Developmental transitions during adulthood and neighborliness: A multilevel cluster analysis

Aiyer, Sophie M.; Zahnow, Renee; Mazerolle, Lorraine

doi:10.1002/jcop.22246

Cited by 3 publications

(4 citation statements)

References 56 publications

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“…Kloos et al [20] used a cluster randomization algorithm to deliver an online positive psychology intervention to nursing home staff. Aiyer et al [21] proposed an analysis of psychological transition and neighbourhood relationships in adulthood using a multilevel clustering algorithm. Evidence was found for the direct effects of cluster membership and structural factors on neighbourhood relationships.…”

Section: Related Researchmentioning

confidence: 99%

“…To test the effectiveness of the improved PCA-based K-means clustering algorithm, a comparison with the typical K-means [29] and multilevel clustering [21] was performed on an artificially simulated dataset. e CPU used for the experiments was an Intel(R) Core(TM) i7-3770 CPU @ 3.40 GHz, with 4 GB of RAM, a 64 bit WIN 10 Operating System, and a MATLAB 2016b software environment.…”

Section: Manual Dataset Validationmentioning

confidence: 99%

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Machine Learning-Based Emotion Factor Analysis of Sport Fan Community

Heng-chuan

Liu

Zhen

2022

Security and Communication Networks

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Football is one of the most popular sports in the world. As the popularity of football continues to grow worldwide, so does the number of incidents of violence on the pitch. Today, doping, match fixing, black whistles, and football hooliganism are ranked as the four most toxic aspects of sport. How to study the factors that cause aggressive behaviour of fans from a psychological perspective has become a key issue in the field of sports. Therefore, this study proposes a method for mining the psychological factors of sport fan community members based on machine learning clustering. Firstly, three different members of a large fan community, i.e., university students, office workers, and unemployed people, are used as research subjects to investigate the psychological factors influencing fans’ aggressive behaviour using a questionnaire method. Secondly, the data obtained were mined and analysed using the K-means clustering algorithm in machine learning techniques. At the same time, a K-means initial clustering centre optimization algorithm based on principal component analysis (PCA) was proposed for the data characteristics of the interaction of psychological factors. The results show that the new algorithm significantly improves the quality of clustering compared with other optimization algorithms and accurately identifies the multiple factors that contribute to the occurrence of fan attacks.

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Section: Related Researchmentioning

confidence: 99%

Section: Manual Dataset Validationmentioning

confidence: 99%

Machine Learning-Based Emotion Factor Analysis of Sport Fan Community

Heng-chuan

Liu

Zhen

2022

Security and Communication Networks

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“…This is the motivation, namely for bacteria from the genera Geobacter and Shewanella to be the most investigated model microorganisms as biocatalysts in MFC. Recently, it was established that a new bacterial strain, Pseudomonas putida 1046 [14], is capable of expressing a cellular redox compound mediating the electron transfer through a polymer matrix at high positive poising potential, which indicated that the bacteria possess electrogenic properties.…”

Section: Introductionmentioning

confidence: 99%

Graphite–Metal Oxide Composites as Potential Anodic Catalysts for Microbial Fuel Cells

et al. 2020

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In this study, graphite–metal oxide (Gr–MO) composites were produced and explored as potential anodic catalysts for microbial fuel cells. Fe2O3, Fe3O4, or Mn3O4 were used as a catalyst precursor. The morphology and structure of the fabricated materials were analyzed by scanning electron microscopy and X-ray diffraction, respectively, and their corrosion resistance was examined by linear voltammetry. The manufactured Gr–MO electrodes were tested at applied constant potential +0.2 V (vs. Ag/AgCl) in the presence of pure culture Pseudomonas putida 1046 used as a model biocatalyst. The obtained data showed that the applied poising resulted in a generation of anodic currents, which gradually increased during the long-term experiments, indicating a formation of electroactive biofilms on the electrode surfaces. All composite electrodes exhibited higher electrocatalytic activity compared to the non-modified graphite. The highest current density (ca. 100 mA.m−2), exceeding over eight-fold that with graphite, was achieved with Gr–Mn3O4. The additional analyses performed by cyclic voltammetry and electrochemical impedance spectroscopy supported the changes in the electrochemical activity and revealed substantial differences in the mechanism of current generation processes with the use of different catalysts.

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“…Neighborliness is a particular form of neighboring, and both neighboring and neighborliness are localized dimensions of more expansive terms of art such as social capital, social organization, and others. Neighborliness occurs when neighbors engage in warm, caring, and mutually supportive relationships and is an element of social integration (Aiyer, Zahnow, & Mazerolle, 2020). Although neighborliness occurs in a variety of venues, as used here the term refers to locality-based, reciprocal social support predicated on positive neighborly relations.…”

mentioning

confidence: 99%

Neighborhood, neighborliness, and family and child well-being.

McDonell

Sianko

2021

American Journal of Orthopsychiatry

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Although neighborhood context is a well-recognized factor in the well-being of children and families, little systematic research exists to guide inquiries into the intersection of neighborhood social processes and child and family well-being. Moreover, despite the increased popularity of neighborhood effects research over the last several decades, crucial questions around the debate on how to align research findings with tangible experiences for children and families remain open. This article reviews selected studies that linked neighborhood factors to specific domains of child and family well-being: parenting, safety, health, and educational outcomes. By focusing on neighborliness, a particular form of neighboring, the study aims to shift the focus from macrolevel indicators of neighborhood context, to a more dynamic set of attributes that characterize neighborhood life, with the hope of inspiring others to build upon the findings and begin to translate the conclusions to meaningful policies and programs. Public Policy Relevance StatementNeighborhoods play a significant role in the well-being of children and families. Research has shown that neighborhood social processes have direct and indirect effects on how children are parented, on child and family health and safety, and on children's educational outcomes. Although research on neighborhood effects has increased in the recent past, there is still much to learn.

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Developmental transitions during adulthood and neighborliness: A multilevel cluster analysis

Cited by 3 publications

References 56 publications

Machine Learning-Based Emotion Factor Analysis of Sport Fan Community

Machine Learning-Based Emotion Factor Analysis of Sport Fan Community

Graphite–Metal Oxide Composites as Potential Anodic Catalysts for Microbial Fuel Cells

Neighborhood, neighborliness, and family and child well-being.

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