ARHCS (Automatic Rainfall Half-Life Cluster System): A Landslides Early Warning System (LEWS) Using Cluster Analysis and Automatic Threshold Definition

A significant portion of Landslide Early Warning Systems (LEWS) relies on the definition of operational thresholds and the monitoring of cumulative rainfall for alert issuance. These thresholds can be obtained in various ways, but most often they are based on previous landslide data. This approach introduces several limitations. For instance, there is a requirement for the location to have been previously monitored in some way to have this type of information recorded. Another significant limitation is the need for information regarding the location and timing of incidents. Despite the current ease of obtaining location information (GPS, drone images, etc.), the timing of the event remains challenging to ascertain for a considerable portion of landslide data. Concerning rainfall monitoring, there are multiple ways to consider it, for instance, examining accumulations over various intervals (1 h, 6 h, 24 h, 72 h), as well as in the calculation of effective rainfall, which represents the precipitation that actually infiltrates the soil. However, in the vast majority of cases, both the thresholds and the rain monitoring approach are defined manually and subjectively, relying on the operators’ experience. This makes the process labor-intensive and time-consuming, hindering the establishment of a truly standardized and rapidly scalable methodology on a large scale. In this work, we propose a Landslides Early Warning System (LEWS) based on the concept of rainfall half-life and the determination of thresholds using Cluster Analysis and data inversion. The system is designed to be applied in extensive monitoring networks, such as the one utilized by Cemaden, Brazil’s National Center for Monitoring and Early Warning of Natural Disasters.

Prevalence of Latent Tuberculosis Infection [LTBI] in Prison Officers: A Systematic Review and Meta-Analysis

This study aimed to perform a systematic review and meta-analysis to determine the LTBI prevalence in prison officers worldwide. A systematic search was performed in PubMed, WoS, Embase, and BVS, including all articles related to LTBI prevalence and risk factors. After critical evaluation and qualitative synthesis of the identified articles, a meta-analysis was used. Five studies carried out between 2012 and 2022 were included, with a total sample size of 1718 prison officers. The overall LTBI prevalence was 50% [95% confidence interval [CI]: 48% - 52%;n = 816], with high heterogeneity between studies. Smoking [OR = 1.76;CI 95% = 1.26 - 2.46] and males [OR = 2.08;CI 95% = 1.31 - 3.31] were positively related to a higher LTBI prevalence among prison officers. Thus, preventive measures and the rapid and accurate diagnosis of new cases should be emphasized to ensure tuberculosis control, especially among risk groups such as prison officers.

Slope deformation partitioning and monitoring points optimization based on cluster analysis

The scientific and fair positioning of monitoring locations for surface displacement on slopes is a prerequisite for early warning and forecasting.However,there is no specific provision on how to effectively determine the number and location of monitoring points according to the actual deformation characteristics of the slope.There are still some defects in the layout of monitoring points.To this end,based on displacement data series and spatial location information of surface displacement monitoring points,by combining displacement series correlation and spatial distance influence factors,a spatial deformation correlation calculation model of slope based on clustering analysis was proposed to calculate the correlation between different monitoring points,based on which the deformation area of the slope was divided.The redundant monitoring points in each partition were eliminated based on the partition's outcome,and the overall optimal arrangement of slope monitoring points was then achieved.This method scientifically addresses the issues of slope deformation zoning and data gathering overlap.It not only eliminates human subjectivity from slope deformation zoning but also increases the efficiency and accuracy of slope monitoring.In order to verify the effectiveness of the method,a sand-mudstone interbedded CounterTilt excavation slope in the Chongqing city of China was used as the research object.Twenty-four monitoring points deployed on this slope were monitored for surface displacement for 13 months.The spatial location of the monitoring points was discussed.The results show that the proposed method of slope deformation zoning and the optimized placement of monitoring points are feasible.

Fuzzy cluster analysis of water mass in the western Taiwan Strait in spring 2019

The classification of the springtime water mass has an important influence on the hydrography,regional climate change and fishery in the Taiwan Strait.Based on 58 stations of CTD profiling data collected in the western and southwestern Taiwan Strait during the spring cruise of 2019,we analyze the spatial distributions of temperature(T)and salinity(S)in the investigation area.Then by using the fuzzy cluster method combined with the T-S similarity number,we classify the investigation area into 5 water masses:the Minzhe Coastal Water(MZCW),the Taiwan Strait Mixed Water(TSMW),the South China Sea Surface Water(SCSSW),the South China Sea Subsurface Water(SCSUW)and the Kuroshio Branch Water(KBW).The MZCW appears in the near surface layer along the western coast of Taiwan Strait,showing low-salinity(<32.0)tongues near the Minjiang River Estuary and the Xiamen Bay mouth.The TSMW covers most upper layer of the investigation area.The SCSSW is mainly distributed in the upper layer of the southwestern Taiwan Strait,beneath which is the SCSUW.The KBW is a high temperature(core value of 26.36℃)and high salinity(core value of 34.62)water mass located southeast of the Taiwan Bank and partially in the central Taiwan Strait.

X-ray Manifestations of Pneumoconiosis Patients and Differential Analysis with Pulmonary Tuberculosis

[Objectives]This study was conducted to explore the X-ray manifestations of pneumoconiosis patients and differentiation from pulmonary tuberculosis.[Methods]Retrospective analysis was conducted on 103 patients who underwent lung examinations,including 47 cases of pneumoconiosis and 56 cases of pulmonary tuberculosis.The differences in nodule characteristics and accompanying cavity sign between pneumoconiosis and pulmonary tuberculosis were compared.[Results]The X-ray manifestations of pneumoconiosis patients mainly included various forms of lung images,which were uneven in density,and had blurry edges,and sometimes thickening of lung markings and reduction of lung volume could be observed.The acinar nodules observed in X-ray films of patients with hematogenous disseminated pulmonary tuberculosis appeared petal like.The uniformity of nodule appearance such as nodule distribution,nodule density,and nodule size was significantly lower in pneumoconiosis than in hematogenous disseminated pulmonary tuberculosis,showing a statistical significance(P<0.05).The diameter of cavities in patients with pneumoconiosis accompanied by cavity sign[(0.64±0.13 vs 3.37±0.95)cm]was lower than that in patients with secondary pulmonary tuberculosis accompanied by cavity sign.There was a significant difference in the thickness of the cavity wall between the two diseases,and patients with pneumoconiosis accompanied by cavity sign had a higher rate of thick wall cavities(>3 mm).The X-ray manifestations of pneumoconiosis and tuberculosis were relatively similar,but the distribution,density and size of nodules in pneumoconiosis were relatively uneven,and the patients accompanied by cavity sign had smaller cavity diameter and higher rate of thick-walled cavities.[Conclusions]This study provides a reference for the clinical differential diagnosis of pneumoconiosis and pulmonary tuberculosis.

Integrated classification method of tight sandstone reservoir based on principal component analysise simulated annealing genetic algorithmefuzzy cluster means

In this research,an integrated classification method based on principal component analysis-simulated annealing genetic algorithm-fuzzy cluster means(PCA-SAGA-FCM)was proposed for the unsupervised classification of tight sandstone reservoirs which lack the prior information and core experiments.A variety of evaluation parameters were selected,including lithology characteristic parameters,poro-permeability quality characteristic parameters,engineering quality characteristic parameters,and pore structure characteristic parameters.The PCA was used to reduce the dimension of the evaluation pa-rameters,and the low-dimensional data was used as input.The unsupervised reservoir classification of tight sandstone reservoir was carried out by the SAGA-FCM,the characteristics of reservoir at different categories were analyzed and compared with the lithological profiles.The analysis results of numerical simulation and actual logging data show that:1)compared with FCM algorithm,SAGA-FCM has stronger stability and higher accuracy;2)the proposed method can cluster the reservoir flexibly and effectively according to the degree of membership;3)the results of reservoir integrated classification match well with the lithologic profle,which demonstrates the reliability of the classification method.

Meta‑analysis of influencing factors associating with treatment outcome of multidrug resistant tuberculosis

Objective:To systematically review the influencing factors of the treatment outcome of multidrug-resistant pulmonary tuberculosis and provide reference for the prevention and treatment of multidrug-resistant pulmonary tuberculosis.Method:Case control studies on the factors influencing the treatment outcome of multidrug-resistant pulmonary tuberculosis in Chinese databases(CNKI,VIP,Wanfang,Sinomed)and English databases(Pubmed,Web of science,Medline,Embase,Scopus)were searched and collected by computer.The search period was from the establishment of the database to January 2023.After screening and quality evaluation,RevMan5.4 was used for meta-analysis.Result:Totally 18 articles were ultimately included,with a sample size of 7328 people.The results showed that retreatment,complications,adverse reactions,and gender were related to the treatment outcome of multidrug-resistant pulmonary tuberculosis.The OR values and 95%CI of each factor were 0.22(0.17-0.29),0.38(0.32-0.46),0.27(0.17-0.44),and 0.43(0.33-0.56),respectively.Conclusion:Complications,retreatment,adverse reactions,and male gender are effective risk factors for the treatment outcome of multidrug-resistant pulmonary tuberculosis.In clinical practice,more targeted measures are needed for different types of patients.Due to the limitations of the number of studies,the above conclusions require more research to support them.

A Shared Natural Neighbors Based-Hierarchical Clustering Algorithm for Discovering Arbitrary-Shaped Clusters

In clustering algorithms,the selection of neighbors significantly affects the quality of the final clustering results.While various neighbor relationships exist,such as K-nearest neighbors,natural neighbors,and shared neighbors,most neighbor relationships can only handle single structural relationships,and the identification accuracy is low for datasets with multiple structures.In life,people’s first instinct for complex things is to divide them into multiple parts to complete.Partitioning the dataset into more sub-graphs is a good idea approach to identifying complex structures.Taking inspiration from this,we propose a novel neighbor method:Shared Natural Neighbors(SNaN).To demonstrate the superiority of this neighbor method,we propose a shared natural neighbors-based hierarchical clustering algorithm for discovering arbitrary-shaped clusters(HC-SNaN).Our algorithm excels in identifying both spherical clusters and manifold clusters.Tested on synthetic datasets and real-world datasets,HC-SNaN demonstrates significant advantages over existing clustering algorithms,particularly when dealing with datasets containing arbitrary shapes.

Study Progress Analysis of Effluent Quality Prediction in Activated Sludge Process Based on CiteSpace

In this paper, CiteSpace, a bibliometrics software, was adopted to collect research papers published on the Web of Science, which are relevant to biological model and effluent quality prediction in activated sludge process in the wastewater treatment. By the way of trend map, keyword knowledge map, and co-cited knowledge map, specific visualization analysis and identification of the authors, institutions and regions were concluded. Furthermore, the topics and hotspots of water quality prediction in activated sludge process through the literature-co-citation-based cluster analysis and literature citation burst analysis were also determined, which not only reflected the historical evolution progress to a certain extent, but also provided the direction and insight of the knowledge structure of water quality prediction and activated sludge process for future research.

CPSO: Chaotic Particle Swarm Optimization for Cluster Analysis

Background:To solve the cluster analysis better,we propose a new method based on the chaotic particle swarm optimization(CPSO)algorithm.Methods:In order to enhance the performance in clustering,we propose a novel method based on CPSO.We first evaluate the clustering performance of this model using the variance ratio criterion(VRC)as the evaluation metric.The effectiveness of the CPSO algorithm is compared with that of the traditional particle swarm optimization(PSO)algorithm.The CPSO aims to improve the VRC value while avoiding local optimal solutions.The simulated dataset is set at three levels of overlapping:non-overlapping,partial overlapping,and severe overlapping.Finally,we compare CPSO with two other methods.Results:By observing the comparative results,our proposed CPSO method performs outstandingly.In the conditions of non-overlapping,partial overlapping,and severe overlapping,our method has the best VRC values of 1683.2,620.5,and 275.6,respectively.The mean VRC values in these three cases are 1683.2,617.8,and 222.6.Conclusion:The CPSO performed better than other methods for cluster analysis problems.CPSO is effective for cluster analysis.

Composition Analysis and Identification of Ancient Glass Products Based on L1 Regularization Logistic Regression

In view of the composition analysis and identification of ancient glass products, L1 regularization, K-Means cluster analysis, elbow rule and other methods were comprehensively used to build logical regression, cluster analysis, hyper-parameter test and other models, and SPSS, Python and other tools were used to obtain the classification rules of glass products under different fluxes, sub classification under different chemical compositions, hyper-parameter K value test and rationality analysis. Research can provide theoretical support for the protection and restoration of ancient glass relics.

Structural Characteristics and Influencing Factors of Carbon Emission Spatial Association Network:A Case Study of Yangtze River Delta City Cluster,China

City cluster is an effective platform for encouraging regionally coordinated development.Coordinated reduction of carbon emissions within city cluster via the spatial association network between cities can help coordinate the regional carbon emission management,realize sustainable development,and assist China in achieving the carbon peaking and carbon neutrality goals.This paper applies the improved gravity model and social network analysis(SNA)to the study of spatial correlation of carbon emissions in city clusters and analyzes the structural characteristics of the spatial correlation network of carbon emissions in the Yangtze River Delta(YRD)city cluster in China and its influencing factors.The results demonstrate that:1)the spatial association of carbon emissions in the YRD city cluster exhibits a typical and complex multi-threaded network structure.The network association number and density show an upward trend,indicating closer spatial association between cities,but their values remain generally low.Meanwhile,the network hierarchy and network efficiency show a downward trend but remain high.2)The spatial association network of carbon emissions in the YRD city cluster shows an obvious‘core-edge’distribution pattern.The network is centered around Shanghai,Suzhou and Wuxi,all of which play the role of‘bridges’,while cities such as Zhoushan,Ma'anshan,Tongling and other cities characterized by the remote location,single transportation mode or lower economic level are positioned at the edge of the network.3)Geographic proximity,varying levels of economic development,different industrial structures,degrees of urbanization,levels of technological innovation,energy intensities and environmental regulation are important influencing factors on the spatial association of within the YRD city cluster.Finally,policy implications are provided from four aspects:government macro-control and market mechanism guidance,structural characteristics of the‘core-edge’network,reconfiguration and optimization of the spatial layout of the YRD city cluster,and the application of advanced technologies.

Space-Time Cluster Analysis of Tuberculosis Incidence in Beijing, China

Tuberculosis is one of the top killer diseases in the globe. The aim of this study was to explore the geographic distribution patterns and clustering characteristics of the disease incidence in terms of both space and time with high relative risk locations for tuberculosis incidence in Beijing area. A retrospective space-time clustering analysis was conducted at the districts level in Beijing area based on reported cases of sputum smear-positive pulmonary tuberculosis (TB) from 2005 to 2014. Global and local Moran’s I, autocorrelation analysis along with Ord (Gi*) statistics was applied to detect spatial patterns and the hotspot of TB incidence. Furthermore, the Kuldorff’s scan statistics were used to analyze space-time clusters. A total of 40,878 TB cases were reported in Beijing from 2005 to 2014. The annual average incidence rate was 22.11 per 100,000 populations (ranged from 16.55 to 25.71). The seasonal incidence occurred from March to July until late autumn. A higher relative risk area for TB incidence was mainly detected in urban and some rural districts of Beijing. The significant most likely space-time clusters and secondary clusters of TB incidence were scattered diversely in Beijing districts in each study year. The risk population was mainly scattered in urban and dense populated districts, including in few rural districts.

Rate of Patient Delay among Students with Pulmonary Tuberculosis in China: A Meta-Analysis

Objective: To systematically review the rate of patient delay of pulmonary tuberculosis (PTB) patients among students in China. Methods: Databases including Web of Science Core Collection, PubMed, The Cochrane Library, CBM, CNKI, VIP, and WANFANG DATA were electronically searched to collect cross-sectional studies on the incidence of delayed consultation in students with PTB in China from January 1, 2000, to November 15, 2022. Two researchers independently screened studies, extracted data, and assessed the risk of bias of the included studies. Meta-analysis was then performed by Stata 16.0 software. Results: In total, 60 cross-sectional studies with 260,707 cases involving 136,701 delayed consultation PTB patients were included. The results of meta-analysis showed that the rate of patient delay was 46.4% (95% CI 44.3% to 48.4%) among students with PTB in China. Results of subgroup analyses showed that: 1) The rates were 46.8% and 50.4% for male and female students, respectively. 2) The rates for the East, Central and West parts of China were 42.3%, 45.6% and 50.5%, respectively. 3) The rates were increased first and then decreased during 2007 to 2020. 4) The rates of students from primary school, junior high school, senior high school and university were 50.3%, 49.8%, 40.7% and 44.9%, respectively. 5) The rates for the Han and the other nationalities were 50.3% and 53.9%, respectively. 6) The rates for local and non-local students were 47.2% and 50.5%, respectively. 7) The rates of patients detected by consultation due to symptoms, recommendation due to symptoms, referral, tracking and healthy physical examination were 50.5%, 51.6%, 46.6%, 55.6% and 16.2%, respectively. 8) The rates of patients with initial PTB and retreatment PTB were 53.1% and 59.6%, respectively. 9) The rates of patients with positive etiology, negative etiology and without etiological results were 55.9%, 47.0% and 51.6%, respectively. 10) The rates of severe and non-severe patients were 59.4% and 52.9%, respectively. Conclusion: The patient delay rate for Chinese students with PTB is generally at a high level. There are substantial differences in the patient delay rate for students with PTB among different genders, regions, study stages, nationalities, household registration types, detection methods, and treatment classifications.

Analysis of the Employment Situation of Non Private Enterprises in Various Regions of China

In the past 30 years, Chinese enterprises have been a hot topic of discussion and concern among the general public in terms of economic and social status, ownership structure, business mechanism, and management level. Solving the problem of employment for the people is an important prerequisite for their peaceful living and work, as well as a prerequisite and foundation for building a harmonious society. The employment situation of private enterprises has always been of great concern to the outside world, and these two major jobs have always occupied an important position in the employment field of China that cannot be ignored. With the establishment of the market economy system, individual and private enterprises have become important components of the socialist economy, making significant contributions to economic development and social progress. The rapid development of China’s economy, on the one hand, is the embodiment of the superiority of China’s socialist market economic system, and on the other hand, it is the role of the tertiary industry and private enterprises in promoting the national economy. Since the 1990s, China’s private enterprises have become a new economic growth point for local and even national countries, and are one of the important ways to arrange employment and achieve social stability. This paper studies the employment of private enterprises and individuals from the perspective of statistics, extracts relevant data from China statistical Yearbook, uses the relevant knowledge of statistics to process the data, obtains the conclusion and puts forward relevant constructive suggestions.

Group decision-making method based on entropy and experts cluster analysis

According to the aggregation method of experts＇ evaluation information in group decision-making,the existing methods of determining experts＇ weights based on cluster analysis take into account the expert＇s preferences and the consistency of expert＇s collating vectors,but they lack of the measure of information similarity.So it may occur that although the collating vector is similar to the group consensus,information uncertainty is great of a certain expert.However,it is clustered to a larger group and given a high weight.For this,a new aggregation method based on entropy and cluster analysis in group decision-making process is provided,in which the collating vectors are classified with information similarity coefficient,and the experts＇ weights are determined according to the result of classification,the entropy of collating vectors and the judgment matrix consistency.Finally,a numerical example shows that the method is feasible and effective.

Clustering Structure Analysis in Time-Series Data With Density-Based Clusterability Measure

Clustering is used to gain an intuition of the struc tures in the data.Most of the current clustering algorithms pro duce a clustering structure even on data that do not possess such structure.In these cases,the algorithms force a structure in the data instead of discovering one.To avoid false structures in the relations of data,a novel clusterability assessment method called density-based clusterability measure is proposed in this paper.I measures the prominence of clustering structure in the data to evaluate whether a cluster analysis could produce a meaningfu insight to the relationships in the data.This is especially useful in time-series data since visualizing the structure in time-series data is hard.The performance of the clusterability measure is evalu ated against several synthetic data sets and time-series data sets which illustrate that the density-based clusterability measure can successfully indicate clustering structure of time-series data.

Cluster analysis on summer precipitation field over Qinghai-Tibet Plateau from 1961 to 2004

The summer day-by-day precipitation data of 97 meteorological stations on the Qinghai-Tibet Plateau from 1961 to 2004 were selected to analyze the temporal-spatial distribution through accumulated variance,correlation analysis,regression analysis,empirical orthogonal function,power spectrum function and spatial analysis tools of GIS.The result showed that summer precipitation occupied a relatively high proportion in the area with less annual precipitation on the Plateau and the correlation between summer precipitation and annual precipitation was strong.The altitude of these stations and summer precipitation tendency presented stronger positive correlation below 2000 m,with correlation value up to 0.604（α=0.01）.The subtracting tendency values between 1961-1983 and 1984-2004 at five altitude ranges（2000-2500 m,2500-3000 m,3500-4000 m,4000-4500 m and above 4500 m）were above zero and accounted for 71.4%of the total.Using empirical orthogonal function, summer precipitation could be roughly divided into three precipitation pattern fields：the Southeast Plateau Pattern Field,the Northeast Plateau Pattern field and the Three Rivers＇ Headstream Regions Pattern Field.The former two ones had a reverse value from the north to the south and opposite line was along 35°N.The potential cycles of the three pattern fields were 5.33a,21.33a and 2.17a respectively,tested by the confidence probability of 90%.The station altitudes and summer precipitation potential cycles presented strong negative correlation in the stations above 4500 m,with correlation value of-0.626（α=0.01）.In Three Rivers Headstream Regions summer precipitation cycle decreased as the altitude rose in the stations above 3500 m and increased as the altitude rose in those below 3500 m.The empirical orthogonal function analysis in June precipitation,July precipitation and August precipitation showed that the June precipitation pattern field was similar to the July＇s,in which southern Plateau was positive and northern Plateau negative.But positive value area in July precipitation pattern field was obviously less than June＇s.The August pattern field was totally opposite to June＇s and July＇s.The positive area in August pattern field jumped from the southern Plateau to the northern Plateau.

A new Multilocus Sequence Analysis Scheme for Mycobacterium tuberculosis

Objective Tuberculosis remains one of the most serious infectious diseases in the world. In this study, a scheme of Mycobacterium tuberculosis （M. tuberculosis） multilocus sequence analysis （MLSA） was established for the phylogenetic and epidemiology analysis. Methods To establish the scheme of M. tuberculosis MLSA, the genome of H37Rv, CCDC5079 and CCDC5180 were compared, and some variable genes were chosen to be the MLSA typing scheme. 44 M. tuberculosis clinical isolates were typed by MLSA, IS6110-RFLP, and soligotyping, to evaluate the MLSA methods. Results After comparison of the genome, seven high discrimination gene loci （recX, rpsL, rmlC, rpmG1, mprA, gcvH, ideR） were chosen to be the MLSA typing scheme finally. 11 variable SNP sites of those seven genes were found among the 44 M. tuberculosis isolate strains and 11 sequence types （STs） were identified. Based on the Hunter-Gaston Index （HGI）, MLSA typing was not as good for discrimination at the strain level as IS6110-RFLP, but the HGI was much better than that of spoligotyping. In addition, the MEGA analysis result of MLSA data was similar to spoligotyping/PGG lineage, showing a strong phylogenetic signal in the modern strains of M. tuberculosis. The MLSA data analysis by eBURST revealed that 4 sequence types （ST） came into a main cluster, showing the major clonal complexes in those 44 strains. Conclusion MLSA genotyping not only can be used for molecular typing, but also is an ideal method for the phylogenetic analysis for M. tuberculosis.

Optimization of constitutive parameters of foundation soils k-means clustering analysis

The goal of this study was to optimize the constitutive parameters of foundation soils using a k-means algorithm with clustering analysis. A database was collected from unconfined compression tests, Proctor tests and grain distribution tests of soils taken from three different types of foundation pits： raft foundations, partial raft foundations and strip foundations. k-means algorithm with clustering analysis was applied to determine the most appropriate foundation type given the un- confined compression strengths and other parameters of the different soils.