Network analyses of internet gaming disorder symptoms and their links with different types of motivation
- Gomez, Rapson, Stavropoulos, Vasileios, Tullett-Prado, Deon, Schivinski, Bruno, Chen, Wai
- Authors: Gomez, Rapson , Stavropoulos, Vasileios , Tullett-Prado, Deon , Schivinski, Bruno , Chen, Wai
- Date: 2022
- Type: Text , Journal article
- Relation: BMC Psychiatry Vol. 22, no. 1 (2022), p.
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- Description: The study used regularized partial correlation network analysis (EBICglasso) to examine the structure of DSM-5 internet gaming disorder (IGD) symptoms (network 1); and the associations of the IGD symptoms in the network with different types of motivation as defined in the self-determination theory i.e., intrinsic motivation (engaging in an activity for something unrelated to the activity), identified regulation (engaging in the activity because it aligns with one’s values and/or goals), external regulation (engagement in activity being driven by external rewards and/or approval), and amotivation (engaging in an activity without often understanding why) (network 2). Participants were 968 adults from the general community. They completed self-rating questionnaires covering IGD symptoms and different types of motivation. The findings for network 1 showed mostly positive connections between the symptoms within the IGD network. The most central symptom was loss of control, followed by continuation, withdrawal symptoms, and tolerance. In general, these symptoms were more strongly connected with each other than with the rest of the IGD symptoms. The findings for network 2 showed that the different types of motivation were connected differently with the different IGD symptoms. For instance, the likeliest motivation for the preoccupation and escape symptoms is intrinsic motivation, and for negative consequences, it is low identified regulation. Overall, the findings showed a novel understanding of the structure of the IGD symptoms, and the motivations underlying them. The clinical implications of the findings for assessment and treatment of IGD are discussed. © 2022, The Author(s).
- Authors: Gomez, Rapson , Stavropoulos, Vasileios , Tullett-Prado, Deon , Schivinski, Bruno , Chen, Wai
- Date: 2022
- Type: Text , Journal article
- Relation: BMC Psychiatry Vol. 22, no. 1 (2022), p.
- Full Text:
- Reviewed:
- Description: The study used regularized partial correlation network analysis (EBICglasso) to examine the structure of DSM-5 internet gaming disorder (IGD) symptoms (network 1); and the associations of the IGD symptoms in the network with different types of motivation as defined in the self-determination theory i.e., intrinsic motivation (engaging in an activity for something unrelated to the activity), identified regulation (engaging in the activity because it aligns with one’s values and/or goals), external regulation (engagement in activity being driven by external rewards and/or approval), and amotivation (engaging in an activity without often understanding why) (network 2). Participants were 968 adults from the general community. They completed self-rating questionnaires covering IGD symptoms and different types of motivation. The findings for network 1 showed mostly positive connections between the symptoms within the IGD network. The most central symptom was loss of control, followed by continuation, withdrawal symptoms, and tolerance. In general, these symptoms were more strongly connected with each other than with the rest of the IGD symptoms. The findings for network 2 showed that the different types of motivation were connected differently with the different IGD symptoms. For instance, the likeliest motivation for the preoccupation and escape symptoms is intrinsic motivation, and for negative consequences, it is low identified regulation. Overall, the findings showed a novel understanding of the structure of the IGD symptoms, and the motivations underlying them. The clinical implications of the findings for assessment and treatment of IGD are discussed. © 2022, The Author(s).
Network analyses of Oppositional Defiant Disorder (ODD) symptoms in children
- Gomez, Rapson, Stavropoulos, Vasileios, Gomez, Andre, Brown, Taylor, Watson, Shaun
- Authors: Gomez, Rapson , Stavropoulos, Vasileios , Gomez, Andre , Brown, Taylor , Watson, Shaun
- Date: 2022
- Type: Text , Journal article
- Relation: BMC Psychiatry Vol. 22, no. 1 (2022), p. 263-263
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- Description: Based on parent and teacher ratings of their children, this study used regularized partial correlation network analysis (EBIC glasso) to examine the structure of DSM-5 Oppositional Defiant Disorder (ODD) symptoms. Parent and teachers (N = 934) from the general community in Malaysia completed questionnaires covering DSM-5 ODD symptoms. The most central ODD symptom for parent ratings was anger, followed by argue. For teacher ratings, it was anger, followed by defy. For both parent and teacher ratings, the networks revealed at least medium effect size connections for temper and argue, defy, and argue, blames others, and annoy, and spiteful and angry. Overall, the findings were highly comparable across parent and teacher ratings, and they showed a novel understanding of the structure of the ODD symptoms. The clinical implications of the findings for assessment and treatment of ODD are discussed.
- Authors: Gomez, Rapson , Stavropoulos, Vasileios , Gomez, Andre , Brown, Taylor , Watson, Shaun
- Date: 2022
- Type: Text , Journal article
- Relation: BMC Psychiatry Vol. 22, no. 1 (2022), p. 263-263
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- Description: Based on parent and teacher ratings of their children, this study used regularized partial correlation network analysis (EBIC glasso) to examine the structure of DSM-5 Oppositional Defiant Disorder (ODD) symptoms. Parent and teachers (N = 934) from the general community in Malaysia completed questionnaires covering DSM-5 ODD symptoms. The most central ODD symptom for parent ratings was anger, followed by argue. For teacher ratings, it was anger, followed by defy. For both parent and teacher ratings, the networks revealed at least medium effect size connections for temper and argue, defy, and argue, blames others, and annoy, and spiteful and angry. Overall, the findings were highly comparable across parent and teacher ratings, and they showed a novel understanding of the structure of the ODD symptoms. The clinical implications of the findings for assessment and treatment of ODD are discussed.
Interactions between fecal gut microbiome, enteric pathogens, and energy regulating hormones among acutely malnourished rural Gambian children
- Nabwera, Helen, Espinoza, Josh, Worwui, Archibald, Betts, Modupeh, Bradbury, Richard
- Authors: Nabwera, Helen , Espinoza, Josh , Worwui, Archibald , Betts, Modupeh , Bradbury, Richard
- Date: 2021
- Type: Text , Journal article
- Relation: EBioMedicine Vol. 73, no. (2021), p.
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- Description: Background: The specific roles that gut microbiota, known pathogens, and host energy-regulating hormones play in the pathogenesis of non-edematous severe acute malnutrition (marasmus SAM) and moderate acute malnutrition (MAM) during outpatient nutritional rehabilitation are yet to be explored. Methods: We applied an ensemble of sample-specific (intra- and inter-modality) association networks to gain deeper insights into the pathogenesis of acute malnutrition and its severity among children under 5 years of age in rural Gambia, where marasmus SAM is most prevalent. Findings: Children with marasmus SAM have distinct microbiome characteristics and biologically-relevant multimodal biomarkers not observed among children with moderate acute malnutrition. Marasmus SAM was characterized by lower microbial richness and biomass, significant enrichments in Enterobacteriaceae, altered interactions between specific Enterobacteriaceae and key energy regulating hormones and their receptors. Interpretation: Our findings suggest that marasmus SAM is characterized by the collapse of a complex system with nested interactions and key associations between the gut microbiome, enteric pathogens, and energy regulating hormones. Further exploration of these systems will help inform innovative preventive and therapeutic interventions. Funding: The work was supported by the UK Medical Research Council (MRC; MC-A760-5QX00) and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement; Bill and Melinda Gates Foundation (OPP 1066932) and the National Institute of Medical Research (NIMR), UK. This network analysis was supported by NIH U54GH009824 [CLD] and NSF OCE-1558453 [CLD]. © 2021 The Author(s). **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Richard Bradbury" is provided in this record**
- Authors: Nabwera, Helen , Espinoza, Josh , Worwui, Archibald , Betts, Modupeh , Bradbury, Richard
- Date: 2021
- Type: Text , Journal article
- Relation: EBioMedicine Vol. 73, no. (2021), p.
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- Description: Background: The specific roles that gut microbiota, known pathogens, and host energy-regulating hormones play in the pathogenesis of non-edematous severe acute malnutrition (marasmus SAM) and moderate acute malnutrition (MAM) during outpatient nutritional rehabilitation are yet to be explored. Methods: We applied an ensemble of sample-specific (intra- and inter-modality) association networks to gain deeper insights into the pathogenesis of acute malnutrition and its severity among children under 5 years of age in rural Gambia, where marasmus SAM is most prevalent. Findings: Children with marasmus SAM have distinct microbiome characteristics and biologically-relevant multimodal biomarkers not observed among children with moderate acute malnutrition. Marasmus SAM was characterized by lower microbial richness and biomass, significant enrichments in Enterobacteriaceae, altered interactions between specific Enterobacteriaceae and key energy regulating hormones and their receptors. Interpretation: Our findings suggest that marasmus SAM is characterized by the collapse of a complex system with nested interactions and key associations between the gut microbiome, enteric pathogens, and energy regulating hormones. Further exploration of these systems will help inform innovative preventive and therapeutic interventions. Funding: The work was supported by the UK Medical Research Council (MRC; MC-A760-5QX00) and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement; Bill and Melinda Gates Foundation (OPP 1066932) and the National Institute of Medical Research (NIMR), UK. This network analysis was supported by NIH U54GH009824 [CLD] and NSF OCE-1558453 [CLD]. © 2021 The Author(s). **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Richard Bradbury" is provided in this record**
Big networks : a survey
- Bedru, Hayat, Yu, Shuo, Xiao, Xinru, Zhang, Da, Xia, Feng
- Authors: Bedru, Hayat , Yu, Shuo , Xiao, Xinru , Zhang, Da , Xia, Feng
- Date: 2020
- Type: Text , Journal article , Review
- Relation: Computer Science Review Vol. 37, no. (2020), p.
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- Description: A network is a typical expressive form of representing complex systems in terms of vertices and links, in which the pattern of interactions amongst components of the network is intricate. The network can be static that does not change over time or dynamic that evolves through time. The complication of network analysis is different under the new circumstance of network size explosive increasing. In this paper, we introduce a new network science concept called a big network. A big networks is generally in large-scale with a complicated and higher-order inner structure. This paper proposes a guideline framework that gives an insight into the major topics in the area of network science from the viewpoint of a big network. We first introduce the structural characteristics of big networks from three levels, which are micro-level, meso-level, and macro-level. We then discuss some state-of-the-art advanced topics of big network analysis. Big network models and related approaches, including ranking methods, partition approaches, as well as network embedding algorithms are systematically introduced. Some typical applications in big networks are then reviewed, such as community detection, link prediction, recommendation, etc. Moreover, we also pinpoint some critical open issues that need to be investigated further. © 2020 Elsevier Inc.
- Authors: Bedru, Hayat , Yu, Shuo , Xiao, Xinru , Zhang, Da , Xia, Feng
- Date: 2020
- Type: Text , Journal article , Review
- Relation: Computer Science Review Vol. 37, no. (2020), p.
- Full Text:
- Reviewed:
- Description: A network is a typical expressive form of representing complex systems in terms of vertices and links, in which the pattern of interactions amongst components of the network is intricate. The network can be static that does not change over time or dynamic that evolves through time. The complication of network analysis is different under the new circumstance of network size explosive increasing. In this paper, we introduce a new network science concept called a big network. A big networks is generally in large-scale with a complicated and higher-order inner structure. This paper proposes a guideline framework that gives an insight into the major topics in the area of network science from the viewpoint of a big network. We first introduce the structural characteristics of big networks from three levels, which are micro-level, meso-level, and macro-level. We then discuss some state-of-the-art advanced topics of big network analysis. Big network models and related approaches, including ranking methods, partition approaches, as well as network embedding algorithms are systematically introduced. Some typical applications in big networks are then reviewed, such as community detection, link prediction, recommendation, etc. Moreover, we also pinpoint some critical open issues that need to be investigated further. © 2020 Elsevier Inc.
Capital structure of SMEs : a systematic literature review and bibliometric analysis
- Kumar, Satish, Sureka, Riya, Colombage, Sisira
- Authors: Kumar, Satish , Sureka, Riya , Colombage, Sisira
- Date: 2020
- Type: Text , Journal article
- Relation: Management Review Quarterly Vol. 70, no. 4 (2020), p. 535-565
- Full Text: false
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- Description: Capital structure is the outcome of market conditions, financial decisions taken by the firm, and credit rationing of fund providers. Research on the capital structure of small and medium enterprises (SMEs) has gained momentum in recent years. The present study aims to identify key contributors, key areas, current dynamics, and suggests future research directions in the field of the capital structure of SMEs. This paper adopts a systematic literature review methodology along with bibliometric, network, and content analysis on a sample of 262 studies taken from the Web of Science database to examine the research activities that have taken place on this topic. Most influential papers are identified based on citations and PageRank, along with the most influential authors. The co-citation network is developed to see the intellectual structure of this research area. Applying bibliometric tools, four research clusters have been identified and content analysis performed on the papers identified in the clusters. It is found that the major research focus in this area is around theory testing—mainly, pecking order theory, trade-off theory, and agency theory. Determinants of capital structure, trade credit, corporate governance, and bankruptcy are also the prominent research topics in this field. Also, this study has identified the research gaps and has proposed five actionable research directions for the future. © 2019, Springer Nature Switzerland AG.
Detection of four-node motif in complex networks
- Ning, Zhaolong, Liu, Lei, Yu, Shuo, Xia, Feng
- Authors: Ning, Zhaolong , Liu, Lei , Yu, Shuo , Xia, Feng
- Date: 2018
- Type: Text , Conference proceedings
- Relation: Complex Networks & Their Applications VI; Lyon, France; November 29th-1st December, 2017 p. 453-462
- Full Text: false
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- Description: Complex network analysis has gained research interests in a wide range of fields. Network motif, which is one of the most popular network properties, is a statistically significant network subgraph. In this paper, we propose a fast methodology, called Four-node Motif Detection Algorithm (FMDA), to extract four-node motifs in complex networks. Specifically, we employ a two-way spectral clustering method to cut big networks into small sub-graphs, and then identify motifs by recognition algorithm to reduce the computational complexity. After that, we use three isomorphic four-node motifs to analyze network structure by American Physical Society (APS) data set.
Trophic cascades in 3D: network analysis reveals how apex predators structure ecosystems
- Wallach, Arian, Dekker, Anthony, Lurgi, Miguel, Montoya, Jose, Fordham, Damien, Ritchie, Euan, Fisher, Diana
- Authors: Wallach, Arian , Dekker, Anthony , Lurgi, Miguel , Montoya, Jose , Fordham, Damien , Ritchie, Euan , Fisher, Diana
- Date: 2017
- Type: Text , Journal article
- Relation: Methods in ecology and evolution Vol. 8, no. 1 (2017), p. 135-142
- Full Text: false
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- Description: Summary Trophic cascade theory predicts that apex predators structure ecosystems by regulating mesopredator and herbivore abundance and behaviour. Studies on trophic cascades have typically focused on short linear chains of species interactions. A framework that integrates more realistic and complex interactions is needed to make broader predictions on ecosystem structuring. Network analysis is used to study food webs and other types of species interaction networks. These often comprise large numbers of species but rarely account for multiple interaction types and strengths. Here, we develop an intermediate complexity theoretical framework that allows specification of multiple interaction types and strengths for the study of trophic cascades. This ecological network is designed to suit data typically derived from field‐based studies. The trophic cascade network contains fewer nodes than food webs, but provides semi‐weighted directional links that enable different types of interactions to be included in a single model. We use this trophic cascade network model to explore how an apex predator shapes ecosystem structure in an Australian arid ecosystem. We compared two networks that contrasted in the dominance of an apex predator, the dingo (Canis dingo), using published results ranking the direction and strength of key interactions. Nodes and links interacted dynamically to shape these networks. We examined how changes to an apex predator population affect ecosystem structure through their direct and indirect influences on different components of this ecological community. Under strong apex predator influence, the network structure was denser and more complex, even and top‐down driven and dingo predation and soil commensalism formed denser interactive modules. Under weak apex predator influence (e.g. reflecting predator control), the resulting network structure was frayed, with mesopredator predation and grazing forming modules. Our study demonstrates that networks of intermediate complexity can provide a powerful tool for elucidating potential ecosystem‐wide effects of apex predators and predicting the consequences of management interventions such as predator control. Integrating trophic cascades, with their array of complex interactions, with the three‐dimensional structure of ecological networks, has the potential to reveal ‘ecological architecture’ that neither captures on its own.
Optimal number and placement of network infrastructure in wireless networks
- Authors: Kouhbor, Shahnaz
- Date: 2007
- Type: Text , Thesis , PhD
- Full Text:
- Description: Wireless Local Area Networks (WLANs) have become a major success in telecommunications during the last few years, due to advantages such as mobility, flexibility, and easier maintenance. A device called an access point (AP) acts as a base station in WLAN for connecting a group of users to the network via radio signal. During the planning of such a network an important problem is to determine the optimal number of these devices and their placement/distribution so that coverage, capacity, and physical security are maximised at minimum cost. In this thesis we are using continuous optimisation techniques to optimise the number of APs and their distribution while cost of deployment is reduced and physical security of the network is enhanced. To find the number and placement of APs, we developed a multi-objective functions model based on path losses and power for free space environments. The two functions in the models are combined by using a balancing parameter. Since it is recognised that some of the objectives can be handled one at a time, in another approach, we followed a step-by-step procedure. We start with a novel optimisation model based on path losses for indoor environments including obstacles. Cost of deployment is saved by finding the minimum number of APs ensuring that the path loss at each test point/receiver is below the given maximum path loss. Next, the physical security of the network is enhanced by placing the APs far from places accessible to unauthorised users to reduce the risk of intrusion into the network. This is achieved in the framework of the model by introducing potential unauthorised users in unauthorised areas for whom coverage is minimised. Due to the presence of obstacles in indoor buildings, the path loss function is discontinuous. Therefore, the objective functions are very complicated and most of the existing optimisation algorithms cannot be applied to solve the problem. We use a global optimisation algorithm that is not used by other researchers to solve the same problem. To validate the accuracy of the optimisation model and performance of the numerical methods, we run tests on several indoor buildings and use wide range of WLAN parameters. The results demonstrate the quality of our model and algorithm. Based on the proposed model and algorithm, we developed a software to assist the network designers in planning wireless LANs.
- Description: Doctor of Philosophy
- Authors: Kouhbor, Shahnaz
- Date: 2007
- Type: Text , Thesis , PhD
- Full Text:
- Description: Wireless Local Area Networks (WLANs) have become a major success in telecommunications during the last few years, due to advantages such as mobility, flexibility, and easier maintenance. A device called an access point (AP) acts as a base station in WLAN for connecting a group of users to the network via radio signal. During the planning of such a network an important problem is to determine the optimal number of these devices and their placement/distribution so that coverage, capacity, and physical security are maximised at minimum cost. In this thesis we are using continuous optimisation techniques to optimise the number of APs and their distribution while cost of deployment is reduced and physical security of the network is enhanced. To find the number and placement of APs, we developed a multi-objective functions model based on path losses and power for free space environments. The two functions in the models are combined by using a balancing parameter. Since it is recognised that some of the objectives can be handled one at a time, in another approach, we followed a step-by-step procedure. We start with a novel optimisation model based on path losses for indoor environments including obstacles. Cost of deployment is saved by finding the minimum number of APs ensuring that the path loss at each test point/receiver is below the given maximum path loss. Next, the physical security of the network is enhanced by placing the APs far from places accessible to unauthorised users to reduce the risk of intrusion into the network. This is achieved in the framework of the model by introducing potential unauthorised users in unauthorised areas for whom coverage is minimised. Due to the presence of obstacles in indoor buildings, the path loss function is discontinuous. Therefore, the objective functions are very complicated and most of the existing optimisation algorithms cannot be applied to solve the problem. We use a global optimisation algorithm that is not used by other researchers to solve the same problem. To validate the accuracy of the optimisation model and performance of the numerical methods, we run tests on several indoor buildings and use wide range of WLAN parameters. The results demonstrate the quality of our model and algorithm. Based on the proposed model and algorithm, we developed a software to assist the network designers in planning wireless LANs.
- Description: Doctor of Philosophy
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