Understanding the impact of COVID-19 pandemic on teleworkers\u27 experiences of perceived threat and professional isolation: The moderating role of friendship

Drawing from conservation of resource theory and the social support resource theory, this study examines how the severity of an exogenous disruptive event – the COVID-19 pandemic – in one\u27s community influences teleworkers\u27 well-being outcomes indirectly through their perceptions of pandemic-related threat and experience of professional isolation, as well as the buffering effect of friendship on these relationships. Utilizing time-lagged data from participants of a two-wave survey panel (N = 351) and objective data of COVID-19 severity from counties around the United States, we found that perceived threat, but not professional isolation, mediated the negative effect of proportion of confirmed COVID-19 cases in the community on teleworkers\u27 well-being outcomes. Further, consistent with our predictions, support from friends significantly weakened the negative effects of threat and professional isolation on well-being. Key theoretical and practical implications of this study are discussed

LSDA: Large Scale Detection Through Adaptation

A major challenge in scaling object detection is the difficulty of obtaining labeled images for large numbers of categories. Recently, deep convolutional neural networks (CNNs) have emerged as clear winners on object classification benchmarks, in part due to training with 1.2M+ labeled classification images. Unfortunately, only a small fraction of those labels are available for the detection task. It is much cheaper and easier to collect large quantities of image-level labels from search engines than it is to collect detection data and label it with precise bounding boxes. In this paper, we propose Large Scale Detection through Adaptation (LSDA), an algorithm which learns the difference between the two tasks and transfers this knowledge to classifiers for categories without bounding box annotated data, turning them into detectors. Our method has the potential to enable detection for the tens of thousands of categories that lack bounding box annotations, yet have plenty of classification data. Evaluation on the ImageNet LSVRC-2013 detection challenge demonstrates the efficacy of our approach. This algorithm enables us to produce a >7.6K detector by using available classification data from leaf nodes in the ImageNet tree. We additionally demonstrate how to modify our architecture to produce a fast detector (running at 2fps for the 7.6K detector). Models and software are available a

Poly[[μ2-1,2-bis­(diphenyl­phosphan­yl)-1,2-diethylhydrazine]-μ4-nitrato-μ2-nitrato-silver(I)]

The title compound, [Ag2(NO3)2(C28H30N2P2)]n, crystallizes in polymeric α-helices. Three O atoms from three different nitrate ions in equatorial positions and two Ag atoms at axial positions set up a trigonal bipyramid. These units are linked by the phosphine ligands into endless helical chains that run along the c axis. The crystal used for the data collection was a racemic twin

Association between food for life, a whole setting healthy and sustainable food programme, and primary school children’s consumption of fruit and vegetables: A Cross-Sectional study in England

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. The promotion of dietary health is a public health priority in England and in other countries. Research shows that the majority of children do not consume the recommended amount of fruit and vegetables (F&V). There has been relatively little research on the impact of programmes, such as Food for Life, that (a) integrate action on nutrition and food sustainability issues, and (b) are delivered as commissions in a local authority area. The study sought to assess pupil F&V in schools engaged with the Food for Life (FFL) programme. The design was a cross-sectional study comparing pupils in FFL engaged (n = 24) and non-engaged (n = 23) schools. A total of 2411 pupils aged 8-10 completed a validated self-report questionnaire. After adjusting for confounders, pupils in schools engaged with FFL consumed significantly more servings of F&V compared to pupils in comparison schools (M = 2.03/1.54, p < 0.001). Pupils in FFL schools were twice as likely to eat five or more portions of F&V per day (Odds Ratio = 2.07, p < 0.001, Confidence Interval = 1.54, 2.77). Total F&V consumption was significantly higher (p < 0.05) amongst pupils in schools with a higher level FFL award. Whilst limitations include possible residual confounding, the study suggests primary school engagement with the FFL programme may be an effective way of improving children’s dietary health

Enhanced energy density with a wide thermal stability in epitaxial Pb0.92La0.08Zr0.52Ti0.48O3 thin films

High-quality epitaxial Pb0.92La0.08Zr0.52Ti0.48O3 (PLZT) films of thickness of 880 nm were fabricated using pulsed laser deposition on (001) Nb doped SrTiO3 (Nb:STO) substrates. Besides a confirmation of the epitaxial relationship [100]PLZT//[100]Nb:STO and (001)PLZT//(001)Nb:STO using X-ray diffraction, a transmission electron microscopy study has revealed a columnar structure across the film thickness. The recoverable energy density (Wrec) of the epitaxial PLZT thin film capacitors increases linearly with the applied electric field and the best value of 31 J/cm3 observed at 2.27 MV/cm is considerably higher by 41% than that of the polycrystalline PLZT film of a comparable thickness. In addition to the high Wrec value, an excellent thermal stability as illustrated in a negligible temperature dependence of the Wrec in the temperature range from room temperature to 180 C is achieved. The enhanced Wrec and the thermal stability are attributed to the reduced defects and grain boundaries in epitaxial PLZT thin films, making them promising for energy storage applications that require both high energy density, power density, and wide operation temperatures

Adaptive restraint design for a diverse population through machine learning

ObjectiveUsing population-based simulations and machine-learning algorithms to develop an adaptive restraint system that accounts for occupant anthropometry variations to further enhance safety balance throughout the whole population.MethodsTwo thousand MADYMO full frontal impact crash simulations at 35 mph using two validated vehicle/restraint models representing a sedan and an SUV along with a parametric occupant model were conducted based on the maximal projection design of experiments, which considers varying occupant covariates (sex, stature, and body mass index) and vehicle restraint design variables (three for airbag, three for safety belt, and one for knee bolster). A Gaussian-process-based surrogate model was trained to rapidly predict occupant injury risks and the associated uncertainties. An optimization framework was formulated to seek the optimal adaptive restraint design policy that minimizes the population injury risk across a wide range of occupant sizes and shapes while maintaining a low difference in injury risks among different occupant subgroups. The effectiveness of the proposed method was tested by comparing the population-wise injury risks under the adaptive design policy and the traditional state-of-the-art design.ResultsCompared to the traditional state-of-the-art design for midsize males, the optimal design policy shows the potential to further reduce the joint injury risk (combining head, chest, and lower extremity injury risks) among the whole population in the sedan and SUV models. Specifically, the two subgroups of vulnerable occupants including tall obese males and short obese females had higher reductions in injury risks.ConclusionsThis study lays out a method to adaptively adjust vehicle restraint systems to improve safety balance. This is the first study where population-based crash simulations and machine-learning methods are used to optimize adaptive restraint designs for a diverse population. Nevertheless, this study shows the high injury risks associated with obese and female occupants, which can be mitigated via restraint adaptability

Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

Effects of systematic asymmetric discounting on physician-patient interactions: a theoretical framework to explain poor compliance with lifestyle counseling

BACKGROUND: This study advances the use of a utility model to model physician-patient interactions from the perspectives of physicians and patients. PRESENTATION OF THE HYPOTHESIS: In cases involving acute care, patient counseling involves a relatively straightforward transfer of information from the physician to a patient. The patient has less information than the physician on the impact the condition and its treatment have on utility. In decisions involving lifestyle changes, the patient may have more information than the physician on his/her utility of consumption; moreover, differences in discounting future health may contribute significantly to differences between patients' preferences and physicians' recommendations. TESTING THE HYPOTHESIS: The expectation of differences in internal discount rate between patients and their physicians is discussed. IMPLICATIONS OF THE HYPOTHESIS: This utility model provides a conceptual basis for the finding that educational approaches alone may not effect changes in patient behavior and suggests other economic variables that could be targeted in the attempt to produce healthier behavior

The Atacama Cosmology Telescope: A Measurement of the Cosmic Microwave Background Power Spectrum at 148 and 218 GHz from the 2008 Southern Survey

We present measurements of the cosmic microwave background (CMB) power spectrum made by the Atacama Cosmology Telescope at 148 GHz and 218 GHz, as well as the cross-frequency spectrum between the two channels. Our results clearly show the second through the seventh acoustic peaks in the CMB power spectrum. The measurements of these higher-order peaks provide an additional test of the {\Lambda}CDM cosmological model. At l > 3000, we detect power in excess of the primary anisotropy spectrum of the CMB. At lower multipoles 500 < l < 3000, we find evidence for gravitational lensing of the CMB in the power spectrum at the 2.8{\sigma} level. We also detect a low level of Galactic dust in our maps, which demonstrates that we can recover known faint, diffuse signals.Comment: 19 pages, 13 figures. Submitted to ApJ. This paper is a companion to Hajian et al. (2010) and Dunkley et al. (2010