. Towards this end, we built a production web server (http://ws.nbcr.net) in August 2007 to support the bioinformatics application called MEME. The server has grown since to include docking analysis with AutoDock and AutoDock Vina, electrostatic calculations using PDB2PQR and APBS, and off-target analysis using SMAP. All the applications on the servers are powered by Opal, a toolkit that allows users to wrap scientific applications easily as web services without any modification to the scientific codes, by writing simple XML configuration files. Opal allows both web forms-based access and programmatic access of all our applications. The Opal toolkit currently supports SOAP-based Web service access to a number of popular applications from the National Biomedical Computation Resource (NBCR) and affiliated collaborative and service projects. In addition, Opal’s programmatic access capability allows our applications to be accessed through many workflow tools, including Vision, Kepler, Nimrod/K and VisTrails. From mid-August 2007 to the end of 2009, we have successfully executed 239 814 jobs. The number of successfully executed jobs more than doubled from 205 to 411 per day between 2008 and 2009. The Opal-enabled service model is useful for a wide range of applications. It provides for interoperation with other applications with Web Service interfaces, and allows application developers to focus on the scientific tool and workflow development. Web server availability: http://ws.nbcr.net

Velocity Dispersion of Dissolving OB Associations Affected by External Pressure of Formation Environment

This paper presents a possible way to understand dissolution of OB associations (or groups). Assuming rapid escape of parental cloud gas from associations, we show that the shadow of the formation environment for associations can be partially imprinted on the velocity dispersion at their dissolution. This conclusion is not surprising as long as associations are formed in a multiphase interstellar medium, because the external pressure should suppress expansion caused by the internal motion of the parental clouds. Our model predicts a few km s$^{-1}$ as the internal velocity dispersion. Observationally, the internal velocity dispersion is $\sim 1$ km s$^{-1}$ which is smaller than our prediction. This suggests that the dissipation of internal energy happens before the formation of OB associations.Comment: 6 pages. AJ accepte

Cybersecurity Enhancement of Transformer Differential Protection Using Machine Learning

The growing use of information and communication technologies (ICT) in power grid operational environments has been essential for operators to improve the monitoring, maintenance and control of power generation, transmission and distribution, however, at the expense of an increased grid exposure to cyber threats. This paper considers cyberattack scenarios targeting substation protective relays that can form the most critical ingredient for the protection of power systems against abnormal conditions. Disrupting the relays operations may yield major consequences on the overall power grid performance possibly leading to widespread blackouts. We investigate methods for the enhancement of substation cybersecurity by leveraging the potential of machine learning for the detection of transformer differential protective relays anomalous behavior. The proposed method analyses operational technology (OT) data obtained from the substation current transformers (CTs) in order to detect cyberattacks. Power systems simulation using OPAL-RT HYPERSIM is used to generate training data sets, to simulate the cyberattacks and to assess the cybersecurity enhancement capability of the proposed machine learning algorithms

Fifty Years of IMF Variation: The Intermediate-Mass Stars

I track the history of star count estimates of the Milky Way field star and open cluster IMFs, concentrating on the neglected mass range from 1 to 15 M${_\odot}$. The prevalent belief in a universal IMF appears to be without basis for this mass range. Two recent estimates of the field star IMF using different methods and samples give values of the average logarithmic slope $\Gamma$ between -1.7 and -2.1 in the mass range 1.1 to 4 M${_\odot}$. Two older estimates between 2 and 15 M${_\odot}$ disagree severely; the field IMF in this range is essentially unknown from star counts. Variations in $\Gamma$ among open cluster IMFs in this mass range have not decreased despite numerous detailed studies, even for studies using homogeneous data and reduction procedures and including only clusters with a significant mass range. These cluster variations \textit{might} be due to the combined effects of sampling, systematic errors, stellar evolution uncertainties, dynamical evolution, and unresolved binaries. If so, then the cluster data are consistent with a universal IMF, but are also consistent with sizeable variations. The cluster data do not allow an estimate of an average IMF or $\Gamma$ because the average depends on the choice of weighting procedure and other effects. If the spread in cluster IMFs is in excess of the effects listed above, real IMF variations must occur that do not depend much on physical conditions explored so far. The complexity of the star formation process seen in observations and simulations suggests that large realization-to-realization differences might be expected, in which case an individual cluster IMF would be in part the product of evolutionary contingency in star formation, and the function of interest is the probability distribution of IMF parameters.Comment: 18 pages, including 4 figures: invited talk presented at the conference on "IMF@50: The Stellar Initial Mass Function Fifty Years Later" held at Abbazia di Spineto, Siena, Italy, May 2004; to be published by Kluwer Academic Publishers, edited by E. Corbelli, F. Palla, and H. Zinnecke