SERVICE CENTRES IN RURAL DEVELOPMENT : A CASE STUDY OF JAUNPUR DISTRICT, UTTAR PRADESH

This paper attempts to deal with the identifying the service centers and calculation of the spatial arrangement with complementary area of service centres in Jaunpur district Jaunpur district of Uttar Pradesh. The study area is situated in Eastern Uttar Pradesh of the Middle Ganga Plain. The study is exclusively based on secondary data collected at block level from different offices. The centrality score has been calculated on the basis of three type of indices like functional centrality index, working population index and tertiary population index. There are 31 function or services selected judicially from five sectors (administrative, agricultural and financial, educational, health and transport and communication) to measure the centrality of service centre. The thissen polygon and berry breaking point method has been used for measure the complementary area. Total 88 service centres have been identified as first, second, third, fourth and fifth order service centre. The number of I, II, III, IV, and V order centres accounts for 43, 24, 16, 4, and 1 respectively.

Participatory Guarantee System and Social Capital for Sustainable Development in Brazil: The Case Study of OPAC Orgânicos Sul de Minas

In recent years there has been a growing international interest in alternative certification strategies for organic products. Specifically, participatory guarantee systems (PGS) have proved to be particularly suitable not only to simplify bureaucratic procedures for small organic producers and reduce the cost of certification, but also to generate empowerment, social inclusion and mutual support among farmers. The purpose of this paper is to study the elements of social capital (SC) found in a PGS through the use of social network indicators using the Organizaçao Participativa de Acreditaçao e Certificaçao “Orgânicos Sul de Minas” (OPAC-OSM) as a case study. The research was carried out in the southern part of Minas Gerais, one of the states of the Brazilian Federation, where organic production represents a viable alternative for small and medium-sized farmers. In particular, a survey was carried out to capture the opinions of managers (presidents or directors) about their participation in the OPAC-OSM, and about the level of interaction and degree of trust between members. Relational skills, which are the basis of structural SC, were analyzed both at the level of individual units and at the level of the general network of the OPAC-OSM. An in-degree centrality score assigned to OPAC-OSM members was obtained from each network. These scores have been correlated with variables of the database that were chosen due to their relevance in assessing the level of social capital. According to the results, the factors that most reinforced the proof of SC among the OPAC-OSM members were the level of information and the degree of trust and collaboration networks, with special emphasis on female participation. From the analysis carried out, it is possible to conclude that PGS are powerful tools in the strengthening of SC far beyond the aspect of quality assurance, which remains the main objective of the OPAC.

Bubble run-ups and sell-offs: a study of Indian stock market

PurposeThis paper tries to locate the sectorial bubbles and examines the possibility for investors making extra profit from these bubbles in the Indian stock market.Design/methodology/approachThe authors use two main indicators: (1) asset centrality and (2) relative value. Asset centrality signals crowded trading, which is associated with the formation of a bubble. Relative value separates the crowded trading during the bubble run-up from the sell-off. The authors observe whether these measures can detect the cycle of bubbles in each sector of the Indian stock market for the period 2004–2019.FindingsThe authors show the sectors going through the inflationary phase delivers much better performance than the index, whereas the sectors in their deflationary phase perform quite worse than the index. This provides attractive opportunities to investors, especially the institutional investors, and fund managers of the Indian market.Originality/valueTo the best of our knowledge, there is no study that looks into the idea of locating a sectoral bubble in the Indian financial stock market using the concept of centrality score and relative score. This work helps to locate a bubble and identify its phases successfully. Traders can enter a bubble in their inflationary period gain profit and exit the trade before the sell-off period begins.

Opinion Dynamics over a Finite Set in Cooperative Multi-robot Systems: An Asynchronous Gossip-Based Consensus Approach

The focus of this paper is to present an algorithm that allows robotic teams to make decisions between a finite set of choices. The approach used was based on models that represent the way groups of humans evolve their opinions through time. Numerous works have explored models that consider the opinion as continuous values, while the literature less frequently considers groups trying to reach an agreement when only a finite set of possible opinions is given. The main contribution of this paper is to present a consensus algorithm that can be applied in those scenarios. For this purpose, it is briefly reviewed some crucial concepts for the definition of the proposed algorithm, which is based on asynchronous gossip. Due to the stochasticity of this approach, it is not possible to precisely predict the behavior of the network. However, the results from both computational and laboratory experiments indicate the eigenvector centrality score as a valuable metric to predict the probability of an initial opinion to become the prevailing one for the group when they reach consensus. Also, the asynchrony of the proposed algorithm made it possible to reach consensus in scenarios where synchronous approaches could not.

Co-expression network analysis of protein phosphatase 2A (PP2A) genes with stress-responsive genes in Arabidopsis thaliana reveals 13 key regulators

Abiotic and biotic stresses adversely affect plant growth and development and eventually result in less yield and threaten food security worldwide. In plants, several studies have been carried out to understand molecular responses to abiotic and biotic stresses. However, the complete circuitry of stress-responsive genes that plants utilise in response to those environmental stresses are still unknown. The protein phosphatase 2A (PP2A) gene has been known to have a crucial role in abiotic and biotic stresses; but how it regulates the stress response in plants is still not known completely. In this study, we constructed gene co-expression networks of PP2A genes with stress-responsive gene datasets from cold, drought, heat, osmotic, genotoxic, salt, and wounding stresses to unveil their relationships with the PP2A under different conditions of stress. The graph analysis identified 13 hub genes and several influential genes based on closeness centrality score (CCS). Our findings also revealed the count of unique genes present in different settings of stresses and subunits. We also formed clusters of influential genes based on the stress, CCS, and co-expression value. Analysis of cis-regulatory elements (CREs), recurring in promoters of these genes was also performed. Our study has led to the identification of 16 conserved CREs.

Visualisasi Pemain Sepak Bola Indonesia pada DBPedia dengan menggunakan Node2Vec dan Closeness Centrality

Visualization of Indonesian Football Players on DBpedia through Node2Vec and Closeness Centrality Implementation. Through Semantic Web, data available on the internet are connected in a large graph. Those data are still raw so that they need to be processed to be an information that can help humans. This research aims to process and analyze the Indonesian soccer player graph by implementing node2vec and closeness centrality algorithm. The graph is modeled through a dataset obtained from the DBpedia by performing a SPARQL query on the SPARQL endpoint. The results of the Node2vec algorithm and closeness centrality are visualized for further analysis. Visualization of node2vec shows that the defenders are distributed over the players. Meanwhile, the result of closeness centrality shows that the strikers have the highest centrality score compared to other positions.Keywords: visualization, node2vec, closeness centralityAbstrak. Dengan adanya web semantik, data yang tersebar di internet dapat saling terhubung dan membentuk suatu graf. Data yang ada pada graf tersebut masih berupa data mentah sehingga perlu dilakukan pengolahan agar data mentah tersebut dapat menjadi informasi yang dapat membantu manusia. Penelitian ini bertujuan untuk melakukan pengolahan dan analisis terhadap graf pemain sepak bola Indonesia dengan mengimplementasikan algoritma node2vec dan closeness centrality. Graf dimodelkan melalui dataset yang didapat dari website DBpedia dengan cara melakukan query SPARQL pada SPARQL endpoint. Hasil dari algoritma node2vec dan closeness centrality divisualisasikan untuk dianalisis. Visualisasi dari node2vec menunjukkan pemain defender tersebar. Hasil closeness centrality menunjukkan bahwa pemain striker memiliki nilai tertinggi daripada posisi lainnya.Kata Kunci: visualisasi, node2vec, closeness centrality

Beyond Google’s PageRank: Complex Number-based Calculations for Node Ranking

This study is focused on a proposed alternative algorithm for Google's PageRank, named Hermitian centrality score, which employs complex numbers for scoring a node of the network to overcome the issues of PageRank’s link analysis. This study presents the Hermitian centrality score as a solution for the problems of PageRank, which are associated with the damping factor of Google’s algorithm. The algorithm for Hermitian centrality score is designed to be free from a damping factor, and it reproduces PageRank results well. Moreover, the proposed algorithm can mathematically and systematically change the point of a node of a network.

Network analysis of empathy items from the Interpersonal Reactivity Index in 1973 young adults

The aim of this work is to perform a network analysis on the French adaptation of the Interpersonal Reactivity Index (IRI) scale from a large Belgian database and provide additional information for the construct of empathy. We analyze a database of 1973 healthy young adults who were queried on the IRI scale. A regularized partial correlation network is estimated. In the visualization of the model, items are displayed as nodes, edges represent regularized partial correlations between the nodes. Centrality denotes a node's connectedness with other nodes in the network. The spinglass algorithm and the walktrap algorithm are used to identify communities of items, and state-of-the-art stability analyses are carried out. The spinglass algorithm identifies four communities, the walktrap algorithm five communities. Positive edges are found among nodes belonging to the same community as well as among nodes belonging to different communities. Item 14 ("Other people's misfortunes do not usually disturb me a great deal") shows the highest strength centrality score. The network edges and node centrality order are accurately estimated. Network analysis highlights interesting connections between indicators of empathy; how these results impact empathy models must be assessed in further studies.