Evaluation of the seismic behavior of reinforced concrete structures with flat slab-column gravity frame and shear walls through nonlinear analysis methods

This paper presents an investigation of the seismic behavior of reinforced concrete(RC)structures in which shear walls are the main lateral load-resisting elements and the participation of flat slab floor systems is not considered in the seismic design procedure.In this regard,the behavior of six prototype structures(with different heights and plan layouts)is investigated through nonlinear static and time history analyses,implemented in the OpenSees platform.The results of the analyses are presented in terms of the behavior of the slab-column connections and their mode of failure at different loading stages.Moreover,the global response of the buildings is discussed in terms of some parameters,such as lateral overstrength due to the gravity flat slab-column frames.According to the nonlinear static analyses,in structures in which the slab-column connections were designed only for gravity loads,the slab-column connections exhibited a punching mode of failure even in the early stages of loading.However,the punching failure was eliminated in structures in which a minimum transverse reinforcement recommended in ACI 318(2019)was provided in the slabs at joint regions.Furthermore,despite neglecting the contribution of gravity flat slab-column frames in the lateral load resistance of the structures,a relatively significant overstrength was imposed on the structures by the gravity frames.

Corrosion behavior of 2A97 Al-Cu-Li alloys in different thermomechanical conditions by quasi-in-situ analysis

As a promising material in the aircraft industry,2A97 Al-Cu-Li alloy exhibits high corrosion susceptibility that may limit its application.In the present work,to illustrate the influences of precipitate and grain-stored energy on localized corrosion evolution in 2A97 Al-Cu-Li alloy,cold working and artificial aging were carried out to produce 2A97 Al-Cu-Li alloys under different thermomechanical conditions.Quasi-in-situ analysis,traditional immersion test and electrochemical measurement were then conducted to examine the corrosion behavior of 2A97 alloys.It is revealed that precipitate significantly affects Cu enrichment at corrosion fronts,which determines corrosion susceptibility of alloys,whereas grain-stored energy distribution is closely associated with localized corrosion propagation.It is also indicated that quasi-in-situ analysis exhibits a consistent corrosion evolution with traditional immersion tests,which is regarded as a proper method to explore localized corrosion mechanisms by providing local microstructural information with enhanced time and spatial resolutions.

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.

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”.

Transformer-Aided Deep Double Dueling Spatial-Temporal Q-Network for Spatial Crowdsourcing Analysis

With the rapid development ofmobile Internet,spatial crowdsourcing has becomemore andmore popular.Spatial crowdsourcing consists of many different types of applications,such as spatial crowd-sensing services.In terms of spatial crowd-sensing,it collects and analyzes traffic sensing data from clients like vehicles and traffic lights to construct intelligent traffic prediction models.Besides collecting sensing data,spatial crowdsourcing also includes spatial delivery services like DiDi and Uber.Appropriate task assignment and worker selection dominate the service quality for spatial crowdsourcing applications.Previous research conducted task assignments via traditional matching approaches or using simple network models.However,advanced mining methods are lacking to explore the relationship between workers,task publishers,and the spatio-temporal attributes in tasks.Therefore,in this paper,we propose a Deep Double Dueling Spatial-temporal Q Network(D3SQN)to adaptively learn the spatialtemporal relationship between task,task publishers,and workers in a dynamic environment to achieve optimal allocation.Specifically,D3SQNis revised through reinforcement learning by adding a spatial-temporal transformer that can estimate the expected state values and action advantages so as to improve the accuracy of task assignments.Extensive experiments are conducted over real data collected fromDiDi and ELM,and the simulation results verify the effectiveness of our proposed models.

User Profile & Attitude Analysis Based on Unstructured Social Media and Online Activity

As social media and online activity continue to pervade all age groups, it serves as a crucial platform for sharing personal experiences and opinions as well as information about attitudes and preferences for certain interests or purchases. This generates a wealth of behavioral data, which, while invaluable to businesses, researchers, policymakers, and the cybersecurity sector, presents significant challenges due to its unstructured nature. Existing tools for analyzing this data often lack the capability to effectively retrieve and process it comprehensively. This paper addresses the need for an advanced analytical tool that ethically and legally collects and analyzes social media data and online activity logs, constructing detailed and structured user profiles. It reviews current solutions, highlights their limitations, and introduces a new approach, the Advanced Social Analyzer (ASAN), that bridges these gaps. The proposed solutions technical aspects, implementation, and evaluation are discussed, with results compared to existing methodologies. The paper concludes by suggesting future research directions to further enhance the utility and effectiveness of social media data analysis.

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.

Improving landscape Characteristics in Port Said’s El Sallam Garden via Observational and Space Syntax Analysis

This paper provides a comprehensive examination of El Sallam Garden in Port Said City,concentrating on its landscape characteristics and potential for design enhancement.This study looks at how space syntax can be used to assess the impact of a tree planting design’s spatial configuration on an urban park’s visual fields.Trees play an important role in determining the spatial characteristics of an outdoor space.According to space syntax theory,an urban area is a collection of connected spaces that can be represented by a matrix of quantitative properties known as syntactic measures.Computer simulations can be used to measure the quantitative properties of these matrices.This study uses space syntax techniques to assess how tree configurations and garden area which can affect the social structures of small-scale gardens in Port Said.It also looks at how these techniques can be used to predict the social structures of four garden zones in El Sallam Garden.The study includes an observational and space syntax study through comparative analysis of four garden zones in El Sallam garden.The results of the study show that the area and planting configurations of the garden had a significant effect on the syntactic social and visual measures of the urban garden.The conclusions and recommendations can be a useful tool for landscape architects,urban planners,and legislators who want to enhance public areas and encourage social interaction in urban settings.

Transportation mobility during COVID-19:a systematic review and bibliometric analysis

The COVID-19 pandemic has significantly affected global transportation mobility,presenting unprecedented challenges to transportation management.Public transit and ride-hailing services saw a drastic reduction in ridership,leading to an increased inclination towards private vehicles.The pandemic also altered travel patterns and individual mobility due to various COVID-19 protocols.This study conducted a comprehensive review of 96 academic papers spanning from January 1,2020,to December 31,2022,focusing on transportation and mobility using the Scopus database.Three major themes were identified:‘Impact on Ride-Hailing Services',‘Impact on Mode Preference',and‘Impact on Trip Purpose',with subdivisions based on keywords and key findings extracted using VOSviewer.The pandemic significantly impacted ride-hailing services,altering demand,usage,and safety measures.Mode preference shifted towards private vehicles due to safety concerns.The present study underscores the long-term implications of the pandemic,emphasizing recovery strategies for ride-hailing services and mode preferences post-pandemic.It highlights the need for sustainable transportation policies,advocating for enhanced public transportation systems,promoting active travel modes,and addressing socioeconomic disparities in mobility patterns.The findings emphasize the need for resilient transportation strategies in the face of future disruptions.

Behavior analysis and formative assessments in online oral medicine education during the COVID-19 pandemic

BACKGROUND During the coronavirus disease 2019(COVID-19)pandemic,traditional teaching methods were disrupted and online teaching became a new topic in education reform and informatization.In this context,it is important to investigate the necessity and effectiveness of online teaching methods for medical students.This study explored stomatology education in China to evaluate the development and challenges facing the field using massive open online courses(MOOCs)for oral medicine education during the pandemic.AIM To investigate the current situation and challenges facing stomatology education in China,and to assess the necessity and effectiveness of online teaching methods among medical students.METHODS Online courses were developed and offered on personal computers and mobile terminals.Behavioral analysis and formative assessments were conducted to evaluate the learning status of students.RESULTS The results showed that most learners had already completed MOOCs and achieved better results.Course behavior analysis and student surveys indicated that students enjoyed the learning experience.However,the development of oral MOOCs during the COVID-19 pandemic faced significant challenges.CONCLUSION This study provides insights into the potential of using MOOCs to support online professional learning and future teaching innovation,but emphasizes the need for careful design and positive feedback to ensure their success.

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.

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.

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 Eco-tourism Tourist Behavior and Potential Market in Taibai Mountain

This paper provided full and accurate material for Taibai Mountain eco-tourism and forecasted its potential market through investigating on the visitors of Taibai Mountain Nature Reserve and the surrounding forest parks eco-tourism tourist.By using Excel and mapping method,this study described the sample characteristics and tourist behavior.In addition,this paper also carried on descriptive statistics factorial analysis by using SPSS statistics software,analyzed the potential market according to tourists' characteristics of Taibai Mountain.The survey results showed that visitors of Taibai Mountain Nature Reserve mainly were middle-income young people,and the majority of tourists were with higher education.With the purpose of enjoying the scenery and relaxing,tourists were interested in natural ecological landscape of Taibai Mountain Nature Reserve.Tourists mainly came from Shaanxi Province and preferred to day trip,the travel route was single.There were a small number of tourists travelling for business,conference and medical treatment in Taibai Mountain Nature Reserve.According to the analysis,related countermeasures were given in this paper as the following:① Promoting activities should be focused on the big or medium cities in Shaanxi Province,such as Xi'an,Xianyang,Baoji,etc..Meanwhile,various means should be adopted to expand its influence and raise awareness around the provincial cities for attracting tourists.② Strengthening the infrastructure construction and improving comprehensive tourist reception capacity with the pursuit of the diversity of tourism resources,and create a good environment for the tourism market;③ Focusing on tourism product development;④ Protecting the ecological resources and developing ecotourism.

2011—2015年国际应用行为分析热点研究——以《Journal of Applied Behavior Analysis》为例

为了探究应用行为分析在国外的研究成果和动态,利用共词分析的原理对2011—2015年JABA刊文的关键词进行了分析,结果显示近五年国外应用行为分析研究热点有自闭症谱系障碍、功能分析、区别性强化、口语行为、进食障碍等。对这些热点进行分类,探讨了各领域所处的研究地位,最后提出我国学界不仅要加强应用行为分析在特殊儿童问题行为管理和干预中的运用,也要把它推广到其他领域。

Dynamic Evolutionary Game-based Modeling,Analysis and Performance Enhancement of Blockchain Channels

The recent development of channel technology has promised to reduce the transaction verification time in blockchain operations.When transactions are transmitted through the channels created by nodes,the nodes need to cooperate with each other.If one party refuses to do so,the channel is unstable.A stable channel is thus required.Because nodes may show uncooperative behavior,they may have a negative impact on the stability of such channels.In order to address this issue,this work proposes a dynamic evolutionary game model based on node behavior.This model considers various defense strategies'cost and attack success ratio under them.Nodes can dynamically adjust their strategies according to the behavior of attackers to achieve their effective defense.The equilibrium stability of the proposed model can be achieved.The proposed model can be applied to general channel networks.It is compared with two state-of-the-art blockchain channels:Lightning network and Spirit channels.The experimental results show that the proposed model can be used to improve a channel's stability and keep it in a good cooperative stable state.Thus its use enables a blockchain to enjoy higher transaction success ratio and lower transaction transmission delay than the use of its two peers.

Assessment of hindlimb motor recovery affer severe thoracic spinal cord injury in rats: classification of CatWalk XT■ gait analysis parameters

Assessment of locomotion recovery in preclinical studies of experimental spinal cord injury remains challenging. We studied the CatWalk XT■gait analysis for evaluating hindlimb functional recovery in a widely used and clinically relevant thoracic contusion/compression spinal cord injury model in rats. Rats were randomly assigned to either a T9 spinal cord injury or sham laminectomy. Locomotion recovery was assessed using the Basso, Beattie, and Bresnahan open field rating scale and the CatWalk XT■gait analysis. To determine the potential bias from weight changes, corrected hindlimb(H) values(divided by the unaffected forelimb(F) values) were calculated. Six weeks after injury, cyst formation, astrogliosis, and the deposition of chondroitin sulfate glycosaminoglycans were assessed by immunohistochemistry staining. Compared with the baseline, a significant spontaneous recovery could be observed in the CatWalk XT■parameters max intensity, mean intensity, max intensity at%, and max contact mean intensity from 4 weeks after injury onwards. Of note, corrected values(H/F) of CatWalk XT■parameters showed a significantly less vulnerability to the weight changes than absolute values, specifically in static parameters. The corrected CatWalk XT■parameters were positively correlated with the Basso, Beattie, and Bresnahan rating scale scores, cyst formation, the immunointensity of astrogliosis and chondroitin sulfate glycosaminoglycan deposition. The CatWalk XT■gait analysis and especially its static parameters, therefore, seem to be highly useful in assessing spontaneous recovery of hindlimb function after severe thoracic spinal cord injury. Because many CatWalk XT■parameters of the hindlimbs seem to be affected by body weight changes, using their corrected values might be a valuable option to improve this dependency.

The Research on E-mail Users' Behavior of Participating in Subjects Based on Social Network Analysis

The e-mail network is a type of social network. This study analyzes user behavior in e-mail subject participation in organizations by using social network analysis. First, the Enron dataset and the position-related information of an employee are introduced, and methods for deletion of false data are presented. Next, the three-layer model(User, Subject, Keyword) is proposed for analysis of user behavior. Then, the proposed keyword selection algorithm based on a greedy approach, and the influence and propagation of an e-mail subject are defined. Finally, the e-mail user behavior is analyzed for the Enron organization. This study has considerable significance in subject recommendation and character recognition.