An Environment-Friendly Multipath Routing Protocol for Underwater Acoustic Sensor Network

Underwater Acoustic Sensor Network (UASN) is a promising technique by facilitating a wide range of aquatic applications. However, routing scheme in UASN is a challenging task because of the characteristics of the nodes mobility, interruption of link, and interference caused by other underwater acoustic systems such as marine mammals. In order to achieve reliable data delivery in UASN, in this work, we present a disjoint multipath disruption-tolerant routing protocol for UASN (ENMR), which incorporates the Hue, Saturation, and Value color space (HSV) model to establish routing paths to greedily forward data packets to sink nodes. ENMR applies the mechanism to maintain the network topology. Simulation results show that, compared with the classic underwater routing protocols named PVBF, ENMR can improve packet delivery ratio and reduce network latency while avoiding introducing additional energy consumption

High-frequency rTMS over bilateral primary motor cortex improves freezing of gait and emotion regulation in patients with Parkinson’s disease: a randomized controlled trial

BackgroundFreezing of gait (FOG) is a common and disabling phenomenon in patients with Parkinson’s disease (PD), but effective treatment approach remains inconclusive. Dysfunctional emotional factors play a key role in FOG. Since primary motor cortex (M1) connects with prefrontal areas via the frontal longitudinal system, where are responsible for emotional regulation, we hypothesized M1 may be a potential neuromodulation target for FOG therapy. The purpose of this study is to explore whether high-frequency rTMS over bilateral M1 could relieve FOG and emotional dysregulation in patients with PD.MethodsThis study is a single-center, randomized double-blind clinical trial. Forty-eight patients with PD and FOG from the Affiliated Hospital of Xuzhou Medical University were randomly assigned to receive 10 sessions of either active (N = 24) or sham (N = 24) 10 Hz rTMS over the bilateral M1. Patients were evaluated at baseline (T0), after the last session of treatment (T1) and 30 days after the last session (T2). The primary outcomes were Freezing of Gait Questionnaire (FOGQ) scores, with Timed Up and Go Test (TUG) time, Standing-Start 180° Turn (SS-180) time, SS-180 steps, United Parkinson Disease Rating Scales (UPDRS) III, Hamilton Depression scale (HAMD)-24 and Hamilton Anxiety scale (HAMA)-14 as secondary outcomes.ResultsTwo patients in each group dropped out at T2 and no serious adverse events were reported by any subject. Two-way repeated ANOVAs revealed significant group × time interactions in FOGQ, TUG, SS-180 turn time, SS-180 turning steps, UPDRS III, HAMD-24 and HAMA-14. Post-hoc analyses showed that compared to T0, the active group exhibited remarkable improvements in FOGQ, TUG, SS-180 turn time, SS-180 turning steps, UPDRS III, HAMD-24 and HAMA-14 at T1 and T2. No significant improvement was found in the sham group. The Spearman correlation analysis revealed a significantly positive association between the changes in HAMD-24 and HAMA-14 scores and FOGQ scores at T1.ConclusionHigh-frequency rTMS over bilateral M1 can improve FOG and reduce depression and anxiety in patients with PD

PC-MAC: A Prescheduling and Collision-Avoided MAC Protocol for Underwater Acoustic Sensor Networks

The impact of the acoustic modem with long preamble characteristic on the collision feature of the media access control scheme in underwater acoustic sensor networks (UANs) is evaluated. It is observed that the collision probability is relatively high due to the extremely long duration of preamble. As a result, UANs generally have much lower network throughput. To address this problem, a prescheduling MAC protocol named PC-MAC for UANs is proposed, which leverages a novel prescheduling scheme for the exchange of control packet to alleviate the collision probability among control packets. PC-MAC is a reservation-based channel access scheme. In the proposed protocol, an extra guard time is introduced to avoid the influence of dynamic spatial-temporal uncertainty of the sender and receiver positions. Simulation results show that PC-MAC outperforms classic reservation-based MAC protocol named SFAMA in terms of network goodput and end-to-end delay and lowers collision probability among control packets in two representative network scenarios

Analysis of Intelligent Vehicle Technologies to Improve Vulnerable Road Users Safety at Signalized Intersections

This project aims to know how the Intelligent Vehicle Technologies (IVT) can improve Vulnerable Road Users’ (VRU) safety in different environments and conditions (e.g., sight distance and traffic flow) at signalized intersections. For the statistical analysis on historical aggregate crash data, the project studied risk factors on crash injury severity for VRU-related crashes at signalized intersections in California cities. The researchers summarize seven critical crash types for the micro-level traffic safety simulation. For the traffic safety simulation part, it is found that Intersection Safety (INS) is empowered to be the most efficient technology to significantly reduce average collision counts for passenger cars under all seven collision types of interest. Blind Spot Detection (BSD) has the most minimal effects on those types. The safety improvement of VRU Beacon Systems (VBS) and Bicycle/Pedestrian to Vehicle Communication (BPTV) are between INS and BSD. Results show that under a certain threshold of sight distance, IVT can significantly reduce the collision probability and IVT can still improve safety under good sight condition if collisions happen in front of vehicles. In the end, the project conducted sensitive analyses of sight distance and traffic volume. For some collision types, INS and BPTV can only reduce ~50% of collision at extremely high traffic volume conditions.View the NCST Project Webpag

How Intelligent Vehicle Technologies Can Improve Vulnerable Road User Safety at Signalized Intersections

Motor vehicle crashes are the leading cause of accidental deaths in the US. In 2020, 38,824 people lost their lives in car-related crashes. Bicyclists and pedestrians are particularly susceptible—7,448 of these “vulnerable road users” were killed nationwide in 2020, and 29% of all reported crash-related fatalities in California were vulnerable road users. A variety of intelligent vehicle technologies hold promise for improving bicycle and pedestrian safety. Sensors in vehicles and/or used by vulnerable road users themselves could alert travelers of potential conflicts, giving them more time to react. However, these technologies all have unique technical, operational, and financial characteristics, and they might perform differently in different environmental conditions and at different levels of deployment. Little research has been done on how these technologies might affect safety. Researchers at the University of California, Davis combined aggregate historical crash data analysis and micro transportation simulation to examine the safety impacts of four different intelligent vehicle technologies: blind spot detection, a vulnerable-road-user beacon system carried by bicyclists or pedestrians, bicycle/pedestrian-to-vehicle communication, and intersection safety.View the NCST Project Webpag

How Intelligent Vehicle Technologies Can Improve Vulnerable Road User Safety at Signalized Intersections [Policy Brief]

Motor vehicle crashes are the leading cause of accidental deaths in the US. In 2020, 38,824 people lost their lives in car-related crashes. Bicyclists and pedestrians are particularly susceptible\u20147,448 of these \u201cvulnerable road users\u201d were killed nationwide in 2020, and 29% of all reported crash-related fatalities in California were vulnerable road users. A variety of intelligent vehicle technologies hold promise for improving bicycle and pedestrian safety. Sensors in vehicles and/or used by vulnerable road users themselves could alert travelers of potential conflicts, giving them more time to react. However, these technologies all have unique technical, operational, and financial characteristics, and they might perform differently in different environmental conditions and at different levels of deployment. Little research has been done on how these technologies might affect safety. Researchers at the University of California, Davis combined aggregate historical crash data analysis and micro transportation simulation to examine the safety impacts of four different intelligent vehicle technologies: blind spot detection, a vulnerable-road-user beacon system carried by bicyclists or pedestrians, bicycle/pedestrian-to-vehicle communication, and intersection safety

Synthesis and fungicidal activities of novel indene-substituted oxime ether strobilurins

Nineteen novel indene-substituted oxime ether strobilurins, which used an indene group to stabilize the (E)-styryl group in SYP-Z071 (an unsaturated oxime strobilurin fungicide under development by the Shenyang Research Institute of Chemical Industry), were designed and synthesized. The biological assay results showed that all compounds possessed good or excellent fungicidal activities. It was found that most of the compounds showed higher fungicidal activities against Pyricularia oryzae, Phytophthora infestans, Erysiphe graminis, and Colletotrichum lagenarium than SYP-Z071 at the tested concentration. The biological assay results also indicated that most of the compounds exhibited higher in vivo fungicidal activities against cucumber Pseudoperonospora cubensis and C. lagenarium than the commercial fungicides trifloxystrobin and kresoxim-methyl at a concentration of 6.25 mg/L. Furthermore, it was found that alpha-(methoxyimino)-N-methylphenylacetamide oxime ethers 6m-s exhibited a broad spectrum and remarkably higher activities against all tested fungi. Especially, the 6-methylindene-substituted compound 6p was identified as the most promising candidate for further study