The recent ratification of IEEE 802.15.4 PHY-MAC specifications for low-rate wireless personal area networks represents a significant milestone in promoting deployment of wireless sensor networks (WSNs) for a variety of commercial uses. The 15.4 specifications specifically target wireless networking among low rate, low power and low cost devices that is expected to be a key market segment for a large number of WSN applications. In this paper, we first analyze the performance of the contention access period specified in IEEE 802.15.4 standard, in terms of throughput and energy consumption. This analysis is facilitated by a modeling of the contention access period as non-persistent CSMA with backoff. We show that in certain applications, in which having an inactive period in the superframe may not be desirable due to delay constraints, shutting down the radio between transmissions provides significant savings in power without significantly compromising the throughput. We also propose and analyze the performance of a modification to the specification which could be used for applications in which MAC-level acknowledgements are not used. Extensive ns-2 simulations are used to verify the analysis.

Abstract-Wireless multicast/broadcast sessions, unlike wired networks, inherently reaches several nodes with a single transmission. For omnidirectional wireless broadcast to a node, all nodes closer will also be reached. An algorithm for constructing the minimum power tree in wireless networks was first proposed by Wieselthier Ø Ð. The ÖÓ ×Ø Ò Ö Ñ ÒØ Ð ÔÓÛ Ö (BIP) algorithm suggested by them is a "node-based" minimum-cost tree algorithm for wireless networks. We propose an alternate search based paradigm wherein minimum-cost trees in wireless networks are found through a search process. Two computationally efficient procedures for checking the feasibility (viability) of a solution in the search space are presented. A straightforward procedure for initializing the search using stochastically generated trees is also proposed.

Abstract-The combination of multiple radio nodes in conjunction with a suitably structured multi-hop or mesh architecture has the potential to solve some of the key limitations of present day wireless access networks that are based on single-radio nodes. This paper addresses the channel assignment problem for multi-channel multi-interface (radio) wireless mesh networks. We focus on static wireless mesh networks where multiple nonoverlapping channels are available for each wireless interface. In this network environment, our objective is to find a fixed channel assignment which maximizes the number of bidirectional links that can be activated simultaneously, subject to interference constraints. We present two mixed integer linear programming models for solving the fixed channel assignment problem with multiple radios. Detailed computational results on various grid topologies are also presented and discussed.

Introduction The COVID-19 pandemic has impacted biopsychosocial health and wellbeing globally. Pre-pandemic studies suggest a high prevalence of common mental disorders, including anxiety and depression in South Asian countries, which may aggravate during this pandemic. This systematic meta-analytic review was conducted to estimate the pooled prevalence of anxiety and depression in South Asian countries during the COVID-19 pandemic. Method We systematically searched for cross-sectional studies on eight major bibliographic databases and additional sources up to October 12, 2020, that reported the prevalence of anxiety or depression in any of the eight South Asian countries. A random-effects model was used to calculate the pooled proportion of anxiety and depression. Results A total of 35 studies representing 41,402 participants were included in this review. The pooled prevalence of anxiety in 31 studies with a pooled sample of 28,877 was 41.3% (95% confidence interval [CI]: 34.7–48.1, I 2 = 99.18%). Moreover, the pooled prevalence of depression was 34.1% (95% CI: 28.9–39.4, I 2 = 99%) among 37,437 participants in 28 studies. Among the South Asian countries, India had a higher number of studies, whereas Bangladesh and Pakistan had a higher pooled prevalence of anxiety and depression. No studies were identified from Afghanistan, Bhutan, and Maldives. Studies in this review had high heterogeneity, high publication bias confirmed by Egger's test, and varying prevalence rates across sub-groups. Conclusion South Asian countries have high prevalence rates of anxiety and depression, suggesting a heavy psychosocial burden during this pandemic. Clinical and public mental health interventions should be prioritized alongside improving the social determinants of mental health in these countries. Lastly, a low number of studies with high heterogeneity requires further research exploring the psychosocial epidemiology during COVID-19, which may inform better mental health policymaking and practice in South Asia.

PurposeThe purpose of this paper is to provide an understanding of different explanations in mergers and acquisitions (M&A) research that deal with M&A performance. After five decades of M&A research, the findings on M&A performance are diverse and sometimes inconsistent with each other. The explanatory variables studied in the empirical works reflect primarily on researchers’ approach, construct, measurement techniques and data availability, leading to inconsistencies among the findings. In order to understand how researchers have measured M&A performance so far, the gaps in existing work and to identify the scope of future work, the authors conduct a systematic review of empirical M&A research on explaining M&A performance.Design/methodology/approachThis research has been carried out as a structured assessment of past literature. The findings from selected research works have been categorized, grouped and summarized to discern a meta‐analytic view of the work carried out to date.FindingsThe M&A performance measures are diverse owing to heterogeneous views on what constitutes M&A performance and organization performance. They are categorized under Accounting Measures, Market Measures and Other Measures, including subjective assessments. The explanatory variables found in the studies are extensive and can be categorized under Deal Characteristics, Managerial Effects, Firm Characteristics and Environmental Factors.Originality/valueThe paper extracts some key trends in M&A performance studies carried out in empirical works over two decades. The findings help to identify drawbacks and set an agenda for future work.

Abstract-Broadcasting in wireless networks, unlike wired networks, inherently reaches several nodes with a single transmission. For omni-directional wireless broadcast to a node, all nodes closer will also be reached. This property can be used to compute routing trees which minimize the sum of the transmitter powers. It has been shown that this problem is NP-complete. In this paper, we present the r-shrink procedure, a heuristic for improving the solutions obtained using fast sub-optimal algorithms. Specifically, we focus on the lowcomplexity BIP algorithm and Prim's minimum spanning tree algorithm and show through extensive simulations that better solutions are obtained almost always, with considerably lower tree power, if the proposed procedure is used to improve the trees generated using these algorithms.

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