Web map display service, in accordance with the WMS-OGC standard, which covers the topic of Public and State Utility Services (item 6, Annex III of the INSPIRE Directive: Us — State and public utility services). The topic Utility and Governmental Services covers a large number of types of geographic entities: different kinds of energy networks, various utilities and different types of facilities dedicated to environmental management. The specification aims to provide some simple data common to all of them, including: · the location of the entity. · administrative link of the service, that is, the organisation that has the mandate for its management. · basic technical characteristics, such as capacity or details about the type of service provided. The theme is structured into three sub-themes: 1- Service networks (utility networks) 2- Administrative and social governmental services 3- Environmental Management Facilites More information: http://blog-idee.blogspot.com/2012/09/los-servicios-de-utilidad-publica-y.html

Network analysis has found widespread utility in many research areas. However, assessing the statistical significance of observed relationships within networks remains a complex challenge. Traditional node permutation tests are often insufficient in capturing the effect of changing network topology by creating reliable null distributions. We propose two randomization alternatives to address this gap: random rewiring and controlled rewiring. These methods incorporate changes in the network topology through edge swaps. However, controlled rewiring allows for more nuanced alterations of the original network than random rewiring. In this sense, this paper introduces a novel evaluation tool, the Expanded Quadratic Assignment Procedure (EQAP), designed to calculate a specific p-value and interpret statistical tests with enhanced precision. The combination of EQAP and controlled rewiring provides a robust network comparison and statistical analysis framework. The methodology is exemplified through two real-world examples: the analysis of an organizational network structure, illustrated by the Enron-Email dataset, and a social network case, represented by the UK Faculty friendship network. The utility of these statistical tests is underscored by their capacity to safeguard researchers against Type I errors when exploring network metrics dependent on intricate topologies.

United Kingdom E Commerce: Social Networks: Utilities data was reported at 44.600 % in 2016. This records a decrease from the previous number of 50.000 % for 2015. United Kingdom E Commerce: Social Networks: Utilities data is updated yearly, averaging 39.400 % from Dec 2012 (Median) to 2016, with 5 observations. The data reached an all-time high of 50.000 % in 2015 and a record low of 26.300 % in 2012. United Kingdom E Commerce: Social Networks: Utilities data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.S040: E Commerce: Proportion of Businesses Using Social Media: By Industry.

The use of social network theory in evaluating animal social groups has gained traction in recent years. Despite the utility of social network analysis in describing attributes of social groups, it remains unclear how comparable this approach is to traditional behavioral observational studies. Using data on Gunnison’s prairie dog (Cynomys gunnisoni) social interactions we describe social networks from three populations. We then compare those social networks to groups identified by traditional behavioral approaches and explore whether individuals group together based on similarities. The social network social groups identified by social network analysis were consistent with those identified by more traditional behavioral approaches. However, fine-grained social sub-structuring was revealed only with social network analysis. We found variation in the patterns of interactions among prairie dog social groups that was largely independent of the behavioral attributes or genetics of the indivi...

Network analysis has typically examined the formation of whole networks while neglecting variation within or across networks. Actors within networks often adopt particular roles. While cross-sectional approaches for inferring latent roles exist, there is a paucity of approaches for considering roles in longitudinal networks. This paper explores the conceptual dynamics of temporally observed roles while deriving and introducing a novel statistical tool, the ego-TERGM, capable of uncovering these latent dynamics. Estimated through an Expectation-Maximization algorithm, the ego-TERGM is quick and accurate in classifying roles within a broader temporal network. An application to the Kapferer strike network illustrates the model's utility.

Since its first appearance in the late 1950s, the neoclassical economic theory of fertility, particularly as exemplified by Gary Becker’s model of household production function that assumes a unitary utility function of the household, has become one of the most popular paradigms with which to examine fertility changes. Recently, the bargaining model that assumes separate utility functions has emerged as a strong opponent to the original paradigm. This article provides network foundation to reconcile two competing economic paradigms. Our formal model predicts that the way in which separate utilities of couples are treated in their joint childbearing decisions depends on the network embeddedness of spouses (i.e. the intra-household network). If spouses are not embedded into each other’s networks, the assumption of the unitary utility function is no longer warranted, and their decision process follows the bargaining model. However, strongly embedded couples behave as if they share the common utility function, predicted by the Becker model. Our model prediction is supported by analysis of three waves of panel data, Korean Longitudinal Survey of Women and Families, collected in South Korea where a dramatic drop in the fertility rate is reported. We find that wife’s bargaining power, measured by the income difference between couples, can exert its influence on having a new-born child only when couples’ intra-household networks are weakly embedded, whereas strongly embedded couples consistently maintain high fertility rates regardless of how much wife earns. We conclude that social networks play a significant role in shaping how neoclassical economic models of fertility work and discuss its implication to the efforts enhancing the fertility rate.

The set contains the directory of the Department of municipal resources - postal and e-mail address, page address in the social network, data about the head, work schedule

Behavior can strongly influence rates and patterns of hybridization between animal populations and species. Yet, few studies have examined reproductive behaviors in natural hybrid zones within the fine-scale social structure in which they take place. We use radio-frequency identification (RFID) tags with social network analyses to test whether phenotypic similarity in plumage and mass correlate with social behavior throughout a breeding season in a California and Gambel's quail hybrid zone. We use a novel approach to partition phenotypic variation in a way that does not confound differences between sexes and species, and illustrate the complex ways that phenotype and behavior structure the social environment, mating opportunities, and male-male associations. Associations within the admixed population were random with respect to species-specific plumage, but showed strong patterns of assortment based upon sexually dimorphic plumage, monomorphic plumage, and mass. Weak behavioral reproductive isolation in this admixed population may be the result of complex patterns of phenotypic assortment based upon multiple traits, rather than a lack of phenotypic discrimination. More generally, our results inform the utility of social network analyses for analyzing behavioral factors affecting genetic exchange between populations and species.

1. Mating behavior and the timing of reproduction can inhibit genetic exchange between closely related species; however, these reproductive barriers are challenging to measure within natural populations. Social network analysis provides promising tools for studying the social context of hybridization, and the exchange of genetic variation, more generally.
2. We test how social networks within a hybrid population of California (Callipepla californica) and Gambel’s quail (Callipepla gambelii) change over discrete periods of a breeding season. We assess patterns of phenotypic and genotypic assortment, and ask whether altered associations between individuals (association rewiring), or changes to the composition of the population (individual turnover) drive network dynamics. We use genetic data to test whether social associations and relatedness between individuals correlate with patterns of parentage within the hybrid population.
3. To achieve these aims, we combine RFID association data, phenotypic data, and genomic measures with social network analyses. We adopt methods from the ecological network literature to quantify shifts in network structure and to partition changes into those due to individual turnover and association rewiring. We integrate genomic data into networks as node-level attributes (ancestry) and edges (relatedness, parentage) to test links between social and parentage networks.
4. We show that rewiring of associations between individuals that persist across network periods, rather than individual turnover, drives the majority of the changes in network structure throughout the breeding season, and that the traits involved in phenotypic/genotypic assortment were highly dynamic over time. Social networks were randomly assorted based upon genetic ancestry, suggesting weak behavioral reproductive isolation within this hybrid population. Finally, we show that the strength of associations within the social network, but not levels of genetic relatedness, predict patterns of parentage.
5. Social networks play an important role in population processes such as the transmission of disease and information, yet there has been less focus on how networks influence the exchange of genetic variation. By integrating analyses of social structure, phenotypic assortment, and reproductive outcomes within a hybrid zone, we demonstrate the utility of social networks for analyzing links between social context and gene flow within wild populations. 08-Jul-2020 Methods We extracted DNA from blood samples and museum tissues using Qiagen DNEasy Blood and Tissue kits (Qiagen, Hilden, Germany). Double-digest restriction associated sequencing (ddRAD-seq) library preparations and sequencing were performed by RTL Genomics (Lubbock, TX). Briefly, 500ng of each sample were digested using restriction enzymes Sbfl and Msp1, and placed in a thermal cycler set to 37°C for three hours and held at 4°C overnight. Samples underwent a 1.5x AMPure cleanup, were quantified using a Quibt 2.0 Fluorometer and DNA HS Assay Kit (Thermo Fisher Scientific, Waltham, MA), and normalized. Samples were ligated with adapters overnight at 4°C, followed by an additional 1.5x AMPure cleanup, and transferred to a PCR plate containing unique Illumina tag barcodes. Individual libraries were pooled, fragment analyzed, and fragment size selected (400-700bp) using BluePippin (Sage Science, Beverly, MA). Samples were sequenced on an Illumina HiSeq 2000 platform with paired-end, 125bp reads. Several samples sequenced at low coverage, and were re-sequenced with paired-end 125bp reads on a single NextSeq run. Reads were combined across runs and demultiplexed using BaseSpace software (Illumina, San Diego, CA).

Comparison between alternatives when changing the network topology.

Comparison of the capabilities between the existing statistical test and the expanded methods.

Behavioural differences among social groups can arise from differing ecological conditions, genetic predispositions and/or social learning. In the past, social learning has typically been inferred as responsible for the spread of behaviour by the exclusion of ecological and genetic factors. This 'method of exclusion' was used to infer that 'sponging', a foraging behaviour involving tool use in the bottlenose dolphin (Tursiops aduncus) population in Shark Bay, Western Australia, was socially transmitted. However, previous studies were limited in that they never fully accounted for alternative factors, and that social learning, ecology and genetics are not mutually exclusive in causing behavioural variation. Here, we quantified the importance of social learning on the diffusion of sponging, for the first time explicitly accounting for ecological and genetic factors, using a multi-network version of 'network-based diffusion analysis' (NBDA). Our results provide compelling support for previous findings that sponging is vertically socially transmitted from mother to (primarily female) offspring. This research illustrates the utility of social network analysis in elucidating the explanatory mechanisms behind the transmission of behaviour in wild animal populations.

Essays on actor models in exchange networks and social dilemmas. Measuring utility by means of the tradeoff method / relation between actors' utility and their behavior in prisoners' dilemma games / bargaining in exchange networks / micro-models of exchange. Social acting / networks / social dilemma's / prisoners' dilemma game.

We present a dynamic model of network formation where nodes find other nodes with whom to form links in two ways: some are found uniformly at random, while others are found by searching locally through the current structure of the network (e.g., meeting friends of friends). This combination of meeting processes results in a spectrum of features exhibited by large social networks, including the presence of more high- and low-degree nodes than when links are formed independently at random, having low distances between nodes in the network, and having high clustering of links on a local level. We fit the model to data from six networks and impute the relative ratio of random to network-based meetings in link formation, which turns out to vary dramatically across applications. We show that as the random/network-based meeting ratio varies, the resulting degree distributions can be ordered in the sense of stochastic dominance, which allows us to infer how the formation process affects average utility in the network. (JEL D85, Z13)

A list of available healthcare facilities in Alaska as provided by the Department of Health and Social Services Division of Public Health. The healthcare facilities in the list come from a Directory of Alaska Health Care Safety Net Providers who are providers delivering care to low-income and other vulnerable populations. Additionally, it includes providers who are required by law to see patients regardless of ability to pay.Source: Department of Health and Social Services, Division of Public Health. For more information and for questions about this data, see: Safety Net Directory.

Web3 Social Networking Market Outlook

According to our latest research, the Web3 Social Networking market size reached USD 1.98 billion in 2024, reflecting a robust surge in adoption and innovation across the globe. The market is projected to grow at a remarkable CAGR of 27.3% from 2025 to 2033, with the forecasted market size expected to reach USD 17.45 billion by 2033. This dynamic growth is being driven by increasing user demand for privacy, data ownership, and decentralized online experiences, as well as the rapid evolution of blockchain and tokenization technologies that underpin Web3 social networking platforms. As per the latest research, the sector is witnessing a paradigm shift as both individuals and enterprises seek to leverage decentralized platforms for enhanced transparency, security, and user empowerment.

One of the primary growth factors for the Web3 Social Networking market is the rising global awareness and adoption of decentralized technologies. As concerns surrounding data privacy and centralized control intensify, users are increasingly gravitating towards platforms that offer greater autonomy and security. Web3 social networks, which are built on blockchain infrastructure, allow users to control their own data, monetize their content, and participate in governance through tokenized ecosystems. This shift is further accelerated by the proliferation of smart contracts and decentralized applications (dApps), enabling seamless peer-to-peer interactions and reducing the reliance on traditional intermediaries. The integration of NFTs and digital assets into social platforms also offers new monetization avenues for content creators and influencers, driving further adoption and engagement.

Another significant driver fueling market expansion is the growing involvement of enterprises and brands in the Web3 social networking ecosystem. Businesses are increasingly leveraging blockchain-based platforms to foster direct engagement with their communities, launch branded tokens, and facilitate transparent reward systems. The ability to build decentralized autonomous organizations (DAOs) within these networks enables collaborative governance and decision-making, which is reshaping how communities and organizations operate online. Additionally, the rise of tokenized social media is creating new business models, where users are incentivized to contribute valuable content and participate in platform governance, thus fostering vibrant, user-centric ecosystems. This enterprise adoption is accelerating the maturation of Web3 infrastructure and expanding its reach beyond early adopters to mainstream audiences.

The rapid evolution of regulatory frameworks and advancements in interoperability standards are also catalyzing the growth of the Web3 Social Networking market. Governments and regulatory bodies are gradually recognizing the potential of decentralized technologies and are working towards developing guidelines that foster innovation while ensuring user protection. Meanwhile, the development of cross-chain interoperability protocols is enabling seamless integration between different blockchain networks, enhancing user experience and expanding the utility of Web3 social platforms. These technological and regulatory advancements are lowering barriers to entry, encouraging a broader spectrum of developers, creators, and users to participate in the Web3 ecosystem, which is expected to sustain high growth rates throughout the forecast period.

From a regional perspective, North America currently leads the market, driven by a strong culture of digital innovation, early adoption of blockchain technologies, and a robust ecosystem of startups and investors. Europe follows closely, with significant investments in blockchain infrastructure and supportive regulatory environments. The Asia Pacific region is emerging as a high-growth market, fueled by a large, tech-savvy population and increasing government initiatives to promote blockchain adoption. Latin America and the Middle East & Africa are also witnessing growing interest, particularly in countries where decentralized platforms offer unique solutions to challenges related to censorship, financial inclusion, and digital identity. The global landscape is thus characterized by diverse adoption patterns, with each region contributing to the overall dynamism of the Web3 Social Networking market.

How do complex social systems evolve in the modern world? This question lies at the heart of social physics, and network analysis has proven critical in providing answers to it. In recent years, network analysis has also been used to gain a quantitative understanding of law as a complex adaptive system, but most research has focused on legal documents of a single type, and there exists no unified framework for quantitative legal document analysis using network analytical tools. Against this background, we present a comprehensive framework for analyzing legal documents as multi-dimensional, dynamic document networks. We demonstrate the utility of this framework by applying it to an original dataset of statutes and regulations from two different countries, the United States and Germany, spanning more than twenty years (1998–2019). Our framework provides tools for assessing the size and connectivity of the legal system as viewed through the lens of specific document collections as well as for tracking the evolution of individual legal documents over time. Implementing the framework for our dataset, we find that at the federal level, the United States legal system is increasingly dominated by regulations, whereas the German legal system remains governed by statutes. This holds regardless of whether we measure the systems at the macro, the meso, or the micro level.

This layer shows District Rural Road Networks in India under DRRP.District Rural Roads PlanThe District Rural Roads Plan would indicate the existing road network system in the district and clearly identify the proposed roads for providing connectivity to Unconnected Habitations, in an economic and efficient manner, in terms of cost and utility. The Core Network will identify the roads required to assure each eligible Habitation with a Basic Access (single all-weather road connectivity) to essential social and economic services. Accordingly, the Core network would consist of some of the existing roads as well as all the roads proposed for New Connectivity under the PMGSY.The attributes are given below: Block Block ID District District ID DRRP Road ER ID Road Category Road Name Road Owner State State ID PMGSY Programme Guidelines: https://pmgsy.nic.in/sites/default/files/PMGSY_III_guidelines.pdfCitation: Pertaining to Section 4(a) regarding attribution under the Open Data License:“Ministry of Rural Development, 2022. PMGSY Rural Connectivity Datasets, https://geosadak-pmgsy.nic.in/opendata/. Published under India’s Government Open Data License: https://data.gov.in/government-open-data-license-india ”Further, by using or downloading the dataset, you are self-certifying to be within the rights granted on the use of geospatial data as prescribed by the “Guidelines for acquiring and producing Geospatial Data and Geospatial Data Services including Maps” or any policy that follows the former on that matter.This map layer is offered by Esri India, for ArcGIS Online subscribers. If you have any question or comments, please let us know via content@esri.in.