An Improved Intrusion Weed Optimization Algorithm for Node Location in Wireless Sensor Networks

The distribution optimization of WSN nodes is one of the key issues in WSN research, and also is a research hotspot in the field of communication. Aiming at the distribution optimization of WSN nodes, the distribution optimization scheme of nodes based on improved invasive weed optimization algorithm(IIWO) is proposed. IIWO improves the update strategy of the initial position of weeds by using cubic mapping chaotic operator, and uses the Gauss mutation operator to increase the diversity of the population. The simulation results show that the algorithm proposed in this paper has a higher solution quality and faster convergence speed than IWO and CPSO. In distribution optimization example of WSN nodes, the optimal network coverage rate obtained by IIWO is respectively improved by 1.82% and 0.93% than the IWO and CPSO. Under the condition of obtaining the same network coverage rate, the number of nodes required by IIWO is fewer.

DESIGN AND TEST OF SELF-PROPELLED STRADDLE-TYPE LYCIUM BARBARUM L. SPRAYING MACHINE

According to the planting agronomy of Lycium barbarum L. in Ningxia, a self-propelled straddle-type sprayer was designed. The aim was to reduce the labor requirements, improve the spraying effect to the middle and lower parts of the canopy, reduce the influence of natural wind on droplet drift, and recycle excess liquid medicine to reduce environmental pollution. Tests showed that the coverage rate of liquid medicine on the leaf surface and back of the leaf peaked at 84.2% and 48.3%, respectively, when spraying pressure was high. Under different spraying distances, the coverage rate of liquid medicine on leaf surface and back of leaf reached 73.3% and 38.3% at the shortest distance. The uniformity of the spray droplet distribution was good, the use error was less than 10%, and the excess liquid was effectively recovered.

COMPARATIVE ANALYSIS OF OPERATIONAL RESPONSE INDICATORS OF FIRE SERVICE UNITS LOCATED IN VARIOUS CLIMATIC CONDITIONS

Проведено изучение показателей оперативного реагирования (скорости следования, времени прибытия первого подразделения, уровня прикрытия) подразделений пожарной охраны для населенных пунктов Краснодарского края и Свердловской области. Выделены города, в которых следует особое внимание уделить совершенствованию функционирования пожарной охраны с целью доведения времени прибытия первого подразделения до нормативного значения. There was carried out the investigation of operational response indicators (speed of movement, first unit arrival time, coverage rate) of fire service units at settlements of the Krasnodar Region and the Sverdlovsk Region. There were highlighted the cities in which it is necessary to improve fire service activities in order to make the first unit arrival time closer to the normative value.

Outreach Practices of Public Employment Services Targeted at NEET Youth in Poland

This paper contributes to our understanding of whether, and if so, how public employment services in Poland are attempting to reach young NEETs, and whether they fail or succeed in their efforts. The study shows that most NEETs below 25 years of age in Poland, including rural NEETs, remain beyond the reach of the PES registers. The coverage rate is particularly low amongst those individuals who are outside the labor force. Effective outreach strategies may prevent them from moving into long-term inactivity. The study shows that the PES offices do not cooperate closely with local institutions: moreover, they use methods for approaching the hardest-to-reach individuals and residents of remote areas infrequently. The article discusses the obstacles to the effective functioning of the PES, the factors that contribute to the PES’ successes and failures, and the consequences for young NEETs of remaining outside of institutional support systems.

A GIS-Based Multi-Criterion Decision-Making Method to Select City Fire Brigade: A Case Study of Wuhan, China

Rapid urban expansion has brought new challenges to firefighting, with the speed of firefighting rescue being crucial for the safety of property and life. Thus, fire prevention and rescuing people in distress have become more challenging for city managers and emergency responders. Unfortunately, existing research does not consider the negative effects of the current spatial distribution of fire-risk areas, land cover, location, and traffic congestion. To address these shortcomings, we use multiple methods (including geographic information system, multi-criterion decision-making, and location–allocation (L-A)) and multi-source geospatial data (including land cover, point-of-interest, drive time, and statistical yearbooks) to identify suitable areas for fire brigades. We propose a method for identifying potential fire-risk areas and to select suitable fire brigade zones. In this method, we first remove exclusion criteria to identify spatially undeveloped zones and use kernel density methods to evaluate the various fire-risk zones. Next, we use analytic hierarchy processes (AHPs) to comprehensively evaluate the undeveloped areas according to the location, orography, and potential fire-risk zones. In addition, based on the multi-time traffic situation, the average traffic speed during rush hour of each road is calculated, a traffic network model is established, and the travel time is calculated. Finally, the L-A model and network analysis are used to map the spatial coverage of the fire brigades, which is optimized by combining various objectives, such as the coverage rate of high-fire-risk zones, the coverage rate of building construction, and the maintenance of a sub-five-minute drive time between the proposed fire brigade and the demand point. The result shows that the top 50% of fire-risk zones in the central part of Wuhan are mainly concentrated to the west of the Yangtze River. Good overall rescue coverage is obtained with existing fire brigades, but the fire brigades in the north, south, southwest, and eastern areas of the study area lack rescue capabilities. The optimized results show that, to cover the high-fire-risk zones and building constructions, nine fire brigades should be added to increase the service coverage rate from 93.28% to 99.01%. The proposed method combines the viewpoint of big data, which provides new ideas and technical methods for the fire brigade site-selection model.

An Algorithm for Fitting Sphere Target of Terrestrial LiDAR

The sphere target played a vital role in terrestrial LiDAR applications, and solving its geometrical center based on point cloud was a widely concerned problem. In this study, we proposed a newly finite random search algorithm for sphere target fitting. Based on the point cloud data and the geometric characteristics of the sphere target, the algorithm realized the target sphere fitting from the perspective of probability and statistics with the help of parameter estimation. Firstly, an initial constraint space was constructed, and the initial center and radius were determined by finite random search. Then, the optimal spherical center and radius were determined gradually through continuous iterative optimization. We tested the algorithm with the simulated and realistic point cloud. Experimental results showed that the proposed algorithm could be effectively applied to all kinds of point cloud fitting. When the coverage rate was bigger than 30%, the fitting accuracy could reach within 0.01 mm for all kinds of point clouds. When the coverage rate was less than 20%, the fitting accuracy can reach ±1 mm, although it was reduced to a certain extent.

Molecular Characterization Based on Whole-Genome Sequencing of Streptococcus pneumoniae in Children Living in Southwest China During 2017-2019

BackgroundStreptococcus pneumoniae is an important pathogen causing high morbidity and high mortality in children and undergoes frequent recombination for capsule switching to neutralize the 13-valent pneumococcal conjugate vaccine (PCV13). This study aimed to investigate the prevalence, and molecular characteristics including serotypes and antibiotic susceptibility of S. pneumoniae isolated from children living in Southwest China from 2017 to 2019 to facilitate the selection of effective vaccine formulations and appropriate antibiotic treatment regimens.MethodsThis study was conducted at West China Second University Hospital (Chengdu, Sichuan Province, China), Zunyi Medical University Third Affiliated Hospital/First People’s Hospital of Zunyi (Zunyi, Guizhou Province, China) and Chengdu Jinjiang District Maternal and Child Healthcare Hospital (Chengdu, Sichuan Province, China). Demographic and clinical characteristics of children infected with S. pneumoniae were collected and analysed. Next-generation sequencing and sequence analysis were used to determine the serotypes, sequence types, antibiotic resistance and potential protein vaccine target genes of the pneumococcal isolates. The coverage rate provided by PCV13 was estimated by calculating the percentage of the specific serotypes that were specifically the PCV13-included serotypes. Antimicrobial susceptibility was determined by the microdilution broth method.ResultsThe most prevalent pneumococcal serotypes were 19F (25.8%), 19A (14.1%), 6B (12.5%), 6A (9.4%) and 14 (7.8%). The predominant STs were ST271 (23.3%), ST320 (15.5%) and ST90 (8.6%), dominated by the clonal complex Taiwan19F-14 (39.1%). The coverage rate of PCV13 was 77.3% in all the isolates, with relatively higher values in invasive isolates (86.4%). Over the decade, the rates of resistance to penicillin, amoxicillin and cefotaxime were 5.6%, 5.3% and 5.1%, respectively, with significantly higher values in invasive isolates (22.4%, 14.9% and 11.9%). Almost all the isolates were resistant to erythromycin (99.1%) and clindamycin (95.9%). All isolates carried virulence-related genes, including ply, psaA, piaA, piuA, phtE, nanA, pepO, danJ, pvaA, clpP, pcsB, stkP, potD, and strH. The carriage of virulence and resistance genes varied among serotypes and clades, with serotype 19F/ST271 showing higher resistance to antibiotics and being more likely to carry pilus genes and other virulence genes.ConclusionThese data provide valuable information for the understanding of pneumococcal pathogenesis, antimicrobial resistance and the development of protein-based vaccines against pneumococcal infection.