Navigating the Web in Search of Resources on Antimicrobial Stewardship in Health Care Institutions

Bacterial resistance to antimicrobials has become a public health threat for which coordinated action at the international, national, and local level is needed. Current recommendations for the control of antimicrobial overuse and resistance in hospitals recommend various strategies, including antimicrobial stewardship programs. Several of these integrated and multidisciplinary antimicrobial management programs provide detailed information and recommendations on the Web. We performed a search of the most relevant and authoritative Web sites in English that were available without need for special registration or cost. The search excluded community-based programs, and we present only established programs or those providing expert information useful for building a hospital-based antimicrobial stewardship program. The overview of these Web sites may be useful either for institutions or individuals planning to implement such programs in their own health care institution or for educational purposes targeted at different professionals involved in improving antimicrobial practic

Auto-FACE: An NMR Based Binding Site Mapping Program for Fast Chemical Exchange Protein-Ligand Systems

10.1371/journal.pone.0008943PLoS ONE52

Cooperative video transmission strategies via caching in small-cell networks

Small-cell network is a promising solution to the high video traffic. However, it has some fundamental problems, i.e., high backhaul cost, quality of experience (QoE) and interference. To address these issues, we propose a cooperative transmission strategy for video transmission in small-cell networks with caching. In the scheme, each video file is encoded into segments using a maximum distance separable rateless code. Then, a portion of each segment is cached at a certain small-cell base station (SBS), so that the SBSs can cooperatively transmit these segments to users without incurring high backhaul cost. When there is only one active user in the network, a greedy algorithm is utilized to deliver the video-file segment from the SBS with good channel state to the user watching videos in real time. This reduces video freezes and improves the QoE. When there exist several active users, interference will appear among them. To deal with interference, interference alignment (IA) is adopted. Based on the scheme for a single user, the greedy algorithm and IA are combined to transmit video-file segments to these users, and the performance of the system can be significantly improved. Simulation results are presented to show the effectiveness of the proposed scheme

Caching UAV-enabled small-cell networks

Unmanned aerial vehicles (UAVs) can be utilized to provide flexible wireless access in future wireless networks, with larger coverage and higher transmission rate. However, the wireless backhaul for UAVs is usually capacity-limited and congested, and UAVs cannot operate for a long time due to the limited battery life. In this paper, a framework of caching UAV-enabled small-cell networks is proposed, to offload data traffic for the small-cell base stations via caching. In the proposed scheme, the most popular contents are stored at the local caches of UAVs in advance, which can be delivered to mobile users directly from the caches when required. Thus, the congestion of wireless backhaul can be alleviated, the energy consumption can be reduced, and the quality of experience can be improved

Accelerating Wireless Federated Learning via Nesterov's Momentum and Distributed Principle Component Analysis

A wireless federated learning system is investigated by allowing a server and workers to exchange uncoded information via orthogonal wireless channels. Since the workers frequently upload local gradients to the server via bandwidth-limited channels, the uplink transmission from the workers to the server becomes a communication bottleneck. Therefore, a one-shot distributed principle component analysis (PCA) is leveraged to reduce the dimension of uploaded gradients such that the communication bottleneck is relieved. A PCA-based wireless federated learning (PCA-WFL) algorithm and its accelerated version (i.e., PCA-AWFL) are proposed based on the low-dimensional gradients and the Nesterov's momentum. For the non-convex loss functions, a finite-time analysis is performed to quantify the impacts of system hyper-parameters on the convergence of the PCA-WFL and PCA-AWFL algorithms. The PCA-AWFL algorithm is theoretically certified to converge faster than the PCA-WFL algorithm. Besides, the convergence rates of PCA-WFL and PCA-AWFL algorithms quantitatively reveal the linear speedup with respect to the number of workers over the vanilla gradient descent algorithm. Numerical results are used to demonstrate the improved convergence rates of the proposed PCA-WFL and PCA-AWFL algorithms over the benchmarks