Coverage Issues in Wireless Ad-Hoc Sensor Networks

Wireless Ad-Hoc sensor networks have a broad range of applications in the military,vigilance, environment monitoring, and healthcare fields. Coverage of the sensor networks describes how well an area is monitored. The coverage problem has been studied extensively, especially when combined with connectivity and well-organized. Coverage is a typical problem in the wireless sensor networks to fulfil issued sensing tasks. In general, sensing analysis represents how well an area is monitored by sensors. The quality of the sensor network can be reflected by levels of coverage and connectivity that it offers. The coverage issues have been studied extensively, especially when combined with connectivity and energy efficiency. Constructing a connected fully covered, and energy efficient sensor network is valuable for real world applications due to limited resources of sensor nodes. The survey recent contributions addressing energy efficient coverage problems in the context of static WASNs, networks in which sensor nodes do not move once they are deployed and present in some detail of the algorithms, assumptions, and results. A comprehensive comparison among these approaches is given from perspective of design objectives, assumptions, algorithm attributes and related results

Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed

Genetic studies on telomere length are important for understanding age-related diseases. Prior GWAS for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally-diverse individuals (European, African, Asian and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n=109,122 individuals. We identified 59 sentinel variants (p-value OBFC1indicated the independent signals colocalized with cell-type specific eQTLs for OBFC1 (STN1). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B (SNM1B) and PARN. In PheWAS, we demonstrated our TL polygenic trait scores (PTS) were associated with increased risk of cancer-related phenotypes

A Philosophical Study of Agricultural Image Processing Techniques

The development of agriculture in China has been substantially aided by the development of image processing technologies. It is simple for people to comprehend the significance of image processing technology for agricultural development by presenting the application status of image processing technology in agriculture and its impact on agricultural production value. This research examines how image processing technology is used in agriculture on the basis of that information. This study first examines how image processing technology is used in the world of agriculture. Second, this study applies both classic machine recognition technology and image processing technology to crop pest identification, analyses their effects, and highlights the application effect of image processing technology in the agricultural industry. The findings indicate that this approach has a recognition rate of 86%, 89%, 91%, 83%, 78%, and 79%, respectively. It is evident that the detection of crop diseases and insect pests is improved by the use of image processing technology