Thomas M Kessler
Full Text Available BACKGROUND: Overactive bladder (OAB affects the lives of millions of people worldwide and antimuscarinics are the pharmacological treatment of choice. Meta-analyses of all currently used antimuscarinics for treating OAB found similar efficacy, making the choice dependent on their adverse event profiles. However, conventional meta-analyses often fail to quantify and compare adverse events across different drugs, dosages, formulations, and routes of administration. In addition, the assessment of the broad variety of adverse events is dissatisfying. Our aim was to compare adverse events of antimuscarinics using a network meta-analytic approach that overcomes shortcomings of conventional analyses. METHODS: Cochrane Incontinence Group Specialized Trials Register, previous systematic reviews, conference abstracts, book chapters, and reference lists of relevant articles were searched. Eligible studies included randomized controlled trials comparing at least one antimuscarinic for treating OAB with placebo or with another antimuscarinic, and adverse events as outcome measures. Two authors independently extracted data. A network meta-analytic approach was applied allowing for joint assessment of all adverse events of all currently used antimuscarinics while fully maintaining randomization. RESULTS: 69 trials enrolling 26'229 patients were included. Similar overall adverse event profiles were found for darifenacin, fesoterodine, transdermal oxybutynin, propiverine, solifenacin, tolterodine, and trospium chloride but not for oxybutynin orally administered when currently used starting dosages were compared. CONCLUSIONS: The proposed generally applicable transparent network meta-analytic approach summarizes adverse events in an easy to grasp way allowing straightforward benchmarking of antimuscarinics for treating OAB in clinical practice. Most currently used antimuscarinics seem to be equivalent first choice drugs to start the treatment of OAB except for
Full Text Available Schwartz' theory of human values has found widespread interest in the social sciences. A central part of the theory is that the 10 proposed basic values (i.e., achievement, power, self-direction, hedonism, stimulation, benevolence, universalism, conformity, security, and tradition are arranged in a circular structure. The present study applies a meta-analytical structural equation modelling approach to test the circular structure. The model tested was the quasi-circumplex model, which is considered the most appropriate representation of the circular structure. Moreover, the study explores how far the circular structure varies with the used samples and methodological characteristics of the studies. The meta-analysis comprised 318 matrices with the correlations among the 10 values gathered from 88 studies and the European Social Survey (overall n = 251,239. To reduce heterogeneity across the matrices, cluster analysis was used to sort the matrices into eight clusters with a similar correlation profile and tested the circular structure in each cluster. The results showed that three clusters demonstrated a good fit with the data and an adequate match to the theoretically proposed structure. The clusters' cultural and methodological profiles indicate potential moderators of the circular structure which should be considered in future research.
Odani, Motoi; Fukimbara, Satoru; Sato, Tosiya
Meta-analyses are frequently performed on adverse event data and are primarily used for improving statistical power to detect safety signals. However, in the evaluation of drug safety for New Drug Applications, simple pooling of adverse event data from multiple clinical trials is still commonly used. We sought to propose a new Bayesian hierarchical meta-analytic approach based on consideration of a hierarchical structure of reported individual adverse event data from multiple randomized clinical trials. To develop our meta-analysis model, we extended an existing three-stage Bayesian hierarchical model by including an additional stage of the clinical trial level in the hierarchical model; this generated a four-stage Bayesian hierarchical model. We applied the proposed Bayesian meta-analysis models to published adverse event data from three premarketing randomized clinical trials of tadalafil and to a simulation study motivated by the case example to evaluate the characteristics of three alternative models. Comparison of the results from the Bayesian meta-analysis model with those from Fisher's exact test after simple pooling showed that 6 out of 10 adverse events were the same within a top 10 ranking of individual adverse events with regard to association with treatment. However, more individual adverse events were detected in the Bayesian meta-analysis model than in Fisher's exact test under the body system "Musculoskeletal and connective tissue disorders." Moreover, comparison of the overall trend of estimates between the Bayesian model and the standard approach (odds ratios after simple pooling methods) revealed that the posterior median odds ratios for the Bayesian model for most adverse events shrank toward values for no association. Based on the simulation results, the Bayesian meta-analysis model could balance the false detection rate and power to a better extent than Fisher's exact test. For example, when the threshold value of the posterior probability for
Schilbach, Leonhard; Müller, Veronika I.; Hoffstaedter, Felix; Clos, Mareike; Goya-Maldonado, Roberto; Gruber, Oliver; Eickhoff, Simon B.
Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a close link between affective and introspective processes relevant for social interactions and alterations thereof in states of depression, we used a meta-analytically informed network analysis to inve...
Van Landuyt, K L; Nawrot, Tim; Geebelen, B; De Munck, J; Snauwaert, J; Yoshihara, K; Scheers, Hans; Godderis, Lode; Hoet, P; Van Meerbeek, B
Resin-based dental materials are not inert in the oral environment, and may release components, initially due to incomplete polymerization, and later due to degradation. Since there are concerns regarding potential toxicity, more precise knowledge of the actual quantity of released eluates is necessary. However, due to a great variety in analytical methodology employed in different studies and in the presentation of the results, it is still unclear to which quantities of components a patient may be exposed. The objective of this meta-analytical study was to review the literature on the short- and long-term release of components from resin-based dental materials, and to determine how much (order of magnitude) of those components may leach out in the oral cavity. Out of an initial set of 71 studies, 22 were included. In spite of the large statistical incertitude due to the great variety in methodology and lack of complete information (detection limits were seldom mentioned), a meta-analytical mean for the evaluated eluates was calculated. To relate the amount of potentially released material components with the size of restorations, the mean size of standard composite restorations was estimated using a 3D graphical program. While the release of monomers was analyzed in many studies, that of additives, such as initiators, inhibitors and stabilizers, was seldom investigated. Significantly more components were found to be released in organic than in water-based media. Resin-based dental materials might account for the total burden of orally ingested bisphenol A, but they may release even higher amounts of monomers, such as HEMA, TEGDMA, BisGMA and UDMA. Compared to these monomers, similar or even higher amounts of additives may elute, even though composites generally only contain very small amounts of additives. A positive correlation was found between the total quantity of released eluates and the volume of extraction solution. There is a clear need for more accurate
Sarah R Braun
Full Text Available OBJECTIVE: Despite numerous investigations, the question whether all bona fide treatments of depression are equally efficacious in adults has not been sufficiently answered. METHOD: We applied two different meta-analytical techniques (conventional meta-analysis and mixed treatment comparisons. Overall, 53 studies with 3,965 patients, which directly compared two or more bona fide psychotherapies in a randomized trial, were included. Meta-analyses were conducted regarding five different types of outcome measures. Additionally, the influence of possible moderators was examined. RESULTS: Direct comparisons of cognitive behavior therapy, behavior activation therapy, psychodynamic therapy, interpersonal therapy, and supportive therapies versus all other respective treatments indicated that at the end of treatment all treatments but supportive therapies were equally efficacious whereas there was some evidence that supportive therapies were somewhat less efficacious than all other treatments according to patient self-ratings and clinical significance. At follow-up no significant differences were present. Age, gender, comorbid mental disorders, and length of therapy session were found to moderate efficacy. Cognitive behavior therapy was superior in studies where therapy sessions lasted 90 minutes or longer, behavior activation therapy was more efficacious when therapy sessions lasted less than 90 minutes. Mixed treatment comparisons indicated no statistically significant differences in treatment efficacy but some interesting trends. CONCLUSIONS: This study suggests that there might be differential effects of bona fide psychotherapies which should be examined in detail.
Dore, Marina Pereira; Farias, Cássia; Hamacher, Cláudia
The exploration and production of oil and gas reserves often result to drill cutting accumulations on the seafloor adjacent to drill locations. In this study, the detection of drilling influence on marine sediments was performed by meta-analytical comparison between data from pre- and post-drilling surveys undertaken in offshore Campos Basin, southeast of Brazil. Besides this overall appraisal on the geochemical variables, a multivariate assessment, considering only the post-drilling data, was performed. Among the variables, fines content, carbonates, total organic carbon, barium, chromium, copper, iron, manganese, nickel, lead, vanadium, zinc, and total petroleum hydrocarbons, only barium, copper, and hydrocarbons were related to drilling impacts. In relation to the point of discharge, relative elevated levels in the post-drilling campaigns were observed preferentially up to 500 m in the northeast and southwest directions, associated to the Brazil Current-predominant direction. Other distributed concentrations in the surroundings seem to indicate the dilution and dispersion of drilling waste promoted by meteoceanographic factors.
It remains unclear whether and to what extent the default network subregions involved in episodic memory (EM) and semantic memory (SM) processes overlap or are separated from one another. This study addresses this issue through a controlled meta-analysis of functional neuroimaging studies involving healthy participants. Various EM and SM task paradigms differ widely in the extent of default network involvement. Therefore, the issue at hand cannot be properly addressed without some control for this factor. In this regard, this study employs a two-stage analysis: a preliminary meta-analysis to select EM and SM task paradigms that recruit relatively extensive default network regions and a main analysis to compare the selected task paradigms. Based on a within-EM comparison, the default network contributed more to recollection/familiarity effects than to old/new effects, and based on a within-SM comparison, it contributed more to word/pseudoword effects than to semantic/phonological effects. According to a direct comparison of recollection/familiarity and word/pseudoword effects, each involving a range of default network regions, there were more overlaps than separations in default network subregions involved in these two effects. More specifically, overlaps included the bilateral posterior cingulate/retrosplenial cortex, left inferior parietal lobule, and left anteromedial prefrontal regions, whereas separations included only the hippocampal formation and the parahippocampal cortex region, which was unique to recollection/familiarity effects. These results indicate that EM and SM retrieval processes involving strong memory signals recruit extensive and largely overlapping default network regions and differ mainly in distinct contributions of hippocampus and parahippocampal regions to EM retrieval. Copyright © 2015 Elsevier Ltd. All rights reserved.
Schilbach, Leonhard; Müller, Veronika I; Hoffstaedter, Felix; Clos, Mareike; Goya-Maldonado, Roberto; Gruber, Oliver; Eickhoff, Simon B
Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a close link between affective and introspective processes relevant for social interactions and alterations thereof in states of depression, we used a meta-analytically informed network analysis to investigate resting-state functional connectivity in an introspective socio-affective (ISA) network in individuals with and without depression. Results of our analysis demonstrate significant differences between the groups with depressed individuals showing hyperconnectivity of the ISA network. These findings demonstrate that neurofunctional alterations exist in individuals with depression in a neural network relevant for introspection and socio-affective processing, which may contribute to the interpersonal difficulties that are linked to depressive symptomatology.
Full Text Available Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a close link between affective and introspective processes relevant for social interactions and alterations thereof in states of depression, we used a meta-analytically informed network analysis to investigate resting-state functional connectivity in an introspective socio-affective (ISA network in individuals with and without depression. Results of our analysis demonstrate significant differences between the groups with depressed individuals showing hyperconnectivity of the ISA network. These findings demonstrate that neurofunctional alterations exist in individuals with depression in a neural network relevant for introspection and socio-affective processing, which may contribute to the interpersonal difficulties that are linked to depressive symptomatology.
The increasing popularity of social networking sites (SNSs) has drawn scholarly attention in recent years, and a large amount of efforts have been made in applying SNSs to health behavior change interventions. However, these interventions showed mixed results, with a large variance of effect sizes in Cohen's d ranging from -1.17 to 1.28. To provide a better understanding of SNS-based interventions' effectiveness, a meta-analysis of 21 studies examining the effects of health interventions using SNS was conducted. Results indicated that health behavior change interventions using SNS are effective in general, but the effects were moderated by health topic, methodological features, and participant features. Theoretical and practical implications of findings are discussed.
Lochbaum, Marc; Jean-Noel, Javan; Pinar, Colleen; Gilson, Todd
Purpose: The purpose of this quantitative review was to summarize the state of Elliot's Hierarchical Model of Approach and Avoidance Motivation, specifically the antecedents of the 2 × 2 achievement goals in the sport, physical activity, and physical education literature. In addition, the intercorrelations amongst the 2 × 2 goals were also examined. Methods: A systematic review of the literature was conducted. Meta-analytic procedures were used with the mean weighted sample correlation (rw...
Prato, Carlo Giacomo
objective judgments for effective route choice set generation. Initially, path generation techniques are implemented within a synthetic network to generate possible subjective choice sets considered by travelers. Next, “true model estimates” and “postulated predicted routes” are assumed from the simulation...... of a route choice model. Then, objective choice sets are applied for model estimation and results are compared to the “true model estimates”. Last, predictions from the simulation of models estimated with objective choice sets are compared to the “postulated predicted routes”. Meta-analysis allows...
Giannì, Costanza; Prosperini, Luca; Jonsdottir, Johanna; Cattaneo, Davide
To determine whether there are demographic, clinical, and instrumental variables useful to detect fall status of patients with multiple sclerosis. PubMed and the Cochrane Library. Eligible studies were identified by two independent investigators. Only studies having a clear distinction between fallers and non-fallers were included and meta-analysed. Odds ratios (ORs) and standard mean differences (SMDs) were calculated and pooled using fixed effect models. Among 115 screened articles, 15 fulfilled criteria for meta-analyses, with a total of 2425 patients included. Proportion of fallers may vary from 30% to 63% in a time frame from 1 to 12 months. No significant publication bias was found, even though 12/15 studies relied on retrospective reports of falls, thus introducing recall biases. Risk factors for falls varied across studies, owing to heterogeneity of populations included and clinical instruments used. The meta-analytic approach found that, compared with non-fallers, fallers had longer disease duration (SMD = 0.14, p = 0.02), progressive course of disease (OR = 2.02, p < 0.0001), assistive device for walking (OR = 3.16, p < 0.0001), greater overall disability level (SMD = 0.74, p < 0.0001), slower walking speed (SMD = 0.45, p = 0.0005), and worse performances in balance tests (Berg Balance Scale: SMD = -0.48, p = 0.002; Timed up-and-go test, SMD = 0.31, p = 0.04), and force-platform measures (postural sway) with eyes opened (SMD = 0.71, p = 0.006) and closed (SMD = 0.83, p = 0.01), respectively. Elucidations regarding risk factors for accidental falls in patients with multiple sclerosis (PwMs) are provided here, with worse disability score, progressive course, use of walking aid, and poorer performances in static and dynamic balance tests strongly associated with fall status. © The Author(s) 2014.
Salsman, John M.; Pustejovsky, James E.; Jim, Heather S.L.; Munoz, Alexis R.; Merluzzi, Thomas V.; George, Login; Park, Crystal L.; Danhauer, Suzanne C.; Sherman, Allen C.; Snyder, Mallory A.; Fitchett, George
Purpose Religion and spirituality (R/S) are patient-centered factors and often resources for managing the emotional sequelae of the cancer experience. Studies investigating the relationship between R/S (e.g., beliefs, experiences, coping) and mental health (e.g., depression, anxiety, well-being) in cancer have used very heterogeneous measures, with correspondingly inconsistent results. A meaningful synthesis of these findings has been lacking; thus, the purpose of this study was to conduct a meta-analysis of the research on R/S and mental health. Methods Four electronic databases were systematically reviewed and 2,073 abstracts met initial selection criteria. Reviewer pairs applied standardized coding schemes to extract correlational indices of the relationship between R/S and mental health. A total of 617 effect sizes from 148 eligible studies were synthesized using meta-analytic generalized estimating equations; subgroup analyses were performed to examine moderators of effects. Results The estimated mean correlation (Fisher z) was 0.19 (95% CI 0.16–0.23), which varied as a function of R/S dimension: affective, z=0.38 (95% CI 0.33-0.43); behavioral, z=0.03 (95% CI -0.02-0.08); cognitive, z=0.10 (95% CI 0.06-0.14); and ‘other,’ z=0.08 (95% CI 0.03-0.13). Aggregate, study-level demographic and clinical factors were not predictive of the relationship between R/S and mental health. There was little indication of publication or reporting biases. Conclusions The relationship between R/S and mental health is generally a positive one. The strength of that relationship is modest and varies as a function of R/S dimensions and mental health domains assessed. Identification of optimal R/S measures and more sophisticated methodological approaches are needed to advance research. PMID:26258536
Salsman, John M; Pustejovsky, James E; Jim, Heather S L; Munoz, Alexis R; Merluzzi, Thomas V; George, Login; Park, Crystal L; Danhauer, Suzanne C; Sherman, Allen C; Snyder, Mallory A; Fitchett, George
Religion and spirituality (R/S) are patient-centered factors and often are resources for managing the emotional sequelae of the cancer experience. Studies investigating the correlation between R/S (eg, beliefs, experiences, coping) and mental health (eg, depression, anxiety, well being) in cancer have used very heterogeneous measures and have produced correspondingly inconsistent results. A meaningful synthesis of these findings has been lacking; thus, the objective of this review was to conduct a meta-analysis of the research on R/S and mental health. Four electronic databases were systematically reviewed, and 2073 abstracts met initial selection criteria. Reviewer pairs applied standardized coding schemes to extract indices of the correlation between R/S and mental health. In total, 617 effect sizes from 148 eligible studies were synthesized using meta-analytic generalized estimating equations, and subgroup analyses were performed to examine moderators of effects. The estimated mean correlation (Fisher z) was 0.19 (95% confidence interval [CI], 0.16-0.23), which varied as a function of R/S dimensions: affective R/S (z = 0.38; 95% CI, 0.33-0.43), behavioral R/S (z = 0.03; 95% CI, -0.02-0.08), cognitive R/S (z = 0.10; 95% CI, 0.06-0.14), and 'other' R/S (z = 0.08; 95% CI, 0.03-0.13). Aggregate, study-level demographic and clinical factors were not predictive of the relation between R/S and mental health. There was little indication of publication or reporting biases. The correlation between R/S and mental health generally was positive. The strength of that correlation was modest and varied as a function of the R/S dimensions and mental health domains assessed. The identification of optimal R/S measures and more sophisticated methodological approaches are needed to advance research. © 2015 American Cancer Society.
Daniel D. Goering
Full Text Available The distinctiveness between work engagement and burnout has long been an issue of debate. To address this issue, we use a recently developed technique by Yu et al. (2016 to specify and test a meta-analytic structural equation model (MASEM which accounts for the non-independence between engagement and burnout as well as the simultaneous effects of all relationships in our model, based on job demands-resources (JD-R theory. We also estimate the degree of variability of these relationships across subpopulations. We report the findings as a distribution of effect size estimates—each estimate in the distribution representing the true effect size for a potential subpopulation—around the mean average estimate for each relationship in the model. Based on the findings, we conclude that overall burnout and engagement display empirically distinct relationships within the JD-R model (i.e., they are not antipodal, particularly in terms of antecedents. Perhaps most interestingly, rather than a polar opposite pattern of relationships, challenge demands have a similarly positive relationship to both burnout (ß = 0.35, SD = 0.10 and engagement (ß = 0.35, SD = 0.08, suggesting that challenge demands simultaneously lead—in equal force—to both engagement and burnout. In addition, the distributions of effect sizes are nearly identical for both relationships, indicating that this holds true for nearly all subpopulations. As expected, hindrance demands have a positive relationship with burnout (ß = 0.31, SD = 0.10 and have a relatively weak, negative relationship on average to engagement (ß = −0.07, SD = 0.07; work resources have a negative relationship with burnout (ß = −0.15, SD = 0.06 and are positively related to engagement, but in absolute terms they are a stronger predictor of engagement (ß = 0.33, SD = 0.05. In terms of outcomes, burnout and engagement predict a variety of behavioral and attitudinal outcomes
Sundaram, Neisha; Schaetti, Christian; Merten, Sonja; Schindler, Christian; Ali, Said M; Nyambedha, Erick O; Lapika, Bruno; Chaignat, Claire-Lise; Hutubessy, Raymond; Weiss, Mitchell G
Controlling cholera remains a significant challenge in Sub-Saharan Africa. In areas where access to safe water and sanitation are limited, oral cholera vaccine (OCV) can save lives. Establishment of a global stockpile for OCV reflects increasing priority for use of cholera vaccines in endemic settings. Community acceptance of vaccines, however, is critical and sociocultural features of acceptance require attention for effective implementation. This study identifies and compares sociocultural determinants of anticipated OCV acceptance across populations in Southeastern Democratic Republic of Congo, Western Kenya and Zanzibar. Cross-sectional studies were conducted using similar but locally-adapted semistructured interviews among 1095 respondents in three African settings. Logistic regression models identified sociocultural determinants of OCV acceptance from these studies in endemic areas of Southeastern Democratic Republic of Congo (SE-DRC), Western Kenya (W-Kenya) and Zanzibar. Meta-analytic techniques highlighted common and distinctive determinants in the three settings. Anticipated OCV acceptance was high in all settings. More than 93% of community respondents overall indicated interest in a no-cost vaccine. Higher anticipated acceptance was observed in areas with less access to public health facilities. In all settings awareness of cholera prevention methods (safe food consumption and garbage disposal) and relating ingestion to cholera causation were associated with greater acceptance. Higher age, larger households, lack of education, social vulnerability and knowledge of oral rehydration solution for self-treatment were negatively associated with anticipated OCV acceptance. Setting-specific determinants of acceptance included reporting a reliable income (W-Kenya and Zanzibar, not SE-DRC). In SE-DRC, intention to purchase an OCV appeared unrelated to ability to pay. Rural residents were less likely than urban counterparts to accept an OCV in W-Kenya, but more
Zhu, Chen; Sun, Xiaoqi; So, Suzanne Ho-Wai
Belief inflexibility has been suggested to maintain delusions. Different measures of assessing belief inflexibility have been developed, and it remains unclear whether patients with delusions display belief inflexibility similarly across measures. As delusions consist of multiple dimensions, the aim of this meta-analytic review was to examine how belief inflexibility is related to different aspects of delusions (conviction, distress, and preoccupation) and to compare these associations between interview-based and task-based measures of belief inflexibility. We conducted a systematic database search (PsycINFO, PsycARTICLES, PubMed, and MEDLINE) and identified relevant articles using the following search items: belief*, delusion*, or overvalued idea*; psychosis or schizo*; flexib*, inflexib*, change, revision, or update. Meta-analyses were conducted for each dimension of delusions and were reported according to the PRISMA guidelines. A total of 16 studies, with a total sample of 1,065, were included in the analysis. Belief inflexibility was associated with global severity of delusions (Hedges' g = 0.452, p belief inflexibility (conviction: Hedges' g = 0.678, p belief inflexibility and overall severity of delusions. Belief inflexibility, across measures, was robustly associated with delusions, with a particularly strong association for delusional conviction. Our results carried implications for process-based interventions for delusions. Positive clinical implications Belief inflexibility is consistently associated with the maintenance of delusions. Assessing belief inflexibility in routine clinical practice will inform psychological interventions for patients with persistent delusions. Interview- and task-based measures of belief inflexibility may be used complementarily to facilitate our understanding of this reasoning bias. Aetiological factors may be more closely associated with some aspects of delusions than the others. In line with a multidimensional view
Lindquist, Kristen A.; Wager, Tor D.; Kober, Hedy; Bliss-Moreau, Eliza; Barrett, Lisa Feldman
Researchers have wondered how the brain creates emotions since the early days of psychological science. With a surge of studies in affective neuroscience in recent decades, scientists are poised to answer this question. In this article, we present a meta-analytic summary of the human neuroimaging literature on emotion. We compare the locationist approach (i.e., the hypothesis that discrete emotion categories consistently and specifically correspond to distinct brain regions) with the psychological constructionist approach (i.e., the hypothesis that discrete emotion categories are constructed of more general brain networks not specific to those categories) to better understand the brain basis of emotion. We review both locationist and psychological constructionist hypotheses of brain–emotion correspondence and report meta-analytic findings bearing on these hypotheses. Overall, we found little evidence that discrete emotion categories can be consistently and specifically localized to distinct brain regions. Instead, we found evidence that is consistent with a psychological constructionist approach to the mind: a set of interacting brain regions commonly involved in basic psychological operations of both an emotional and non-emotional nature are active during emotion experience and perception across a range of discrete emotion categories. PMID:22617651
Lindquist, Kristen A; Wager, Tor D; Kober, Hedy; Bliss-Moreau, Eliza; Barrett, Lisa Feldman
Researchers have wondered how the brain creates emotions since the early days of psychological science. With a surge of studies in affective neuroscience in recent decades, scientists are poised to answer this question. In this target article, we present a meta-analytic summary of the neuroimaging literature on human emotion. We compare the locationist approach (i.e., the hypothesis that discrete emotion categories consistently and specifically correspond to distinct brain regions) with the psychological constructionist approach (i.e., the hypothesis that discrete emotion categories are constructed of more general brain networks not specific to those categories) to better understand the brain basis of emotion. We review both locationist and psychological constructionist hypotheses of brain-emotion correspondence and report meta-analytic findings bearing on these hypotheses. Overall, we found little evidence that discrete emotion categories can be consistently and specifically localized to distinct brain regions. Instead, we found evidence that is consistent with a psychological constructionist approach to the mind: A set of interacting brain regions commonly involved in basic psychological operations of both an emotional and non-emotional nature are active during emotion experience and perception across a range of discrete emotion categories.
Todd, E Michelle; Watts, Logan L; Mulhearn, Tyler J; Torrence, Brett S; Turner, Megan R; Connelly, Shane; Mumford, Michael D
Despite the growing body of literature on training in the responsible conduct of research, few studies have examined the effectiveness of delivery formats used in ethics courses (i.e., face-to-face, online, hybrid). The present effort sought to address this gap in the literature through a meta-analytic review of 66 empirical studies, representing 106 ethics courses and 10,069 participants. The frequency and effectiveness of 67 instructional and process-based content areas were also assessed for each delivery format. Process-based contents were best delivered face-to-face, whereas contents delivered online were most effective when restricted to compliance-based instructional contents. Overall, hybrid courses were found to be most effective, suggesting that ethics courses are best delivered using a blend of formats and content areas. Implications and recommendations for future development of ethics education courses in the sciences are discussed.
Full Text Available Previous research has indicated that exposure to traditional media (i.e., television, film, and print predicts the likelihood of internalization of a thin ideal; however, the relationship between exposure to internet-based social media on internalization of this ideal remains less understood. Social media differ from traditional forms of media by allowing users to create and upload their own content that is then subject to feedback from other users. This meta-analysis examined the association linking the use of social networking sites (SNSs and the internalization of a thin ideal in females. Systematic searches were performed in the databases: PsychINFO, PubMed, Web of Science, Communication and Mass Media Complete, and ProQuest Dissertations and Theses Global. Six studies were included in the meta-analysis that yielded 10 independent effect sizes and a total of 1,829 female participants ranging in age from 10 to 46 years. We found a positive association between extent of use of SNSs and extent of internalization of a thin ideal with a small to moderate effect size (r = 0.18. The positive effect indicated that more use of SNSs was associated with significantly higher internalization of a thin ideal. A comparison was also made between study outcomes measuring broad use of SNSs and outcomes measuring SNS use solely as a function of specific appearance-related features (e.g., posting or viewing photographs. The use of appearance-related features had a stronger relationship with the internalization of a thin ideal than broad use of SNSs. The finding suggests that the ability to interact with appearance-related features online and be an active participant in media creation is associated with body image disturbance. Future research should aim to explore the way SNS users interact with the media posted online and the relationship linking the use of specific appearance features and body image disturbance.
Mingoia, John; Hutchinson, Amanda D; Wilson, Carlene; Gleaves, David H
Previous research has indicated that exposure to traditional media (i.e., television, film, and print) predicts the likelihood of internalization of a thin ideal; however, the relationship between exposure to internet-based social media on internalization of this ideal remains less understood. Social media differ from traditional forms of media by allowing users to create and upload their own content that is then subject to feedback from other users. This meta-analysis examined the association linking the use of social networking sites (SNSs) and the internalization of a thin ideal in females. Systematic searches were performed in the databases: PsychINFO, PubMed, Web of Science, Communication and Mass Media Complete, and ProQuest Dissertations and Theses Global. Six studies were included in the meta-analysis that yielded 10 independent effect sizes and a total of 1,829 female participants ranging in age from 10 to 46 years. We found a positive association between extent of use of SNSs and extent of internalization of a thin ideal with a small to moderate effect size ( r = 0.18). The positive effect indicated that more use of SNSs was associated with significantly higher internalization of a thin ideal. A comparison was also made between study outcomes measuring broad use of SNSs and outcomes measuring SNS use solely as a function of specific appearance-related features (e.g., posting or viewing photographs). The use of appearance-related features had a stronger relationship with the internalization of a thin ideal than broad use of SNSs. The finding suggests that the ability to interact with appearance-related features online and be an active participant in media creation is associated with body image disturbance. Future research should aim to explore the way SNS users interact with the media posted online and the relationship linking the use of specific appearance features and body image disturbance.
Full Text Available Applying a multilevel approach to meta-analysis is a strong method for dealing with dependency of effect sizes. However, this method is relatively unknown among researchers and, to date, has not been widely used in meta-analytic research. Therefore, the purpose of this tutorial was to show how a three-level random effects model can be applied to meta-analytic models in R using the rma.mv function of the metafor package. This application is illustrated by taking the reader through a step-by-step guide to the multilevel analyses comprising the steps of (1 organizing a data file; (2 setting up the R environment; (3 calculating an overall effect; (4 examining heterogeneity of within-study variance and between-study variance; (5 performing categorical and continuous moderator analyses; and (6 examining a multiple moderator model. By example, the authors demonstrate how the multilevel approach can be applied to meta-analytically examining the association between mental health disorders of juveniles and juvenile offender recidivism. In our opinion, the rma.mv function of the metafor package provides an easy and flexible way of applying a multi-level structure to meta-analytic models in R. Further, the multilevel meta-analytic models can be easily extended so that the potential moderating influence of variables can be examined.
Conclusion: Future research is encouraged to grow and enrich the understanding of achievement goals within Elliot's complete Hierarchical Model of Approach and Avoidance Motivation to include both antecedents and outcomes simultaneously to improve upon the understanding of achievement motivation in sport, exercise, and physical activity settings.
Van Overwalle, Frank; D'aes, Tine; Mariën, Peter
This meta-analytic connectivity modeling (MACM) study explores the functional connectivity of the cerebellum with the cerebrum in social cognitive processes. In a recent meta-analysis, Van Overwalle, Baetens, Mariën, and Vandekerckhove (2014) documented that the cerebellum is implicated in social processes of "body" reading (mirroring; e.g., understanding other persons' intentions from observing their movements) and "mind" reading (mentalizing, e.g., inferring other persons' beliefs, intentions or personality traits, reconstructing persons' past, future, or hypothetical events). In a recent functional connectivity study, Buckner et al. (2011) offered a novel parcellation of cerebellar topography that substantially overlaps with the cerebellar meta-analytic findings of Van Overwalle et al. (2014). This overlap suggests that the involvement of the cerebellum in social reasoning depends on its functional connectivity with the cerebrum. To test this hypothesis, we explored the meta-analytic co-activations as indices of functional connectivity between the cerebellum and the cerebrum during social cognition. The MACM results confirm substantial and distinct connectivity with respect to the functions of (a) action understanding ("body" reading) and (b) mentalizing ("mind" reading). The consistent and strong connectivity findings of this analysis suggest that cerebellar activity during social judgments reflects distinct mirroring and mentalizing functionality, and that these cerebellar functions are connected with corresponding functional networks in the cerebrum. © 2015 Wiley Periodicals, Inc.
Cortese, Samuele; Castellanos, F Xavier; Eickhoff, Claudia R; D'Acunto, Giulia; Masi, Gabriele; Fox, Peter T; Laird, Angela R; Eickhoff, Simon B
Task-based functional magnetic resonance imaging (fMRI) studies of adult attention-deficit/hyperactivity disorder (ADHD) have revealed various ADHD-related dysfunctional brain regions, with heterogeneous findings across studies. Here, we used novel meta-analytic data-driven approaches to characterize the function and connectivity profile of ADHD-related dysfunctional regions consistently detected across studies. We first conducted an activation likelihood estimation meta-analysis of 24 task-based fMRI studies in adults with ADHD. Each ADHD-related dysfunctional region resulting from the activation likelihood estimation meta-analysis was then analyzed using functional decoding based on ~7500 fMRI experiments in the BrainMap database. This approach allows mapping brain regions to functions not necessarily tested in individual studies, thus suggesting possible novel functions for those regions. Additionally, ADHD-related dysfunctional regions were clustered based on their functional coactivation profiles across all the experiments stored in BrainMap (meta-analytic connectivity modeling). ADHD-related hypoactivation was found in the left putamen, left inferior frontal gyrus (pars opercularis), left temporal pole, and right caudate. Functional decoding mapped the left putamen to cognitive aspects of music perception/reproduction and the left temporal lobe to language semantics; both these regions clustered together on the basis of their meta-analytic functional connectivity. Left inferior gyrus mapped to executive function tasks; right caudate mapped to both executive function tasks and music-related processes. Our study provides meta-analytic support to the hypothesis that, in addition to well-known deficits in typical executive functions, impairment in processes related to music perception/reproduction and language semantics may be involved in the pathophysiology of adult ADHD. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights
Chan, Darius K-S.; Lam, Chun Bun; Chow, Suk Yee; Cheung, Shu Fai
This study was designed to examine the job-related, psychological, and physical outcomes of sexual harassment in the workplace. Using a meta-analytic approach, we analyzed findings from 49 primary studies, with a total sample size of 89,382, to obtain estimates of the population mean effect size of the association between sexual harassment and…
Savelsbergh, E.R.|info:eu-repo/dai/nl/17345853X; Prins, G.T.|info:eu-repo/dai/nl/304847208; Rietbergen, C.|info:eu-repo/dai/nl/322847796; Fechner, S.|info:eu-repo/dai/nl/370531671; Vaessen, B.E.|info:eu-repo/dai/nl/369415361; Draijer, J.M.|info:eu-repo/dai/nl/412435802; Bakker, A.|info:eu-repo/dai/nl/272605778
Many teaching approaches have been tried to improve student attitudes and achievement in science and mathematics education. Achievement effects have been synthesized, but a systematic overview of attitude effects is missing. This study provides a meta analytic review based on 56 publications
Polanin, Joshua R.; Pigott, Terri D.
Meta-analysis multiplicity, the concept of conducting multiple tests of statistical significance within one review, is an underdeveloped literature. We address this issue by considering how Type I errors can impact meta-analytic results, suggest how statistical power may be affected through the use of multiplicity corrections, and propose how…
Follmer, D. Jake
This article presents a meta-analytic review of the relation between executive function and reading comprehension. Results (N = 6,673) supported a moderate positive association between executive function and reading comprehension (r = 0.36). Moderator analyses suggested that correlations between executive function and reading comprehension did not…
Shadish, William R.; Lecy, Jesse D.
This article looks at the impact of meta-analysis and then explores why meta-analysis was developed at the time and by the scholars it did in the social sciences in the 1970s. For the first problem, impact, it examines the impact of meta-analysis using citation network analysis. The impact is seen in the sciences, arts and humanities, and on such…
Shadish, William R; Lecy, Jesse D
This article looks at the impact of meta-analysis and then explores why meta-analysis was developed at the time and by the scholars it did in the social sciences in the 1970s. For the first problem, impact, it examines the impact of meta-analysis using citation network analysis. The impact is seen in the sciences, arts and humanities, and on such contemporaneous developments as multilevel modeling, medical statistics, qualitative methods, program evaluation, and single-case design. Using a constrained snowball sample of citations, we highlight key articles that are either most highly cited or most central to the systematic review network. Then, the article examines why meta-analysis came to be in the 1970s in the social sciences through the work of Gene Glass, Robert Rosenthal, and Frank Schmidt, each of whom developed similar theories of meta-analysis at about the same time. The article ends by explaining how Simonton's chance configuration theory and Campbell's evolutionary epistemology can illuminate why meta-analysis occurred with these scholars when it did and not in medical sciences. Copyright © 2015 John Wiley & Sons, Ltd.
This book explains how to employ MASEM, the combination of meta-analysis (MA) and structural equation modelling (SEM). It shows how by using MASEM, a single model can be tested to explain the relationships between a set of variables in several studies. This book gives an introduction to MASEM, with a focus on the state of the art approach: the two stage approach of Cheung and Cheung & Chan. Both, the fixed and the random approach to MASEM are illustrated with two applications to real data. All steps that have to be taken to perform the analyses are discussed extensively. All data and syntax files are available online, so that readers can imitate all analyses. By using SEM for meta-analysis, this book shows how to benefit from all available information from all available studies, even if few or none of the studies report about all relationships that feature in the full model of interest.
Jeong, Se-Hoon; Cho, Hyunyi; Hwang, Yoori
Although numerous media literacy interventions have been developed and delivered over the past 3 decades, a comprehensive meta-analytic assessment of their effects has not been available. This study investigates the average effect size and moderators of 51 media literacy interventions. Media literacy interventions had positive effects (d=.37) on outcomes including media knowledge, criticism, perceived realism, influence, behavioral beliefs, attitudes, self-efficacy, and behavior. Moderator an...
Van Overwalle, Frank; Baetens, Kris; Mariën, Peter; Vandekerckhove, Marie
A recent meta-analysis explored the role of the cerebellum in social cognition and documented that this part of the brain is critically implicated in social cognition, especially in more abstract and complex forms of mentalizing. The authors found an overlap with clusters involved in sensorimotor (during mirror and self-judgment tasks) as well as in executive processes (across all tasks) documented in earlier nonsocial cerebellar meta-analyses, and hence interpreted their results in terms of a domain-general function of the cerebellum. However, these meta-analytic results might be interpreted in a different, complementary way. Indeed, the results reveal a striking overlap with the parcellation of cerebellar topography offered by a recent functional connectivity analysis. In particular, the majority of social cognitive activity in the cerebellum can also be explained as located within the boundaries of a default/mentalizing network of the cerebellum, with the exception of the involvement of primary and integrative somatomotor networks for self-related and mirror tasks, respectively. Given the substantial overlap, a novel interpretation of the meta-analytic findings is put forward suggesting that cerebellar activity during social judgments might reflect a more domain-specific mentalizing functionality in some areas of the cerebellum than assumed before.
Mallikarjun, Sreekanth; Sieburth, Rebecca McNeill
Aspartame (APM) is the most commonly used artificial sweetener and flavor enhancer in the world. There is a rise in concern that APM is carcinogenic due to a variation in the findings of the previous APM carcinogenic bioassays. This article conducts a meta-analytic review of all previous APM carcinogenic bioassays on rodents that were conducted before 31 December 2012. The search yielded 10 original APM carcinogenic bioassays on rodents. The aggregate effect sizes suggest that APM consumption has no significant carcinogenic effect in rodents.
Jeong, Se-Hoon; Cho, Hyunyi; Hwang, Yoori
Although numerous media literacy interventions have been developed and delivered over the past 3 decades, a comprehensive meta-analytic assessment of their effects has not been available. This study investigates the average effect size and moderators of 51 media literacy interventions. Media literacy interventions had positive effects (d=.37) on outcomes including media knowledge, criticism, perceived realism, influence, behavioral beliefs, attitudes, self-efficacy, and behavior. Moderator analyses indicated that interventions with more sessions were more effective, but those with more components were less effective. Intervention effects did not vary by the agent, target age, the setting, audience involvement, the topic, the country, or publication status.
Jeong, Se-Hoon; Cho, Hyunyi; Hwang, Yoori
Although numerous media literacy interventions have been developed and delivered over the past 3 decades, a comprehensive meta-analytic assessment of their effects has not been available. This study investigates the average effect size and moderators of 51 media literacy interventions. Media literacy interventions had positive effects (d=.37) on outcomes including media knowledge, criticism, perceived realism, influence, behavioral beliefs, attitudes, self-efficacy, and behavior. Moderator analyses indicated that interventions with more sessions were more effective, but those with more components were less effective. Intervention effects did not vary by the agent, target age, the setting, audience involvement, the topic, the country, or publication status. PMID:22736807
Liu, Songqi; Huang, Jason L; Wang, Mo
The current meta-analytic review examined the effectiveness of job search interventions in facilitating job search success (i.e., obtaining employment). Major theoretical perspectives on job search interventions, including behavioral learning theory, theory of planned behavior, social cognitive theory, and coping theory, were reviewed and integrated to derive a taxonomy of critical job search intervention components. Summarizing the data from 47 experimentally or quasi-experimentally evaluated job search interventions, we found that the odds of obtaining employment were 2.67 times higher for job seekers participating in job search interventions compared to job seekers in the control group, who did not participate in such intervention programs. Our moderator analysis also suggested that job search interventions that contained certain components, including teaching job search skills, improving self-presentation, boosting self-efficacy, encouraging proactivity, promoting goal setting, and enlisting social support, were more effective than interventions that did not include such components. More important, job search interventions effectively promoted employment only when both skill development and motivation enhancement were included. In addition, we found that job search interventions were more effective in helping younger and older (vs. middle-aged) job seekers, short-term (vs. long-term) unemployed job seekers, and job seekers with special needs and conditions (vs. job seekers in general) to find employment. Furthermore, meta-analytic path analysis revealed that increased job search skills, job search self-efficacy, and job search behaviors partially mediated the positive effect of job search interventions on obtaining employment. Theoretical and practical implications and future research directions are discussed. PsycINFO Database Record (c) 2014 APA, all rights reserved.
Sened, Haran; Lavidor, Michal; Lazarus, Gal; Bar-Kalifa, Eran; Rafaeli, Eshkol; Ickes, William
Empathic accuracy (EA; Ickes & Hodges, 2013) is the extent to which people accurately perceive their peers' thoughts, feelings, and other inner mental states. EA has particularly interested researchers in the context of romantic couples. Reviews of the literature suggest a possible link between romantic partners' EA and their relationship satisfaction (Ickes & Simpson, 2001; Sillars & Scott, 1983). To assess the magnitude of this association and examine possible moderators, we performed a meta-analytic review of 21 studies (total N = 2,739 participants) that examined the association between EA and satisfaction. We limited our review to studies measuring EA using the dyadic interaction paradigm (Ickes, Stinson, Bissonnette, & Garcia, 1990). We found a small but significant association between the two (r = .134, p .1). The association was also stronger in relationships of moderate length, suggesting that EA may be more meaningful when relationships are consolidating but before they become stable. Gender and procedural variations on the dyadic interaction paradigm did not moderate the association, and there was no difference depending on whether the association was between EA and perceivers' or targets' satisfaction (i.e., actor or partner effects). We discuss the implications of these findings and offer recommendations for future EA studies. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Gorrese, Anna; Ruggieri, Ruggero
In adolescence, peers represent key actors within individual social network. Given the relevance of peer connections and the growing literature examining them, the purpose of this article was to review, through a meta-analytic approach, studies on adolescent and youth peer relationships within the theoretical framework of attachment. First, we synthesized results of 44 studies focused on relationships between parent and peer attachment. Second, we summarized findings of 54 studies reporting gender differences on peer attachment. Third, we computed an overall effect for age differences on peer attachment documented in 19 studies. Main findings highlighted that parent attachment is moderately correlated to peer attachment; that females were significantly more attached to their peers than males; and that the correlation between age and peer attachment was not significant. This set of findings was confirmed examining both overall peer attachment as well as specific dimensions of attachment, such as trust and communication. Furthermore, since a significant heterogeneity was found across studies, we tested the effects of various categorical (i.e., year and language of publication, country, attachment measure) and continuous (i.e., mean age and percentage of females of the sample, number of items of the peer attachment scale) moderators related to characteristics of the study samples and designs. Implications of these findings for future research are discussed. A focus on cultural dimensions and on peer attachment processes would be worthwhile to address relevant research questions: How do peer relationships progressively become mature attachment relationships? How is this process shaped for individuals with different parent attachment histories?
Gao, S.; Assink, M.; Cipriani, A.; Lin, K.
Rejection sensitivity is a personality disposition characterized by oversensitivity to social rejection. Using a three-level meta-analytic model, 75 studies were reviewed that examined associations between rejection sensitivity and five mental health outcomes: depression, anxiety, loneliness,
Salsman, John M; Fitchett, George; Merluzzi, Thomas V; Sherman, Allen C; Park, Crystal L
A growing body of research shows that a majority of patients with cancer report having religious and spiritual (R/S) beliefs, engaging in R/S behaviors, or deriving comfort from R/S experiences. These studies have been reviewed but not subjected to rigorous critical analysis. A meta-analytic approach is needed to provide a more definitive understanding of the relationships between R/S (affective, behavioral, and cognitive dimensions) and physical, mental, and social health in all phases of cancer including diagnosis, treatment, survivorship, and palliative care. A meta-analysis can quantify the degree of association between R/S dimensions and patient-reported health outcomes and the conditions under which these associations are strengthened or attenuated. Results can, in turn, help focus future work in this area by highlighting key variables for inclusion in studies of R/S and cancer and identifying particular subgroups for whom dimensions of R/S are particularly important to their health. © 2015 American Cancer Society.
Yuan, Rui; Taylor, Paul A; Alvarez, Tara L; Misra, Durga; Biswal, Bharat B
Meta-analysis of neuroimaging results has proven to be a popular and valuable method to study human brain functions. A number of studies have used meta-analysis to parcellate distinct brain regions. A popular way to perform meta-analysis is typically based on the reported activation coordinates from a number of published papers. However, in addition to the coordinates associated with the different brain regions, the text itself contains considerably amount of additional information. This textual information has been largely ignored in meta-analyses where it may be useful for simultaneously parcellating brain regions and studying their characteristics. By leveraging recent advances in document clustering techniques, we introduce an approach to parcellate the brain into meaningful regions primarily based on the text features present in a document from a large number of studies. This new method is called MAPBOT (Meta-Analytic Parcellation Based On Text). Here, we first describe how the method works and then the application case of understanding the sub-divisions of the thalamus. The thalamus was chosen because of the substantial body of research that has been reported studying this functional and structural structure for both healthy and clinical populations. However, MAPBOT is a general-purpose method that is applicable to parcellating any region(s) of the brain. The present study demonstrates the powerful utility of using text information from neuroimaging studies to parcellate brain regions. Copyright © 2017 Elsevier Inc. All rights reserved.
Sherman, Allen C; Merluzzi, Thomas V; Pustejovsky, James E; Park, Crystal L; George, Login; Fitchett, George; Jim, Heather SL; Munoz, Alexis R; Danhauer, Suzanne C; Snyder, Mallory A; Salsman, John M
Background Religion and spirituality (R/S) play an important role in the daily lives of many cancer patients. There has been great interest in determining whether R/S factors are related to clinically-relevant health outcomes. This meta-analytic review examined associations between dimensions of R/S and social health (e.g., social roles and relationships). Methods A systematic search of PubMed, PsycInfo, Cochrane Library, and CINAHL databases was conducted, and data were extracted by four pairs of investigators. Bivariate associations between specific R/S dimensions and social health outcomes were examined in a meta-analysis using a generalized estimating equation (GEE) approach. Results A total of 78 independent samples encompassing 14,277 patients were included in the meta-analysis. Social health was significantly associated with overall R/S (Fisher z effect size = .20, PGod, R/S beliefs, and composite R/S measures (all P’s < .05). None of the demographic or clinical moderating variables examined was significant. Conclusions Several R/S dimensions are modestly associated with patients’ capacity to maintain satisfying social roles and relationships in the context of cancer. Further research is needed to examine the temporal nature of these associations and the mechanisms that underlie them. PMID:26258730
Burnette, Jeni L; O'Boyle, Ernest H; VanEpps, Eric M; Pollack, Jeffrey M; Finkel, Eli J
This review builds on self-control theory (Carver & Scheier, 1998) to develop a theoretical framework for investigating associations of implicit theories with self-regulation. This framework conceptualizes self-regulation in terms of 3 crucial processes: goal setting, goal operating, and goal monitoring. In this meta-analysis, we included articles that reported a quantifiable assessment of implicit theories and at least 1 self-regulatory process or outcome. With a random effects approach used, meta-analytic results (total unique N = 28,217; k = 113) across diverse achievement domains (68% academic) and populations (age range = 5-42; 10 different nationalities; 58% from United States; 44% female) demonstrated that implicit theories predict distinct self-regulatory processes, which, in turn, predict goal achievement. Incremental theories, which, in contrast to entity theories, are characterized by the belief that human attributes are malleable rather than fixed, significantly predicted goal setting (performance goals, r = -.151; learning goals, r = .187), goal operating (helpless-oriented strategies, r = -.238; mastery-oriented strategies, r = .227), and goal monitoring (negative emotions, r = -.233; expectations, r = .157). The effects for goal setting and goal operating were stronger in the presence (vs. absence) of ego threats such as failure feedback. Discussion emphasizes how the present theoretical analysis merges an implicit theory perspective with self-control theory to advance scholarship and unlock major new directions for basic and applied research.
Peterson, Larry L
This best-selling and classic book teaches you the key principles of computer networks with examples drawn from the real world of network and protocol design. Using the Internet as the primary example, the authors explain various protocols and networking technologies. Their systems-oriented approach encourages you to think about how individual network components fit into a larger, complex system of interactions. Whatever your perspective, whether it be that of an application developer, network administrator, or a designer of network equipment or protocols, you will come away with a "big pictur
Anderson, Craig A.; Shibuya, Akiko; Ihori, Nobuko; Swing, Edward L.; Bushman, Brad J.; Sakamoto, Akira; Rothstein, Hannah R.; Saleem, Muniba
Meta-analytic procedures were used to test the effects of violent video games on aggressive behavior, aggressive cognition, aggressive affect, physiological arousal, empathy/desensitization, and prosocial behavior. Unique features of this meta-analytic review include (a) more restrictive methodological quality inclusion criteria than in past…
Farahmand, Farahnaz K.; Duffy, Sophia N.; Tailor, Megha A.; Dubois, David L.; Lyon, Aaron L.; Grant, Kathryn E.; Zarlinski, Jennifer C.; Masini, Olivia; Zander, Keith J.; Nathanson, Alison M.
A meta-analytic review of 33 studies and 41 independent samples was conducted of the effectiveness of community-based mental health and behavioral programs for low-income urban youth. Findings indicated positive effects, with an overall mean effect of 0.25 at post-test. While this is comparable to previous meta-analytic intervention research with…
Anderson, C.A.; Shibuya, A.; Ihori, N.; Swing, E.L.; Bushman, B.J.; Sakamoto, A.; Rothstein, H.R.; Saleem, M.; Barlett, C.P.
Meta-analytic procedures were used to test the effects of violent video games on aggressive behavior, aggressive cognition, aggressive affect, physiological arousal, empathy/desensitization, and prosocial behavior. Unique features of this meta-analytic review include (a) more restrictive
Zhao, Hao; Seibert, Scott E.
In this study, the authors used meta-analytical techniques to examine the relationship between personality and entrepreneurial status. Personality variables used in previous studies were categorized according to the five-factor model of personality. Results indicate significant differences between entrepreneurs and managers on 4 personality…
Porath-Waller, Amy J.; Beasley, Erin; Beirness, Douglas J.
This investigation used meta-analytic techniques to evaluate the effectiveness of school-based prevention programming in reducing cannabis use among youth aged 12 to 19. It summarized the results from 15 studies published in peer-reviewed journals since 1999 and identified features that influenced program effectiveness. The results from the set of…
Cole, M.S.; Walter, F.; Bedeian, A.G.; O'Boyle, E.H.
Drawing on 50 unique samples (from 37 studies), the authors used meta-analytical techniques to assess the extent to which job burnout and employee engagement are independent and useful constructs. The authors found that (a) dimension-level correlations between burnout and engagement are high, (b)
Diener, Marc J.; Geenen, Rinie; Koelen, Jurrijn A.; Aarts, Floor; Gerdes, Victor E. A.; Brandjes, Dees P. M.; Hinnen, Chris
Theoretical considerations and empirical results suggest that attachment quality is relevant to obesity. This study used meta-analytic methods to systematically examine the empirical, peer-reviewed evidence regarding the relationship between attachment quality and body mass index (BMI) in separate
Prof. Dr. Jo J.M.A Hermanns; Prof. Dr. Ruben R.G. Fukkink; dr. Christa C.C. Nieuwboer
Background. A number of parenting programs, aimed at improving parenting competencies,have recently been adapted or designed with the use of online technologies. Although webbased services have been claimed to hold promise for parent support, a meta-analytic review of online parenting interventions
Gozuyesil, Eda; Dikici, Ayhan
This study's aim is to measure the effect sizes of the quantitative studies that examined the effectiveness of brain-based learning on students' academic achievement and to examine with the meta-analytical method if there is a significant difference in effect in terms of the factors of education level, subject matter, sampling size, and the…
Hoffler, Tim N.
This meta-analytical review focuses on the role of spatial ability when learning with pictorial visualizations. By means of selective theoretical review and meta-analysis (the latter regarding 27 different experiments from 19 studies), several sub-factors of spatial ability are considered as well as dynamic and non-dynamic, interactive and…
Diener, Marc J.; Geenen, Rinie; Koelen, Jurrijn A.; Aarts, Floor; Gerdes, Victor E. A.; Brandjes, Dees P. M.; Hinnen, Chris
Theoretical considerations and empirical results suggest that attachment quality is relevant to obesity. This study used meta-analytic methods to systematically examine the empirical, peer-reviewed evidence regarding the relationship between attachment quality and body mass index (BMI) in separate
Bowling, Nathan A.
The job satisfaction-job performance relationship has attracted much attention throughout the history of industrial and organizational psychology. Many researchers and most lay people believe that a causal relationship exists between satisfaction and performance. In the current study, however, analyses using meta-analytic data suggested that the…
Mihov, Konstantin M.; Denzler, Markus; Forster, Jens
In the last two decades research on the neurophysiological processes of creativity has found contradicting results. Whereas most research suggests right hemisphere dominance in creative thinking, left-hemisphere dominance has also been reported. The present research is a meta-analytic review of the literature to establish how creative thinking…
Lucier-Greer, Mallory; Adler-Baeder, Francesca
Recent meta-analytic efforts have documented how couple and relationship education (CRE) programs promote healthy relationship and family functioning. The current meta-analysis contributes to this body of literature by examining stepfamily couples, an at-risk, subpopulation of participants, and assessing the effectiveness of CRE programs for…
Furr, Jami M.; Comer, Jonathan S.; Edmunds, Julie M.; Kendall, Philip C.
Objective: Meta-analyze the literature on posttraumatic stress (PTS) symptoms in youths post-disaster. Method: Meta-analytic synthesis of the literature (k = 96 studies; N[subscript total] = 74,154) summarizing the magnitude of associations between disasters and youth PTS, and key factors associated with variations in the magnitude of these…
Crede, Marcus; Phillips, L. Alison
The current paper presents a meta-analytic review of the Motivated Strategies for Learning Questionnaire (MSLQ), which consists of fifteen subscales designed from classic social-cognitive learning theories and which is widely used to predict academic performance. Results based on 2158 correlations from 67 independent samples and 19,900 college…
Huo, Zhiguang; Ding, Ying; Liu, Silvia; Oesterreich, Steffi; Tseng, George
Disease phenotyping by omics data has become a popular approach that potentially can lead to better personalized treatment. Identifying disease subtypes via unsupervised machine learning is the first step towards this goal. In this paper, we extend a sparse K-means method towards a meta-analytic framework to identify novel disease subtypes when expression profiles of multiple cohorts are available. The lasso regularization and meta-analysis identify a unique set of gene features for subtype characterization. An additional pattern matching reward function guarantees consistent subtype signatures across studies. The method was evaluated by simulations and leukemia and breast cancer data sets. The identified disease subtypes from meta-analysis were characterized with improved accuracy and stability compared to single study analysis. The breast cancer model was applied to an independent METABRIC dataset and generated improved survival difference between subtypes. These results provide a basis for diagnosis and development of targeted treatments for disease subgroups. PMID:27330233
Hartnell, Chad A; Ou, Amy Yi; Kinicki, Angelo
We apply Quinn and Rohrbaugh's (1983) competing values framework (CVF) as an organizing taxonomy to meta-analytically test hypotheses about the relationship between 3 culture types and 3 major indices of organizational effectiveness (employee attitudes, operational performance [i.e., innovation and product and service quality], and financial performance). The paper also tests theoretical suppositions undergirding the CVF by investigating the framework's nomological validity and proposed internal structure (i.e., interrelationships among culture types). Results based on data from 84 empirical studies with 94 independent samples indicate that clan, adhocracy, and market cultures are differentially and positively associated with the effectiveness criteria, though not always as hypothesized. The findings provide mixed support for the CVF's nomological validity and fail to support aspects of the CVF's proposed internal structure. We propose an alternative theoretical approach to the CVF and delineate directions for future research.
AIMS: This meta-analysis sought to identify which subgroups of clients with severe mental illness (SMI) benefited from evidence-based supported employment. METHODS: We used meta-analysis to pool the samples from 4 randomized controlled trials comparing the Individual Placement and Support (IPS) model of supported employment to well-regarded vocational approaches using stepwise models and brokered services. Meta-analysis was used to determine the magnitude of effects for IPS\\/control group differences within specific client subgroups (defined by 2 work history, 7 sociodemographic, and 8 clinical variables) on 3 competitive employment outcomes (obtaining a job, total weeks worked, and job tenure). RESULTS: The findings strongly favored IPS, with large effect sizes across all outcomes: 0.96 for job acquisition, 0.79 for total weeks worked, and 0.74 for job tenure. Overall, 90 (77%) of the 117 effect sizes calculated for the 39 subgroups exceeded 0.70, and all 117 favored IPS. CONCLUSIONS: IPS produces better competitive employment outcomes for persons with SMI than alternative vocational programs regardless of background demographic, clinical, and employment characteristics.
Grijalva, Emily; Newman, Daniel A; Tay, Louis; Donnellan, M Brent; Harms, P D; Robins, Richard W; Yan, Taiyi
Despite the widely held belief that men are more narcissistic than women, there has been no systematic review to establish the magnitude, variability across measures and settings, and stability over time of this gender difference. Drawing on the biosocial approach to social role theory, a meta-analysis performed for Study 1 found that men tended to be more narcissistic than women (d = .26; k = 355 studies; N = 470,846). This gender difference remained stable in U.S. college student cohorts over time (from 1990 to 2013) and across different age groups. Study 1 also investigated gender differences in three facets of the Narcissistic Personality Inventory (NPI) to reveal that the narcissism gender difference is driven by the Exploitative/Entitlement facet (d = .29; k = 44 studies; N = 44,108) and Leadership/Authority facet (d = .20; k = 40 studies; N = 44,739); whereas the gender difference in Grandiose/Exhibitionism (d = .04; k = 39 studies; N = 42,460) was much smaller. We further investigated a less-studied form of narcissism called vulnerable narcissism-which is marked by low self-esteem, neuroticism, and introversion-to find that (in contrast to the more commonly studied form of narcissism found in the DSM and the NPI) men and women did not differ on vulnerable narcissism (d = -.04; k = 42 studies; N = 46,735). Study 2 used item response theory to rule out the possibility that measurement bias accounts for observed gender differences in the three facets of the NPI (N = 19,001). Results revealed that observed gender differences were not explained by measurement bias and thus can be interpreted as true sex differences. Discussion focuses on the implications for the biosocial construction model of gender differences, for the etiology of narcissism, for clinical applications, and for the role of narcissism in helping to explain gender differences in leadership and aggressive behavior. Readers are warned against overapplying small effect sizes to perpetuate gender
Venkataraman, Archana; Duncan, James S.; Yang, Daniel Y.-J.; Pelphrey, Kevin A.
Resting-state functional magnetic resonance imaging (rsfMRI) studies reveal a complex pattern of hyper- and hypo-connectivity in children with autism spectrum disorder (ASD). Whereas rsfMRI findings tend to implicate the default mode network and subcortical areas in ASD, task fMRI and behavioral experiments point to social dysfunction as a unifying impairment of the disorder. Here, we leverage a novel Bayesian framework for whole-brain functional connectomics that aggregates population differences in connectivity to localize a subset of foci that are most affected by ASD. Our approach is entirely data-driven and does not impose spatial constraints on the region foci or dictate the trajectory of altered functional pathways. We apply our method to data from the openly shared Autism Brain Imaging Data Exchange (ABIDE) and pinpoint two intrinsic functional networks that distinguish ASD patients from typically developing controls. One network involves foci in the right temporal pole, left posterior cingulate cortex, left supramarginal gyrus, and left middle temporal gyrus. Automated decoding of this network by the Neurosynth meta-analytic database suggests high-level concepts of “language” and “comprehension” as the likely functional correlates. The second network consists of the left banks of the superior temporal sulcus, right posterior superior temporal sulcus extending into temporo-parietal junction, and right middle temporal gyrus. Associated functionality of these regions includes “social” and “person”. The abnormal pathways emanating from the above foci indicate that ASD patients simultaneously exhibit reduced long-range or inter-hemispheric connectivity and increased short-range or intra-hemispheric connectivity. Our findings reveal new insights into ASD and highlight possible neural mechanisms of the disorder. PMID:26106561
Pommer, Bernhard; Becker, Kathrin; Arnhart, Christoph; Fabian, Ferenc; Rathe, Florian; Stigler, Robert G
To investigate the impact of meta-analytic evidence in scientific literature on clinical decision making in the field of oral implantology. A Delphi opinion poll was performed at the meeting of the "Next Generation" Committees of the Austrian, German and Swiss Societies for Implantology (ÖGI, DGI and SGI). First, the experts gave their opinion on 20 questions regarding routine implant treatment (uninformed decisions), then they were confronted with up-to-date Level I evidence from scientific literature on these topics and again asked to give their opinion (informed decisions) as well as to rate the available evidence as satisfactory or insufficient. Topics involved surgical issues, such as immediate implant placement, flapless surgery, tilted and short implants and bone substitute materials, as well as opinions on prosthodontic paradigms, such as immediate loading, abutment materials and platform switching. Compared to their uninformed decisions prior to confrontation with recent scientific literature, on average, 37% of experts (range: 15-50%) changed their opinion on the topic. When originally favoring one treatment alternative, less than half were still convinced after review of meta-analytic evidence. Discrepancy between uninformed and informed decisions was significantly associated with insufficient evidence (P = 0.014, 49% change of opinion vs. 26% on topics rated as sufficiently backed with evidence). Agreement regarding strength of evidence could be reached for eight topics (40%), in three issues toward sufficiency and in five issues toward lack of evidence. Confrontation with literature results significantly changes clinical decisions of implantologists, particularly in cases of ambiguous or lacking meta-analytic evidence. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Schutte, Nicola S; Malouff, John M
The enzyme telomerase, through its influence on telomere length, is associated with health and mortality. Four pioneering randomized control trials, including a total of 190 participants, provided information on the effect of mindfulness meditation on telomerase. A meta-analytic effect size of d=0.46 indicated that mindfulness meditation leads to increased telomerase activity in peripheral blood mononuclear cells. These results suggest the need for further large-scale trials investigating optimal implementation of mindfulness meditation to facilitate telomerase functioning. Copyright © 2014 Elsevier Ltd. All rights reserved.
This handbook aims to highlight fundamental, methodological and computational aspects of networks of queues to provide insights and to unify results that can be applied in a more general manner. The handbook is organized into five parts: Part 1 considers exact analytical results such as of product form type. Topics include characterization of product forms by physical balance concepts and simple traffic flow equations, classes of service and queue disciplines that allow a product form, a unified description of product forms for discrete time queueing networks, insights for insensitivity, and aggregation and decomposition results that allow subnetworks to be aggregated into single nodes to reduce computational burden. Part 2 looks at monotonicity and comparison results such as for computational simplification by either of two approaches: stochastic monotonicity and ordering results based on the ordering of the proces generators, and comparison results and explicit error bounds based on an underlying Markov r...
Ferguson, Christopher J
Social scientists continue to debate the impact of spanking and corporal punishment (CP) on negative child outcomes including externalizing and internalizing behavior problems and cognitive performance. Previous meta-analytic reviews have mixed long- and short-term studies and relied on bivariate r, which may inflate effect sizes. The current meta-analysis focused on longitudinal studies, and compared effects using bivariate r and better controlled partial r coefficients controlling for time-1 outcome variables. Consistent with previous findings, results based on bivariate r found small but non-trivial long-term relationships between spanking/CP use and negative outcomes. Spanking and CP correlated .14 and .18 respectively with externalizing problems, .12 and .21 with internalizing problems and -.09 and -.18 with cognitive performance. However, when better controlled partial r coefficients (pr) were examined, results were statistically significant but trivial (at or below pr = .10) for externalizing (.07 for spanking, .08 for CP) and internalizing behaviors (.10 for spanking, insufficient studies for CP) and near the threshold of trivial for cognitive performance (-.11 for CP, insufficient studies for spanking). It is concluded that the impact of spanking and CP on the negative outcomes evaluated here (externalizing, internalizing behaviors and low cognitive performance) are minimal. It is advised that psychologists take a more nuanced approach in discussing the effects of spanking/CP with the general public, consistent with the size as well as the significance of their longitudinal associations with adverse outcomes.
Montesano, Adrián; López-González, María Angeles; Saúl, Luis Angel; Feixas, Guillem
Recent research has highlighted the role of implicative dilemmas in a variety of clinical conditions. These dilemmas are a type of cognitive conflict, in which different aspects of the self are countered in such a way that a desired change in a personal dimension (eg, symptom improvement) may be hindered by the need of personal coherence in another dimension. The aim of this study was to summarize, using a meta-analytical approach, the evidence relating to the presence and the level of this conflict, as well as its relationship with well-being, in various clinical samples. A systematic review using multiple electronic databases found that out of 37 articles assessed for eligibility, nine fulfilled the inclusion criteria for meta-analysis. Random effects model was applied when computing mean effect sizes and testing for heterogeneity level. Statistically significant associations were observed between the clinical status and the presence of dilemmas, as well as level of conflict across several clinical conditions. Likewise, the level of conflict was associated with symptom severity. Results highlighted the clinical relevance and the transdiagnostic nature of implicative dilemmas.
Full Text Available Adrián Montesano,1 María Angeles López-González,2 Luis Angel Saúl,2 Guillem Feixas1 1Department of Personality, Assessment and Psychological Treatments, University of Barcelona, Barcelona, 2Department of Personality, Assessment and Psychological Treatments, Faculty of Psychology, National Distance Education University, Madrid, Spain Abstract: Recent research has highlighted the role of implicative dilemmas in a variety of clinical conditions. These dilemmas are a type of cognitive conflict, in which different aspects of the self are countered in such a way that a desired change in a personal dimension (eg, symptom improvement may be hindered by the need of personal coherence in another dimension. The aim of this study was to summarize, using a meta-analytical approach, the evidence relating to the presence and the level of this conflict, as well as its relationship with well-being, in various clinical samples. A systematic review using multiple electronic databases found that out of 37 articles assessed for eligibility, nine fulfilled the inclusion criteria for meta-analysis. Random effects model was applied when computing mean effect sizes and testing for heterogeneity level. Statistically significant associations were observed between the clinical status and the presence of dilemmas, as well as level of conflict across several clinical conditions. Likewise, the level of conflict was associated with symptom severity. Results highlighted the clinical relevance and the transdiagnostic nature of implicative dilemmas. Keywords: implicative dilemmas, cognitive conflicts, intrapersonal conflicts, meta-analysis
Martin G. Köllner
Full Text Available The correlation between implicit and explicit motive measures and potential moderators of this relationship were examined meta-analytically, using Hunter and Schmidt’s (2004 approach. Studies from a comprehensive search in PsycINFO, data sets of our research group, a literature list compiled by an expert, and the results of a request for grey literature were examined for relevance and coded. Analyses were based on 49 papers, 56 independent samples, 6151 subjects, and 167 correlations. The correlations (ρ between implicit and explicit measures were 0.130 (CI: 0.077 - 0.183 for the overall relationship, 0.116 (CI: 0.050 - 0.182 for affiliation, 0.139 (CI: 0.080 - 0.198 for achievement, and 0.038 (CI: -0.055 - 0.131 for power. Participant age did not moderate the size of these relationships. However, a greater proportion of males in the samples and an earlier publication year were associated with larger effect sizes.
Gnambs, Timo; Staufenbiel, Thomas
The General Health Questionnaire (GHQ-12) is a popular measure of psychological distress. Despite its widespread use, an ongoing controversy pertains to its internal structure. Although the GHQ-12 was originally constructed to capture a unitary construct, empirical studies identified different factor structures. Therefore, this study examined the dimensionality of the GHQ-12 in two independent meta-analyses. The first meta-analysis used summary data published in 38 primary studies (total N = 76,473). Meta-analytic exploratory factor analyses identified two factors formed by negatively and positively worded items. The second meta-analysis included individual responses of 410,640 participants from 84 independent samples. Meta-analytic confirmatory factor analyses corroborated the two-dimensional structure of the GHQ-12. However, bifactor modelling showed that most of the variance was explained by a general factor. Therefore, subscale scores reflected rather limited unique variance. Overall, the two meta-analyses demonstrated that the GHQ-12 is essentially unidimensional. It is not recommended to use and interpret subscale scores because they primarily reflect general mental health rather than distinct constructs.
Michael M. Mackay
Full Text Available This article offers a correlation matrix of meta-analytic estimates between various employee job attitudes (i.e., Employee engagement, job satisfaction, job involvement, and organizational commitment and indicators of employee effectiveness (i.e., Focal performance, contextual performance, turnover intention, and absenteeism. The meta-analytic correlations in the matrix are based on over 1100 individual studies representing over 340,000 employees. Data was collected worldwide via employee self-report surveys. Structural path analyses based on the matrix, and the interpretation of the data, can be found in “Investigating the incremental validity of employee engagement in the prediction of employee effectiveness: a meta-analytic path analysis” (Mackay et al., 2016 .
Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.
Melioli, Tiffany; Bauer, Stephanie; Franko, Debra L; Moessner, Markus; Ozer, Fikret; Chabrol, Henri; Rodgers, Rachel F
The purpose of this meta-analytic review was, first, to evaluate the efficacy of Internet-based programs in decreasing eating disorder (ED) symptoms, and, second, to identify moderator variables these effects. Twenty studies were identified and between-group effect sizes were calculated for ED symptoms and risk factors. Compared with control conditions, Internet-based programs successfully decreased body dissatisfaction (d = 0.28, 95% CI [0.15-0.41], p analytic strategy on intervention effects. Similarly, participant risk status was not a moderator for most outcomes. Internet-based programs are successful in decreasing ED symptoms and risk factors with small to moderate between-group effect sizes. © 2015 Wiley Periodicals, Inc.
Stice, Eric; Shaw, Heather; Marti, C Nathan
This meta-analytic review found that 51% of eating disorder prevention programs reduced eating disorder risk factors and 29% reduced current or future eating pathology. Larger effects occurred for programs that were selected (versus universal), interactive (versus didactic), multisession (versus single session), solely offered to females (versus both sexes), offered to participants over 15 years of age (versus younger ones), and delivered by professional interventionists (versus endogenous providers). Programs with body acceptance and dissonance-induction content and without psychoeducational content and programs evaluated in trials using validated measures and a shorter follow-up period also produced larger effects. Results identify promising programs and delineate sample, format, and design features associated with larger effects, which may inform the design of more effective prevention programs in the future.
Ng, Thomas W H; Feldman, Daniel C
This study examines the criterion-related and incremental validity of ethical leadership (EL) with meta-analytic data. Across 101 samples published over the last 15 years (N = 29,620), we observed that EL demonstrated acceptable criterion-related validity with variables that tap followers' job attitudes, job performance, and evaluations of their leaders. Further, followers' trust in the leader mediated the relationships of EL with job attitudes and performance. In terms of incremental validity, we found that EL significantly, albeit weakly in some cases, predicted task performance, citizenship behavior, and counterproductive work behavior-even after controlling for the effects of such variables as transformational leadership, use of contingent rewards, management by exception, interactional fairness, and destructive leadership. The article concludes with a discussion of ways to strengthen the incremental validity of EL. (PsycINFO Database Record (c) 2015 APA, all rights reserved).
Ferguson, Christopher J; Kilburn, John
To conduct a meta-analytic review of studies that examine the impact of violent media on aggressive behavior and to determine whether this effect could be explained through methodological problems inherent in this research field. A detailed literature search identified peer-reviewed articles addressing media violence effects. Effect sizes were calculated for all studies. Effect sizes were adjusted for observed publication bias. Publication bias was a problem for studies of aggressive behavior, and methodological problems such as the use of poor aggression measures inflated effect size. Once corrected for publication bias, studies of media violence effects provided little support for the hypothesis that media violence is associated with higher aggression. The corrected overall effect size for all studies was r = .08. Results from the current analysis do not support the conclusion that media violence leads to aggressive behavior. It cannot be concluded at this time that media violence presents a significant public health risk.
Birkley, Erica L; Eckhardt, Christopher I
Prior reviews have identified elevated trait anger as a risk factor for intimate partner violence (IPV) perpetration. Given that 10 years have passed since the last comprehensive review of this literature, we provide an updated meta-analytic review examining associations among anger, hostility, internalizing negative emotions, and IPV for male and female perpetrators. One hundred and five effect sizes from 64 independent samples (61 studies) were included for analysis. IPV perpetration was moderately associated with the constructs of anger, hostility, and internalizing negative emotions. This association appeared stronger for those who perpetrated moderate to severe IPV compared to those who perpetrated low to moderate IPV, and did not vary across perpetrator sex, measurement method, relationship type, or perpetrator population. Implications and limitations of findings were reviewed in the context of theoretical models of IPV, and future directions for empirical and clinical endeavors were proposed. Copyright © 2015 Elsevier Ltd. All rights reserved.
Nohe, Christoph; Hertel, Guido
Based on social exchange theory, we examined and contrasted attitudinal mediators (affective organizational commitment, job satisfaction) and relational mediators (trust in leader, leader-member exchange; LMX) of the positive relationship between transformational leadership and organizational citizenship behavior (OCB). Hypotheses were tested using meta-analytic path models with correlations from published meta-analyses (761 samples with 227,419 individuals overall). When testing single-mediator models, results supported our expectations that each of the mediators explained the relationship between transformational leadership and OCB. When testing a multi-mediator model, LMX was the strongest mediator. When testing a model with a latent attitudinal mechanism and a latent relational mechanism, the relational mechanism was the stronger mediator of the relationship between transformational leadership and OCB. Our findings help to better understand the underlying mechanisms of the relationship between transformational leadership and OCB.
Kaminski, Jennifer Wyatt; Valle, Linda Anne; Filene, Jill H; Boyle, Cynthia L
This component analysis used meta-analytic techniques to synthesize the results of 77 published evaluations of parent training programs (i.e., programs that included the active acquisition of parenting skills) to enhance behavior and adjustment in children aged 0-7. Characteristics of program content and delivery method were used to predict effect sizes on measures of parenting behaviors and children's externalizing behavior. After controlling for differences attributable to research design, program components consistently associated with larger effects included increasing positive parent-child interactions and emotional communication skills, teaching parents to use time out and the importance of parenting consistency, and requiring parents to practice new skills with their children during parent training sessions. Program components consistently associated with smaller effects included teaching parents problem solving; teaching parents to promote children's cognitive, academic, or social skills; and providing other, additional services. The results have implications for selection and strengthening of existing parent training programs.
Jiang, Kaifeng; Liu, Dong; McKay, Patrick F; Lee, Thomas W; Mitchell, Terence R
The present meta-analytic study introduces an overall model of the relationships between job embeddedness and turnover outcomes. Drawing on 65 independent samples (N = 42,907), we found that on-the-job and off-the-job embeddedness negatively related to turnover intentions and actual turnover, after controlling for job satisfaction, affective commitment, and job alternatives. In addition, the negative relationships between on-the-job embeddedness (off-the-job embeddedness) and turnover criteria were stronger in female-dominated samples and public organizations (collectivistic countries). Finally, turnover intentions, job search behavior, and job performance fully (partially) mediated the effect of on-the-job embeddedness (off-the-job embeddedness) on actual turnover. The research and practical implications of our findings are noted, in light of study limitations and future research needs.
Crane, Cory A; Hawes, Samuel W; Weinberger, Andrea H
The current meta-analytic review represents the first comprehensive empirical evaluation of the strength of the relationship between intimate partner violence (IPV) victimization and cigarette smoking. Thirty-nine effect sizes, drawn from 31 peer-reviewed publications, determined the existence of a small to medium composite effect size for the victimization-smoking relationship (d = .41, 95% confidence interval = [.35, .47]). Results indicate that victims of IPV are at greater smoking risk than nonvictims. Subsequent moderator analyses indicated that the association between victimization and smoking is moderately stronger among pregnant compared to nonpregnant victims. The strength of the victimization-smoking relationship did not differ by relationship type or ethnicity. More research is needed on the smoking behavior of male victims, victims of psychological violence, and victims who identify as Latino/Latina. It would be useful for professionals working with IPV victims to assess for smoking and incorporate smoking prevention and cessation skills in intervention settings.
Sala, Giovanni; Tatlidil, K Semir; Gobet, Fernand
As a result of considerable potential scientific and societal implications, the possibility of enhancing cognitive ability by training has been one of the most influential topics of cognitive psychology in the last two decades. However, substantial research into the psychology of expertise and a recent series of meta-analytic reviews have suggested that various types of cognitive training (e.g., working memory training) benefit performance only in the trained tasks. The lack of skill generalization from one domain to different ones-that is, far transfer-has been documented in various fields of research such as working memory training, music, brain training, and chess. Video game training is another activity that has been claimed by many researchers to foster a broad range of cognitive abilities such as visual processing, attention, spatial ability, and cognitive control. We tested these claims with three random-effects meta-analytic models. The first meta-analysis (k = 310) examined the correlation between video game skill and cognitive ability. The second meta-analysis (k = 315) dealt with the differences between video game players and nonplayers in cognitive ability. The third meta-analysis (k = 359) investigated the effects of video game training on participants' cognitive ability. Small or null overall effect sizes were found in all three models. These outcomes show that overall cognitive ability and video game skill are only weakly related. Importantly, we found no evidence of a causal relationship between playing video games and enhanced cognitive ability. Video game training thus represents no exception to the general difficulty of obtaining far transfer. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
McDougall, Dennis; Ornelles, Cecily; Mersberg, Kawika; Amona, Kekama
In this meta-analytic review, we critically evaluate procedures and outcomes from nine intervention studies in which students used tactile-cued self-monitoring in educational settings. Findings suggest that most tactile-cued self-monitoring interventions have moderate to strong effects, have emerged only recently, and have not yet achieved the…
Naess, Kari-Anne B.; Lyster, Solveig-Alma Halaas; Hulme, Charles; Melby-Lervag, Monica
This study presents a meta-analytic review of language and verbal short-term memory skills in children with Down syndrome. The study examines the profile of strengths and weaknesses in children with Down syndrome compared to typically developing children matched for nonverbal mental age. The findings show that children with Down syndrome have…
Yonker, Julie E.; Schnabelrauch, Chelsea A.; DeHaan, Laura G.
The present study used meta-analytic techniques to examine the association between spirituality and religiosity (S/R) and psychological outcomes in adolescents and emerging adults. The outcome measures of risk behavior, depression, well-being, self-esteem, and personality were examined with respect to the influence of S/R across 75 independent…
Kalaian, Sema A.; Kasim, Rafa M.
This meta-analytic study focused on the quantitative integration and synthesis of the accumulated pedagogical research in undergraduate statistics education literature. These accumulated research studies compared the academic achievement of students who had been instructed using one of the various forms of small-group learning methods to those who…
Desmarais, Sarah L; Don Read, J
Surveys typically characterize lay knowledge of eyewitness factors as low and highly variable. However, there are notable differences across methodologies, samples, and individual factors. To examine these differences systematically, we took a meta-analytic approach to reviewing the findings of 23 surveys assessing lay knowledge of eyewitness issues. Our analyses examined the beliefs of 4,669 respondents. Overall, respondents correctly agreed with survey items approximately two-thirds of the time. Results revealed significant differences in performance as a function of variable type, question format, and over time. We found few differences as a function of sample type, publication status, or jurisdiction. Although performance varied, a majority of lay respondents achieved "correct" consensus for as many as 11 of the 16 items included in this review.
Tolan, Patrick H.; Henry, David B.; Schoeny, Michael S.; Lovegrove, Peter; Nichols, Emily
Objectives To conduct a meta-analytic review of selective and indicated mentoring interventions for effects for youth at risk on delinquency and key associated outcomes (aggression, drug use, academic functioning). We also undertook the first systematic evaluation of intervention implementation features and organization and tested for effects of theorized key processes of mentor program effects. Methods Campbell Collaboration review inclusion criteria and procedures were used to search and evaluate the literature. Criteria included a sample defined as at-risk for delinquency due to individual behavior such as aggression or conduct problems or environmental characteristics such as residence in high-crime community. Studies were required to be random assignment or strong quasi-experimental design. Of 163 identified studies published 1970 - 2011, 46 met criteria for inclusion. Results Mean effects sizes were significant and positive for each outcome category (ranging form d =.11 for Academic Achievement to d = .29 for Aggression). Heterogeneity in effect sizes was noted for all four outcomes. Stronger effects resulted when mentor motivation was professional development but not by other implementation features. Significant improvements in effects were found when advocacy and emotional support mentoring processes were emphasized. Conclusions This popular approach has significant impact on delinquency and associated outcomes for youth at-risk for delinquency. While evidencing some features may relate to effects, the body of literature is remarkably lacking in details about specific program features and procedures. This persistent state of limited reporting seriously impedes understanding about how mentoring is beneficial and ability to maximize its utility. PMID:25386111
Lewis, Jenny; Ricard, Lykke Margot
examine two contradictory leadership strategies using social network theory: structural holes, where ego (the focal individual) benefits from brokering between two disconnected alters (low redundancy); and network closure, where ego is embedded in very dense local structures (high redundancy). Using......Leaders’ ego-networks within an organization are pivotal as focal points that point to other organizational factors such as innovation capacity and leadership effectiveness. The aim of the paper is to provide a framework for exploring leaders’ ego-networks within the boundary of an organization. We...... redundancy and effective size, and the potential for either divide and conquer or distributed leadership strategies. The empirical testing of this framework adds to our knowledge of the micro level role of individuals within networks. This will be used to examine the relationships between leadership, network...
Husslage, B.G.M.; Lindelauf, R.; Hamers, H.J.M.
Abstract: Lindelauf et al. (2009a) introduced a quantitative approach to investigate optimal structures of covert networks. This approach used an objective function which is based on the secrecy versus information trade-off these organizations face. Sageman (2008) hypothesized that covert networks
Qin Shaomeng; Chen Yong; Zhang Pan
We propose a novel network growth model coupled with the competition interaction to simulate macroevolution. Our work shows that competition plays an important role in macroevolution and it is more rational to describe the interaction between species by network structures. Our model presents a complete picture of the development of phyla and the splitting process. It is found that periodic mass extinction occurred in our networks without any extraterrestrial factors and the lifetime distribution of species is very close to the fossil record. We also perturb networks with two scenarios of mass extinctions on different hierarchic levels in order to study their recovery
Nowak, Donald E; Aloe, Ariel M
The problem of gambling addiction can be especially noteworthy among college and university students, many of whom have the resources, proximity, free time, and desire to become involved in the myriad options of gambling now available. Although limited attention has been paid specifically to college student gambling in the body of literature, there have been two published meta-analyses estimating the prevalence of probable pathological gambling among college students. This present study aims to be the third, presenting an up-to-date proportion of those students exhibiting gambling pathology, and is the first to include international studies from outside the United States and Canada. The purpose of this study was to use the most up-to-date meta-analytical procedures to synthesize the rates of probable pathological gambling for college and university students worldwide. A thorough literature review and coding procedure resulted in 19 independent data estimates retrieved from 18 studies conducted between 2005 and 2013. To synthesize the studies, a random effects model for meta-analysis was applied. The estimated proportion of probable pathological gamblers among the over 13,000 college students surveyed was computed at 10.23%, considerably higher than either of the two previously published meta-analyses, and more than double the rate reported in the first meta-analysis of this type published in 1999. Implications and recommendations for future practice in dealing with college students and gambling addiction are outlined and described for both administrators and mental health professionals.
Kvaale, Erlend P; Haslam, Nick; Gottdiener, William H
Reducing stigma is crucial for facilitating recovery from psychological problems. Viewing these problems biomedically may reduce the tendency to blame affected persons, but critics have cautioned that it could also increase other facets of stigma. We report on the first meta-analytic review of the effects of biogenetic explanations on stigma. A comprehensive search yielded 28 eligible experimental studies. Four separate meta-analyses (Ns=1207-3469) assessed the effects of biogenetic explanations on blame, perceived dangerousness, social distance, and prognostic pessimism. We found that biogenetic explanations reduce blame (Hedges g=-0.324) but induce pessimism (Hedges g=0.263). We also found that biogenetic explanations increase endorsement of the stereotype that people with psychological problems are dangerous (Hedges g=0.198), although this result could reflect publication bias. Finally, we found that biogenetic explanations do not typically affect social distance. Promoting biogenetic explanations to alleviate blame may induce pessimism and set the stage for self-fulfilling prophecies that could hamper recovery from psychological problems. Copyright © 2013 Elsevier Ltd. All rights reserved.
Greer, Lindred L; de Jong, Bart A; Schouten, Maartje E; Dannals, Jennifer E
Hierarchy has the potential to both benefit and harm team effectiveness. In this article, we meta-analytically investigate different explanations for why and when hierarchy helps or hurts team effectiveness, drawing on results from 54 prior studies (N = 13,914 teams). Our findings show that, on net, hierarchy negatively impacts team effectiveness (performance: ρ = -.08; viability: ρ = -.11), and that this effect is mediated by increased conflict-enabling states. Additionally, we show that the negative relationship between hierarchy and team performance is exacerbated by aspects of the team structure (i.e., membership instability, skill differentiation) and the hierarchy itself (i.e., mutability), which make hierarchical teams prone to conflict. The predictions regarding the positive effect of hierarchy on team performance as mediated by coordination-enabling processes, and the moderating roles of several aspects of team tasks (i.e., interdependence, complexity) and the hierarchy (i.e., form) were not supported, with the exception that task ambiguity enhanced the positive effects of hierarchy. Given that our findings largely support dysfunctional views on hierarchy, future research is needed to understand when and why hierarchy may be more likely to live up to its purported functional benefits. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Totura, Christine M Wienke; Fields, Sherecce A; Karver, Marc S
Patient nonadherence to psychopharmacological treatment is a significant barrier to effective treatment. The therapeutic relationship is known to be a critical component of effective psychological treatment, but it has received limited study. A meta-analysis was conducted to examine the role of the therapeutic relationship in the delivery of effective psychopharmacological treatment. PubMed, PsycINFO, CINAHL, Google Scholar, Ingenta, and the Web of Science-Science Citation Index were searched, including reference lists of found articles. Meta-analytic methods were used to examine the association between the physician-patient therapeutic relationship and outcomes in psychopharmacological treatment. Eight independent studies of psychopharmacological treatment reported in nine articles met the inclusion criterion (1,065 participants) of being an empirically based study in which measures of the therapeutic relationship were administered and psychiatric treatment outcomes were assessed. The overall average weighted effect size for the association between the therapeutic relationship and treatment outcomes was z=.30 (95% confidence interval=.20-.39), demonstrating a statistically significant, moderate effect. Findings indicate that a positive therapeutic relationship or alliance between the physician and the psychiatric patient is associated with patient improvement over the course of psychopharmacological treatment. Results suggest that more attention should be paid to psychiatrist communication skills that may enhance the therapeutic alliance in psychopharmacological treatment.
Weight-related problems, including obesity and disordered eating, have emerged as major public health concerns for adolescents. To address these deviations from healthy eating and weight regulation, prevention and intervention efforts have targeted the influence of peers. Yet, evidence that peers influence weight-related outcomes, often inferred from similarity among peers, is inconsistent. This meta-analytic review evaluated peer similarity and influence not only for body size and symptoms of disordered eating, but also for key determinants of obesity (food intake and physical activity levels) and eating pathology (body dissatisfaction and weight control strategies). For each of the six outcomes, data was summarized from 9 to 24 independent studies. Results revealed significant, non-trivial similarity among peers across outcome variables, with the exception of disordered eating. Findings indicated that resemblances among peers were unlikely to be solely the reflection of cognitive biases or the selection of alike friends, but may be partially due to influence. To better understand the influence of peers, further longitudinal research is needed, particularly focusing on the factors that moderate susceptibility to conformity. © 2013.
Lee, Eun-Suk; Park, Tae-Youn; Koo, Bonjin
Organizational identification has been argued to have a unique value in explaining individual attitudes and behaviors in organizations, as it involves the essential definition of entities (i.e., individual and organizational identities). This review seeks meta-analytic evidence of the argument by examining how this identity-relevant construct functions in the nexus of attitudinal/behavioral constructs. The findings show that, first, organizational identification is significantly associated with key attitudes (job involvement, job satisfaction, and affective organizational commitment) and behaviors (in-role performance and extra-role performance) in organizations. Second, in the classic psychological model of attitude-behavior relations (Fishbein & Ajzen, 1975), organizational identification is positioned as a basis from which general sets of those attitudes and behaviors are engendered; organizational identification has a direct effect on general behavior above and beyond the effect of general attitude. Third, the effects of organizational identification are moderated by national culture, a higher-level social context wherein the organization is embedded, such that the effects are stronger in a collectivistic culture than in an individualistic culture. Theoretical and practical implications of the findings and future research directions are discussed. (c) 2015 APA, all rights reserved).
Wang, Ping; Liu, Han-Hui; Zhu, Xing-Ting; Meng, Tian; Li, Hui-Jie; Zuo, Xi-Nian
Action video game (AVG) has attracted increasing attention from both the public and from researchers. More and more studies found video game training improved a variety of cognitive functions. However, it remains controversial whether healthy adults can benefit from AVG training, and whether young and older adults benefit similarly from AVG training. In the present study, we aimed to quantitatively assess the AVG training effect on the cognitive ability of adults and to compare the training effects on young and older adults by conducting a meta-analysis on previous findings. We systematically searched video game training studies published between January 1986 and July 2015. Twenty studies were included in the present meta-analysis, for a total of 313 participants included in the training group and 323 participants in the control group. The results demonstrate that healthy adults achieve moderate benefit from AVG training in overall cognitive ability and moderate to small benefit in specific cognitive domains. In contrast, young adults gain more benefits from AVG training than older adults in both overall cognition and specific cognitive domains. Age, education, and some methodological factors, such as the session duration, session number, total training duration, and control group type, modulated the training effects. These meta-analytic findings provide evidence that AVG training may serve as an efficient way to improve the cognitive performance of healthy adults. We also discussed several directions for future AVG training studies.
Holt-Lunstad, Julianne; Smith, Timothy B; Baker, Mark; Harris, Tyler; Stephenson, David
Actual and perceived social isolation are both associated with increased risk for early mortality. In this meta-analytic review, our objective is to establish the overall and relative magnitude of social isolation and loneliness and to examine possible moderators. We conducted a literature search of studies (January 1980 to February 2014) using MEDLINE, CINAHL, PsycINFO, Social Work Abstracts, and Google Scholar. The included studies provided quantitative data on mortality as affected by loneliness, social isolation, or living alone. Across studies in which several possible confounds were statistically controlled for, the weighted average effect sizes were as follows: social isolation odds ratio (OR) = 1.29, loneliness OR = 1.26, and living alone OR = 1.32, corresponding to an average of 29%, 26%, and 32% increased likelihood of mortality, respectively. We found no differences between measures of objective and subjective social isolation. Results remain consistent across gender, length of follow-up, and world region, but initial health status has an influence on the findings. Results also differ across participant age, with social deficits being more predictive of death in samples with an average age younger than 65 years. Overall, the influence of both objective and subjective social isolation on risk for mortality is comparable with well-established risk factors for mortality. © The Author(s) 2015.
Steffens, Niklas K; Haslam, S Alexander; Schuh, Sebastian C; Jetten, Jolanda; van Dick, Rolf
We provide a meta-analytical review examining two decades of work on the relationship between individuals' social identifications and health in organizations (102 effect sizes, k = 58, N = 19,799). Results reveal a mean-weighted positive association between organizational identification and health ( r = .21, T = .14). Analysis identified a positive relationship for both workgroup ( r = .21) and organizational identification ( r = .21), and in studies using longitudinal/experimental ( r = .13) and cross-sectional designs ( r = .22). The relationship is stronger (a) for indicators of the presence of well-being ( r = .27) than absence of stress ( r = .18), (b) for psychological ( r = .23) than physical health ( r = .16), (c) to the extent that identification is shared among group members, and (d) as the proportion of female participants in a sample decreases. Overall, results indicate that social identifications in organizations are positively associated with health but that there is also substantial variation in effect size strength. We discuss implications for theory and practice and outline a roadmap for future research.
Deffenbacher, Kenneth A; Bornstein, Brian H; Penrod, Steven D; McGorty, E Kiernan
In the past 30 years researchers have examined the impact of heightened stress on the fidelity of eyewitness memory. Meta-analyses were conducted on 27 independent tests of the effects of heightened stress on eyewitness identification of the perpetrator or target person and separately on 36 tests of eyewitness recall of details associated with the crime. There was considerable support for the hypothesis that high levels of stress negatively impact both types of eyewitness memory. Meta-analytic Z-scores, whether unweighted or weighted by sample size, ranged from -5.40 to -6.44 (high stress condition-low stress condition). The overall effect sizes were -.31 for both proportion of correct identifications and accuracy of eyewitness recall. Effect sizes were notably larger for target-present than for target-absent lineups, for eyewitness identification studies than for face recognition studies and for eyewitness studies employing a staged crime than for eyewitness studies employing other means to induce stress.
Wang, Ping; Liu, Han-Hui; Zhu, Xing-Ting; Meng, Tian; Li, Hui-Jie; Zuo, Xi-Nian
Action video game (AVG) has attracted increasing attention from both the public and from researchers. More and more studies found video game training improved a variety of cognitive functions. However, it remains controversial whether healthy adults can benefit from AVG training, and whether young and older adults benefit similarly from AVG training. In the present study, we aimed to quantitatively assess the AVG training effect on the cognitive ability of adults and to compare the training effects on young and older adults by conducting a meta-analysis on previous findings. We systematically searched video game training studies published between January 1986 and July 2015. Twenty studies were included in the present meta-analysis, for a total of 313 participants included in the training group and 323 participants in the control group. The results demonstrate that healthy adults achieve moderate benefit from AVG training in overall cognitive ability and moderate to small benefit in specific cognitive domains. In contrast, young adults gain more benefits from AVG training than older adults in both overall cognition and specific cognitive domains. Age, education, and some methodological factors, such as the session duration, session number, total training duration, and control group type, modulated the training effects. These meta-analytic findings provide evidence that AVG training may serve as an efficient way to improve the cognitive performance of healthy adults. We also discussed several directions for future AVG training studies. PMID:27378996
Full Text Available For more than four decades, researchers have examined theoretically and empirically the relationship between internationalization and firm performance. While existing studies have provided important contributions, the stream of research still lacks consistency due to ambiguous findings on the internationalization-firm performance relationship. Moreover, previous research has often been limited to developed countries. The present study focuses on the emerging Chindia countries and determines the direction and the strength of the internationalization-firm performance relationship. Additionally, we have identified moderators of the relationship. Drawing on 21 studies, based on 9026 firms, we utilize a meta-analytic review to assess our hypotheses. Our results show that there is a significant and positive internationalization-firm performance relationship in Chindia countries. The effect of internationalization in India and China does not significantly differ. Moreover, we find that the effect of internationalization is significantly stronger in the United States as compared to the Chindia countries. The time period of data collection did not play an important role as a moderator. The present study contributes to the International Business literature by examining how and to which extent internationalization influences firm performance and offers implications for theory and practice as well as recommendations for future research.
Colquitt, J A; LePine, J A; Noe, R A
This article meta-analytically summarizes the literature on training motivation, its antecedents, and its relationships with training outcomes such as declarative knowledge, skill acquisition, and transfer. Significant predictors of training motivation and outcomes included individual characteristics (e.g., locus of control, conscientiousness, anxiety, age, cognitive ability, self-efficacy, valence, job involvement) and situational characteristics (e.g., climate). Moreover, training motivation explained incremental variance in training outcomes beyond the effects of cognitive ability. Meta-analytic path analyses further showed that the effects of personality, climate, and age on training outcomes were only partially mediated by self-efficacy, valence, and job involvement. These findings are discussed in terms of their practical significance and their implications for an integrative theory of training motivation.
Simpson, David M; Leonhardt, Nathan D; Hawkins, Alan J
Despite recent policy initiatives and substantial federal funding of individually oriented relationship education programs for youth, there have been no meta-analytic reviews of this growing field. This meta-analytic study draws on 17 control-group studies and 13 one-group/pre-post studies to evaluate the effectiveness of relationship education programs on adolescents' and emerging adults' relationship knowledge, attitudes, and skills. Overall, control-group studies produced a medium effect (d = .36); one-group/pre-post studies also produced a medium effect (d = .47). However, the lack of studies with long-term follow-ups of relationship behaviors in the young adult years is a serious weakness in the field, limiting what we can say about the value of these programs for helping youth achieve their aspirations for healthy romantic relationships and stable marriages.
Pan, Rong; Ding, Zhongli; Yu, Yang; Peng, Yun
.... In this approach, the source and target ontologies are first translated into Bayesian networks (BN); the concept mapping between the two ontologies are treated as evidential reasoning between the two translated BNs...
Woodin, Erica M
This meta-analysis of 64 studies (5,071 couples) used a metacoding system to categorize observed couple conflict behaviors into categories differing in terms of valence (positive to negative) and intensity (high to low) and resulting in five behavioral categories: hostility, distress, withdrawal, problem solving, and intimacy. Aggregate effect sizes indicated that women were somewhat more likely to display hostility, distress, and intimacy during conflict, whereas men were somewhat more likely to display withdrawal and problem solving. Gender differences were of a small magnitude. For both men and women, hostility was robustly associated with lower relationship satisfaction (medium effect), distress and withdrawal were somewhat associated (small effect), and intimacy and problem solving were both closely associated with relationship satisfaction (medium effect). Effect sizes were moderated in several cases by study characteristics including year of publication, developmental period of the sample, recruitment design, duration of observed conflict, method used to induce conflict, and type of coding system used. Findings from this meta-analysis suggest that high-intensity conflict behaviors of both a positive and negative nature are important correlates of relationship satisfaction and underscore the relatively small gender differences in many conflict behaviors. 2011 APA, all rights reserved
Ngugi, Anthony K; Bottomley, Christian; Kleinschmidt, Immo; Sander, Josemir W; Newton, Charles R
To estimate the burden of lifetime epilepsy (LTE) and active epilepsy (AE) and examine the influence of study characteristics on prevalence estimates. We searched online databases and identified articles using prespecified criteria. Random-effects meta-analyses were used to estimate the median prevalence in developed countries and in urban and rural settings in developing countries. The impact of study characteristics on prevalence estimates was determined using meta-regression models. The median LTE prevalence for developed countries was 5.8 per 1,000 (5th-95th percentile range 2.7-12.4) compared to 15.4 per 1,000 (4.8-49.6) for rural and 10.3 (2.8-37.7) for urban studies in developing countries. The median prevalence of AE was 4.9 per 1,000 (2.3-10.3) for developed countries and 12.7 per 1,000 (3.5-45.5) and 5.9 (3.4-10.2) in rural and urban studies in developing countries. The estimates of burden for LTE and AE in developed countries were 6.8 million (5th-95th percentile range 3.2-14.7) and 5.7 million (2.7-12.2), respectively. In developing countries these were 45 (14-145) million LTE and 17 (10-133) million AE in rural areas and 17 (5-61) million LTE and 10 (5-17) million AE in urban areas. Studies involving all ages or only adults showed higher estimates than pediatric studies. Higher prevalence estimates were also associated with rural location and small study size. This study estimates the global burden of epilepsy and the proportions with AE, which may benefit from treatment. There are systematic differences in reported prevalence estimates, which are only partially explained by study characteristics.
Rather than simply providing a narrative literature survey on the CAPM, a comprehensive meta-analysis of the effect of the beta on stock returns was performed. Our meta-analysis covers 47 papers that met inclusion criteria for a 38 year period that spans from 1972 to 2009. The papers examining the three main versions of ...
Molly A. Erickson
Full Text Available The mismatch negativity (MMN is an event-related potential that is consistently attenuated in people with schizophrenia. Within the predictive coding model of psychosis, MMN impairment is thought to reflect the same prediction failures that are also thought to underlie the development and crystallization of delusions and hallucinations. However, the true relationship between symptom severity and MMN impairment across studies has not yet been established. The present meta-analysis used meta-regressions to examine the relationship between MMN impairment (quantified as Hedges' g and PANSS positive and negative symptom totals across 62 and 68 samples, respectively. Furthermore, we examined the relationship between MMN impairment and group differences in educational achievement (n = 47 samples, cognitive ability (n = 36 samples, and age (n = 86 samples. Overall, we found no significant associations between MMN impairment and symptom severity (p's > 0.50; however, we did observe a trend-level association between MMN impairment and lower education (p = 0.07 and a significant association with older age (p < 0.01 in the schizophrenia patient group. Taken together, these results challenge a simple predictive coding model of psychosis, and suggest that MMN impairment may be more closely associated with premorbid functioning than with the expression of psychotic symptoms.
Wang, X T; Rao, Li-Lin; Zheng, Hongming
We hypothesize that framing effects (risk-averse in the positive frame and risk-seeking in the negative frame) are likely to occur when ambiguous social contexts result in ambiguous or ambivalent risk preferences, leading the decision-maker to search for more subtle cues, such as verbal framing. In a functional magnetic resonance imaging (fMRI) study, we examined framing effects in both unambiguous homogeneous group and more ambiguous heterogeneous group contexts. We began by conducting a meta-analysis and identified three regions of interest: the right inferior frontal gyrus, the left anterior cingulate (ACC)/ventromedial prefrontal cortex (vmPFC), and the left amygdala. Our own fMRI data were collected while the participants made choices between a sure option and a gamble framed in terms of the number of lives to either save or die. The framing effect was evident in a heterogeneous context with a mixture of kin and strangers, but disappeared in a homogeneous group of either all kin-members or all strangers. The fMRI results revealed a greater activation in the right middle/inferior frontal gyrus under the negative than the positive framing, and less ACC/vmPFC deactivation under positive framing in the heterogamous/ambiguous context. The activation of the amygdala was correlated with greater risk-seeking preference in homogeneous kinship contexts.
Kim, Boram; Jee, Sooin; Lee, Joungwha; An, Sunghee; Lee, Sang Min
This study is a meta-analysis of 19 relevant studies, with 95,434 participants, investigating the relationships between various types of social support and 3 dimensions of student burnout. The overall results indicate that social support is negatively correlated with student burnout. Specifically, school or teacher supports have the strongest negative relationship to student burnout. Social supports from parents and from peers also have a significant negative relationship with student burnout. Among the 3 dimensions of student burnout, inefficacy was more strongly related to social support than emotional exhaustion or cynicism. The results of a moderation analysis suggest that the type of schools (secondary school and postsecondary school) affected the relationships between the overall social support and student burnout. We discuss the implications to ameliorate student burnout. Copyright © 2017 John Wiley & Sons, Ltd.
Nietzel, Michael T.; And Others
Used meta-analysis to study the clinical significance of psychotherapy for symptoms of unipolar depression, using the Beck Depression Inventory. Results indicated that psychotherapy produces outcomes of moderate clinical significance which are well-maintained at follow-up, that individual therapy is associated with greater clinical significance…
Canada, M J
The networking approach to providing needed services to pregnant and parenting teenagers has numerous merits. An historical overview of the formation of the Brooklyn Teen Pregnancy Network highlights service agency need for information and resource sharing, and improved client referral systems as key factors in the genesis of the Network. The borough-wide approach and its spread as an agency model throughout New York City's other boroughs and several other northeastern cities is also attributed to its positive client impact, including: improved family communication and cooperation; early prenatal care with its concomitant improved pregnancy outcomes; financial support for teens; continued teen education; and parenting skills development. Resource information is provided regarding networks operating in the Greater New York metropolitan area. A planned Eastern Regional network initiative is under development.
Unique among computer networking texts, the Seventh Edition of the popular Computer Networking: A Top Down Approach builds on the author’s long tradition of teaching this complex subject through a layered approach in a “top-down manner.” The text works its way from the application layer down toward the physical layer, motivating readers by exposing them to important concepts early in their study of networking. Focusing on the Internet and the fundamentally important issues of networking, this text provides an excellent foundation for readers interested in computer science and electrical engineering, without requiring extensive knowledge of programming or mathematics. The Seventh Edition has been updated to reflect the most important and exciting recent advances in networking.
Cong, Jin; Liu, Haitao
The interest in modeling and analyzing human language with complex networks is on the rise in recent years and a considerable body of research in this area has already been accumulated. We survey three major lines of linguistic research from the complex network approach: 1) characterization of human language as a multi-level system with complex network analysis; 2) linguistic typological research with the application of linguistic networks and their quantitative measures; and 3) relationships between the system-level complexity of human language (determined by the topology of linguistic networks) and microscopic linguistic (e.g., syntactic) features (as the traditional concern of linguistics). We show that the models and quantitative tools of complex networks, when exploited properly, can constitute an operational methodology for linguistic inquiry, which contributes to the understanding of human language and the development of linguistics. We conclude our review with suggestions for future linguistic research from the complex network approach: 1) relationships between the system-level complexity of human language and microscopic linguistic features; 2) expansion of research scope from the global properties to other levels of granularity of linguistic networks; and 3) combination of linguistic network analysis with other quantitative studies of language (such as quantitative linguistics).
Chaplin, Tara M; Aldao, Amelia
Emotion expression is an important feature of healthy child development that has been found to show gender differences. However, there has been no empirical review of the literature on gender and facial, vocal, and behavioral expressions of different types of emotions in children. The present study constitutes a comprehensive meta-analytic review of gender differences and moderators of differences in emotion expression from infancy through adolescence. We analyzed 555 effect sizes from 166 studies with a total of 21,709 participants. Significant but very small gender differences were found overall, with girls showing more positive emotions (g = -.08) and internalizing emotions (e.g., sadness, anxiety, sympathy; g = -.10) than boys, and boys showing more externalizing emotions (e.g., anger; g = .09) than girls. Notably, gender differences were moderated by age, interpersonal context, and task valence, underscoring the importance of contextual factors in gender differences. Gender differences in positive emotions were more pronounced with increasing age, with girls showing more positive emotions than boys in middle childhood (g = -.20) and adolescence (g = -.28). Boys showed more externalizing emotions than girls at toddler/preschool age (g = .17) and middle childhood (g = .13) and fewer externalizing emotions than girls in adolescence (g = -.27). Gender differences were less pronounced with parents and were more pronounced with unfamiliar adults (for positive emotions) and with peers/when alone (for externalizing emotions). Our findings of gender differences in emotion expression in specific contexts have important implications for gender differences in children's healthy and maladaptive development. 2013 APA, all rights reserved
Full Text Available Abstract Hypertension affects 25% of the world's population and is considered a risk factor for cardiovascular disorders and other diseases. The aim of this study was to examine the evidence regarding the acute effect of exercise on blood pressure (BP using meta-analytic measures. Sixty-five studies were compared using effect sizes (ES, and heterogeneity and Z tests to determine whether the ES were different from zero. The mean corrected global ES for exercise conditions were -0.56 (-4.80 mmHg for systolic BP (sBP and -0.44 (-3.19 mmHg for diastolic BP (dBP; z ≠ 0 for all; p < 0.05. The reduction in BP was significant regardless of the participant's initial BP level, gender, physical activity level, antihypertensive drug intake, type of BP measurement, time of day in which the BP was measured, type of exercise performed, and exercise training program (p < 0.05 for all. ANOVA tests revealed that BP reductions were greater if participants were males, not receiving antihypertensive medication, physically active, and if the exercise performed was jogging. A significant inverse correlation was found between age and BP ES, body mass index (BMI and sBP ES, duration of the exercise's session and sBP ES, and between the number of sets performed in the resistance exercise program and sBP ES (p < 0.05. Regardless of the characteristics of the participants and exercise, there was a reduction in BP in the hours following an exercise session. However, the hypotensive effect was greater when the exercise was performed as a preventive strategy in those physically active and without antihypertensive medication.
Wojtalik, Jessica A; Smith, Matthew J; Keshavan, Matcheri S; Eack, Shaun M
Individuals with schizophrenia are burdened with impairments in functional outcome, despite existing interventions. The lack of understanding of the neurobiological correlates supporting adaptive function in the disorder is a significant barrier to developing more effective treatments. This research conducted a systematic and meta-analytic review of all peer-reviewed studies examining brain-functional outcome relationships in schizophrenia. A total of 53 (37 structural and 16 functional) brain imaging studies examining the neural correlates of functional outcome across 1631 individuals with schizophrenia were identified from literature searches in relevant databases occurring between January, 1968 and December, 2016. Study characteristics and results representing brain-functional outcome relationships were systematically extracted, reviewed, and meta-analyzed. Results indicated that better functional outcome was associated with greater fronto-limbic and whole brain volumes, smaller ventricles, and greater activation, especially during social cognitive processing. Thematic observations revealed that the dorsolateral prefrontal cortex, anterior cingulate, posterior cingulate, parahippocampal gyrus, superior temporal sulcus, and cerebellum may have role in functioning. The neural basis of functional outcome and disability is infrequently studied in schizophrenia. While existing evidence is limited and heterogeneous, these findings suggest that the structural and functional integrity of fronto-limbic brain regions is consistently related to functional outcome in individuals with schizophrenia. Further research is needed to understand the mechanisms and directionality of these relationships, and the potential for identifying neural targets to support functional improvement. © The Author 2017. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: firstname.lastname@example.org.
Horrey, William J; Wickens, Christopher D
The performance costs associated with cell phone use while driving were assessed meta-analytically using standardized measures of effect size along five dimensions. There have been many studies on the impact of cell phone use on driving, showing some mixed findings. Twenty-three studies (contributing 47 analysis entries) met the appropriate conditions for the meta-analysis. The statistical results from each of these studies were converted into effect sizes and combined in the meta-analysis. Overall, there were clear costs to driving performance when drivers were engaged in cell phone conversations. However, subsequent analyses indicated that these costs were borne primarily by reaction time tasks, with far smaller costs associated with tracking (lane-keeping) performance. Hands-free and handheld phones revealed similar patterns of results for both measures of performance. Conversation tasks tended to show greater costs than did information-processing tasks (e.g., word games). There was a similar pattern of results for passenger and remote (cell phone) conversations. Finally, there were some small differences between simulator and field studies, though both exhibited costs in performance for cell phone use. We suggest that (a) there are significant costs to driver reactions to external hazards or events associated with cell phone use, (b) hands-free cell phones do not eliminate or substantially reduce these costs, and (c) different research methodologies or performance measures may underestimate these costs. Potential applications of this research include the assessment of performance costs attributable to different types of cell phones, cell phone conversations, experimental measures, or methodologies.
Mathews, Brittany L; Koehn, Amanda J; Abtahi, Mahsa Movahed; Kerns, Kathryn A
Anxiety is conceptualized as a state of negative emotional arousal that is accompanied by concern about future threat. The purpose of this meta-analytic review was to evaluate the evidence of associations between emotional competence and anxiety by examining how specific emotional competence domains (emotion recognition, emotion expression, emotion awareness, emotion understanding, acceptance of emotion, emotional self-efficacy, sympathetic/empathic responses to others' emotions, recognition of how emotion communication and self-presentation affect relationships, and emotion regulatory processes) relate to anxiety in childhood and adolescence. A total of 185 studies were included in a series of meta-analyses (N's ranged from 573 to 25,711). Results showed that anxious youth are less effective at expressing (r = -0.15) and understanding emotions (r = -0.20), less aware of (r = -0.28) and less accepting of their own emotions (r = -0.49), and report less emotional self-efficacy (r = -0.36). More anxious children use more support-seeking coping strategies (r = 0.07) and are more likely to use less adaptive coping strategies including avoidant coping (r = 0.18), externalizing (r = 0.18), and maladaptive cognitive coping (r = 0.34). Emotion acceptance and awareness, emotional self-efficacy, and maladaptive cognitive coping yielded the largest effect sizes. Some effects varied with children's age. The findings inform intervention and treatment programs of anxiety in youth and identify several areas for future research.
Chaplin, Tara M.; Aldao, Amelia
Emotion expression is an important feature of healthy child development that has been found to show gender differences. However, there has been no empirical review of the literature on gender and facial, vocal, and behavioral expressions of different types of emotions in children. The present study constitutes a comprehensive meta-analytic review of gender differences, and moderators of differences, in emotion expression from infancy through adolescence. We analyzed 555 effect sizes from 166 studies with a total of 21,709 participants. Significant, but very small, gender differences were found overall, with girls showing more positive emotions (g = −.08) and internalizing emotions (e.g., sadness, anxiety, sympathy; g = −.10) than boys, and boys showing more externalizing emotions (e.g., anger; g = .09) than girls. Notably, gender differences were moderated by age, interpersonal context, and task valence, underscoring the importance of contextual factors in gender differences. Gender differences in positive emotions were more pronounced with increasing age, with girls showing more positive emotions than boys in middle childhood (g = −.20) and adolescence (g = −.28). Boys showed more externalizing emotions than girls at toddler/preschool age (g = .17) and middle childhood (g = .13) and fewer externalizing emotions than girls in adolescence (g = −.27). Gender differences were less pronounced with parents and were more pronounced with unfamiliar adults (for positive emotions) and with peers/when alone (for externalizing emotions). Our findings of gender differences in emotion expression in specific contexts have important implications for gender differences in children’s healthy and maladaptive development. PMID:23231534
Lee, Jonathan; Weger, Ronald C.; Sengupta, Sailes K.; Welch, Ronald M.
It is shown that, using high-spatial-resolution data, very high cloud classification accuracies can be obtained with a neural network approach. A texture-based neural network classifier using only single-channel visible Landsat MSS imagery achieves an overall cloud identification accuracy of 93 percent. Cirrus can be distinguished from boundary layer cloudiness with an accuracy of 96 percent, without the use of an infrared channel. Stratocumulus is retrieved with an accuracy of 92 percent, cumulus at 90 percent. The use of the neural network does not improve cirrus classification accuracy. Rather, its main effect is in the improved separation between stratocumulus and cumulus cloudiness. While most cloud classification algorithms rely on linear parametric schemes, the present study is based on a nonlinear, nonparametric four-layer neural network approach. A three-layer neural network architecture, the nonparametric K-nearest neighbor approach, and the linear stepwise discriminant analysis procedure are compared. A significant finding is that significantly higher accuracies are attained with the nonparametric approaches using only 20 percent of the database as training data, compared to 67 percent of the database in the linear approach.
Landry, Mathieu; Lifshitz, Michael; Raz, Amir
Imaging of the living human brain elucidates the neural dynamics of hypnosis; however, few reliable brain patterns emerge across studies. Here, we methodically assess neuroimaging assays of hypnosis to uncover common neural configurations using a twofold approach. First, we systematically review research on the neural correlates of hypnotic phenomena; then, we meta-analyze these collective data seeking specific activation and deactivation patterns that typify hypnosis. Anchored around the role of top-down control processes, our comprehensive examination focuses on the involvement of intrinsic brain networks known to support cognitive control and self-referential cognition, including the executive, salience, and default networks. We discuss how these neural dynamics may relate to contemporary theories of hypnosis and show that hypnosis correlates with activation of the lingual gyrus-a brain region involved in higher-order visual processing and mental imagery. Our findings help to better understand the neurobiological substrates comprising the appellation hypnosis. Copyright © 2017 Elsevier Ltd. All rights reserved.
Clustering is a fundamental data analysis method. It is widely used for pattern recognition, feature extraction, vector quantization (VQ), image segmentation, function approximation, and data mining. As an unsupervised classification technique, clustering identifies some inherent structures present in a set of objects based on a similarity measure. Clustering methods can be based on statistical model identification (McLachlan & Basford, 1988) or competitive learning. In this paper, we give a comprehensive overview of competitive learning based clustering methods. Importance is attached to a number of competitive learning based clustering neural networks such as the self-organizing map (SOM), the learning vector quantization (LVQ), the neural gas, and the ART model, and clustering algorithms such as the C-means, mountain/subtractive clustering, and fuzzy C-means (FCM) algorithms. Associated topics such as the under-utilization problem, fuzzy clustering, robust clustering, clustering based on non-Euclidean distance measures, supervised clustering, hierarchical clustering as well as cluster validity are also described. Two examples are given to demonstrate the use of the clustering methods.
de Castro, Ana Paula A.; da Silva, José D. S.
This paper describes a neural network based multiscale image restoration approach. Multilayer perceptrons are trained with artificial images of degraded gray level circles, in an attempt to make the neural network learn inherent space relations of the degraded pixels. The present approach simulates the degradation by a low pass Gaussian filter blurring operation and the addition of noise to the pixels at pre-established rates. The training process considers the degraded image as input and the non-degraded image as output for the supervised learning process. The neural network thus performs an inverse operation by recovering a quasi non-degraded image in terms of least squared. The main difference of the approach to existing ones relies on the fact that the space relations are taken from different scales, thus providing relational space data to the neural network. The approach is an attempt to come up with a simple method that leads to an optimum solution to the problem. Considering different window sizes around a pixel simulates the multiscale operation. In the generalization phase the neural network is exposed to indoor, outdoor, and satellite degraded images following the same steps use for the artificial circle image.
In this paper, a network based formulation of a permutation flow shop problem is presented. Two nuances of flow shop problems with different levels of complexity are solved using different approaches to the linear programming formulation. Key flow shop parameters inclosing makespan of the flow shop problems were ...
Full Text Available Large-scale distributed systems such as sensor networks usually experience dynamic topology changes, data losses, and node failures in various catastrophic or emergent environments. As such, maintaining data persistence in a scalable fashion has become critical and essential for such systems. The existing major efforts such as coding, routing, and traditional modulation all have their own limitations. In this work, we propose a novel network modulation (NeMo approach to significantly improve the data persistence. Built on algebraic number theory, NeMo operates at the level of modulated symbols (so-called "modulation over modulation". Its core notion is to mix data at intermediate network nodes and meanwhile guarantee the symbol recovery at the sink(s without prestoring or waiting for other symbols. In contrast to the traditional thought that n linearly independent equations are needed to solve for n unknowns, NeMo opens a new regime to boost the convergence speed of achieving persistence. Different performance criteria (e.g., modulation and demodulation complexity, convergence speed, finite-bit representation, and noise robustness have been evaluated in the comprehensive simulations and real experiments to show that the proposed approach is efficient to enhance the network data persistence.
Bühlmayer, Lucia; Birrer, Daniel; Röthlin, Philipp; Faude, Oliver; Donath, Lars
Mindfulness as a present-oriented form of mental training affects cognitive processes and is increasingly considered meaningful for sport psychological training approaches. However, few intervention studies have examined the effects of mindfulness practice on physiological and psychological performance surrogates or on performance outcomes in sports. The aim of the present meta-analytical review was to examine the effects of mindfulness practice or mindfulness-based interventions on physiological and psychological performance surrogates and on performance outcomes in sports in athletes over 15 years of age. A structured literature search was conducted in six electronic databases (CINAHL, EMBASE, ISI Web of Knowledge, PsycINFO, MEDLINE and SPORTDiscus). The following search terms were used with Boolean conjunction: (mindful* OR meditat* OR yoga) AND (sport* OR train* OR exercis* OR intervent* OR perform* OR capacity OR skill*) AND (health* OR adult* OR athlete*). Randomized and non-randomized controlled studies that compared mindfulness practice techniques as an intervention with an inactive control or a control that followed another psychological training program in healthy sportive participants were screened for eligibility. Eligibility and study quality [Physiotherapy Evidence Database (PEDro)] scales were independently assessed by two researchers. A third independent researcher was consulted to achieve final consensus in case of disagreement between both researchers. Standardized mean differences (SMDs) were calculated as weighted Hedges' g and served as the main outcomes in comparing mindfulness practice versus control. Statistical analyses were conducted using a random-effects inverse-variance model. Nine trials of fair study quality (mean PEDro score 5.4, standard deviation 1.1) with 290 healthy sportive participants (athletics, cyclists, dart throwers, hammer throwers, hockey players, hurdlers, judo fighters, rugby players, middle-distance runners, long
Anderson, Craig A; Shibuya, Akiko; Ihori, Nobuko; Swing, Edward L; Bushman, Brad J; Sakamoto, Akira; Rothstein, Hannah R; Saleem, Muniba
Meta-analytic procedures were used to test the effects of violent video games on aggressive behavior, aggressive cognition, aggressive affect, physiological arousal, empathy/desensitization, and prosocial behavior. Unique features of this meta-analytic review include (a) more restrictive methodological quality inclusion criteria than in past meta-analyses; (b) cross-cultural comparisons; (c) longitudinal studies for all outcomes except physiological arousal; (d) conservative statistical controls; (e) multiple moderator analyses; and (f) sensitivity analyses. Social-cognitive models and cultural differences between Japan and Western countries were used to generate theory-based predictions. Meta-analyses yielded significant effects for all 6 outcome variables. The pattern of results for different outcomes and research designs (experimental, cross-sectional, longitudinal) fit theoretical predictions well. The evidence strongly suggests that exposure to violent video games is a causal risk factor for increased aggressive behavior, aggressive cognition, and aggressive affect and for decreased empathy and prosocial behavior. Moderator analyses revealed significant research design effects, weak evidence of cultural differences in susceptibility and type of measurement effects, and no evidence of sex differences in susceptibility. Results of various sensitivity analyses revealed these effects to be robust, with little evidence of selection (publication) bias.
Li, Jun; Ouazzane, Karim; Kazemian, Hassan B; Afzal, Muhammad Sajid
Text entry from people is not only grammatical and distinct, but also noisy. For example, a user's typing stream contains all the information about the user's interaction with computer using a QWERTY keyboard, which may include the user's typing mistakes as well as specific vocabulary, typing habit, and typing performance. In particular, these features are obvious in disabled users' typing streams. This paper proposes a new concept called noisy language modeling by further developing information theory and applies neural networks to one of its specific application-typing stream. This paper experimentally uses a neural network approach to analyze the disabled users' typing streams both in general and specific ways to identify their typing behaviors and subsequently, to make typing predictions and typing corrections. In this paper, a focused time-delay neural network (FTDNN) language model, a time gap model, a prediction model based on time gap, and a probabilistic neural network model (PNN) are developed. A 38% first hitting rate (HR) and a 53% first three HR in symbol prediction are obtained based on the analysis of a user's typing history through the FTDNN language modeling, while the modeling results using the time gap prediction model and the PNN model demonstrate that the correction rates lie predominantly in between 65% and 90% with the current testing samples, and 70% of all test scores above basic correction rates, respectively. The modeling process demonstrates that a neural network is a suitable and robust language modeling tool to analyze the noisy language stream. The research also paves the way for practical application development in areas such as informational analysis, text prediction, and error correction by providing a theoretical basis of neural network approaches for noisy language modeling.
Fontoura Costa, Luciano da
An approach to modeling knowledge acquisition in terms of walks along complex networks is described. Each subset of knowledge is represented as a node, and relations between such knowledge are expressed as edges. Two types of edges are considered, corresponding to free and conditional transitions. The latter case implies that a node can only be reached after visiting previously a set of nodes (the required conditions). The process of knowledge acquisition can then be simulated by considering the number of nodes visited as a single agent moves along the network, starting from its lowest layer. It is shown that hierarchical networks--i.e., networks composed of successive interconnected layers--are related to compositions of the prerequisite relationships between the nodes. In order to avoid deadlocks--i.e., unreachable nodes--the subnetwork in each layer is assumed to be a connected component. Several configurations of such hierarchical knowledge networks are simulated and the performance of the moving agent quantified in terms of the percentage of visited nodes after each movement. The Barabasi-Albert and random models are considered for the layer and interconnecting subnetworks. Although all subnetworks in each realization have the same number of nodes, several interconnectivities, defined by the average node degree of the interconnection networks, have been considered. Two visiting strategies are investigated: random choice among the existing edges and preferential choice to so far untracked edges. A series of interesting results are obtained, including the identification of a series of plateaus of knowledge stagnation in the case of the preferential movement strategy in the presence of conditional edges
Undergraduate Student Paper Postgraduate Student Paper Parametric Identification of Aircraft Loads: An Artificial Neural Network Approach...monitoring, flight parameter, nonlinear modeling, Artificial Neural Network , typical loadcase. Introduction Aircraft load monitoring is an... Neural Networks (ANN), i.e. the BP network and Kohonen Clustering Network , are applied and revised by Kalman Filter and Genetic Algorithm to build
Auconi, P; Caldarelli, G; Scala, A; Ierardo, G; Polimeni, A
Network analysis, a recent advancement in complexity science, enables understanding of the properties of complex biological processes characterized by the interaction, adaptive regulation, and coordination of a large number of participating components. We applied network analysis to orthodontics to detect and visualize the most interconnected clinical, radiographic, and functional data pertaining to the orofacial system. The sample consisted of 104 individuals from 7 to 13 years of age in the mixed dentition phase without previous orthodontic intervention. The subjects were divided according to skeletal class; their clinical, radiographic, and functional features were represented as vertices (nodes) and links (edges) connecting them. Class II subjects exhibited few highly connected orthodontic features (hubs), while Class III patients showed a more compact network structure characterized by strong co-occurrence of normal and abnormal clinical, functional, and radiological features. Restricting our analysis to the highest correlations, we identified critical peculiarities of Class II and Class III malocclusions. The topology of the dentofacial system obtained by network analysis could allow orthodontists to visually evaluate and anticipate the co-occurrence of auxological anomalies during individual craniofacial growth and possibly localize reactive sites for a therapeutic approach to malocclusion. © 2011 John Wiley & Sons A/S.
Whitman, Daniel S; Caleo, Suzette; Carpenter, Nichelle C; Horner, Margaret T; Bernerth, Jeremy B
This article uses meta-analytic methods (k = 38) to examine the relationship between organizational justice climate and unit-level effectiveness. Overall, our results suggest that the relationship between justice and effectiveness is significant (ρ = .40) when both constructs are construed at the collective level. Our results also indicate that distributive justice climate was most strongly linked with unit-level performance (e.g., productivity, customer satisfaction), whereas interactional justice was most strongly related to unit-level processes (e.g., organizational citizenship behavior, cohesion). We also show that a number of factors moderate this relationship, including justice climate strength, the level of referent in the justice measure, the hierarchical level of the unit, and how criteria are classified. We elaborate on these findings and attempt to provide a clearer direction for future research in this area. (PsycINFO Database Record (c) 2012 APA, all rights reserved).
Safari, Reza; Van der Linden, Marietta L; Mercer, Tom H
Although exercise training has been advocated as a nonpharmacological treatment for multiple sclerosis (MS) related fatigue, no consensus exists regarding its effectiveness. To address this, we collated meta-analytic reviews that explored the effectiveness of exercise training for the treatment of MS-related fatigue. We searched five online databases for relevant reviews, published since 2005, and identified 172 records. Five reviews were retained for systematic extraction of information and evidence quality analysis. Although our review synthesis indicated that exercise training interventions have a moderate effect on fatigue reduction in people with MS, no clear insight was obtained regarding the relative effectiveness of specific types or modes of exercise intervention. Moreover, Grading of Recommendation Assessment, Development and Evaluation revealed that the overall quality of evidence emanating from these five reviews was 'very low'.
Crawford, Eean R; Lepine, Jeffery A; Rich, Bruce Louis
We refine and extend the job demands-resources model with theory regarding appraisal of stressors to account for inconsistencies in relationships between demands and engagement, and we test the revised theory using meta-analytic structural modeling. Results indicate support for the refined and updated theory. First, demands and burnout were positively associated, whereas resources and burnout were negatively associated. Second, whereas relationships among resources and engagement were consistently positive, relationships among demands and engagement were highly dependent on the nature of the demand. Demands that employees tend to appraise as hindrances were negatively associated with engagement, and demands that employees tend to appraise as challenges were positively associated with engagement. Implications for future research are discussed. Copyright 2010 APA, all rights reserved
Næss, Kari-Anne B; Lyster, Solveig-Alma Halaas; Hulme, Charles; Melby-Lervåg, Monica
This study presents a meta-analytic review of language and verbal short-term memory skills in children with Down syndrome. The study examines the profile of strengths and weaknesses in children with Down syndrome compared to typically developing children matched for nonverbal mental age. The findings show that children with Down syndrome have broad language deficits (that are not restricted to measures of expressive language) and associated verbal short-term memory deficits. The profile of language skills in children with Down syndrome shows similarities to that seen in children with Specific Language Impairment. The practical and theoretical implications of these findings are discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.
Kangas, Maria; Bovbjerg, Dana H.; Montgomery, Guy H.
Reports an error in "Cancer-related fatigue: A systematic and meta-analytic review of non-pharmacological therapies for cancer patients" by Maria Kangas, Dana H. Bovbjerg and Guy H. Montgomery (Psychological Bulletin, 2008[Sep], Vol 134, 700-741). The URL to the Supplemental Materials for the article is listed incorrectly in two places in the…
This meta-analytic review was performed to determine the relationship between gender and two constructs measuring success in distance learning--academic performance and self-efficacy--with a particular interest in identifying whether females or males have an advantage in distance learning environments. Data from 15 studies resulted in 18 effect…
Son, L.T.; Schiøler, Henrik; Madsen, Ole Brun
This paper analyzes network traffic control issues in Bluetooth data networks as convex optimization problem. We formulate the problem of maximizing of total network flows and minimizing the costs of flows. An adaptive distributed network traffic control scheme is proposed as an approximated...... as capacity limitations and flow requirements in the network. Simulation shows that the performance of Bluetooth networks could be improved by applying the adaptive distributed network traffic control scheme...... solution of the stated optimization problem that satisfies quality of service requirements and topologically induced constraints in Bluetooth networks, such as link capacity and node resource limitations. The proposed scheme is decentralized and complies with frequent changes of topology as well...
Full Text Available The economic world in which tourism companies act today is in a continuous changing process. The most important factor of these changes is the globalization of their environment, both in economic, social, natural and cultural aspects. The tourism companies can benefit from the opportunities brought by globalization, but also could be menaced by the new context. How could react the companies to these changes in order to create and maintain long term competitive advantage for their business? In the present paper we make a literature review of the new tourism companies´ business approach: the networks - a result and/or a reason for exploiting the opportunities or, on the contrary, for keeping their actual position on the market. It’s a qualitative approach and the research methods used are analyses, synthesis, abstraction, which are considered the most appropriate to achieve the objective of the paper.
John M. Beggs
Full Text Available Understanding how ensembles of neurons collectively interact will be a key step in developing a mechanistic theory of cognitive processes. Recent progress in multineuron recording and analysis techniques has generated tremendous excitement over the physiology of living neural networks. One of the key developments driving this interest is a new class of models based on the principle of maximum entropy. Maximum entropy models have been reported to account for spatial correlation structure in ensembles of neurons recorded from several different types of data. Importantly, these models require only information about the firing rates of individual neurons and their pairwise correlations. If this approach is generally applicable, it would drastically simplify the problem of understanding how neural networks behave. Given the interest in this method, several groups now have worked to extend maximum entropy models to account for temporal correlations. Here, we review how maximum entropy models have been applied to neuronal ensemble data to account for spatial and temporal correlations. We also discuss criticisms of the maximum entropy approach that argue that it is not generally applicable to larger ensembles of neurons. We conclude that future maximum entropy models will need to address three issues: temporal correlations, higher-order correlations, and larger ensemble sizes. Finally, we provide a brief list of topics for future research.
Ardila, Alfredo; Bernal, Byron; Rosselli, Monica
Understanding the functions of different brain areas has represented a major endeavor of neurosciences. Historically, brain functions have been associated with specific cortical brain areas; however, modern neuroimaging developments suggest cognitive functions are associated to networks rather than to areas. The purpose of this paper was to analyze the connectivity of Brodmann area (BA) 37 (posterior, inferior, and temporal/fusiform gyrus) in relation to (1) language and (2) visual processing. Two meta-analyses were initially conducted (first level analysis). The first one was intended to assess the language network in which BA37 is involved. The second one was intended to assess the visual perception network. A third meta-analysis (second level analysis) was then performed to assess contrasts and convergence between the two cognitive domains (language and visual perception). The DataBase of Brainmap was used. Our results support the role of BA37 in language but by means of a distinct network from the network that supports its second most important function: visual perception. It was concluded that left BA37 is a common node of two distinct networks-visual recognition (perception) and semantic language functions.
Hiller, Rachel M; Meiser-Stedman, Richard; Fearon, Pasco; Lobo, Sarah; McKinnon, Anna; Fraser, Abigail; Halligan, Sarah L
Understanding the natural course of child and adolescent posttraumatic stress disorder (PTSD) has significant implications for the identification of, and intervention for, at-risk youth. We used a meta-analytic approach to examine longitudinal changes in youth PTSD prevalence and symptoms over the first 12 months posttrauma. We conducted a systematic review to identify longitudinal studies of PTSD in young people (5-18 years old), excluding treatment trials. The search yielded 27 peer-reviewed studies and one unpublished dataset for analysis of pooled prevalence estimates, relative prevalence reduction and standardised mean symptom change. Key moderators were also explored, including age, proportion of boys in the sample, initial prevalence of PTSD and PTSD measurement type. Analyses demonstrated moderate declines in PTSD prevalence and symptom severity over the first 3-6 months posttrauma. From 1 to 6 months posttrauma, the prevalence of PTSD reduced by approximately 50%. Symptoms also showed moderate decline, particularly across the first 3 months posttrauma. There was little evidence of further change in prevalence or symptom severity after 6 months, suggesting that it is unlikely a child would lose a PTSD diagnosis without intervention beyond this point. The current findings provide key information about the likelihood of posttrauma recovery in the absence of intervention and have important implications for our understanding of child and adolescent PTSD. Results are discussed with reference to the timing of PTSD screening and the potential role of early interventions. Findings particularly highlight the importance of future research to develop our understanding of what factors prevent the action of normal recovery from the 'acute' posttrauma period. © 2016 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.
Full Text Available Background. Understanding the functions of different brain areas has represented a major endeavor of neurosciences. Historically, brain functions have been associated with specific cortical brain areas; however, modern neuroimaging developments suggest cognitive functions are associated to networks rather than to areas. Objectives. The purpose of this paper was to analyze the connectivity of Brodmann area (BA 37 (posterior, inferior, and temporal/fusiform gyrus in relation to (1 language and (2 visual processing. Methods. Two meta-analyses were initially conducted (first level analysis. The first one was intended to assess the language network in which BA37 is involved. The second one was intended to assess the visual perception network. A third meta-analysis (second level analysis was then performed to assess contrasts and convergence between the two cognitive domains (language and visual perception. The DataBase of Brainmap was used. Results. Our results support the role of BA37 in language but by means of a distinct network from the network that supports its second most important function: visual perception. Conclusion. It was concluded that left BA37 is a common node of two distinct networks—visual recognition (perception and semantic language functions.
Nizamani, Sarwat; Memon, Nasrullah
In the paper we present a cluster based approach for terrorist network evolution. We have applied hierarchical agglomerative clustering approach to 9/11 case study. We show that, how individual actors who are initially isolated from each other are converted in small clusters and result in a fully...... evolved network. This method of network evolution can help intelligence security analysts to understand the structure of the network....
Sattari, Pegah; Markopoulou, Athina; Fragouli, Christina
Network tomography aims at inferring internal network characteristics based on measurements at the edge of the network. In loss tomography, in particular, the characteristic of interest is the loss rate of individual links. There is a significant body of work dedicated to this problem using multi...... and multiple paths between sources and receivers. This work was the first to make the connection between active network tomography and network coding, and thus opened a new research direction....
Ardila, Alfredo; Bernal, Byron; Rosselli, Monica
Background. Understanding the functions of different brain areas has represented a major endeavor of neurosciences. Historically, brain functions have been associated with specific cortical brain areas; however, modern neuroimaging developments suggest cognitive functions are associated to networks rather than to areas. Objectives. The purpose of this paper was to analyze the connectivity of Brodmann area (BA) 37 (posterior, inferior, and temporal/fusiform gyrus) in relation to (1) language a...
Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internation
Scalco, Andrea; Noventa, Stefano; Sartori, Riccardo; Ceschi, Andrea
During the last decade, the purchase of organic food within a sustainable consumption context has gained momentum. Consequently, the amount of research in the field has increased, leading in some cases to discrepancies regarding both methods and results. The present review examines those works that applied the theory of planned behavior (TPB; Ajzen, 1991) as a theoretical framework in order to understand and predict consumers' motivation to buy organic food. A meta-analysis has been conducted to assess the strength of the relationships between attitude, subjective norms, perceived behavioral control, and intention, as well as between intention and behavior. Results confirm the major role played by individual attitude in shaping buying intention, followed by subjective norms and perceived behavioral control. Intention-behavior shows a large effect size, few studies however explicitly reported such an association. Furthermore, starting from a pooled correlation matrix, a meta-analytic structural equation model has been applied to jointly evaluate the strength of the relationships among the factors of the original model. Results suggest the robustness of the TPB model. In addition, mediation analysis indicates a potential direct effect from subjective norms to individual attitude in the present context. Finally, some issues regarding methodological aspects of the application of the TPB within the context of organic food are discussed for further research developments. Copyright © 2017 Elsevier Ltd. All rights reserved.
Wang, Lamei; Mesman, Judi
In the last 30 years, China has undergone one of the largest rural-to-urban migrations in human history, with many children left behind because of parental migration. We present a meta-analytic review of empirical studies on Chinese children's rural-to-urban migration and on rural children left behind because of parental migration. We examine how these events relate to children's emotional, social, and academic developmental outcomes. We include publications in English and in Chinese to uncover and quantify a part of the research literature that has been inaccessible to most Western scholars in the field of child and family studies. Overall, both migrant children and children left behind by migrant parents in China show significantly less favorable functioning across domains than other Chinese children. It appears that, similar to processes found in other parts of the world, the experience of economic and acculturation stress as well as disrupted parent-child relations constitute a risk for nonoptimal child functioning in the Chinese context. Further, we found evidence for publication bias against studies showing less favorable development for migrant children and children left behind. We discuss the results in terms of challenges to Chinese society and to future empirical research on Chinese family life. © The Author(s) 2015.
Yang, Liu-Qin; Caughlin, David E; Gazica, Michele W; Truxillo, Donald M; Spector, Paul E
This meta-analytic study summarizes relations between workplace mistreatment climate-MC (specific to incivility, aggression, and bullying) and potential outcomes. We define MC as individual or shared perceptions of organizational policies, procedures, and practices that deter interpersonal mistreatment. We located 35 studies reporting results with individual perceptions of MC (psychological MC) that yielded 36 independent samples comprising 91,950 employees. Through our meta-analyses, we found significant mean correlations between psychological MC and employee and organizational outcomes including mistreatment reduction effort (motivation and performance), mistreatment exposure, strains, and job attitudes. Moderator analyses revealed that the psychological MC-outcome relations were generally stronger for perceived civility climate than for perceived aggression-inhibition climate, and content contamination of existing climate scales accentuated the magnitude of the relations between psychological MC and some outcomes (mistreatment exposure and employee strains). Further, the magnitudes of the psychological MC-outcome relations were generally comparable across studies using dominant (i.e., most commonly used) and other climate scales, but for some focal relations, magnitudes varied with respect to cross-sectional versus prospective designs. The 4 studies that assessed MC at the unit-level had results largely consistent with those at the employee level.
Sundell, Knut; Beelmann, Andreas; Hasson, Henna; von Thiele Schwarz, Ulrica
One of the major dilemmas in intervention and implementation research is adaptation versus adherence. High fidelity to an intervention protocol is essential for internal validity. At the same time, it has been argued that adaptation is necessary for improving the adoption and use of interventions by, for example, improving the match between an intervention and its cultural context, thus improving external validity. This study explores the origins of intervention programs (i.e., novel programs, programs adopted from other contexts with or without adaptation) in two meta-analytic intervention data sets from two European countries and compares the effect sizes of the outcomes of the interventions evaluated. Results are based on two samples of studies evaluating German child and youth preventative interventions (k = 158), and Swedish evaluations of a variety of psychological and social interventions (k = 139). The studies were categorized as novel programs, international adoption and contextual adaptation, with a total of six subcategories. In the German sample, after statistically controlling for some crucial methodological aspects, novel programs were significantly more effective than adopted programs. In the Swedish sample, a trend was found suggesting that adopted programs were less effective than adapted and novel programs. If these results are generalizable and unbiased, they favor novel and adapted programs over adopted programs with no adaptation and indicate that adoption of transported programs should not be done without considering adaptation.
Hall, Deborah L; Matz, David C; Wood, Wendy
A meta-analytic review of past research evaluated the link between religiosity and racism in the United States since the Civil Rights Act. Religious racism partly reflects intergroup dynamics. That is, a strong religious in-group identity was associated with derogation of racial out-groups. Other races might be treated as out-groups because religion is practiced largely within race, because training in a religious in-group identity promotes general ethnocentrism, and because different others appear to be in competition for resources. In addition, religious racism is tied to basic life values of social conformity and respect for tradition. In support, individuals who were religious for reasons of conformity and tradition expressed racism that declined in recent years with the decreased societal acceptance of overt racial discrimination. The authors failed to find that racial tolerance arises from humanitarian values, consistent with the idea that religious humanitarianism is largely expressed to in-group members. Only religious agnostics were racially tolerant.
Sagi-Schwartz, Abraham; van IJzendoorn, Marinus H; Bakermans-Kranenburg, Marian J
In a series of meta-analyses with the second generation of Holocaust survivors, no evidence for secondary traumatization was found (Van IJzendoorn, Bakermans-Kranenburg, & Sagi-Schwartz, 2003). With regard to third generation traumatization, various reports suggest the presence of intergenerational transmission of trauma. Some scholars argue that intergenerational transmission of trauma might skip a generation. Therefore, we focus in this study on the transmission of trauma to the third generation offspring (the grandchildren) of the first generation's traumatic Holocaust experiences (referred to as "tertiary traumatization"), and we present a narrative review of the pertinent studies. Meta-analytic results of 13 non-clinical samples involving 1012 participants showed no evidence for tertiary traumatization in Holocaust survivor families. Our previous meta-analytic study on secondary traumatization and the present one on third generation's psychological consequences of the Holocaust indicate a remarkable resilience of profoundly traumatized survivors in their (grand-)parental roles.
van Dijk, H.W.; Scholten, Johan; Tobalina, Alvaro; García Muñoz, Victor; Milanini, Stephane; Kung, Antonio
The current trend for home appliances is networking. Although more and more of these appliances are networked, there is not a standard way of interaction, which restrains the development of services for in-home networks. The lack of standardisation is partly due to a legacy of business interests;
van Dijk, H.W.; Scholten, Johan; Tobalina, Alvaro; García Muñoz, Victor; Milanini, Stephane; Kung, Antonio; Dini, C.; Smekal, Z.; Lochin, E.; Verma, P.
The current trend for home appliances is networking. Although more and more of these appliances are networked, there is not a standard way of interaction, which restrains the development of services for in-home networks. The lack of standardisation is partly due to a legacy of business interests;
van der Schaft, Abraham; Rao, S.; Jayawardhana, B.
A treatment of chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a
Syahputra, Ramadoni; Soesanti, Indah
This paper proposes an artificial immune system (AIS) algorithm approach for reconfiguring distribution network with the presence distributed generators (DG). The distribution network with high-performance is a network that has a low power loss, better voltage profile, and loading balance among feeders. The task for improving the performance of the distribution network is optimization of network configuration. The optimization has become a necessary study with the presence of DG in entire networks. In this work, optimization of network configuration is based on an AIS algorithm. The methodology has been tested in a model of 33 bus IEEE radial distribution networks with and without DG integration. The results have been showed that the optimal configuration of the distribution network is able to reduce power loss and to improve the voltage profile of the distribution network significantly.
Peterson, Larry L
Computer Networks, 4E is the only introductory computer networking book written by authors who have had first-hand experience with many of the protocols discussed in the book, who have actually designed some of them as well, and who are still actively designing the computer networks today. This newly revised edition continues to provide an enduring, practical understanding of networks and their building blocks through rich, example-based instruction. The authors' focus is on the why of network design, not just the specifications comprising today's systems but how key technologies and p
Goh, Swee C.; Elliott, Catherine; Quon, Tony K.
Purpose: The purpose of this paper is to present a meta-analysis of a subset of published empirical research papers that measure learning capability and link it to organizational performance. It also seeks to examine both financial and non-financial performance. Design/methodology/approach: In a search of published research on learning capability…
Bleys, Dries; Luyten, Patrick; Soenens, Bart; Claes, Stephan
Meta-analyses have yielded contradictory findings concerning the role of 5-HTTLPR in interaction with stress (GxE) in depression. The current meta-analysis investigates if these contradictory findings are a result of differences between studies in methodological approaches towards the assessment of stress and depression. After performing a systematic database search (February to December 2016), first, a meta-analysis was used to investigate the total effect size and publication bias. Second, stratified meta-analyses were used to investigate the potential moderating influence of different methodological approaches on heterogeneity of study findings. Third, a meta-regression was used to investigate the combined influence of the methodological approaches on the overall effect size. Results showed a small but significant effect of 5-HTTLPR in interaction with stress in the prediction of depression (OR[95%CI] = 1.18[1.09; 1.28], n = 48 effect sizes from 51 studies, totaling 51,449 participants). There was no evidence of publication bias. Heterogeneity of effect sizes was a result of outliers and not due to different methodological approaches towards the assessment of stress and depression. Yet, there was some evidence that studies adopting a categorical and interview approach to the assessment of stress report higher GxE effects, but further replication of this finding is needed. A large amount of heterogeneity (i.e., 46%) was not explained by the methodological factors included in the study and there was a low response rate of invited studies. The current meta-analysis provides new evidence for the robustness of the interaction between stress and 5-HTTLPR in depression. Copyright © 2017 Elsevier B.V. All rights reserved.
Effectiveness of cognitive behavioral therapy in the treatment of fibromyalgia syndrome: a meta-analytic literature review Effectiveness of cognitive behavioral therapy in the treatment of fibromyalgia syndrome: a meta-analytic literature review
Full Text Available Fibromyalgia (FM is a chronic disorder caused by a dysfunction of central nervous system sensitization. This syndrome is characterized by widespread pain and diffuse tenderness, but often also presents fatigue, sleep disturbances, and a whole range of symptoms such as morning stiffness, decreased physical function and dyscognition. FM is usually treated with pharmacological and non-pharmacological treatments. The non-pharmacological interventions include cognitive behavioral therapy (CBT, physiotherapy, acupuncture and patient education programs. In order to evaluate the efficacy of CBT and compare it with other non-pharmacological treatments, we performed a review of the meta-analytic literature. We evaluated the methodological quality of publications found by following the recommendations of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Data showed that CBT does not provide better results than other non-pharmacological treatments on outcomes of pain, fatigue, sleep disturbance and quality of life, at either a short or long-term evaluation. On the contrary, CBT seems to be more effective on symptoms of depression for a short period, whereas it considerably improves the pain self-management and reduces the number of visits to the doctor. The data currently available indicate that cost-effectiveness studies could help us to understand whether the reduction in the number of visits to the doctor could balance the cost of CBT to the health public system.Fibromyalgia (FM is a chronic disorder caused by a dysfunction of central nervous system sensitization. This syndrome is characterized by widespread pain and diffuse tenderness, but often also presents fatigue, sleep disturbances, and a whole range of symptoms such as morning stiffness, decreased physical function and dyscognition. FM is usually treated with pharmacological and non-pharmacological treatments. The nonpharmacological interventions include
Porta, Sergio; Crucitti, Paolo; Latora, Vito
The application of the network approach to the urban case poses several questions in terms of how to deal with metric distances, what kind of graph representation to use, what kind of measures to investigate, how to deepen the correlation between measures of the structure of the network and measures of the dynamics on the network, what are the possible contributions from the GIS community. In this paper, the authors addresses a study of six cases of urban street networks characterised by diff...
The use of contextually aware, pervasive, distributed computing, and sensor networks to bridge the gap between the physical and online worlds is the basis of mobile social networking. This book shows how applications can be built to provide mobile social networking, the research issues that need to be solved to enable this vision, and how mobile social networking can be used to provide computational intelligence that will improve daily life. With contributions from the fields of sociology, computer science, human-computer interaction and design, this book demonstrates how mobile social networks can be inferred from users' physical interactions both with the environment and with others, as well as how users behave around them and how their behavior differs on mobile vs. traditional online social networks.
Software Defined Networks discusses the historical networking environment that gave rise to SDN, as well as the latest advances in SDN technology. The book gives you the state of the art knowledge needed for successful deployment of an SDN, including: How to explain to the non-technical business decision makers in your organization the potential benefits, as well as the risks, in shifting parts of a network to the SDN modelHow to make intelligent decisions about when to integrate SDN technologies in a networkHow to decide if your organization should be developing its own SDN applications or
Motter, Adilson E.; Gray, Kimberly A.
A city is a complex, emergent system and as such can be conveniently represented as a network of interacting components. A fundamental aspect of networks is that the systemic properties can depend as much on the interactions as they depend on the properties of the individual components themselves. Another fundamental aspect is that changes to one component can affect other components, in a process that may cause the entire or a substantial part of the system to change behavior. Over the past 2 decades, much research has been done on the modeling of large and complex networks involved in communication and transportation, disease propagation, and supply chains, as well as emergent phenomena, robustness and optimization in such systems...
Sanne P. A. Rasing
Full Text Available Depression and anxiety disorders are among the most common mental disorders during adolescence. During this life phase, the incidence of these clinical disorders rises dramatically, and even more adolescents suffer from symptoms of depression or anxiety that are just below the clinical threshold. Both clinical and subclinical levels of depression or anxiety symptoms are related to decreased functioning in various areas, such as social and academic functioning. Prevention of depression and anxiety in adolescents is therefore imperative. We conducted a meta-analytic review of the effects of school-based and community-based prevention programs that are based on cognitive behavioral therapy with the primary goal preventing depression, anxiety, or both in high risk adolescents. Articles were obtained by searching databases and hand searching reference lists of relevant articles and reviews. The selection process yielded 32 articles in the meta-analyses. One article reported on two studies and three articles reported on both depression and anxiety. This resulted in a total of 36 studies, 23 on depression and 13 on anxiety. For depression prevention aimed at high risk adolescents, meta-analysis showed a small effect of prevention programs directly after the intervention, but no effect at 3–6 months and at 12 months follow-up. For anxiety prevention aimed at high risk adolescents, no short-term effect was found, nor at 12 months follow-up. Three to six months after the preventive intervention, symptoms of anxiety were significantly decreased. Although effects on depression and anxiety symptoms were small and temporary, current findings cautiously suggest that depression and anxiety prevention programs based on CBT might have small effects on mental health of adolescents. However, it also indicates that there is still much to be gained for prevention programs. Current findings and possibilities for future research are discussed in order to further
Joseph, Dana L; Jin, Jing; Newman, Daniel A; O'Boyle, Ernest H
Recent empirical reviews have claimed a surprisingly strong relationship between job performance and self-reported emotional intelligence (also commonly called trait EI or mixed EI), suggesting self-reported/mixed EI is one of the best known predictors of job performance (e.g., ρ = .47; Joseph & Newman, 2010b). Results further suggest mixed EI can robustly predict job performance beyond cognitive ability and Big Five personality traits (Joseph & Newman, 2010b; O'Boyle, Humphrey, Pollack, Hawver, & Story, 2011). These criterion-related validity results are problematic, given the paucity of evidence and the questionable construct validity of mixed EI measures themselves. In the current research, we update and reevaluate existing evidence for mixed EI, in light of prior work regarding the content of mixed EI measures. Results of the current meta-analysis demonstrate that (a) the content of mixed EI measures strongly overlaps with a set of well-known psychological constructs (i.e., ability EI, self-efficacy, and self-rated performance, in addition to Conscientiousness, Emotional Stability, Extraversion, and general mental ability; multiple R = .79), (b) an updated estimate of the meta-analytic correlation between mixed EI and supervisor-rated job performance is ρ = .29, and (c) the mixed EI-job performance relationship becomes nil (β = -.02) after controlling for the set of covariates listed above. Findings help to establish the construct validity of mixed EI measures and further support an intuitive theoretical explanation for the uncommonly high association between mixed EI and job performance--mixed EI instruments assess a combination of ability EI and self-perceptions, in addition to personality and cognitive ability. PsycINFO Database Record (c) 2015 APA, all rights reserved.
Hegde, Shankar S.; Prewitt, Judith M.
Although the functions performed by the different nodes on the PACS network are many, it is possible to formulate a minimum set of service primitives such that the application software residing at the nodes can utilize those primitives to perform the functions. These primitives define the framework for the communication interface. The question of how these primitives fit into the concept of a layered network architecture is explored in this paper. The OSI model as applicable to the PACS network is described, the areas that need standardization are briefly mentioned, and the ongoing standardization efforts are addressed from the OSI perspective.
Rehak, Martin; Pechoucek, Michal; Grill, Martin; Bartos, Karel; Celeda, Pavel; Krmicek, Vojtech
Network Behavior Analysis techniques are designed to detect intrusions and other undesirable behavior in computer networks by analyzing the traffic statistics. We present an efficient framework for integration of anomaly detection algorithms working on the identical input data. This framework is based on high-speed network traffic acquisition subsystem and on trust modeling, a well-established set of techniques from the multi-agent system field. Trust-based integration of algorithms results in classification with lower error rate, especially in terms of false positives. The presented framework is suitable for both online and offline processing, and introduces a relatively low computational overhead compared to deployment of isolated anomaly detection algorithms.
OSPFv2) is the most common occurrence of OSPF for IPv4. OSPF version 3 (OSPFv3) was developed to support Internet Protocol version 6 ( IPv6 ...Protocol Version 6 ( IPV6 ) or Internet Protocol Version 4 (IPV4) at the network layer. NTP has three different modes of operation; client/server, symmetric
Reinhardt, Wolfgang; Wilke, Adrian; Moi, Matthias; Drachsler, Hendrik; Sloep, Peter
Reinhardt, W., Wilke, A., Moi, M., Drachsler, H., & Sloep, P. B. (2012). Mining and Visualizing Research Networks using the Artefact-Actor-Network Approach. In A. Abraham (Ed.), Computational Social Networks. Mining and Visualization (pp. 233-268). Springer. Also available at
Marwan, Norbert, E-mail: email@example.com [Potsdam Institute for Climate Impact Research, PO Box 601203, 14412 Potsdam (Germany); Donges, Jonathan F. [Potsdam Institute for Climate Impact Research, PO Box 601203, 14412 Potsdam (Germany)] [Department of Physics, Humboldt University Berlin, Newtonstr. 15, 12489 Berlin (Germany); Zou Yong [Potsdam Institute for Climate Impact Research, PO Box 601203, 14412 Potsdam (Germany); Donner, Reik V. [Potsdam Institute for Climate Impact Research, PO Box 601203, 14412 Potsdam (Germany)] [Institute for Transport and Economics, Dresden University of Technology, Andreas-Schubert-Str. 23, 01062 Dresden (Germany)] [Graduate School of Science, Osaka Prefecture University, 1-1 Gakuencho, Naka-ku, Sakai 599-8531 (Japan); Kurths, Juergen [Potsdam Institute for Climate Impact Research, PO Box 601203, 14412 Potsdam (Germany)] [Department of Physics, Humboldt University Berlin, Newtonstr. 15, 12489 Berlin (Germany)
We propose a novel approach for analysing time series using complex network theory. We identify the recurrence matrix (calculated from time series) with the adjacency matrix of a complex network and apply measures for the characterisation of complex networks to this recurrence matrix. By using the logistic map, we illustrate the potential of these complex network measures for the detection of dynamical transitions. Finally, we apply the proposed approach to a marine palaeo-climate record and identify the subtle changes to the climate regime.
Pokhrel, Basanta Raj; Nainar, Karthikeyan; Bak-Jensen, Birgitte
This paper presents a novel intelligent observability approach for active distribution systems. Observability assessment of the measured power system network, which is a preliminary task in state estimation, is handled via an algebraic method that uses the triangular factors of singular, symmetric...... measurements, network topology, and network parameters. However, since there are large margin of errors exist in the calculation phase, estimated states may be significantly differed from the actual values though network is classified as observable. Hence, an approach based on numerical observability analysis...
Wolf Fredric M
Full Text Available Abstract Background Meta-analysis can be used to pool rate measures across studies, but challenges arise when follow-up duration varies. Our objective was to compare different statistical approaches for pooling count data of varying follow-up times in terms of estimates of effect, precision, and clinical interpretability. Methods We examined data from a published Cochrane Review of asthma self-management education in children. We selected two rate measures with the largest number of contributing studies: school absences and emergency room (ER visits. We estimated fixed- and random-effects standardized weighted mean differences (SMD, stratified incidence rate differences (IRD, and stratified incidence rate ratios (IRR. We also fit Poisson regression models, which allowed for further adjustment for clustering by study. Results For both outcomes, all methods gave qualitatively similar estimates of effect in favor of the intervention. For school absences, SMD showed modest results in favor of the intervention (SMD -0.14, 95% CI -0.23 to -0.04. IRD implied that the intervention reduced school absences by 1.8 days per year (IRD -0.15 days/child-month, 95% CI -0.19 to -0.11, while IRR suggested a 14% reduction in absences (IRR 0.86, 95% CI 0.83 to 0.90. For ER visits, SMD showed a modest benefit in favor of the intervention (SMD -0.27, 95% CI: -0.45 to -0.09. IRD implied that the intervention reduced ER visits by 1 visit every 2 years (IRD -0.04 visits/child-month, 95% CI: -0.05 to -0.03, while IRR suggested a 34% reduction in ER visits (IRR 0.66, 95% CI 0.59 to 0.74. In Poisson models, adjustment for clustering lowered the precision of the estimates relative to stratified IRR results. For ER visits but not school absences, failure to incorporate study indicators resulted in a different estimate of effect (unadjusted IRR 0.77, 95% CI 0.59 to 0.99. Conclusions Choice of method among the ones presented had little effect on inference but affected the
Guevara, James P; Berlin, Jesse A; Wolf, Fredric M
Meta-analysis can be used to pool rate measures across studies, but challenges arise when follow-up duration varies. Our objective was to compare different statistical approaches for pooling count data of varying follow-up times in terms of estimates of effect, precision, and clinical interpretability. We examined data from a published Cochrane Review of asthma self-management education in children. We selected two rate measures with the largest number of contributing studies: school absences and emergency room (ER) visits. We estimated fixed- and random-effects standardized weighted mean differences (SMD), stratified incidence rate differences (IRD), and stratified incidence rate ratios (IRR). We also fit Poisson regression models, which allowed for further adjustment for clustering by study. For both outcomes, all methods gave qualitatively similar estimates of effect in favor of the intervention. For school absences, SMD showed modest results in favor of the intervention (SMD -0.14, 95% CI -0.23 to -0.04). IRD implied that the intervention reduced school absences by 1.8 days per year (IRD -0.15 days/child-month, 95% CI -0.19 to -0.11), while IRR suggested a 14% reduction in absences (IRR 0.86, 95% CI 0.83 to 0.90). For ER visits, SMD showed a modest benefit in favor of the intervention (SMD -0.27, 95% CI: -0.45 to -0.09). IRD implied that the intervention reduced ER visits by 1 visit every 2 years (IRD -0.04 visits/child-month, 95% CI: -0.05 to -0.03), while IRR suggested a 34% reduction in ER visits (IRR 0.66, 95% CI 0.59 to 0.74). In Poisson models, adjustment for clustering lowered the precision of the estimates relative to stratified IRR results. For ER visits but not school absences, failure to incorporate study indicators resulted in a different estimate of effect (unadjusted IRR 0.77, 95% CI 0.59 to 0.99). Choice of method among the ones presented had little effect on inference but affected the clinical interpretability of the findings. Incidence rate
Hoff, Peter D; Raftery, Adrian E; Handcock, Mark S
.... In studies of social networks, recent emphasis has been placed on random graph models where the nodes usually represent individual social actors and the edges represent the presence of a specified...
Cotacallapa, M.; Hase, M. O.
A problem closely related to epidemiology, where a subgraph of ‘infected’ links is defined inside a larger network, is investigated. This subgraph is generated from the underlying network by a random variable, which decides whether a link is able to propagate a disease/information. The relaxation timescale of this random variable is examined in both annealed and quenched limits, and the effectiveness of propagation of disease/information is analyzed. The dynamics of the model is governed by a master equation and two types of underlying network are considered: one is scale-free and the other has exponential degree distribution. We have shown that the relaxation timescale of the contagion variable has a major influence on the topology of the subgraph of infected links, which determines the efficiency of spreading of disease/information over the network.
Trabelsi, Zouheir; Al Braiki, Arwa; Mathew, Sujith Samuel
The attacks on computers and business networks are growing daily, and the need for security professionals who understand how malfeasants perform attacks and compromise networks is a growing requirement to counter the threat. Network security education generally lacks appropriate textbooks with detailed, hands-on exercises that include both offensive and defensive techniques. Using step-by-step processes to build and generate attacks using offensive techniques, Network Attacks and Defenses: A Hands-on Approach enables students to implement appropriate network security solutions within a laborat
Helfrick, Albert D
This book presents fundamentals and the latest techniques of electrical spectrum analysis. It focuses on instruments and techniques used on spectrum and network analysis, rather than theory. The book covers the use of spectrum analyzers, tracking generators, and network analyzers. Filled with practical examples, the book presents techniques that are widely used in signal processing and communications applications, yet are difficult to find in most literature.Key Features* Presents numerous practical examples, including actual spectrum analyzer circuits* Instruction on how to us
Barabási, Albert-László; Gulbahce, Natali; Loscalzo, Joseph
Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction are essential to identify new diseases genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases. PMID:21164525
Fu, King-Wa; Yip, Paul S F
Evidence suggests that there is an increase in the suicide rate following incidents of celebrity suicide in different countries, but there are no data on the overall suicide risk across countries. The duration of increased suicide rates is usually assumed to be on a monthly basis, but the weekly increase remains uncertain. This study aims at estimating the risk for suicide after the suicide deaths of entertainment celebrities in Asia during the first 4 weeks after the celebrity suicides and on a weekly basis. An ecological, retrospective time-series analysis and a meta-analysis of the suicide deaths in 3 Asian regions: Hong Kong (from 2001 to 2003), Taiwan, and South Korea (both from 2003 to 2005). The combined risks for suicide were found to be 1.43 (95% CI = 1.23 to 1.66), 1.29 (95% CI = 1.12 to 1.50), and 1.25 (95% CI = 1.08 to 1.45) in the first, second, and third week, respectively, after suicides of entertainment celebrities, while adjusting for secular trends, seasonality, economic situation, and temporal autocorrelation. The same-gender and same-method specific increases suggest that as people identify more with the celebrity, their risk for suicide rises. A medium-term rise in suicides up to 24 weeks after the incidents of celebrity suicide is also evident. This study is the first to estimate risk for suicides following celebrity suicides across 3 Asian regions. The results provide important information for public health policy makers in assessing the elevated risk associated with excessive media coverage of celebrity suicide and developing timely evidence-based interventions. Copyright 2009 Physicians Postgraduate Press, Inc.
Full Text Available Judo requires endurance capacity to recover from its high-intensity intermittent actions. This systematic review aimed to evaluate VO2max and the anaerobic threshold in competitive male and female judo athletes. Twelve eligible studies were chosen for quantitative meta-analysis, including results for 188 male and 159 female athletes. Combined values were calculated and compared by gender prior to and following altered combat regulations in 2003. No significant differences in VO2max were noted following the rule changes, but female athletes’ values increased to a level comparable to those reported in male athletes prior to the alterations. VO2max in male judo athletes was higher (54.8±1.9 ml·kg-1·min-1 than in female athletes (48.7±2.2 ml·kg-1·min-1. The effect size of gender was large (d = 1.30 for VO2max and negligible for the anaerobic threshold. Sexual dimorphism exists in VO2max of judo athletes and changes in combat duration did not affect these differences.
Oirschot, B.A. van; Bronkhorst, E.M.; Beucken, J.J.J.P van den; Meijer, G.J.; Jansen, J.A.; Junker, R.
BACKGROUND: Calcium phosphate ceramic coatings have the potential to compensate for challenging bone conditions such as delayed or impaired bone healing and low bone quantity or density. Thus, the increasing universal prevalence of subjects with such challenging bone conditions might be paralleled
Full Text Available The Drug Abuse Resistance Education (D.A.R.E. program is a widespread but controversial school-based drug prevention program in the United States as well as in many other countries. The present multivariate meta-analysis reviewed 20 studies that assessed the effectiveness of the D.A.R.E. program in the United States. The results showed that the effects of the D.A.R.E. program on drug use did not vary across the studies with a less than small overall effect while the effects on psychosocial behavior varied with still a less than small overall effect. In addition, the characteristics of the studies significantly explained the variation of the heterogeneous effects on psychosocial behavior, which provides empirical evidence for improving the school-based drug prevention program.
Zafar, M.F.; Naheed, F.; Ahmad, Z.; Anwar, M.M.
Security is an essential element of information technology (IT) infrastructure and applications. Concerns about security of networks and information systems have been growing along with the rapid increase in the number of network users and the value of their transactions. The hasty security threats have driven the development of security products known as Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) to detect and protect the network, server and desktop infrastructure ahead of the threat. Authentication and signing techniques are used to prevent integrity threats. Users, devices, and applications should always be authenticated and authorized before they are allowed to access networking resources. Though a lot of information is available on the internet about IDS and IPS but it all is spread on so many sites and one has to spend a considerable part of his precious time to search it. In this regard a thorough survey has been conducted to facilitate and assist the researchers. The issues and defend challenges in fighting with cyber attacks have been discussed. A comparison of the categories of network security technologies has been presented. In this paper an effort has been made to gather the scattered information and present it at one place. This survey will provide best available up-to-date advancement in the area. A brief description of open source IPS has also been presented. (author)
Glassmeier, Franziska; Feingold, Graham
Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth's climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis's Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav-Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes.
Stokking, H.M.; Deventer, M.O. van; Niamut, O.A.; Walraven, F.A.; Mekuria, R.N.
This paper introduces a novel network-based approach to inter-destination media synchronization. The approach meets the need for synchronization in advanced TV concepts like social TV and offers high scalability, unlike conventional end-point based approaches. The solution for interdestination media
Wagh, Sanjeev; Prasad, Ramjee
the cluster head intelligently using auction data of node i.e. its local battery power, topology strength and external battery support. The network lifetime is the centre focus of the research paper which explores intelligently selection of cluster head using auction based approach. The multi......The wireless sensor networks are designed to install the smart network applications or network for emergency solutions, where human interaction is not possible. The nodes in wireless sensor networks have to self organize as per the users requirements through monitoring environments. As the sensor...... nodes are deployed in an inaccessible location for particular mission, it is difficult to exchange or recharge the nodes battery. Hence the important issues to design the sensor network for maximum time duration of network and also for low power operation of the nodes. The proposal is to select...
van Dijk, Johannes A.G.M.
Social and media networks, the Internet in particular, increasingly link interpersonal, organizational and mass communication. It is argued that this gives a cause for an interdisciplinary and multilevel approach of the network society. This will have to link traditional micro- and meso-level
problems considered were solved using LINGO 7.0. The present technique has been shown to be very effective and efficient efficient. Keywords: Flow shop, network, linear programming, makespan, Gantt Chart, LINGO. 1. INTRODUCTION. INTRODUCTION. INTRODUCTION. The traditional flow shop scheduling problem, in.
Travieso, Gonzalo; Ruggiero, Carlos Antônio; Bruno, Odemir Martinez; Costa, Luciano da Fontoura
Cloud computing has become an important means to speed up computing. One problem influencing heavily the performance of such systems is the choice of nodes as servers responsible for executing the clients’ tasks. In this article we report how complex networks can be used to model such a problem. More specifically, we investigate the performance of the processing respectively to cloud systems underlaid by Erdős–Rényi (ER) and Barabási-Albert (BA) topology containing two servers. Cloud networks involving two communities not necessarily of the same size are also considered in our analysis. The performance of each configuration is quantified in terms of the cost of communication between the client and the nearest server, and the balance of the distribution of tasks between the two servers. Regarding the latter, the ER topology provides better performance than the BA for smaller average degrees and opposite behaviour for larger average degrees. With respect to cost, smaller values are found in the BA topology irrespective of the average degree. In addition, we also verified that it is easier to find good servers in ER than in BA networks. Surprisingly, balance and cost are not too much affected by the presence of communities. However, for a well-defined community network, we found that it is important to assign each server to a different community so as to achieve better performance. (paper: interdisciplinary statistical mechanics )
F. I. Karpelevich
Full Text Available R.L. Dobrushin (1929-1995 made substantial contributions to Queueing Network Theory (QNT. A review of results from QNT which arose from his ideas or were connected to him in other ways is given. We also comment on various related open problems.
Dekker, Kim; Blanken, Tessa F; Van Someren, Eus J W
Studies on personality traits and insomnia have remained inconclusive about which traits show the most direct associations with insomnia severity. It has moreover hardly been explored how traits relate to specific characteristics of insomnia. We here used network analysis in a large sample (N =
Dekker, Kim; Blanken, Tessa F; Van Someren, Eus J W
Studies on personality traits and insomnia have remained inconclusive about which traits show the most direct associations with insomnia severity. It has moreover hardly been explored how traits relate to specific characteristics of insomnia. We here used network analysis in a large sample (N= 2089)
Zerenner, Tanja, E-mail: firstname.lastname@example.org [Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn (Germany); Friederichs, Petra; Hense, Andreas [Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn (Germany); Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53119 Bonn (Germany); Lehnertz, Klaus [Department of Epileptology, University of Bonn, Sigmund-Freud-Straße 25, 53105 Bonn (Germany); Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Nussallee 14-16, 53115 Bonn (Germany); Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53119 Bonn (Germany)
Distinguishing between direct and indirect connections is essential when interpreting network structures in terms of dynamical interactions and stability. When constructing networks from climate data the nodes are usually defined on a spatial grid. The edges are usually derived from a bivariate dependency measure, such as Pearson correlation coefficients or mutual information. Thus, the edges indistinguishably represent direct and indirect dependencies. Interpreting climate data fields as realizations of Gaussian Random Fields (GRFs), we have constructed networks according to the Gaussian Graphical Model (GGM) approach. In contrast to the widely used method, the edges of GGM networks are based on partial correlations denoting direct dependencies. Furthermore, GRFs can be represented not only on points in space, but also by expansion coefficients of orthogonal basis functions, such as spherical harmonics. This leads to a modified definition of network nodes and edges in spectral space, which is motivated from an atmospheric dynamics perspective. We construct and analyze networks from climate data in grid point space as well as in spectral space, and derive the edges from both Pearson and partial correlations. Network characteristics, such as mean degree, average shortest path length, and clustering coefficient, reveal that the networks posses an ordered and strongly locally interconnected structure rather than small-world properties. Despite this, the network structures differ strongly depending on the construction method. Straightforward approaches to infer networks from climate data while not regarding any physical processes may contain too strong simplifications to describe the dynamics of the climate system appropriately.
Zerenner, Tanja; Friederichs, Petra; Hense, Andreas; Lehnertz, Klaus
Distinguishing between direct and indirect connections is essential when interpreting network structures in terms of dynamical interactions and stability. When constructing networks from climate data the nodes are usually defined on a spatial grid. The edges are usually derived from a bivariate dependency measure, such as Pearson correlation coefficients or mutual information. Thus, the edges indistinguishably represent direct and indirect dependencies. Interpreting climate data fields as realizations of Gaussian Random Fields (GRFs), we have constructed networks according to the Gaussian Graphical Model (GGM) approach. In contrast to the widely used method, the edges of GGM networks are based on partial correlations denoting direct dependencies. Furthermore, GRFs can be represented not only on points in space, but also by expansion coefficients of orthogonal basis functions, such as spherical harmonics. This leads to a modified definition of network nodes and edges in spectral space, which is motivated from an atmospheric dynamics perspective. We construct and analyze networks from climate data in grid point space as well as in spectral space, and derive the edges from both Pearson and partial correlations. Network characteristics, such as mean degree, average shortest path length, and clustering coefficient, reveal that the networks posses an ordered and strongly locally interconnected structure rather than small-world properties. Despite this, the network structures differ strongly depending on the construction method. Straightforward approaches to infer networks from climate data while not regarding any physical processes may contain too strong simplifications to describe the dynamics of the climate system appropriately
María Jesús Barroso-Méndez
Full Text Available Partnerships between businesses and non-governmental organizations (NGOs have become widely adopted mechanisms for collaboration in addressing complex social issues, the aim being to take advantage of the two types of organizational rationale to generate mutual value. Many such alliances have proved to be unsuccessful, however. To assist managers improve the likelihood of success of their collaborative relationships, the authors propose a success model of business-NGO partnering processes based on Relationship Marketing Theory. They also analyse the theoretical bases of the model's hypotheses through a meta-analytical study of the existing literature.
of the eyes ; that is shapes, colors and animations with the language of the mind; such as the concepts of relationships, processes, models and...Religion became a way to regain dignity, find a spiritual call, and promote self - esteem (Bramadat & Dawson, 2014). Terrorism researchers have often...result was a flexible, self -forming enemy network with an impressive capability to grow and sustain losses (McChrystal, 2011): In bitter, bloody fights
Aquaro, V.; Bardoscia, M.; Bellotti, R.; Consiglio, A.; De Carlo, F.; Ferri, G.
A system for Operational Risk management based on the computational paradigm of Bayesian Networks is presented. The algorithm allows the construction of a Bayesian Network targeted for each bank and takes into account in a simple and realistic way the correlations among different processes of the bank. The internal losses are averaged over a variable time horizon, so that the correlations at different times are removed, while the correlations at the same time are kept: the averaged losses are thus suitable to perform the learning of the network topology and parameters; since the main aim is to understand the role of the correlations among the losses, the assessments of domain experts are not used. The algorithm has been validated on synthetic time series. It should be stressed that the proposed algorithm has been thought for the practical implementation in a mid or small sized bank, since it has a small impact on the organizational structure of a bank and requires an investment in human resources which is limited to the computational area.
Werner, Marlene; Štulhofer, Aleksandar; Waldorp, Lourens; Jurin, Tanja
In spite of a growing interest in research on hypersexuality, consensus about its etiology and best treatment strategy has not been achieved. To further the empirical and clinical understanding of hypersexuality by exploring the structure of its symptoms using a network analytic approach. In 2014, an online survey advertised as focusing on Internet pornography, sexual health, and relationships was carried out among Croatian men and women aged 18-60 years (M age = 31.1 years, SD = 9.67). In a sample of 3,028 participants, we applied a network analytic approach to explore the structure of hypersexuality symptoms. In the network, nodes represented hypersexuality symptoms and associated sexual behaviors, while their connections were operationalized as partial correlations. 4 Research questions were addressed: (1) does the hypersexuality network differ between genders; (2) which symptoms are centrally positioned; (3) what is the topological location of pornography use; and (4) are there distinct clusters ("communities") of symptoms in the network? We estimated and plotted hypersexuality networks by gender using items from the Hypersexual Disorder Screening Inventory and the Hypersexual Behavioral Consequences Scale, as well as indicators of sexual desire, pornography use, sexual intercourse, and masturbation frequency. The structure of the hypersexuality network was surprisingly similar in women and men, both in terms of symptom centrality and the clustering of symptoms. Psychological distress and negative emotions triggered by sexual fantasies and/or behaviors, together with a loss of control over sexual feelings, occupied central positions in the networks. Pornography use was located peripherally in both the men's and women's hypersexuality networks. Psychological distress and negative emotions triggered by sexual fantasies and/or behaviors constituted the core of the hypersexuality network, which makes them potential prime targets for clinical intervention and
Full Text Available Boolean networks are a simple but efficient model for describing gene regulatory systems. A number of algorithms have been proposed to infer Boolean networks. However, these methods do not take full consideration of the effects of noise and model uncertainty. In this paper, we propose a full Bayesian approach to infer Boolean genetic networks. Markov chain Monte Carlo algorithms are used to obtain the posterior samples of both the network structure and the related parameters. In addition to regular link addition and removal moves, which can guarantee the irreducibility of the Markov chain for traversing the whole network space, carefully constructed mixture proposals are used to improve the Markov chain Monte Carlo convergence. Both simulations and a real application on cell-cycle data show that our method is more powerful than existing methods for the inference of both the topology and logic relations of the Boolean network from observed data.
Haynie, Dana L.; Doogan, Nathan J.; Soller, Brian
Researchers have examined selection and influence processes in shaping delinquency similarity among friends, but little is known about the role of gender in moderating these relationships. Our objective is to examine differences between adolescent boys and girls regarding delinquency-based selection and influence processes. Using longitudinal network data from adolescents attending two large schools in AddHealth (N = 1,857) and stochastic actor-oriented models, we evaluate whether girls are influenced to a greater degree by friends' violence or delinquency than boys (influence hypothesis) and whether girls are more likely to select friends based on violent or delinquent behavior than boys (selection hypothesis). The results indicate that girls are more likely than boys to be influenced by their friends' involvement in violence. Although a similar pattern emerges for nonviolent delinquency, the gender differences are not significant. Some evidence shows that boys are influenced toward increasing their violence or delinquency when exposed to more delinquent or violent friends but are immune to reducing their violence or delinquency when associating with less violent or delinquent friends. In terms of selection dynamics, although both boys and girls have a tendency to select friends based on friends' behavior, girls have a stronger tendency to do so, suggesting that among girls, friends' involvement in violence or delinquency is an especially decisive factor for determining friendship ties. PMID:26097241
Shultz, Thomas R.
This article reviews a particular computational modeling approach to the study of psychological development--that of constructive neural networks. This approach is applied to a variety of developmental domains and issues, including Piagetian tasks, shift learning, language acquisition, number comparison, habituation of visual attention, concept…
Ding, Fei; Jiang, Huaiguang; Tan, Jin
This paper proposes an event-driven approach for reconfiguring distribution systems automatically. Specifically, an optimal synchrophasor sensor placement (OSSP) is used to reduce the number of synchrophasor sensors while keeping the whole system observable. Then, a wavelet-based event detection and location approach is used to detect and locate the event, which performs as a trigger for network reconfiguration. With the detected information, the system is then reconfigured using the hierarchical decentralized approach to seek for the new optimal topology. In this manner, whenever an event happens the distribution network can be reconfigured automatically based on the real-time information that is observable and detectable.
Jay Krishna Thakur
Full Text Available The aim of this work is to investigate new approaches using methods based on statistics and geo-statistics for spatio-temporal optimization of groundwater monitoring networks. The formulated and integrated methods were tested with the groundwater quality data set of Bitterfeld/Wolfen, Germany. Spatially, the monitoring network was optimized using geo-statistical methods. Temporal optimization of the monitoring network was carried out using Sen’s method (1968. For geostatistical network optimization, a geostatistical spatio-temporal algorithm was used to identify redundant wells in 2- and 2.5-D Quaternary and Tertiary aquifers. Influences of interpolation block width, dimension, contaminant association, groundwater flow direction and aquifer homogeneity on statistical and geostatistical methods for monitoring network optimization were analysed. The integrated approach shows 37% and 28% redundancies in the monitoring network in Quaternary aquifer and Tertiary aquifer respectively. The geostatistical method also recommends 41 and 22 new monitoring wells in the Quaternary and Tertiary aquifers respectively. In temporal optimization, an overall optimized sampling interval was recommended in terms of lower quartile (238 days, median quartile (317 days and upper quartile (401 days in the research area of Bitterfeld/Wolfen. Demonstrated methods for improving groundwater monitoring network can be used in real monitoring network optimization with due consideration given to influencing factors.
Full Text Available In this research we investigate how the evidences provided by both static and mobile nodes that are part of a heterogenous sensor network can be combined to have trustworthy results. A solution relying on a network agreement-based approach was implemented and tested.
Anusic, Ivana; Schimmack, Ulrich
The stability of individual differences is a fundamental issue in personality psychology. Although accumulating evidence suggests that many psychological attributes are both stable and change over time, existing research rarely takes advantage of theoretical models that capture both stability and change. In this article, we present the Meta-Analytic Stability and Change model (MASC), a novel meta-analytic model for synthesizing data from longitudinal studies. MASC is based on trait-state models that can separate influences of stable and changing factors from unreliable variance (Kenny & Zautra, 1995). We used MASC to evaluate the extent to which personality traits, life satisfaction, affect, and self-esteem are influenced by these different factors. The results showed that the majority of reliable variance in personality traits is attributable to stable influences (83%). Changing factors had a greater influence on reliable variance in life satisfaction, self-esteem, and affect than in personality (42%-56% vs. 17%). In addition, changing influences on well-being were more stable than changing influences on personality traits, suggesting that different changing factors contribute to personality and well-being. Measures of affect were less reliable than measures of the other 3 constructs, reflecting influences of transient factors, such as mood on affective judgments. After accounting for differences in reliability, stability of affect did not differ from other well-being variables. Consistent with previous research, we found that stability of individual differences increases with age. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Bada Algom, O; Fabry, C; Leroy, P L; Hornick, J-L
Kouri (Bos taurus) is a breed aboriginal from Lake Chad and threatened with extinction. This study aimed to compare milk fatty acid profiles measured on Kouri cows and on high-yielding dairy cattle in Europe and elsewhere as reported by meta-analytical data (22 experimentations). Milk samples were collected from 14 Kouri dairy cows in dry season (March to June) and fatty acids (FA) were determined by gas chromatography. Overall, 32 FA have been identified. Kouri showed lower values (P < 0.001) in the sum of saturated FA (SFA, -10.9 pts), cis-9, cis-12 18:2 (-1.00 pt) (P < 0.01, higher values (P < 0.001) in the sum of monounsaturated FA (MUFA, +15.3 pts), C18:0) (+3.5 pts), cis-9, trans-11 C18:2-CLA (+1.00 pts), trans-11 18:1 (+1.4 pts) and (P < 0.01) in cis-9, C18:1 (+3.00 pts) acids. The differences between the milk FA profile of the Kouri cows and that obtained from meta-analytical data could be the possible consequence of the use of particular lake pastures by Kouri cows.
Nuijten, M.B.; Deserno, M.K.; Cramer, A.O.J.; Borsboom, D.
Mental disorders have traditionally been conceptualized as latent variables, which impact observable symptomatology. Recent alternative approaches, however, view mental disorders as systems of mutually reinforcing symptoms, and utilize network models to analyze the structure of these symptom-symptom
Gomadam, Krishna; Cadambe, Viveck R.; Jafar, Syed A.
Recent results establish the optimality of interference alignment to approach the Shannon capacity of interference networks at high SNR. However, the extent to which interference can be aligned over a finite number of signalling dimensions remains unknown. Another important concern for interference alignment schemes is the requirement of global channel knowledge. In this work we provide examples of iterative algorithms that utilize the reciprocity of wireless networks to achieve interference ...
There is a great need for fast accurate text retrieval systems to support many intelligent activities. The text search problem can be broken down into two main tasks; database searching and message routing. Database searching consists of searching through a large database of text from certain key words, phrases, or other simple functions of strings. Message routing is classifying incoming messages and sending them to the appropriate `mail box.'' These are actually very similar tasks. Both are really just pattern matching tasks. What matters are the methods used. In addition to searching and classifying, it would be nice to perform other tasks such as inferencing and prediction, so these are discussed briefly. We discuss and compare current leading edge solutions to this problem and introduce some new ideas based on recent neural network theories and experiments. All text-search and retrieval technology is predicted on the assumption that the semantic content of text can be predictd from its syntactic properties: specifically, the existence, frequency, or absence of certain character strings or words; the relationship clustering among words and phrases; the occurrence of particular patterns in particular fields within the document.
The interactions among different microbial populations in a community could play more important roles in determining ecosystem functioning than species numbers and their abundances, but very little is known about such network interactions at a community level. The goal of this project is to develop novel framework approaches and associated software tools to characterize the network interactions in microbial communities based on high throughput, large scale high-throughput metagenomics data and apply these approaches to understand the impacts of environmental changes (e.g., climate change, contamination) on network interactions among different nitrifying populations and associated microbial communities.
Rocco S, Claudio M.; Moreno, Jose Ali
Two cellular automata (CA) models that evaluate the s-t connectedness and shortest path in a network are presented. CA based algorithms enhance the performance of classical algorithms, since they allow a more reliable and straightforward parallel implementation resulting in a dynamic network evaluation, where changes in the connectivity and/or link costs can readily be incorporated avoiding recalculation from scratch. The paper also demonstrates how these algorithms can be applied for network reliability evaluation (based on Monte-Carlo approach) and for finding s-t path with maximal reliability
Soliman, Maha; Nasraoui, Olfa; Cooper, Nigel G F
The volume of biomedical literature and its underlying knowledge base is rapidly expanding, making it beyond the ability of a single human being to read through all the literature. Several automated methods have been developed to help make sense of this dilemma. The present study reports on the results of a text mining approach to extract gene interactions from the data warehouse of published experimental results which are then used to benchmark an interaction network associated with glaucoma. To the best of our knowledge, there is, as yet, no glaucoma interaction network derived solely from text mining approaches. The presence of such a network could provide a useful summative knowledge base to complement other forms of clinical information related to this disease. A glaucoma corpus was constructed from PubMed Central and a text mining approach was applied to extract genes and their relations from this corpus. The extracted relations between genes were checked using reference interaction databases and classified generally as known or new relations. The extracted genes and relations were then used to construct a glaucoma interaction network. Analysis of the resulting network indicated that it bears the characteristics of a small world interaction network. Our analysis showed the presence of seven glaucoma linked genes that defined the network modularity. A web-based system for browsing and visualizing the extracted glaucoma related interaction networks is made available at http://neurogene.spd.louisville.edu/GlaucomaINViewer/Form1.aspx. This study has reported the first version of a glaucoma interaction network using a text mining approach. The power of such an approach is in its ability to cover a wide range of glaucoma related studies published over many years. Hence, a bigger picture of the disease can be established. To the best of our knowledge, this is the first glaucoma interaction network to summarize the known literature. The major findings were a set of
Ho, Jessica; Boughton, Nick; Kehoe, Dennis; Michaelides, Zenon
The Internet is playing an increasingly important role in enhancing the operations of supply networks as many organizations begin to recognize the benefits of Internet- enabled supply arrangements. However, the developments and applications to-date do not extend significantly beyond the dyadic model, whereas the real advantages are to be made with the external and network models to support a coordinated and collaborative based approach. The DOMAIN research group at the University of Liverpool is currently defining new Internet- enabled approaches to enable greater collaboration across supply chains. Different e-business models and tools are focusing on different applications. Using inappropriate e- business models, tools or techniques will bring negative results instead of benefits to all the tiers in the supply network. Thus there are a number of issues to be considered before addressing Internet based supply network integration, in particular an understanding of supply chain management, the emergent business models and evaluating the effects of deploying e-business to the supply network or a particular tier. It is important to utilize a contingent approach to selecting the right e-business model to meet the specific supply chain requirements. This paper addresses the issues and provides a case study on the indirect materials supply networks.
Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia
A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.
The Data Management System network is a complex and important part of manned space platforms. Its efficient operation is vital to crew, subsystems and experiments. AI is being considered to aid in the initial design of the network and to augment the management of its operation. The Intelligent Resource Management for Local Area Networks (IRMA-LAN) project is concerned with the application of AI techniques to network configuration and management. A network simulation was constructed employing real time process scheduling for realistic loads, and utilizing the IEEE 802.4 token passing scheme. This simulation is an integral part of the construction of the IRMA-LAN system. From it, a causal model is being constructed for use in prediction and deep reasoning about the system configuration. An AI network design advisor is being added to help in the design of an efficient network. The AI portion of the system is planned to evolve into a dynamic network management aid. The approach, the integrated simulation, project evolution, and some initial results are described.
Carter, Dorothy R; DeChurch, Leslie A; Braun, Michael T; Contractor, Noshir S
Contemporary definitions of leadership advance a view of the phenomenon as relational, situated in specific social contexts, involving patterned emergent processes, and encompassing both formal and informal influence. Paralleling these views is a growing interest in leveraging social network approaches to study leadership. Social network approaches provide a set of theories and methods with which to articulate and investigate, with greater precision and rigor, the wide variety of relational perspectives implied by contemporary leadership theories. Our goal is to advance this domain through an integrative conceptual review. We begin by answering the question of why-Why adopt a network approach to study leadership? Then, we offer a framework for organizing prior research. Our review reveals 3 areas of research, which we term: (a) leadership in networks, (b) leadership as networks, and (c) leadership in and as networks. By clarifying the conceptual underpinnings, key findings, and themes within each area, this review serves as a foundation for future inquiry that capitalizes on, and programmatically builds upon, the insights of prior work. Our final contribution is to advance an agenda for future research that harnesses the confluent ideas at the intersection of leadership in and as networks. Leadership in and as networks represents a paradigm shift in leadership research-from an emphasis on the static traits and behaviors of formal leaders whose actions are contingent upon situational constraints, toward an emphasis on the complex and patterned relational processes that interact with the embedding social context to jointly constitute leadership emergence and effectiveness. (c) 2015 APA, all rights reserved.
Mochizuki, Atsushi; Fiedler, Bernold
In biological cells, chemical reaction pathways lead to complex network systems like metabolic networks. One experimental approach to the dynamics of such systems examines their "sensitivity": each enzyme mediating a reaction in the system is increased/decreased or knocked out separately, and the responses in the concentrations of chemicals or their fluxes are observed. In this study, we present a mathematical method, named structural sensitivity analysis, to determine the sensitivity of reaction systems from information on the network alone. We investigate how the sensitivity responses of chemicals in a reaction network depend on the structure of the network, and on the position of the perturbed reaction in the network. We establish and prove some general rules which relate the sensitivity response to the structure of the underlying network. We describe a hierarchical pattern in the flux response which is governed by branchings in the network. We apply our method to several hypothetical and real life chemical reaction networks, including the metabolic network of the Escherichia coli TCA cycle. Copyright © 2014 Elsevier Ltd. All rights reserved.
Full Text Available Due to the increasing complexity and heterogeneity of networks and services, many efforts have been made to develop intelligent techniques for management. Network intelligent management is a key technology for operating large heterogeneous data transmission networks. This paper presents a proposal for an architecture that integrates management object specifications and the knowledge of expert systems. We present a new approach named Integrated Expert Management, for learning objects based on expert management rules and describe the design and implementation of an integrated intelligent management platform based on OSI and Internet management models. The main contributions of our approach is the integration of both expert system and managed models, so we can make use of them to construct more flexible intelligent management network. The prototype SONAP (Software for Network Assistant and Performance is accuracy-aware since it can control and manage a network. We have tested our system on real data to the fault diagnostic in a telecommunication system of a power utility. The results validate the model and show a significant improvement with respect to the number of rules and the error rate in others systems.
Alistair McNair Senior
Full Text Available Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent advances in nutrition research, combining state-space models of nutritional geometry with agent-based models of systems biology, show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a tangible and practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit agent-based models that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition. Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interaction in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments.
Senior, Alistair M; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J
Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments.
We consider a nonlinear nonseparable functional approximation to the value function of a dynamic programming formulation for the network revenue management (RM) problem with customer choice. We propose a simultaneous dynamic programming approach to solve the resulting problem, which is a nonlinear optimization problem with nonlinear constraints. We show that our approximation leads to a tighter upper bound on optimal expected revenue than some known bounds in the literature. Our approach can ...
Sun Wei-Gang; Cao Jian-Ting; Wang Ru-Bin
In clinical practice, brain death is the irreversible end of all brain activity. Compared to current statistical methods for the determination of brain death, we focus on the approach of complex networks for real-world electroencephalography in its determination. Brain functional networks constructed by correlation analysis are derived, and statistical network quantities used for distinguishing the patients in coma or brain death state, such as average strength, clustering coefficient and average path length, are calculated. Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state. Our findings might provide valuable insights on the determination of brain death. (cross-disciplinary physics and related areas of science and technology)
The science of graphs and networks has become by now a well-established tool for modelling and analyzing a variety of systems with a large number of interacting components. Starting from the physical sciences, applications have spread rapidly to the natural and social sciences, as well as to economics, and are now further extended, in this volume, to the concept of innovations, viewed broadly. In an abstract, systems-theoretical approach, innovation can be understood as a critical event which destabilizes the current state of the system, and results in a new process of self-organization leading to a new stable state. The contributions to this anthology address different aspects of the relationship between innovation and networks. The various chapters incorporate approaches in evolutionary economics, agent-based modeling, social network analysis and econophysics and explore the epistemic tension between insights into economics and society-related processes, and the insights into new forms of complex dynamics.
O.L. Listes (Ovidiu); R. Dekker (Rommert)
textabstractIncreased uncertainty is one of the characteristics of product recovery networks. In particular the strategic design of their logistic infrastructure has to take uncertain information into account. In this paper we present stochastic programming based approaches by which a deterministic
Bets, van L.K.J.; Lamers, M.A.J.; Tatenhove, van J.P.M.
Conceptual approaches to thoroughly study governance of cruise tourism are lacking in the literature. Relying on Castells’ network society, we analyze how two interconnected flows of cruise ships and passengers are governed by a marine community of users and policy makers. Bonaire is used as a case
Home; Journals; Journal of Earth System Science; Volume 122; Issue 2. Using artificial neural network approach for modelling ... Nevertheless, water level and flow records are essential in hydrological analysis for designing related water works of flood management. Due to the complexity of the hydrological process, ...
Choi, Daejeong; Oh, In-Sue; Colbert, Amy E
We examined the relationships between the Five-Factor Model (FFM) of personality traits and three forms of organizational commitment (affective, normative, and continuance commitment) and their variability across individualistic and collectivistic cultures. Meta-analytic results based on 55 independent samples from 50 studies (N = 18,262) revealed that (a) all FFM traits had positive relationships with affective commitment; (b) all FFM traits had positive relationships with normative commitment; and (c) Emotional Stability, Extraversion, and Openness to Experience had negative relationships with continuance commitment. In particular, Agreeableness was found to be the trait most strongly related to both affective and normative commitment. The results also showed that Agreeableness had stronger relationships with affective and normative commitment in collectivistic cultures than in individualistic cultures. We provide theoretical and practical implications of these findings for personality, job attitudes, and employee selection and retention. (c) 2015 APA, all rights reserved).
Greitemeyer, Tobias; Mügge, Dirk O
Whether video game play affects social behavior is a topic of debate. Many argue that aggression and helping are affected by video game play, whereas this stance is disputed by others. The present research provides a meta-analytical test of the idea that depending on their content, video games do affect social outcomes. Data from 98 independent studies with 36,965 participants revealed that for both violent video games and prosocial video games, there was a significant association with social outcomes. Whereas violent video games increase aggression and aggression-related variables and decrease prosocial outcomes, prosocial video games have the opposite effects. These effects were reliable across experimental, correlational, and longitudinal studies, indicating that video game exposure causally affects social outcomes and that there are both short- and long-term effects.
Lent, Robert W; Sheu, Hung-Bin; Miller, Matthew J; Cusick, Megan E; Penn, Lee T; Truong, Nancy N
We tested the interest and choice portion of social-cognitive career theory (SCCT; Lent, Brown, & Hackett, 1994) in the context of science, technology, engineering, and mathematics (STEM) domains. Data from 143 studies (including 196 independent samples) conducted over a 30-year period (1983 through 2013) were subjected to meta-analytic path analyses. The interest/choice model was found to fit the data well over all samples as well as within samples composed primarily of women and men and racial/ethnic minority and majority persons. The model also accounted for large portions of the variance in interests and choice goals within each path analysis. Despite the general predictive utility of SCCT across gender and racial/ethnic groups, we did find that several parameter estimates differed by group. We present both the group similarities and differences and consider their implications for future research, intervention, and theory refinement. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Hagger, Martin S; Chan, Derwin K C; Protogerou, Cleo; Chatzisarantis, Nikos L D
Synthesizing research on social cognitive theories applied to health behavior is an important step in the development of an evidence base of psychological factors as targets for effective behavioral interventions. However, few meta-analyses of research on social cognitive theories in health contexts have conducted simultaneous tests of theoretically-stipulated pattern effects using path analysis. We argue that conducting path analyses of meta-analytic effects among constructs from social cognitive theories is important to test nomological validity, account for mediation effects, and evaluate unique effects of theory constructs independent of past behavior. We illustrate our points by conducting new analyses of two meta-analyses of a popular theory applied to health behaviors, the theory of planned behavior. We conducted meta-analytic path analyses of the theory in two behavioral contexts (alcohol and dietary behaviors) using data from the primary studies included in the original meta-analyses augmented to include intercorrelations among constructs and relations with past behavior missing from the original analysis. Findings supported the nomological validity of the theory and its hypotheses for both behaviors, confirmed important model processes through mediation analysis, demonstrated the attenuating effect of past behavior on theory relations, and provided estimates of the unique effects of theory constructs independent of past behavior. Our analysis illustrates the importance of conducting a simultaneous test of theory-stipulated effects in meta-analyses of social cognitive theories applied to health behavior. We recommend researchers adopt this analytic procedure when synthesizing evidence across primary tests of social cognitive theories in health. Copyright © 2016 Elsevier Inc. All rights reserved.
Rivas, T.; Taboada, J.; Ordonez, C.; Matias, J. M.
We describe the results of an expert system applied to the evaluation of samples of kaolin for industrial use in paper or ceramic manufacture. Different machine learning techniques - classification trees, support vector machines and Bayesian networks - were applied with the aim of evaluating and comparing their interpretability and prediction capacities. The predictive capacity of these models for the samples analyzed was highly satisfactory, both for ceramic quality and paper quality. However, Bayesian networks generally proved to be the most useful technique for our study, as this approach combines good predictive capacity with excellent interpretability of the kaolin quality structure, as it graphically represents relationships between variables and facilitates what-if analyses.
Mihovska, Albena D.
Abstract— Introducing intelligence by means of cognition for managing, protecting, processing, and delivering of information in mobile communication systems is the way towards ubiquitous, converged and secure communications. In this context, this paper introduces the concept of quality...... of information (QoI). QoI means QoS while all the requirements for dependability, security, privacy and trust are satisfied at the highest possible level. This work proposes and describes an approach to network monitoring in a heterogeneous communication environment based on use of cognitive techniques...... is an improved network performance in terms of maximized throughput and faster accessibility to services, minimized transport delay, improved network coverage and simplified security management. This is achieved by introducing an intelligent functionality that entails the use of cognitive learning algorithms...
Kustiawan, I.; Purnama, W.
Seamless mobility and service continuity anywhere at any time are an important issue in the wireless Internet. This research proposes a scheme to make handoff decisions effectively in heterogeneous wireless networks using a fuzzy system. Our design lies in an inference engine which takes RSS (received signal strength), data rate, network latency, and user preference as strategic determinants. The logic of our engine is realized on a UE (user equipment) side in faster reaction to network dynamics while roaming across different radio access technologies. The fuzzy system handles four metrics jointly to deduce a moderate decision about when to initiate handoff. The performance of our design is evaluated by simulating move-out mobility scenarios. Simulation results show that our scheme outperforms other approaches in terms of reducing unnecessary handoff.
Full Text Available Network intrusion starts off with a series of unsuccessful breakin attempts and results eventually with the permanent or transient failure of an authentication or authorization system. Due to the current complexity of authentication systems, clandestine attempts at intrusion generally take considerable time before the system gets compromised or damaging change is affected to the system giving administrators a window of opportunity to proactively detect and prevent intrusion. Therefore maintaining a high level of sensitivity to abnormal access patterns is a very effective way of preventing possible break-ins. Under normal circumstances, gross errors on the part of the user can cause authentication and authorization failures on all systems. A normal distribution of failed attempts should be tolerated while abnormal attempts should be recognized as such and flagged. But one cannot manage what one cannot measure. This paper proposes a method that can efficiently quantify the behaviour of users on a network so that transient changes in usage can be detected, categorized based on severity, and closely investigated for possible intrusion. The author proposes the identification of patterns in protocol usage within a network to categorize it for surveillance. Statistical anomaly detection, under which category this approach falls, generally uses simple statistical tests such as mean and standard deviation to detect behavioural changes. The author proposes a novel approach using spectral density as opposed to using time domain data, allowing a clear separation or access patterns based on periodicity. Once a spectral profile has been identified for network, deviations from this profile can be used as an indication of a destabilized or compromised network. Spectral analysis of access patterns is done using the Fast Fourier Transform (FFT, which can be computed in Θ(N log N operations. The paper justifies the use of this approach and presents preliminary
Grygorenko Tetyana M.
Full Text Available Methodical approaches to selecting strategic areas of managing the future location of franchise retail network outlets are presented. The main stages in the assessment of strategic areas of managing the future location of franchise retail network outlets have been determined and the evaluation criteria have been suggested. Since such selection requires consideration of a variety of indicators and directions of the assessment, the author proposes a scale of evaluation, which allows generalizing and organizing the research data and calculations of the previous stages of the analysis. The most important criteria and sequence of the selection of the potential franchisees for the franchise retail network have been identified, the technique for their evaluation has been proposed. The use of the suggested methodological approaches will allow the franchiser making sound decisions on the selection of potential target markets, minimizing expenditures of time and efforts on the selection of franchisees and hence optimizing the process of development of the franchise retail network, which will contribute to the formation of its structure.
Munoz, David Andres; Queupil, Juan Pablo; Fraser, Pablo
Purpose: The purpose of this paper is to analyze collaboration networks and their patterns among higher education institutions (HEIs) in Chile and the Latin American region. This will provide evidence to educational managements in order to properly allocate their efforts to improve collaboration. Design/methodology/approach: This quantitative…
Kerczewski, Robert J.; Chomos, Gerald J.; Griner, James H.; Mainger, Steven W.; Martzaklis, Konstantinos S.; Kachmar, Brian A.
Rapid growth in air travel has been projected to continue for the foreseeable future. To maintain a safe and efficient national and global aviation system, significant advances in communications systems supporting aviation are required. Satellites will increasingly play a critical role in the aeronautical communications network. At the same time, current ground-based communications links, primarily very high frequency (VHF), will continue to be employed due to cost advantages and legacy issues. Hence a hybrid satellite-terrestrial network, or group of networks, will emerge. The increased complexity of future aeronautical communications networks dictates that system-level modeling be employed to obtain an optimal system fulfilling a majority of user needs. The NASA Glenn Research Center is investigating the current and potential future state of aeronautical communications, and is developing a simulation and modeling program to research future communications architectures for national and global aeronautical needs. This paper describes the primary requirements, the current infrastructure, and emerging trends of aeronautical communications, including a growing role for satellite communications. The need for a hybrid communications system architecture approach including both satellite and ground-based communications links is explained. Future aeronautical communication network topologies and key issues in simulation and modeling of future aeronautical communications systems are described.
Hallinan, J S; James, K; Wipat, A
Large amounts of detailed biological data have been generated over the past few decades. Much of these data is freely available in over 1000 online databases; an enticing, but frustrating resource for microbiologists interested in a systems-level view of the structure and function of microbial cells. The frustration engendered by the need to trawl manually through hundreds of databases in order to accumulate information about a gene, protein, pathway, or organism of interest can be alleviated by the use of computational data integration to generated network views of the system of interest. Biological networks can be constructed from a single type of data, such as protein-protein binding information, or from data generated by multiple experimental approaches. In an integrated network, nodes usually represent genes or gene products, while edges represent some form of interaction between the nodes. Edges between nodes may be weighted to represent the probability that the edge exists in vivo. Networks may also be enriched with ontological annotations, facilitating both visual browsing and computational analysis via web service interfaces. In this review, we describe the construction, analysis of both single-data source and integrated networks, and their application to the inference of protein function in microbes. Copyright © 2011 Elsevier Ltd. All rights reserved.
Manser, Kristina; Hillebrand, Bas; Klein Woolthuis, R.J.A.; Ziggers, Gerrit Willem; Driessen, Paul H.; Bloemer, Josée
Over the last few decades, the industrial marketing literature and the business network literature have promoted a holistic approach to marketing and provided a framework for understanding interorganizational networks. However, our understanding of how interorganizational networks govern themselves
Manser, K.; Hillebrand, B.; Klein Woolthuis, R.J.A.; Ziggers, G.W.; Driessen, P.H.; Bloemer, J.M.M.; Klein Woolthuis, R.
Over the last few decades, the industrial marketing literature and the business network literature have promoted a holistic approach to marketing and provided a framework for understanding interorganizational networks. However, our understanding of how interorganizational networks govern themselves
Whitbred, Robert; Fonti, Fabio; Steglich, Christian; Contractor, Noshir
Structuration theory (ST) and network analysis are promising approaches for studying the emergence of communication networks. We offer a model that integrates the conceptual richness of structuration with the precision of relevant concepts and mechanisms offered from communication network research.
YongSeog Kim; W. Nick Street; Gary J. Russell; Filippo Menczer
One of the key problems in database marketing is the identification and profiling of households that are most likely to be interested in a particular product or service. Principal component analysis (PCA) of customer background information followed by logistic regression analysis of response behavior is commonly used by database marketers. In this paper, we propose a new approach that uses artificial neural networks (ANNs) guided by genetic algorithms (GAs) to target households. We show that ...
Cacace, Simone; Camilli, Fabio; De Maio, Raul; Tosin, Andrea
We consider a class of optimal control problems for measure-valued nonlinear transport equations describing traffic flow problems on networks. The objective isto minimise/maximise macroscopic quantities, such as traffic volume or average speed,controlling few agents, for example smart traffic lights and automated cars. The measuretheoretic approach allows to study in a same setting local and nonlocal drivers interactionsand to consider the control variables as additional measures interacting ...
Oksana Loginova; X. Henry Wang; Haibin Lu
In this paper we use mechanism design approach to find the optimal file-sharing mechanism in a peer-to-peer network. This mechanism improves upon existing incentive schemes. In particular, we show that peer-approved scheme is never optimal and service-quality scheme is optimal only under certain circumstances. Moreover, we find that the optimal mechanism can be implemented by a mixture of peer-approved and service-quality schemes.
Chiaruttini, C.; Roberto, V.
After discussing the current status of the automation in signal interpretation from seismic networks, a new approach, based on artificial-intelligence tecniques, is proposed. The knowledge of the human expert analyst is examined, with emphasis on its objects, strategies and reasoning techniques. It is argued that knowledge-based systems (or expert systems) provide the most appropriate tools for designing an automatic system, modelled on the expert behaviour
Dondo, Maxwell G.; Japkowicz, Nathalie; Smith, Reuben
Intrusion detection analysts are often swamped by multitudes of alerts originating from installed intrusion detection systems (IDS) as well as logs from routers and firewalls on the networks. Properly managing these alerts and correlating them to previously seen threats is critical in the ability to effectively protect a network from attacks. Manually correlating events can be a slow tedious task prone to human error. We present a two-stage alert correlation approach involving an artificial neural network (ANN) autoassociator and a single parameter decision threshold-setting unit. By clustering closely matched alerts together, this approach would be beneficial to the analyst. In this approach, alert attributes are extracted from each alert content and used to train an autoassociator. Based on the reconstruction error determined by the autoassociator, closely matched alerts are grouped together. Whenever a new alert is received, it is automatically categorised into one of the alert clusters which identify the type of attack and its severity level as previously known by the analyst. If the attack is entirely new and there is no match to the existing clusters, this would be appropriately reflected to the analyst. There are several advantages to using an ANN based approach. First, ANNs acquire knowledge straight from the data without the need for a human expert to build sets of domain rules and facts. Second, once trained, ANNs can be very fast, accurate and have high precision for near real-time applications. Finally, while learning, ANNs perform a type of dimensionality reduction allowing a user to input large amounts of information without fearing an effciency bottleneck. Thus, rather than storing the data in TCP Quad format (which stores only seven event attributes) and performing a multi-stage query on reduced information, the user can input all the relevant information available and instead allow the neural network to organise and reduce this knowledge in an
network inferred from a T cell immune response dataset. An SBN can also implement the function of an asynchronous PBN and is potentially useful in a hybrid approach in combination with a continuous or single-molecule level stochastic model. Conclusions Stochastic Boolean networks (SBNs are proposed as an efficient approach to modelling gene regulatory networks (GRNs. The SBN approach is able to recover biologically-proven regulatory behaviours, such as the oscillatory dynamics of the p53-Mdm2 network and the dynamic attractors in a T cell immune response network. The proposed approach can further predict the network dynamics when the genes are under perturbation, thus providing biologically meaningful insights for a better understanding of the dynamics of GRNs. The algorithms and methods described in this paper have been implemented in Matlab packages, which are attached as Additional files.
Caramella, D.; Poli, R.; Rucci, M.; Valli, G.
The problems usually faced in the development of automatic systems for MR and CT image analysis are briefly discussed. Afterward, an approach based on the integration of artificial neural networks and computer vision techniques which should be capable of overcoming the encountered difficulties is described. According to this approach, a system for the construction of 3D descriptions of the organs as imaged by MR or CT slice sequences has been developed. The architecture and preliminary results of this system are reported. (orig.) [de
Jeffrey Martin Spielberg
Full Text Available Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal pursuit processes (e.g., motivation has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity vital to goal pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures.
Paiman, Nuur Azreen; Hariri, Azian; Masood, Ibrahim
Prediction models are increasingly gaining popularity and had been used in numerous areas of studies to complement and fulfilled clinical reasoning and decision making nowadays. The adoption of such models assist physician's decision making, individual's behavior, and consequently improve individual outcomes and the cost-effectiveness of care. The objective of this paper is to reviewed articles related to risk prediction model in order to understand the suitable approach, development and the validation process of risk prediction model. A qualitative review of the aims, methods and significant main outcomes of the nineteen published articles that developed risk prediction models from numerous fields were done. This paper also reviewed on how researchers develop and validate the risk prediction models based on statistical and artificial neural network approach. From the review done, some methodological recommendation in developing and validating the prediction model were highlighted. According to studies that had been done, artificial neural network approached in developing the prediction model were more accurate compared to statistical approach. However currently, only limited published literature discussed on which approach is more accurate for risk prediction model development.
Full Text Available In some online social network services (SNSs, the members are allowed to label their relationships with others, and such relationships can be represented as the links with signed values (positive or negative. The networks containing such relations are named signed social networks (SSNs, and some real-world complex systems can be also modeled with SSNs. Given the information of the observed structure of an SSN, the link prediction aims to estimate the values of the unobserved links. Noticing that most of the previous approaches for link prediction are based on the members’ similarity and the supervised learning method, however, research work on the investigation of the hidden principles that drive the behaviors of social members are rarely conducted. In this paper, the deep belief network (DBN-based approaches for link prediction are proposed. Including an unsupervised link prediction model, a feature representation method and a DBN-based link prediction method are introduced. The experiments are done on the datasets from three SNSs (social networking services in different domains, and the results show that our methods can predict the values of the links with high performance and have a good generalization ability across these datasets.
Solmaz, Berkan; Dey, Soumyabrata; Rao, A. Ravishankar; Shah, Mubarak
Attention Deficit Hyperactivity Disorder (ADHD) is receiving lots of attention nowadays mainly because it is one of the common brain disorders among children and not much information is known about the cause of this disorder. In this study, we propose to use a novel approach for automatic classification of ADHD conditioned subjects and control subjects using functional Magnetic Resonance Imaging (fMRI) data of resting state brains. For this purpose, we compute the correlation between every possible voxel pairs within a subject and over the time frame of the experimental protocol. A network of voxels is constructed by representing a high correlation value between any two voxels as an edge. A Bag-of-Words (BoW) approach is used to represent each subject as a histogram of network features; such as the number of degrees per voxel. The classification is done using a Support Vector Machine (SVM). We also investigate the use of raw intensity values in the time series for each voxel. Here, every subject is represented as a combined histogram of network and raw intensity features. Experimental results verified that the classification accuracy improves when the combined histogram is used. We tested our approach on a highly challenging dataset released by NITRC for ADHD-200 competition and obtained promising results. The dataset not only has a large size but also includes subjects from different demography and edge groups. To the best of our knowledge, this is the first paper to propose BoW approach in any functional brain disorder classification and we believe that this approach will be useful in analysis of many brain related conditions.
Garg, Amit Kumar
Optical fibres have been developed as a transmission medium to carry traffic in order to provide various services in telecommunications platform. Failure of this fibre caused loss of data which can interrupt communication services. This paper has been focused only on survivable schemes in order to guarantee both protection and restoration in WDM optical networks. In this paper, a dynamic resilience approach has been proposed whose objective is to route the flows in a way which minimizes the total amount of bandwidth used for working and protection paths. In the proposed approach, path-based protection is utilized because it yields lower overhead and is also suitable for global optimization where, in case of a single link failure, all the flows utilizing the failed link are re-routed to a pre-computed set of paths. The simulation results demonstrate that proposed approach is much more efficient as it provides better quality of services (QoS) in terms of network resource utilization, blocking probability etc. as compared to conventional protection and restoration schemes. The proposed approach seems to offer an attractive combination of features, with both ring like speed and mesh-like efficiency.
Full Text Available Smart systems are today increasingly developed with the number of wireless sensor devices drastically increasing. They are implemented within several contexts throughout our environment. Thus, sensed data transported in ubiquitous systems are important, and the way to carry them must be efficient and reliable. For that purpose, several routing protocols have been proposed for wireless sensor networks (WSN. However, one stage that is often neglected before their deployment is the conformance testing process, a crucial and challenging step. Compared to active testing techniques commonly used in wired networks, passive approaches are more suitable to the WSN environment. While some works propose to specify the protocol with state models or to analyze them with simulators and emulators, we here propose a logic-based approach for formally specifying some functional requirements of a novel WSN routing protocol. We provide an algorithm to evaluate these properties on collected protocol execution traces. Further, we demonstrate the efficiency and suitability of our approach by its application into common WSN functional properties, as well as specific ones designed from our own routing protocol. We provide relevant testing verdicts through a real indoor testbed and the implementation of our protocol. Furthermore, the flexibility, genericity and practicability of our approach have been proven by the experimental results.
Che, Xiaoping; Maag, Stephane; Tan, Hwee-Xian; Tan, Hwee-Pink; Zhou, Zhangbing
Smart systems are today increasingly developed with the number of wireless sensor devices drastically increasing. They are implemented within several contexts throughout our environment. Thus, sensed data transported in ubiquitous systems are important, and the way to carry them must be efficient and reliable. For that purpose, several routing protocols have been proposed for wireless sensor networks (WSN). However, one stage that is often neglected before their deployment is the conformance testing process, a crucial and challenging step. Compared to active testing techniques commonly used in wired networks, passive approaches are more suitable to the WSN environment. While some works propose to specify the protocol with state models or to analyze them with simulators and emulators, we here propose a logic-based approach for formally specifying some functional requirements of a novel WSN routing protocol. We provide an algorithm to evaluate these properties on collected protocol execution traces. Further, we demonstrate the efficiency and suitability of our approach by its application into common WSN functional properties, as well as specific ones designed from our own routing protocol. We provide relevant testing verdicts through a real indoor testbed and the implementation of our protocol. Furthermore, the flexibility, genericity and practicability of our approach have been proven by the experimental results. PMID:26610495
Derek de Beurs
Full Text Available Although suicide is a major public health issue worldwide, we understand little of the onset and development of suicidal behaviour. Suicidal behaviour is argued to be the end result of the complex interaction between psychological, social and biological factors. Epidemiological studies resulted in a range of risk factors for suicidal behaviour, but we do not yet understand how their interaction increases the risk for suicidal behaviour. A new approach called network analysis can help us better understand this process as it allows us to visualize and quantify the complex association between many different symptoms or risk factors. A network analysis of data containing information on suicidal patients can help us understand how risk factors interact and how their interaction is related to suicidal thoughts and behaviour. A network perspective has been successfully applied to the field of depression and psychosis, but not yet to the field of suicidology. In this theoretical article, I will introduce the concept of network analysis to the field of suicide prevention, and offer directions for future applications and studies.
Arceo, Carlene Perpetua P; Jose, Editha C; Marin-Sanguino, Alberto; Mendoza, Eduardo R
This paper provides a framework to represent a Biochemical Systems Theory (BST) model (in either GMA or S-system form) as a chemical reaction network with power law kinetics. Using this representation, some basic properties and the application of recent results of Chemical Reaction Network Theory regarding steady states of such systems are shown. In particular, Injectivity Theory, including network concordance  and the Jacobian Determinant Criterion , a "Lifting Theorem" for steady states  and the comprehensive results of Müller and Regensburger  on complex balanced equilibria are discussed. A partial extension of a recent Emulation Theorem of Cardelli for mass action systems  is derived for a subclass of power law kinetic systems. However, it is also shown that the GMA and S-system models of human purine metabolism  do not display the reactant-determined kinetics assumed by Müller and Regensburger and hence only a subset of BST models can be handled with their approach. Moreover, since the reaction networks underlying many BST models are not weakly reversible, results for non-complex balanced equilibria are also needed. Copyright © 2015 Elsevier Inc. All rights reserved.
O'Connor, Edel; Smeaton, Alan F; O'Connor, Noel E; Regan, Fiona
Environmental monitoring is evolving towards large-scale and low-cost sensor networks operating reliability and autonomously over extended periods of time. Sophisticated analytical instrumentation such as chemo-bio sensors present inherent limitations because of the number of samples that they can take. In order to maximize their deployment lifetime, we propose the coordination of multiple heterogeneous information sources. We use rainfall radar images and information from a water depth sensor as input to a neural network (NN) to dictate the sampling frequency of a phosphate analyzer at the River Lee in Cork, Ireland. This approach shows varied performance for different times of the year but overall produces output that is very satisfactory for the application context in question. Our study demonstrates that even with limited training data, a system for controlling the sampling rate of the nutrient sensor can be set up and can improve the efficiency of the more sophisticated nodes of the sensor network.
Full Text Available Environmental monitoring is evolving towards large-scale and low-cost sensor networks operating reliability and autonomously over extended periods of time. Sophisticated analytical instrumentation such as chemo-bio sensors present inherent limitations because of the number of samples that they can take. In order to maximize their deployment lifetime, we propose the coordination of multiple heterogeneous information sources. We use rainfall radar images and information from a water depth sensor as input to a neural network (NN to dictate the sampling frequency of a phosphate analyzer at the River Lee in Cork, Ireland. This approach shows varied performance for different times of the year but overall produces output that is very satisfactory for the application context in question. Our study demonstrates that even with limited training data, a system for controlling the sampling rate of the nutrient sensor can be set up and can improve the efficiency of the more sophisticated nodes of the sensor network.
Frolov, I.; Vaguine, A.; Silin, A.
This paper describes a new approach in development of data flow control and investigation system for computer networks. This approach was developed and applied in the Moscow Radiotechnical Institute for control and investigations of Institute computer network. It allowed us to solve our network current problems successfully. Description of our approach is represented below along with the most interesting results of our work. (author)
Bastolla, Ugo; Roman, H. Eduardo; Vendruscolo, Michele
Structural requirements constrain the evolution of biological entities at all levels, from macromolecules to their networks, right up to populations of biological organisms. Classical models of molecular evolution, however, are focused at the level of the symbols - the biological sequence - rather than that of their resulting structure. Now recent advances in understanding the thermodynamics of macromolecules, the topological properties of gene networks, the organization and mutation capabilities of genomes, and the structure of populations make it possible to incorporate these key elements into a broader and deeply interdisciplinary view of molecular evolution. This book gives an account of such a new approach, through clear tutorial contributions by leading scientists specializing in the different fields involved.
Ferreri, Luca; Ivaldi, Marco; Daolio, Fabio; Giacobini, Mario; Rainoldi, Alberto; Tomassini, Marco
In order to investigate the behaviour of athletes in choosing sports, we analyse data from part of the We-Sport database, a vertical social network that links athletes through sports. In particular, we explore connections between people sharing common sports and the role of age and gender by applying "network science" approaches and methods. The results show a disassortative tendency of athletes in choosing sports, a negative correlation between age and number of chosen sports and a positive correlation between age of connected athletes. Some interesting patterns of connection between age classes are depicted. In addition, we propose a method to classify sports, based on the analyses of the behaviour of people practising them. Thanks to this brand new classifications, we highlight the links of class of sports and their unexpected features. We emphasise some gender dependency affinity in choosing sport classes.
Full Text Available Energy constraints restrict the lifetime of wireless sensor networks (WSNs with battery-powered nodes, which poses great challenges for their large scale application. In this paper, we propose a family of collaborative distributed scheduling approaches (CDSAs based on the Markov process to reduce the energy consumption of a WSN. The family of CDSAs comprises of two approaches: a one-step collaborative distributed approach and a two-step collaborative distributed approach. The approaches enable nodes to learn the behavior information of its environment collaboratively and integrate sleep scheduling with transmission scheduling to reduce the energy consumption. We analyze the adaptability and practicality features of the CDSAs. The simulation results show that the two proposed approaches can effectively reduce nodes’ energy consumption. Some other characteristics of the CDSAs like buffer occupation and packet delay are also analyzed in this paper. We evaluate CDSAs extensively on a 15-node WSN testbed. The test results show that the CDSAs conserve the energy effectively and are feasible for real WSNs.
Shashurin, A.; Fang, X.; Zemlyanov, D.; Keidar, M.
Graphene platelet networks (GPNs) comprised of randomly oriented graphene flakes two to three atomic layers thick are synthesized using a novel plasma-based approach. The approach uses a substrate capable of withstanding synthesis temperatures around 800 °C, but is fully independent of the substrate material. The synthesis occurs directly on the substrate surface without the necessity of any additional steps. GPNs were synthesized on various substrate materials including silicon (Si), thermally oxidized Si (SiO2), molybdenum (Mo), nickel (Ni) and copper (Cu), nickel-chromium (NiCr) alloy and alumina ceramics (Al2O3). The mismatch between the atomic structures of sp2 honeycomb carbon networks and the substrate material is fully eliminated shortly after the synthesis initiation, namely when about 100 nm thick deposits are formed on the substrate. GPN structures synthesized on a substrate at a temperature of about 800 °C are significantly more porous in comparison to the much denser packed amorphous carbon deposits synthesized at lower temperatures. The method proposed here can potentially revolutionize the area of electrochemical energy storage by offering a single-step direct approach for the manufacture of graphene-based electrodes for non-Faradaic supercapacitors. Mass production can be achieved using this method if a roll-to-roll system is utilized.
Babloyantz, A.; Ivanov, V.V.; Zrelov, P.V.
A new approach for the detection of slight changes in the form of the ECG signal is proposed. It is based on the approximation of raw ECG data inside each RR-interval by the expansion in polynomials of special type and on the classification of samples represented by sets of expansion coefficients using a layered feed-forward neural network. The transformation applied provides significantly simpler data structure, stability to noise and to other accidental factors. A by-product of the method is the compression of ECG data with factor 5
Ferguson, Christopher John
Video game violence has become a highly politicized issue for scientists and the general public. There is continuing concern that playing violent video games may increase the risk of aggression in players. Less often discussed is the possibility that playing violent video games may promote certain positive developments, particularly related to visuospatial cognition. The objective of the current article was to conduct a meta-analytic review of studies that examine the impact of violent video games on both aggressive behavior and visuospatial cognition in order to understand the full impact of such games. A detailed literature search was used to identify peer-reviewed articles addressing violent video game effects. Effect sizes r (a common measure of effect size based on the correlational coefficient) were calculated for all included studies. Effect sizes were adjusted for observed publication bias. Results indicated that publication bias was a problem for studies of both aggressive behavior and visuospatial cognition. Once corrected for publication bias, studies of video game violence provided no support for the hypothesis that violent video game playing is associated with higher aggression. However playing violent video games remained related to higher visuospatial cognition (r (x) = 0.36). Results from the current analysis did not support the conclusion that violent video game playing leads to aggressive behavior. However, violent video game playing was associated with higher visuospatial cognition. It may be advisable to reframe the violent video game debate in reference to potential costs and benefits of this medium.
Leppanen, Jenni; Sedgewick, Felicity; Treasure, Janet; Tchanturia, Kate
This meta-analytic review examines the theory of mind profiles in both patients with anorexia nervosa (AN) and autistic individuals. The studies examining theory of mind were divided into the following categories: emotional theory of mind, understanding simple social situations, understanding complex social interactions, and implicit social attribution. All included studies investigated differences between healthy control (HCs) individuals and people with AN or autistic people. Differences in theory of mind profile between people with AN and autistic people were explored by conducting moderator analyses. People with AN and autistic people showed a similar theory of mind profile, but autistic individuals showed greater difficulties, particularly in emotional theory of mind. Although both people with AN and autistic people have significant difficulties in all aspects of theory of mind relative to the HCs, some differences in the underlying profile may be present. However, due to relative paucity of theory of mind research among people with AN, further research is still needed before firm conclusion can be drawn. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.
Bogusch, Leah M; O'Brien, William H
Mindfulness-based interventions (MBIs) have improved psychological outcomes for multiple chronic health conditions, including diabetes. A meta-analytic review of the literature was conducted on all located studies (n = 14) investigating MBIs that targeted diabetes-related distress (DRD) and diabetes-related outcomes among people with Type 1 and Type 2 diabetes. PsychInfo, PubMed, Medline, and Web of Science were searched for MBIs that were designed to improve DRD and other secondary outcomes, including quality of life and measures of metabolic control. A meta-analysis of these outcomes uncovered small-to-moderate effect sizes for intervention studies measuring pretreatment to posttreatment changes in DRD and metabolic control among treatment group participants. However, the pretreatment to follow-up comparisons for DRD and metabolic control were small and unreliable. For control groups, all pre-treatment to post-treatment and pre-treatment to follow-up comparisons were unreliable for all outcomes. A moderate effect size for treatment-control comparisons was found for intervention studies measuring quality of life outcomes at posttreatment, but not at follow-up comparisons. All other effect sizes for treatment-control comparisons were unreliable. Limitations and implications for MBIs among individuals with diabetes are discussed.
Simoni, Jane M; Pearson, Cynthia R; Pantalone, David W; Marks, Gary; Crepaz, Nicole
Adherence to highly active antiretroviral therapy (HAART) is generally suboptimal, limiting the effectiveness of HAART. This meta-analytic review examined whether behavioral interventions addressing HAART adherence are successful in increasing the likelihood of a patient attaining 95% adherence or an undetectable HIV-1 RNA viral load (VL). We searched electronic databases from January 1996 to September 2005, consulted with experts in the field, and hand searched reference sections from relevant articles. Nineteen studies (with a total of 1839 participants) met the selection criteria of describing a randomized controlled trial among adults evaluating a behavioral intervention with HAART adherence or VL as an outcome. Random-effects models indicated that across studies, participants in the intervention arm were more likely than those in the control arm to achieve 95% adherence (odds ratio [OR] = 1.50, 95% confidence interval [CI]: 1.16 to 1.94); the effect was nearly significant for undetectable VL (OR = 1.25; 95% CI: 0.99 to 1.59). The intervention effect for 95% adherence was significantly stronger in studies that used recall periods of 2 weeks or 1 month (vs. =7 days). No other stratification variables (ie, study, sample, measurement, methodologic quality, intervention characteristics) moderated the intervention effect, but some potentially important factors were observed. In sum, various HAART adherence intervention strategies were shown to be successful, but more research is needed to identify the most efficacious intervention components and the best methods for implementing them in real-world settings with limited resources.
Nahrgang, Jennifer D; Morgeson, Frederick P; Hofmann, David A
In this article, we develop and meta-analytically test the relationship between job demands and resources and burnout, engagement, and safety outcomes in the workplace. In a meta-analysis of 203 independent samples (N = 186,440), we found support for a health impairment process and for a motivational process as mechanisms through which job demands and resources relate to safety outcomes. In particular, we found that job demands such as risks and hazards and complexity impair employees' health and positively relate to burnout. Likewise, we found support for job resources such as knowledge, autonomy, and a supportive environment motivating employees and positively relating to engagement. Job demands were found to hinder an employee with a negative relationship to engagement, whereas job resources were found to negatively relate to burnout. Finally, we found that burnout was negatively related to working safely but that engagement motivated employees and was positively related to working safely. Across industries, risks and hazards was the most consistent job demand and a supportive environment was the most consistent job resource in terms of explaining variance in burnout, engagement, and safety outcomes. The type of job demand that explained the most variance differed by industry, whereas a supportive environment remained consistent in explaining the most variance in all industries.
McMorris, Terry; Hale, Beverley J; Corbett, Jo; Robertson, Kevin; Hodgson, Christopher I
The primary purpose of this study was to examine, using meta-analytical measures, whether research into the performance of whole-body, psychomotor tasks following moderate and heavy exercise demonstrates an inverted-U effect. A secondary purpose was to compare the effects of acute exercise on tasks requiring static maintenance of posture versus dynamic, ballistic skills. Moderate intensity exercise was determined as being between 40% and 79% maximum power output (ẆMAX) or equivalent, while ≥80% ẆMAX was considered to be heavy. There was a significant difference (Zdiff=4.29, p=0.001, R(2)=0.42) between the mean effect size for moderate intensity exercise (g=0.15) and that for heavy exercise size (g=-0.86). These data suggest a catastrophe effect during heavy exercise. Mean effect size for static tasks (g=-1.24) was significantly different (Zdiff=3.24, p=0.001, R(2)=0.90) to those for dynamic/ballistic tasks (g=-0.30). The result for the static versus dynamic tasks moderating variables point to perception being more of an issue than peripheral fatigue for maintenance of static posture. The difference between this result and those found in meta-analyses examining the effects of acute exercise on cognition shows that, when perception and action are combined, the complexity of the interaction induces different effects to when cognition is detached from motor performance. Copyright © 2015 Elsevier Inc. All rights reserved.
Full Text Available Achieving sustainability in sports events requires effective management, political leadership, and ensuring that all stakeholders adhere to a sustainable philosophy. In order to stage a mega-event, tremendous infrastructure and construction are required with significant consumption of private and public resources. Multiple stakeholder groups are recognized as key entities responsible for an efficient trigger of a mega-event. The aim of this study is to conduct a systematic review of Korean sport literature with regard to CSR practices (ES-linked of different stakeholder groups and examine through a meta-analytic methodology their impact on the “images” of these groups. The CMA program was utilized as the main analysis tool to calculate the effect sizes from the selected empirical studies. The results indicated that CSR performance of governmental organizations had the highest effect size level on their own image (brand identity as perceived by visitors and participants. Among the stakeholder groups, effect size levels of their CSR performances were followed by those of corporate sponsors and professional teams. It was found that stakeholder groups are pressured to maintain a balance between financial performance, consumer well-being, and brand identity to bring in external investment.
Humphrey, Stephen E; Nahrgang, Jennifer D; Morgeson, Frederick P
The authors developed and meta-analytically examined hypotheses designed to test and extend work design theory by integrating motivational, social, and work context characteristics. Results from a summary of 259 studies and 219,625 participants showed that 14 work characteristics explained, on average, 43% of the variance in the 19 worker attitudes and behaviors examined. For example, motivational characteristics explained 25% of the variance in subjective performance, 2% in turnover perceptions, 34% in job satisfaction, 24% in organizational commitment, and 26% in role perception outcomes. Beyond motivational characteristics, social characteristics explained incremental variances of 9% of the variance in subjective performance, 24% in turnover intentions, 17% in job satisfaction, 40% in organizational commitment, and 18% in role perception outcomes. Finally, beyond both motivational and social characteristics, work context characteristics explained incremental variances of 4% in job satisfaction and 16% in stress. The results of this study suggest numerous opportunities for the continued development of work design theory and practice. (c) 2007 APA.
Rapport, Mark D; Orban, Sarah A; Kofler, Michael J; Friedman, Lauren M
Children with ADHD are characterized frequently as possessing underdeveloped executive functions and sustained attentional abilities, and recent commercial claims suggest that computer-based cognitive training can remediate these impairments and provide significant and lasting improvement in their attention, impulse control, social functioning, academic performance, and complex reasoning skills. The present review critically evaluates these claims through meta-analysis of 25 studies of facilitative intervention training (i.e., cognitive training) for children with ADHD. Random effects models corrected for publication bias and sampling error revealed that studies training short-term memory alone resulted in moderate magnitude improvements in short-term memory (d=0.63), whereas training attention did not significantly improve attention and training mixed executive functions did not significantly improve the targeted executive functions (both nonsignificant: 95% confidence intervals include 0.0). Far transfer effects of cognitive training on academic functioning, blinded ratings of behavior (both nonsignificant), and cognitive tests (d=0.14) were nonsignificant or negligible. Unblinded raters (d=0.48) reported significantly larger benefits relative to blinded raters and objective tests (both pacademic outcomes these training programs are intended to ameliorate. Collectively, meta-analytic results indicate that claims regarding the academic, behavioral, and cognitive benefits associated with extant cognitive training programs are unsupported in ADHD. The methodological limitations of the current evidence base, however, leave open the possibility that cognitive training techniques designed to improve empirically documented executive function deficits may benefit children with ADHD. © 2013.
Boccia, M; Barbetti, S; Piccardi, L; Guariglia, C; Ferlazzo, F; Giannini, A M; Zaidel, D W
Here we aimed at finding the neural correlates of the general aspect of visual aesthetic experience (VAE) and those more strictly correlated with the content of the artworks. We applied a general activation likelihood estimation (ALE) meta-analysis to 47 fMRI experiments described in 14 published studies. We also performed four separate ALE analyses in order to identify the neural substrates of reactions to specific categories of artworks, namely portraits, representation of real-world-visual-scenes, abstract paintings, and body sculptures. The general ALE revealed that VAE relies on a bilateral network of areas, and the individual ALE analyses revealed different maximal activation for the artworks' categories as function of their content. Specifically, different content-dependent areas of the ventral visual stream are involved in VAE, but a few additional brain areas are involved as well. Thus, aesthetic-related neural responses to art recruit widely distributed networks in both hemispheres including content-dependent brain areas of the ventral visual stream. Together, the results suggest that aesthetic responses are not independent of sensory, perceptual, and cognitive processes. Copyright © 2015 Elsevier Ltd. All rights reserved.
Sebastian H. Bitzenhofer
Full Text Available Coordinated patterns of electrical activity are critical for the functional maturation of neuronal networks, yet their interrogation has proven difficult in the developing brain. Optogenetic manipulations strongly contributed to the mechanistic understanding of network activation in the adult brain, but difficulties to specifically and reliably express opsins at neonatal age hampered similar interrogation of developing circuits. Here, we introduce a protocol that enables to control the activity of specific neuronal populations by light, starting from early postnatal development. We show that brain area-, layer- and cell type-specific expression of opsins by in utero electroporation (IUE, as exemplified for the medial prefrontal cortex (PFC and hippocampus (HP, permits the manipulation of neuronal activity in vitro and in vivo. Both individual and population responses to different patterns of light stimulation are monitored by extracellular multi-site recordings in the medial PFC of neonatal mice. The expression of opsins via IUE provides a flexible approach to disentangle the cellular mechanism underlying early rhythmic network activity, and to elucidate the role of early neuronal activity for brain maturation, as well as its contribution to neurodevelopmental disorders.
Bitzenhofer, Sebastian H; Ahlbeck, Joachim; Hanganu-Opatz, Ileana L
Coordinated patterns of electrical activity are critical for the functional maturation of neuronal networks, yet their interrogation has proven difficult in the developing brain. Optogenetic manipulations strongly contributed to the mechanistic understanding of network activation in the adult brain, but difficulties to specifically and reliably express opsins at neonatal age hampered similar interrogation of developing circuits. Here, we introduce a protocol that enables to control the activity of specific neuronal populations by light, starting from early postnatal development. We show that brain area-, layer- and cell type-specific expression of opsins by in utero electroporation (IUE), as exemplified for the medial prefrontal cortex (PFC) and hippocampus (HP), permits the manipulation of neuronal activity in vitro and in vivo . Both individual and population responses to different patterns of light stimulation are monitored by extracellular multi-site recordings in the medial PFC of neonatal mice. The expression of opsins via IUE provides a flexible approach to disentangle the cellular mechanism underlying early rhythmic network activity, and to elucidate the role of early neuronal activity for brain maturation, as well as its contribution to neurodevelopmental disorders.
Mengov, George D.; Zinovieva, Irina L.; Sotirov, George R.
In this paper we introduce a neural networks based approach to analyzing empirical data and models from work and organizational psychology (WOP), and suggest possible implications for the practice of managers and business consultants. With this method it becomes possible to have quantitative answers to a bunch of questions like: What are the characteristics of an organization in terms of its employees' motivation? What distinct attitudes towards the work exist? Which pattern is most desirable from the standpoint of productivity and professional achievement? What will be the dynamics of behavior as quantified by our method, during an ongoing organizational change or consultancy intervention? Etc. Our investigation is founded on the theoretical achievements of Maslow (1954, 1970) in human motivation, and of Hackman & Oldham (1975, 1980) in job diagnostics, and applies the mathematical algorithm of the dARTMAP variation (Carpenter et al., 1998) of the Adaptive Resonance Theory (ART) neural networks introduced by Grossberg (1976). We exploit the ART capabilities to visualize the knowledge accumulated in the network's long-term memory in order to interpret the findings in organizational research.
Sefcik, Lauren S; Wilson, Jennifer L; Papin, Jason A; Botchwey, Edward A
Microvascular remodeling is a complex process that includes many cell types and molecular signals. Despite a continued growth in the understanding of signaling pathways involved in the formation and maturation of new blood vessels, approximately half of all compounds entering clinical trials will fail, resulting in the loss of much time, money, and resources. Most pro-angiogenic clinical trials to date have focused on increasing neovascularization via the delivery of a single growth factor or gene. Alternatively, a focus on the concerted regulation of whole networks of genes may lead to greater insight into the underlying physiology since the coordinated response is greater than the sum of its parts. Systems biology offers a comprehensive network view of the processes of angiogenesis and arteriogenesis that might enable the prediction of drug targets and whether or not activation of the targets elicits the desired outcome. Systems biology integrates complex biological data from a variety of experimental sources (-omics) and analyzes how the interactions of the system components can give rise to the function and behavior of that system. This review focuses on how systems biology approaches have been applied to microvascular growth and remodeling, and how network analysis tools can be utilized to aid novel pro-angiogenic drug discovery.
Zhang, Xiaoge; Mahadevan, Sankaran; Deng, Xinyang
In practical applications of reliability assessment of a system in-service, information about the condition of a system and its components is often available in text form, e.g., inspection reports. Estimation of the system reliability from such text-based records becomes a challenging problem. In this paper, we propose a four-step framework to deal with this problem. In the first step, we construct an evidential network with the consideration of available knowledge and data. Secondly, we train a Naive Bayes text classification algorithm based on the past records. By using the trained Naive Bayes algorithm to classify the new records, we build interval basic probability assignments (BPA) for each new record available in text form. Thirdly, we combine the interval BPAs of multiple new records using an evidence combination approach based on evidence theory. Finally, we propagate the interval BPA through the evidential network constructed earlier to obtain the system reliability. Two numerical examples are used to demonstrate the efficiency of the proposed method. We illustrate the effectiveness of the proposed method by comparing with Monte Carlo Simulation (MCS) results. - Highlights: • We model reliability analysis with linguistic data using evidential network. • Two examples are used to demonstrate the efficiency of the proposed method. • We compare the results with Monte Carlo Simulation (MCS).
Full Text Available Embedded within large-scale protein interaction networks are signaling pathways that encode response cascades in the cell. Unfortunately, even for well-studied species like S. cerevisiae, only a fraction of all true protein interactions are known, which makes it difficult to reason about the exact flow of signals and the corresponding causal relations in the network. To help address this problem, we introduce a framework for predicting new interactions that aid connectivity between upstream proteins (sources and downstream transcription factors (targets of a particular pathway. Our algorithms attempt to globally minimize the distance between sources and targets by finding a small set of shortcut edges to add to the network. Unlike existing algorithms for predicting general protein interactions, by focusing on proteins involved in specific responses our approach homes-in on pathway-consistent interactions. We applied our method to extend pathways in osmotic stress response in yeast and identified several missing interactions, some of which are supported by published reports. We also performed experiments that support a novel interaction not previously reported. Our framework is general and may be applicable to edge prediction problems in other domains.
Mehtab Singh Kahlon
An ad-hoc wireless network is a collection of wireless mobile nodes that self-configure to construct a network without the need for any established infrastructure or backbone. Ad hoc networks use mobile nodes to enable communication outside wireless transmission range. With the advancement in wireless communications, more and more wireless networks appear, e.g., Mobile Ad Hoc Network (MANET), Wireless Sensor Network (WSN), etc. So, in this paper we have discussed Ad Hoc Networks along with it...
Daniel B Larremore
Full Text Available The var genes of the human malaria parasite Plasmodium falciparum present a challenge to population geneticists due to their extreme diversity, which is generated by high rates of recombination. These genes encode a primary antigen protein called PfEMP1, which is expressed on the surface of infected red blood cells and elicits protective immune responses. Var gene sequences are characterized by pronounced mosaicism, precluding the use of traditional phylogenetic tools that require bifurcating tree-like evolutionary relationships. We present a new method that identifies highly variable regions (HVRs, and then maps each HVR to a complex network in which each sequence is a node and two nodes are linked if they share an exact match of significant length. Here, networks of var genes that recombine freely are expected to have a uniformly random structure, but constraints on recombination will produce network communities that we identify using a stochastic block model. We validate this method on synthetic data, showing that it correctly recovers populations of constrained recombination, before applying it to the Duffy Binding Like-α (DBLα domain of var genes. We find nine HVRs whose network communities map in distinctive ways to known DBLα classifications and clinical phenotypes. We show that the recombinational constraints of some HVRs are correlated, while others are independent. These findings suggest that this micromodular structuring facilitates independent evolutionary trajectories of neighboring mosaic regions, allowing the parasite to retain protein function while generating enormous sequence diversity. Our approach therefore offers a rigorous method for analyzing evolutionary constraints in var genes, and is also flexible enough to be easily applied more generally to any highly recombinant sequences.
Larremore, Daniel B.; Clauset, Aaron; Buckee, Caroline O.
The var genes of the human malaria parasite Plasmodium falciparum present a challenge to population geneticists due to their extreme diversity, which is generated by high rates of recombination. These genes encode a primary antigen protein called PfEMP1, which is expressed on the surface of infected red blood cells and elicits protective immune responses. Var gene sequences are characterized by pronounced mosaicism, precluding the use of traditional phylogenetic tools that require bifurcating tree-like evolutionary relationships. We present a new method that identifies highly variable regions (HVRs), and then maps each HVR to a complex network in which each sequence is a node and two nodes are linked if they share an exact match of significant length. Here, networks of var genes that recombine freely are expected to have a uniformly random structure, but constraints on recombination will produce network communities that we identify using a stochastic block model. We validate this method on synthetic data, showing that it correctly recovers populations of constrained recombination, before applying it to the Duffy Binding Like-α (DBLα) domain of var genes. We find nine HVRs whose network communities map in distinctive ways to known DBLα classifications and clinical phenotypes. We show that the recombinational constraints of some HVRs are correlated, while others are independent. These findings suggest that this micromodular structuring facilitates independent evolutionary trajectories of neighboring mosaic regions, allowing the parasite to retain protein function while generating enormous sequence diversity. Our approach therefore offers a rigorous method for analyzing evolutionary constraints in var genes, and is also flexible enough to be easily applied more generally to any highly recombinant sequences. PMID:24130474
Fujiwara, Naoya; Kirchen, Kathrin; Donges, Jonathan F.; Donner, Reik V.
Complex network approaches have been successfully applied for studying transport processes in complex systems ranging from road, railway, or airline infrastructures over industrial manufacturing to fluid dynamics. Here, we utilize a generic framework for describing the dynamics of geophysical flows such as ocean currents or atmospheric wind fields in terms of Lagrangian flow networks. In this approach, information on the passive advection of particles is transformed into a Markov chain based on transition probabilities of particles between the volume elements of a given partition of space for a fixed time step. We employ perturbation-theoretic methods to investigate the effects of modifications of transport processes in the underlying flow for three different problem classes: efficient absorption (corresponding to particle trapping or leaking), constant input of particles (with additional source terms modeling, e.g., localized contamination), and shifts of the steady state under probability mass conservation (as arising if the background flow is perturbed itself). Our results demonstrate that in all three cases, changes to the steady state solution can be analytically expressed in terms of the eigensystem of the unperturbed flow and the perturbation itself. These results are potentially relevant for developing more efficient strategies for coping with contaminations of fluid or gaseous media such as ocean and atmosphere by oil spills, radioactive substances, non-reactive chemicals, or volcanic aerosols.
Michalec, Barret; Grbic, Douglas; Veloski, J Jon; Cuddy, Monica M; Hafferty, Frederic W
Minimal attention has been paid to what factors may predict peer nomination or how peer nominations might exhibit a clustering effect. Focusing on the homophily principle that "birds of a feather flock together," and using a social network analysis approach, the authors investigated how certain student- and/or school-based factors might predict the likelihood of peer nomination, and the clusters, if any, that occur among those nominations. In 2013, the Jefferson Longitudinal Study of Medical Education included a special instrument to evaluate peer nominations. A total of 211 (81%) of 260 graduating medical students from the Sidney Kimmel Medical College responded to the peer nomination question. Data were analyzed using a relational contingency table and an ANOVA density model. Although peer nominations did not cluster around gender, age, or class rank, those students within an accelerated program, as well as those entering certain specialties, were more likely to nominate each other. The authors suggest that clerkships in certain specialties, as well as the accelerated program, may provide structured opportunities for students to connect and integrate, and that these opportunities may have an impact on peer nomination. The findings suggest that social network analysis is a useful approach to examine various aspects of peer nomination processes. The authors discuss implications regarding harnessing social cohesion within clinical clerkships, the possible development of siloed departmental identity and in-group favoritism, and future research possibilities.
Li, Rui; Chen, Kewei; Zhang, Nan; Fleisher, Adam S.; Li, Yao; Wu, Xia
This work proposed to use the linear Gaussian Bayesian network (BN) to construct the effective connectivity model of the brain's default mode network (DMN), a set of regions characterized by more increased neural activity during rest-state than most goal-oriented tasks. In a complete unsupervised data-driven manner, Bayesian information criterion (BIC) based learning approach was utilized to identify a highest scored network whose nodes (brain regions) were selected based on the result from the group independent component analysis (Group ICA) examining the DMN. We put forward to adopt the statistical significance testing method for regression coefficients used in stepwise regression analysis to further refine the network identified by BIC. The final established BN, learned from the functional magnetic resonance imaging (fMRI) data acquired from 12 healthy young subjects during rest-state, revealed that the hippocampus (HC) was the most influential brain region that affected activities in all other regions included in the BN. In contrast, the posterior cingulate cortex (PCC) was influenced by other regions, but had no reciprocal effects on any other region. Overall, the configuration of our BN illustrated that a prominent connection from HC to PCC existed in the DMN.
Full Text Available Data mining is nontrivial extraction of implicit, previously unknown and potential useful information from the data. For a database with number of records and for a set of classes such that each record belongs to one of the given classes, the problem of classification is to decide the class to which the given record belongs. The classification problem is also to generate a model for each class from given data set. We are going to make use of supervised classification in which we have training dataset of record, and for each record the class to which it belongs is known. There are many approaches to supervised classification. Decision tree is attractive in data mining environment as they represent rules. Rules can readily expressed in natural languages and they can be even mapped o database access languages. Now a days classification based on decision trees is one of the important problems in data mining which has applications in many areas. Now a days database system have become highly distributed, and we are using many paradigms. we consider the problem of inducing decision trees in a large distributed network of highly distributed databases. The classification based on decision tree can be done on the existence of distributed databases in healthcare and in bioinformatics, human computer interaction and by the view that these databases are soon to contain large amounts of data, characterized by its high dimensionality. Current decision tree algorithms would require high communication bandwidth, memory, and they are less efficient and scalability reduces when executed on such large volume of data. So there are some approaches being developed to improve the scalability and even approaches to analyse the data distributed over a network.[keywords: Data mining, Decision tree, decision tree induction, distributed data, classification
Johnson, C. E.; Aikin, K. E.
While seismic networks have expanded over the past few decades, and social needs for accurate and timely information has increased dramatically, approaches to the operational needs of both global and regional seismic observatories have been slow to adopt new technologies. This presentation presents the xQuake system that provides a fresh approach to seismic network analytics based on complexity theory and an adaptive architecture of streaming connected microservices as diverse data (picks, beams, and other data) flow into a final, curated catalog of events. The foundation for xQuake is the xGraph (executable graph) framework that is essentially a self-organizing graph database. An xGraph instance provides both the analytics as well as the data storage capabilities at the same time. Much of the analytics, such as synthetic annealing in the detection process and an evolutionary programing approach for event evolution, draws from the recent GLASS 3.0 seismic associator developed by and for the USGS National Earthquake Information Center (NEIC). In some respects xQuake is reminiscent of the Earthworm system, in that it comprises processes interacting through store and forward rings; not surprising as the first author was the lead architect of the original Earthworm project when it was known as "Rings and Things". While Earthworm components can easily be integrated into the xGraph processing framework, the architecture and analytics are more current (e.g. using a Kafka Broker for store and forward rings). The xQuake system is being released under an unrestricted open source license to encourage and enable sthe eismic community support in further development of its capabilities.
Boccia, Maddalena; Piccardi, Laura; Palermo, Liana; Nori, Raffaella; Palmiero, Massimiliano
Many studies have assessed the neural underpinnings of creativity, failing to find a clear anatomical localization. We aimed to provide evidence for a multi-componential neural system for creativity. We applied a general activation likelihood estimation (ALE) meta-analysis to 45 fMRI studies. Three individual ALE analyses were performed to assess creativity in different cognitive domains (Musical, Verbal, and Visuo-spatial). The general ALE revealed that creativity relies on clusters of activations in the bilateral occipital, parietal, frontal, and temporal lobes. The individual ALE revealed different maximal activation in different domains. Musical creativity yields activations in the bilateral medial frontal gyrus, in the left cingulate gyrus, middle frontal gyrus, and inferior parietal lobule and in the right postcentral and fusiform gyri. Verbal creativity yields activations mainly located in the left hemisphere, in the prefrontal cortex, middle and superior temporal gyri, inferior parietal lobule, postcentral and supramarginal gyri, middle occipital gyrus, and insula. The right inferior frontal gyrus and the lingual gyrus were also activated. Visuo-spatial creativity activates the right middle and inferior frontal gyri, the bilateral thalamus and the left precentral gyrus. This evidence suggests that creativity relies on multi-componential neural networks and that different creativity domains depend on different brain regions. PMID:26322002
Full Text Available Understanding the functions of different brain areas has represented a major endeavor of contemporary neurosciences. The purpose of this paper was to pinpoint the connectivity of Brodmann area 20 (BA20 (inferior temporal gyrus, fusiform gyrus in language tasks. A meta-analysis was conducted to assess the language network in which BA20 is involved. The DataBase of Brainmap was used; 11 papers corresponding to 12 experimental conditions with a total of 207 subjects were included in this analysis. Our results demonstrated seven clusters of activation including other temporal lobe areas (BA3, BA21, the insula, and the prefrontal cortex; minor clusters in the cingulate gyrus and the occipital lobe were observed; however, the volumes of all the activation clusters were small. Our results suggest that regardless of BA20 having certain participation in language processes it cannot be considered as a core language processing area (Wernicke’s area; nonetheless, it could be regarded as kind of language processing marginal area, participating in “extended Wernicke’s area” or simply “Wernicke’s system.” It is suggested that “core Wernicke’s area” roughly corresponds to BA21, BA22, BA41, and BA42, while a “language associations area” roughly corresponds to BA20, BA37, BA38, BA39, and BA40 (“extended Wernicke’s area” or “Wernicke’s system”.
Full Text Available Many studies have assessed the neural underpinnings of creativity, failing to find a clear anatomical localization. We aimed to provide evidence for a multi-componential neural system for creativity. We applied a general activation likelihood estimation (ALE meta-analysis to 45 fMRI studies. Three individual ALE analyses were performed to assess creativity in different cognitive domains (Musical, Verbal and Visuo-spatial. The general ALE revealed that creativity relies on clusters of activations in the bilateral occipital, parietal, frontal and temporal lobes. The individual ALE revealed different maximal activation in different domains. Musical creativity yields activations in the bilateral medial frontal gyrus, in the left cingulate gyrus, middle frontal gyrus and inferior parietal lobule and in the right postcentral and fusiform gyri. Verbal creativity yields activations mainly located in the left hemisphere, in the prefrontal cortex, middle and superior temporal gyri, inferior parietal lobule, postcentral and supramarginal gyri, middle occipital gyrus and insula. The right inferior frontal gyrus and the lingual gyrus were also activated. Visuo-spatial creativity activates the right middle and inferior frontal gyri, the bilateral thalamus and the left precentral gyrus. This evidence suggests that creativity relies on multi-componential neural networks and that different creativity domains depend on different brain regions.
Full Text Available Wireless Sensor Network (WSN can facilitate the process of monitoring the crops through agriculture monitoring network. However, it is challenging to implement the agriculture monitoring network in large scale and large distributed area. Typically, a large and dense network as a form of multihop network is used to establish communication between source and destination. This network continuously monitors the crops without sensitivity classification that can lead to message collision and packets drop. Retransmissions of drop messages can increase the energy consumption and delay. Therefore, to ensure a high quality of service (QoS, we propose an agriculture monitoring network that monitors the crops based on their sensitivity conditions wherein the crops with higher sensitivity are monitored constantly, while less sensitive crops are monitored occasionally. This approach selects a set of nodes rather than utilizing all the nodes in the network which reduces the power consumption in each node and network delay. The QoS of the proposed classified based approach is compared with the nonclassified approach in two scenarios; the backoff periods are changed in the first scenario while the numbers of nodes are changed in the second scenario. The simulation results demonstrate that the proposed approach outperforms the nonclassified approach on different test scenarios.
Full Text Available Working memory training has been increasingly popular in the last year. Previous studies has shown that children with intellectual disabilities have low working memory capacity and therefore have a great potential for improvement by this type of intervention. The aim of this study was to investigate the effect of working memory and cognitive training for children with intellectual disabilities. The effects reported in previous studies have varied and therefore meta-analysis of articles in the major databases was conducted. Inclusion criteria included to have a pretest-posttest design with a training group and a control group and to have measures of working memory or short-term memory. Ten studies with 28 comparisons were included. The results reveal a significant overall pretest-posttest small effect size for of working memory training for children with intellectual disabilities compared to controls. A mixed working memory approach, considering both verbal and visuo-spatial components and working mainly on strategies, was the only significantly effective training type with a medium effect size. The most commonly reported training type with 60 percent of the included comparisons, visuo-spatial working memory training, had a non-significant effect size that was close to zero. We conclude that even if there is an overall effect of working memory training, a mixed working memory approach appears to cause this effect. Given the few studies included and the different characteristics of the included studies, interpretations should be done with caution. However, different types of interventions appear to have different effects. Even if the results were promising, more studies are needed to better understand how to design an effective working memory intervention for this group and to understand if, and how, these short-term effects remains over time and transfer to everyday activities.
Full Text Available Conference on Ambient Systems, Networks and Technologies (ANT-2014) Approach to Sensor Node Calibration for Efficient Localisation in Wireless Sensor Networks in Realistic Scenarios Martin K. Mwilaa, Karim Djouanib, Anish Kurienc,∗ a...
Social network analysis (SNA) is based on a conceptual network representation of social interactions and is an invaluable tool for conservation professionals to increase collaboration, improve information flow, and increase efficiency. We present two approaches to constructing in...
Kang, Guoliang; Li, Jun; Tao, Dacheng
Recent years have witnessed the success of deep neural networks in dealing with a plenty of practical problems. Dropout has played an essential role in many successful deep neural networks, by inducing regularization in the model training. In this paper, we present a new regularized training approach: Shakeout. Instead of randomly discarding units as Dropout does at the training stage, Shakeout randomly chooses to enhance or reverse each unit's contribution to the next layer. This minor modification of Dropout has the statistical trait: the regularizer induced by Shakeout adaptively combines L0, L1 and L2 regularization terms. Our classification experiments with representative deep architectures on image datasets MNIST, CIFAR-10 and ImageNet show that Shakeout deals with over-fitting effectively and outperforms Dropout. We empirically demonstrate that Shakeout leads to sparser weights under both unsupervised and supervised settings. Shakeout also leads to the grouping effect of the input units in a layer. Considering the weights in reflecting the importance of connections, Shakeout is superior to Dropout, which is valuable for the deep model compression. Moreover, we demonstrate that Shakeout can effectively reduce the instability of the training process of the deep architecture.
Lensa, W. von
The present situation of nuclear power in general and of the innovative nuclear reactor systems in particular requires more comprehensive, coordinated R and D efforts on a broad international level to respond to today's requirements with respect to public and economic acceptance as well as to globalization trends and global environmental problems. HTGR technology development has already reached a high degree of maturity that will be complemented by the operation of the two new test reactors in Japan and China, representing technological milestones for the demonstration of HTGR safety characteristics and Nuclear Process Heat generation capabilities. It is proposed by the IAEA 'International Working Group on Gas-Cooled Reactors' to establish a 'Global HTGR R and D Network' on basic HTGR technology for the stable, long-term advancement of the specific HTGR features and as a basis for the future market introduction of this innovative reactor system. The background and the motivation for this approach are illustrated, as well as first proposals on the main objectives, the structure and the further procedures for the implementation of such a multinational working sharing R and D network. Modern telecooperation methods are foreseen as an interactive tool for effective communication and collaboration on a global scale. (author)
This authored monograph covers a viability to approach to traffic management by advising to vehicles circulated on the network the velocity they should follow for satisfying global traffic conditions;. It presents an investigation of three structural innovations: The objective is to broadcast at each instant and at each position the advised celerity to vehicles, which could be read by auxiliary speedometers or used by cruise control devices. Namely, 1. Construct regulation feedback providing at each time and position advised velocities (celerities) for minimizing congestion or other requirements. 2. Taking into account traffic constraints of different type, the first one being to remain on the roads, to stop at junctions, etc. 3. Use information provided by the probe vehicles equipped with GPS to the traffic regulator; 4. Use other global traffic measures of vehicles provided by different types of sensors; These results are based on convex analysis, intertemporal optimization and viability theory as mathemati...
Full Text Available This paper focuses on a social marketing project proposal for a community in a social housing neighborhood in Faro, in southern Portugal. The aim of the research is to discuss the possibility of the implementation of a neighborhood network, using a social marketing approach with the goal of strengthening the ties of cooperation, solidarity and friendship between the inhabitants of the neighborhood with a view to fostering social cohesion in the city. The paper offers a theoretical and empirical discussion about the characteristics of particular areas designated as social housing neighborhoods. Data collection was performed in loco by giving a questionnaire to the inhabitants of the neighborhood and by direct observation. The results facilitated a balance between the needs of the residents and their ability to help their neighbors. The results are followed by a discussion and a proposal for a social marketing project targeted to the neighborhood under study.
Sugden, Nicole A; Marquis, Alexandra R
Infants show facility for discriminating between individual faces within hours of birth. Over the first year of life, infants' face discrimination shows continued improvement with familiar face types, such as own-race faces, but not with unfamiliar face types, like other-race faces. The goal of this meta-analytic review is to provide an effect size for infants' face discrimination ability overall, with own-race faces, and with other-race faces within the first year of life, how this differs with age, and how it is influenced by task methodology. Inclusion criteria were (a) infant participants aged 0 to 12 months, (b) completing a human own- or other-race face discrimination task, (c) with discrimination being determined by infant looking. Our analysis included 30 works (165 samples, 1,926 participants participated in 2,623 tasks). The effect size for infants' face discrimination was small, 6.53% greater than chance (i.e., equal looking to the novel and familiar). There was a significant difference in discrimination by race, overall (own-race, 8.18%; other-race, 3.18%) and between ages (own-race: 0- to 4.5-month-olds, 7.32%; 5- to 7.5-month-olds, 9.17%; and 8- to 12-month-olds, 7.68%; other-race: 0- to 4.5-month-olds, 6.12%; 5- to 7.5-month-olds, 3.70%; and 8- to 12-month-olds, 2.79%). Multilevel linear (mixed-effects) models were used to predict face discrimination; infants' capacity to discriminate faces is sensitive to face characteristics including race, gender, and emotion as well as the methods used, including task timing, coding method, and visual angle. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Geraldina F Gaastra
Full Text Available Children with attention-deficit/hyperactivity disorder (ADHD often exhibit problem behavior in class, which teachers often struggle to manage due to a lack of knowledge and skills to use classroom management strategies. The aim of this meta-analytic review was to determine the effectiveness of several types of classroom interventions (antecedent-based, consequence-based, self-regulation, combined that can be applied by teachers in order to decrease off-task and disruptive classroom behavior in children with symptoms of ADHD. A second aim was to identify potential moderators (classroom setting, type of measure, students' age, gender, intelligence, and medication use. Finally, it was qualitatively explored whether the identified classroom interventions also directly or indirectly affected behavioral and academic outcomes of classmates. Separate meta-analyses were performed on standardized mean differences (SMDs for 24 within-subjects design (WSD and 76 single-subject design (SSD studies. Results showed that classroom interventions reduce off-task and disruptive classroom behavior in children with symptoms of ADHD (WSDs: MSMD = 0.92; SSDs: MSMD = 3.08, with largest effects for consequence-based (WSDs: MSMD = 1.82 and self-regulation interventions (SSDs: MSMD = 3.61. Larger effects were obtained in general education classrooms than in other classroom settings. No reliable conclusions could be formulated about moderating effects of type of measure and students' age, gender, intelligence, and medication use, mainly because of power problems. Finally, classroom interventions appeared to also benefit classmates' behavioral and academic outcomes.
Schneider, Martha; Voracek, Martin; Tran, Ulrich S
Humor and mental health are interconnected as is evidenced by a large number of studies. However, associations are only small and inconsistent as the operationalization of humor poses a methodological challenge. The Humor Styles Questionnaire (HSQ) differentiates four humor styles that might be beneficial or harmful to mental health. The aim of the present study was to meta-analytically aggregate studies using the HSQ to assess the associations of different humor styles with four areas of mental health (self-esteem, life satisfaction, optimism, depression). An extensive electronic database literature search identified 37 studies that reported correlations between the HSQ scales and the four areas of mental health in 45 independent samples (total N = 12,734). In total, 16 meta-analyses were conducted. Moderating effects of participant age, sex, and geographic region were examined via subgroup analyses and meta-regression. Humor styles differed in terms of their associations with mental health. Health-promoting humor styles were overall positively correlated with mental health (small-to-medium effect sizes). Self-defeating humor was overall negatively correlated with mental health. Aggressive humor was overall unrelated with mental health. Moderator analyses suggested geographic differences (Eastern vs. Western samples) and sex differences for some of these associations. Fostering specific humor styles may be beneficial for mental health. In addition, observing the habitual use of humor styles might help therapists to develop a better understanding of their clients. Differences in the utilization and the correlates of humor styles in Eastern and Western societies, and sex differences, need to be addressed in future research. © 2018 Scandinavian Psychological Associations and John Wiley & Sons Ltd.
Faber, Aida; Dubé, Laurette; Knäuper, Bärbel
Attachment relationships play an important role in people's wellbeing and affliction with physical and mental illnesses, including eating disorders. Seven reviews from the clinical field have consistently shown that higher attachment insecurity-failure to form trusting and reliable relationships with others-systematically characterized individuals with eating disorders. Nevertheless, to date, it is unclear whether (and if so how) these findings apply to the population at large. Consequently, the objective of the present meta-analysis is to quantify the relationship between attachment and unhealthy and healthy eating in the general population. Data from 70 studies and 19,470 participants were converted into r effect sizes and analysed. Results showed that higher attachment insecurity (r = 0.266), anxiety (r = 0.271), avoidance (r = 0.119), and fearfulness (r = 0.184) was significantly associated with more unhealthy eating behaviors, ps = 0.000; conversely, higher attachment security correlated with lower unhealthy eating behaviors (r = -0.184, p = 0.000). This relationship did not vary across type of unhealthy eating behavior (i.e., binge eating, bulimic symptoms, dieting, emotional eating, and unhealthy food consumption). The little exploratory evidence concerning healthy eating and attachment was inconclusive with one exception-healthy eating was associated with lower attachment avoidance (r = -0.211, p = 0.000). Our results extend previous meta-analytic findings to show that lack of trusting and reliable relationships does not only set apart eating disordered individuals from controls, but also characterizes unhealthy eating behaviors in the general population. More evidence is needed to determine how attachment and healthy eating are linked and assess potential mechanisms influencing the attachment-eating relationship. Copyright © 2017 Elsevier Ltd. All rights reserved.
Pedroche, Francisco; Romance, Miguel; Criado, Regino
In this paper, we present a new view of the PageRank algorithm inspired by multiplex networks. This new approach allows to introduce a new centrality measure for classic complex networks and a new proposal to extend the usual PageRank algorithm to multiplex networks. We give some analytical relations between these new approaches and the classic PageRank centrality measure, and we illustrate the new parameters presented by computing them on real underground networks.
Pedroche, Francisco; Romance, Miguel; Criado, Regino
In this paper, we present a new view of the PageRank algorithm inspired by multiplex networks. This new approach allows to introduce a new centrality measure for classic complex networks and a new proposal to extend the usual PageRank algorithm to multiplex networks. We give some analytical relations between these new approaches and the classic PageRank centrality measure, and we illustrate the new parameters presented by computing them on real underground networks.
Rincón-Pérez, Irene; Sánchez-Carmona, Alberto J; Albert, Jacobo; Hinojosa, José A
Response inhibition has been shown to be associated with monoamine-related gene polymorphisms, although evidence is inconclusive. To comprehensively examine these genotype effects on behavioural correlates of response inhibition in non-clinical adult populations, we performed a two-step approach. A systematic review of studies using Go/No-Go and/or Stop-Signal paradigms was first carried out. Thirty-eight eligible research articles were identified, which examined over 15 candidate genes. Remarkably, no firm conclusions could be drawn from these studies. Thus, in a second step, we conducted meta-analyses using random effects models on those polymorphisms that had previously been investigated in at least three studies. Specifically, data from 11 studies was analysed in three meta-analyses for the following polymorphisms: SLC6A3 3'UTR VNTR (k=6 samples; n=1463 participants), COMT Val158Met SNP (k=7 samples; n=784) and SLC6A4 5-HTTLPR (k=4 samples, n=204). None of these polymorphisms showed a reliable association with response inhibition performance. The methodological and theoretical implications of these findings are discussed, along with recommendations for future research. Copyright © 2017 Elsevier Ltd. All rights reserved.
Keri B Dotson
Full Text Available Norms clarification has been identified as an effective component of college student drinking interventions, prompting research on norms clarification as a single-component intervention known as Personalized Normative Feedback (PNF. Previous reviews have examined PNF in combination with other components but not as a stand-alone intervention.To investigate the degree to which computer-delivered stand-alone personalized normative feedback interventions reduce alcohol consumption and alcohol-related harms among college students and to compare gender-neutral and gender-specific PNF.Electronic databases were searched systematically through November 2014. Reference lists were reviewed manually and forward and backward searches were conducted.Outcome studies that compared computer-delivered, stand-alone PNF intervention with an assessment only, attention-matched, or active treatment control and reported alcohol use and harms among college students.Between-group effect sizes were calculated as the standardized mean difference in change scores between treatment and control groups divided by pooled standard deviation. Within-group effect sizes were calculated as the raw mean difference between baseline and follow-up divided by pooled within-groups standard deviation.Eight studies (13 interventions with a total of 2,050 participants were included. Compared to control participants, students who received gender-neutral (dbetween = 0.291, 95% CI [0.159, 0.423] and gender-specific PNF (dbetween = 0.284, 95% CI [0.117, 0.451] reported greater reductions in drinking from baseline to follow-up. Students who received gender-neutral PNF reported 3.027 (95% CI [2.171, 3.882] fewer drinks per week at first follow-up and gender-specific PNF reported 3.089 (95% CI [0.992, 5.186] fewer drinks. Intervention effects were small for harms (dbetween = 0.157, 95% CI [0.037, 0.278].Computer-delivered PNF is an effective stand-alone approach for reducing college student
Dotson, Keri B; Dunn, Michael E; Bowers, Clint A
Norms clarification has been identified as an effective component of college student drinking interventions, prompting research on norms clarification as a single-component intervention known as Personalized Normative Feedback (PNF). Previous reviews have examined PNF in combination with other components but not as a stand-alone intervention. To investigate the degree to which computer-delivered stand-alone personalized normative feedback interventions reduce alcohol consumption and alcohol-related harms among college students and to compare gender-neutral and gender-specific PNF. Electronic databases were searched systematically through November 2014. Reference lists were reviewed manually and forward and backward searches were conducted. Outcome studies that compared computer-delivered, stand-alone PNF intervention with an assessment only, attention-matched, or active treatment control and reported alcohol use and harms among college students. Between-group effect sizes were calculated as the standardized mean difference in change scores between treatment and control groups divided by pooled standard deviation. Within-group effect sizes were calculated as the raw mean difference between baseline and follow-up divided by pooled within-groups standard deviation. Eight studies (13 interventions) with a total of 2,050 participants were included. Compared to control participants, students who received gender-neutral (dbetween = 0.291, 95% CI [0.159, 0.423]) and gender-specific PNF (dbetween = 0.284, 95% CI [0.117, 0.451]) reported greater reductions in drinking from baseline to follow-up. Students who received gender-neutral PNF reported 3.027 (95% CI [2.171, 3.882]) fewer drinks per week at first follow-up and gender-specific PNF reported 3.089 (95% CI [0.992, 5.186]) fewer drinks. Intervention effects were small for harms (dbetween = 0.157, 95% CI [0.037, 0.278]). Computer-delivered PNF is an effective stand-alone approach for reducing college student drinking and
Zweig, Katharina A
Network Analysis Literacy focuses on design principles for network analytics projects. The text enables readers to: pose a defined network analytic question; build a network to answer the question; choose or design the right network analytic methods for a particular purpose, and more.
Ganio, L.M.; Torgersen, C.E.; Gresswell, R.E.
The shape and configuration of branched networks influence ecological patterns and processes. Recent investigations of network influences in riverine ecology stress the need to quantify spatial structure not only in a two-dimensional plane, but also in networks. An initial step in understanding data from stream networks is discerning non-random patterns along the network. On the other hand, data collected in the network may be spatially autocorrelated and thus not suitable for traditional statistical analyses. Here we provide a method that uses commercially available software to construct an empirical variogram to describe spatial pattern in the relative abundance of coastal cutthroat trout in headwater stream networks. We describe the mathematical and practical considerations involved in calculating a variogram using a non-Euclidean distance metric to incorporate the network pathway structure in the analysis of spatial variability, and use a non-parametric technique to ascertain if the pattern in the empirical variogram is non-random.
Ganio, L.M.; Torgersen, C.E.; Gresswell, R.E.
The shape and configuration of branched networks influence ecological patterns and processes. Recent investigations of network influences in riverine ecology stress the need to quantify spatial structure not only in a two-dimensional plane, but also in networks. An initial step in understanding data from stream networks is discerning non-random patterns along the network. On the other hand, data collected in the network may be spatially autocorrelated and thus not suitable for traditional statistical analyses. Here we provide a method that uses commercially available software to construct an empirical variogram to describe spatial pattern in the relative abundance of coastal cutthroat trout in headwater stream networks. We describe the mathematical and practical considerations involved in calculating a variogram using a non-Euclidean distance metric to incorporate the network pathway structure in the analysis of spatial variability, and use a non-parametric technique to ascertain if the pattern in the empirical variogram is non-random.
Supervisory Control and Data Acquisition (SCADA) networks are commonly deployed to aid the operation of large industrial facilities, such as water treatment facilities. Historically, these networks were composed by special-purpose embedded devices communicating through proprietary protocols.
Full Text Available Multiradio wireless mesh network (WMN is a feasible choice for several applications, as routers with multiple network interface cards have become cheaper. Routing in any network has a great impact on the overall network performance, thus a routing protocol or algorithm for WMN should be carefully designed taking into account the specific characteristics of the network. In addition, in wireless networks, serious unfairness can occur between users if the issue is not addressed in the network protocols or algorithms. In this paper, we are proposing a novel centralized routing algorithm, called Subscriber Aware Fair Routing in WMN (SAFARI, for multiradio WMN that assures fairness, leads to a feasible scheduling, and does not collapse the aggregate network throughput with a strict fairness criterion. We show that our protocol is feasible and practical, and exhaustive simulations show that the performance is improved compared to traditional routing algorithms.
This book presents the latest results on modeling and analysis of OBS networks. It classifies all the literature on the topic, and its scope extends to include discussion of high-speed communication networks with limited or no buffers.
Supervisory Control and Data Acquisition (SCADA) networks are commonly deployed to aid the operation of large industrial facilities, such as water treatment facilities. Historically, these networks were composed by special-purpose embedded devices communicating through proprietary protocols.
Rosenow, Felix; van Alphen, Natascha; Becker, Albert; Chiocchetti, Andreas; Deichmann, Ralf; Deller, Thomas; Freiman, Thomas; Freitag, Christine M; Gehrig, Johannes; Hermsen, Anke M; Jedlicka, Peter; Kell, Christian; Klein, Karl Martin; Knake, Susanne; Kullmann, Dimitri M; Liebner, Stefan; Norwood, Braxton A; Omigie, Diana; Plate, Karlheinz; Reif, Andreas; Reif, Philipp S; Reiss, Yvonne; Roeper, Jochen; Ronellenfitsch, Michael W; Schorge, Stephanie; Schratt, Gerhard; Schwarzacher, Stephan W; Steinbach, Joachim P; Strzelczyk, Adam; Triesch, Jochen; Wagner, Marlies; Walker, Matthew C; von Wegner, Frederic; Bauer, Sebastian
Despite the availability of more than 15 new "antiepileptic drugs", the proportion of patients with pharmacoresistant epilepsy has remained constant at about 20-30%. Furthermore, no disease-modifying treatments shown to prevent the development of epilepsy following an initial precipitating brain injury or to reverse established epilepsy have been identified to date. This is likely in part due to the polyetiologic nature of epilepsy, which in turn requires personalized medicine approaches. Recent advances in imaging, pathology, genetics and epigenetics have led to new pathophysiological concepts and the identification of monogenic causes of epilepsy. In the context of these advances, the First International Symposium on Personalized Translational Epilepsy Research (1st ISymPTER) was held in Frankfurt on September 8, 2016, to discuss novel approaches and future perspectives for personalized translational research. These included new developments and ideas in a range of experimental and clinical areas such as deep phenotyping, quantitative brain imaging, EEG/MEG-based analysis of network dysfunction, tissue-based translational studies, innate immunity mechanisms, microRNA as treatment targets, functional characterization of genetic variants in human cell models and rodent organotypic slice cultures, personalized treatment approaches for monogenic epilepsies, blood-brain barrier dysfunction, therapeutic focal tissue modification, computational modeling for target and biomarker identification, and cost analysis in (monogenic) disease and its treatment. This report on the meeting proceedings is aimed at stimulating much needed investments of time and resources in personalized translational epilepsy research. Part I includes the clinical phenotyping and diagnostic methods, EEG network-analysis, biomarkers, and personalized treatment approaches. In Part II, experimental and translational approaches will be discussed (Bauer et al., 2017) . Copyright © 2017 Elsevier Inc
Vivier, J.; Mehablia, A.
To improve traditional neural networks, the present research used the wavelet network, a special feedforward neural network with a single hidden layer supported by the wavelet theory. Prediction performance and efficiency of the proposed network were examined with a published experimental dataset of cross-flow membrane filtration. The dataset was divided into two parts: 70 samples for training data and 330 samples for testing data. Various combinations of transmembrane pressure, filtration...
Full Text Available A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models.
Chen, Bowen; Zhao, Yongli; Zhang, Jie
In this paper, we develop a virtual link priority mapping (LPM) approach and a virtual node priority mapping (NPM) approach to improve the energy efficiency and to reduce the spectrum usage over the converged flexible bandwidth optical networks and data centers. For comparison, the lower bound of the virtual optical network mapping is used for the benchmark solutions. Simulation results show that the LPM approach achieves the better performance in terms of power consumption, energy efficiency, spectrum usage, and the number of regenerators compared to the NPM approach.
Larsen, Claus Popp; Limal, Emmanuel
A method of implementing a transparent self-healing meshed network is described here. In case of a cable break or signal detoriation, this network will perform protection switching without needing direct correspondance with the overlaying management system. This causes simpler network management...
Chinthavali, Supriya [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Surface transportation road networks share structural properties similar to other complex networks (e.g., social networks, information networks, biological networks, and so on). This research investigates the structural properties of road networks for any possible correlation with the traffic characteristics such as link flows those determined independently. Additionally, we define a criticality index for the links of the road network that identifies the relative importance in the network. We tested our hypotheses with two sample road networks. Results show that, correlation exists between the link flows and centrality measures of a link of the road (dual graph approach is followed) and the criticality index is found to be effective for one test network to identify the vulnerable nodes.
Son, L.T.; Schiøler, Henrik; Madsen, Ole Brun
issues in Bluetooth network as convex optimization problem. We formulate the problem of maximizing of total network flows and minimizing the costs of flows. The hybrid distributed capacity allocation scheme HDICA is proposed as an approximated solution of the stated optimization problem that satisfies...... quality of service requirements and topologically induced constraints in the Bluetooth network, such as node and link capacity limitations. The proposed scheme is decentralized and complies with frequent changes of topology as well as capacity limitations and flow requirements in the network. Simulation...... shows that the performance of Bluetooth network could be improved by applying the hybrid distributed iterative capacity allocation scheme....
Cristiane Chaves Gattaz
Full Text Available The most recent operations and management frameworks in innovation have not been complete to explicit required knowledge to manage the cooperation of its networked open innovation value chain in the knowledge economy and open enterprise. Strategic actors from the Virtual Innovation Society network were interviewed to identify critical semantic parameters that address this issue. As a result, this study suggests the characterization of inter-dependent added-values and its performance metrics, under the “managing as designing” approach, as input for managing the externalities, the integration of the articulation between business operations, strategy and information technology, and waste of innovation. In this context, the identification of the main managerial indicators for future command and control of existing innovation network operations under the “managing as designing” approach becomes a new challenge for future research. Keywords: Managing as Designing; Innovation Management; Network Managament; Operations Management; Virtual Networks.
Madden, L V; Piepho, H-P; Paul, P A
Meta-analysis, the methodology for analyzing the results from multiple independent studies, has grown tremendously in popularity over the last four decades. Although most meta-analyses involve a single effect size (summary result, such as a treatment difference) from each study, there are often multiple treatments of interest across the network of studies in the analysis. Multi-treatment (or network) meta-analysis can be used for simultaneously analyzing the results from all the treatments. However, the methodology is considerably more complicated than for the analysis of a single effect size, and there have not been adequate explanations of the approach for agricultural investigations. We review the methods and models for conducting a network meta-analysis based on frequentist statistical principles, and demonstrate the procedures using a published multi-treatment plant pathology data set. A major advantage of network meta-analysis is that correlations of estimated treatment effects are automatically taken into account when an appropriate model is used. Moreover, treatment comparisons may be possible in a network meta-analysis that are not possible in a single study because all treatments of interest may not be included in any given study. We review several models that consider the study effect as either fixed or random, and show how to interpret model-fitting output. We further show how to model the effect of moderator variables (study-level characteristics) on treatment effects, and present one approach to test for the consistency of treatment effects across the network. Online supplemental files give explanations on fitting the network meta-analytical models using SAS.
van Dijk, Freke; Treur, J.
In this paper a way to analyse psychopathy computationally is explored. This is done by creating and analysing a temporal-causal network model using a Network-Oriented Modeling approach. The network model was designed using knowledge from the field of Cognitive and Social Neuroscience and simulates
Pedersen, Martin Wæver; Burgess, Greg; Weng, Kevin C.
Static sensor networks to observe animals are widely used in ecological, management and conservation research, but quantitative methods for designing these networks are underdeveloped. In the context of aquatic systems, we present a method for quasi-optimal network design, which accounts for bloc......Static sensor networks to observe animals are widely used in ecological, management and conservation research, but quantitative methods for designing these networks are underdeveloped. In the context of aquatic systems, we present a method for quasi-optimal network design, which accounts...... for blocking of detections by obstacles, horizontal and vertical movement behaviour of the target animals, and type of research question (is the network intended for estimation of detailed movement or home range?). Optimal design is defined as the sensor configuration that maximizes the expected number...
This study examined the personal, household, and social structural attributes of alcoholimpaired : drivers in Maryland. The study used an egocentric approach of social network : analysis. This approach concentrated on specific actors (alcohol-impaire...
Budich, Reinhard; Nyberg, Per; Weigel, Tobias
Climate Knowledge Discovery Workshop; Hamburg, Germany, 30 March to 1 April 2011 Do complex networks combined with semantic Web technologies offer the next generation of solutions in climate science? To address this question, a first Climate Knowledge Discovery (CKD) Workshop, hosted by the German Climate Computing Center (Deutsches Klimarechenzentrum (DKRZ)), brought together climate and computer scientists from major American and European laboratories, data centers, and universities, as well as representatives from industry, the broader academic community, and the semantic Web communities. The participants, representing six countries, were concerned with large-scale Earth system modeling and computational data analysis. The motivation for the meeting was the growing problem that climate scientists generate data faster than it can be interpreted and the need to prepare for further exponential data increases. Current analysis approaches are focused primarily on traditional methods, which are best suited for large-scale phenomena and coarse-resolution data sets. The workshop focused on the open discussion of ideas and technologies to provide the next generation of solutions to cope with the increasing data volumes in climate science.
Johnson, C. E.
Modern seismic networks present a number of challenges, but perhaps most notably are those related to 1) extreme variation in station density, 2) temporal variation in station availability, and 3) the need to achieve detectability for much smaller events of strategic importance. The first of these has been reasonably addressed in the development of modern seismic associators, such as GLASS 3.0 by the USGS/NEIC, though some work still remains to be done in this area. However, the latter two challenges demand special attention. Station availability is impacted by weather, equipment failure or the adding or removing of stations, and while thresholds have been pushed to increasingly smaller magnitudes, new algorithms are needed to achieve even lower thresholds. Station availability can be addressed by a modern, adaptive architecture that maintains specified performance envelopes using adaptive analytics coupled with complexity theory. Finally, detection thresholds can be lowered using a novel approach that tightly couples waveform analytics with the event detection and association processes based on a principled repicking algorithm that uses particle realignment for enhanced phase discrimination.
Full Text Available Identification of important nodes in complex networks has attracted an increasing attention over the last decade. Various measures have been proposed to characterize the importance of nodes in complex networks, such as the degree, betweenness and PageRank. Different measures consider different aspects of complex networks. Although there are numerous results reported on undirected complex networks, few results have been reported on directed biological networks. Based on network motifs and principal component analysis (PCA, this paper aims at introducing a new measure to characterize node importance in directed biological networks. Investigations on five real-world biological networks indicate that the proposed method can robustly identify actually important nodes in different networks, such as finding command interneurons, global regulators and non-hub but evolutionary conserved actually important nodes in biological networks. Receiver Operating Characteristic (ROC curves for the five networks indicate remarkable prediction accuracy of the proposed measure. The proposed index provides an alternative complex network metric. Potential implications of the related investigations include identifying network control and regulation targets, biological networks modeling and analysis, as well as networked medicine.
A. Sarfaraz Ahmed; T. Senthil Kumaran; S. Syed Abdul Syed; S. Subburam
In mobile ad hoc networks, communication among mobile nodes occurs through wireless medium The design of ad hoc network protocol, generally based on a traditional “layered approach”, has been found ineffective to deal with receiving signal strength (RSS)-related problems, affecting the physical layer, the network layer and transport layer. This paper proposes a design approach, deviating from the traditional network design, toward enhancing the cross-layer interaction among different layers, ...
Lorena Isabel Barona López
Full Text Available 5G networks expect to provide significant advances in network management compared to traditional mobile infrastructures by leveraging intelligence capabilities such as data analysis, prediction, pattern recognition and artificial intelligence. The key idea behind these actions is to facilitate the decision-making process in order to solve or mitigate common network problems in a dynamic and proactive way. In this context, this paper presents the design of Self-Organized Network Management in Virtualized and Software Defined Networks (SELFNET Analyzer Module, which main objective is to identify suspicious or unexpected situations based on metrics provided by different network components and sensors. The SELFNET Analyzer Module provides a modular architecture driven by use cases where analytic functions can be easily extended. This paper also proposes the data specification to define the data inputs to be taking into account in diagnosis process. This data specification has been implemented with different use cases within SELFNET Project, proving its effectiveness.
Csermely, Peter; Rajnai, Gabor; Sulyok, Katalin
In 2006 a novel approach to talent support was promoted by several talent support programmes in Hungary. The new idea was a network approach. The nationwide network of so-called TalentPoints and its framework, the Hungarian Genius Program, gained substantial European Union funding in 2009, and today it is growing rapidly. A novel concept of talent…
Full Text Available Control of gene regulatory networks is one of the fundamental topics in systems biology. In the last decade, control theory of Boolean networks (BNs, which is well known as a model of gene regulatory networks, has been widely studied. In this review paper, our previously proposed methods on optimal control of probabilistic Boolean networks (PBNs are introduced. First, the outline of PBNs is explained. Next, an optimal control method using polynomial optimization is explained. The finite-time optimal control problem is reduced to a polynomial optimization problem. Furthermore, another finite-time optimal control problem, which can be reduced to an integer programming problem, is also explained.
Cellular operators are continuously densifying their networks to cope with the ever-increasing capacity demand. Furthermore, an extreme densification phase for cellular networks is foreseen to fulfill the ambitious fifth generation (5G) performance requirements. Network densification improves spectrum utilization and network capacity by shrinking base stations\\' (BSs) footprints and reusing the same spectrum more frequently over the spatial domain. However, network densification also increases the handover (HO) rate, which may diminish the capacity gains for mobile users due to HO delays. In highly dense 5G cellular networks, HO delays may neutralize or even negate the gains offered by network densification. In this paper, we present an analytical paradigm, based on stochastic geometry, to quantify the effect of HO delay on the average user rate in cellular networks. To this end, we propose a flexible handover scheme to reduce HO delay in case of highly dense cellular networks. This scheme allows skipping the HO procedure with some BSs along users\\' trajectories. The performance evaluation and testing of this scheme for only single HO skipping shows considerable gains in many practical scenarios. © 2016 IEEE.
Anderson, Brian D O
Geared toward upper-level undergraduates and graduate students, this book offers a comprehensive look at linear network analysis and synthesis. It explores state-space synthesis as well as analysis, employing modern systems theory to unite the classical concepts of network theory. The authors stress passive networks but include material on active networks. They avoid topology in dealing with analysis problems and discuss computational techniques. The concepts of controllability, observability, and degree are emphasized in reviewing the state-variable description of linear systems. Explorations
Li, Jun; Zhao, Patrick X
Identification of functional modules/sub-networks in large-scale biological networks is one of the important research challenges in current bioinformatics and systems biology. Approaches have been developed to identify functional modules in single-class biological networks; however, methods for systematically and interactively mining multiple classes of heterogeneous biological networks are lacking. In this paper, we present a novel algorithm (called mPageRank) that utilizes the Multiplex PageRank approach to mine functional modules from two classes of biological networks. We demonstrate the capabilities of our approach by successfully mining functional biological modules through integrating expression-based gene-gene association networks and protein-protein interaction networks. We first compared the performance of our method with that of other methods using simulated data. We then applied our method to identify the cell division cycle related functional module and plant signaling defense-related functional module in the model plant Arabidopsis thaliana. Our results demonstrated that the mPageRank method is effective for mining sub-networks in both expression-based gene-gene association networks and protein-protein interaction networks, and has the potential to be adapted for the discovery of functional modules/sub-networks in other heterogeneous biological networks. The mPageRank executable program, source code, the datasets and results of the presented two case studies are publicly and freely available at http://plantgrn.noble.org/MPageRank/.
Javidi, Mohammad M.; Aliahmadipour, Laya
An important and essential issue for wireless networks is routing protocol design that is a major technical challenge due to the function of the network. Game theory is a powerful mathematical tool that analyzes the strategic interactions among multiple decision makers and the results of researches show that applied game theory in routing protocol lead to improvement the network performance through reduce overhead and motivates selfish nodes to collaborate in the network. This paper presents a review and comparison for typical representatives of routing protocols designed that applied game theory approaches for various wireless networks such as ad hoc networks, mobile ad hoc networks and sensor networks that all of them lead to improve the network performance.
Wessling, Matthias; Mulder, M.H.V.; Bos, A.; Bos, A.; van der Linden, M.K.T.; Bos, M.; van der Linden, W.E.
In this short communication, the prediction of the permeability of carbon dioxide through different polymers using a neural network is studied. A neural network is a numeric-mathematical construction that can model complex non-linear relationships. Here it is used to correlate the IR spectrum of a
Information and Communication Technology (ICT) is changing the way we live and has become an essential part of our life. With the advent of Internet of Things (IoT), and Wireless Sensor Networks (WSN) in particular, the number of devices that are networked is increasing exponentially over the years.
Boschma, R.; Balland, P.A.; de Vaan, M.
Over the last two decades, scholars from different scientific fields have increasingly acknowledged that network structures play a crucial role in economic activities (Granovetter, 1985; Powell et al., 2005; Cowan et al., 2007; Jackson, 2008). Network structures refer to the particular way relations
Zhu, Ling; Robinson, Scott E.; Torenvlied, René
The study of managerial networking has been growing in the field of public administration; a field that analyzes how managers in open system organizations interact with different external actors and organizations. Coincident with this interest in managerial networking is the use of self-reported
Cohen, Ira L.; And Others
Neural network technology was compared with simultaneous and stepwise linear discriminant analysis in terms of their ability to classify and predict persons (n=138) as having autism or mental retardation. The neural network methodology was superior in both classifying groups and in generalizing to new cases that were not part of the training…
Network forensic analysis is a process that analyzes intrusion evidence captured from networked environment to identify suspicious entities and stepwise actions in an attack scenario. Unfortunately, the overwhelming amount and low quality of output from security sensors make it difficult for analysts to obtain a succinct high-level view of complex…
Chekaleva, Nadezhda V.; Makarova, Natalia S.; Drobotenko, Yulia B.
The study presented in the article is devoted to the analysis of theory and practice of network interaction within the framework of education clusters. Education clusters are considered to be a novel form of network interaction in pedagogical education in Russia. The aim of the article is to show the advantages and disadvantages of the cluster…
The aim of this paper is to present and accurate fault detection technique for high speed distance protection using artificial neural networks. The feed-forward multi-layer neural network with the use of supervised learning and the common training rule of error back-propagation is chosen for this study. Information available locally at the relay point is passed to a neural network in order for an assessment of the fault location to be made. However in practice there is a large amount of information available, and a feature extraction process is required to reduce the dimensionality of the pattern vectors, whilst retaining important information that distinguishes the fault point. The choice of features is critical to the performance of the neural networks learning and operation. A significant feature in this paper is that an artificial neural network has been designed and tested to enhance the precision of the adaptive capabilities for distance protection
Xin, Chen; Zhang, Huishu; Huang, Jiping
Complex network has been regarded as a useful tool handling systems with vague interactions. Hence, numerous applications have arised. In this paper we construct complex networks for 770 classical piano compositions of Mozart, Beethoven and Chopin based on musical note pitches and lengths. We find prominent distinctions among network edges of different composers. Some stylized facts can be explained by such parameters of network structures and topologies. Further, we propose two classification methods for music styles and genres according to the discovered distinctions. These methods are easy to implement and the results are sound. This work suggests that complex network could be a decent way to analyze the characteristics of musical notes, since it could provide a deep view into understanding of the relationships among notes in musical compositions and evidence for classification of different composers, styles and genres of music.
Full Text Available Formal techniques have been devoted to analyzing whether network protocol specifications violate security policies; however, these methods cannot detect vulnerabilities in the implementations of the network protocols themselves. Symbolic execution can be used to analyze the paths of the network protocol implementations, but for stateful network protocols, it is difficult to reach the deep states of the protocol. This paper proposes a novel model-guided approach to detect vulnerabilities in network protocol implementations. Our method first abstracts a finite state machine (FSM model, then utilizes the model to guide the symbolic execution. This approach achieves high coverage of both the code and the protocol states. The proposed method is implemented and applied to test numerous real-world network protocol implementations. The experimental results indicate that the proposed method is more effective than traditional fuzzing methods such as SPIKE at detecting vulnerabilities in the deep states of network protocol implementations.
Wen, Shameng; Meng, Qingkun; Feng, Chao; Tang, Chaojing
Formal techniques have been devoted to analyzing whether network protocol specifications violate security policies; however, these methods cannot detect vulnerabilities in the implementations of the network protocols themselves. Symbolic execution can be used to analyze the paths of the network protocol implementations, but for stateful network protocols, it is difficult to reach the deep states of the protocol. This paper proposes a novel model-guided approach to detect vulnerabilities in network protocol implementations. Our method first abstracts a finite state machine (FSM) model, then utilizes the model to guide the symbolic execution. This approach achieves high coverage of both the code and the protocol states. The proposed method is implemented and applied to test numerous real-world network protocol implementations. The experimental results indicate that the proposed method is more effective than traditional fuzzing methods such as SPIKE at detecting vulnerabilities in the deep states of network protocol implementations.
Çakır, Tunahan; Khatibipour, Mohammad Jafar
The primary focus in the network-centric analysis of cellular metabolism by systems biology approaches is to identify the active metabolic network for the condition of interest. Two major approaches are available for the discovery of the condition-specific metabolic networks. One approach starts from genome-scale metabolic networks, which cover all possible reactions known to occur in the related organism in a condition-independent manner, and applies methods such as the optimization-based Flux-Balance Analysis to elucidate the active network. The other approach starts from the condition-specific metabolome data, and processes the data with statistical or optimization-based methods to extract information content of the data such that the active network is inferred. These approaches, termed bottom-up and top-down, respectively, are currently employed independently. However, considering that both approaches have the same goal, they can both benefit from each other paving the way for the novel integrative analysis methods of metabolome data- and flux-analysis approaches in the post-genomic era. This study reviews the strengths of constraint-based analysis and network inference methods reported in the metabolic systems biology field; then elaborates on the potential paths to reconcile the two approaches to shed better light on how the metabolism functions.
Full Text Available The output of state-of-the-art reverse-engineering methods for biological networks is often based on the fitting of a mathematical model to the data. Typically, different datasets do not give single consistent network predictions but rather an ensemble of inconsistent networks inferred under the same reverse-engineering method that are only consistent with the specific experimentally measured data. Here, we focus on an alternative approach for combining the information contained within such an ensemble of inconsistent gene networks called meta-analysis, to make more accurate predictions and to estimate the reliability of these predictions. We review two existing meta-analysis approaches; the Fisher transformation combined coefficient test (FTCCT and Fisher's inverse combined probability test (FICPT; and compare their performance with five well-known methods, ARACNe, Context Likelihood or Relatedness network (CLR, Maximum Relevance Minimum Redundancy (MRNET, Relevance Network (RN and Bayesian Network (BN. We conducted in-depth numerical ensemble simulations and demonstrated for biological expression data that the meta-analysis approaches consistently outperformed the best gene regulatory network inference (GRNI methods in the literature. Furthermore, the meta-analysis approaches have a low computational complexity. We conclude that the meta-analysis approaches are a powerful tool for integrating different datasets to give more accurate and reliable predictions for biological networks.
Smith Ann E
Full Text Available Abstract Background Classification of the electrocardiogram using Neural Networks has become a widely used method in recent years. The efficiency of these classifiers depends upon a number of factors including network training. Unfortunately, there is a shortage of evidence available to enable specific design choices to be made and as a consequence, many designs are made on the basis of trial and error. In this study we develop prediction models to indicate the point at which training should stop for Neural Network based Electrocardiogram classifiers in order to ensure maximum generalisation. Methods Two prediction models have been presented; one based on Neural Networks and the other on Genetic Programming. The inputs to the models were 5 variable training parameters and the output indicated the point at which training should stop. Training and testing of the models was based on the results from 44 previously developed bi-group Neural Network classifiers, discriminating between Anterior Myocardial Infarction and normal patients. Results Our results show that both approaches provide close fits to the training data; p = 0.627 and p = 0.304 for the Neural Network and Genetic Programming methods respectively. For unseen data, the Neural Network exhibited no significant differences between actual and predicted outputs (p = 0.306 while the Genetic Programming method showed a marginally significant difference (p = 0.047. Conclusions The approaches provide reverse engineering solutions to the development of Neural Network based Electrocardiogram classifiers. That is given the network design and architecture, an indication can be given as to when training should stop to obtain maximum network generalisation.
Livneh, Ran; CERN. Geneva
The extremely high rate of events that will be produced in the future Large Hadron Collider requires the triggering mechanism to make precise decisions in a few nano-seconds. This poses a complicated inverse problem, arising from the inhomogeneous nature of the magnetic fields in ATLAS. This thesis presents a study of an application of Artificial Neural Networks to the muon triggering problem in the ATLAS end-cap. A comparison with realistic results from the ATLAS first level trigger simulation was in favour of the neural network, but this is mainly due to superior resolution available off-line. Other options for applying a neural network to this problem are discussed.
Tran, Duc A
Evidenced by the success of Facebook, Twitter, and LinkedIn, online social networks (OSNs) have become ubiquitous, offering novel ways for people to access information and communicate with each other. As the increasing popularity of social networking is undeniable, scalability is an important issue for any OSN that wants to serve a large number of users. Storing user data for the entire network on a single server can quickly lead to a bottleneck, and, consequently, more servers are needed to expand storage capacity and lower data request traffic per server. Adding more servers is just one step
Juang, Jonq; Liang, Yu-Hao
Global synchronization in complex networks has attracted considerable interest in various fields. There are mainly two analytical approaches for studying such time-varying networks. The first approach is Lyapunov function-based methods. For such an approach, the connected-graph-stability (CGS) method arguably gives the best results. Nevertheless, CGS is limited to the networks with cooperative couplings. The matrix measure approach (MMA) proposed by Chen, although having a wider range of applications in the network topologies than that of CGS, works for smaller numbers of nodes in most network topologies. The approach also has a limitation with networks having partial-state coupling. Other than giving yet another MMA, we introduce a new and, in some cases, optimal coordinate transformation to study such networks. Our approach fixes all the drawbacks of CGS and MMA. In addition, by merely checking the structure of the vector field of the individual oscillator, we shall be able to determine if the system is globally synchronized. In summary, our results can be applied to rather general time-varying networks with a large number of nodes.
Weaver, Sallie J; Lofthus, Jennifer; Sawyer, Melinda; Greer, Lee; Opett, Kristin; Reynolds, Catherine; Wyskiel, Rhonda; Peditto, Stephanie; Pronovost, Peter J
Collaborative improvement networks draw on the science of collaborative organizational learning and communities of practice to facilitate peer-to-peer learning, coaching, and local adaption. Although significant improvements in patient safety and quality have been achieved through collaborative methods, insight regarding how collaborative networks are used by members is needed. Improvement Strategy: The Comprehensive Unit-based Safety Program (CUSP) Learning Network is a multi-institutional collaborative network that is designed to facilitate peer-to-peer learning and coaching specifically related to CUSP. Member organizations implement all or part of the CUSP methodology to improve organizational safety culture, patient safety, and care quality. Qualitative case studies developed by participating members examine the impact of network participation across three levels of analysis (unit, hospital, health system). In addition, results of a satisfaction survey designed to evaluate member experiences were collected to inform network development. Common themes across case studies suggest that members found value in collaborative learning and sharing strategies across organizational boundaries related to a specific improvement strategy. The CUSP Learning Network is an example of network-based collaborative learning in action. Although this learning network focuses on a particular improvement methodology-CUSP-there is clear potential for member-driven learning networks to grow around other methods or topic areas. Such collaborative learning networks may offer a way to develop an infrastructure for longer-term support of improvement efforts and to more quickly diffuse creative sustainment strategies.
Bertran, Maria-Ona; Anaya-Reza, Omar; Lopez-Arenas, Maria Teresa
into account the available technologies, geographical location, future technological developments and global market changes. The problem of optimal design of biorefinery networks is solved in this work through three different stages: (i) synthesis stage, (ii) design stage, and (iii) innovation stage......, the selected processing network is simulated and analyzed and targets for improvement are identified. Finally, a more sustainable design is achieved at the innovation stage by generating innovative solutions that satisfy the targets from the design stage. This work is concerned with the first stage......]. The optimal synthesis of biorefinery networks problem is defined as: given a set of biomass derived feedstock and a set of desired final products and specifications, determine a flexible, sustainable and innovative processing network with the targets of minimum cost and sustainable development taking...
PON) planning problem necessitates the search for a subset of deployed facilities (splitters) and their allocated demand points (optical network units) to minimise the overall deployment cost. A mixed integer linear programming formulation ...
Mohammadi, Soma; Bojesen, Carsten
dynamically while the flow and pressure are calculated on the basis of steady state conditions. The implicit finite element method is applied to simulate the transient temperature behaviour in the network. Pipe network heat losses, pressure drop in the network and return temperature to the plant...... of this study is to develop a model for thermo-hydraulic calculation of low temperature DH system. The modelling is performed with emphasis on transient heat transfer in pipe networks. The pseudo-dynamic approach is adopted to model the District Heating Network [DHN] behaviour which estimates the temperature...
paradigm classifies the system as a Network Behavior Analysis solution ( NBA ) in the NIST nomenclature . As the network conditions change over time...several subsystems interacting with each other. Most of the subsystems are implemented as one or more agents, and all agents communicate solely by the...SSH PASSWORD KNOWLEDGE ?DSTIP) :effect (MALWARE PROPAGATION ?DSTIP)) Outgoing communication : Duration Protocol Src IP Dst IP Src Port Dst Port Flags
K. K. Kannan
A priority based packet scheduling scheme is proposed which aims at scheduling different types of data packets, such as real time and non-real-time data packets at sensor nodes with resource constraints in Wireless Sensor Networks. Most of the existing packet-scheduling mechanisms of Wireless Sensor Networks use First Come First Served (FCFS), non-preemptive priority and preemptive priority scheduling algorithms. These algorithms results in long end-to-end data transmission delay, high energy...
Islam, Noman; Shaikh, Zubair A.
Mobile Adhoc Network (MANET) is a network of a number of mobile routers and associated hosts, organized in a random fashion via wireless links. During recent years MANET has gained enormous amount of attention and has been widely used for not only military purposes but for search-and-rescue operations, intelligent transportation system, data collection, virtual classrooms and ubiquitous computing. Service Discovery is one of the most important issues in MANET. It is defined as the process of ...
Tickotsky, Nili; Moskovitz, Moti
Kallmann syndrome (KS) is defined by the combination of isolated hypogonadotrophic hypogonadism (IHH) and anosmia, with renal agenesis occurring in 30% of KS cases with KAL1 gene mutations. Unlike other KS-related disorders, renal agenesis cannot be directly associated with mutations in the KAL1 gene. We hypothesized that protein interaction networks may suggest a link between genes currently known to be associated with KS on the one hand and those associated with renal agenesis on the other hand. We created a STRING protein interaction network from KS-related genes and renal-agenesis-associated genes and analyzed it with Cytoscape 3.0.1 network software. The STRING protein interaction network provided a conceptual framework for current knowledge on the subject of renal morphogenesis in Kallmann syndrome. In addition, STRING and Cytoscape 3.0.1 software identified new potential KS renal-aplasia-associated genes (PAX2, BMP4, and SOX10). The use of protein-protein interaction networks and network analysis tools provided interesting insights and possible directions for future studies on the subject of renal aplasia in Kallmann syndrome. © 2014 John Wiley & Sons Ltd/University College London.
Full Text Available This paper selects Changsha as a case study and constructs the models of the subway network and the urban spatial network by using planning data. In the network models, the districts of Changsha are regarded as nodes and the connections between each pair of districts are regarded as edges. The method is based on quantitative analysis of the node weights and the edge weights, which are defined in the complex network theory. And the structures of subway and urban space are visualized in the form of networks. Then, through analyzing the discrepancy coefficients of the corresponding nodes and edges, the paper carries out a comparison between the two networks to evaluate the coordination. The results indicate that only 21.4% of districts and 13.2% of district connections have a rational coordination. Finally, the strategies are put forward for optimization, which suggest adjusting subway transit density, regulating land-use intensity and planning new mass transits for the uncoordinated parts.
The current research investigated how the contextual expression of personality differs across interpersonal relationships. Two related studies were conducted with college samples (Study 1: N = 52, 38 female; Study 2: N = 111, 72 female). Participants in each study completed a five-factor measure of personality and constructed a social network detailing their 30 most important relationships. Participants used a brief Five-Factor Model scale to rate their personality as they experience it when with each person in their social network. Multiple informants selected from each social network then rated the target participant's personality (Study 1: N = 227, Study 2: N = 777). Contextual personality ratings demonstrated incremental validity beyond standard global self-report in predicting specific informants' perceptions. Variability in these contextualized personality ratings was predicted by the position of the other individuals within the social network. Across both studies, participants reported being more extraverted and neurotic, and less conscientious, with more central members of their social networks. Dyadic social network-based assessments of personality provide incremental validity in understanding personality, revealing dynamic patterns of personality variability unobservable with standard assessment techniques. © 2013 Wiley Periodicals, Inc.
Rodewald, Amanda D; Rohr, Rudolf P; Fortuna, Miguel A; Bascompte, Jordi
Ecological networks are known to influence ecosystem attributes, but we poorly understand how interspecific network structure affect population demography of multiple species, particularly for vertebrates. Establishing the link between network structure and demography is at the crux of being able to use networks to understand population dynamics and to inform conservation. We addressed the critical but unanswered question, does network structure explain demographic consequences of urbanization? We studied 141 ecological networks representing interactions between plants and nesting birds in forests across an urbanization gradient in Ohio, USA, from 2001 to 2011. Nest predators were identified by video-recording nests and surveyed from 2004 to 2011. As landscapes urbanized, bird-plant networks were more nested, less compartmentalized and dominated by strong interactions between a few species (i.e. low evenness). Evenness of interaction strengths promoted avian nest survival, and evenness explained demography better than urbanization, level of invasion, numbers of predators or other qualitative network metrics. Highly uneven networks had approximately half the nesting success as the most even networks. Thus, nest survival reflected how urbanization altered species interactions, particularly with respect to how nest placement affected search efficiency of predators. The demographic effects of urbanization were not direct, but were filtered through bird-plant networks. This study illustrates how network structure can influence demography at the community level and further, that knowledge of species interactions and a network approach may be requisite to understanding demographic responses to environmental change. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.
Lauren, Ari; Hökkä, Hannu; Launiainen, Samuli; Palviainen, Marjo; Repo, Tapani; Leena, Finer; Piirainen, Sirpa
Ditch network maintenance (DNM), implemented annually in 70 000 ha area in Finland, is the most controversial of all forest management practices. Nationwide, it is estimated to increase the forest growth by 1…3 million m3 per year, but simultaneously to cause 65 000 tons export of suspended solids and 71 tons of phosphorus (P) to water courses. A systematic approach that allows simultaneous quantification of the positive and negative effects of DNM is required. Excess water in the rooting zone slows the gas exchange and decreases biological activity interfering with the forest growth in boreal forested peatlands. DNM is needed when: 1) the excess water in the rooting zone restricts the forest growth before the DNM, and 2) after the DNM the growth restriction ceases or decreases, and 3) the benefits of DNM are greater than the caused adverse effects. Aeration in the rooting zone can be used as a drainage criterion. Aeration is affected by several factors such as meteorological conditions, tree stand properties, hydraulic properties of peat, ditch depth, and ditch spacing. We developed a 2-dimensional DNM simulator that allows the user to adjust these factors and to evaluate their effect on the soil aeration at different distance from the drainage ditch. DNM simulator computes hydrological processes and soil aeration along a water flowpath between two ditches. Applying daily time step it calculates evapotranspiration, snow accumulation and melt, infiltration, soil water storage, ground water level, soil water content, air-filled porosity and runoff. The model performance in hydrology has been tested against independent high frequency field monitoring data. Soil aeration at different distance from the ditch is computed under steady-state assumption using an empirical oxygen consumption model, simulated air-filled porosity, and diffusion coefficient at different depths in soil. Aeration is adequate and forest growth rate is not limited by poor aeration if the
Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Brasjen, Noud; Uijlenhoet, Remko
The suitability of commercial microwave link networks for ground validation of GPM (Global Precipitation Measurement) data is evaluated here. Two state-of-the-art rainfall products are compared over the land surface of the Netherlands for a period of 7 months, i.e., rainfall maps from commercial cellular communication networks and Integrated Multi-satellite Retrievals for GPM (IMERG). Commercial microwave link networks are nowadays the core component in telecommunications worldwide. Rainfall rates can be retrieved from measurements of attenuation between transmitting and receiving antennas. If adequately set up, these networks enable rainfall monitoring tens of meters above the ground at high spatiotemporal resolutions (temporal sampling of seconds to tens of minutes, and spatial sampling of hundreds of meters to tens of kilometers). The GPM mission is the successor of TRMM (Tropical Rainfall Measurement Mission). For two years now, IMERG offers rainfall estimates across the globe (180°W - 180°E and 60°N - 60°S) at spatiotemporal resolutions of 0.1° x 0.1° every 30 min. These two data sets are compared against a Dutch gauge-adjusted radar data set, considered to be the ground truth given its accuracy, spatiotemporal resolution and availability. The suitability of microwave link networks in satellite rainfall evaluation is of special interest, given the independent character of this technique, its high spatiotemporal resolutions and availability. These are valuable assets for water management and modeling of floods, landslides, and weather extremes; especially in places where rain gauge networks are scarce or poorly maintained, or where weather radar networks are too expensive to acquire and/or maintain.
Bhattacharyya, Moitrayee; Bhat, Chanda R; Vishveshwara, Saraswathi
Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of β2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html. PMID:23934896
Penfold, Christopher A; Shifaz, Ahmed; Brown, Paul E; Nicholson, Ann; Wild, David L
Here we introduce the causal structure identification (CSI) package, a Gaussian process based approach to inferring gene regulatory networks (GRNs) from multiple time series data. The standard CSI approach infers a single GRN via joint learning from multiple time series datasets; the hierarchical approach (HCSI) infers a separate GRN for each dataset, albeit with the networks constrained to favor similar structures, allowing for the identification of context specific networks. The software is implemented in MATLAB and includes a graphical user interface (GUI) for user friendly inference. Finally the GUI can be connected to high performance computer clusters to facilitate analysis of large genomic datasets.
Riza Permana, Angga; Rintis Hadiani, Rr.; Syafi'i
Ponorogo Regency has 440 Irrigation Area with a total area of 17,950 Ha. Due to the limited budget and lack of maintenance cause decreased function on the irrigation. The aim of this study is to make an appropriate system to determine the indices weighted of the rank prioritization criteria for irrigation network maintenance using a fuzzy-based methodology. The criteria that are used such as the physical condition of irrigation networks, area of service, estimated maintenance cost, and efficiency of irrigation water distribution. 26 experts in the field of water resources in the Dinas Pekerjaan Umum were asked to fill out the questionnaire, and the result will be used as a benchmark to determine the rank of irrigation network maintenance priority. The results demonstrate that the physical condition of irrigation networks criterion (W1) = 0,279 has the greatest impact on the assessment process. The area of service (W2) = 0,270, efficiency of irrigation water distribution (W4) = 0,249, and estimated maintenance cost (W3) = 0,202 criteria rank next in effectiveness, respectively. The proposed methodology deals with uncertainty and vague data using triangular fuzzy numbers, and, moreover, it provides a comprehensive decision-making technique to assess maintenance priority on irrigation network.
Christian L Barrett
Full Text Available The number of complete, publicly available genome sequences is now greater than 200, and this number is expected to rapidly grow in the near future as metagenomic and environmental sequencing efforts escalate and the cost of sequencing drops. In order to make use of this data for understanding particular organisms and for discerning general principles about how organisms function, it will be necessary to reconstruct their various biochemical reaction networks. Principal among these will be transcriptional regulatory networks. Given the physical and logical complexity of these networks, the various sources of (often noisy data that can be utilized for their elucidation, the monetary costs involved, and the huge number of potential experiments approximately 10(12 that can be performed, experiment design algorithms will be necessary for synthesizing the various computational and experimental data to maximize the efficiency of regulatory network reconstruction. This paper presents an algorithm for experimental design to systematically and efficiently reconstruct transcriptional regulatory networks. It is meant to be applied iteratively in conjunction with an experimental laboratory component. The algorithm is presented here in the context of reconstructing transcriptional regulation for metabolism in Escherichia coli, and, through a retrospective analysis with previously performed experiments, we show that the produced experiment designs conform to how a human would design experiments. The algorithm is able to utilize probability estimates based on a wide range of computational and experimental sources to suggest experiments with the highest potential of discovering the greatest amount of new regulatory knowledge.
Full Text Available We develop an efficient learning strategy of Chinese characters based on the network of the hierarchical structural relations between Chinese characters. A more efficient strategy is that of learning the same number of useful Chinese characters in less effort or time. We construct a node-weighted network of Chinese characters, where character usage frequencies are used as node weights. Using this hierarchical node-weighted network, we propose a new learning method, the distributed node weight (DNW strategy, which is based on a new measure of nodes' importance that considers both the weight of the nodes and its location in the network hierarchical structure. Chinese character learning strategies, particularly their learning order, are analyzed as dynamical processes over the network. We compare the efficiency of three theoretical learning methods and two commonly used methods from mainstream Chinese textbooks, one for Chinese elementary school students and the other for students learning Chinese as a second language. We find that the DNW method significantly outperforms the others, implying that the efficiency of current learning methods of major textbooks can be greatly improved.
Full Text Available Reducing energy consumption of sensor nodes to prolong the lifetime of finite-capacity batteries and how to enhance the fault-tolerant ability of networks are the major challenges in design of Wireless Sensor Networks (WSNs. In this paper, we present an energy-efficient system of WSNs for black pepper monitoring in tropical areas. At first, we optimized the base station antenna height in order to facilitate reliable communication, after which the Energy-efficient Sensor Protocol for Information via Negotiation (ESPIN routing protocol was utilized to solve the energy saving challenge. We conducted radio propagation experiments in actual black pepper fields. The practical test results illustrate that the ESPIN protocol reduces redundant data transmission and whole energy consumption of network, and enhances the success rate of data transmission compared with traditional Sensor Protocol for Information via Negotiation (SPIN protocol. To further optimize topology for improving the network lifetime, we designed a symmetrical double-chain (SDC topology which is suitable to be deployed in farmland and compared the lifetime with traditional tree topology. Experiment results indicate SDC topology has a longer network lifetime than traditional tree topology. The system we designed will greatly help farmers to make more informed decisions on the efficient use of resources and hence improve black pepper productivity.
Yan, Xiaoyong; Fan, Ying; Di, Zengru; Havlin, Shlomo; Wu, Jinshan
We develop an efficient learning strategy of Chinese characters based on the network of the hierarchical structural relations between Chinese characters. A more efficient strategy is that of learning the same number of useful Chinese characters in less effort or time. We construct a node-weighted network of Chinese characters, where character usage frequencies are used as node weights. Using this hierarchical node-weighted network, we propose a new learning method, the distributed node weight (DNW) strategy, which is based on a new measure of nodes' importance that considers both the weight of the nodes and its location in the network hierarchical structure. Chinese character learning strategies, particularly their learning order, are analyzed as dynamical processes over the network. We compare the efficiency of three theoretical learning methods and two commonly used methods from mainstream Chinese textbooks, one for Chinese elementary school students and the other for students learning Chinese as a second language. We find that the DNW method significantly outperforms the others, implying that the efficiency of current learning methods of major textbooks can be greatly improved.
Barritt, Brian; Bhasin, Kul; Eddy, Wesley; Matthews, Seth
Network simulator software tools are often used to model the behaviors and interactions of applications, protocols, packets, and data links in terrestrial communication networks. Other software tools that model the physics, orbital dynamics, and RF characteristics of space systems have matured to allow for rapid, detailed analysis of space communication links. However, the absence of a unified toolset that integrates the two modeling approaches has encumbered the systems engineers tasked with the design, architecture, and analysis of complex space communication networks and systems. This paper presents the unified approach and describes the motivation, challenges, and our solution - the customization of the network simulator to integrate with astronautical analysis software tools for high-fidelity end-to-end simulation. Keywords space; communication; systems; networking; simulation; modeling; QualNet; STK; integration; space networks
A. Sarfaraz Ahmed
Full Text Available In mobile ad hoc networks, communication among mobile nodes occurs through wireless medium The design of ad hoc network protocol, generally based on a traditional “layered approach”, has been found ineffective to deal with receiving signal strength (RSS-related problems, affecting the physical layer, the network layer and transport layer. This paper proposes a design approach, deviating from the traditional network design, toward enhancing the cross-layer interaction among different layers, namely physical, MAC and network. The Cross-Layer design approach for Power control (CLPC would help to enhance the transmission power by averaging the RSS values and to find an effective route between the source and the destination. This cross-layer design approach was tested by simulation (NS2 simulator and its performance over AODV was found to be better.
Kusmanoff, Antone L.; Barton, Timothy J.
The main goal is to resolve the interoperability problem of applications employing DOD TCP/IP (Department of Defence Transmission Control Protocol/Internet Protocol) family of protocols on a CCITT/ISO based network. The objective is to allow them to communicate over the CCITT/ISO protocol GPLAN (General Purpose Local Area Network) network without modification to the user's application programs. There were two primary assumptions associated with the solution that was actually realized. The first is that the solution had to allow for future movement to the exclusive use of the CCITT/ISO standards. The second is that the solution had to be software transparent to the currently installed TCP/IP and CCITT/ISO user application programs.
Full Text Available ABSTRACT Managing a one-way vehicle sharing system means periodically moving free access vehicles from excess to deficit stations in order to avoid local shortages. We propose and study here several network flow oriented models and algorithms which deal with a static version of this problem while unifying preemption and non preemption as well as carrier riding cost, vehicle riding time and carrier number minimization. Those network flow models are vehicle driven, which means that they focus on the way vehicles are exchanged between excess and deficit stations. We perform a lower bound and approximation analysis which leads us to the design and test of several heuristics. One of them involves implicit dynamic network handling.
Rossi, Vivien; Vila, Jean-Pierre
A Bayesian method for the comparison and selection of multioutput feedforward neural network topology, based on the predictive capability, is proposed. As a measure of the prediction fitness potential, an expected utility criterion is considered which is consistently estimated by a sample-reuse computation. As opposed to classic point-prediction-based cross-validation methods, this expected utility is defined from the logarithmic score of the neural model predictive probability density. It is shown how the advocated choice of a conjugate probability distribution as prior for the parameters of a competing network, allows a consistent approximation of the network posterior predictive density. A comparison of the performances of the proposed method with the performances of usual selection procedures based on classic cross-validation and information-theoretic criteria, is performed first on a simulated case study, and then on a well known food analysis dataset.
Christensen, Kim Hardam; Sørensen, Torben
penetration, when the gap width is varying during the welding process. The process modeling to facilitate the mapping from joint geometry and reference weld quality to significant welding parameters has been based on a multi-layer feed-forward network. The Levenberg-Marquardt algorithm for non-linear least......This paper describes the application of the neural network technology for gas metal arc welding (GMAW) control. A system has been developed for modeling and online adjustment of welding parameters, appropriate to guarantee a certain degree of quality in the field of butt joint welding with full...... squares has been used with the back-propagation algorithm for training the network, while a Bayesian regularization technique has been successfully applied for minimizing the risk of inexpedient over-training. Finally, a predictive closed-loop control strategy based on a so-called single-neuron self...
Khairuddin, Rozieana; Marlizawati Zainuddin, Zaitul; Jiun, Gan Jia
Now a day, several companies consider downsizing their distribution networks in ways that involve consolidation or phase-out of some of their current warehousing facilities due to the increasing competition, mounting cost pressure and taking advantage on the economies of scale. Consequently, the changes on economic situation after a certain period of time require an adjustment on the network model in order to get the optimal cost under the current economic conditions. This paper aimed to develop a mixed-integer linear programming model for a two-echelon warehouse network redesign problem with capacitated plant and uncapacitated warehouses. The main contribution of this study is considering capacity constraint for existing warehouses. A Simulated Annealing algorithm is proposed to tackle with the proposed model. The numerical solution showed the model and method of solution proposed was practical.
Qin Buzhi; Lu Xinbiao
Global synchronization of directed networks with switching topologies is investigated. It is found that if there exists at least one directed spanning tree in the network with the fixed time-average topology and the time-average topology is achieved sufficiently fast, the network will reach global synchronization for appreciate coupling strength. Furthermore, this appreciate coupling strength may be obtained by local adaptive approach. A sufficient condition about the global synchronization is given. Numerical simulations verify the effectiveness of the adaptive strategy.
Ирина Александровна Гавриленко
Full Text Available The approach to automated management of load flow in engineering networks considering functional reliability was proposed in the article. The improvement of the concept of operational and strategic management of load flow in engineering networks was considered. The verbal statement of the problem for thesis research is defined, namely, the problem of development of information technology for exact calculation of the functional reliability of the network, or the risk of short delivery of purpose-oriented product for consumers
Christensen, Kim Hardam; Sørensen, Torben
This paper describes the application of the neural network technology for gas metal arc welding (GMAW) control. A system has been developed for modeling and online adjustment of welding parameters, appropriate to guarantee a certain degree of quality in the field of butt joint welding with full...... penetration, when the gap width is varying during the welding process. The process modeling to facilitate the mapping from joint geometry and reference weld quality to significant welding parameters has been based on a multi-layer feed-forward network. The Levenberg-Marquardt algorithm for non-linear least...
Duarte, Otto Carlos M B
The first chapter of this title concerns virtualization techniques that allow sharing computational resources basically, slicing a real computational environment into virtual computational environments that are isolated from one another.The Xen and OpenFlow virtualization platforms are then presented in Chapter 2 and a performance analysis of both is provided. This chapter also defines the primitives that the network virtualization infrastructure must provide for allowing the piloting plane to manage virtual network elements.Following this, interfaces for system management of the two platform
Li, Xiaohong; Chen, Peiwen; Chen, Feng; Wang, Zijia
To quantify the spatiotemporal distribution of passenger flow and the characteristics of an urban rail transit network, we introduce four radius fractal dimensions and two branch fractal dimensions by combining a fractal approach with passenger flow assignment model. These fractal dimensions can numerically describe the complexity of passenger flow in the urban rail transit network and its change characteristics. Based on it, we establish a fractal quantification method to measure the fractal characteristics of passenger follow in the rail transit network. Finally, we validate the reasonability of our proposed method by using the actual data of Beijing subway network. It has been shown that our proposed method can effectively measure the scale-free range of the urban rail transit network, network development and the fractal characteristics of time-varying passenger flow, which further provides a reference for network planning and analysis of passenger flow.
Full Text Available Wireless sensor networks (WSN empower applications for critical decision-making through collaborative computing, communications, and distributed sensing. However, they face several challenges due to their peculiar use in a wide variety of applications. One of the inherent challenges with any battery operated sensor is the efficient consumption of energy and its effect on network lifetime. In this paper, we introduce a novel grid-based hybrid network deployment (GHND framework which ensures energy efficiency and load balancing in wireless sensor networks. This research is particularly focused on the merge and split technique to achieve even distribution of sensor nodes across the grid. Low density neighboring zones are merged together whereas high density zones are strategically split to achieve optimum balance. Extensive simulations reveal that the proposed method outperforms state-of-the-art techniques in terms of load balancing, network lifetime, and total energy consumption.
Anatol E. Wegner
Full Text Available Many real-world networks contain a statistically surprising number of certain subgraphs, called network motifs. In the prevalent approach to motif analysis, network motifs are detected by comparing subgraph frequencies in the original network with a statistical null model. In this paper, we propose an alternative approach to motif analysis where network motifs are defined to be connectivity patterns that occur in a subgraph cover that represents the network using minimal total information. A subgraph cover is defined to be a set of subgraphs such that every edge of the graph is contained in at least one of the subgraphs in the cover. Some recently introduced random graph models that can incorporate significant densities of motifs have natural formulations in terms of subgraph covers, and the presented approach can be used to match networks with such models. To prove the practical value of our approach, we also present a heuristic for the resulting NP hard optimization problem and give results for several real-world networks.
Hofstra, B.; Corten, R.; van Tubergen, F.A.; Ellison, Nicole
Most research on segregation in social networks considers small circles of strong ties, and little is known about segregation among the much larger number of weaker ties. This article proposes a novel approach to the study of these more extended networks, through the use of data on personal ties in
Dittmann, Lars; Christiansen, Henrik Lehrmann; Checko, Aleksandra
In future mobile networks aggregation at different levels is necessary but at the same time imposes challenges that mandate looking into new architectures. This paper presents the design consideration approach for a C-RAN based mobile aggregation network used in the EU HARP project. With this arc...
Lisboa, Eliana Santana; Coutinho, Clara Pereira
This article presents the sociometric analysis of the interactions in a forum of a social network created for the professional development of Portuguese-speaking teachers. The main goal of the forum, which was titled Stricto Sensu, was to discuss the educational value of programmes that joined the distance learning model in Brazil. The empirical…
Microwave sensor MSMR (Multifrequency Scanning Microwave Radiometer) data onboard Oceansat-1 was used for retrieval of monthly averages of near surface specific humidity (a) and air temperature (a) by means of Artificial Neural Network (ANN). The MSMR measures the microwave radiances in 8 channels at ...
R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22
mine it from space is an active research topic. Few attempts (Jourdan and .... Multi-layer networks use a variety of learn- ing techniques, the most popular being .... a learning rate of 0.7. Thus the back-propagation formula computes the delta error from the output layer back towards the input layer, in a layer-by- layer manner.
Islam, Tanvirul; Bedington, Robert; Ling, Alexander
Progress in realising quantum computers threatens to weaken existing public key encryption infrastructure. A global quantum key distribution (QKD) network can play a role in computational attack-resistant encryption. Such a network could use a constellation of high altitude platforms such as airships and satellites as trusted nodes to facilitate QKD between any two points on the globe on demand. This requires both space-to-ground and inter-platform links. However, the prohibitive cost of traditional satellite based development limits the experimental work demonstrating relevant technologies. To accelerate progress towards a global network, we use an emerging class of shoe-box sized spacecraft known as CubeSats. We have designed a polarization entangled photon pair source that can operate on board CubeSats. The robustness and miniature form factor of our entanglement source makes it especially suitable for performing pathfinder missions that studies QKD between two high altitude platforms. The technological outcomes of such mission would be the essential building blocks for a global QKD network.
Bordin, Chiara; Gordini, Angelo; Vigo, Daniele
District heating systems provide the heat generated in a centralized location to a set of users for their residential and commercial heating requirements. Heat distribution is generally obtained by using hot water or steam flowing through a closed network of insulated pipes and heat exchange
Full Text Available Current global market is driven by many factors, such as the information age, the time and amount of information distributed by many data channels it is practically impossible analyze all kinds of incoming information flows and transform them to data with classical methods. New requirements could be met by using other methods. Once trained on patterns artificial neural networks can be used for forecasting and they are able to work with extremely big data sets in reasonable time. The patterns used for learning process are samples of past data. This paper uses Radial Basis Functions neural network in comparison with Multi Layer Perceptron network with Back-propagation learning algorithm on prediction task. The task works with simplified numerical time series and includes forty observations with prediction for next five observations. The main topic of the article is the identification of the main differences between used neural networks architectures together with numerical forecasting. Detected differences then verify on practical comparative example.
Jäger, W.S.; Den Heijer, C.; Bolle, A.; Hanea, A.M.
In this paper we develop a Bayesian network (BN) that relates offshore storm conditions to their accompagnying flood characteristics and damages to residential buildings, following on the trend of integrated flood impact modeling. It is based on data from hydrodynamic storm simulations, information
R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22
However, with the advent of satellite technology, there are unique and .... neurons. The neurons are connected by links in term of weights. Each neuron in one layer has direct connection to the neurons of the subsequent layer. .... The structure of 5 layers feed-forward neural network and the details of single neuron. with the ...
Jason L. Wright; Milos Manic
Finding and identifying cryptography is a growing concern in the malware analysis community. In this paper, artificial neural networks are used to classify functional blocks from a disassembled program as being either cryptography related or not. The resulting system, referred to as NNLC (Neural Net for Locating Cryptography) is presented and results of applying this system to various libraries are described.
Van Reisen, J.L.B.
Process plants have high energy consumption. Much energy can be saved by a proper design of the heat exchanger network, which contains the main heat transferring equipment of the plant. Existing plants can often be made more energy-efficient by a retrofit: the (physical) modification of the
Goodson, Justin; Jang, Wooseung; Rantz, Marilyn
Purpose: The purpose of this research is twofold. The first purpose is to utilize a new methodology (Bayesian networks) for aggregating various quality indicators to measure the overall quality of care in nursing homes. The second is to provide new insight into the relationships that exist among various measures of quality and how such measures…
apply.54 Securing present day networking architectures with physical infrastructure presents known system environments to defend. However, cloud...There is a perception that migration to the cloud computing environment will also yield cost savings through reduced physical infrastructure and...technical staff. While the reality of reduced physical infrastructure will occur, it is not clear that the technical staff will be significantly reduced
van der Schaft, Arjan; Maschke, B.M.; Ortega, Romeo; Banos, A.; Lamnabhi-lagarrigue, F; Montoya, F.J.
It is discussed how network modeling of lumped-parameter physical systems naturally leads to a geometrically defined class of systems, called port-controlled Hamiltonian systems (with dissipation). The structural properties of these systems are investigated, in particular the existence of Casimir
Volker, L.; Scharpff, J.; De Weerdt, M.M.; Herder, P.M.
Transportation networks are important public infrastructures because they enable economic and social activity. Trends in contracting the maintenance of such assets have caused a shift in governance from a public body to market-like arrangements and changed the roles and responsibilities among asset
Martin, Julia W.; Hughes, Brian
This article highlights a middle ground for academic publishing between formal peer-reviewed journals and informal blogging that we call "Small "p" Publishing." Having implemented and tested a publishing network that illustrates this middle ground, we describe its unique contributions to scholars and learning communities. Three features that…
reliable runoff is hardly predicted by applying linear and non-linear regression methods. Therefore, in this study ... propagation network (FFBP) and conventional regression analysis (CRA) were employed to study their performances. From the .... tested ANNs against the regression-based, simple conceptual black box, or ...
Jevremovic, Aleksandar; Shimic, Goran; Veinovic, Mladen; Ristic, Nenad
The case study presented in this paper describes the pedagogical aspects and experience gathered while using an e-learning tool named IPA-PBL. Its main purpose is to provide additional motivation for adopting theoretical principles and procedures in a computer networks course. In the proposed model, the sequencing of activities of the learning…
Beck, Jessica; Kempener, Ruud; Cohen, Brett; Petrie, Jim
This paper explores a new approach to planning and optimization of energy networks, using a mix of global optimization and agent-based modeling tools. This approach takes account of techno-economic, environmental and social criteria, and engages explicitly with inherent network complexity in terms of the autonomous decision-making capability of individual agents within the network, who may choose not to act as economic rationalists. This is an important consideration from the standpoint of meeting sustainable development goals. The approach attempts to set targets for energy planning, by determining preferred network development pathways through multi-objective optimization. The viability of such plans is then explored through agent-based models. The combined approach is demonstrated for a case study of regional electricity generation in South Africa, with biomass as feedstock
Full Text Available Abstract Collaboration among health care providers and across systems is proposed as a strategy to improve health care delivery the world over. Over the past two decades, health care providers have been encouraged to work in partnership and build interdisciplinary teams. More recently, the notion of networks has entered this discourse but the lack of consensus and understanding about what is meant by adopting a network approach in health services limits its use. Also crucial to this discussion is the work of distinguishing the nature and extent of the impact of social relationships – generally referred to as social capital. In this paper, we review the rationale for collaboration in health care systems; provide an overview and synthesis of key concepts; dispel some common misconceptions of networks; and apply the theory to an example of primary healthcare network reform in Alberta (Canada. Our central thesis is that a relational approach to systems change, one based on a synthesis of network theory and social capital can provide the fodation for a multi-focal approach to primary healthcare reform. Action strategies are recommended to move from an awareness of 'networks' to fully translating knowledge from existing theory to guide planning and practice innovations. Decision-makers are encouraged to consider a multi-focal approach that effectively incorporates a network and social capital approach in planning and evaluating primary healthcare reform.
Scott, Catherine; Hofmeyer, Anne
Collaboration among health care providers and across systems is proposed as a strategy to improve health care delivery the world over. Over the past two decades, health care providers have been encouraged to work in partnership and build interdisciplinary teams. More recently, the notion of networks has entered this discourse but the lack of consensus and understanding about what is meant by adopting a network approach in health services limits its use. Also crucial to this discussion is the work of distinguishing the nature and extent of the impact of social relationships - generally referred to as social capital. In this paper, we review the rationale for collaboration in health care systems; provide an overview and synthesis of key concepts; dispel some common misconceptions of networks; and apply the theory to an example of primary healthcare network reform in Alberta (Canada). Our central thesis is that a relational approach to systems change, one based on a synthesis of network theory and social capital can provide the fodation for a multi-focal approach to primary healthcare reform. Action strategies are recommended to move from an awareness of 'networks' to fully translating knowledge from existing theory to guide planning and practice innovations. Decision-makers are encouraged to consider a multi-focal approach that effectively incorporates a network and social capital approach in planning and evaluating primary healthcare reform.
Full Text Available The unattended nature of wireless sensor networks makes them very vulnerable to malicious attacks. Therefore, how to preserve secure data collection is an important issue to wireless sensor networks. In this paper, we propose a novel approach of secure data collection for wireless sensor networks. We explore secret sharing and multipath routing to achieve secure data collection in wireless sensor network with compromised nodes. We present a novel tracing-feedback mechanism, which makes full use of the routing functionality of wireless sensor networks, to improve the quality of data collection. The major advantage of the approach is that the secure paths are constructed as a by-product of data collection. The process of secure routing causes little overhead to the sensor nodes in the network. Compared with existing works, the algorithms of the proposed approach are easy to implement and execute in resource-constrained wireless sensor networks. According to the result of a simulation experiment, the performance of the approach is better than the recent approaches with a similar purpose.
Full Text Available A new transient-based hybrid heuristic approach is developed to optimize a transient generation process and to detect leaks in pipe networks. The approach couples the ordinal optimization approach (OOA and the symbiotic organism search (SOS to solve the optimization problem by means of iterations. A pipe network analysis model (PNSOS is first used to determine steady-state head distribution and pipe flow rates. The best transient generation point and its relevant valve operation parameters are optimized by maximizing the objective function of transient energy. The transient event is created at the chosen point, and the method of characteristics (MOC is used to analyze the transient flow. The OOA is applied to sift through the candidate pipes and the initial organisms with leak information. The SOS is employed to determine the leaks by minimizing the sum of differences between simulated and computed head at the observation points. Two synthetic leaking scenarios, a simple pipe network and a water distribution network (WDN, are chosen to test the performance of leak detection ordinal symbiotic organism search (LDOSOS. Leak information can be accurately identified by the proposed approach for both of the scenarios. The presented technique makes a remarkable contribution to the success of leak detection in the pipe networks.
Full Text Available Argentina is among the four largest producers of soybeans, sunflower, corn, and wheat, among other agricultural products. Institutional and policy changes during the 1990s fostered the development of Argentine agriculture and the introduction of innovative process and product technologies (no-till, agrochemicals, GMO, GPS and new investments in modern, large-scale sunflower and soybean processing plants. In addition to technological changes, a "quiet revolution" occurred in the way agricultural production was carried out and organized: from self-production or ownership agriculture to a contract-based agriculture. The objective of this paper is to explore and describe the emergence of networks in the Argentine crop production sector. The paper presents and describes four cases that currently represent about 50% of total grain and oilseed production in Argentina: "informal hybrid form", "agricultural trust fund", "investor-oriented corporate structure", and "network of networks". In all cases, hybrid forms involve a group of actors linked by common objectives, mainly to gain scale, share resources, and improve the profitability of the business. Informal contracts seem to be the most common way of organizing the agriculture process, but using short-term contracts and sequential interfirm collaboration. Networks of networks involve long-term relationships and social development, and reciprocal interfirm collaboration. Agricultural trust fund and investor-oriented corporate structures have combined interfirm collaboration and medium-term relationships. These organizational forms are highly flexible and show a great capacity to adapt to challenges; they are competitive because they enjoy aligned incentives, flexibility, and adaptability.
Ghaddar, Bissan; Jabr, Rabih
Transmission network expansion planning is a mixed-integer optimization problem, whose solution is used to guide future investment in transmission equipment. An approach is presented to find the global solution of the transmission planning problem using an AC network model. The approach builds on the semidefinite relaxation of the AC optimal power flow problem (ACOPF); its computational engine is a new specialized branch-and-cut algorithm for transmission expansion planning to deal with the u...
Mortensen, Kjeld Høyer; Schougaard, Kari Rye; Schultz, Ulrik Pagh
Home networks and the interconnection of home appliances is a classical theme in pervasive computing research. Security is usually addressed through the use of encryption and authentication, but there is a lack of awareness of safety: reventing the computerized house from harming the inhabitants......, even in a worst-case scenario where an unauthorized user gains remote control of the facilities. We address this safety issue at the programming language level by restricting the operations that can be performed on devices according to the physical location of the user initiating the request......-based restrictions on operations. This model has been implemented in a middleware for home AV devices written in Java, using infrared communication and a FireWire network to implement location awareness....
Mortensen, Kjeld Høyer; Schougaard, Kari Sofie Fogh; Schultz, Ulrik Pagh
Home networks and the interconnection of home appliances is a classical theme in pervasive computing research. Security is usually addressed through the use of encryption and authentication, but there is a lack of awareness of safety: preventing the computerized house from harming the inhabitants......, even in a worst-case scenario where an unauthorized user gains remote control of the facilities. We address this safety issue at the programming language level by restricting the operations that can be performed on devices according to the physical location of the user initiating the request......-based restrictions on operations. This model has been implemented in a middleware for home AV devices written in Java, using infrared communication and a FireWire network to implement location awareness....
López, Diego M; Blobel, Bernd; González, Carolina
Quality of information and privacy and safety issues are frequently identified as main limitations to make most benefit from social media in healthcare. The objective of the paper is to contribute to the analysis of healthcare social networks (SN), and online healthcare social network services (SNS) by proposing a formal architectural analysis of healthcare SN and SNS, considering the complexity of both systems, but stressing on quality, safety and usability aspects. Quality policies are necessary to control the quality of content published by experts and consumers. Privacy and safety policies protect against inappropriate use of information and users responsibility for sharing information. After the policies are established and documented, a proof of concept online SNS supporting primary healthcare promotion is presented in the paper.
Full Text Available Abstract The current technology allows the integration on a single die of complex systems-on-chip (SoCs that are composed of manufactured blocks (IPs, interconnected through specialized networks on chip (NoCs. IPs have usually been validated by diverse techniques (simulation, test, formal verification and the key problem remains the validation of the communication infrastructure. This paper addresses the formal verification of NoCs by means of a mechanized proof tool, the ACL2 theorem prover. A metamodel for NoCs has been developed and implemented in ACL2. This metamodel satisfies a generic correctness statement. Its verification for a particular NoC instance is reduced to discharging a set of proof obligations for each one of the NoC constituents. The methodology is demonstrated on a realistic and state-of-the-art design, the Spidergon network from STMicroelectronics.
Neshati, Mahmood; Hashemi, Seyyed Hadi; Beigy, Hamid
Expert finding problem in bibliographic networks has received increased interest in recent years. This problem concerns finding relevant researchers for a given topic. Motivated by the observation that rarely do all coauthors contribute to a paper equally, in this paper, we propose two discriminative methods for realizing leading authors contributing in a scientific publication. Specifically, we cast the problem of expert finding in a bibliographic network to find leading experts in a research group, which is easier to solve. We recognize three feature groups that can discriminate relevant experts from other authors of a document. Experimental results on a real dataset, and a synthetic one that is gathered from a Microsoft academic search engine, show that the proposed model significantly improves the performance of expert finding in terms of all common information retrieval evaluation metrics.
Xu, Xin; Cui, Qiang
This paper focuses on evaluating airline energy efficiency, which is firstly divided into four stages: Operations Stage, Fleet Maintenance Stage, Services Stage and Sales Stage. The new four-stage network structure of airline energy efficiency is a modification of existing models. A new approach, integrated with Network Epsilon-based Measure and Network Slacks-based Measure, is applied to assess the overall energy efficiency and divisional efficiency of 19 international airlines from 2008 to 2014. The influencing factors of airline energy efficiency are analyzed through the regression analysis. The results indicate the followings: 1. The integrated model can identify the benchmarking airlines in the overall system and stages. 2. Most airlines' energy efficiencies keep steady during the period, except for some sharply fluctuations. The efficiency decreases mainly centralized in the year 2008–2011, affected by the financial crisis in the USA. 3. The average age of fleet is positively correlated with the overall energy efficiency, and each divisional efficiency has different significant influencing factors. - Highlights: • An integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure is developed. • 19 airlines' energy efficiencies are evaluated. • Garuda Indonesia has the highest overall energy efficiency.
Mueller Laurin AJ
Full Text Available Abstract Background Identifying group-specific characteristics in metabolic networks can provide better insight into evolutionary developments. Here, we present an approach to classify the three domains of life using topological information about the underlying metabolic networks. These networks have been shown to share domain-independent structural similarities, which pose a special challenge for our endeavour. We quantify specific structural information by using topological network descriptors to classify this set of metabolic networks. Such measures quantify the structural complexity of the underlying networks. In this study, we use such measures to capture domain-specific structural features of the metabolic networks to classify the data set. So far, it has been a challenging undertaking to examine what kind of structural complexity such measures do detect. In this paper, we apply two groups of topological network descriptors to metabolic networks and evaluate their classification performance. Moreover, we combine the two groups to perform a feature selection to estimate the structural features with the highest classification ability in order to optimize the classification performance. Results By combining the two groups, we can identify seven topological network descriptors that show a group-specific characteristic by ANOVA. A multivariate analysis using feature selection and supervised machine learning leads to a reasonable classification performance with a weighted F-score of 83.7% and an accuracy of 83.9%. We further demonstrate that our approach outperforms alternative methods. Also, our results reveal that entropy-based descriptors show the highest classification ability for this set of networks. Conclusions Our results show that these particular topological network descriptors are able to capture domain-specific structural characteristics for classifying metabolic networks between the three domains of life.
Merrett, Geoff V.; Weddell, Alex S.; Harris, Nick R.; White, Neil M.; Al-Hashimi, Bashir M.
Since its introduction in the mid-1970s, the OSI Basic Reference Model (OSI-BRM) has been widely used as a foundation for communication models and standards. While many of these have modified the OSI-BRM for specific communication requirements (protocols such as ZigBee and Fieldbus – used in sensor networks), little structure or standardisation has been developed for other aspects of the hardware/software interface – for example sensing, energy management, actuation or locationing. Such proce...
Gracia-Lázaro, Carlos; Quijandría, Fernando; Hernández, Laura; Floría, Luis Mario; Moreno, Yamir
Starting from Axelrod's model of cultural dissemination, we introduce a rewiring probability, enabling agents to cut the links with their unfriendly neighbors if their cultural similarity is below a tolerance parameter. For low values of tolerance, rewiring promotes the convergence to a frozen monocultural state. However, intermediate tolerance values prevent rewiring once the network is fragmented, resulting in a multicultural society even for values of initial cultural diversity in which the original Axelrod model reaches globalization.
Wan, Thomas T H; Wang, Bill B L
This study examines the effects of integration on the performance ratings of the top 100 integrated healthcare networks (IHNs) in the United States. A strategic-contingency theory is used to identify the relationship of IHNs' performance to their structural and operational characteristics and integration strategies. To create a database for the panel study, the top 100 IHNs selected by the SMG Marketing Group in 1998 were followed up in 1999 and 2000. The data were merged with the Dorenfest data on information system integration. A growth curve model was developed and validated by the Mplus statistical program. Factors influencing the top 100 IHNs' performance in 1998 and their subsequent rankings in the consecutive years were analyzed. IHNs' initial performance scores were positively influenced by network size, number of affiliated physicians and profit margin, and were negatively associated with average length of stay and technical efficiency. The continuing high performance, judged by maintaining higher performance scores, tended to be enhanced by the use of more managerial or executive decision-support systems. Future studies should include time-varying operational indicators to serve as predictors of network performance.
Full Text Available Pseudomonas aeruginosa is a metabolically flexible member of the Gammaproteobacteria. Under anaerobic conditions and the presence of nitrate, P. aeruginosa can perform (complete denitrification, a respiratory process of dissimilatory nitrate reduction to nitrogen gas via nitrite (NO2, nitric oxide (NO and nitrous oxide (N2O. This study focuses on understanding the influence of environmental conditions on bacterial denitrification performance, using a mathematical model of a metabolic network in P. aeruginosa. To our knowledge, this is the first mathematical model of denitrification for this bacterium. Analysis of the long-term behavior of the network under changing concentration levels of oxygen (O2, nitrate (NO3, and phosphate (PO4 suggests that PO4 concentration strongly affects denitrification performance. The model provides three predictions on denitrification activity of P. aeruginosa under various environmental conditions, and these predictions are either experimentally validated or supported by pertinent biological literature. One motivation for this study is to capture the effect of PO4 on a denitrification metabolic network of P. aeruginosa in order to shed light on mechanisms for greenhouse gas N2O accumulation during seasonal oxygen depletion in aquatic environments such as Lake Erie (Laurentian Great Lakes, USA. Simulating the microbial production of greenhouse gases in anaerobic aquatic systems such as Lake Erie allows a deeper understanding of the contributing environmental effects that will inform studies on, and remediation strategies for, other hypoxic sites worldwide.
Arat, Seda; Bullerjahn, George S; Laubenbacher, Reinhard
Pseudomonas aeruginosa is a metabolically flexible member of the Gammaproteobacteria. Under anaerobic conditions and the presence of nitrate, P. aeruginosa can perform (complete) denitrification, a respiratory process of dissimilatory nitrate reduction to nitrogen gas via nitrite (NO2), nitric oxide (NO) and nitrous oxide (N2O). This study focuses on understanding the influence of environmental conditions on bacterial denitrification performance, using a mathematical model of a metabolic network in P. aeruginosa. To our knowledge, this is the first mathematical model of denitrification for this bacterium. Analysis of the long-term behavior of the network under changing concentration levels of oxygen (O2), nitrate (NO3), and phosphate (PO4) suggests that PO4 concentration strongly affects denitrification performance. The model provides three predictions on denitrification activity of P. aeruginosa under various environmental conditions, and these predictions are either experimentally validated or supported by pertinent biological literature. One motivation for this study is to capture the effect of PO4 on a denitrification metabolic network of P. aeruginosa in order to shed light on mechanisms for greenhouse gas N2O accumulation during seasonal oxygen depletion in aquatic environments such as Lake Erie (Laurentian Great Lakes, USA). Simulating the microbial production of greenhouse gases in anaerobic aquatic systems such as Lake Erie allows a deeper understanding of the contributing environmental effects that will inform studies on, and remediation strategies for, other hypoxic sites worldwide.
Qi, Hongsheng; Liu, Meiqi; Zhang, Lihui; Wang, Dianhai
Urban road congestions change both temporally and spatially. They are essentially caused by network bottlenecks. Therefore, understanding bottleneck dynamics is critical in the goal of reasonably allocating transportation resources. In general, a typical bottleneck experiences the stages of formation, propagation and dispersion. In order to understand the three stages of a bottle neck and how the bottleneck moves on a road network, traffic flow data can be used to reconstruct these dynamics. However, raw traffic flow data is usually flawed in many ways. For instance some portion of data may be missing due to the failure of data collection devices, or some random factors in the data make it hard to identify real bottlenecks. In this paper a "user voting method" is proposed to deal with such raw-data-related issues. In this method, road links are ranked according to the weighed sum of certain performance measures and the links that are ranked relatively high are regarded as recurrent bottlenecks in a network, and several bottlenecks form a bottleneck area. A series of bottleneck parameters can be defined based on the identified bottleneck areas, such as bottleneck coverage, bottleneck link length, etc. Identifying bottleneck areas and calculating the bottleneck parameters for each time interval can reflect the evolution of the bottlenecks and also help trace how the bottlenecks move.
Full Text Available Abstract Background Pulmonary surfactant is required for lung function at birth and throughout life. Lung lipid and surfactant homeostasis requires regulation among multi-tiered processes, coordinating the synthesis of surfactant proteins and lipids, their assembly, trafficking, and storage in type II cells of the lung. The mechanisms regulating these interrelated processes are largely unknown. Results We integrated mRNA microarray data with array independent knowledge using Gene Ontology (GO similarity analysis, promoter motif searching, protein interaction and literature mining to elucidate genetic networks regulating lipid related biological processes in lung. A Transcription factor (TF - target gene (TG similarity matrix was generated by integrating data from different analytic methods. A scoring function was built to rank the likely TF-TG pairs. Using this strategy, we identified and verified critical components of a transcriptional network directing lipogenesis, lipid trafficking and surfactant homeostasis in the mouse lung. Conclusions Within the transcriptional network, SREBP, CEBPA, FOXA2, ETSF, GATA6 and IRF1 were identified as regulatory hubs displaying high connectivity. SREBP, FOXA2 and CEBPA together form a common core regulatory module that controls surfactant lipid homeostasis. The core module cooperates with other factors to regulate lipid metabolism and transport, cell growth and development, cell death and cell mediated immune response. Coordinated interactions of the TFs influence surfactant homeostasis and regulate lung function at birth.
Stamenković Lidija J.
Full Text Available The aim of this study was to develop a model for forecasting CH4 emissions at the national level, using Artificial Neural Networks (ANN with broadly available sustainability, economical and industrial indicators as their inputs. ANN modeling was performed using two different types of architecture; a Backpropagation Neural Network (BPNN and a General Regression Neural Network (GRNN. A conventional multiple linear regression (MLR model was also developed in order to compare model performance and assess which model provides the best results. ANN and MLR models were developed and tested using the same annual data for 20 European countries. The ANN model demonstrated very good performance, significantly better than the MLR model. It was shown that a forecast of CH4 emissions at the national level using the ANN model can be made successfully and accurately for a future period of up to two years, thereby opening the possibility to apply such a modeling technique which can be used to support the implementation of sustainable development strategies and environmental management policies. [Projekat Ministarstva nauke Republike Srbije, br. 172007
Chuah, Teong Chee; Sharif, B S; Hinton, O R
Abstract-Recently, a robust version of the linear decorrelating detector (LDD) based on the Huber's M-estimation technique has been proposed. In this paper, we first demonstrate the use of a three-layer recurrent neural network (RNN) to implement the LDD without requiring matrix inversion. The key idea is based on minimizing an appropriate computational energy function iteratively. Second, it will be shown that the M-decorrelating detector (MDD) can be implemented by simply incorporating sigmoidal neurons in the first layer of the RNN. A proof of the redundancy of the matrix inversion process is provided and the computational saving in realistic network is highlighted. Third, we illustrate how further performance gain could be achieved for the subspace-based blind MDD by using robust estimates of the signal subspace components in the initial stage. The impulsive noise is modeled using non-Gaussian alpha-stable distributions, which do not include a Gaussian component but facilitate the use of the recently proposed geometric signal-to-noise ratio (G-SNR). The characteristics and performance of the proposed neural-network detectors are investigated by computer simulation.
Blikra, Espen; The ATLAS collaboration
ATLAS is a high energy physics experiment in the Large Hadron Collider located at CERN. During the so called Long Shutdown 2 period scheduled for late 2019, ATLAS will undergo several modifications and upgrades on its data acquisition system in order to cope with the higher luminosity requirements. As part of these activities, a new read-out chain will be built for the New Small Wheel muon detector and the one of the Liquid Argon calorimeter will be upgraded. The subdetector specific electronic boards will be replaced with new commodity-server-based systems and instead of the custom serial-link-based communication, the new system will make use of a yet to be chosen commercial network technology. The new network will be used as a data acquisition network and at the same time it is intended to allow communication for the control, calibration and monitoring of the subdetectors. Therefore several types of traffic with different bandwidth requirements and different criticality will be competing for the same underl...
Christiano Silva, Thiago; Raphael Amancio, Diego
Many patterns have been uncovered in complex systems through the application of concepts and methodologies of complex networks. Unfortunately, the validity and accuracy of the unveiled patterns are strongly dependent on the amount of unavoidable noise pervading the data, such as the presence of homonymous individuals in social networks. In the current paper, we investigate the problem of name disambiguation in collaborative networks, a task that plays a fundamental role on a myriad of scientific contexts. In special, we use an unsupervised technique which relies on a particle competition mechanism in a networked environment to detect the clusters. It has been shown that, in this kind of environment, the learning process can be improved because the network representation of data can capture topological features of the input data set. Specifically, in the proposed disambiguating model, a set of particles is randomly spawned into the nodes constituting the network. As time progresses, the particles employ a movement strategy composed of a probabilistic convex mixture of random and preferential walking policies. In the former, the walking rule exclusively depends on the topology of the network and is responsible for the exploratory behavior of the particles. In the latter, the walking rule depends both on the topology and the domination levels that the particles impose on the neighboring nodes. This type of behavior compels the particles to perform a defensive strategy, because it will force them to revisit nodes that are already dominated by them, rather than exploring rival territories. Computer simulations conducted on the networks extracted from the arXiv repository of preprint papers and also from other databases reveal the effectiveness of the model, which turned out to be more accurate than traditional clustering methods.
Andersen, Jacob; Bardram, Jakob Eyvind
Using body sensor networks (BSN) in critical clinical settings like emergency units in hospitals or in accidents requires that such a network can be deployed, configured, and started in a fast and easy way, while maintaining trust in the network. In this paper we present a novel approach called...... BLIG (Blinking Led Indicated Grouping) for easy deployment of BSNs on patients in critical situations, including mechanisms for uniquely identifying and grouping sensor nodes belonging to a patient in a secure and trusted way. This approach has been designed in close cooperation with users, and easy...
Full Text Available Cardiovascular diseases (CVDs are the leading health problem worldwide. Investigating causes and mechanisms of CVDs calls for an integrative approach that would take into account its complex etiology. Biological networks generated from available data on biomolecular interactions are an excellent platform for understanding interconnectedness of all processes within a living cell, including processes that underlie diseases. Consequently, topology of biological networks has successfully been used for identifying genes, pathways, and modules that govern molecular actions underlying various complex diseases. Here, we review approaches that explore and use relationships between topological properties of biological networks and mechanisms underlying CVDs.
Kreakie, B. J.; Hychka, K. C.; Belaire, J. A.; Minor, E.; Walker, H. A.
Social network analysis (SNA) is based on a conceptual network representation of social interactions and is an invaluable tool for conservation professionals to increase collaboration, improve information flow, and increase efficiency. We present two approaches to constructing internet-based social networks, and use an existing traditional (survey-based) case study to illustrate in a familiar context the deviations in methods and results. Internet-based approaches to SNA offer a means to overcome institutional hurdles to conducting survey-based SNA, provide unique insight into an institution's web presences, allow for easy snowballing (iterative process that incorporates new nodes in the network), and afford monitoring of social networks through time. The internet-based approaches differ in link definition: hyperlink is based on links on a website that redirect to a different website and relatedness links are based on a Google's "relatedness" operator that identifies pages "similar" to a URL. All networks were initiated with the same start nodes [members of a conservation alliance for the Calumet region around Chicago ( n = 130)], but the resulting networks vary drastically from one another. Interpretation of the resulting networks is highly contingent upon how the links were defined.
Röhl, Annika; Bockmayr, Alexander
Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.
Tavakoli Taba, Seyedamir; Hossain, Liaquat; Heard, Robert; Brennan, Patrick; Lee, Warwick; Lewis, Sarah
Rationale and objectives: Observer performance has been widely studied through examining the characteristics of individuals. Applying a systems perspective, while understanding of the system's output, requires a study of the interactions between observers. This research explains a mixed methods approach to applying a social network analysis (SNA), together with a more traditional approach of examining personal/ individual characteristics in understanding observer performance in mammography. Materials and Methods: Using social networks theories and measures in order to understand observer performance, we designed a social networks survey instrument for collecting personal and network data about observers involved in mammography performance studies. We present the results of a study by our group where 31 Australian breast radiologists originally reviewed 60 mammographic cases (comprising of 20 abnormal and 40 normal cases) and then completed an online questionnaire about their social networks and personal characteristics. A jackknife free response operating characteristic (JAFROC) method was used to measure performance of radiologists. JAFROC was tested against various personal and network measures to verify the theoretical model. Results: The results from this study suggest a strong association between social networks and observer performance for Australian radiologists. Network factors accounted for 48% of variance in observer performance, in comparison to 15.5% for the personal characteristics for this study group. Conclusion: This study suggest a strong new direction for research into improving observer performance. Future studies in observer performance should consider social networks' influence as part of their research paradigm, with equal or greater vigour than traditional constructs of personal characteristics.
malware . Our approach for this learning problem has been to view this as hypothesis testing on graphs – given noisy and partial information on both...hypothesis (spreading process such as malware ). This approach has been used in a sequence of studies, starting from distinguishing with partial...remain attractive due to their low computational cost . The most natural greedy algorithm would be one which, essentially, adds neighbors to a node
Qiu, Lu; Gu, Changgui; Xiao, Qin; Yang, Huijie; Wu, Guolin
Extensive works have reported that a financial crisis can induce significant changes to topological structure of a stock network constructed with cross-correlations between stocks. But there are still some problems to be answered, such as what is the relationship between different crises in history and how to classify them? In the present work, we propose a new network-based solution to extract and display the relationships between the crises. The Dow Jones stock market is investigated as a typical example. The cross-correlation matrix between stocks is used to measure the state of stock market, called state matrix. All the states cluster into six sub-categories. A state network is constructed further to display the relationships between all the states, which contains a total of nine communities. It is found that three crises C , D and E (refer to the Lehman's bankruptcy in 2008, the Euro-zone and International Monetary Fund decide the first bailout for Greece in 2010, and the European sovereign debt crisis in 2011, respectively) belong to a specific sub-category and cluster in a single community. The mid-stage of C is closely linked with E, while the other stages with D. The other two crises A and B (refer to the financial crisis in Asia in 1997, and the burst of "dot-com bubble" in 2002, respectively) belong to another sub-category and gather in a corner of another single community. A and B are linked directly with C and D by two edges. By this way, we give a clear picture of the relationships between the crises.
Full Text Available Mobile ad hoc networks (MANETs are multi-hop wireless networks ofautonomous mobile nodes without any fixed infrastructure. In MANETs, it isdifficult to detect malicious nodes because the network topology constantly changesdue to node mobility. Intrusion detection is the means to identify the intrusivebehaviors and provide useful information to intruded systems to respond fast and toavoid or reduce damages. The anomaly detection algorithms have the advantagebecause they can detect new types of attacks (zero-day attacks.In this paper, wepresent a Intrusion Detection System clustering-based (ID-Cluster that fits therequirement of MANET. This dissertation addresses both routing layer misbehaviorsissues, with main focuses on thwarting routing disruption attack Dynamic SourceRouting (DSR. To validate the research, a case study is presented using thesimulation with GloMoSum at different mobility levels. Simulation results show thatour proposed system can achieve desirable performance and meet the securityrequirement of MANET.
Núñez-Serna, Rosa I.; Zamora, Juan M.
Highlights: • An NLP model for the optimal design of heat exchanger networks is proposed. • The NLP model is developed from a stage-wise grid diagram representation. • A two-phase stochastic multi-start optimization methodology is utilized. • Improved network designs are obtained with different heat load distributions. • Structural changes and reductions in the number of heat exchangers are produced. - Abstract: Heat exchanger network synthesis methodologies frequently identify good network structures, which nevertheless, might be accompanied by suboptimal values of design variables. The objective of this work is to develop a nonlinear programming (NLP) model and an optimization approach that aim at identifying the best values for intermediate temperatures, sub-stream flow rate fractions, heat loads and areas for a given heat exchanger network topology. The NLP model that minimizes the total annual cost of the network is constructed based on a stage-wise grid diagram representation. To improve the possibilities of obtaining global optimal designs, a two-phase stochastic multi-start optimization algorithm is utilized for the solution of the developed model. The effectiveness of the proposed optimization approach is illustrated with the optimization of two network designs proposed in the literature for two well-known benchmark problems. Results show that from the addressed base network topologies it is possible to achieve improved network designs, with redistributions in exchanger heat loads that lead to reductions in total annual costs. The results also show that the optimization of a given network design sometimes leads to structural simplifications and reductions in the total number of heat exchangers of the network, thereby exposing alternative viable network topologies initially not anticipated.
O’Keefe, Daniel J.; Wu, Daisy
Persuading people to undertake actions to prevent skin cancer is an important public health challenge. A number of studies have compared the effectiveness of gain-framed and loss-framed appeals in this domain, often expecting gain-framed appeals to be more persuasive. A meta-analytic review (k = 33, N = 4,168), however, finds no significant difference in the persuasiveness of gain- and loss-framed appeals for encouraging skin cancer prevention. This conclusion is unaffected by differences in the specific protective action advocated or by differences in the kind of outcomes invoked. But the results offer an intimation that men might be more susceptible to framing variations in this domain—with loss-framed appeals potentially having a persuasive advantage. PMID:22829794
Bayraktarli, Yahya; Faber, Michael
This paper considers the application of Bayesian probabilistic networks (BPNs) to large-scale risk based decision making in regard to earthquake risks. A recently developed risk management framework is outlined which utilises Bayesian probabilistic modelling, generic indicator based risk models...... and a fourth module on the consequences of an earthquake. Each of these modules is integrated into a BPN. Special attention is given to aggregated risk, i.e. the risk contribution from assets at multiple locations in a city subjected to the same earthquake. The application of the methodology is illustrated...
simulation, we used open source XviD MPEG-4 compliant video codec . Sixty seconds of a high motion video sequence (football match) are encoded at 15...Johnson, “Design and demonstration of live audio and video over multi-hop wireless networks,” In MILCOM, 2002.  T. Goff, N. Abu-Ghazaleh, D...24] E. Gilbert, “Capacity of a burst-noise channel,” Bell Syst. Tech. J., vol. 39, no. 9, pp. 1253-1265, Sept. 1960.  XviD MPEG-4 video codec
Qiao, D M; Shi, H B; Pang, H B
as a demonstrating example. The inputs to the neural network model included soil moisture, electrical conductivity of the soil solution, height and diameter of plant shoot, potential evapotranspiration, atmospheric humidity and air temperature. The outputs were the root water uptake rate at different depths...... in the soil profile. To train and test the model, the root water uptake rate was directly measured based on mass balance and Darcy's law assessed from the measured soil moisture content and soil water matric potential in profiles from the soil surface to a depth of 100 cm. The ‘measured' root water uptake...
Khan, Bisma S.; Niazi, Muaz A.
Communication networks, in general, and internet technology, in particular, is a fast-evolving area of research. While it is important to keep track of emerging trends in this domain, it is such a fast-growing area that it can be very difficult to keep track of literature. The problem is compounded by the fast-growing number of citation databases. While other databases are gradually indexing a large set of reliable content, currently the Web of Science represents one of the most highly valued...
Ahamed, Syed V
This textbook offers an insightful study of the intelligent Internet-driven revolutionary and fundamental forces at work in society. Readers will have access to tools and techniques to mentor and monitor these forces rather than be driven by changes in Internet technology and flow of money. These submerged social and human forces form a powerful synergistic foursome web of (a) processor technology, (b) evolving wireless networks of the next generation, (c) the intelligent Internet, and (d) the motivation that drives individuals and corporations. In unison, the technological forces can tear
Full Text Available This paper introduces the sensor-networked IoT model as a prototype to support the design of Body Area Network (BAN applications for healthcare. Using the model, we analyze the synergistic effect of the functional requirements (data collection from the human body and transferring it to the top level and non-functional requirements (trade-offs between energy-security-environmental factors, treated as Quality-of-Service (QoS. We use feature models to represent the requirements at the earliest stage for the analysis and describe a model-driven methodology to design the possible BAN applications. Firstly, we specify the requirements as the problem domain (PD variability model for the BAN applications. Next, we introduce the generative technology (meta-programming as the solution domain (SD and the mapping procedure to map the PD feature-based variability model onto the SD feature model. Finally, we create an executable meta-specification that represents the BAN functionality to describe the variability of the problem domain though transformations. The meta-specification (along with the meta-language processor is a software generator for multiple BAN-oriented applications. We validate the methodology with experiments and a case study to generate a family of programs for the BAN sensor controllers. This enables to obtain the adequate measure of QoS efficiently through the interactive adjustment of the meta-parameter values and re-generation process for the concrete BAN application.
Biswas, M.A. Rafe; Robinson, Melvin D.; Fumo, Nelson
Some of the challenges to predict energy utilization has gained recognition in the residential sector due to the significant energy consumption in recent decades. However, the modeling of residential building energy consumption is still underdeveloped for optimal and robust solutions while this research area has become of greater relevance with significant advances in computation and simulation. Such advances include the advent of artificial intelligence research in statistical model development. Artificial neural network has emerged as a key method to address the issue of nonlinearity of building energy data and the robust calculation of large and dynamic data. The development and validation of such models on one of the TxAIRE Research houses has been demonstrated in this paper. The TxAIRE houses have been designed to serve as realistic test facilities for demonstrating new technologies. The input variables used from the house data include number of days, outdoor temperature and solar radiation while the output variables are house and heat pump energy consumption. The models based on Levenberg-Marquardt and OWO-Newton algorithms had promising results of coefficients of determination within 0.87–0.91, which is comparable to prior literature. Further work will be explored to develop a robust model for residential building application. - Highlights: • A TxAIRE research house energy consumption data was collected in model development. • Neural network models developed using Levenberg–Marquardt or OWO-Newton algorithms. • Model results match well with data and statistically consistent with literature.
Ahmed, Z.; Nazir, B.; Zafar, M.F.; Anwar, M.M.; Azam, K.; Asar, A.U.
Network security is a discipline that focuses on securing networks from unauthorized access. Given the Escalating threats of malicious cyber attacks, modern enterprises employ multiple lines of defense. A comprehensive defense strategy against such attacks should include (I) an attack detection component that deter- mines the fact that a program is compromised, (2) an attack identification and prevention component that identifies attack packets so that one can block such packets in the future and prevents the attack from further propagation. Over the last decade, a significant amount of research has been vested in the systems that can detect cyber attacks either statically at compile time or dynamically at run time, However, not much effort is spent on automated attack packet identification or attack prevention. In this paper we present a unified solution to the problems mentioned above. We implemented this solution after the forward engineering of Open Source Security Information Management (OSSIM) system called Preventive Information Security management (PrISM) system that correlates input from different sensors so that the resulting product can automatically detect any cyber attack against it and prevents by identifying the actual attack packet(s). The PrISM was always able to detect the attacks, identify the attack packets and most often prevent by blocking the attacker's IP address to continue normal execution. There is no additional run-time performance overhead for attack prevention. (author)
Full Text Available The paper deals with the development of simple electromagnetic models of small airplanes, which can contain composite materials in their construction. Electromagnetic waves can penetrate through the surface of the aircraft due to the specific electromagnetic properties of the composite materials, which can increase the intensity of fields inside the airplane and can negatively influence the functionality of the sensitive avionics. The airplane is simulated by two parallel dielectric layers (the left-hand side wall and the right-hand side wall of the airplane. The layers are put into a rectangular metallic waveguide terminated by the absorber in order to simulate the illumination of the airplane by the external wave (both of the harmonic nature and pulse one. Thanks to the simplicity of the model, the parametric analysis can be performed, and the results can be used in order to train an artificial neural network. The trained networks excel in further reduction of CPU-time demands of an airplane modeling.
Das Suprem R.
Full Text Available Although transparent conductive oxides such as indium tin oxide (ITO are widely employed as transparent conducting electrodes (TCEs for applications such as touch screens and displays, new nanostructured TCEs are of interest for future applications, including emerging transparent and flexible electronics. A number of twodimensional networks of nanostructured elements have been reported, including metallic nanowire networks consisting of silver nanowires, metallic carbon nanotubes (m-CNTs, copper nanowires or gold nanowires, and metallic mesh structures. In these single-component systems, it has generally been difficult to achieve sheet resistances that are comparable to ITO at a given broadband optical transparency. A relatively new third category of TCEs consisting of networks of 1D-1D and 1D-2D nanocomposites (such as silver nanowires and CNTs, silver nanowires and polycrystalline graphene, silver nanowires and reduced graphene oxide have demonstrated TCE performance comparable to, or better than, ITO. In such hybrid networks, copercolation between the two components can lead to relatively low sheet resistances at nanowire densities corresponding to high optical transmittance. This review provides an overview of reported hybrid networks, including a comparison of the performance regimes achievable with those of ITO and single-component nanostructured networks. The performance is compared to that expected from bulk thin films and analyzed in terms of the copercolation model. In addition, performance characteristics relevant for flexible and transparent applications are discussed. The new TCEs are promising, but significant work must be done to ensure earth abundance, stability, and reliability so that they can eventually replace traditional ITO-based transparent conductors.
The researchers took a commodity-based approach to evaluate the value of a list of selected commodities moved on the Texas freight network. This approach takes advantage of commodity-specific data sources and modeling processes. It provides a unique ...
Brandeau, Margaret L.
For many communicable diseases, knowledge of the underlying contact network through which the disease spreads is essential to determining appropriate control measures. When behavior change is the primary intervention for disease prevention, it is important to understand how to best modify network connectivity using the limited resources available to control disease spread. We describe and compare four algorithms for selecting a limited number of links to remove from a network: two “preventive” approaches (edge centrality, R0 minimization), where the decision of which links to remove is made prior to any disease outbreak and depends only on the network structure; and two “reactive” approaches (S-I edge centrality, optimal quarantining), where information about the initial disease states of the nodes is incorporated into the decision of which links to remove. We evaluate the performance of these algorithms in minimizing the total number of infections that occur over the course of an acute outbreak of disease. We consider different network structures, including both static and dynamic Erdős-Rényi random networks with varying levels of connectivity, a real-world network of residential hotels connected through injection drug use, and a network exhibiting community structure. We show that reactive approaches outperform preventive approaches in averting infections. Among reactive approaches, removing links in order of S-I edge centrality is favored when the link removal budget is small, while optimal quarantining performs best when the link removal budget is sufficiently large. The budget threshold above which optimal quarantining outperforms the S-I edge centrality algorithm is a function of both network structure (higher for unstructured Erdős-Rényi random networks compared to networks with community structure or the real-world network) and disease infectiousness (lower for highly infectious diseases). We conduct a value-of-information analysis of knowing
Full Text Available This paper presents a leader-based approach to routing in Mobile Wireless Sensor Networks (MWSN. Using local information from neighbour nodes, a leader election mechanism maintains a spanning tree in order to provide the necessary adaptations for efficient routing upon the connectivity changes resulting from the mobility of sensors or sink nodes. We present two protocols following the leader election approach, which have been implemented using Castalia and OMNeT++. The protocols have been evaluated, besides other reference MWSN routing protocols, to analyse the impact of network size and node velocity on performance, which has demonstrated the validity of our approach.
Burgos, Unai; Amozarrain, Ugaitz; Gómez-Calzado, Carlos; Lafuente, Alberto
This paper presents a leader-based approach to routing in Mobile Wireless Sensor Networks (MWSN). Using local information from neighbour nodes, a leader election mechanism maintains a spanning tree in order to provide the necessary adaptations for efficient routing upon the connectivity changes resulting from the mobility of sensors or sink nodes. We present two protocols following the leader election approach, which have been implemented using Castalia and OMNeT++. The protocols have been evaluated, besides other reference MWSN routing protocols, to analyse the impact of network size and node velocity on performance, which has demonstrated the validity of our approach.
Zeng, Liuting; Yang, Kailin; Liu, Huiping; Zhang, Guomin
To investigate the pharmacological mechanism of Guizhi Fuling Wan (GFW) in the treatment of uterine fibroids, a network pharmacology approach was used. Information on GFW compounds was collected from traditional Chinese medicine (TCM) databases, and input into PharmMapper to identify the compound targets. Genes associated with uterine fibroids genes were then obtained from the GeneCards and Online Mendelian Inheritance in Man databases. The interaction data of the targets and other human proteins was also collected from the STRING and IntAct databases. The target data were input into the Database for Annotation, Visualization and Integrated Discovery for gene ontology (GO) and pathway enrichment analyses. Networks of the above information were constructed and analyzed using Cytoscape. The following networks were compiled: A compound-compound target network of GFW; a herb-compound target-uterine fibroids target network of GWF; and a compound target-uterine fibroids target-other human proteins protein-protein interaction network, which were subjected to GO and pathway enrichment analyses. According to this approach, a number of novel signaling pathways and biological processes underlying the effects of GFW on uterine fibroids were identified, including the negative regulation of smooth muscle cell proliferation, apoptosis, and the Ras, wingless-type, epidermal growth factor and insulin-like growth factor-1 signaling pathways. This network pharmacology approach may aid the systematical study of herbal formulae and make TCM drug discovery more predictable.
Chiadamrong, N.; Piyathanavong, V.
Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.
Full Text Available Networks will continue to become increasingly heterogeneous as we move toward 5G. Meanwhile, the intelligent programming of the core network makes the available radio resource be more changeable rather than static. In such a dynamic and heterogeneous network environment, how to help terminal users select optimal networks to access is challenging. Prior implementations of network selection are usually applicable for the environment with static radio resources, while they cannot handle the unpredictable dynamics in 5G network environments. To this end, this paper considers both the fluctuation of radio resources and the variation of user demand. We model the access network selection scenario as a multiagent coordination problem, in which a bunch of rationally terminal users compete to maximize their benefits with incomplete information about the environment (no prior knowledge of network resource and other users’ choices. Then, an adaptive learning based strategy is proposed, which enables users to adaptively adjust their selections in response to the gradually or abruptly changing environment. The system is experimentally shown to converge to Nash equilibrium, which also turns out to be both Pareto optimal and socially optimal. Extensive simulation results show that our approach achieves significantly better performance compared with two learning and non-learning based approaches in terms of load balancing, user payoff and the overall bandwidth utilization efficiency. In addition, the system has a good robustness performance under the condition with non-compliant terminal users.
Keum, J.; Coulibaly, P. D.
Obtaining quality hydrologic observations is the first step towards a successful water resources management. While remote sensing techniques have enabled to convert satellite images of the Earth's surface to hydrologic data, the importance of ground-based observations has never been diminished because in-situ data are often highly accurate and can be used to validate remote measurements. The existence of efficient hydrometric networks is becoming more important to obtain as much as information with minimum redundancy. The World Meteorological Organization (WMO) has recommended a guideline for the minimum hydrometric network density based on physiography; however, this guideline is not for the optimum network design but for avoiding serious deficiency from a network. Moreover, all hydrologic variables are interconnected within the hydrologic cycle, while monitoring networks have been designed individually. This study proposes an integrated network design method using entropy theory with a multiobjective optimization approach. In specific, a precipitation and a streamflow networks in a semi-urban watershed in Ontario, Canada were designed simultaneously by maximizing joint entropy, minimizing total correlation, and maximizing conditional entropy of streamflow network given precipitation network. After comparing with the typical individual network designs, the proposed design method would be able to determine more efficient optimal networks by avoiding the redundant stations, in which hydrologic information is transferable. Additionally, four quantization cases were applied in entropy calculations to assess their implications on the station rankings and the optimal networks. The results showed that the selection of quantization method should be considered carefully because the rankings and optimal networks are subject to change accordingly.
Full Text Available This study focuses on seismic fragility assessment of horizontal curved bridge, which has been derived by neural network prediction. The objective is the optimization of structural responses of metaheuristic solutions. A regression model for the responses of the horizontal curved bridge with variable coefficients is built in the neural networks simulation environment based on the existing NTHA data. In order to achieve accurate results in a neural network, 1677 seismic analysis was performed in OpenSees. To achieve better performance of neural network and reduce the dimensionality of input data, dimensionality reduction techniques such as factor analysis approach were applied. Different types of neural network training algorithm were used and the best algorithm was adopted. The developed ANN approach is then used to verify the fragility curves of NTHA. The obtained results indicated that neural network approach could be used for predicting the seismic behavior of bridge elements and fragility, with enough feature extraction of ground motion records and response of structure according to the statistical works. Fragility curves extracted from the two approaches generally show proper compliance.
Blankendaal, Romy; Parinussa, Sarah; Treur, Jan
This paper introduces an integrated temporal-causal model for dynamics in social networks addressing the contagion principle by which states are affected mutually, and both the homophily principle and the more-becomes-more principle by which connections are adapted over time. The integrated model
Taylor-King, Jake P.; Basanta, David; Chapman, S. Jonathan; Porter, Mason A.
We consider evolving networks in which each node can have various associated properties (a state) in addition to those that arise from network structure. For example, each node can have a spatial location and a velocity, or it can have some more abstract internal property that describes something like a social trait. Edges between nodes are created and destroyed, and new nodes enter the system. We introduce a "local state degree distribution" (LSDD) as the degree distribution at a particular point in state space. We then make a mean-field assumption and thereby derive an integro-partial differential equation that is satisfied by the LSDD. We perform numerical experiments and find good agreement between solutions of the integro-differential equation and the LSDD from stochastic simulations of the full model. To illustrate our theory, we apply it to a simple model for osteocyte network formation within bones, with a view to understanding changes that may take place during cancer. Our results suggest that increased rates of differentiation lead to higher densities of osteocytes, but with a smaller number of dendrites. To help provide biological context, we also include an introduction to osteocytes, the formation of osteocyte networks, and the role of osteocytes in bone metastasis.
Browning, Christopher R; Soller, Brian; Jackson, Aubrey L
This study integrates insights from social network analysis, activity space perspectives, and theories of urban and spatial processes to present an novel approach to neighborhood effects on health-risk behavior among youth. We suggest spatial patterns of neighborhood residents' non-home routines may be conceptualized as ecological, or "eco"-networks, which are two-mode networks that indirectly link residents through socio-spatial overlap in routine activities. We further argue structural configurations of eco-networks are consequential for youth's behavioral health. In this study we focus on a key structural feature of eco-networks--the neighborhood-level extent to which household dyads share two or more activity locations, or eco-network reinforcement--and its association with two dimensions of health-risk behavior, substance use and delinquency/sexual activity. Using geographic data on non-home routine activity locations among respondents from the Los Angeles Family and Neighborhood Survey (L.A.FANS), we constructed neighborhood-specific eco-networks by connecting sampled households to "activity clusters," which are sets of spatially-proximate activity locations. We then measured eco-network reinforcement and examined its association with dimensions of adolescent health risk behavior employing a sample of 830 youth ages 12-17 nested in 65 census tracts. We also examined whether neighborhood-level social processes (collective efficacy and intergenerational closure) mediate the association between eco-network reinforcement and the outcomes considered. Results indicated eco-network reinforcement exhibits robust negative associations with both substance use and delinquency/sexual activity scales. Eco-network reinforcement effects were not explained by potential mediating variables. In addition to introducing a novel theoretical and empirical approach to neighborhood effects on youth, our findings highlight the importance of intersecting conventional routines for
Bayraktarli, Yahya; Faber, Michael
This paper considers the application of Bayesian probabilistic networks (BPNs) to large-scale risk based decision making in regard to earthquake risks. A recently developed risk management framework is outlined which utilises Bayesian probabilistic modelling, generic indicator based risk models...... and geographical information systems. The proposed framework comprises several modules: A module on the probabilistic description of potential future earthquake shaking intensity, a module on the probabilistic assessment of spatial variability of soil liquefaction, a module on damage assessment of buildings...... and a fourth module on the consequences of an earthquake. Each of these modules is integrated into a BPN. Special attention is given to aggregated risk, i.e. the risk contribution from assets at multiple locations in a city subjected to the same earthquake. The application of the methodology is illustrated...
Okoroh, Michael Iheoma; Ilozor, Benedict Dozie; Gombera, Peter
Hospitals as learning organisations have evolved through complex phases of service failures and continuous service improvement to meet the business needs of a varied continuum of care customers. This paper explores the use of Artificial Neural Network (ANN) in the development of a decision support system to manage healthcare non-clinical services. The information (postal questionnaires and repertory grid interviews) used to develop the input to the National Healthcare Service Facilities Risk Exposure System (NHSFRES) was articulated from 60 experienced healthcare operators. The system provides a reasonable early warning signal to the healthcare managers, and can be used by decision makers to evaluate the severity of risks on healthcare non clinical business operations. The advantage of using NHSFRES is that healthcare managers can provide their own risk assessment values (point score system) based on their own healthcare management business knowledge/judgement and corporate objectives.
Boutkhamouine, Brahim; Roux, Hélène; Pérès, François
Climate change is contributing to the increase of natural disasters such as extreme weather events. Sometimes, these events lead to sudden flash floods causing devastating effects on life and property. Most recently, many regions of the French Mediterranean perimeter have endured such catastrophic flood events; Var (October 2015), Ardèche (November 2014), Nîmes (October 2014), Hérault, Gard and Languedoc (September 2014), and Pyrenees mountains (Jun 2013). Altogether, it resulted in dozens of victims and property damages amounting to millions of euros. With this heavy loss in mind, development of hydrological forecasting and warning systems is becoming an essential element in regional and national strategies. Flash flood forecasting but also monitoring is a difficult task because small ungauged catchments ( 10 km2) are often the most destructive ones as for the extreme flash flood event of September 2002 in the Cévennes region (France) (Ruin et al., 2008). The problem of measurement/prediction uncertainty is particularly crucial when attempting to develop operational flash-flood forecasting methods. Taking into account the uncertainty related to the model structure itself, to the model parametrization or to the model forcing (spatio-temporal rainfall, initial conditions) is crucial in hydrological modelling. Quantifying these uncertainties is of primary importance for risk assessment and decision making. Although significant improvements have been made in computational power and distributed hydrologic modelling, the issue dealing with integration of uncertainties into flood forecasting remains up-to-date and challenging. In order to develop a framework which could handle these uncertainties and explain their propagation through the model, we propose to explore the potential of graphical models (GMs) and, more precisely, Bayesian Networks (BNs). These networks are Directed Acyclic Graphs (DAGs) in which knowledge of a certain phenomenon is represented by
The work presented in this dissertation concerns the study of a connectionist architecture to treat sequential inputs. In this context, the model proposed by J.L. Elman, a recurrent multilayers network, is used. Its abilities and its limits are evaluated. Modifications are done in order to treat erroneous or noisy sequential inputs and to classify patterns. The application context of this study concerns the realisation of a lexical decoder for analytical multi-speakers continuous speech recognition. Lexical decoding is completed from lattices of phonemes which are obtained after an acoustic-phonetic decoding stage relying on a K Nearest Neighbors search technique. Test are done on sentences formed from a lexicon of 20 words. The results are obtained show the ability of the proposed connectionist model to take into account the sequentiality at the input level, to memorize the context and to treat noisy or erroneous inputs. (author) [fr
Liu, Enqiang; Liu, Zengliang; Shao, Fei; Zhang, Zhiyong
The contents access and sharing in multimedia social networks (MSNs) mainly rely on access control models and mechanisms. Simple adoptions of security policies in the traditional access control model cannot effectively establish a trust relationship among parties. This paper proposed a novel two-party trust architecture (TPTA) to apply in a generic MSN scenario. According to the architecture, security policies are adopted through game-theoretic analyses and decisions. Based on formalized utilities of security policies and security rules, the choice of security policies in content access is described as a game between the content provider and the content requester. By the game method for the combination of security policies utility and its influences on each party's benefits, the Nash equilibrium is achieved, that is, an optimal and stable combination of security policies, to establish and enhance trust among stakeholders. PMID:24977226
Mendes, G. A.; Axhausen, K. W.; Andrade, J. S.; Herrmann, H. J.
We study a vehicular traffic scenario on Swiss roads in an emergency situation, calculating how sequentially roads block due to excessive traffic load until global collapse (gridlock) occurs and in this way displays the fragilities of the system. We used a database from Bundesamt für Raumentwicklung which contains length and maximum allowed speed of all roads in Switzerland. The present work could be interesting for government agencies in planning and managing for emergency logistics for a country or a big city. The model used to generate the flux on the Swiss road network was proposed by Mendes et al. [Physica A 391, 362 (2012)]. It is based on the conservation of the number of vehicles and allows for an easy and fast way to follow the formation of traffic jams in large systems. We also analyze the difference between a nonlinear and a linear model and the distribution of fluxes on the Swiss road.
Tominaga, Taiki; Osada, Yoshihito; Gong, Jian Ping
Most hydrogels are mechanically too weak to be used as any load bearing devices. We have overcome this problem by synthesizing hydrogels with a double network (DN) structure. Despite the presence of 90% water in their composition, these tough gels exhibit a fracture stress of 170 kg/cm2, similar to that of cartilage. The relation between their mechanical strength and structure for a wide range of conditions should be analyzed to apprehend the origin of the toughness of the DN-gels. We recently reported some experi- mental results obtained by dynamic light scattering and small angle neutron scattering. Some new experimental results obtained by neutron scattering in both deformed and undeformed conditions provided for a new under- standing of the origin of toughness. We review the studies on the structure of DN-gels towards understanding of the toughness origin. Studies on DN-gels for biomedical applications are also described.
In this paper, we propose and derive a slotted-time model for analyzing the burst blocking probability in Optical Burst Switched (OBS) networks. We evaluated the immediate and delayed signaling reservation schemes. The proposed model compares the performance of both just-in-time (JIT) and just-enough-time (JET) signaling protocols associated with of void/non-void filling link scheduling schemes. It also considers none and limited range wavelength conversions scenarios. Our model is distinguished by being adaptable to different offset-time and burst length distributions. We observed that applying a limited range of wavelength conversion, burst blocking probability is reduced by several orders of magnitudes and yields a better burst delivery ratio compared with full wavelength conversion.
Liu, Enqiang; Liu, Zengliang; Shao, Fei; Zhang, Zhiyong
The contents access and sharing in multimedia social networks (MSNs) mainly rely on access control models and mechanisms. Simple adoptions of security policies in the traditional access control model cannot effectively establish a trust relationship among parties. This paper proposed a novel two-party trust architecture (TPTA) to apply in a generic MSN scenario. According to the architecture, security policies are adopted through game-theoretic analyses and decisions. Based on formalized utilities of security policies and security rules, the choice of security policies in content access is described as a game between the content provider and the content requester. By the game method for the combination of security policies utility and its influences on each party's benefits, the Nash equilibrium is achieved, that is, an optimal and stable combination of security policies, to establish and enhance trust among stakeholders.
Van Nes, R.
Multimodal transport, that is using two or more transport modes for a trip between which a transfer is necessary, seems an interesting approach to solving today's transportation problems with respect to the deteriorating accessibility of city centres, recurrent congestion, and environmental impact.
The presences of these flaws make a secured system a mirage for now, hence the need for intrusion detection system. In this paper, an ensemble approach – Bagging was used on five different machine learning techniques to improve accuracy of classifiers. Machine learning seeks for methods of extracting hidden pattern ...
Holland, David O; Krainak, Nicholas C; Saucerman, Jeffrey J
Model reduction is a central challenge to the development and analysis of multiscale physiology models. Advances in model reduction are needed not only for computational feasibility but also for obtaining conceptual insights from complex systems. Here, we introduce an intuitive graphical approach to model reduction based on phase plane analysis. Timescale separation is identified by the degree of hysteresis observed in phase-loops, which guides a "concentration-clamp" procedure for estimating explicit algebraic relationships between species equilibrating on fast timescales. The primary advantages of this approach over Jacobian-based timescale decomposition are that: 1) it incorporates nonlinear system dynamics, and 2) it can be easily visualized, even directly from experimental data. We tested this graphical model reduction approach using a 25-variable model of cardiac β(1)-adrenergic signaling, obtaining 6- and 4-variable reduced models that retain good predictive capabilities even in response to new perturbations. These 6 signaling species appear to be optimal "kinetic biomarkers" of the overall β(1)-adrenergic pathway. The 6-variable reduced model is well suited for integration into multiscale models of heart function, and more generally, this graphical model reduction approach is readily applicable to a variety of other complex biological systems.
David O Holland
Full Text Available Model reduction is a central challenge to the development and analysis of multiscale physiology models. Advances in model reduction are needed not only for computational feasibility but also for obtaining conceptual insights from complex systems. Here, we introduce an intuitive graphical approach to model reduction based on phase plane analysis. Timescale separation is identified by the degree of hysteresis observed in phase-loops, which guides a "concentration-clamp" procedure for estimating explicit algebraic relationships between species equilibrating on fast timescales. The primary advantages of this approach over Jacobian-based timescale decomposition are that: 1 it incorporates nonlinear system dynamics, and 2 it can be easily visualized, even directly from experimental data. We tested this graphical model reduction approach using a 25-variable model of cardiac β(1-adrenergic signaling, obtaining 6- and 4-variable reduced models that retain good predictive capabilities even in response to new perturbations. These 6 signaling species appear to be optimal "kinetic biomarkers" of the overall β(1-adrenergic pathway. The 6-variable reduced model is well suited for integration into multiscale models of heart function, and more generally, this graphical model reduction approach is readily applicable to a variety of other complex biological systems.
Omar M. Zakaria
Full Text Available Multiradio wireless mesh network is a promising architecture that improves the network capacity by exploiting multiple radio channels concurrently. Channel assignment and routing are underlying challenges in multiradio architectures since both determine the traffic distribution over links and channels. The interdependency between channel assignments and routing promotes toward the joint solutions for efficient configurations. This paper presents an in-depth review of the joint approaches of channel assignment and routing in multiradio wireless mesh networks. First, the key design issues, modeling, and approaches are identified and discussed. Second, existing algorithms for joint channel assignment and routing are presented and classified based on the channel assignment types. Furthermore, the set of reconfiguration algorithms to adapt the network traffic dynamics is also discussed. Finally, the paper presents some multiradio practical implementations and test-beds and points out the future research directions.
Full Text Available Predicting critical nodes of Opportunistic Sensor Network (OSN can help us not only to improve network performance but also to decrease the cost in network maintenance. However, existing ways of predicting critical nodes in static network are not suitable for OSN. In this paper, the conceptions of critical nodes, region contribution, and cut-vertex in multiregion OSN are defined. We propose an approach to predict critical node for OSN, which is based on multiple attribute decision making (MADM. It takes RC to present the dependence of regions on Ferry nodes. TOPSIS algorithm is employed to find out Ferry node with maximum comprehensive contribution, which is a critical node. The experimental results show that, in different scenarios, this approach can predict the critical nodes of OSN better.
Sharma, Ashwini Kumar; König, Rainer
Metabolism is the functional phenotype of a cell, at a given condition, resulting from an intricate interplay of various regulatory processes. The study of these dynamic metabolic processes and their capabilities help to identify the fundamental properties of living systems. Metabolic deregulation is an emerging hallmark of cancer cells. This deregulation results in rewiring of the metabolic circuitry conferring an exploitative metabolic advantage for the tumor cells which leads to a distinct benefit in survival and lays the basis for unbound progression. Metabolism can be considered as a thermodynamic open-system in which source substrates of high value are being processed through a well established interconnected biochemical conversion system, strictly obeying physiochemical principles, generating useful intermediates and finally resulting in the release of byproducts. Based on this basic principle of an input-output balance, various models have been developed to interrogate metabolism elucidating its underlying functional properties. However, only a few modeling approaches have proved computationally feasible in elucidating the metabolic nature of cancer at a systems level. Besides this, statistical approaches have been set up to identify biochemical pathways being more relevant for specific types of tumor cells. In this review, we are briefly introducing the basic statistical approaches followed by the major modeling concepts. We have put an emphasis on the methods and their applications that have been used to a greater extent in understanding the metabolic remodeling of cancer. Copyright © 2013 Elsevier Ltd. All rights reserved.
Hald, Bjørn Olav
The physiology of biological structures is inherently dynamic and emerges from the interaction and assembly of large collections of small entities. The extent of coupled entities complicates modeling and increases computational load. Here, microvascular networks are used to present a novel...... generative approach to connectivity based on the observation that biological organization is hierarchical and composed of a limited set of building blocks, i.e. a vascular network consists of blood vessels which in turn are composed by one or more cell types. Fast electrical communication is crucial...... to synchronize vessel tone across the vast distances within a network. We hypothesize that electrical conduction capacity is delimited by the size of vascular structures and connectivity of the network. Generation and simulation of series of dynamical models of electrical spread within vascular networks...
Full Text Available Social networks are formed by individuals, in which personalities, utility functions, and interaction rules are made as close to reality as possible. Taking the competitive product-related information as a case, we proposed a game-theoretic model for competitive information dissemination in social networks. The model is presented to explain how human factors impact competitive information dissemination which is described as the dynamic of a coordination game and players’ payoff is defined by a utility function. Then we design a computational system that integrates the agent, the evolutionary game, and the social network. The approach can help to visualize the evolution of % of competitive information adoption and diffusion, grasp the dynamic evolution features in information adoption game over time, and explore microlevel interactions among users in different network structure under various scenarios. We discuss several scenarios to analyze the influence of several factors on the dissemination of competitive information, ranging from personality of individuals to structure of networks.
Leung, Chi-Sing; Wan, Wai Yan; Feng, Ruibin
Many existing results on fault-tolerant algorithms focus on the single fault source situation, where a trained network is affected by one kind of weight failure. In fact, a trained network may be affected by multiple kinds of weight failure. This paper first studies how the open weight fault and the multiplicative weight noise degrade the performance of radial basis function (RBF) networks. Afterward, we define the objective function for training fault-tolerant RBF networks. Based on the objective function, we then develop two learning algorithms, one batch mode and one online mode. Besides, the convergent conditions of our online algorithm are investigated. Finally, we develop a formula to estimate the test set error of faulty networks trained from our approach. This formula helps us to optimize some tuning parameters, such as RBF width.
Balasubramaniam, P.; Kalpana, M.; Rakkiyappan, R.
Fuzzy cellular neural networks (FCNNs) are special kinds of cellular neural networks (CNNs). Each cell in an FCNN contains fuzzy operating abilities. The entire network is governed by cellular computing laws. The design of FCNNs is based on fuzzy local rules. In this paper, a linear matrix inequality (LMI) approach for synchronization control of FCNNs with mixed delays is investigated. Mixed delays include discrete time-varying delays and unbounded distributed delays. A dynamic control scheme is proposed to achieve the synchronization between a drive network and a response network. By constructing the Lyapunov—Krasovskii functional which contains a triple-integral term and the free-weighting matrices method an improved delay-dependent stability criterion is derived in terms of LMIs. The controller can be easily obtained by solving the derived LMIs. A numerical example and its simulations are presented to illustrate the effectiveness of the proposed method. (interdisciplinary physics and related areas of science and technology)
Evis Trandafili; Marenglen Biba
Social networks have an outstanding marketing value and developing data mining methods for viral marketing is a hot topic in the research community. However, most social networks remain impossible to be fully analyzed and understood due to prohibiting sizes and the incapability of traditional machine learning and data mining approaches to deal with the new dimension in the learning process related to the large-scale environment where the data are produced. On one hand, the birth and evolution...