Using Hybrid Angle/Distance Information for Distributed Topology Control in Vehicular Sensor Networks

In a vehicular sensor network (VSN), the key design issue is how to organize vehicles effectively, such that the local network topology can be stabilized quickly. In this work, each vehicle with on-board sensors can be considered as a local controller associated with a group of communication members. In order to balance the load among the nodes and govern the local topology change, a group formation scheme using localized criteria is implemented. The proposed distributed topology control method focuses on reducing the rate of group member change and avoiding the unnecessary information exchange. Two major phases are sequentially applied to choose the group members of each vehicle using hybrid angle/distance information. The operation of Phase I is based on the concept of the cone-based method, which can select the desired vehicles quickly. Afterwards, the proposed time-slot method is further applied to stabilize the network topology. Given the network structure in Phase I, a routing scheme is presented in Phase II. The network behaviors are explored through simulation and analysis in a variety of scenarios. The results show that the proposed mechanism is a scalable and effective control framework for VSNs

TCN AA: A Wi Fi based Temporal Convolution Network for Human to Human Interaction Recognition with Augmentation and Attention

The utilization of Wi-Fi-based human activity recognition (HAR) has gained considerable interest in recent times, primarily owing to its applications in various domains such as healthcare for monitoring breath and heart rate, security, elderly care, and others. These Wi-Fi-based methods exhibit several advantages over conventional state-of-the-art techniques that rely on cameras and sensors, including lower costs and ease of deployment. However, a significant challenge associated with Wi-Fi-based HAR is the significant decline in performance when the scene or subject changes. To mitigate this issue, it is imperative to train the model using an extensive dataset. In recent studies, the utilization of CNN-based models or sequence-to-sequence models such as LSTM, GRU, or Transformer has become prevalent. While sequence-to-sequence models can be more precise, they are also more computationally intensive and require a larger amount of training data. To tackle these limitations, we propose a novel approach that leverages a temporal convolution network with augmentations and attention, referred to as TCN-AA. Our proposed method is computationally efficient and exhibits improved accuracy even when the data size is increased threefold through our augmentation techniques. Our experiments on a publicly available dataset indicate that our approach outperforms existing state-of-the-art methods, with a final accuracy of 99.42%.Comment: Published to IEEE Internet of things Journal but haven't been accepted yet (under review

Ankle-Brachial Index Is a Powerful Predictor of Renal Outcome and Cardiovascular Events in Patients with Chronic Kidney Disease

Ankle-brachial index (ABI) is an accurate tool to diagnose peripheral arterial disease. The aim of this study was to evaluate whether ABI is also a good predictor of renal outcome and cardiovascular events in patients with chronic kidney disease (CKD). We enrolled 436 patients with stage 3–5 CKD who had not been undergoing dialysis. Patients were stratified into two groups according to the ABI value with a cut point of 0.9. The composite renal outcome, including doubling of serum creatinine level and commencement of dialysis, and the incidence of cardiovascular events were compared between the two groups. After a median follow-up period of 13 months, the lower ABI group had a poorer composite renal outcome (OR = 2.719, P = 0.015) and a higher incidence of cardiovascular events (OR = 3.260, P = 0.001). Our findings illustrated that ABI is a powerful predictor of cardiovascular events and renal outcome in patients with CKD

Experimental observation of flat focusing mirror based on photonic jet effect

In this work, we experimentally demonstrate that a thin rectangle dielectric-metal structure can have a function of a flat focusing mirror based on photonic jet effect in reflection mode. Using polydimethylsiloxane (PDMS) rectangle with size length of 10 µm and wavelength-scale thickness of 1 µm on the top of a silicon wafer, we have built a flat mirror which focuses an incident beam at the focal length changing from 1.38 µm to 11.67 µm upon tuning the beam incidence angle from 30° to 75°. The focusing properties of such a mirror persist in the wavelength range of 405¿nm to 671¿nm. Our approach can be extended to realize other optical functionalities by properly controlling rectangle dimensions and materials. This flat focusing mirror is able to guide the incident beam in free space without perceptible diffraction at the distance equal to the photonic jet length and suitable for small-scale photonic circuits.Postprint (published version

CR3 and Dectin-1 Collaborate in Macrophage Cytokine Response through Association on Lipid Rafts and Activation of Syk-JNK-AP-1 Pathway

Copyright: © 2015 Huang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Acknowledgments We are grateful to the Second Core Laboratory of Research Core Facility at the National Taiwan University Hospital for confocal microscopy service and providing ultracentrifuge. We thank Dr. William E. Goldman (University of North Carolina, Chapel Hill, NC) for kindly providing WT and ags1-null mutant of H. capsulatum G186A. Funding: This work is supported by research grants 101-2320-B-002-030-MY3 from the Ministry of Science and Technology (http://www.most.gov.tw) and AS-101-TP-B06-3 from Academia Sinica (http://www.sinica.edu.tw) to BAWH. GDB is funded by research grant 102705 from Welcome Trust (http://www.wellcome.ac.uk). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD