J Interpers Violence

Homicide-suicide incidents involving child victims can have a detrimental impact on survivors of the violence, family members and friends of the decedents, and other community members, but the rare occurrence of these acts makes using quantitative data to examine their associated antecedents challenging. Therefore, using qualitative data from the 2003-2011 National Violent Death Reporting System, we examined 175 cases of homicide-suicide involving child victims in an effort to better understand the complex situational factors of these events. Our findings indicate that 98% of homicide-suicides with child victims are perpetrated by adults (mostly parents) and propelled by the perpetrators' intimate partner problems, mental health problems, and criminal/legal problems. These events are often premeditated, and plans for the violence are sometimes disclosed prior to its occurrence. Findings provide support for several theoretical perspectives, and implications for prevention are discussed.CC999999/Intramural CDC HHS/United States2019-02-01T00:00:00Z26385898PMC4795978vault:1634

Predicting online product sales via online reviews, sentiments, and promotion strategies

Purpose – The purpose of this paper is to investigate if online reviews (e.g. valence and volume), online promotional strategies (e.g. free delivery and discounts) and sentiments from user reviews can help predict product sales. Design/methodology/approach – The authors designed a big data architecture and deployed Node.js agents for scraping the Amazon.com pages using asynchronous input/output calls. The completed web crawling and scraping data sets were then preprocessed for sentimental and neural network analysis. The neural network was employed to examine which variables in the study are important predictors of product sales. Findings – This study found that although online reviews, online promotional strategies and online sentiments can all predict product sales, some variables are more important predictors than others. The authors found that the interplay effects of these variables become more important variables than the individual variables themselves. For example, online volume interactions with sentiments and discounts are more important than the individual predictors of discounts, sentiments or online volume. Originality/value – This study designed big data architecture, in combination with sentimental and neural network analysis that can facilitate future business research for predicting product sales in an online environment. This study also employed a predictive analytic approach (e.g. neural network) to examine the variables, and this approach is useful for future data analysis in a big data environment where prediction can have more practical implications than significance testing. This study also examined the interplay between online reviews, sentiments and promotional strategies, which up to now have mostly been examined individually in previous studies

Identification of material properties of orthotropic composite plate using hybrid non-destructive evaluation approach

Identification of material properties is one of the key issues in composite materials research. The mechanical properties of composite materials depend on diverse factors such as configuration of the laminates, constituent materials used and production method adopted. Conventional testing approach tends to be time-consuming, expensive and destructive. As an alternative, a rapid, inexpensive, hybrid and non-destructive evaluation approach which utilises experimental modal analysis and finite element analysis is proposed. Experimental modal data which consist of natural frequencies and mode shapes of an orthotropic composite plate are utilised for correlation purpose with its finite element model. This finite element model of the composite plate is continuously updated and achieves less than 5% in difference of natural frequencies and over 70% in modal assurance criterion. Material properties such as Young's moduli, inplane shear modulus and Poisson ratio of the composite plate are then successfully determined using the well-correlated FE model

Energy Harvesting Based on a Novel Piezoelectric 0.7PbZn0.3Ti0.7O3-0.3Na2TiO3 Nanogenerator

Recently, piezoelectric materials have achieved remarkable attention for charging wireless sensor nodes. Among piezoelectric materials, non-ferroelectric materials are more cost effective because they can be prepared without a polarization process. In this study, a non-ferroelectric nanogenerator was manufactured from 0.7PbZn0.3Ti0.7O3-0.3Na2TiO3 (PZnT-NT). It was demonstrated that the increment of conductivity via adding the Na2TiO3 plays an essential role in increasing the permittivity of the non-ferroelectric nanogenerator and hence improved the generated power density. The dielectric measurements of this material demonstrated high conductivity that quenched the polarization phase. The performance of the device was studied experimentally over a cantilever test rig; the vibrating cantilever (0.4 ms-2) was excited by a motor operated at 30 Hz. The generated power successfully illuminated a light emitting diode (LED). The PZnT-NT nanogenerator produced a volume power density of 0.10 μw/mm3 and a surface power density of 10 μw/cm2. The performance of the proposed device with a size of (20 × 15 × 1 mm3) was higher in terms of power output than that of the commercial microfiber composite (MFC) (80 × 57 × 0.335 mm3) and piezoelectric bimorph device (70 × 50 × 0.7 mm3). Compared to other existing ferroelectric and non-ferroelectric nanogenerators, the proposed device demonstrated great performance in harvesting the energy at low acceleration and in a low frequency environment

Interaction studies between high-density oil and sand particles in oil flotation technology

In the event of a sand contamination, the first course of action would be to ensure that a successful flotation is through the detachment of oil from sand for the ease of flotation. It is widely recognized that the initial oil-sand contact is crucial for oil removal and recovery. Due to its high viscosity and adhesive nature, high density bunker oil could pick up any silica particles (sand) of any size at a short contact time as low as several milliseconds. Nevertheless, the resulting detachment of sand particles from oil would vary under different conditions. Therefore, this study aims at investigating the interactions between oil and sand to further understand the detachment process between oil and sand in a flotation process under various conditions including pH, temperature, sand particle size and wettability. An increase in the water content in the sand sample from 0 wt to 12 wt aids the liberation of oil from contaminated sand from 0.7 to 65, due to the presence of thin film of water which weakens the attachment forces between the oil and sand particles. On the other hand, the coarse sand particles of 1.0 mm easily detach themselves from the oil layer compared to finer sand particles of 0.125 mm which implicate that the attachment forces between oil and said particles increase with the decrease in sand particle size. An increase in the solution pH from pH 6 to pH 14 and temperature from 20 degrees C to 60 degrees C also showed an increase in the sand detachment efficiencies from 25.1 to 60.9, and from 15.2 to 85.1 respectively for 1 mm sand particle size. Further verification experiments including the differential zeta potential results and the DLVO theory supported the results of these former detachment studies, whereby differential zeta potential results showed that increase in pH increased the repulsive forces between particles, while the increase in temperature did not significantly affect the interparticle forces. Hence, the enhanced detachment efficiency due to increase in temperature is mainly attributed to the decrease in oil viscosity which reduces the adhesiveness of bunker oil which also facilitates oil liberation. Finally, the results are in good agreement with the oil flotation efficiencies. (C) 2015 Elsevier B.V. All rights reserved

Integration of Unmanned Aerial Systems in Class E Airspace: The Effect on Air Traffic Controller Workload

As technology rapidly advances and our imagination is no longer fantasy but instead reality, the aviation community needs to concentrate on the harsh truth of airspace safety. In the situation of integrating unmanned aerial systems (UASs) into the National airspace, UASs outside of terminal areas would generally be permitted to fly their preferred routes, and self-separate, with minimal intervention from air traffic control. From an air traffic control perspective, the integration could raise a number of human performance problems including workload extremes and passive-monitoring demands. One fundamental requirement for operation in the National Air Space is to preserve the safety of the general public. This paper describes an experimental evaluation of the effect different levels of UAS intent information has on air traffic controller workload. The simulation specifically manipulates intent sharing, that is, whether unmanned aerial vehicles provided advance notice of their intended maneuvers. The Effects on air traffic controller workload when control capability is altered were also explored

Advances and challenges in grid tied photovoltaic systems

Photovoltaic (PV) technology is gathering momentum around the word. Global PV energy harvest has been more than doubled since 2010. Grid connected PV (GCPV) systems can be found in different scales classified into three categories of small scale, medium scale and utility scale. Considering size of the system various configurations are suggested for the GCPV systems while each configuration might be assessed by factors such as efficiency, reliability, expandability and cost. Moreover, high integration of GCPV systems into the power system network creates several technical problems mostly coming from the intermittent nature of solar energy. In addition, to achieve a higher degree of power system reliability, GCPV systems are required to support the grid in abnormal condition such a faults and deviation from standard frequency. This paper provides a comprehensive review on GCPV systems. Various configuration proposed by the literature will be discussed. Cost study and impact of technical and environmental factors on the total expense and revenue of GCPV installation will be investigated. Different aspects of PV integration into the power network will be discussed. Problem and solutions will be studied as well. Finally grid requirements and active and reactive power support will be reviewed. (C) 2015 Elsevier Ltd. All rights reserved

Impact force identification with pseudo-inverse method on a lightweight structure for under-determined, even-determined and over-determined cases

Force identification using inverse technique is important especially when direct measurement through force transducer is not possible. Considering the effects of impact excitation force on the integrity of a lightweight structure, impact force identification has become the subject of several studies. A methodology utilising Operating Deflection Shape (ODS) analysis, Frequency Response Function (FRF) measurement and pseudo-inverse method to evaluate the dynamic force is presented. A rectangular plate with four ground supports was used as a test rig to simulate the motions of a simple vehicle body. By using the measured responses at remote points that are away from impact locations and measured FRFs of the test rig, unknown force locations and their time histories can be recovered by the proposed method. The performance of this approach in various cases such as under-determined, even-determined and over-determined cases was experimentally demonstrated. Good and bad combinations of response locations were selected based on the condition number of FRF matrix. This force identification method was examined under different response combinations and various numbers of response locations. It shows that in the over-determined case, good combination of response locations (i.e. low average of condition number of FRF matrix) and high number of response locations give the best accuracy of force identification result compared to under-determined and even-determined cases

Patterns of psychological responses among the public during the early phase of COVID-19: A cross-regional analysis

This study aimed to compare the mediation of psychological flexibility, prosociality and coping in the impacts of illness perceptions toward COVID-19 on mental health among seven regions. Convenience sampled online survey was conducted between April and June 2020 from 9130 citizens in 21 countries. Illness perceptions toward COVID-19, psychological flexibility, prosociality, coping and mental health, socio-demographics, lockdown-related variables and COVID-19 status were assessed. Results showed that psychological flexibility was the only significant mediator in the relationship between illness perceptions toward COVID-19 and mental health across all regions (all ps = 0.001–0.021). Seeking social support was the significant mediator across subgroups (all ps range = <0.001–0.005) except from the Hong Kong sample (p = 0.06) and the North and South American sample (p = 0.53). No mediation was found for problem-solving (except from the Northern European sample, p = 0.009). Prosociality was the significant mediator in the Hong Kong sample (p =0.016) and the Eastern European sample (p = 0.008). These findings indicate that fostering psychological flexibility may help to mitigate the adverse mental impacts of COVID-19 across regions. Roles of seeking social support, problem-solving and prosociality vary across regions. © 2021 by the authors. Licensee MDPI, Basel, Switzerland