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This work proposes a new approach in addressing Economic Load Dispatch (ELD) optimization problem in power unit systems using nature-inspired metaheuristics search algorithms. Solving such a problem requires a degree of maximization of the economic pact of a power network system, where this is possible with some existing population-based metaheuristic search algorithms. The key issue to be handled here is how to maximize the economic benevolence of a power network under a variety of operational constraints, taking into account the reduction in the generated fuel cost as well as the aggregate power loss in the transmission power network system. Some nature-inspired metaheuristics will be explored. Meanwhile, we shall focus our attention on a newly developed nature-inspired search algorithm, referred to as the Crow Search Algorithm or CSA for short, as well as the Differential Evolution (DE) that is commonly known as a metaheuristic. The CSA emerged to light by simulating the intelligent flocking behavior of crows. The practicability of the proposed approach-based CSA was conducted to common types of power generators, including three and six buses (nodes) in addition to the IEEE 30-bus standard system. The results of the presented approaches were compared to other results developed using existing nature-inspired metaheuristic algorithms like particle swarm optimization and genetic algorithms and also compared to traditional approaches such as quadratic programming method. The results reported here support that CSA has achieved an outstanding performance in solving the problem of ELD in power systems, demonstrating their good optimization capabilities through arriving at a combination of power loads that consummate the constraints of the ELD problem while simultaneously lessening the entire fuel cost. The experimental results also showed that the CSA solutions were capable of maximizing the reliability of the power supplied to the customers, and also reducing both the generated power cost and the loss of power in the transmission power systems.

Regrettably, a large proportion of likely patients with sleep apnea are underdiagnosed. Obstructive sleep apnea (OSA) is one of the main causes of hypertension, type II diabetes, stroke, coronary artery disease, and heart failure. OSA affects not only adults but also children where it forms one of the sources of learning disabilities for children. This study aims to provide a classification model for one of the well-known sleep disorders known as OSA, which causes a serious malady that affects both men and women. OSA affects both genders with different scope. Men versus women diagnosed with OSA are about 8:1. In this research, logistic regression (LR) and artificial neural networks were applied successfully in several classification applications with promising results, particularly in the bio-statistics area. LR was used to derive a membership probability for a potential OSA system from a range of anthropometric features including weight, height, body mass index (BMI), hip, waist, age, neck circumference, modified Friedman, snoring, Epworth sleepiness scale (ESS), sex, and daytime sleepiness. We developed two models to predict OSA, one for men and one for women. The proposed sleep apnea diagnosis model has yielded accurate classification results and possibly a prototype software module that can be used at home. These findings shall reduce the patient’s need to spend a night at a laboratory and make the study of sleep apnea to implement at home.

The Inside-Out Prison Exchange Program is an experiential learning program that involves teaching college courses inside correctional facilitates to classes that include incarcerated and nonincarcerated students. This teaching note describes the program and argues that its congruence with social work values makes it a valuable tool for preparing students to take on social justice work. The impact of the program’s pedagogy and structure on students’ and faculty’s capacity for critical thinking and self-reflection is described. Logistical issues to consider in developing programs are discussed.

We investigate the impact of prior alliance relationships on subsequent mergers between partner firms. We argue that an acquirer’s prior alliance experience with the target reduces information asymmetry, which helps improve acquisition performance. Alternatively, agency problems arising from familiarity may lead to inefficient decision making. Examining mergers between 1986 and 2014, we find evidence that prior alliance collaboration is positively associated with the acquirer’s long-term profitability and growth. This positive effect is more pronounced when target-specific learning and experience are more crucial to merger success, such as targets in knowledge-intensive or organizational-capital-intensive industries as well as cross-industry mergers. However, we cannot formally rule out the possibility that our results are partly driven by the small size of our sample.

For courses in family law for students in paralegal studies programs, broader legal studies programs, and those majoring in criminal justice, social work, and education. Connecting theory, history, and practice in family law Family Law and Practice prepares students to enter the workplace with a firm grasp of family law and procedural components of family law practice. To meet this challenge, the authors have divided the 5th edition into two parts: the first introducing the principles of family law and the second translating theory into practice. The new edition also addresses changing views on marriage, spousal roles, children’s status in the family, and even what constitutes a family. It also adds cases, statutes, and legal forms from a variety of US states to engage students across the country.

This paper is a sequel to [8] where we introduced an invariant, called canonical degree, of Cohen–Macaulay local rings that admit a canonical ideal. Here to each such ring R with a canonical ideal, we attach a different invariant, called bi-canonical degree, which in dimension 1 appears also in [12] as the residue of R. The minimal values of these functions characterize specific classes of Cohen–Macaulay rings. We give a uniform presentation of such degrees and discuss some computational opportunities offered by the bi-canonical degree. © 2019 Elsevier Inc.

The popular business media argues that the “fear of missing out” (FoMO) on work-related opportunities harms employees’ health and performance. Yet, these claims rely on the study of FoMO in college students in non-work contexts. Therefore, we explored workplace FoMO among employees across three studies. We first developed a measure and provided validation evidence for workplace FoMO among diverse employees (N = 324; Study 1) and MBA students (N = 223; Study 2). Using a third large employee sample (N = 300; Study 3), we tested whether workplace FoMO predicted health (i.e., work burnout and work well-being) and motivational outcomes (i.e., message-checking behaviors and work engagement). We also examined whether family-supportive organizational perceptions (FSOP) moderated these relationships. Results indicated that workplace FoMO is a distinct construct from other measures, including general FoMO. Workplace FoMO also predicted work burnout and message checking behavior, but not work well-being. Lower levels of FSOP strengthened the positive relationship between workplace FoMO and message checking behavior, but also produced a positive relationship between workplace FoMO and work well-being. Overall, FoMO appears to be relevant to the work context and predicts both employee well-being and behavior outcomes. © 2019 Elsevier Ltd

In this study, we examine the intra-industry effect of proxy contests. Proxy contests convey the information of common industrial risks or expected competitive relationship change. We find significant negative abnormal returns in the group of competitors of target firms with negative abnormal returns, and such negative abnormal returns become larger for similar-size competitors. In contrast, there are no significant abnormal returns for competitors of target firms with positive abnormal returns. These findings are consistent with the information-based theory but not the competitive theory. © 2019, Academy of Economics and Finance.