Spatio-Temporal Analysis of Drought in the North-Eastern Coastal Region of Vietnam Using the Standardized Precipitation Index (SPI)

Spatio-temporal analysis of drought provides valuable information for drought management and damage mitigation. In this study, the Standardized Precipitation Index at the time scale of 6 months (SPI-6) is selected to reflect drought conditions in the North-Eastern coastal region of Vietnam. The drought events and their characteristics from 1981 to 2019 are detected at 9 meteorological stations and 10 Chirps rainfall stations. The spatio-temporal variation of drought in the study region is analyzed on the basis of the number, duration, severity, intensity, and peak of the detected drought events at the 19 stations. The results show that from 1981 to 2019 the drought events mainly occurred with 1-season duration and moderate intensity and peak. The number, duration, severity, and peak of the drought events were the greatest in the period 2001-2010 and were the smallest in the period 2011-2019. Among the 19 stations, the drought duration tends to decrease at 11 stations, increase at 7 stations, and has a slight variant at 1 station;the drought severity tends to decrease at 14 stations, increase at 4 stations, and has not a significant trend at 1 station;the drought intensity tends to decrease at 17 stations, increase at 1 station, and has a slight variant at 1 station;and the drought peak tends to decrease at 18 stations and increase at 1 station.

A Hybrid Optimization Approach of Single Point Incremental Sheet Forming of AISI 316L Stainless Steel Using Grey Relation Analysis Coupled with Principal Component Analysiss

We investigated the parametric optimization on incremental sheet forming of stainless steel using Grey Relational Analysis(GRA) coupled with Principal Component Analysis(PCA). AISI 316L stainless steel sheets were used to develop double wall angle pyramid with aid of tungsten carbide tool. GRA coupled with PCA was used to plan the experiment conditions. Control factors such as Tool Diameter(TD), Step Depth(SD), Bottom Wall Angle(BWA), Feed Rate(FR) and Spindle Speed(SS) on Top Wall Angle(TWA) and Top Wall Angle Surface Roughness(TWASR) have been studied. Wall angle increases with increasing tool diameter due to large contact area between tool and workpiece. As the step depth, feed rate and spindle speed increase,TWASR decreases with increasing tool diameter. As the step depth increasing, the hydrostatic stress is raised causing severe cracks in the deformed surface. Hence it was concluded that the proposed hybrid method was suitable for optimizing the factors and response.

Design & Test of an Advanced Web Security Analysis Tool (AWSAT)

Considering the escalating frequency and sophistication of cyber threats targeting web applications, this paper proposes the development of an automated web security analysis tool to address the accessibility gap for non-security professionals. This paper presents the design and implementation of an automated web security analysis tool, AWSAT, aimed at enabling individuals with limited security expertise to effectively assess and mitigate vulnerabilities in web applications. Leveraging advanced scanning techniques, the tool identifies common threats such as Cross-Site Scripting (XSS), SQL Injection, and Cross-Site Request Forgery (CSRF), providing detailed reports with actionable insights. By integrating sample payloads and reference study links, the tool facilitates informed decision-making in enhancing the security posture of web applications. Through its user-friendly interface and robust functionality, the tool aims to democratize web security practices, empowering a wider audience to proactively safeguard against cyber threats.

Spatio-Temporal Change of Dispersal Areas of Greater Kudu (Tragelaphus strepsiceros) in Lake Bogoria Landscape, Kenya

Decline in wildlife populations is manifest globally, regionally and locally. A wildlife decline of 68% has been reported in Kenya’s rangelands with Baringo County experiencing more than 85% wildlife loss in the last four decades. Greater Kudu (Tragelaphus strepsiceros) is endemic to Lake Bogoria landscape in Baringo County and constitutes a major tourist attraction for the region necessitating use of its photo on the County’s logo and thus a flagship species. Tourism plays a central role in Baringo County’s economy and is a major source of potential growth and employment creation. The study was carried out to assess spatio-temporal change of dispersal areas of Greater Kudu (GK) in Lake Bogoria landscape in the last four years for enhanced adaptive management and improved livelihoods. GK population distribution primary data collected in December 2022 and secondary data acquired from Lake Bogoria National Game Reserve (LBNGR) for 2019 and 2020 were digitized using in a Geographic Information System (GIS). Measures of dispersion and point pattern analysis (PPA) were used to analyze dispersal of GK population using GIS. Spatio-temporal change of GK dispersal in LBNR was evident thus the null hypothesis was rejected. It is recommended that anthropogenic activities contributing to GK’s habitat degradation be curbed by providing alternative livelihood sources and promoting community adoption of sustainable technologies for improved livelihoods.

Gas monitoring data anomaly identification based on spatio-temporal correlativity analysis

Based on spatio-temporal correlativity analysis method, the automatic identification techniques for data anomaly monitoring of coal mining working face gas are presented. The asynchronous correlative characteristics of gas migration in working face airflow direction are qualitatively analyzed. The calculation method of asynchronous correlation delay step and the prediction and inversion formulas of gas concentration changing with time and space after gas emission in the air return roadway are provided. By calculating one hundred and fifty groups of gas sensors data series from a coal mine which have the theoretical correlativity, the correlative coefficient values range of eight kinds of data anomaly is obtained. Then the gas moni- toring data anomaly identification algorithm based on spatio-temporal correlativity analysis is accordingly presented. In order to improve the efficiency of analysis, the gas sensors code rules which can express the spatial topological relations are sug- gested. The experiments indicate that methods presented in this article can effectively compensate the defects of methods based on a single gas sensor monitoring data.

Modeling and Analysis of Production Logistics Spatio-Temporal Graph Network Driven by Digital Twin

In the process of logistics distribution of manufacturing enterprises, the automatic scheduling method based on the algorithm model has the advantages of accurate calculation and stable operation, but it excessively relies on the results of data calculation, ignores historical information and empirical data in the solving process, and has the bottleneck of low processing dimension and small processing scale. Therefore, in the digital twin(DT) system based on virtual and real fusion, a modeling and analysis method of production logistics spatio-temporal graph network model is proposed, considering the characteristics of road network topology and time-varying data. In the DT system, the temporal graph network model of the production logistics task is established and combined with the network topology, and the historical scheduling information about logistics elements is stored in the nodes. When the dynamic task arrives, a multi-stage links probability prediction method is adopted to predict the possibility of loading, driving, and other link relationships between task-related entity nodes at each stage. Several experiments are carried out, and the prediction accuracy of the digital twin-based temporal graph network(DTGN) model trained by historical scheduling information reaches 99.2% when the appropriate batch size is selected. Through logistics simulation experiments, the feasibility and the effectiveness of production logistics spatio-temporal graph network analysis methods based on historical scheduling information are verified.

Modern applications of scanning electrochemical microscopy in the analysis of electrocatalytic surface reactions

Development of reaction-tailored electrocatalysts is becoming increasingly important as energy and environment are among key issues governing our sustainable future.Electrocatalysts are inherently optimized for application towards reactions of interest in renewable energy,such as those involved in water splitting and artificial photosynthesis,owing to its energy efficiency,simple fabrication,and ease of operation.In this view,it is important to secure logical design principles for the synthesis of electrocatalysts for various reactions of interest,and also understand their catalytic mechanisms in the respective reactions for improvements in further iterations.In this review,we introduce several key methods of scanning electrochemical microscopy(SECM)in its applications towards electrocatalysis.A brief history and a handful of seminal works in the SECM field is introduced in advancing the synthetic designs of electrocatalysts and elucidation of the operating mechanism.New developments in nano-sizing of the electrodes in attempts for improved spatial resolution of SECM is also introduced,and the application of nanoelectrodes towards the investigation of formerly inaccessible single catalytic entities is shared.

Spatio-temporal analysis of the incidence of colorectal cancer in Guangzhou,2010-2014

Introduction: Colorectal cancer(CRC) is a common type of neoplasm. This study examined the spatio?temporal distribution of the CRC incidence in Guangzhou during 2010–2014.Methods: Colorectal cancer incidence data were obtained from the Guangzhou Cancer Registry System. Spatial autocorrelation analysis and a retrospective spatio?temporal scan were used to assess the spatio?temporal cluster distribution of CRC cases.Results: A total of 14,618 CRC cases were registered in Guangzhou during 2010–2014, with a crude incidence of 35.56/100,000 and an age?standardized rate of incidence by the world standard population(ASRIW) of 23.58/100,000. The crude incidence increased by 19.70% from 2010(32.88/100,000) to 2014(39.36/100,000) with an average annual percentage change(AAPC) of 4.33%. The AAPC of ASRIW was not statistically significant. The spatial autocorrelation analysis revealed a CRC incidence hot spot in central urban areas in Guangzhou City, which included 25 streets in southwestern Baiyun District, northwestern Haizhu District, and the border region between Liwan and Yuexiu Dis?tricts. Three high? and five low?incidence clusters were identified according to spatio?temporal scan of CRC incidence clusters. The high?incidence clusters were located in central urban areas including the border regions between Bai?yun, Haizhu, Liwan, and Yuexiu Districts.Conclusions: This study revealed the spatio?temporal cluster pattern of the incidence of CRC in Guangzhou. This information can inform allocation of health resources for CRC screening.

Spatio-temporal analysis of the melt onset dates over Arctic sea ice from 1979 to 2017

The melt onset dates(MOD)over Arctic sea ice plays an important role in the seasonal cycle of sea ice surface properties,which impacts Arctic surface solar radiation absorbed by the ice-ocean system.Monitoring interannual variations in MOD is valuable for understanding climate change.In this study,we investigated the spatio-temporal variability of MOD over Arctic sea ice and 14 Arctic sub-regions in the period of 1979 to 2017 from passive microwave satellite data.A set of mathematical and statistical methods,including the Sen’s slope and Mann-Kendall mutation tests,were used to comprehensively assess the variation trend and abrupt points of MOD during the past 39 years for different Arctic sub-regions.Additionally,the correlation between Arctic Oscillation(AO)and MOD was analyzed.The results indicate that:(1)all Arctic sub-regions show a trend toward earlier MOD except the Bering Sea and St.Lawrence Gulf.The East Siberian Sea exhibits a significantly earlier trend,with the highest rate of-9.45 d/decade;(2)the temporal variability and statistical significance of MOD trend exhibit large interannual differences with different time windows for most regions in the Arctic;(3)during the past 39 years,the MOD changed abruptly in different years for different sub-regions;(4)the seasonal AO has more influence on MOD than monthly AO.The findings in this study can improve our knowledge of MOD changes and are beneficial for further Arctic climate change study.

DAVS:Dockerfile Analysis for Container Image Vulnerability Scanning

Container technology plays an essential role in many Information and Communications Technology(ICT)systems.However,containers face a diversity of threats caused by vulnerable packages within container images.Previous vulnerability scanning solutions for container images are inadequate.These solutions entirely depend on the information extracted from package managers.As a result,packages installed directly from the source code compilation,or packages downloaded from the repository,etc.,are ignored.We introduce DAVS–A Dockerfile analysis-based vulnerability scanning framework for OCI-based container images to deal with the limitations of existing solutions.DAVS performs static analysis using file extraction based on Dockerfile information to obtain the list of Potentially Vulnerable Files(PVFs).The PVFs are then scanned to figure out the vulnerabilities in the target container image.The experimental shows the outperform of DAVS on detecting Common Vulnerabilities and Exposures(CVE)of 10 known vulnerable images compared to Clair–the most popular container image scanning project.Moreover,DAVS found that 68%of real-world container images are vulnerable from different image registries.

Neutron Activation Analysis and Scanning Electron Microscopy of Phytoplankton in the Coastal Zone of Crimea (The Black Sea)

The physiology and ecology of planktonic organisms are influenced by the concentration, chemical speciation and resulting bioavailability of some trace metals. The determination of the elemental structure of phytoplankton is important for interpretation of physiological and functional states of coastal ecosystems. The present study is focused on the structure and elemental composition of the phytoplankton assemblages from the different coastal zones by instrumental neutron activation analysis (INAA), scanning electron microscopy (SEM) and energy-dispersive X-ray spectrometry (EDS). For the first time these complementary techniques were simultaneously applied to study the Black Sea phytoplankton. The concentrations of 45 elements in the coastal phytoplankton communities used as bioindicator of inorganic contamination of the Black Sea coastal area near Sevastopol, Ukraine, were determined. Phytoplankton samples were collected by total tows of the plankton net with 35 μm pore size at 3 stations situated in polluted and relatively pristine water areas of the Sevastopol coastal zone during autumn period of the phytoplankton growth. The concentration of Mg, Al, Sc, Ti, V, Mn, As, Rb, Ba, Th and Fe, Cr increases exponentially from relatively pristine station to more polluted station and 10-times and 3-times greater, respectively, in the phytoplankton of the Sevastopol Bay. The rare-earth elements have relatively the same concentration values less than 1 μg/g and tend to accumulate in the phytoplankton from the polluted station in the Sevastopol Bay. The obtained results are in a good agreement with the elemental concentration data in the oceanic plankton, plankton communities from the White Sea and the Black Sea. Using energy-dispersive X-ray spectrometry the mineral particles of unknown origin and impurities of copper (0.42% by weight) in the phytoplankton at the polluted station and zinc (0.57% by weight) at the relatively pristine station were determined.

Implementing geostatistical analysis to study spatio-temporal distribution patterns of swimming crabs(Portunus trituberculatus)

This study attempted to compare the performance of local polynomial interpolation,inverse distance weighted interpolation,and ordinary kriging in studying distribution patterns of swimming crabs.Cross-validation was used to select the optimum method to get distribution results,and kriging was used for making spatial variability analysis.Data were collected from 87 sampling stations in November of 2015(autumn)and February(winter),May(spring)and August(summer)of 2016.Results indicate that swimming crabs widely distributed in autumn and summer:in the summer,they were more spatially independent,and resources in each sampling station varied a lot;in the winter and spring,the abundance of crabs was much lower,but the individual crab size was bigger,and they showed the patchy and more concentrative distribution pattern,which means they were more spatially dependent.Distribution patterns were in accordance with ecological migration features of swimming crabs,which were affected by the changing marine environment.This study could infer that it is applicable to study crab fishery or even other crustacean species using geostatistical analysis.It not only helps practitioners have a better understanding of how swimming crabs migrate from season to season,but also assists researchers in carrying out a more comprehensive assessment of the fishery.Therefore,it may facilitate advancing the implementation in the pilot quota management program of swimming crabs in northern Zhejiang fishing grounds.

Analysis of Systematic Error Influences on Accuracy of Airborne Laser Scanning Altimetry

The error sources related to the laser rangefinder, GPS and INS are analyzed in details. Several coordinates systems used in airborne laser scanning are set up, and then the basic formula of system is given. This paper emphasizes on discussing the kinematic offset correction between GPS antenna phase center and laser fired point. And kinematic time delay influence on laser footprint position, the ranging errors, positioning errors, attitude errors and integration errors of the system are also explored. Finally, the result shows that the kinematic time delay can be neglected as compared with other error sources. The accuracy of the coordinates is not only influenced by the amplitude of the error, but also controlled by the operation parameters such as flight height, scanning angle amplitude and attitude magnitude of the platform.

Hotshots of Spatio-temporal Behavior of Chinese Residents in the Context of Big Data:Visual Analysis Based on CiteSpace

By using CiteSpace software to create a knowledge map of authors,institutions and keywords,the literature on the spatio-temporal behavior of Chinese residents based on big data in the architectural planning discipline published in the China Academic Network Publishing Database(CNKI)was analyzed and discussed.It is found that there was a lack of communication and cooperation among research institutions and scholars;the research hotspots involved four main areas,including“application in tourism research”,“application in traffic travel research”,“application in work-housing relationship research”,and“application in personal family life research”.

Numerical Investigation of Laser Surface Hardening of AISI 4340 Using 3D FEM Model for Thermal Analysis of Different Laser Scanning Patterns

Laser surface hardening is becoming one of the most successful heat treatment processes for improving wear and fatigue properties of steel parts. In this process, the heating system parameters and the material properties have important effects on the achieved hardened surface characteristics. The control of these variables using predictive modeling strategies leads to the desired surface properties without following the fastidious trial and error method. However, when the dimensions of the surface to be treated are larger than the cross section of the laser beam, various laser scanning patterns can be used. Due to their effects on the hardened surface properties, the attributes of the selected scanning patterns become significant variables in the process. This paper presents numerical and experimental investigations of four scanning patterns for laser surface hardening of AISI 4340 steel. The investigations are based on exhaustive modelling and simulation efforts carried out using a 3D finite element thermal analysis and structured experimental study according to Taguchi method. The temperature distribution and the hardness profile attributes are used to evaluate the effects of heating parameters and patterns design parameters on the hardened surface characteristics. This is very useful for integrating the scanning patterns’ features in an efficient predictive modeling approach. A structured experimental design combined to improved statistical analysis tools is used to assess the 3D model performance. The experiments are performed on a 3 kW Nd:Yag laser system. The modeling results exhibit a great agreement between the predicted and measured values for the hardened surface characteristics. The model evaluation reveals also its ability to provide not only accurate and robust predictions of the temperature distribution and the hardness profile as well an in-depth analysis of the effects of the process parameters.

ANALYSIS OF HUMAN PLACENTA BY ^(31)P NUCLEAR MAGNETIC RESONANCE AND THIN-LAYER CHROMATOGRAPHY SCANNING COMBINED WITH THE CORRECTIVE METHOD OF ABSORBANCE PROPORTIONAL COEFFICIENT

Five phospholipids in human placenta were determined by phosphorus 31 nuclear magnetic resonance(^(31)P NMR)spectroscopy and thin-layer chromatography(TLC) scanning combined with the corrective method of absorbance proportional coefficient. The NMR spectrometer used this investigation was a Bruker AM-500 spectrometer operating at 202.4 MHz for ^(31)P chemical shifts are relative to 85% phosphoric acid. TIC was carried out by silica gel H plate developed in chloroform-methanol-glacial acetic acid-ethanol-water(25:4:6:2:0.5),with Vaskovsky reagent as colour -developing agent of phospholipids.

Knowledge-embedded spatio-temporal analysis for euploidy embryos identification in couples with chromosomal rearrangements

Background:The goal of the assisted reproductive treatment is to transfer one euploid blastocyst and to help infertile women giving birth one healthy neonate.Some algorithms have been used to assess the ploidy status of embryos derived from couples with normal chromosome,who subjected to preimplantation genetic testing for aneuploidy(PGT-A)treatment.However,it is currently unknown whether artificial intelligence model can be used to assess the euploidy status of blastocyst derived from populations with chromosomal rearrangement.Methods:From February 2020 to May 2021,we collected the whole raw time-lapse videos at multiple focal planes from in vitro cultured embryos,the clinical information of couples,and the comprehensive chromosome screening results of those blastocysts that had received PGT treatment.Initially,we developed a novel deep learning model called the Attentive Multi-Focus Selection Network(AMSNet)to analyze time-lapse videos in real time and predict blastocyst formation.Building upon AMSNet,we integrated additional clinically predictive variables and created a second deep learning model,the Attentive Multi-Focus Video and Clinical Information Fusion Network(AMCFNet),to assess the euploidy status of embryos.The efficacy of the AMCFNet was further tested in embryos with parental chromosomal rearrangements.The receiver operating characteristic curve(ROC)was used to evaluate the superiority of the model.Results:A total of 4112 embryos with complete time-lapse videos were enrolled for the blastocyst formation prediction task,and 1422 qualified blastocysts received PGT-A(n=589)or PGT for chromosomal structural rearrangement(PGT-SR,n=833)were enrolled for the euploidy assessment task in this study.The AMSNet model using seven focal raw time-lapse videos has the best real-time accuracy.The real-time accuracy for AMSNet to predict blastocyst formation reached above 70%on the day 2 of embryo culture,and then increased to 80%on the day 4 of embryo culture.Combing with 4 clinical features of couples,the AUC of AMCFNet with 7 focal points increased to 0.729 in blastocysts derived from couples with chromosomal rearrangement.Conclusion:Integrating seven focal raw time-lapse images of embryos and parental clinical information,AMCFNet model have the capability of assessing euploidy status in blastocysts derived from couples with chromosomal rearrangement.

Feature Extraction of Sectorial Scan Image of Thick-Walled Electron Beam Welding Seam Based on Principal Component Analysis

A feature extraction method was proposed to sectorial scan image of Ti-6Al-4V electron beam welding seam based on principal component analysis to solve problem of high-dimensional data resulting in timeconsuming in defect recognition. Seven features were extracted from the image and represented 87. 3% information of the original data. Both the extracted features and the original data were used to train support vector machine model to assess the feature extraction performance in two aspects: recognition accuracy and training time. The results show that using the extracted features the recognition accuracy of pore,crack,lack of fusion and lack of penetration are 93%,90.7%,94.7% and 89.3%,respectively,which is slightly higher than those using the original data. The training time of the models using the extracted features is extremely reduced comparing with those using the original data.

T-Scan咬合分析系统在口腔治疗中的研究进展

在口腔临床治疗中,咬合功能的测量和分析对治疗发挥不可忽略的作用,而以往测量咬合状态的方法受口腔医师主观影响,准确性不高,无法量化。大量研究显示T-Scan咬合分析系统能精确测量不同咬合状态下的咬合力与时间实时的关系,精确记录咬合接触时间、力量、面积,并动态分析咬合接触情况。在颞颌关节紊乱疾病、正畸正颌、修复和种植、牙周病等多种口腔疾病治疗中,该系统协助临床医生执行精确和有针对性的咬合诊断和调整,并通过可预测和数值测量的治疗结果评价减少咬合并发症发生,获得良好的治疗效果。该系统量化的数据以可视化的方式展示出来,可最大限度地促进医患沟通,更能满足现代口腔疾病临床治疗的需求。本文就T-Scan咬合分析系统的特点及其在口腔临床中的应用进展做一综述。