Spatial Social Network Analysis: Program Pengembangan Usaha Agribisnis Perdesaan (PUAP) or an Exertion Development Program in Supporting the Region Revitalization Development

As the exertion development (PUAP) develop in Rejang Lebong Regency in Bengkulu province which had been started since 2008 by giving a kind of fund aid called Bantuan Langsung Masyarakat (BLM PUAP), to Gapoktan (Gabungan Kelompok Tani) or an organization of farmers such by giving some money as the capital used for 1) food plant cultiva-tion, horticulture, animal husbandry, plantation, and2) non-cultivation exertion such as;home industry of agriculture, small marketing scale and another agriculture exertion. By the approach which had been done is hoped to get the important result, on the other way the role of analysis factor (Social Network Analysis) from all undertaking stakeholders programs PUAP to be relevance steps aimed to understand the relation or connectivity from all factors in the network and also the role of factor inside the network itself be the relevance steps in arranging the strategy and work intention from the realization stage of PUAP program for the continuity of the realization program in the future (finding the good strategy) which aimed to develop the program of PUAP in Rejang Lebong Regency in Bengkulu Province, and to be a reference from doing the program as a national program in Indonesia.

Single-cell network analysis reveals gene expression programs for Arabidopsis root development and metabolism

Single-cell RNA-sequencing datasets of Arabidopsis roots have been generated,but related comprehensive gene co-expression network analyses are lacking.We conducted a single-cell gene co-expression network analysis with publicly available scRNA-seq datasets of Arabidopsis roots using a SingleCellGGM algorithm.The analysis identified 149 gene co-expression modules,which we considered to be gene expression programs(GEPs).By examining their spatiotemporal expression,we identified GEPs specifically expressed in major root cell types along their developmental trajectories.These GEPs define gene programs regulating root cell development at different stages and are enriched with relevant developmental regulators.As examples,a GEP specific for the quiescent center(QC)contains 20 genes regulating QC and stem cell niche homeostasis,and four GEPs are expressed in sieve elements(SEs)from early to late developmental stages,with the early-stage GEP containing 17 known SE developmental regulators.We also identified GEPs for metabolic pathways with cell-type-specific expression,suggesting the existence of cell-type-specific metabolism in roots.Using the GEPs,we discovered and verified a columellaspecific gene,NRL27,as a regulator of the auxin-related root gravitropism response.Our analysis thus systematically reveals GEPs that regulate Arabidopsis root development and metabolism and provides ample resources for root biology studies.

Citation and bibliographic coupling between authors in the field of social network analysis

Purpose:We analyzed the structure of a community of authors working in the field of social network analysis(SNA)based on citation indicators:direct citation and bibliographic coupling metrics.We observed patterns at the micro,meso,and macro levels of analysis.Design/methodology/approach:We used bibliometric network analysis,including the“temporal quantities”approach proposed to study temporal networks.Using a two-mode network linking publications with authors and a one-mode network of citations between the works,we constructed and analyzed the networks of citation and bibliographic coupling among authors.We used an iterated saturation data collection approach.Findings:At the macro-level,we observed the global structural features of citations between authors,showing that 80%of authors have not more than 15 citations from other works.At the meso-level,we extracted the groups of authors citing each other and similar to each other according to their citation patterns.We have seen a division of authors in SNA into groups of social scientists and physicists,as well as into other groups of authors from different disciplines.We found some examples of brokerage between different groups that maintained the common identity of the field.At the micro-level,we extracted authors with extremely high values of received citations,who can be considered as the most prominent authors in the field.We examined the temporal properties of the most popular authors.Research limitations:The main challenge in this approach is the resolution of the author’s name(synonyms and homonyms).We faced the author disambiguation,or“multiple personalities”(Harzing,2015)problem.To remain consistent and comparable with our previously published articles,we used the same SNA data collected up to 2018.The analysis and conclusions on the activity,productivity,and visibility of the authors are relative only to the field of SNA.Practical implications:The proposed approach can be utilized for similar objectives and identifying key structures and characteristics in other disciplines.This may potentially inspire the application of network approaches in other research areas,creating more authors collaborating in the field of SNA.Originality/value:We identified and applied an innovative approach and methods to study the structure of scientific communities,which allowed us to get the findings going beyond those obtained with other methods.We used a new approach to temporal network analysis,which is an important addition to the analysis as it provides detailed information on different measures for the authors and pairs of authors over time.

Structural characteristics and influencing factors of spatial correlation network for regional high-quality development in China

On the basis of measuring the regional high-quality development in China from 2011 to 2020,this study uses gravity model to build spatial correlation network,and uses social network analysis method to analyze the structural characteristics and influencing factors of correlation network.The results are shown as follows.First,from 2011 to 2020,the level of regional high-quality development in China is rising gradually,and the discrete characteristics between regions are gradually obvious,showing a step-like distribution structure decreasing from east to west.Second,the network density of regional high-quality development is generally low and tends to decline,but it has strong stability and correlation strength.Third,the spatial correlation network has an obvious core-edge structure.Shanghai is always at the center of the network and plays a significant intermediary role,while Qinghai and Xinjiang are always at the edge of the network.Fourth,the regional high-quality development association network can be divided into four major sectors:main benefit,net benefit,net spillover,and broker,showing the spatial correlation characteristics of inter-plate contact and intra-plate agglomeration.Fifth,the level of economic development,the level of urbanization and geographical proximity have a significant impact on the formation of regional high-quality development correlation network.

Impact of Low-Impact Development Technologies from an Ecological Perspective in Different Residential Zones of the City of Atlanta, Georgia

Low-impact development （LID） technologies have a great potential to reduce water usage and stormwa- ter runoff and are therefore seen as sustainable improvements that can be made to traditional water infrastructure, These technologies include bioretention areas, rainwater capturing, and xeriscaping, all of which can be used in residential zones, Within the City of Atlanta, residential water usage accounts for 53% of the total water consumption; therefore, residential zones offer significant impact potential for the implementation of LID, This study analyzes the use of LID strategies within the different residen- tial zones of the City of Atlanta from an ecological perspective by drawing analogies to natural ecosys- tems, The analysis shows that these technologies, especially with the addition of a graywater system, work to improve the conventional residential water network based upon these ecological metrics, The higher metric values suggest greater parity with healthy, natural ecosystems.

Prioritizing sustainable development goals and linking them to ecosystem services:A global expert’s knowledge evaluation

The implementation of strategies to achieve the Sustainable Development Goals(SDGs)is frequently hindered by potential trade-offs between priorities for either environmental protection or human well-being.However,ecosystem services(ES)-based solutions can offer possible co-benefits for SDGs implementation that are often overlooked or underexploited.In this study,we cover this gap and investigate how experts from different countries value the SDGs and relate them with ES.A total of 66 countries participated to the survey,and answers were grouped into three macro-regions:Asia;Europe,North America,and Oceania(ENO);Latin America,Caribbean and Africa(LA).Results show that the most prioritized SDGs in the three macro-regions are usually those related to essential material needs and environmental conditions,such as SDG2(Zero Hunger),SDG1(No Poverty),and SDG6(Clean Water).At a global scale,the number of prioritized synergies between SDGs and ES largely exceeded trade-offs.The highest amount of synergies was observed for SDG1(No Poverty),mainly with SDG2,SDG3(Good Health),SDG5(Gender Equality),and SDG8(Economic Growth).Other major synergies among SDGs include SDG14-15(Life below water-Life on land),SDG5-10(Gender Equity-Reduced Inequality),and SDG1-2(No poverty-Zero Hunger).At a global scale,SDG15,SDG13,SDG14,and SDG6 were closely related to ES like climate regulation,freshwater,food,water purification,biodiversity,and education.SDG11(Sustainable Cities)and SDG3 were also relevant in Asia and in LA,respectively.Overall,this study shows the potential to couple future policies that can implement SDGs’strategies while adopting ES-based solutions in different regions of the world.

Examining the Impacts of Key Influencers on Community Development

In this research,we aim to identify and investigate the impacts of key influencers on community formations and developments.We assess the impacts of key influencers by analyzing the activities and structure of the social media presence of a local community.Results of our analysis show that key influencers play important roles in connecting the community,transferring information,and improving overall sentiment of the community members.Our findings suggest that community practitioners can apply social network analysis to identify value-added influencers and discover strategies for improving the community and keeping leadership roles.

A systems perspective on national prioritisation of sustainable development goals:Insights from Australia

Achieving the Sustainable Development Goals(SDGs)requires effective national initiatives and resource allo-cation.Yet,the simultaneous attainment of all goals is hindered by constraints such as limited budgets and resources,varied national priorities,and the intricate nature of the goals.As we approach 2030 and beyond,an urgent need for an effective,data-driven prioritisation system exists to optimise what can be accomplished.A considerable knowledge gap persists in identifying the priority areas that demand concentrated attention and how their improvement would propel overall sustainability goals.To bridge this gap,our study presents a priori-tisation approach that identifies significant SDG indicators based on urgency and impact,utilising Benchmarking,Bivariate,and Network analysis.Furthermore,we introduce an innovative Impact Index(IMIN)to assess an indi-cator’s extensive effect on the SDG network.This system carries significant international relevance by establishing a robust framework to identify key,potent,and interconnected indicators.It supports decision-makers worldwide in comprehending their nation’s SDG performance and promotes efficient resource allocation.In the specific con-text of Australia,our analysis spotlights several impactful,yet underperforming SDG indicators.These include the protection of Freshwater,Terrestrial,and Mountain Key Biodiversity Areas(KBAs),the share of renewable energy and energy intensity level of primary energy,targeted research and development,gender equality in national parliaments,and carbon-efficient manufacturing,amongst others.

Network Management of Food Additives Quality Analysis and Inspection

In this paper, on the basis of the implementation of the national chemical industry standard analytical test methods and analysis of test items, a food additive quality analysis and inspection of network management applications are developed using the development technology of Visual Basic language and computer system operating environment, to achieve a network management software for users on food additives of quality analytical testing. The software sets up an information sharing network platform for enterprise and quality management departments, which is a major innovation in the food additive quality analysis on test management methods and tools.

The roles of computer-aided drug synthesis in drug development

With the improvements in computer computing ability,data accumulation and rapid algorithm development,the integration of artificial intelligence(AI)and drug synthesis has been accelerated,significantly improving the design and synthesis of drug molecules.Recently,data-driven computer-aided synthesis tools have been quickly and widely applied in retrosynthetic analysis,reaction prediction and automated synthesis,which can effectively accelerate the process of drug discovery and development and improve the quality of designed and synthesized drug molecules.Here,we review the development and applications of computer-aided synthesis technology and introduce recent advances in computer-aided drug development from three aspects:computer-aided drug design,computer-aided drug synthesis route design and computer-aided intelligent drug synthesis machines.Furthermore,the challenges and opportunities of computer-aided drug synthesis technology are discussed.

iNID： An Analytical Framework for Identifying Network Models for Interplays among Developmental Signaling in Arabidopsis

Integration of internal and external cues into developmental programs is indispensable for growth and development of plants, which involve complex interplays among signaling pathways activated by the internal and external factors （IEFs）. However, decoding these complex interplays is still challenging. Here, we present a web-based platform that identifies key regulators and Network models delineating Interplays among Developmental signaling （iNID） in Arabidopsis. iNID provides a comprehensive resource of （1） transcriptomes previously collected under the conditions treated with a broad spectrum of IEFs and （2） protein and genetic interactome data in Arabidopsis. In addition, iNID provides an array of tools for identifying key regulators and network models related to interplays among IEFs using transcriptome and interactome data. To demonstrate the utility of iNID, we investigated the interplays of （1） phytohormones and light and （2） phytohormones and biotic stresses. The results revealed 34 potential regulators of the interplays, some of which have not been reported in association with the interplays, and also network models that delineate the involvement of the 34 regulators in the interplays, providing novel insights into the interplays collectively defined by phytohormones, light, and biotic stresses. We then experimentally verified that BME3 and TEM1, among the selected regulators, are involved in the auxin-brassinosteroid （BR）-blue light interplay. Therefore, iNID serves as a useful tool to provide a basis for understanding interplays among IEFs.

Relationships and Evolving Networks of Rural Manufacturing Clusters: A Case Study in Yucheng County, Henan Province of China

The evolution of networks in rural industrial clusters,in particular in the context of China has been paid more attention to in the world.Applying the theory and techniques of social network analysis (SNA),this study is with particular regard to the business network relationships and their evolutionary dynamics of steel measuring tape manufacturing clustered in Nanzhuang Village,Yucheng County of Henan Province,China,which is important for better understanding the industrial and regional development in less developed rural areas.From data collected by comprehensive questionnaire survey in 2002 and mass interviews with 60 enterprises and assembling families and several government authorities in 2002,2003,2004,2005 and 2008,four types of networks are identified: spin-off,consulting,communication and cooperative.The characteristic of these networks is outlined in detail.Compared with the high-tech clusters of typical developed areas,the networks that have evolved in traditional manufacturing clusters are more affected by emotive linkages.The cluster networks are shown to exhibit a polycentric hierarchical structure.The family relationships are the dominate spin-off channels of enterprises,while the supply and demand relationships and the mobility of the skilled workers are also important paths of network learning,and the cooperation relationships are comparatively stable.Besides the root enterprises,the middle-sized enterprises are comparatively more active than small-sized enterprises,and the intermediary agencies and the service institutions act as bridges of the inter-enterprises cooperation.By analysis of the structure of networks and the interactions between the networks,the four stages of network evolution are also identified.The four stages are dominated by the family networks,the internal division production networks,the local innovation networks and the global supply networks respectively,and they play different roles in cluster development.

中国数字经济空间动态演进的区域现状

数字经济已成为引领我国经济一体化高质量发展的主要驱动力,立足于国家整体经济及区域经济稳步协调发展的战略。文章基于中国2013—2020年省级数据,运用主成分分析法对中国数字经济进行测度,并运用社会网络分析及核密度等方法对我国数字经济动态演化的空间关联及区域差异进行研究。研究发现:(1)2013—2020年我国数字经济发展整体网络密度稳步提升但依旧处于低水平。(2)中国各省份数字经济发展两极分化,东部与西北、东北等边缘地区存在“数字经济鸿沟”,加之整体关联水平低,分化严重,发达地区对边缘地区的辐射效应较低,差距可能愈发扩大。(3)将其划分为四个板块,发现存在“弱关联”板块,板块间溢出关系及关联度差异悬殊,进一步研究各省份数字经济发展的“中间人”作用,发现各省份承担角色更是“极化”严重。研究结果可为我国持续深化数字经济建设,推动经济协调、稳定、高质量发展提供参考。

中国民营经济高质量发展空间关联网络结构特征及影响因素分析

了解民营经济高质量发展的空间关联网络结构状态及其影响因素,对促进民营经济实现高质量发展具有重要作用。以2014年至2021年我国31个省(自治区、直辖市)民营经济的省际面板数据为样本,基于修正后的引力模型测算民营经济高质量发展空间关联关系,在此基础上运用社会网络分析法(SNA)和二次指派程序(QAP)探究其空间关联网络结构整体、个体、块模特征及其影响因素。结果表明:我国民营经济高质量发展的空间关联网络结构特征相对稳定,并具有一定等级性;省际民营经济高质量发展的空间关联网络可以分为四个板块;城市距离对民营经济高质量发展的空间关联强度产生显著负向作用,科技投入水平差异、贸易经济水平差异和经济发展水平差异对其产生显著正向影响。研究结果可为推动民营经济高质量发展及引导省际民营经济形成高质量发展的关联网络结构提供参考。

武汉都市圈协同创新时空特征、影响因素及对策研究

将2014—2021年分为四个时间段,构建武汉都市圈协同创新网络及影响因素模型;基于社会网络分析方法,研究武汉都市圈协同创新网络时空特征;采用QAP回归分析,探讨创新主体、经济水平、技术邻近性、地理邻近性、研发机构对武汉都市圈协同创新的影响。研究表明:武汉都市圈城市间协同创新主要表现为以武汉为中心的星型结构,其协同创新网络可分为三个梯队;创新主体、经济水平、技术邻近、研发机构对武汉都市圈协同创新网络具有显著正向影响,地理邻近仅在早期表现出正向作用。

农村普惠金融发展的空间关联网络及驱动因素研究--兼论农村普惠金融高质量发展的推进路径

推动农村普惠金融高质量发展,为“中小微弱”提供有效的金融服务,创造良好环境促使农村金融高质量服务实体经济,是解决我国经济发展不平衡不充分问题的关键环节,更是实现包容性增长、促进社会和谐稳定的应有之义。通过构建农村普惠金融评价指标体系,并基于2008—2018年中国30个省(自治区、直辖市)的数据测算农村普惠金融指数,同时利用社会网络分析(SNA)、空间杜宾模型(SDM)分析农村普惠金融发展的空间关联网络特征及其驱动因素,研究发现:(1)农村普惠金融空间关联网络的关联关系数及网络密度均呈现先递增后下降的趋势,并于2011年达到峰值,整体关联网络通达性好,同时又存在“等级森严”的网络结构,所有网络特征指标均较为稳定。(2)上海、江苏、北京、浙江、山东、广东6个省份的度数中心度、接近中心度、中间中心度均最高,一直处于空间关联网络的核心区,掌控和支配能力更强,且对其他省份金融资源具有极强的虹吸作用,导致农村普惠金融的发展仍然处于集聚阶段。(3)经济发展水平、人口密度、政府干预程度、产业结构、银行业竞争是影响农村普惠金融发展的五个重要变量。从直接效应看,经济发展、高人口密度、银行业竞争均促进本地农村普惠金融的发展;从间接效应看,某地人口密集、第一产业占比过高、激烈的银行竞争均会抑制周边地区农村普惠金融的发展,而政府加大对某地的财政支出也可以对周边地区产生正向的溢出效应。

现代化产业体系区域协同发展及驱动因素研究

本文在构建现代化产业体系发展评价指标体系的基础上,使用熵权法测算中国30个省(区、市)2012—2021年现代化产业体系发展水平指数,借助修正的引力模型和社会网络分析法测算现代化产业体系区域协同发展水平,采用二次指派程序(QAP)考察现代化产业体系区域协同发展的驱动因素。研究发现,样本考察期内,东部及中部地区现代化产业体系发展水平较高,西部及东北地区发展水平较低;省份间空间关联较弱,区域协同发展程度较低;块模型分析表明,净溢出板块现代化产业体系发展协同性最好;总体而言,内部驱动因素中的产业绿色化、产业数字化、产业基础高级化以及外部驱动因素中的政府创新支持度、人口流动对现代化产业体系区域协同发展促进作用较强。

我国数字经济发展水平及区域网络结构

基于2013—2021全国30个省(区、市)的面板数据,利用CRITIC-熵权法测度省域数字经济发展水平,借助QAP分析法揭示各维度差异对数字经济发展水平差异的影响程度,并运用改进的修正引力模型,构建有向加权的省域数字经济关联网络,从整体、局部、个体3个维度量化其网络结构。研究发现,各省数字经济发展水平稳步提升,但不同省域间数字经济发展水平存在较大差异,北京、广东、上海数字经济发展水平遥遥领先;各省域数实融合平均水平变化最小,数字产业平均水平变化次之,数字基础设施和数字创新平均水平变化较大,数字基础设施差异和数字创新差异是数字经济发展水平差异的主要来源。从网络结构来看,各省份之间数字经济联系不够紧密,邻近省份更易形成凝聚子群,北京、上海、江苏、广东等省(市)占据网络中心位置,在数字经济关联网络中具有较强的影响力和吸引力。

自贸区制度创新网络联动的空间溢出效应——以长三角地区为例

以长三角的上海自贸区和浙江自贸区为例,采用2008—2019年包括其所在城市及周边47个地级市的面板数据,首先采用空间社会网络分析方法筛选处理组与控制组,然后分别构建政策综合视角下的异质性双重差分模型(Heterogeneous DID)和政策空间分割视角下的三重差分模型(DDD),深入考察评估“双自贸区之间的制度创新空间联动”对区域经济发展的溢出叠加效应。研究发现:不仅自贸区各自的制度创新对周边区域经济发展具有显著的异质性溢出效应,而且自贸区之间的“制度创新联动”更是对中间区域的经济发展具有时空两个维度上的序贯“溢出叠加效应”;而且,定量评估还表明,中间区域受到的这种“溢出叠加效应”要远大于单一自贸区对周边地区的单纯溢出效应。进一步的异质性分析更表明:自贸区对省会城市、内陆城市、地理临近城市和大型城市经济的溢出效应更加显著。

黄河流域绿色发展效率空间关联网络及影响因素研究

黄河流域是我国重要的生态屏障和经济地带,流域内各区域的绿色发展问题研究显得尤为重要。基于2006—2020年黄河流域60个城市的面板数据,采用非期望Super-SBM模型对该区域城市绿色发展效率进行测度,并通过修正的引力模型和社会网络分析方法深入探究绿色发展效率的关联网络结构特征及影响因素。结果表明:(1)黄河流域绿色发展效率总体处于波动上升状态,空间上呈现为上游地区>下游地区>中游地区的梯性差异;(2)黄河流域绿色发展效率关联网络在一定程度上突破了地理邻近效应,并表现出复杂的网络结构,但整体网络密度仍处于较低水平,具有较大的发展潜力;(3)黄河流域城市绿色发展效率关联网络包括净溢出、经纪人、双向溢出和净受益4个板块,关联路径以板块间为主;(4)城市间地理临近、经济发展水平、科技创新水平和产业结构差异等自然和社会经济因素对黄河流域绿色发展效率关联网络的形成具有显著影响。