Gormsenfrench3251

heir residents. In this study, it has been observed that the call light system is perceived to be an important factor affecting the outcomes of the care process and satisfaction of both residents and staff as well as the staff's performance. It is important to recognize that communication and notification technology contributes to the challenges the staff faced during their work, making their working conditions more difficult and challenging. ©Haneen Ali, Huiyang Li. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 27.03.2020.BACKGROUND Although gun violence has been identified as a major public health concern, the scope and significance of internet gun advertising is not known. OBJECTIVE This study aimed to quantify the characteristics of gun advertising on social media and to compare the reach of posts by manufacturers with those of influencers. METHODS Using a systematic search, we created a database of recent and popular Twitter and YouTube posts made public by major firearm manufacturers and influencers. From our sample of social media posts, we reviewed the content of the posts on the basis of 19 different characteristics, such as type of gun, presence of women, and military or police references. Our content analysis summarized statistical differences in the information conveyed in posts to compare advertising approaches across social media platforms. RESULTS Sample posts revealed that firearm manufacturers use social media to attract audiences to websites that sell firearms 14.1% (131/928; ±2.9) of Twitter posts, 53.6% (228 Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 27.03.2020.BACKGROUND Airline passengers often experience symptoms when travelling on long and ultra-long flights. These range from minor discomforts such as gastrointestinal symptoms to more serious life-threatening clinical conditions such as deep vein thrombosis. The food and supplement industry have responded with a plethora of products that claim to prevent one or more of the physiological or psychological symptoms associated with air travel. OBJECTIVE The aim of this literature review is to evaluate the efficacy of functional foods, beverages, and supplements that claim to address the unwanted effects of air travel in healthy adult populations. METHODS This research is a two-stage process. The first step is a scoping review of the functional foods, beverages, and supplements making claims that they lessen or prevent the physical or psychological symptoms associated with commercial air travel. Databases (ie, Medline, Embase, PsycINFO, and Web of Science), gray literature (ie, the flight catering magazines PAX Interudged using the Grading of Recommendations, Assessments, Developments, and Evaluations approach, and the risk of bias will be assessed using the appropriate Cochrane Collaboration tool (Risk of Bias for Randomized Control Trials II or Robins I for Nonrandomized Interventions). RESULTS The scoping review of available functional foods, beverages, and supplements was conducted from March 6, 2019, to August 31, 2019. The systematic literature review commenced on October 1, 2019. The review is expected to be completed in 2020. CONCLUSIONS The review findings will help consumers and employees of commercial airlines make informed decisions on their use of functional foods and beverages for alleviating air travel-related symptoms. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/16155. ©Virginia Chan, Margaret Allman-Farinelli. Originally published in JMIR Research Protocols (http//www.researchprotocols.org), 27.03.2020.Due to the curse of dimensionality of search space, it is extremely difficult for evolutionary algorithms to approximate the optimal solutions of large-scale multiobjective optimization problems (LMOPs) by using a limited budget of evaluations. If the Pareto-optimal subspace is approximated during the evolutionary process, the search space can be reduced and the difficulty encountered by evolutionary algorithms can be highly alleviated. Following the above idea, this article proposes an evolutionary algorithm to solve sparse LMOPs by learning the Pareto-optimal subspace. The proposed algorithm uses two unsupervised neural networks, a restricted Boltzmann machine, and a denoising autoencoder to learn a sparse distribution and a compact representation of the decision variables, where the combination of the learnt sparse distribution and compact representation is regarded as an approximation of the Pareto-optimal subspace. Saracatinib The genetic operators are conducted in the learnt subspace, and the resultant offspring solutions then can be mapped back to the original search space by the two neural networks. According to the experimental results on eight benchmark problems and eight real-world problems, the proposed algorithm can effectively solve sparse LMOPs with 10,000 decision variables by only 100,000 evaluations.In this article, we address the bearing-only formation control problem of 3-D networked robotic systems with parametric uncertainties. The contributions of this article are two-fold 1) the bearing-rigid theory is extended to solve the nonlinear robotic systems with the Euler-Lagrange-like model and 2) a novel almost global stable distributed bearing-only formation control law is proposed for the nonlinear robotic systems. Specifically, the robotic systems subject to nonholonomic constraints and dynamics are first transformed into a Euler-Lagrange-like model. By exploring the bearing-rigid graph theory, a backstepping approach is used to design the distributed formation controller. Simulations for 3-D robotics are given to demonstrate the effectiveness of the proposed control law. Compared to the distance-rigid formation control approach, the bearing-rigid approach guarantees almost global stability while naturally excluding flip ambiguities.Band selection has become a significant issue for the efficiency of the hyperspectral image (HSI) processing. Although many unsupervised band selection (UBS) approaches have been developed in the last decades, a flexible and robust method is still lacking. The lack of proper understanding of the HSI data structure has resulted in the inconsistency in the outcome of UBS. Besides, most of the UBS methods are either relying on complicated measurements or rather noise sensitive, which hinder the efficiency of the determined band subset. In this article, an adaptive distance-based band hierarchy (ADBH) clustering framework is proposed for UBS in HSI, which can help to avoid the noisy bands while reflecting the hierarchical data structure of HSI. With a tree hierarchy-based framework, we can acquire any number of band subset. By introducing a novel adaptive distance into the hierarchy, the similarity between bands and band groups can be computed straightforward while reducing the effect of noisy bands. Experiments on four datasets acquired from two HSI systems have fully validated the superiority of the proposed framework.