Concept Of Neighborhood Research Articles

Chronological Analysis of The Ontological Sequence of The Neighborhood in Urban Physical Stratification; Şükran Neighborhood-Konya

The aim of this study is to understand the change in the spatial structure of Şükran district, which has been shaped by the concept of neighborhood from past to present in the urban memory of Konya. In this context, the stratification in the urban space with the historical stratification, the structure and road relationship that will be revealed together with the ontological structure of the neighborhood, and the evolution of the land subdivision form and situation over the years will be examined in detail. In this sense, the connection of the structure, which is expected to be completely changed in the future with the urban transformation of the neighborhood, which is located in the historical city center of Konya and where mainly dwellings are built, will be questioned and the systematic structure of the transformation will be investigated. As a result, questioning the transformation of urban spaces where the urban physical gradation continues is important in order to transfer urban memory to future generations. In line with these purposes, within the scope of the study, the ontological structure of the neighborhood will be questioned within the urban physical stratification that took place in the historical process, its formation in the city in unplanned and planned periods from the past to the present will be investigated in detail within the framework of the decisions taken by the city administrators and the changing regulations and a documentation will be done at the point of transferring the urban memory to the future.

Child health-friendly neighbourhood: a qualitative study to explore the perspectives and experiences of experts and mothers of children under 6 years of age in Tehran, Iran

ObjectivesCreating health-supportive environments is one of the key strategies for health promotion. The WHO launched the Healthy Cities Initiative which has inspired other international organisations to develop settings-based health initiatives,...

Kinematic origin of white dwarfs in the solar neighborhood

Context. White dwarfs are considered to be efficient cosmochronometers. Thanks to the recent space-borne mission Gaia, a nearly complete sample up to about 100 parsecs from the Sun has been compiled. However, the Galaxy, as a dynamic system, implies that these objects may have very diverse origins. It is therefore of paramount importance to characterize the origins of white dwarfs from the different Galactic structure components found in our solar neighborhood. Aims. We aim to compute the Galactic orbits for white dwarfs of the thin and thick disk, as well as the halo components observed in our solar neighborhood. On the basis of these determinations, we analyze the most probable regions of the Galaxy where they could have formed, along with the distribution of their orbital parameters and the observational biases introduced when constructing the local sample. Methods. We used a detailed Galactic orbit integration package, in conjunction with a detailed population synthesis code specifically designed to replicate the different Galactic components of the white dwarf population. Synthetic stars were generated based on the current observational sample and their orbital integration allowed for the reconstruction of the population’s history. Results. Our kinematic analysis of the white dwarf population reveals the ephemeral nature of the concept of the solar neighborhood, as the majority of thin-disk, thick-disk, and halo white dwarfs will have left our 100 pc neighborhood in approximately 3.30 Myr, 1.05 Myr, and 0.6 Myr, respectively. Moreover, the spatial distribution of the integrated thin-disk orbits suggests that 68% of these stars were formed at less than 1 kpc from the Sun, while most of the thick-disk members have undergone radial disk migration. Halo members are those stars that typically belong to the “inner halo”, given that their orbits mostly planar and do not extend beyond R = 20 − 25 kpc. Despite the observational bias, which mostly affects the oldest stars in the thick disk and halo, we show that the wider distribution of orbital parameters is well represented by the sample. Conclusions. The solar neighborhood is a transitory concept, whereby its current population of white dwarfs originates from larger regions of the Galaxy. This fact must be taken into account when analyzing the overall properties of such a population, such as its age distribution, metallicities, and formation history. Even so, the kinematic properties observed by recent missions such as Gaia are representative of the total population up to a distance of approximately 500 pc.

Integration of Manifold Learning and Density Estimation for Fine-Tuned Face Recognition

With the rapid advancements in data analysis and the increasing complexity of high-dimensional datasets, traditional dimensionality reduction techniques like Local Linear Embedding (LLE) often face challenges in maintaining accuracy and efficiency. This research aims to overcome the limitations of LLE, specifically its reliance on the nearest neighbor concept, its inability to distinguish differences among manifold points, and its underutilization of data discrimination information. To address these issues, we propose an advanced LLE algorithm that integrates decision tree-based neighbor recognition with Gaussian kernel density estimation. Decision trees accurately determine neighboring relationships, which are then optimized using Gaussian kernel density estimation to better reflect the distribution of sample points on the manifold. The algorithm also incorporates data discrimination information to enhance classification accuracy and efficiency. Evaluations in facial recognition tasks using SVM classifiers demonstrate significant improvements. Integrating decision trees (LLE-DT) yielded accuracy gains, with LFW at 98.75%, CFP 96.10%, and Olivetti 92.18%. Gaussian density estimation (LLE-GDE) achieved further enhancements, especially in LFW (99.13%), with CFP at 96.85%, and Olivetti at 91.82%. Combining both methods (LLE-DT-GDE) led to substantial improvements: LFW 99.61%, CFP 97.23%, and Olivetti 93.56%, highlighting the synergy between decision trees and Gaussian estimation. This advanced LLE algorithm effectively addresses the limitations of traditional approaches, showing promising results in complex data processing tasks such as facial recognition. These findings suggest its potential for broader applications in fields requiring robust data analysis and classification.

Do traffic flow states follow Markov properties? A high-order spatiotemporal traffic state reconstruction approach for traffic prediction and imputation

Assessing traffic states accurately is challenging due to the complex, high-dimensional, and nonlinear nature of traffic systems. This study introduces the innovative High-Order Spatiotemporal Traffic State Reconstruction (HOSTSR) algorithm, designed to track and predict traffic flow dynamics effectively. It combines phase space reconstruction with time delays and high-order neighborhood concepts from graph theory to improve traffic state assessments' accuracy. The algorithm's effectiveness is validated using chi-square tests and the Chapman-Kolmogorov equation to confirm the Markovian properties of traffic flows. A lean autoencoder, informed by prior Markov knowledge of traffic states, is developed for mapping traffic states to real traffic data, proving highly effective for traffic data imputation due to the Markov model's memoryless property. Experimental results from the PeMSD04 and PeMSD08 datasets show that HOSTSR outperforms traditional state reconstruction methods based on delayed coordinate embedding in predicting future traffic flow state based on four key metrics. The autoencoder framework, guided by prior Markov knowledge, shows significant advantages in addressing traffic data gaps in different cases over six baseline models. Gradient sensitivity analysis further evaluates the impact of prior knowledge on improving the autoencoder's interpretability for interpolation efforts.

A new semi-local centrality for identifying influential nodes based on local average shortest path with extended neighborhood

Quantifying the importance of nodes in complex networks is known as the problem of identifying influential nodes and is considered a critical aspect in interacting with these networks. This problem has many applications such as controlling rumors, sickness spreading, and viral marketing, where its importance has been understood by the research society in the last decade. This paper proposes a new semi-local centrality to identify influential nodes in complex networks based on the theory of Local Average Shortest Path with extended Neighborhood concept (LASPN). LASPN focuses on a distributed technique to extract the subgraph associated with each node and apply the average shortest path theory to it. We use the extended neighborhood concept to find the nearest neighbors of each node with low complexity, where this can lead to high efficiency in dealing with large-scale networks. In addition to applying relative changes in the average shortest path, the proposed metric considers the importance of the node itself as well as its nearest neighbors in ranking the nodes. Evaluation of the proposed centrality metric has been done through numerical simulations on several real-world networks. The results based on Kendall's τ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ au$$\\end{document} coefficient under the SIR infection spreading model show that LASPN improves the performance by 2.7% compared to the best available equivalent method.

The Agency of Socially Mixed Neighbourhoods Insights from the Historic Centre of Naples

In a city like Naples, the concept of neighbourhood is continuously negotiated and redefined through everyday practices of urban interaction and through the existence of multiple forms of social capital that animate daily life. In the historic centre of the city the negotiation of the neighbourhoods is influenced by the coexistence and close proximity of different social groups, which compels us to think about the significance of the 'agency of place' and how social difference defines the neighbourhood itself. The diverse housing situations and economic activities shape the characteristics of these central neighbourhoods that, crucially, are not captured in formal, administrative definitions of the city's districts. Through the case of the Condominio Sociale divia S. Nicola a Nilo, a city council housing policy to build a socially inclusive block of flats, this article discusses how the coexistence of various inhabitants, social networks, and spatial relationships represent a fundamental feature of the concept of neighbourhood in Naples. In doing so, the article points to the importance of the 'agency of place' and the maintenance of social heterogeneity as key to inclusive urban policies.

Soft rough sets based on covering and their applications

Soft rough based on covering SRC\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\mathcal {S}RC$\\end{document} theory has become a useful and well-known area of research in theories of uncertainty. The present work follows up on this flourishing research topic. We introduce a new model of SRC\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\mathcal {S}RC$\\end{document} in a fusion of soft set theory SST\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\mathcal {S}ST$\\end{document} and rough set depending on covering CRS\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\mathcal {C}RS$\\end{document}. We put forth a definition of soft rough covering approximation space SCAS\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\mathcal {S}CAS$\\end{document} via neighborhood concept. Some axiomatic systems of our model of SRC\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\mathcal {S}RC$\\end{document} are discussed. We study the relationship between our model of SRC\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\mathcal {S}RC$\\end{document} and three other SRC\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\mathcal {S}RC$\\end{document}-models. An algorithm for reduction of the attributes of the information systems using SCAS\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\mathcal {S}CAS$\\end{document} is established. Based on the theoretical discussion, we set forth some applications of our model which will be helpful in decision making process via SRC\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\mathcal {S}RC$\\end{document} theory.

Analysis and Application Research of E-Commerce Financial Management Based on T-DPC Optimization Algorithm

Given the intricate, multifaceted nature of financial data in e-commerce enterprises, this article presents a T-DPC algorithm for analyzing financial management in these businesses. The algorithm utilizes the t-SNE method to reduce the dimensionality of financial data, whilst also implementing an enhanced DPC algorithm based on the K-nearest neighbor concept to analyze financial data clusters. The results show that the F-measure metrics of the DPC algorithm optimized by t-SNE improve 16.7% and 3.07% over the DPC algorithm after testing on the PID and Wine datasets, and its running time is faster than the DPC algorithm on the Aggregation, D31, and R15 datasets by 16.2. Therefore, the algorithm has reference significance for the financial analysis of e-commerce enterprises.

How neighborhoods came to matter more over time: A broad historical sketch

ABSTRACT The demise of neighbourhood-scale community has been lamented for decades. Tight-knit neighboring has indeed declined. However, its significance is colored by nostalgia. In cities and suburbs, the loosening of neighborhoods has encouraged residents and agents to create imaginary local communities, partly by fashioning local traditions. In changed form, community persists. Underlying it, for those able to choose, are individualistic calculations. With increasing homeownership more people have a financial stake in place, the investment aspects becoming prominent since the 1980s. Because most children attend local schools, the growing importance of education has made them a major factor in neighborhood choice, with financial implications. In counterpoint, lower-income households with little choice are constrained to neighborhoods where the disadvantages of crime, poor mobility, and indifferent schools are exacerbated by growing wealth inequality. The concept and reality of neighborhoods have never been more important, in urban studies and in urban life.

KIRSAL VE KENTSEL ALANDA MAHALLE: KÖYLERDE, KENT VE KASABALARDA, BÜYÜKŞEHİRLERDE MAHALLE KAVRAMI

Bu çalışmada Türkiye'de mevcut mahalle kavramı, yapısı, gelişimi, kırsal ve kentsel özellikleri ve bunların farklı yönleri temelinde açıklanmaya çalışılacaktır. Öncelikle kırsal alan ve kentsel alan ifadeleri ele alınacak, kırsal alanda mahalle kavramının ne anlama geldiği, kentsel alanda kurulan mahallelerin varlığı ve büyükşehirlerde kırsal mahalle kavramının anlamı ve nedenleri araştırılacak ve karşılaştırılacaktır. Çalışmada yapılacak açıklamalar literatür ve hukuki metinlere dayandırılacaktır. Kırsal ve kentsel alanlardaki mahalle türleri karşılaştırılacak, sorunları sıralanacak ve öneriler getirilmeye çalışılacaktır.
 Türkiye'de üç tür mahalle uygulaması bulunmaktadır. Kırsal alanlarda bazı köylerin bünyesinde bulunan mahalleler, şehir ve kasabalarda belediyeler tarafından kurulan mahalleler, büyükşehirlerde kırsal mahalle olarak adlandırılan, daha önce köy veya belde belediyesi iken mahalleye dönüştürülen kırsal karakterli yerleşmeler. Bu çalışmada, bahsedilen üç farklı mahalle tipi açıklanmaya çalışılmıştır.
 Türkiye'de TÜİK, ülkenin kırsal nüfusunu hesaplarken yerleşim yerleri ölçeğinde köy, belde ve köy altı yerleşim yerlerini (oba, kom, mezra, divan gibi) esas almaktadır. Bazen nüfus büyüklüğü de bir ölçü olarak kullanılmaktadır. Örneğin Türkiye'de Köy Kanunu kent ölçütünü 20 binin üzerindeki nüfusa dayandırmaktadır. Ancak, nüfus büyüklüğü kentsel ve kırsal karakteri ölçmek için her zaman tek başına yeterli değildir.
 Avrupa Birliği'nde uygulanmakta olan DEGURBA (kentleşme derecesi) istatistik sistemi 2022 yılından itibaren Türkiye'de de uygulanmaya başlanmıştır. Köy ve mahalle bazında coğrafyanın her 1 km2'lik alanının nüfus büyüklüğü ve farklı sosyo-ekonomik işlevi dikkate alınarak bu 1 km2'lik plakalar yoğun kentsel alan, orta yoğun kentsel alan ve kırsal alan olarak kodlanmaktadır. Bu yeni kır-kent alan sınıflandırması köy ve mahalle düzeyinde yapıldığı için o yerleşmenin idari statüsünün daha etkin bir şekilde belirlenmesine olanak sağlamaktadır.

Theoretical framework of the Isfahani style: Inspiring sustainable aspects of a vernacular urban development

The Isfahani style represents a method of traditional Iranian architecture and urban development that existed in the early 20th century and is regarded as a leading model in most traditional Iranian cities. It exhibits several vigorous features contributing to its recognition as a traditional approach to sustainable architecture and urban development. This research endeavors to reveal a theoretical framework beneath these inspiring aspects using the typology of sustainable modern forms, including the hierarchy, passive design strategies, compactness, density, diversity, mixed land use, pluralism, balance, good composition, and integration over time. To this end, the study employs qualitative research methods, drawing from traditional samples, to identify innovative, energy and socially efficient, and low-impact strategies implemented in this vernacular architecture of Iran's semi-arid and hot climates. The findings revealed that the neighborhood concept as a local and plural community (Mahalla) was a vital phenomenon in Iran's urban development. Apparently, the demise of this paradigm effectively played an important role in the numerous challenges regarding the social, energy, and economic viability of modern Iranian cities. Hence, this study presented theoretical frameworks—aligned with sustainable concepts—from the Isfahani style through its analysis, classification, and interpretation, which can contribute to modern urban development.

Link prediction using extended neighborhood based local random walk in multilayer social networks

One of these challenges in the analysis of social networks is the problem of link prediction. The purpose of this problem is to find links that have not yet been observed, but may exist in the future. There are many solutions for link prediction on monoplex networks. However, many real social networks model communication in multiple layers, which are known as multilayer social networks. A solution for multilayer networks involves taking into account the information of all layers to make predictions for a target layer. Among the existing solutions, local random walk has been confirmed as an efficient technique for link prediction in monoplex networks, but this technique is inefficient for link prediction in multilayer networks due to computational complexity. In order to address this issue, in this paper we propose Extended Neighborhood based Local Random Walk (ENLRW) for link prediction in multilayer networks. ENLRW is an extended version of the classical local random walk technique in which the nearest neighbors are considered based on the extended neighborhood concept. ENLRW calculates the similarity between vertices by integrating several different metrics through reliable paths that include intra-layer and inter-layer information. Besides, ENLRW considers vertex influence as a similarity metric to provide an effective reliable biased random walk. The results of the simulations show that the use of different inter-layer and intra-layer information as well as the local random walk configuration with extended neighborhood provides a trade-off between precision and complexity. Specifically, ENLRW improves the average precision by 3.1% compared to the best available state-of-the-art method.

Коммунальная квартира (коммуналка) в референтном поле современной художественной литературы для детей и подростков

Representation in the modern culture of the Soviet past is associated with such a phenomenon as a communal apartment, which is also in demand in modern literature for children and adolescents. In the article, based on the material of the Corpus of Russian Prose for Children and Youth, as well as the most representative examples from the works of the last decade for children and adolescents, an attempt is made to determine the specifics of the topos of a communal apartment, which has become a “system sign” (referent) of Soviet childhood. The vectors of interpretation of a communal apartment set the ideological and spatial “us vs them” and “individual vs common” oppositions and their assessment. At the same time, various attributes of a communal apartment are significant for artistic modeling, defining the subject organization (neighbor, family member, etc.), the organization of space (room, corridor, kitchen, etc.), subject realities (bell, door, etc.). Modern writers’ work with the topos of a communal apartment is based on the tradition that developed in children’s literature of the Soviet period. The child hero, reproducing the stable components of the associative field of the concept “communal apartment” necessary for the objectification of the attribute, translates a potentially conflict situation associated with the concept of neighbor and determined by a stable set of plot situations and motifs into a comic one. In children’s and adolescent literature, the process of blurring the boundaries between anomaly and norm under the influence of communal life is reflected (the character type “crazy old woman”, zoomorphic images of neighbors, the acquisition of supernatural significance by things, the process of segmentation of “our” space, etc.). The transformation of the binary opposition “us vs them” can occur due to the inclusion of the element “nobody’s”, fixed in the definition of a unique type of character - “nobody’s grandmother”. In modern children’s literature, the situation associated with the marginal position of “nobody’s” old people in communal apartments, due to inclusion in the context of children’s play, loses its negative assessment, due to the functional connection of the types of “nobody’s grandmother” and “nanny”, which leads to the correlation of “nobody’s” and “common” in the picture of the communal world. The semantics of the “common” is more often manifested in relation to referents defining the spatial organization. The allocation of certain loci in a communal apartment that transmit ideas about one’s own and someone else’s or about one’s own and common, returns us to the description of relations with neighbors in the apartment, more precisely, to the predominance of emotive characteristics of the topos in question, objectified through the motif of quarrels and conflicts over the use of common places and property. “Common” loci (kitchen, corridor, restroom), being a boundary space, can, depending on the plot situation, actualize the “own” or “alien” semes. For example, a corridor, in accordance with the strategy of mastering and appropriating someone else’s space during the game, can also act as “own” space. The representation of the topos of a communal apartment in children’s literature, of course, reflects the realities of the Soviet era and the everyday life of the “inhabitants” of the communal apartment, with its “conflict zones”, but the child’s consciousness, acting as a focalizer of the narrative, allows emphasizing the semantics of the common. We can talk about the transformation of the opposition “us vs them” according to the laws of dialectics. The realities of the time, seen through the eyes of a child, allow us to consider the topos of a communal apartment/kommunalka as a “system sign” (referent) of Soviet childhood, as a dialectical image expressing the collectivist pathos of Soviet culture and metaphorically reflecting Iosif Vareikis’ idea of a communal apartment as the USSR. The authors declare no conflicts of interests.

Neighborhood Trip. How do guests’ neighborhood preferences shape the touristification process?

Urban tourists experience neighborhoods in a Peer-to-Peer context. However, literature overlooked the neighborhood concept in guests' accommodation location decisions, emphasizing the centrality (for a given quality) as the primary driver of urban touristification. This paper assesses how guests' preferences for neighborhoods could disrupt tourists' preferences for centrality. We discuss the exogeneity of the neighborhood tourism concept, verify its significance, and explore the relationship between neighborhoods and centrality in the urban touristification process. By extracting latent dimensions of 2,186 neighborhoods in 31 French cities and using a two-step hedonic approach (GW/2SLS regressions) on 45,600 Airbnb listings, we identify significant guests' preferences for neighborhood dimensions independently of embedded accommodation characteristics. Findings indicate that guests’ preference for touristy neighborhoods reinforces touristification but non-linearly (concavity), suggesting a touristification maximum threshold. With threshold effects, the other neighborhood dimensions (youthful-hub, popular, well-off) shape the touristification overflow, suggesting new regulations of the accommodations gathering.

WSLC: Weighted semi-local centrality to identify influential nodes in complex networks

Identifying and ranking influential nodes in complex networks is a critical aspect to study the survival and robustness of networks. Many ongoing researches have proposed centrality metrics to address this problem, so that the performance of each is attributed to specific scenarios. For example, metrics based on local structure have low ranking accuracy due to the use of limited information, and metrics based on global structure suffer from high complexity. Meanwhile, metrics based on semi-local structure are amazingly well, but an efficient centrality for identifying influential nodes is still not available due to differences in the structure and scale of networks. In addition, most semi-local centrality metrics only consider one aspect of each node's information, and their development still faces serious challenges. This paper develops a Weighted Semi-Local Centrality (WSLC) to identify influential nodes in complex networks based on extended neighborhood concept. Here, several different weights are investigated to find the best performance on WSLC. We use the extended neighborhood concept to select the nearest neighbors, which considers the global information of the network in a limited and efficient way to calculate the ranks. Here, a distributed approach is presented that can cut a subgraph of the entire network for each node with low complexity. This subgraph contains neighbors with different hops, which are used to maintain high efficiency when facing large-scale networks. In addition to the importance of the node itself, WSLC also combines the importance of the node's nearest neighbors with different hops for ranking. Therefore, defining semi-local structure with a distributed approach as well as using an efficient edge weighting policy differentiates WSLC from other existing centrality metrics. The evaluation of WSLC has been done through several real-world networks using Kendall's correlation. The effectiveness of WSLC under the SIR infection spreading model has been verified by extensive simulations compared to state-of-the-art centrality metrics.

Modeling dynamic social networks using concept of neighborhood theory

Dynamic social network analysis basically deals with the study of how the nodes and edges and associations among them within the network alter with time, thereby forming a special category of social network. Geometrical analysis has been done on various occasions, but there is a difference in the approximate distances of nodes. Snapshots for social networks are taken at each time slot and then are bound for these studies. The paper will discuss an efficient way of modeling dynamic social networks with the concept of neighborhood theory of cellular automata. So far, no model that uses the concept of neighborhood has been proposed to the best of our knowledge and the literature survey. Besides cellular automata that has been important tool in various applications has remained unexplored in the area of modelling. To this extent the paper, is the 1st attempt in modelling the social network that is evolving in nature. A link prediction algorithm based on some basic graph theory concepts has also been additionally proposed for the emergence of new nodes within the network. Theoretical and programming simulations have been explained in support to the model. Finally, the paper will discuss the model with a real-life scenario.

Searching natural neighbors in an accelerated way

Natural neighbor (NaN) is an adaptive neighbor concept for automatically determining k value for k-nearest neighbors, which has been proved effective in clustering analysis, classification, and outlier detection. However, the existing algorithms for searching NaN employ the global search strategy, which increases unnecessary consumption of time on non-critical points. To solve this problem, we propose a novel accelerated algorithm by utilizing a local search strategy, called ASNN. ASNN is based on the fact that if remote points have reverse nearest neighbors, others are likely to have reverse nearest neighbors. Firstly, it extracts the remote points by defining remote radius. Secondly, only the neighbors of remote points are searched, so that ASNN can quickly obtain the natural neighbor eigenvalue (NaNE). Compared to existing algorithms for searching NaNs, ASNN drastically reduces the number of query points and time consumption. The efficiency and effectiveness of ASNN are proved on synthetic and real datasets.

Inequalities in neighbourhood features within children's 20-minute neighbourhoods and variation in time spent locally, measured using GPS

There has been a growing interest in policies that encourage local living by promoting accessible and walkable communities, such as the 20-minute neighborhood concept. Despite the widespread adoption of this policy worldwide, little research has been conducted on the characteristics of children's 20-minute neighborhoods and their association with time spent locally.This study aimed to explore the features of Scottish children's 20-minute neighborhoods by analysing an 800 m road and path network buffer surrounding 687 children's homes. Based on existing literature, the study identified key features associated with children's time spent locally and the 20-minute neighborhood policy. The study then examined variations in these features by socioeconomic status, urbanicity, and gender.The findings revealed significant inequalities in the presence of health-benefiting (e.g., green spaces, recreational facilities, healthy food outlets) and health-harming (e.g., major roads, unhealthy commodity retailers) environments within children's 20-minute neighborhoods. Children from more deprived areas had access to more of both types of environments. The study also found that having a school within a 20-minute neighborhood was associated with an increased amount of time spent locally (IRR 1.62, 95% CI 1.5 to 1.8, p<0.001).The study suggests that the 20-minute neighborhood policy should extend beyond mere access to local amenities and prioritise creating healthy 20-minute neighborhoods, particularly in socioeconomically deprived areas. The research highlights the importance of promoting equal access to quality local environments, which can contribute to improved health and well-being outcomes for children.

Fine-tuning of colloidal polymer crystals by molecular simulation.

Through extensive molecular simulations we determine a phase diagram of attractive, fully flexible polymer chains in two and three dimensions. A rich collection of distinct crystal morphologies appear, which can be finely tuned through the range of attraction. In three dimensions these include the face-centered cubic, hexagonal close packed, simple hexagonal, and body-centered cubic crystals and the Frank-Kasper phase. In two dimensions the dominant structures are the triangular and square crystals. A simple geometric model is proposed, based on the concept of cumulative neighbors of ideal crystals, which can accurately predict most of the observed structures and the corresponding transitions. The attraction range can thus be considered as an adjustable parameter for the design of colloidal polymer crystals with tailored morphologies.