The public health workforce is a key component of public health system.To articulate the scope of public health workforce,we reviewed the relevant World Health Organization(wHO)guidance and peer-reviewed journal artic...The public health workforce is a key component of public health system.To articulate the scope of public health workforce,we reviewed the relevant World Health Organization(wHO)guidance and peer-reviewed journal articles on this subject.Specifically,we assessed and compared the relevant publications produced by WHO Headquarters and Regional Offices along with other literature on this issue.Our focus was on the“occupation,workplace setting,and employer of public health workforce”.It is noteworthy that WHO has adopted a conceptual framework with an inclusive scope of the public health workforce,while setting out a 5-year vision to strengthen capacity across all WHO Member States for a multidisciplinary workforce to deliver the essential public health functions,including emergency preparedness and response.The importance of public health workforce in global and national responses to the coronavirus disease 2019(COVID-19)pandemic is recognized.We also observed that there were diverse understandings of the scope of public health workforce worldwide,including macro-,meso-and micro-level perspectives.In the post-COVID-19 era,we suggest that policy-makers and practitioners at the national,regional and global level adopt a coordinated approach to expand and strengthen the national workforce as guided by the WHO towards the health-related targets of United Nations Sustainable Development Goals such as health security and Universal Health Coverage.展开更多
Dictated handwriting samples are widely used in practice due to their simplicity,convenience,and practicality.However,dictation is typically listed as one of the many collection methods in textbooks and monographs,and...Dictated handwriting samples are widely used in practice due to their simplicity,convenience,and practicality.However,dictation is typically listed as one of the many collection methods in textbooks and monographs,and there is usually no separate section focusing on dictated handwriting samples.Therefore,further study of dictated handwriting samples will have important practical significance.Consideration of the definition,existing problems,collection techniques,and critical aspects of dictated handwriting samples willsupport investigators and document examiners in their professional abilities and contribute to the theoretical system of document examination.In this article,an exploratory analysis will be conducted and ideas about dictated handwriting samples will be shared,including the definition of dictated samples,their relationship to experimental samples,practical problems,feasible collection methods,and some critical points that require special attention.Dictation is widely used but problematic because of a lack of quantity and low levels of comparability.Those difficulties are mainly caused by a lack of theoreticalstudy and understanding of the requirements and collection techniques of dictated handwriting samples among first‑line investigators.Dictated samples should be collected based on subjective and objective conditions of formation with aims to improve comparability and five similarities.Further studies are needed to improve the theoretical system and practical use of dictated samples so that they can contribute to successfully reaching conclusions in investigations.展开更多
The purpose of this study was to explore the psychometric properties of the Chinese version of the autism spectrum rating scale（ASRS）. We recruited 1,625community-based children and 211 autism spectrum disorder（ASD...The purpose of this study was to explore the psychometric properties of the Chinese version of the autism spectrum rating scale（ASRS）. We recruited 1,625community-based children and 211 autism spectrum disorder（ASD） cases from 4 sites, and the parents of all participants completed the Chinese version of the ASRS. A robust weighted least squares means and variance adjusted estimator was used for exploratory factor analysis. The3-factor structure included 59 items suitable for the current sample. The item reliability for the modi？ed Chinese version of the ASRS（MC-ASRS） was excellent. Moreover,with 60 as the cut-off point, receiver operating characteristic analysis showed that the MC-ASRS had excellent discriminate validity, comparable to that of the unmodi？ed Chinese version（UC-ASRS）, with area under the curve values of 0.952（95% CI： 0.936–0.967） and 0.948（95% CI：0.930–0.965）, respectively. Meanwhile, the con？rm factor analysis revealed that MC-ASRS had a better construct validity than UC-ASRS based on the above factor solution in another children sample. In conclusion, the MC-ASRS shows better ef？cacy in epidemiological screening for ASD in Chinese children.展开更多
A factor analysis was applied to soil geochemical data to define anomalies related to buried Pb-Zn mineralization.A favorable main factor with a strong association of the elements Zn,Cu and Pb,related to mineralizatio...A factor analysis was applied to soil geochemical data to define anomalies related to buried Pb-Zn mineralization.A favorable main factor with a strong association of the elements Zn,Cu and Pb,related to mineralization,was selected for interpretation.The median+2 MAD(median absolute deviation)method of exploratory data analysis(EDA)and C-A(concentration-area)fractal modeling were then applied to the Mahalanobis distance,as defined by Zn,Cu and Pb from the factor analysis to set the thresholds for defining multi-element anomalies.As a result,the median+2 MAD method more successfully identified the Pb-Zn mineralization than the C-A fractal model.The soil anomaly identified by the median+2 MAD method on the Mahalanobis distances defined by three principal elements(Zn,Cu and Pb)rather than thirteen elements(Co,Zn,Cu,V,Mo,Ni,Cr,Mn,Pb,Ba,Sr,Zr and Ti)was the more favorable reflection of the ore body.The identified soil geochemical anomalies were compared with the in situ economic Pb-Zn ore bodies for validation.The results showed that the median+2 MAD approach is capable of mapping both strong and weak geochemical anomalies related to buried Pb-Zn mineralization,which is therefore useful at the reconnaissance drilling stage.展开更多
Exploratory data analysis plays a major role in obtaining insights from data.Over the last two decades,researchers have proposed several visual data exploration tools that can assist with each step of the analysis pro...Exploratory data analysis plays a major role in obtaining insights from data.Over the last two decades,researchers have proposed several visual data exploration tools that can assist with each step of the analysis process.Nevertheless,in recent years,data analysis requirements have changed significantly.With constantly increasing size and types of data to be analyzed,scalability and analysis duration are now among the primary concerns of researchers.Moreover,in order to minimize the analysis cost,businesses are in need of data analysis tools that can be used with limited analytical knowledge.To address these challenges,traditional data exploration tools have evolved within the last few years.In this paper,with an in-depth analysis of an industrial tabular dataset,we identify a set of additional exploratory requirements for large datasets.Later,we present a comprehensive survey of the recent advancements in the emerging field of exploratory data analysis.We investigate 50 academic and non-academic visual data exploration tools with respect to their utility in the six fundamental steps of the exploratory data analysis process.We also examine the extent to which these modern data exploration tools fulfill the additional requirements for analyzing large datasets.Finally,we identify and present a set of research opportunities in the field of visual exploratory data analysis.展开更多
Over the past years,there has been an expanding intrigued in building refurbishment projects because of the alter in financial conditions and the accentuation on sustainable development.Increasing demand for building ...Over the past years,there has been an expanding intrigued in building refurbishment projects because of the alter in financial conditions and the accentuation on sustainable development.Increasing demand for building refurbishment projects will lead to an increase in organizational interactions in the construction works as building refurbishment works involve interactions among many different organizations and it can cause Inter-Organizational conflict(IOC)among organizations involved in projects.This paper adopted an Exploratory Factor Analysis(EFA)approach to analyses IOC in building refurbishment projects.For this study,a fivepoint Likert Scale was adopted to ensure the instruments of the study are reliable.The researcher ultimately sent questionnaires as a web-link and email invitation to 1050 construction firms and 733 architectural firms.The questionnaire sent to managers and professionals from construction and architectural firms in Malaysia.Finally,one-hundred-seventy-nine(179)refurbishment projects formed a database for this paper.The finding of this paper shows the IOC factors that contribute to the improve the performance of building refurbishment project can be conflict during the construction stage,conflict between the client and the consultant,task expectations,basic responsibilities,final duration,project’s goals,conflict between the client and the contractor,final cost,final quality,standards of behaviors,conflict between the contractor and the consultant,interference and conflict during the design stage.展开更多
Being the major players in promoting innovation,enterprises are therefore central to innovation–based development.Establishing how vibrant they are in terms of innovation has become a heavily debated issue in both ac...Being the major players in promoting innovation,enterprises are therefore central to innovation–based development.Establishing how vibrant they are in terms of innovation has become a heavily debated issue in both academic and industry circles.Through a sample involving Chinese listed companies in advanced material manufacturing,this study utilizes exploratory factor analysis to develop an evaluation system of enterprises’innovation vitality on the basis of three dimensions:innovation persistence,volatility,and growth.The study establishes deeper interaction between innovation vitality and two major indicators-persistence and volatility formats input and cooperation,while also promoting the growth of innovative input and output.This study adds insights related to the objective assessment of enterprises’innovation vitality and the promotion of subsequent innovation efforts.展开更多
BACKGROUND Esophageal cancer(EC),primarily esophageal squamous cell carcinoma in China,has a poor prognosis with a 5-year survival rate of approximately 25%after surgery alone.Neoadjuvant chemoradiotherapy combined wi...BACKGROUND Esophageal cancer(EC),primarily esophageal squamous cell carcinoma in China,has a poor prognosis with a 5-year survival rate of approximately 25%after surgery alone.Neoadjuvant chemoradiotherapy combined with surgery is the standard treatment for locally advanced EC,with a 47%5-year survival rate,although adverse events are common.Immunotherapy,particularly PD-1 inhibitors,has shown promise in treating advanced EC,and neoadjuvant chemotherapy with immunotherapy is effective.However,the efficacy of postoperative immunotherapy remains unclear,with studies like Checkmate577 showing promising results but limited applicability to surgery-only patients,highlighting the need for further research.AIM To evaluate the efficacy,prognostic factors,and safety of adjuvant immunotherapy with anti-PD-1 inhibitors following radical surgery for EC.METHODS A retrospective analysis was conducted on EC patients who received adjuvant immunotherapy after radical treatment at the 900th Hospital of the China Joint Logistics Force between January 2018 and October 2024.Demographic,treatment and laboratory data were collected.Progression-free survival(PFS)was assessed using the Kaplan-Meier method,and independent prognostic factors were identified using Cox regression.Optimal cutoff values for continuous variables,including body mass index(BMI)difference and neutrophil-to-lymphocyte ratio(NLR),were determined using the maxstat package in R.RESULTS A total of 44 patients were included,with a 2-year PFS rate of 68.6%[95%confidence interval(CI):53%-88.7%].Univariate analysis identified several factors significantly associated with prognosis,including the interval between surgery and immunotherapy,BMI difference between before surgery and first immunotherapy,presurgical lymphocyte count,and presurgical NLR.Multivariable Cox regression revealed that a BMI difference<3.86 was an independent protective factor for PFS(hazard ratio:0.42,95%CI:0.21-0.85,P<0.05).At the last followup,the median PFS for patients with BMI<3.86 had not been reached,compared to 8.83 months for those with BMI>3.86.The 1-year PFS for patients receiving postoperative chemotherapy combined with immunotherapy was 88.5%,suggesting superior efficacy over chemotherapy alone.CONCLUSION Adjuvant immunotherapy for EC shows good efficacy and safety.A BMI difference<3.86 is a protective factor for PFS,highlighting the importance of monitoring nutrition and inflammation for personalized treatment.展开更多
Improving early diagnosis of autism spectrum disorder(ASD)in children increasingly relies on predictive models that are reliable and accessible to non-experts.This study aims to develop such models using Python-based ...Improving early diagnosis of autism spectrum disorder(ASD)in children increasingly relies on predictive models that are reliable and accessible to non-experts.This study aims to develop such models using Python-based tools to improve ASD diagnosis in clinical settings.We performed exploratory data analysis to ensure data quality and identify key patterns in pediatric ASD data.We selected the categorical boosting(CatBoost)algorithm to effectively handle the large number of categorical variables.We used the PyCaret automated machine learning(AutoML)tool to make the models user-friendly for clinicians without extensive machine learning expertise.In addition,we applied Shapley additive explanations(SHAP),an explainable artificial intelligence(XAI)technique,to improve the interpretability of the models.Models developed using CatBoost and other AI algorithms showed high accuracy in diagnosing ASD in children.SHAP provided clear insights into the influence of each variable on diagnostic outcomes,making model decisions transparent and understandable to healthcare professionals.By integrating robust machine learning methods with user-friendly tools such as PyCaret and leveraging XAI techniques such as SHAP,this study contributes to the development of reliable,interpretable,and accessible diagnostic tools for ASD.These advances hold great promise for supporting informed decision-making in clinical settings,ultimately improving early identification and intervention strategies for ASD in the pediatric population.However,the study is limited by the dataset’s demographic imbalance and the lack of external clinical validation,which should be addressed in future research.展开更多
The analysis of Android malware shows that this threat is constantly increasing and is a real threat to mobile devices since traditional approaches,such as signature-based detection,are no longer effective due to the ...The analysis of Android malware shows that this threat is constantly increasing and is a real threat to mobile devices since traditional approaches,such as signature-based detection,are no longer effective due to the continuously advancing level of sophistication.To resolve this problem,efficient and flexible malware detection tools are needed.This work examines the possibility of employing deep CNNs to detect Android malware by transforming network traffic into image data representations.Moreover,the dataset used in this study is the CIC-AndMal2017,which contains 20,000 instances of network traffic across five distinct malware categories:a.Trojan,b.Adware,c.Ransomware,d.Spyware,e.Worm.These network traffic features are then converted to image formats for deep learning,which is applied in a CNN framework,including the VGG16 pre-trained model.In addition,our approach yielded high performance,yielding an accuracy of 0.92,accuracy of 99.1%,precision of 98.2%,recall of 99.5%,and F1 score of 98.7%.Subsequent improvements to the classification model through changes within the VGG19 framework improved the classification rate to 99.25%.Through the results obtained,it is clear that CNNs are a very effective way to classify Android malware,providing greater accuracy than conventional techniques.The success of this approach also shows the applicability of deep learning in mobile security along with the direction for the future advancement of the real-time detection system and other deeper learning techniques to counter the increasing number of threats emerging in the future.展开更多
Urban resilience assesses a city’s ability to withstand unknown risks.Scholars are not comprehensive in assessing urban resilience,and they lack consideration of population resilience.This study investigated 110 pref...Urban resilience assesses a city’s ability to withstand unknown risks.Scholars are not comprehensive in assessing urban resilience,and they lack consideration of population resilience.This study investigated 110 prefecturelevel cities in the Yangtze River Economic Belt(YREB)as study areas.We calculated the YREB’s level of urban resilience based on the aspects of“economy-society-population-ecology-infrastructure”,which ensured that the comprehensive evaluation of urban resilience is complete and sufficient.The spatio-temporal evolution of urban resilience was analyzed using exploratory spatial data.Geodetectors were used to investigate the impact of several indicators,focusing on economic,social,population,ecological,and infrastructure factors,on urban resilience.The results showed that the urban resilience of the YREB has maintained a slow upward trend from 2005 to 2018,and the average urban resilience of the YREB has risen from 0.2442 to 0.2560.The resilience gap between cities in the study region increased initially and then decreased.The dominant factor in the spatial differentiation of urban resilience was the economic factors,followed by the population factors.Urban resilience has been clarified and an evaluation index system is constructed,which can provide an effective reference for the evaluation of urban resilience among countries around the world.Based on this,factors that optimize urban resilience are configured,and the regional and national sustainable development can be promoted.展开更多
Self-regulated learning （SRL） is one of the precious ways in teachers＇ professional development, and its operation level includes different factors. With studies abroad and our preliminary investigation as base, th...Self-regulated learning （SRL） is one of the precious ways in teachers＇ professional development, and its operation level includes different factors. With studies abroad and our preliminary investigation as base, this study developed a scale to test the factors SRL includes. According to the result of 905 teachers working in elementary school by exploratory factor analysis, the SRL for elementary teachers is consisted of its sociality （it included selecting leads and seeking for instructing）, its motivation（it included self-improvement and self-excelling）, its methods（it included strategy use and habitual behavior）, and its outcomes（it included extensive reading and teachers＇ professional development）. All the result indicated Teachers＇ SRL Scale had clear factor structure, good reliability and validity. It can be used to test the current operating situation of SRL for teachers working in elementary school.展开更多
The Yellow River Basin of China is a key region that contains myriad interactions between human activities and natural environment.Industrialization and urbanization promote social-economic development,but they also h...The Yellow River Basin of China is a key region that contains myriad interactions between human activities and natural environment.Industrialization and urbanization promote social-economic development,but they also have generated a series of environmental and ecological issues in this basin.Previous researches have evaluated urban resilience at the national,regional,urban agglomeration,city,and prefecture levels,but not at the watershed level.To address this research gap and elevate the Yellow River Basin’s urban resilience level,we constructed an urban resilience evaluation index system from five dimensions:industrial resilience,social resilience,environmental resilience,technological resilience,and organizational resilience.The entropy weight method was used to comprehensively evaluate urban resilience in the Yellow River Basin.The exploratory spatial data analysis method was employed to study the spatiotemporal differences in urban resilience in the Yellow River Basin in 2010,2015,and 2020.Furthermore,the grey correlation analysis method was utilized to explore the influencing factors of these differences.The results of this study are as follows:(1)the overall level of urban resilience in the Yellow River Basin was relatively low but showed an increasing trend during 2010–2015,and significant spatial distribution differences were observed,with a higher resilience level in the eastern region and a low-medium resilience level in the western region;(2)the differences in urban resilience were noticeable,with industrial resilience and social resilience being relatively highly developed,whereas organizational resilience and environmental resilience were relatively weak;and(3)the correlation ranking of resilience influencing factors was as follows:science and technology level>administrative power>openness>market forces.This research can provide a basis for improving the resilience level of cities in the Yellow River Basin and contribute to the high-quality development of the region.展开更多
Factor analysis is widely utilized to identify latent factors underlying the observed variables.This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of fa...Factor analysis is widely utilized to identify latent factors underlying the observed variables.This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis,the K1 rule,and parallel analysis,along with a more recently developed method,the bass-ackward method.We provide an in-depth exploration of these techniques,discussing their historical development,advantages,and limitations.Using a series of Monte Carlo simulations,we assess the efficacy of these methods in accurately determining the appropriate number of factors.Specifically,we examine two cessation criteria within the bass-ackward framework:BA-maxLoading and BA-cutoff.Our findings offer nuanced insights into the performance of these methods under various conditions,illuminating their respective advantages and potential pitfalls.To enhance accessibility,we create an online visualization tool tailored to the factor structures generated by the bass-ackward method.This research enriches the understanding of factor analysis methodology,assists researchers in method selection,and facilitates comprehensive interpretation of latent factor structures.展开更多
AIM To understand the experience of maternal depression,the factors implicated in accessing health,and the acceptability of the psychosocial intervention.METHODS The participants were recruited from the paediatrics ou...AIM To understand the experience of maternal depression,the factors implicated in accessing health,and the acceptability of the psychosocial intervention.METHODS The participants were recruited from the paediatrics outpatient department of Civil Hospital Karachi,Pakistan.The study started in December 2009 and completed in December 2010.Women with maternal depression,aged 18-44 years with children aged 0-30 mo who had received nutritional supplements,and participated in the intervention programme[called Learning through Play(LTP)plus]were included in the study.Qualitative interviews were conducted with 8 participants before the intervention and 7 participants after the intervention.A semi structured topic guide was used to conduct the interviews.RESULTS Framework analysis procedures were used to analyse the qualitative data.Four themes emerged:(1)the women's contextual environment:Interpersonal conflicts,lack of social support and financial issues being the major barriers in assessing healthcare;(2)women's isolation and powerlessness within the environment:Sense of loneliness was identified as a restricting factor to access healthcare;(3)the impact of the intervention(LTP-Plus):Women felt"listened to"and seemed empowered;and(4)empowered transformed women within the same contextual environment:The facilitator provided a"gardening role"in nurturing the women resulting in a positive transformation within the same environment.The women's homes seemed to be more happy homes and there was a positive change in their behaviour towards their children.CONCLUSION Findings informed the further development and testing of culturally-appropriate psychosocial intervention(LTP^+)for addressing maternal depression.展开更多
In 2007,China surpassed the USA to become the largest carbon emitter in the world.China has promised a 60%–65%reduction in carbon emissions per unit GDP by 2030,compared to the baseline of 2005.Therefore,it is import...In 2007,China surpassed the USA to become the largest carbon emitter in the world.China has promised a 60%–65%reduction in carbon emissions per unit GDP by 2030,compared to the baseline of 2005.Therefore,it is important to obtain accurate dynamic information on the spatial and temporal patterns of carbon emissions and carbon footprints to support formulating effective national carbon emission reduction policies.This study attempts to build a carbon emission panel data model that simulates carbon emissions in China from 2000–2013 using nighttime lighting data and carbon emission statistics data.By applying the Exploratory Spatial-Temporal Data Analysis(ESTDA)framework,this study conducted an analysis on the spatial patterns and dynamic spatial-temporal interactions of carbon footprints from 2001–2013.The improved Tapio decoupling model was adopted to investigate the levels of coupling or decoupling between the carbon emission load and economic growth in 336 prefecture-level units.The results show that,firstly,high accuracy was achieved by the model in simulating carbon emissions.Secondly,the total carbon footprints and carbon deficits across China increased with average annual growth rates of 4.82%and 5.72%,respectively.The overall carbon footprints and carbon deficits were larger in the North than that in the South.There were extremely significant spatial autocorrelation features in the carbon footprints of prefecture-level units.Thirdly,the relative lengths of the Local Indicators of Spatial Association(LISA)time paths were longer in the North than that in the South,and they increased from the coastal to the central and western regions.Lastly,the overall decoupling index was mainly a weak decoupling type,but the number of cities with this weak decoupling continued to decrease.The unsustainable development trend of China’s economic growth and carbon emission load will continue for some time.展开更多
Rural development inequality is an important practical issue during the course of full establishment of a ′moderately well-off society′ in modern China,and the objective understanding and evaluation of the status an...Rural development inequality is an important practical issue during the course of full establishment of a ′moderately well-off society′ in modern China,and the objective understanding and evaluation of the status and regional inequality of rural development can provide scientific basis for ′building a new countryside′ and coordination development of rural-urban regions.Based on the county-level data of 2000,2005 and 2009,this paper examines the rural development inequality of Jilin Province in Northeast China by establishing a rural development index.The spatio-temporal dynamic patterns and domain factors are discussed by using the method of exploratory spatial data analysis and multi-regression model.The results are shown as follows.Firstly,most of the counties were in lower development level,which accounted for 58.3%,62.5% and 66.7% of the total counties in 2000,2005 and 2009,respectively.The characteristics of spatial inequality were very obvious at county level.For example,rural development level of Changchun Proper and the proper of seven prefecture-level cities were much higher than that of the surrounding regions.The counties in the eastern and northern Jilin Province were the lowest regions of rural development level,while the middle counties were the rapid growth areas in rural economy.Secondly,Moran′s I of rural development index(RDI) was 0.01,–0.16 and –0.06 in 2000,2005 and 2009,respectively,which indicated that spatial agglomeration of RDI was not obvious in Jilin Province,and took on the characteristic of random distribution.The counties of both the units and its adjacent units have higher development level(HH) were transferred from the western areas to the eastern areas,while the countries of both the units and its adjacent units have lower development level(LL) were diffused from the eastern to middle and western Jilin Province.Finally,the result of multi-regression analysis showed that the improvement of agricultural production condition,development of agricultural economics and the adjustment of industrial structure were the domain factors affecting rural development inequality of Jilin Province in the later ten years.展开更多
This paper principally focuses on the morphological differences,spatial pattern and regional types of rural settlements in Xuzhou City of Jiangsu Province in China.Using satellite images of Xuzhou City taken in 2007 a...This paper principally focuses on the morphological differences,spatial pattern and regional types of rural settlements in Xuzhou City of Jiangsu Province in China.Using satellite images of Xuzhou City taken in 2007 and 2008 and models of exploratory spatial data analysis(ESDA) and spatial metrics,the paper conducts a quantitative analysis of the morphological pattern of rural settlements,and finds significant characteristics.First,rural settlements in Xuzhou City are significantly agglomerated in terms of their spatial distribution;meanwhile,there is significant variation in the geographical density distribution.Second,the scale of rural settlements in Xuzhou City is larger than the average in Jiangsu Province,and the histogram of the scale data is more even and more like a gamma distribution.There are a significant high-value cluster in the scale distribution,and local negative correlation between the scale and density distribution of rural settlements in Xuzhou City.Third,the morphology of rural settlements in Xuzhou City shows relative regularity with good connection and integrity,but the spatial variation of the morphology is anisotropic.Finally,according to the characteristics of density,scale,and form of rural settlements,the rural settlements of Xuzhou City are divided into three types:A high-density and point-scattered type,a low-density and cluster-like type and a mass-like and sparse type.The research findings could be used as the scientific foundation for rural planning and community rebuilding,particularly in less-developed areas.展开更多
With the increasing effects of global climate change and fishing activities,the spatial distribution of the neon flying squid(Ommastrephes bartramii) is changing in the traditional fishing ground of 150°-160°...With the increasing effects of global climate change and fishing activities,the spatial distribution of the neon flying squid(Ommastrephes bartramii) is changing in the traditional fishing ground of 150°-160°E and 38°-45°N in the northwest Pacific Ocean.This research aims to identify the spatial hot and cold spots(i.e.spatial clusters) of O.bartramii to reveal its spatial structure using commercial fishery data from2007 to 2010 collected by Chinese mainland squid-j igging fleets.A relatively strongly-clustered distribution for O.bartramii was observed using an exploratory spatial data analysis(ESDA) method.The results show two hot spots and one cold spot in 2007 while only one hot and one cold spots were identified each year from2008 to 2010.The hot and cold spots in 2007 occupied 8.2%and 5.6%of the study area,respectively;these percentages for hot and cold spot areas were 5.8%and 3.1%in 2008,10.2%and 2.9%in 2009,and 16.4%and 11.9%in 2010,respectively.Nearly half(>45%) of the squid from 2007 to 2009 reported by Chinese fleets were caught in hot spot areas while this percentage reached its peak at 68.8%in 2010,indicating that the hot spot areas are central fishing grounds.A further change analysis shows the area centered at156°E/43.5°N was persistent as a hot spot over the whole period from 2007 to 2010.Furthermore,the hot spots were mainly identified in areas with sea surface temperature(SST) in the range of 15-20℃ around warm Kuroshio Currents as well as with the chlorophyll-a(chl-a) concentration above 0.3 mg/m^3.The outcome of this research improves our understanding of spatiotemporal hotspots and its variation for O.bartramii and is useful for sustainable exploitation,assessment,and management of this squid.展开更多
文摘The public health workforce is a key component of public health system.To articulate the scope of public health workforce,we reviewed the relevant World Health Organization(wHO)guidance and peer-reviewed journal articles on this subject.Specifically,we assessed and compared the relevant publications produced by WHO Headquarters and Regional Offices along with other literature on this issue.Our focus was on the“occupation,workplace setting,and employer of public health workforce”.It is noteworthy that WHO has adopted a conceptual framework with an inclusive scope of the public health workforce,while setting out a 5-year vision to strengthen capacity across all WHO Member States for a multidisciplinary workforce to deliver the essential public health functions,including emergency preparedness and response.The importance of public health workforce in global and national responses to the coronavirus disease 2019(COVID-19)pandemic is recognized.We also observed that there were diverse understandings of the scope of public health workforce worldwide,including macro-,meso-and micro-level perspectives.In the post-COVID-19 era,we suggest that policy-makers and practitioners at the national,regional and global level adopt a coordinated approach to expand and strengthen the national workforce as guided by the WHO towards the health-related targets of United Nations Sustainable Development Goals such as health security and Universal Health Coverage.
文摘Dictated handwriting samples are widely used in practice due to their simplicity,convenience,and practicality.However,dictation is typically listed as one of the many collection methods in textbooks and monographs,and there is usually no separate section focusing on dictated handwriting samples.Therefore,further study of dictated handwriting samples will have important practical significance.Consideration of the definition,existing problems,collection techniques,and critical aspects of dictated handwriting samples willsupport investigators and document examiners in their professional abilities and contribute to the theoretical system of document examination.In this article,an exploratory analysis will be conducted and ideas about dictated handwriting samples will be shared,including the definition of dictated samples,their relationship to experimental samples,practical problems,feasible collection methods,and some critical points that require special attention.Dictation is widely used but problematic because of a lack of quantity and low levels of comparability.Those difficulties are mainly caused by a lack of theoreticalstudy and understanding of the requirements and collection techniques of dictated handwriting samples among first‑line investigators.Dictated samples should be collected based on subjective and objective conditions of formation with aims to improve comparability and five similarities.Further studies are needed to improve the theoretical system and practical use of dictated samples so that they can contribute to successfully reaching conclusions in investigations.
基金supported by the National Health and Family Planning Commission of the People’s Republic of China(201302002Clinical Trials.gov number NCT 02200679)+1 种基金the Shanghai International Cooperation Ministry of Science Projects(14430712200)the Development Project of Shanghai Peak Discipline-Integrated Chinese and Western Medicine
文摘The purpose of this study was to explore the psychometric properties of the Chinese version of the autism spectrum rating scale（ASRS）. We recruited 1,625community-based children and 211 autism spectrum disorder（ASD） cases from 4 sites, and the parents of all participants completed the Chinese version of the ASRS. A robust weighted least squares means and variance adjusted estimator was used for exploratory factor analysis. The3-factor structure included 59 items suitable for the current sample. The item reliability for the modi？ed Chinese version of the ASRS（MC-ASRS） was excellent. Moreover,with 60 as the cut-off point, receiver operating characteristic analysis showed that the MC-ASRS had excellent discriminate validity, comparable to that of the unmodi？ed Chinese version（UC-ASRS）, with area under the curve values of 0.952（95% CI： 0.936–0.967） and 0.948（95% CI：0.930–0.965）, respectively. Meanwhile, the con？rm factor analysis revealed that MC-ASRS had a better construct validity than UC-ASRS based on the above factor solution in another children sample. In conclusion, the MC-ASRS shows better ef？cacy in epidemiological screening for ASD in Chinese children.
文摘A factor analysis was applied to soil geochemical data to define anomalies related to buried Pb-Zn mineralization.A favorable main factor with a strong association of the elements Zn,Cu and Pb,related to mineralization,was selected for interpretation.The median+2 MAD(median absolute deviation)method of exploratory data analysis(EDA)and C-A(concentration-area)fractal modeling were then applied to the Mahalanobis distance,as defined by Zn,Cu and Pb from the factor analysis to set the thresholds for defining multi-element anomalies.As a result,the median+2 MAD method more successfully identified the Pb-Zn mineralization than the C-A fractal model.The soil anomaly identified by the median+2 MAD method on the Mahalanobis distances defined by three principal elements(Zn,Cu and Pb)rather than thirteen elements(Co,Zn,Cu,V,Mo,Ni,Cr,Mn,Pb,Ba,Sr,Zr and Ti)was the more favorable reflection of the ore body.The identified soil geochemical anomalies were compared with the in situ economic Pb-Zn ore bodies for validation.The results showed that the median+2 MAD approach is capable of mapping both strong and weak geochemical anomalies related to buried Pb-Zn mineralization,which is therefore useful at the reconnaissance drilling stage.
文摘Exploratory data analysis plays a major role in obtaining insights from data.Over the last two decades,researchers have proposed several visual data exploration tools that can assist with each step of the analysis process.Nevertheless,in recent years,data analysis requirements have changed significantly.With constantly increasing size and types of data to be analyzed,scalability and analysis duration are now among the primary concerns of researchers.Moreover,in order to minimize the analysis cost,businesses are in need of data analysis tools that can be used with limited analytical knowledge.To address these challenges,traditional data exploration tools have evolved within the last few years.In this paper,with an in-depth analysis of an industrial tabular dataset,we identify a set of additional exploratory requirements for large datasets.Later,we present a comprehensive survey of the recent advancements in the emerging field of exploratory data analysis.We investigate 50 academic and non-academic visual data exploration tools with respect to their utility in the six fundamental steps of the exploratory data analysis process.We also examine the extent to which these modern data exploration tools fulfill the additional requirements for analyzing large datasets.Finally,we identify and present a set of research opportunities in the field of visual exploratory data analysis.
基金the Exploratory Research Grant Scheme(ERGS)of Universiti Teknologi MARA(UiTM)Malaysia(No.ERGS/1/2013/SSl11/UITM/01/01)High-Level Talents Introduction Funding of Haixi Research Institute,the Chinese Academy of Sciences(No.19Q3671boa).
文摘Over the past years,there has been an expanding intrigued in building refurbishment projects because of the alter in financial conditions and the accentuation on sustainable development.Increasing demand for building refurbishment projects will lead to an increase in organizational interactions in the construction works as building refurbishment works involve interactions among many different organizations and it can cause Inter-Organizational conflict(IOC)among organizations involved in projects.This paper adopted an Exploratory Factor Analysis(EFA)approach to analyses IOC in building refurbishment projects.For this study,a fivepoint Likert Scale was adopted to ensure the instruments of the study are reliable.The researcher ultimately sent questionnaires as a web-link and email invitation to 1050 construction firms and 733 architectural firms.The questionnaire sent to managers and professionals from construction and architectural firms in Malaysia.Finally,one-hundred-seventy-nine(179)refurbishment projects formed a database for this paper.The finding of this paper shows the IOC factors that contribute to the improve the performance of building refurbishment project can be conflict during the construction stage,conflict between the client and the consultant,task expectations,basic responsibilities,final duration,project’s goals,conflict between the client and the contractor,final cost,final quality,standards of behaviors,conflict between the contractor and the consultant,interference and conflict during the design stage.
基金supported by the National Social Science Foundation of China(Grant No.20&ZD074)the National Natural Science Foundation of China(Grant No.72204037)+2 种基金Dalian High-Level Talent Innovation Program(Youth Science and Technology Star)(Project No.2022RQ055)the China Postdoctoral Science Foundation(Grant No.2024M750330)Humanities and Social Science Fundation of Ministry of Eduction,China(Project No.22YJC870009).
文摘Being the major players in promoting innovation,enterprises are therefore central to innovation–based development.Establishing how vibrant they are in terms of innovation has become a heavily debated issue in both academic and industry circles.Through a sample involving Chinese listed companies in advanced material manufacturing,this study utilizes exploratory factor analysis to develop an evaluation system of enterprises’innovation vitality on the basis of three dimensions:innovation persistence,volatility,and growth.The study establishes deeper interaction between innovation vitality and two major indicators-persistence and volatility formats input and cooperation,while also promoting the growth of innovative input and output.This study adds insights related to the objective assessment of enterprises’innovation vitality and the promotion of subsequent innovation efforts.
基金Supported by Wu Jieping Medical Foundation,No.320.6750.2024-16-28.
文摘BACKGROUND Esophageal cancer(EC),primarily esophageal squamous cell carcinoma in China,has a poor prognosis with a 5-year survival rate of approximately 25%after surgery alone.Neoadjuvant chemoradiotherapy combined with surgery is the standard treatment for locally advanced EC,with a 47%5-year survival rate,although adverse events are common.Immunotherapy,particularly PD-1 inhibitors,has shown promise in treating advanced EC,and neoadjuvant chemotherapy with immunotherapy is effective.However,the efficacy of postoperative immunotherapy remains unclear,with studies like Checkmate577 showing promising results but limited applicability to surgery-only patients,highlighting the need for further research.AIM To evaluate the efficacy,prognostic factors,and safety of adjuvant immunotherapy with anti-PD-1 inhibitors following radical surgery for EC.METHODS A retrospective analysis was conducted on EC patients who received adjuvant immunotherapy after radical treatment at the 900th Hospital of the China Joint Logistics Force between January 2018 and October 2024.Demographic,treatment and laboratory data were collected.Progression-free survival(PFS)was assessed using the Kaplan-Meier method,and independent prognostic factors were identified using Cox regression.Optimal cutoff values for continuous variables,including body mass index(BMI)difference and neutrophil-to-lymphocyte ratio(NLR),were determined using the maxstat package in R.RESULTS A total of 44 patients were included,with a 2-year PFS rate of 68.6%[95%confidence interval(CI):53%-88.7%].Univariate analysis identified several factors significantly associated with prognosis,including the interval between surgery and immunotherapy,BMI difference between before surgery and first immunotherapy,presurgical lymphocyte count,and presurgical NLR.Multivariable Cox regression revealed that a BMI difference<3.86 was an independent protective factor for PFS(hazard ratio:0.42,95%CI:0.21-0.85,P<0.05).At the last followup,the median PFS for patients with BMI<3.86 had not been reached,compared to 8.83 months for those with BMI>3.86.The 1-year PFS for patients receiving postoperative chemotherapy combined with immunotherapy was 88.5%,suggesting superior efficacy over chemotherapy alone.CONCLUSION Adjuvant immunotherapy for EC shows good efficacy and safety.A BMI difference<3.86 is a protective factor for PFS,highlighting the importance of monitoring nutrition and inflammation for personalized treatment.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(No.RS-2023-00218176)the Soonchunhyang University Research Fund.
文摘Improving early diagnosis of autism spectrum disorder(ASD)in children increasingly relies on predictive models that are reliable and accessible to non-experts.This study aims to develop such models using Python-based tools to improve ASD diagnosis in clinical settings.We performed exploratory data analysis to ensure data quality and identify key patterns in pediatric ASD data.We selected the categorical boosting(CatBoost)algorithm to effectively handle the large number of categorical variables.We used the PyCaret automated machine learning(AutoML)tool to make the models user-friendly for clinicians without extensive machine learning expertise.In addition,we applied Shapley additive explanations(SHAP),an explainable artificial intelligence(XAI)technique,to improve the interpretability of the models.Models developed using CatBoost and other AI algorithms showed high accuracy in diagnosing ASD in children.SHAP provided clear insights into the influence of each variable on diagnostic outcomes,making model decisions transparent and understandable to healthcare professionals.By integrating robust machine learning methods with user-friendly tools such as PyCaret and leveraging XAI techniques such as SHAP,this study contributes to the development of reliable,interpretable,and accessible diagnostic tools for ASD.These advances hold great promise for supporting informed decision-making in clinical settings,ultimately improving early identification and intervention strategies for ASD in the pediatric population.However,the study is limited by the dataset’s demographic imbalance and the lack of external clinical validation,which should be addressed in future research.
基金funded by the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University,through the Research Funding Program,Grant No.(FRP-1443-15).
文摘The analysis of Android malware shows that this threat is constantly increasing and is a real threat to mobile devices since traditional approaches,such as signature-based detection,are no longer effective due to the continuously advancing level of sophistication.To resolve this problem,efficient and flexible malware detection tools are needed.This work examines the possibility of employing deep CNNs to detect Android malware by transforming network traffic into image data representations.Moreover,the dataset used in this study is the CIC-AndMal2017,which contains 20,000 instances of network traffic across five distinct malware categories:a.Trojan,b.Adware,c.Ransomware,d.Spyware,e.Worm.These network traffic features are then converted to image formats for deep learning,which is applied in a CNN framework,including the VGG16 pre-trained model.In addition,our approach yielded high performance,yielding an accuracy of 0.92,accuracy of 99.1%,precision of 98.2%,recall of 99.5%,and F1 score of 98.7%.Subsequent improvements to the classification model through changes within the VGG19 framework improved the classification rate to 99.25%.Through the results obtained,it is clear that CNNs are a very effective way to classify Android malware,providing greater accuracy than conventional techniques.The success of this approach also shows the applicability of deep learning in mobile security along with the direction for the future advancement of the real-time detection system and other deeper learning techniques to counter the increasing number of threats emerging in the future.
基金I would like to thank the National Natural Science Foundation of China(Grant No.42061041)for the funding.
文摘Urban resilience assesses a city’s ability to withstand unknown risks.Scholars are not comprehensive in assessing urban resilience,and they lack consideration of population resilience.This study investigated 110 prefecturelevel cities in the Yangtze River Economic Belt(YREB)as study areas.We calculated the YREB’s level of urban resilience based on the aspects of“economy-society-population-ecology-infrastructure”,which ensured that the comprehensive evaluation of urban resilience is complete and sufficient.The spatio-temporal evolution of urban resilience was analyzed using exploratory spatial data.Geodetectors were used to investigate the impact of several indicators,focusing on economic,social,population,ecological,and infrastructure factors,on urban resilience.The results showed that the urban resilience of the YREB has maintained a slow upward trend from 2005 to 2018,and the average urban resilience of the YREB has risen from 0.2442 to 0.2560.The resilience gap between cities in the study region increased initially and then decreased.The dominant factor in the spatial differentiation of urban resilience was the economic factors,followed by the population factors.Urban resilience has been clarified and an evaluation index system is constructed,which can provide an effective reference for the evaluation of urban resilience among countries around the world.Based on this,factors that optimize urban resilience are configured,and the regional and national sustainable development can be promoted.
文摘Self-regulated learning （SRL） is one of the precious ways in teachers＇ professional development, and its operation level includes different factors. With studies abroad and our preliminary investigation as base, this study developed a scale to test the factors SRL includes. According to the result of 905 teachers working in elementary school by exploratory factor analysis, the SRL for elementary teachers is consisted of its sociality （it included selecting leads and seeking for instructing）, its motivation（it included self-improvement and self-excelling）, its methods（it included strategy use and habitual behavior）, and its outcomes（it included extensive reading and teachers＇ professional development）. All the result indicated Teachers＇ SRL Scale had clear factor structure, good reliability and validity. It can be used to test the current operating situation of SRL for teachers working in elementary school.
基金supported by the Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences.
文摘The Yellow River Basin of China is a key region that contains myriad interactions between human activities and natural environment.Industrialization and urbanization promote social-economic development,but they also have generated a series of environmental and ecological issues in this basin.Previous researches have evaluated urban resilience at the national,regional,urban agglomeration,city,and prefecture levels,but not at the watershed level.To address this research gap and elevate the Yellow River Basin’s urban resilience level,we constructed an urban resilience evaluation index system from five dimensions:industrial resilience,social resilience,environmental resilience,technological resilience,and organizational resilience.The entropy weight method was used to comprehensively evaluate urban resilience in the Yellow River Basin.The exploratory spatial data analysis method was employed to study the spatiotemporal differences in urban resilience in the Yellow River Basin in 2010,2015,and 2020.Furthermore,the grey correlation analysis method was utilized to explore the influencing factors of these differences.The results of this study are as follows:(1)the overall level of urban resilience in the Yellow River Basin was relatively low but showed an increasing trend during 2010–2015,and significant spatial distribution differences were observed,with a higher resilience level in the eastern region and a low-medium resilience level in the western region;(2)the differences in urban resilience were noticeable,with industrial resilience and social resilience being relatively highly developed,whereas organizational resilience and environmental resilience were relatively weak;and(3)the correlation ranking of resilience influencing factors was as follows:science and technology level>administrative power>openness>market forces.This research can provide a basis for improving the resilience level of cities in the Yellow River Basin and contribute to the high-quality development of the region.
基金supported by Grants from the Department of Education(R305D140037,R305D210023).
文摘Factor analysis is widely utilized to identify latent factors underlying the observed variables.This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis,the K1 rule,and parallel analysis,along with a more recently developed method,the bass-ackward method.We provide an in-depth exploration of these techniques,discussing their historical development,advantages,and limitations.Using a series of Monte Carlo simulations,we assess the efficacy of these methods in accurately determining the appropriate number of factors.Specifically,we examine two cessation criteria within the bass-ackward framework:BA-maxLoading and BA-cutoff.Our findings offer nuanced insights into the performance of these methods under various conditions,illuminating their respective advantages and potential pitfalls.To enhance accessibility,we create an online visualization tool tailored to the factor structures generated by the bass-ackward method.This research enriches the understanding of factor analysis methodology,assists researchers in method selection,and facilitates comprehensive interpretation of latent factor structures.
文摘AIM To understand the experience of maternal depression,the factors implicated in accessing health,and the acceptability of the psychosocial intervention.METHODS The participants were recruited from the paediatrics outpatient department of Civil Hospital Karachi,Pakistan.The study started in December 2009 and completed in December 2010.Women with maternal depression,aged 18-44 years with children aged 0-30 mo who had received nutritional supplements,and participated in the intervention programme[called Learning through Play(LTP)plus]were included in the study.Qualitative interviews were conducted with 8 participants before the intervention and 7 participants after the intervention.A semi structured topic guide was used to conduct the interviews.RESULTS Framework analysis procedures were used to analyse the qualitative data.Four themes emerged:(1)the women's contextual environment:Interpersonal conflicts,lack of social support and financial issues being the major barriers in assessing healthcare;(2)women's isolation and powerlessness within the environment:Sense of loneliness was identified as a restricting factor to access healthcare;(3)the impact of the intervention(LTP-Plus):Women felt"listened to"and seemed empowered;and(4)empowered transformed women within the same contextual environment:The facilitator provided a"gardening role"in nurturing the women resulting in a positive transformation within the same environment.The women's homes seemed to be more happy homes and there was a positive change in their behaviour towards their children.CONCLUSION Findings informed the further development and testing of culturally-appropriate psychosocial intervention(LTP^+)for addressing maternal depression.
基金National Natural Science Foundation of China Youth Science Foundation ProjectNo.41701170+1 种基金National Natural Science Foundation of China,No.41661025,No.42071216Fundamental Research Funds for the Central Universities,No.18LZUJBWZY068。
文摘In 2007,China surpassed the USA to become the largest carbon emitter in the world.China has promised a 60%–65%reduction in carbon emissions per unit GDP by 2030,compared to the baseline of 2005.Therefore,it is important to obtain accurate dynamic information on the spatial and temporal patterns of carbon emissions and carbon footprints to support formulating effective national carbon emission reduction policies.This study attempts to build a carbon emission panel data model that simulates carbon emissions in China from 2000–2013 using nighttime lighting data and carbon emission statistics data.By applying the Exploratory Spatial-Temporal Data Analysis(ESTDA)framework,this study conducted an analysis on the spatial patterns and dynamic spatial-temporal interactions of carbon footprints from 2001–2013.The improved Tapio decoupling model was adopted to investigate the levels of coupling or decoupling between the carbon emission load and economic growth in 336 prefecture-level units.The results show that,firstly,high accuracy was achieved by the model in simulating carbon emissions.Secondly,the total carbon footprints and carbon deficits across China increased with average annual growth rates of 4.82%and 5.72%,respectively.The overall carbon footprints and carbon deficits were larger in the North than that in the South.There were extremely significant spatial autocorrelation features in the carbon footprints of prefecture-level units.Thirdly,the relative lengths of the Local Indicators of Spatial Association(LISA)time paths were longer in the North than that in the South,and they increased from the coastal to the central and western regions.Lastly,the overall decoupling index was mainly a weak decoupling type,but the number of cities with this weak decoupling continued to decrease.The unsustainable development trend of China’s economic growth and carbon emission load will continue for some time.
基金Under the auspices of Key Research Program of Chinese Academy of Sciences(No.KZZD-EW-06-03KSZD-EW-Z-021-03)National Key Science and Technology Support Program of China(No.2008BAH31B06)
文摘Rural development inequality is an important practical issue during the course of full establishment of a ′moderately well-off society′ in modern China,and the objective understanding and evaluation of the status and regional inequality of rural development can provide scientific basis for ′building a new countryside′ and coordination development of rural-urban regions.Based on the county-level data of 2000,2005 and 2009,this paper examines the rural development inequality of Jilin Province in Northeast China by establishing a rural development index.The spatio-temporal dynamic patterns and domain factors are discussed by using the method of exploratory spatial data analysis and multi-regression model.The results are shown as follows.Firstly,most of the counties were in lower development level,which accounted for 58.3%,62.5% and 66.7% of the total counties in 2000,2005 and 2009,respectively.The characteristics of spatial inequality were very obvious at county level.For example,rural development level of Changchun Proper and the proper of seven prefecture-level cities were much higher than that of the surrounding regions.The counties in the eastern and northern Jilin Province were the lowest regions of rural development level,while the middle counties were the rapid growth areas in rural economy.Secondly,Moran′s I of rural development index(RDI) was 0.01,–0.16 and –0.06 in 2000,2005 and 2009,respectively,which indicated that spatial agglomeration of RDI was not obvious in Jilin Province,and took on the characteristic of random distribution.The counties of both the units and its adjacent units have higher development level(HH) were transferred from the western areas to the eastern areas,while the countries of both the units and its adjacent units have lower development level(LL) were diffused from the eastern to middle and western Jilin Province.Finally,the result of multi-regression analysis showed that the improvement of agricultural production condition,development of agricultural economics and the adjustment of industrial structure were the domain factors affecting rural development inequality of Jilin Province in the later ten years.
基金Under the auspices of National Natural Science Foundation of China(No.41071116)Humanity and Social ScienceFoundation of Ministry of Education(No.09YJC790225,11YJA630008)
文摘This paper principally focuses on the morphological differences,spatial pattern and regional types of rural settlements in Xuzhou City of Jiangsu Province in China.Using satellite images of Xuzhou City taken in 2007 and 2008 and models of exploratory spatial data analysis(ESDA) and spatial metrics,the paper conducts a quantitative analysis of the morphological pattern of rural settlements,and finds significant characteristics.First,rural settlements in Xuzhou City are significantly agglomerated in terms of their spatial distribution;meanwhile,there is significant variation in the geographical density distribution.Second,the scale of rural settlements in Xuzhou City is larger than the average in Jiangsu Province,and the histogram of the scale data is more even and more like a gamma distribution.There are a significant high-value cluster in the scale distribution,and local negative correlation between the scale and density distribution of rural settlements in Xuzhou City.Third,the morphology of rural settlements in Xuzhou City shows relative regularity with good connection and integrity,but the spatial variation of the morphology is anisotropic.Finally,according to the characteristics of density,scale,and form of rural settlements,the rural settlements of Xuzhou City are divided into three types:A high-density and point-scattered type,a low-density and cluster-like type and a mass-like and sparse type.The research findings could be used as the scientific foundation for rural planning and community rebuilding,particularly in less-developed areas.
基金Supported by the National Natural Science Foundation of China(Nos.41406146,41476129)the Natural Science Foundation of Shanghai Municipality(No.13ZR1419300)+1 种基金the Research Fund for the Doctoral Program of Higher Education of China(No.20123104120002)the Shanghai Universities First-Class Disciplines Project-Fisheries(A)
文摘With the increasing effects of global climate change and fishing activities,the spatial distribution of the neon flying squid(Ommastrephes bartramii) is changing in the traditional fishing ground of 150°-160°E and 38°-45°N in the northwest Pacific Ocean.This research aims to identify the spatial hot and cold spots(i.e.spatial clusters) of O.bartramii to reveal its spatial structure using commercial fishery data from2007 to 2010 collected by Chinese mainland squid-j igging fleets.A relatively strongly-clustered distribution for O.bartramii was observed using an exploratory spatial data analysis(ESDA) method.The results show two hot spots and one cold spot in 2007 while only one hot and one cold spots were identified each year from2008 to 2010.The hot and cold spots in 2007 occupied 8.2%and 5.6%of the study area,respectively;these percentages for hot and cold spot areas were 5.8%and 3.1%in 2008,10.2%and 2.9%in 2009,and 16.4%and 11.9%in 2010,respectively.Nearly half(>45%) of the squid from 2007 to 2009 reported by Chinese fleets were caught in hot spot areas while this percentage reached its peak at 68.8%in 2010,indicating that the hot spot areas are central fishing grounds.A further change analysis shows the area centered at156°E/43.5°N was persistent as a hot spot over the whole period from 2007 to 2010.Furthermore,the hot spots were mainly identified in areas with sea surface temperature(SST) in the range of 15-20℃ around warm Kuroshio Currents as well as with the chlorophyll-a(chl-a) concentration above 0.3 mg/m^3.The outcome of this research improves our understanding of spatiotemporal hotspots and its variation for O.bartramii and is useful for sustainable exploitation,assessment,and management of this squid.
