scholarly journals Segregation, integration, and balance of large-scale resting brain networks configure different cognitive abilities

2021 ◽  
Vol 118 (23) ◽  
pp. e2022288118
Author(s):  
Rong Wang ◽  
Mianxin Liu ◽  
Xinhong Cheng ◽  
Ying Wu ◽  
Andrea Hildebrandt ◽  
...  
Keyword(s):  
Cognitive Abilities ◽  
Structural Equation ◽  
Large Scale ◽  
Functional Organization ◽  
Diffusion Tensor ◽  
Brain Activity ◽  
Brain Networks ◽  
Deep Understanding ◽  
Human Cognition ◽  
Equation Modeling

Diverse cognitive processes set different demands on locally segregated and globally integrated brain activity. However, it remains an open question how resting brains configure their functional organization to balance the demands on network segregation and integration to best serve cognition. Here we use an eigenmode-based approach to identify hierarchical modules in functional brain networks and quantify the functional balance between network segregation and integration. In a large sample of healthy young adults (n = 991), we combine the whole-brain resting state functional magnetic resonance imaging (fMRI) data with a mean-filed model on the structural network derived from diffusion tensor imaging and demonstrate that resting brain networks are on average close to a balanced state. This state allows for a balanced time dwelling at segregated and integrated configurations and highly flexible switching between them. Furthermore, we employ structural equation modeling to estimate general and domain-specific cognitive phenotypes from nine tasks and demonstrate that network segregation, integration, and their balance in resting brains predict individual differences in diverse cognitive phenotypes. More specifically, stronger integration is associated with better general cognitive ability, stronger segregation fosters crystallized intelligence and processing speed, and an individual’s tendency toward balance supports better memory. Our findings provide a comprehensive and deep understanding of the brain’s functioning principles in supporting diverse functional demands and cognitive abilities and advance modern network neuroscience theories of human cognition.

scholarly journals Cyberstalking Victimization Model Using Criminological Theory: A Systematic Literature Review, Taxonomies, Applications, Tools, and Validations

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1670
Author(s):  
Waheeb Abu-Ulbeh ◽  
Maryam Altalhi ◽  
Laith Abualigah ◽  
Abdulwahab Ali Almazroi ◽  
Putra Sumari ◽  
...  
Keyword(s):  
Data Analysis ◽  
Structural Equation ◽  
Large Scale ◽  
Review Paper ◽  
Essential Element ◽  
Routine Activities ◽  
Criminological Theory ◽  
Equation Modeling ◽  
Future Research ◽  
Proposed Model

Cyberstalking is a growing anti-social problem being transformed on a large scale and in various forms. Cyberstalking detection has become increasingly popular in recent years and has technically been investigated by many researchers. However, cyberstalking victimization, an essential part of cyberstalking, has empirically received less attention from the paper community. This paper attempts to address this gap and develop a model to understand and estimate the prevalence of cyberstalking victimization. The model of this paper is produced using routine activities and lifestyle exposure theories and includes eight hypotheses. The data of this paper is collected from the 757 respondents in Jordanian universities. This review paper utilizes a quantitative approach and uses structural equation modeling for data analysis. The results revealed a modest prevalence range is more dependent on the cyberstalking type. The results also indicated that proximity to motivated offenders, suitable targets, and digital guardians significantly influences cyberstalking victimization. The outcome from moderation hypothesis testing demonstrated that age and residence have a significant effect on cyberstalking victimization. The proposed model is an essential element for assessing cyberstalking victimization among societies, which provides a valuable understanding of the prevalence of cyberstalking victimization. This can assist the researchers and practitioners for future research in the context of cyberstalking victimization.

Green Practices Implementation as Prerequisite to Sustain Firm Competitive Advantages

2015 ◽  
Vol 6 (4) ◽  
pp. 34-53
Author(s):  
Kardison Lumbanbatu ◽  
Vincent Didiek Wiet Aryanto
Keyword(s):  
Product Innovation ◽  
Structural Equation ◽  
Large Scale ◽  
Management Practices ◽  
Corporate Image ◽  
Equation Modeling ◽  
Competitive Advantages ◽  
Green Management ◽  
Marketing Performance

Encompassing firms to apply green policy in a holistic management practices are strongly required in order to maintain competitive advantages and experience long-term marketing performance. This current empirical research is aimed to fill the lack of empirical findings and empirical studies on firm's innovative concept. Green-based product innovation, green management practices and green corporate image are presented as the antecedents and postulated as the sources of sustaining firm competitive advantages. A questionnaire-based survey was deployed to collect data from Large Scale Enterprises in Indonesia with Top Management, Operational and Marketing Managers served as respondents. 500 questionnaires were mailed and 388 were valid for further analysis. Data was analyzed by using Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) via AMOS statistical software. Statistical findings demonstrated that green-based product innovation, green management practices and green corporate image significantly has a positive affect to sustain firm competitive advantages which is led to enhance long term marketing performance. However, green-based product innovation plays insignificant direct relationship on long term marketing performance. This study discusses some managerial implications for enterprises and recommendations on a basis of green implementation.

Consumers’ self-congruence with a “Liked” brand

2017 ◽  
Vol 51 (2) ◽  
pp. 367-390 ◽  
Author(s):  
Elaine Wallace ◽  
Isabel Buil ◽  
Leslie de Chernatony
Keyword(s):  
Social Relations ◽  
Brand Loyalty ◽  
Structural Equation ◽  
Large Scale ◽  
Equation Modeling ◽  
Future Research ◽  
Tie Strength ◽  
Brand Love ◽  
Content Type ◽  
Self Image

Purpose Brand “Likes” on Facebook facilitate self-expression, forming part of consumers’ virtual selves. Yet, consumers’ brand “Likes” may bear little resemblance to their material realities. This paper aims to test similarities of brand image with self-image for Facebook “Likes” to determine whether self-congruence with a “Liked” brand leads to positive offline brand outcomes. It also investigates whether consumers’ perceptions about their Facebook social relations influence self-congruent brand “Likes”. Design/methodology/approach A large-scale survey was conducted of regular Facebook users who “Liked” brands. Data from 438 respondents was analysed and hypotheses tested using structural equation modeling. Findings Empirical results show that the perceived self-congruence with a “Liked” brand increases with social tie strength. Perceived social tie strength is informed by perceived attitude homophily. When the perceived self-congruence with a “Liked” brand is higher, brand love and word of mouth (WOM) are enhanced. Consumers also have greater brand loyalty and offer more WOM when brands are loved. Research limitations/implications Findings demonstrate the influence of consumers’ cognitive network on “Likes” and brand outcomes. Further replication would enhance generalisability. Future research should use a wider sample and investigate other variables. Practical implications Findings support managers seeking to grow and analyse Facebook “Likes” by providing insights into brand loyalty, brand love and WOM for “Liked” brands. Originality/value The paper addresses the dearth of research exploring how consumers’ perceptions of their Facebook network influence their online brand behaviour and how perceived self-congruence with a “Liked” brand relates to brand outcomes.

CNTM-01. Evaluating Traditional and Non-Traditional Eloquent Areas in Patients with Brain Tumors: Large-scale Network Analysis Using a Machine Learning-Based Platform

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi224-vi224
Author(s):  
Alexis Morell ◽  
Daniel Eichberg ◽  
Ashish Shah ◽  
Evan Luther ◽  
Victor Lu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Brain Tumors ◽  
Large Scale ◽  
Diffusion Tensor ◽  
Brain Networks ◽  
Tumor Resection ◽  
Central Executive ◽  
Default Mode ◽  
Eloquent Areas ◽  
Neurologic Deficits

Abstract BACKGROUND Developing mapping tools that allow identification of traditional or non-traditional eloquent areas is necessary to minimize the risk of postoperative neurologic deficits. The objective of our study is to evaluate the use of a novel cloud-based platform that uses machine learning to identify cerebral networks in patients with brain tumors. METHODS We retrospectively included all adult patients who underwent surgery for brain tumor resection or thermal ablation at our Institution between the 16th of February and the 15th of May of 2021. Pre and postoperative contrast-enhanced MRI with T1-weighted and high-resolution Diffusion Tensor Imaging (DTI) sequences were uploaded into the Quicktome platform. After processing the data, we categorized the integrity of seven large-scale brain networks: sensorimotor, visual, ventral attention, central executive, default mode, dorsal attention and limbic. Affected networks were correlated with pre and postoperative clinical data, including neurologic deficits. RESULTS Thirty-five (35) patients were included in the study. The average age of the sample was 63.2 years, and 51.4% (n=18) were females. The most affected network was the central executive network (40%), followed by the dorsal attention and default mode networks (31.4%), while the least affected were the visual (11%) and ventral attention networks (17%). Patients with preoperative deficits showed a significantly higher number of altered networks before the surgery (p=0.021), compared to patients without deficits. In addition, we found that patients without neurologic deficits had an average of 2.06 large-scale networks affected, with 75% of them not being related to traditional eloquent areas as the sensorimotor, language or visual circuits. CONCLUSIONS The Quicktome platform is a practical tool that allows automatic visualization of large-scale brain networks in patients with brain tumors. Although further studies are needed, it may assist in the surgical management of traditional and non-traditional eloquent areas.

scholarly journals Resident Perceptions toward Tourism Development at a Large Scale

2019 ◽  
Vol 11 (18) ◽  
pp. 5074 ◽  
Author(s):  
Rong Li ◽  
Li Peng ◽  
Wei Deng
Keyword(s):  
Social Order ◽  
Structural Equation ◽  
Large Scale ◽  
Tourism Development ◽  
Equation Modeling ◽  
Affecting Factors ◽  
High Priority Task ◽  
Resident Perceptions ◽  
Environmental Deterioration ◽  
Economic Improvement

Tourism has been experiencing a rapid increase in the developed world, especially in China, and resident perceptions toward tourism development have been receiving increasing attention. However, resident perceptions on a large scale and the associated affecting factors remain unknown. In this study, 63 independent samples across China were analyzed using structural equation modeling, and the effects of three factors of per capita gross domestic product (GDP), tourist receipts and length of tourism development from the perceptive of economy, society and culture, and environment were investigated. Residents demonstrated a positive attitude toward tourism development on a large scale across China. However, the resident perceptions were GDP-dependent, which indicated a lower awareness of infrastructure improvement with the increase in GDP. Meanwhile, residents became more aware of environmental deterioration and social-order disturbance with the increase in the length of tourism development and tourist receipts. In addition, tourist receipts and length of tourism development exerted indirect effects on other perceptions by affecting the perception of environmental deterioration and economic improvement. Our results implied that to minimize the effect of negative perception, attention should be paid to the optimization of the perceptions of economic improvement and environmental deterioration, and the protection of the residential environment should be viewed as a high-priority task in improving resident perceptions.

scholarly journals Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition

2016 ◽  
Author(s):  
Timothy N. Rubin ◽  
Oluwasanmi Koyejo ◽  
Krzysztof J. Gorgolewski ◽  
Michael N. Jones ◽  
Russell A. Poldrack ◽  
...  
Keyword(s):  
Large Scale ◽  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Brain Activity ◽  
Human Cognition ◽  
Brain Images ◽  
Whole Brain ◽  
Context Sensitive ◽  
Cognitive States ◽  
Small Set

AbstractA central goal of cognitive neuroscience is to decode human brain activity--i.e., to infer mental processes from observed patterns of whole-brain activation. Previous decoding efforts have focused on classifying brain activity into a small set of discrete cognitive states. To attain maximal utility, a decoding framework must be open-ended, systematic, and context-sensitive--i.e., capable of interpreting numerous brain states, presented in arbitrary combinations, in light of prior information. Here we take steps towards this objective by introducing a Bayesian decoding framework based on a novel topic model---Generalized Correspondence Latent Dirichlet Allocation---that learns latent topics from a database of over 11,000 published fMRI studies. The model produces highly interpretable, spatially-circumscribed topics that enable flexible decoding of whole-brain images. Importantly, the Bayesian nature of the model allows one to “seed” decoder priors with arbitrary images and text--enabling researchers, for the first time, to generative quantitative, context-sensitive interpretations of whole-brain patterns of brain activity.

scholarly journals NEW TRENDS OF INTELLIGENT E-MARKETING AND CONSUMER BUYING BEHAVIOUR: A STUDY OF SELECTED UNIVERSITIES IN OSUN STATE, NIGERIA

2020 ◽  
Vol 5 (1) ◽  
pp. 14-25
Author(s):  
Haorayau Bolaji Babalola ◽  
Saheed Ademola Lateef ◽  
Abu Abu Zekeri
Keyword(s):  
Structural Equation ◽  
Large Scale ◽  
Mobile Marketing ◽  
Primary Data ◽  
Equation Modeling ◽  
Buying Behavior ◽  
Diffusion Of Technology ◽  
Product Service ◽  
Buying Behaviour ◽  
Consumer Buying Behavior

Understanding the attitude and behavior of customers is essential for every company where consumers differ in attitudes towards product/service. The consumer buying behavior in today's information-saturated world is based on how a product/service is marketed. However, the rapid diffusion of technology anchored growth and challenges on e-marketing trends. For instance, despite the widespread and large-scale adoption of e-marketing around the world, one does not see this trend happening on a big scale in Nigeria. Therefore, this study examines the influence of e-marketing factors on consumer buying behavior in the Nigerian context with particular reference to the University students participating in online business. The study employed the quantitative method, where primary data were collected via online distribution of the questionnaires among 233 customers, specifically students of the Osun state Universities in Nigeria. Also, structural equation modeling using AMOS software was employed to examine the relationship and hypothesis testing. The findings of this study revealed that e-marketing is positively and significantly influence consumer buying behavior in the area of e-mail marketing, mobile marketing, and e-advertising factors. The study asserted that firms must engage the consumers using technology that are more likely acceptable by consumers in the present digital and customer-oriented era. Also, knowing fully the emerging technologies may furnish valuable insights for various stakeholders to work well in Nigeria. Finally, the new trends in e-marketing are recommended from a strategic and operational level in which different techniques ease the buying behavior of consumers.  

scholarly journals The effect of IC components on innovation performance in Serbian companies

2018 ◽  
Vol 48 (3) ◽  
pp. 448-466 ◽  
Author(s):  
Sladjana Cabrilo ◽  
Aino Kianto ◽  
Bojana Milic
Keyword(s):  
Structural Equation ◽  
Deep Understanding ◽  
Business Environment ◽  
Innovation Performance ◽  
Equation Modeling ◽  
Content Type ◽  
Innovative Performance ◽  
Positive Effects ◽  
Innovation Potential ◽  
Structural Capital

Purpose In investigating the linkage between intellectual capital (IC) and innovation, it is important not only to explore how IC as a whole is associated with organizations’ innovative performance but also to gain a deep understanding of the role of different IC components (groups of intangibles) in companies’ innovation performance, which is the purpose of this paper in the context of Serbian companies. Design/methodology/approach This research is based on survey data collected from 100 Serbian companies with at least 100 employees during 2014/2015. Six IC components were analyzed (human, structural, internal relational, external relational, renewal and entrepreneurial) in terms of their effect on innovation performance. Analyses were conducted using structural equation modeling and correlation analysis. Findings Findings demonstrate that renewal capital, internal relational capital and structural capital have statistically significant positive effects on overall innovative performance in Serbian companies. Practical implications The outcomes reveal potential and barriers within IC that are crucial to innovation performance in Serbian companies. In this way, this study enables a deeper understanding of intangible drivers of innovation and highlights possibilities to foster intangible innovation potential in Serbian companies. Originality/value As context (economic and cultural) has emerged as a relevant factor in researching IC, this study is original in investigating IC effect on innovation within the Serbian business environment. Additionally, the broad sexpartite taxonomy of IC contributes to a wider understanding of knowledge and its linkages to innovation.

End-Users’ Acceptance of Biometrics Authentication to Secure E-Commerce within the Context of Saudi Culture

2013 ◽  
pp. 1356-1376
Author(s):  
Fahad AL Harby ◽  
Rami Qahwaji ◽  
Mumtaz Kamala
Keyword(s):  
Structural Equation ◽  
Large Scale ◽  
Sem Analysis ◽  
Equation Modeling ◽  
Factors Affecting ◽  
Moderating Variables ◽  
Use Of Technology ◽  
Moderating Factors ◽  
Education Levels ◽  
Scale Experiment

This book study presents recent findings from an ongoing cross-cultural study exploring the acceptance of a new security method based on biometrics authentication systems to be applied to an e-commerce application within the context of Saudi culture. The aim of the study was to explore factors affecting users’ acceptance of biometrics authentication system. The authors conducted a large scale experiment of 306 Saudis using a login fingerprint system and examined a proposed conceptual framework based on the Unified Theory of Acceptance and Use of Technology (UTAUT) with moderating variables. The findings from Structural Equation Modeling (SEM) analysis indicate that education levels are significant moderating factors, while gender and age do not record as significant. The findings of this study propose the need to take cultural background and disposition into consideration when applying biometrics technology.

Developing an Instrument for E-Public Services’ Acceptance Using Confirmatory Factor Analysis

2012 ◽  
Vol 24 (3) ◽  
pp. 18-44 ◽  
Author(s):  
Ahmed Alzahrani ◽  
Bernd Carsten Stahl ◽  
Mary Prior
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Technology Acceptance ◽  
Structural Equation ◽  
Large Scale ◽  
Public Services ◽  
Equation Modeling ◽  
Data Sampling ◽  
Potential Cost ◽  
Confirmatory Factor

Governments worldwide spend billions from their allocated IT budgets to deliver convenient electronic services to their citizens. As a result, it is important to encourage citizens to use these services to avoid potential failures. Yet, few empirical studies exist that cover the relevant issues of adoption from the perspective of citizens in developing countries. Moreover, the need for a well-validated instrument to capture citizen adoption of such services is vital, given the vast investment in technology and the potential cost-saving implications. This study integrates elements from the most popular theories, including adoption technology acceptance model (TAM), innovation diffusion theory (IDT), and theory of planned behavior (TPB), in conjunction with web trust models. It develops an instrument to measure citizens’ acceptance of electronic public services by utilizing confirmatory factor analysis (CFA) within the structural equation modeling technique. Findings of a large scale data sampling of citizens in Saudi Arabia indicate that the proposed measurement model is an acceptable fit with the data. Overall, the findings supply a rigorous instrument for measuring citizens’ acceptance of e-public services, providing further insights for researchers and offering policy makers a suitable tool with which to study proposed strategies.

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