577 research outputs found
“Repackaging the Patriarchy”: A Comparative Analysis Between Soviet and Contemporary Russian Reproductive Health Policies and Ideologies
Senior Project submitted to The Division of Languages and Literature of Bard College
Mediation to deal with information heterogeneity ? application to Earth System Science
International audienceWe address the problem of data and information interoperability in the Earth System Science information domain. We believe that well-established architectures and standard technologies are now available to implement data interoperability. In particular, we elaborate on the mediated approach, and present several technological aspects of our implementation of a Mediator-based Information System for Earth System Science Data. We highlight some limitations of current standard-based solutions and introduce possible future improvements
Lycopersicon esculentum lectin: an effective and versatile endothelial marker of normal and tumoral blood vessels in the central nervous system
The binding of Lycopersicon esculentum lectin (LEA) to the vascular endothelium was studied in the central nervous system of rat, mouse and guinea pig at different developmental ages, and in a gliosarcoma model. Our observations showed that LEA consistently stained the entire vascular tree in the spinal cord and in the brain of all animal species at all developmental ages investigated. In the tumor model, the staining of the vascular network was very reproducible, enabled an easy identification of vascular profiles and displayed a higher efficiency when compared to two other commonly used vascular marker (EHS laminin and PECAM-1). Moreover, our results showed that LEA staining was comparable in both vibratome and paraffin sections and could be easily combined with other markers in double labeling experiments. These observations indicate that LEA staining may represent an effective and versatile endothelial marker for the study of the vasculature of the central nervous system in different animal species and experimental conditions
\u201cWoulda, coulda, shoulda\u201d. Workers\u2019 proactivity in the association between emotional demands and mental health
The present study aimed to explore the mediating role of hostile customer relations in the association between emotional dissonance and workers\u2019 mental health. Moreover, the moderating role of proactive personality as a buffer against hostile customer relations was assessed. Emotional demands become crucial within professions that involve a direct relationship with clients and, if poorly managed, can negatively affect workers\u2019 health and performance. Accordingly, data were collected on a sample of n = 918 mass-retail employees working for one of the leading Italian supermarket companies. Most participants were women (62.7%) with a mean age = 40.38 (SD = 7.68). The results of a moderated mediation analysis revealed that emotional dissonance was related to more hostile customer relations that, in turn, were associated with higher rates of mental health symptoms. Proactive personality emerged as a protecting factor that prevented the onset of conflicts with clients, particularly among workers experiencing high levels of emotional dissonance. The identification of resources enabling management of emotional demands could suggest suitable adaptive strategies for customer-facing roles, thus preventing the occurrence of adverse mental health symptoms
Health, Stress and Technologies : Integrating Technology Acceptance and Health Belief Models for Smartphone-Based Stress Intervention
Work-related stress significantly jeopardizes employees’ physical and mental health due to the considerable time they spend at work. Smartphone-based interventions provide a promising solution, eliminating traditional face-to-face interventions’ barriers. However, the elements that influence workers’ intentions to use this still remain unexplored. This study explores the link between health belief model (HBM) and technology acceptance model (TAM) factors. In this study, 336 Italian workers (64% female) answered an online questionnaire. We employed a structural equation model (SEM) to analyze the data. The results unveiled an indirect relationship: individuals perceiving health risks were more inclined to use stress-management apps, mediated by perceived utility (PU). This study underscores the significant potential of integrating the HBM with the TAM in predicting users’ preparedness for smartphone-based health interventions. These findings not only hold substantial value but also illuminate a path forward for professionals and organizations, offering insights to tailor and optimize smartphone tools for stress management and the promotion of workplace well-being. Ultimately, this research paves the way for the cultivation of healthier work environments, marking a noteworthy contribution to the field
Transient Effects of Self-adjustment of Pressure Reducing Valves
AbstractPressure control strategy through Pressure Reducing Valves (PRV) has been deeply investigated as management strategy, aimed at water leakages reduction avoiding very expensive pipe replacement programs. On the contrary, few experimental data are available in literature, with regard to PRV transient behavior in terms of its response to incoming pressure waves, as well as the time required for achieving the pressure set point. In this paper, the results of some experimental tests are presented. The PRV is installed in a single high density polyethylene pipe and transients are generated by operating the downstream end valve. Two types of tests are considered: a partial valve closure and opening simulating a water demand decrease and increase, respectively. The analysis of the experimental pressure traces points out the valuable effects of the PRV on transient characteristics with respect to the case of a partially closed in-line valve with a constant opening degree
Radiomics to predict response to neoadjuvant chemotherapy in rectal cancer: influence of simultaneous feature selection and classifier optimization
According to the guidelines, patients with locally advanced colorectal cancer undergo neoadjuvant chemotherapy. However, response to therapy is reached only up to 30% of cases. Therefore, it would be important to predict response to therapy before treatment. In this study, we demonstrated that the simultaneous optimization of feature subset and classifier parameters on different imaging datasets (T2w, DWI and PET) could improve classification performance. On a dataset of 51 patients (21 responders, 30 non responders), we obtained an accuracy of 90%, 84% and 76% using three optimized SVM classifiers fed with selected features from PET, T2w and ADC images, respectively
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