A specific characteristic of sensor network applications is that the major traffic consists of data collection from various sensor source nodes to a sink via a unidirectional tree. In this paper, we propose DMAC, an energy efficient and low latency MAC that is designed and optimized for such data gathering trees in wireless sensor networks. We first show that previously proposed MAC protocols for sensor networks that utilize activation/sleep duty cycles suffer from a data forwarding interruption problem, whereby not all nodes on a multihop path to the sink can be notified of data delivery in progress, resulting in significant sleep delay. DMAC is designed to solve the interruption problem, by giving the active/sleep schedule of a node an offset that depends upon its depth on the tree. This scheme allows continuous packet forwarding because all nodes on the multihop path can be notified of the data delivery in progress. DMAC also adjusts node duty cycles adaptively according to the traffic load in the network by varying the number of active slots in an schedule interval. We further propose a data prediction mechanism and the use of more to send (MTS) packets in order to alleviate problems pertaining to channel contention and collisions. Our simulation results as well as experimental results with the Mote platform show that by exploiting the applicationspecific structure of data gathering trees in sensor networks, DMAC provides significant energy savings and latency reduction while ensuring high data reliability.
Background: China's coastal wetlands belong to some of the most threatened ecosystems worldwide. The loss and degradation of these wetlands seriously threaten waterbirds that depend on wetlands.
Lumpy skin disease (LSD) is a viral disease of cattle caused by LSD virus (LSDV). This disease poses a significant threat to stockbreeding and is listed as one of bovine notifiable diseases by OIE. Before 2019, LSD has not been reported in China. The first LSD outbreak was determined in China on August 3, 2019. Since then, a total of 7 LSD outbreaks have been reported in other 6 provinces in China, infecting 91 and killing 7 cattle. As of now, LSDV was detected in western and eastern China and also in Taiwan Island outside Mainland China. LSD is undoubtedly an emerging threat to the cattle industry in China.
A novel equine parvovirus, equine parvovirus-hepatitis (EqPV-H), was first discovered in a horse that died of equine serum hepatitis in the USA in 2018. EqPV-H was shown to be a novel etiological agent associated with equine serum hepatitis. Following this initial report, no additional studies on EqPV-H have been published. In this study, a total of 143 serum samples were collected from racehorses at 5 separate farms in China and were analyzed to detect EqPV-H DNA via nested PCR. The results indicated a high prevalence of EqPV-H (11.9%, 17/143) in the studied animals. In addition, a remarkably high coinfection rate (58.8%, 10/17) with 2 equine flaviviruses (equine hepacivirus and equine pegivirus) was observed in the EqPV-H positive equines. However, all equines tested negative for Theiler’s disease-associated virus, an etiological agent associated with equine serum hepatitis. The genomes of six field EqPV-H strains were sequenced and analyzed, with the results indicating that the Chinese EqPV-H strains have low genetic diversity and high genetic similarity with the USA EqPV-H strain BCT-01. A phylogenetic analysis demonstrated that the Chinese EqPV-H strains clustered with BCT-01 in the genus Copiparvovirus but were distantly related to another equine parvovirus identified in horse cerebrospinal fluid. In addition, liver enzyme levels were detected in the EqPV-H positive serum samples, and all the values were in the normal range, indicating that infection can occur without concurrent liver disease. This study will promote an understanding of the geographical distribution, genetic diversity, and pathogenicity of EqPV-H.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.