Neighborhood Influences Research Articles

Condensation phenomena in preferential attachment trees with neighbourhood influence

We introduce a model of evolving preferential attachment trees where vertices are assigned weights, and the evolution of a vertex depends not only on its own weight, but also on the weights of its neighbours. We study empirical measures associated with edges with endpoints having certain weights, and degrees of vertices having a given weight. We show that the former exhibits a condensation phenomenon under a certain critical condition, whereas the latter behaves like a mixture of a power law distribution, depending on the weight distribution. Moreover, in the absence of condensation, for any measurable set we prove almost-sure convergence of the measure of that set under the related measure. This generalises existing results on the Bianconi-Barabási tree as well as on an evolving tree model introduced by the second author. Finally, as an application of our results, we provide criteria under which the degree distribution of this model behaves like a power law, and prove a limiting statement about the growth of the neighbourhood of a fixed vertex.

Middle-Class “Chavs” From Working-Class Areas? Habitus, the Attainment Gap, and the Commodification of Higher Education Among Communication Students in England

The purpose of the article is to compare and contrast higher education and research among public relations and journalism students of middle-class and working-class origin. The paper applied Bourdieu’s theory of habitus to analyze prejudices against the working class, explores whether working-class students express an anti-education view, and whether the appreciation of education (and research in particular) is a predominantly middle-class attitude. Focus groups and an online questionnaire were used to obtain views of students at a university in Northern England. Triple coding (open, axial, selective) was used and the data was then analyzed and presented using thematic analysis. Findings show that early socialization about education as well as students’ type of neighborhoods (habitus) influence studies’ views of higher education and research in particular. While the findings show some similarity with views in the literature of the middle-class being more inclined to value education, these findings show that this is true only for those who grow up in middle class areas whereas middle-class students who grew up in working-class areas show working-class attitudes toward education. Equally, working-class students who grew up in middle-class areas show what is usually perceived as a middle-class view of education. Both groups of students show a tendency toward embracing a consumerist view of higher education.

THE IMPACT OF SOCIAL-PHYSICAL FACTORS ON PUBLIC HOUSING TRANSFORMATION IN TRIPOLI

Researchers have acknowledged that physical surroundings are a concrete manifestation of spatial organisation. Its arrangement outlines spatial relationship of social activity networks within housing units. In Libya, cities display minimal sensitivity to socio-physical attributes which affect public housing transformation. In order to focus on users’ transformations experience and emphasis on socio-physical environment influence. Public housing dwellers are surveyed to determine the socio-physical impact on housing transformations initiatives. The aim of this study is to develop a socio-physical responsive design framework for public housing projects based on user-initiated transformation experience. A survey is carried out among 304 households in twelve public housings areas in western Libya to evaluate users’ experience on the socio-physical model of housing transformation. Public housing such as neighbourhood influence, technology, plot size and quality of urban living standards are investigated using a questionnaire and analysed using SEM (AMOS). The findings revealed that socio-physical constituents have influence on housing transformation decisions made by house owners. It contributes to a housing design which respects both the users requirements and provide a healthy urban development at the same time.

The Influence of Negative Orthographic Neighborhood in the Lexical Decision Task: Valence and Arousal Contributions.

This study investigated whether the visual recognition of neutral words might be influenced by the emotional dimensions (i.e., valence and arousal) of orthographically similar lexical representations, and whether this might also depend on emotional-related traits of participants (i.e., alexithymia). To this end, 108 participants performed a lexical decision task with 80 neutral words with a higher frequency orthographic neighbor that varied in valence (from neutral to negative) and arousal (from low to high). The main finding was the expected interaction effect between the valence and arousal of the neighbor on the lexical decision times of neutral stimulus words. Longer reaction times were found when the valence score of the neighbor decreased from neutral to negative for words with a low-arousal orthographic neighbor while this emotional neighbor effect was reversed for words with a high-arousal negative neighbor. This combined influence of the valence and arousal of the neighbor was interpreted in terms of increased lexical competition processes and direct influence of the affective system on the participant's response. Moreover, this interaction effect was smaller when the level of alexithymia of the participants increased, suggesting that people with a higher level of alexithymia are less sensitive to the emotional content of the neighbor. The results are discussed within an interactive activation model of visual word recognition incorporating an affective system with valence and arousal dimensions, with regard to the role of the alexithymia level of participants.

Association of neighborhood socioeconomic disadvantage and cognitive decline

AbstractBackgroundThere is increasing emphasis on research recruitment of persons of color to understand the influence of race/ethnicity on Alzheimer’s disease (AD) and AD‐related dementia (ADRD) risk. Normal persons with subjective cognitive decline (SCD) are considered at risk for future decline as SCD is thought to be a preclinical stage of AD/ADRD. Yet the validity of SCD across racial and ethnic groups is unclear. Race/ethnicity‐related conditions such as socio‐economic disadvantage, neighborhood segregation, and poor housing quality (neighborhood deprivation) are important factors in stress, discrimination and other social determinants of health and may provide more in‐depth explanations for SCD than race/ethnicity alone.MethodWe examined the role of neighborhood deprivation and compared this to the role of race/ethnicity in SCD using a validated instrument, the Brief Cognitive Rating Scale (BCRS). Using the Area Deprivation Index (ADI), we cross‐sectionally examined the relationship between neighborhood characteristics and SCD in a racially and ethnically diverse group of community‐residing older adults in New York City. For those having available addresses, we used data from participants with normal cognition in the NYU Alzheimer’s Disease Research Center (n=313) and conducted multivariable logistic regressions, comparing two models with the BCRS as our outcome: using the ADI without race/ethnicity and then with race/ethnicity, both adjusting for age, sex, education (years).ResultParticipant mean age was 72.8.0 ± 7.4 years; mean education was 16.3± 3.1 years. Seventy‐six percent of the cohort was female (n=232); 12.1% (n= 38) reported as Hispanic, 73.5% (n=230) non‐Hispanic (NH) White; 13.4% reported as NH Black or African‐American (n=42); and 3 were other. In multivariable logistic regressions of BCRS domain‐specific analysis, ADI was a significant predictor of BCRS‐measured SCD even when race/ethnicity was included as a covariate (p<0.05), suggesting independent influence of neighborhood deprivation.ConclusionNeighborhood characteristics may play an influential role in SCD regardless of race/ethnicity and thus are likely important risk factors for AD/ADRD. If larger and more diverse studies generate similar findings, neighborhood investment and recruitment goals for AD/ADRD studies will require more focus on neighborhoods with greater deprivation.

Crime hotspot prediction based on dynamic spatial analysis

Crime is not a completely random event but rather shows a pattern in space and time. Capturing the dynamic nature of crime patterns is a challenging task. Crime prediction models that rely only on neighborhood influence and demographic features might not be able to capture the dynamics of crime patterns, as demographic data collection does not occur frequently and is static. This work proposes a novel approach for crime count and hotspot prediction to capture the dynamic nature of crime patterns using taxi data along with historical crime and demographic data. The proposed approach predicts crime events in spatial units and classifies each of them into a hotspot category based on the number of crime events. Four models are proposed, which consider different covariates to select a set of independent variables. The experimental results show that the proposed combined subset model (CSM), in which static and dynamic aspects of crime are combined by employing the taxi dataset, is more accurate than the other models presented in this study.

Relationships Among Neighborhood Poverty, Access to Healthy Food, and Diabetes Self-Management in Women Who Received Perinatal Nurse Home Visits

ObjectiveTo examine the relationships among neighborhood poverty, access to healthy food, and diabetes self-management in pregnant women in an urban setting who received perinatal nurse home visits. DesignExploratory descriptive secondary analysis of existing individual-level and neighborhood-level data. SettingPhiladelphia, Pennsylvania, United States. ParticipantsWomen who were pregnant, had diabetes, and were enrolled in the citywide perinatal nurse home visiting program because of their diabetes (N = 264). MethodsWe retrieved neighborhood-level aggregated data on poverty and access to healthy food from PolicyMap, a geographic information system. We retrieved individual-level data from a clinical research database. Access to healthy food was operationalized at the individual level by reported use of the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). We operationalized diabetes self-management as good or poor glycemic control. We conducted descriptive and logistic regression analyses. ResultsWe found no relationship between neighborhood-level poverty and neighborhood-level access to healthy food with women’s glycemic control. However, at the individual level, use of the WIC program was associated with glycemic control (p = .034). Participants who reported not using this program were two times more likely to have poor glycemic control than those who did (OR = 2.045, 95% confidence interval [1.003, 2.045]). ConclusionIt is important to understand how the complex interplay between neighborhoods and individual factors of poverty and access to healthy food influences health outcomes among pregnant women. The WIC program may mediate neighborhood influence on diabetes self-management. Future research is warranted on how this program and nurse home visiting services can optimize maternal health outcomes among women who have diabetes during pregnancy.

Who’s your Neighbour? Social Influences on Domestic Violence

We examine the impact of neighbourhood physical domestic violence on the likelihood of being exposed to physical abuse within a household using nationally representative data from the fourth wave of the National Family Health Survey of India. To address potential endogeneity issues in analysing neighbourhood influences, we utilise an instrumental variables approach that compares households in the same state but different neighbourhoods. Using exogenous variation in neighbouring women’s exposure to parental violence in her natal family as an instrument for average neighbourhood domestic violence, we find that a 1 standard deviation increase in neighbourhood domestic violence leads to a 0.2 standard deviation increase in the probability of domestic violence within a household. We establish that domestic violence is not only driven by intra-household factors but also observable changes at a neighbourhood level.

Global Climate Model Tracking Using Geospatial Neighborhoods

A key problem in climate science is how to combine the predictions of the multi-model ensemble of global climate models. Recent work in machine learning (Monteleoni et al. 2011) showed the promise of an algorithm for online learning with experts for this task.We extend the Tracking Climate Models (TCM) approach to (1) take into account climate model predictions at higher spatial resolutions and (2) to model geospatial neighborhood influence between regions. Our algorithm enables neighborhood influence by modifying the transition dynamics of the Hidden Markov Model used by TCM, allowing the performance of spatial neighbors to influence the temporal switching probabilities for the best expert (climate model) at a given location. In experiments on historical data at a variety of spatial resolutions, our algorithm demonstrates improvements over TCM, when tracking global temperature anomalies.

The subnational crowding out effect of mining windfalls on local tax effort: Does the level of local provision of public goods matter?

Although the resource curse offers evidence for the national crowding out generated by resource windfalls from mining, subnational crowding is not fully understood. This knowledge gap is problematic because these windfalls should cover the negative externalities that exist in host zones. Additionally, these communities have different fiscal responsibilities due to the mining industry's environmental, economic, and social costs. This article estimates the subnational crowd out of mining windfalls on local tax collection by considering different levels of fiscal responsibility. We employ panel data for 322 Chilean municipalities between 2008 and 2019 using an exogenous rule for assigning mining windfalls in order to attribute causality. Our results confirm the crowding out hypothesis. First, a US$1.0 increase in mining windfalls results in a US$0.2 decrease in the property tax collected. Second, subnational crowding out is twice as high in municipalities with a high level of fiscal responsibility; a US$1.0 increase in windfalls crowds out US$0.4 in non-resource revenue. Third, considering the influence of nearby neighborhoods and the spatial interdependence, crowding out is four times higher than non-spatial estimations. These results call for local policies that consider the fiscal capacity of a municipality in order to disincentivize undesirable behavior from extra resource revenues.

Role of crystallographic orientation on intragranular void growth in polycrystalline FCC materials

In this work, we study the effect of crystallographic orientation and applied triaxiality on the growth of intragranular voids. Two 3D full-field micromechanics methods are used, the dilatational visco-plastic fast-Fourier transform (DVP-FFT) and the crystal plasticity Finite Elements (CP-FE), both of which incorporate a combination of crystalline plasticity and dilatational plasticity. We demonstrate with several select cases that predictions of void growth from both formulations agree qualitatively. With the more computationally efficient DVP-FFT, additional effects of polycrystalline microstructure and the influence of nearest neighborhood are investigated. Crystals bearing a single intracrystalline void are studied in three types of 3D microstructural environments: isolated single crystals, individual equal-sized grains within a regular polycrystal, and individual variable sized grains within a polycrystal with grains and voids randomly located. We show that loading type plays a significant role. In strain-rate controlled conditions, voids in the hardest [111]-crystals grow the fastest in time, whereas in stress-controlled conditions, voids in the softest [100]-crystal grow the fastest in time. The analysis reveals that on average void growth is slower for the same starting orientation in the polycrystal than in the single crystal. We find that at the highest triaxiality tested that the correlation between crystal orientation and void growth rate in the polycrystal strengthens, drawing closer to that seen in the isolated single crystals. These results and model can help guide the microstructural design of polycrystalline materials with high strength and damage-tolerance in high-rate deformation.

Does tree canopy moderate the association between neighborhood walkability and street crime?

Creating walkable places and increasing urban vegetation in neighborhoods have emerged as important planning strategies to promote health, social, and environmental benefits. Although past studies have found that walkability and tree canopy are associated with crime, little research has comprehensively examined how neighborhood walkability and tree canopy are associated with street crime. The current study fills this gap by analyzing the relationship among walkable access to amenities measured by Walk Score, urban tree canopy, and the five-year violent and property street crime rates (2014–2018) across an entire city. This study used the case of Austin, Texas to investigate the association exists between 1) neighborhood walkability and street crime and 2) tree canopy and street crime. We also assessed whether the association between neighborhood walkability and street crime was moderated by tree canopy. The first set of models based on a negative binomial regression showed that neighborhood walkability was positively associated with both violent and property street crime rates while tree canopy was inversely associated with violent and property street crime rates. The second set of models revealed a nonlinear relationship between neighborhood walkability and the street crime rate. The final set of models showed that tree canopy cover can moderate the relationship between street crime and neighborhood walkability, suggesting that tree canopy can somewhat offset the negative influence of walkable neighborhoods, such as crowdedness and noise, in relation to street crime. The findings have implications for developing evidence-based planning, design, and policy strategies to create livable streets and prevent street crime by planting more trees in walking-friendly environments.

Discovering influential users in social network using weighted cumulative centrality

AbstractThe sharing of information is an inherent tendency of human beings that helps in content dissemination as it cascades to the larger networked audience. In this article, we have proposed a novel weighted cumulative measure for discovering influential users in such networked structures. Our method generically combines the impact of multiple structural features of the network, along with local and global information to produce weighted cumulative centrality (WCC) score. Local information internments nodes direct neighborhood influence whereas global information scrutinizes network structure as a whole via propagating shortest paths. To assess the performance of our innovated measure, a benchmark diffusion model is employed as an artificial stochastic model to track the rate of information spread. The resultant outcome is verified on five different networks including scale‐free and random, and real‐world networks, namely, Facebook, BlogCatalog, and Twitter network. Furthermore, a comparative study is conducted to justify the spreading ability of proposed multifeature based WCC against existing single‐feature based approaches using relative performance ratio. Simulation with single and multiple triggering nodes endorse the efficacy of our proposed method over existing counterparts in terms of the coverage rate, thus showing support for early adoption phenomena in proposed WCC to infest a social network.

Assessment of disaster-prone areas considering the influence of terrain and neighborhood

Assessment of disaster-prone areas considering the influence of terrain and neighborhood

Surveying the Level of Knowledge, Awareness and Health Related Risk of Substance Abuse among Students in University of Port Harcourt’s Host Communities

Background: Substance abuse refers to the use of all chemicals, drugs and industrial solvents that can produce dependence (psychological and physical). It can also be referred to as the repeated non-medical use of potentially addictive chemical and organic substances. There is poor data about the health related risk of substance abuse among students in Nigeria. Hence, this survey was done to determine the level of knowledge, awareness & the health related risk of substance abuse among students and her host communities as an attempt to curb the menace and its effect on students and the entire society at large. 
 Materials and Methods: The study was a descriptive cross-sectional study carried out in ALUU Community in Ikwerre Local Government Area of Rivers State. The study involved 150 volunteers recruited randomly through a multi-staged sampling technique which included secondary school students, undergraduates and postgraduates who are 13yrs and above residing in ALUU community while those who did not give consent were excluded. The data was collected using self-structured close-ended self-administered questionnaires and data analysis done using SPSS version 25. 
 Results and Discussions: The results of the study showed that 98.67% have knowledge of drug abuse, the knowledge of health and social effects of substances of abuse on humans was 96.67%. The most prevalent health/social effects were: memory loss 74.67%, sleeping and eating disorders 67.33%. The results of the study have shown that more than 2/3rd of the participants had good knowledge of drug abuse. Similarly, more than 2/3rd of the participants heard about drug/substance abuse via the mass media. The most abused drug/substance was alcohol, 9 in 10 persons abused alcohol. This goes on to imply that the chance that a student who is resident in Aluu abuses alcohol is 90%. 
 Conclusion: The results of the study showed that 98.67% have knowledge of drug abuse, the knowledge of health and social effects of substances of abuse on humans was 96.67%. The most prevalent health/social effects were: memory loss 74.67%, sleeping and eating disorders 67.33%. Peer group, neighbourhood influence, and ‘the only child syndrome’ were the attributed contributing factors to the continual use of alcohol/drugs, even when the health and social effects are well known.

Private school enrolment and changes in regional voucher policies: Empirical evidence from an Italian regional plan

We estimate the effect of a change in the voucher policy of the most densely populated region in Italy (Lombardy) on private school enrolment at primary, junior and upper secondary educational levels. The policy change has been implemented in 2008 and we observe the potential effects in the short run (i.e., between 2008 and 2012). After controlling for anticipation effects and potential neighborhood influence in school choice policies through a conditional difference-in-differences procedure, we find that the policy change did not affect private school enrolment in the region across all educational levels.

The Economic Incentives of Cultural Transmission: Spatial Evidence from Naming Patterns Across France

Abstract This paper studies how economic incentives influence cultural transmission, using a crucial expression of cultural identity: child naming decisions. Our focus is on Arabic versus non-Arabic names given in France over the 2003–2007 period. Our model of cultural transmission features three determinants: (i) vertical (parental) cultural transmission culture; (ii) horizontal (neighbourhood) influence; (iii) information on the economic penalty associated with Arabic names. We find that economic incentives largely influence naming choices: if the parental expectation on the economic penalty was zero, the annual number of babies born with an Arabic name would be more than 50% larger.

Modeling spatial diffusion of decentralized water technologies and impacts on the urban water systems

Understanding the market demand for decentralized water technologies and the impacts on the urban water systems (UWS) is critical to sustainable promotion in urban communities. In this paper, we developed a spatial agent-based model (ABM) that simulates the adoption of home-based rainwater harvesting (RWH) and greywater recycling (GWR) by single-family households in Boston, United States. We applied system dynamics modeling (SDM) to evaluate the impacts of decentralized technologies on the UWS. The change in carbon emissions of the UWS was modeled as the environmental benefit for household choice decisions in ABM. We validated our integration by comparing the simulated reservoir elevations with the reference-year values and comparing where early adoptions emerge with the reported installations. In the results, we first examined the sensitivity of the adoption and diffusion to the market promotion, neighbor's influence, environmental benefits, and economic attractiveness. Our simulation highlights the diffusion from central downtown to the suburban. RWH has higher adoptions than GWR, and RWH starts diffusing much earlier. Reservoir water availability is improved through the adoption of RWH and GWR. As the tradeoffs, reservoirs discharge more water for storage security, and hydropower generation becomes less as the need of water transfer decreases. The UWS do not reduce carbon emissions due to the high electricity consumption of GWR. Utilizing the improved water resources and reducing the impact of decentralized technologies are required for sustainable promotion of water decentralization. Our integrated modeling can be improved by including more critical socio-technical interactions for spatial planning of decentralized water technologies.

Influence of neighbourhoods on the extent and compactness of tropical tree crowns and root systems

Influence of neighbourhoods on the extent and compactness of tropical tree crowns and root systems

Accessibility and Historical Change: An Emergent Cluster Led Uncles and Aunts to Become Aunts and Uncles.

There are times when a curiously odd relic of language presents us with a thread, which when pulled, reveals deep and general facts about human language. This paper unspools such a case. Prior to 1930, English speakers uniformly preferred male-before-female word order in conjoined nouns such as uncles and aunts; nephews and nieces; men and women. Since then, at least a half dozen items have systematically reversed their preferred order (e.g., aunts and uncles, nieces and nephews) while others have not (men and women). We review evidence that the unusual reversals began with mother and dad(dy) and spread to semantically and morphologically related binomials over a period of decades. The present work proposes that three aspects of cognitive accessibility combine to quantify the probability of A&B order: (1) the relative accessibility of the A&B terms individually, (2) competition from B&A order, and critically, (3) cluster strength (i.e., similarity to related A'&B' cases). The emergent cluster of female-first binomials highlights the influence of semantic neighborhoods in memory retrieval. We suggest that cognitive accessibility can be used to predict the word order of both familiar and novel binomials generally, as well as the diachronic change focused on here.