Improving the quality of healthcare and the prospects of "aging in place" using wireless sensor technology requires solving difficult problems in scale, energy management, data access, security, and privacy. We present AlarmNet, a novel system for assisted-living and residential monitoring that uses a two-way flow of data and analysis between the front and back-ends to enable context-aware protocols that are tailored to residents' individual patterns of living.AlarmNet integrates environmental, physiological, and activity sensors in a scalable, heterogeneous architecture.The SenQ query protocol provides real-time access to data and lightweight in-network processing. Circadian Activity Rhythm (CAR) analysis learns resident activity patterns and feeds them back into the network to aid context-aware power management and dynamic privacy policies.

Outbreaks in fish of motile Aeromonad septicemia (MAS) caused by Aeromonas hydrophila have caused a great concern worldwide. Here, for the first time, we provide two complete genomes of epidemic A. hydrophila strains isolated in China. To gain an insight into the pathogenicity of epidemic A. hydrophila, we performed comparative genomic analyses of five epidemic strains belonging to sequence type (ST) 251, together with the environmental strain ATCC 7966T. We found that the known virulence factors, including a type III secretion system, a type VI secretion system and lateral flagella, are not required for the high virulence of the ST251 clonal group. Additionally, our work identifies three utilization pathways for myo-inositol, sialic acid and L-fucose providing clues regarding the factors that underlie the epidemic and virulent nature of ST251 A. hydrophila. Based on the geographical distribution and biological resources of the ST251 clonal group, we conclude that ST251 is a high-risk clonal group of A. hydrophila which may be responsible for the MAS outbreaks in China and the southeastern United States.

This paper demonstrates how to use multiple channels to improve communication performance in Wireless Sensor Networks (WSNs). We first investigate multi-channel realities in WSNs through intensive empirical experiments with Micaz motes. Our study shows that current multi-channel protocols are not suitable for WSNs, because of the small number of available channels and unavoidable time errors found in real networks. With these observations, we propose a novel tree-based multichannel scheme for data collection applications, which allocates channels to disjoint trees and exploits parallel transmissions among trees. In order to minimize interference within trees, we define a new channel assignment problem which is proven NPcomplete. Then we propose a greedy channel allocation algorithm which outperforms other schemes in dense networks with a small number of channels. We implement our protocol, called TMCP, in a real testbed. Through both simulation and real experiments, we show that TMCP can significantly improve network throughput and reduce packet losses. More importantly, evaluation results show that TMCP better accommodates multi-channel realities found in WSNs than other multi-channel protocols.

Abstract-This paper demonstrates how to use multiple channels to improve communication performance in Wireless Sensor Networks (WSNs). We first investigate multi-channel realities in WSNs through intensive empirical experiments with Micaz motes. Our study shows that current multi-channel protocols are not suitable for WSNs, because of the small number of available channels and unavoidable time errors found in real networks. With these observations, we propose a novel tree-based multichannel scheme for data collection applications, which allocates channels to disjoint trees and exploits parallel transmissions among trees. In order to minimize interference within trees, we define a new channel assignment problem which is proven NPcomplete. Then we propose a greedy channel allocation algorithm which outperforms other schemes in dense networks with a small number of channels. We implement our protocol, called TMCP, in a real testbed. Through both simulation and real experiments, we show that TMCP can significantly improve network throughput and reduce packet losses. More importantly, evaluation results show that TMCP better accommodates multi-channel realities found in WSNs than other multi-channel protocols.

Background Many studies have reported the predictive value of the atherogenic index of plasma (AIP) in the progression of atherosclerosis and the prognosis of percutaneous coronary intervention (PCI). However, the utility of the AIP for prediction is unknown after PCI among type 2 diabetes mellitus (T2DM). Methods 2356 patients with T2DM who underwent PCI were enrolled and followed up for 4 years. The primary outcome was major cardiovascular and cerebrovascular adverse events (MACCEs), considered to be a combination of cardiogenic death, myocardial infarction, repeated revascularization, and stroke. Secondary endpoints included all-cause mortality, target vessel revascularization (TVR), and non-target vessel revascularization (non-TVR). Multivariate Cox proportional hazards regression modelling found that the AIP was correlated with prognosis and verified by multiple models. According to the optimal cut-off point of the ROC curve, the population was divided into high/low-AIP groups. A total of 821 pairs were successfully matched using propensity score matching. Then, survival analysis was performed on both groups. Results The overall incidence of MACCEs was 20.50% during a median of 47.50 months of follow-up. The multivariate Cox proportional hazards regression analysis before matching suggested that the AIP was an independent risk factor for the prognosis of T2DM after PCI (hazard ratio [HR] 1.528, 95% CI 1.100–2.123, P = 0.011). According to the survival analysis of the matched population, the prognosis of the high AIP group was significantly worse than that of the low AIP group (HR (95% CI) 1.614 (1.303–2.001), P < 0.001), and the difference was mainly caused by repeat revascularization. The low-density lipoprotein-cholesterol (LDL-C) level did not affect the prognosis of patients with T2DM (P = 0.169), and the effect of the AIP on prognosis was also not affected by LDL-C level (P < 0.001). Conclusions The AIP, a comprehensive index of lipid management in patients with T2DM, affects prognosis after PCI. The prognosis of diabetic patients with high levels of the AIP included more MACCEs and was not affected by LDL-C levels. It is recommended to monitor the AIP for lipid management in diabetic patients after PCI and ensure that the AIP is not higher than 0.318. Trial registration This is an observational cohort study that does not involve interventions. So we didn’t register. We guarantee that the research is authentic and reliable, and hope that your journal can give us a chance.