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Sample records for social link prediction

  1. Link prediction in multiplex online social networks

    PubMed Central

    Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin

    2017-01-01

    Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%. PMID:28386441

  2. Link prediction in multiplex online social networks.

    PubMed

    Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin; Perc, Matjaž

    2017-02-01

    Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.

  3. Link prediction in multiplex online social networks

    NASA Astrophysics Data System (ADS)

    Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin; Perc, Matjaž

    2017-02-01

    Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.

  4. Link prediction in social network based on local information and attributes of nodes

    NASA Astrophysics Data System (ADS)

    Liang, Yingying; Huang, Lan; Wang, Zhe

    2017-08-01

    Link prediction is essential to both research areas and practical applications. In order to make full use of information of the network, we proposed a new method to predict links in the social network. Firstly, we extracted topological information and attributes of nodes in the social network. Secondly, we integrated them into feature vectors. Finally, we used XGB classifier to predict links using feature vectors. Through expanding information source, experiments on a co-authorship network suggest that our method can improve the accuracy of link prediction significantly.

  5. Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks

    PubMed Central

    Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S.

    2017-01-01

    Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a=(u,v) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages. PMID:28771201

  6. Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks.

    PubMed

    Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S

    2017-08-03

    Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a = ( u , v ) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages.

  7. Time Score: A New Feature for Link Prediction in Social Networks

    NASA Astrophysics Data System (ADS)

    Munasinghe, Lankeshwara; Ichise, Ryutaro

    Link prediction in social networks, such as friendship networks and coauthorship networks, has recently attracted a great deal of attention. There have been numerous attempts to address the problem of link prediction through diverse approaches. In the present paper, we focus on the temporal behavior of the link strength, particularly the relationship between the time stamps of interactions or links and the temporal behavior of link strength and how link strength affects future link evolution. Most previous studies have not sufficiently discussed either the impact of time stamps of the interactions or time stamps of the links on link evolution. The gap between the current time and the time stamps of the interactions or links is also important to link evolution. In the present paper, we introduce a new time-aware feature, referred to as time score, that captures the important aspects of time stamps of interactions and the temporality of the link strengths. We also analyze the effectiveness of time score with different parameter settings for different network data sets. The results of the analysis revealed that the time score was sensitive to different networks and different time measures. We applied time score to two social network data sets, namely, Facebook friendship network data set and a coauthorship network data set. The results revealed a significant improvement in predicting future links.

  8. Link prediction measures considering different neighbors’ effects and application in social networks

    NASA Astrophysics Data System (ADS)

    Luo, Peng; Wu, Chong; Li, Yongli

    Link prediction measures have been attracted particular attention in the field of mathematical physics. In this paper, we consider the different effects of neighbors in link prediction and focus on four different situations: only consider the individual’s own effects; consider the effects of individual, neighbors and neighbors’ neighbors; consider the effects of individual, neighbors, neighbors’ neighbors, neighbors’ neighbors’ neighbors and neighbors’ neighbors’ neighbors’ neighbors; consider the whole network participants’ effects. Then, according to the four situations, we present our link prediction models which also take the effects of social characteristics into consideration. An artificial network is adopted to illustrate the parameter estimation based on logistic regression. Furthermore, we compare our methods with the some other link prediction methods (LPMs) to examine the validity of our proposed model in online social networks. The results show the superior of our proposed link prediction methods compared with others. In the application part, our models are applied to study the social network evolution and used to recommend friends and cooperators in social networks.

  9. Link direction for link prediction

    NASA Astrophysics Data System (ADS)

    Shang, Ke-ke; Small, Michael; Yan, Wei-sheng

    2017-03-01

    Almost all previous studies on link prediction have focused on using the properties of the network to predict the existence of links between pairs of nodes. Unfortunately, previous methods rarely consider the role of link direction for link prediction. In fact, many real-world complex networks are directed and ignoring the link direction will mean overlooking important information. In this study, we propose a phase-dynamic algorithm of the directed network nodes to analyse the role of link directions and demonstrate that the bi-directional links and the one-directional links have different roles in link prediction and network structure formation. From this, we propose new directional prediction methods and use six real networks to test our algorithms. In real networks, we find that compared to a pair of nodes which are connected by a one-directional link, a pair of nodes which are connected by a bi-directional link always have higher probabilities to connect to the common neighbours with only bi-directional links (or conversely by one-directional links). We suggest that, in the real networks, the bi-directional links will generally be more informative for link prediction and network structure formation. In addition, we propose a new directional randomized algorithm to demonstrate that the direction of the links plays a significant role in link prediction and network structure formation.

  10. Link-prediction to tackle the boundary specification problem in social network surveys

    PubMed Central

    De Wilde, Philippe; Buarque de Lima-Neto, Fernando

    2017-01-01

    Diffusion processes in social networks often cause the emergence of global phenomena from individual behavior within a society. The study of those global phenomena and the simulation of those diffusion processes frequently require a good model of the global network. However, survey data and data from online sources are often restricted to single social groups or features, such as age groups, single schools, companies, or interest groups. Hence, a modeling approach is required that extrapolates the locally restricted data to a global network model. We tackle this Missing Data Problem using Link-Prediction techniques from social network research, network generation techniques from the area of Social Simulation, as well as a combination of both. We found that techniques employing less information may be more adequate to solve this problem, especially when data granularity is an issue. We validated the network models created with our techniques on a number of real-world networks, investigating degree distributions as well as the likelihood of links given the geographical distance between two nodes. PMID:28426826

  11. Link prediction on Twitter

    PubMed Central

    Martinčić-Ipšić, Sanda; Močibob, Edvin

    2017-01-01

    With over 300 million active users, Twitter is among the largest online news and social networking services in existence today. Open access to information on Twitter makes it a valuable source of data for research on social interactions, sentiment analysis, content diffusion, link prediction, and the dynamics behind human collective behaviour in general. Here we use Twitter data to construct co-occurrence language networks based on hashtags and based on all the words in tweets, and we use these networks to study link prediction by means of different methods and evaluation metrics. In addition to using five known methods, we propose two effective weighted similarity measures, and we compare the obtained outcomes in dependence on the selected semantic context of topics on Twitter. We find that hashtag networks yield to a large degree equal results as all-word networks, thus supporting the claim that hashtags alone robustly capture the semantic context of tweets, and as such are useful and suitable for studying the content and categorization. We also introduce ranking diagrams as an efficient tool for the comparison of the performance of different link prediction algorithms across multiple datasets. Our research indicates that successful link prediction algorithms work well in correctly foretelling highly probable links even if the information about a network structure is incomplete, and they do so even if the semantic context is rationalized to hashtags. PMID:28719651

  12. Link prediction on Twitter.

    PubMed

    Martinčić-Ipšić, Sanda; Močibob, Edvin; Perc, Matjaž

    2017-01-01

    With over 300 million active users, Twitter is among the largest online news and social networking services in existence today. Open access to information on Twitter makes it a valuable source of data for research on social interactions, sentiment analysis, content diffusion, link prediction, and the dynamics behind human collective behaviour in general. Here we use Twitter data to construct co-occurrence language networks based on hashtags and based on all the words in tweets, and we use these networks to study link prediction by means of different methods and evaluation metrics. In addition to using five known methods, we propose two effective weighted similarity measures, and we compare the obtained outcomes in dependence on the selected semantic context of topics on Twitter. We find that hashtag networks yield to a large degree equal results as all-word networks, thus supporting the claim that hashtags alone robustly capture the semantic context of tweets, and as such are useful and suitable for studying the content and categorization. We also introduce ranking diagrams as an efficient tool for the comparison of the performance of different link prediction algorithms across multiple datasets. Our research indicates that successful link prediction algorithms work well in correctly foretelling highly probable links even if the information about a network structure is incomplete, and they do so even if the semantic context is rationalized to hashtags.

  13. Link prediction via matrix completion

    NASA Astrophysics Data System (ADS)

    Pech, Ratha; Hao, Dong; Pan, Liming; Cheng, Hong; Zhou, Tao

    2017-02-01

    Inspired by the practical importance of social networks, economic networks, biological networks and so on, studies on large and complex networks have attracted a surge of attention in the recent years. Link prediction is a fundamental issue to understand the mechanisms by which new links are added to the networks. We introduce the method of robust principal component analysis (robust PCA) into link prediction, and estimate the missing entries of the adjacency matrix. On the one hand, our algorithm is based on the sparse and low-rank property of the matrix, while, on the other hand, it also performs very well when the network is dense. This is because a relatively dense real network is also sparse in comparison to the complete graph. According to extensive experiments on real networks from disparate fields, when the target network is connected and sufficiently dense, whether it is weighted or unweighted, our method is demonstrated to be very effective and with prediction accuracy being considerably improved compared to many state-of-the-art algorithms.

  14. Predicting missing links and identifying spurious links via likelihood analysis

    PubMed Central

    Pan, Liming; Zhou, Tao; Lü, Linyuan; Hu, Chin-Kun

    2016-01-01

    Real network data is often incomplete and noisy, where link prediction algorithms and spurious link identification algorithms can be applied. Thus far, it lacks a general method to transform network organizing mechanisms to link prediction algorithms. Here we use an algorithmic framework where a network’s probability is calculated according to a predefined structural Hamiltonian that takes into account the network organizing principles, and a non-observed link is scored by the conditional probability of adding the link to the observed network. Extensive numerical simulations show that the proposed algorithm has remarkably higher accuracy than the state-of-the-art methods in uncovering missing links and identifying spurious links in many complex biological and social networks. Such method also finds applications in exploring the underlying network evolutionary mechanisms. PMID:26961965

  15. Predicting missing links and identifying spurious links via likelihood analysis.

    PubMed

    Pan, Liming; Zhou, Tao; Lü, Linyuan; Hu, Chin-Kun

    2016-03-10

    Real network data is often incomplete and noisy, where link prediction algorithms and spurious link identification algorithms can be applied. Thus far, it lacks a general method to transform network organizing mechanisms to link prediction algorithms. Here we use an algorithmic framework where a network's probability is calculated according to a predefined structural Hamiltonian that takes into account the network organizing principles, and a non-observed link is scored by the conditional probability of adding the link to the observed network. Extensive numerical simulations show that the proposed algorithm has remarkably higher accuracy than the state-of-the-art methods in uncovering missing links and identifying spurious links in many complex biological and social networks. Such method also finds applications in exploring the underlying network evolutionary mechanisms.

  16. Selectivity predictions for troposcatter links

    NASA Astrophysics Data System (ADS)

    Collin, C.

    An empirical evaluation of the correlation bandwidth and the R.M.S. multipath spread according to the parameters of the tropo link is proposed. Attention is given to the troposcatter propagation channel, selectivity predictions for troposcatter links, a comparison between measured data and performance predictions, a prediction of the correlation bandwidth exceeded for a certain percentage of the time, and a prediction of R.M.S. multipath spread not exceeded for X% of the time. Performance predictions of the correlation bandwidth and R.M.S. multipath spread on troposcatter links are based on an analysis of existing data on 15 troposcatter links.

  17. A novel time series link prediction method: Learning automata approach

    NASA Astrophysics Data System (ADS)

    Moradabadi, Behnaz; Meybodi, Mohammad Reza

    2017-09-01

    Link prediction is a main social network challenge that uses the network structure to predict future links. The common link prediction approaches to predict hidden links use a static graph representation where a snapshot of the network is analyzed to find hidden or future links. For example, similarity metric based link predictions are a common traditional approach that calculates the similarity metric for each non-connected link and sort the links based on their similarity metrics and label the links with higher similarity scores as the future links. Because people activities in social networks are dynamic and uncertainty, and the structure of the networks changes over time, using deterministic graphs for modeling and analysis of the social network may not be appropriate. In the time-series link prediction problem, the time series link occurrences are used to predict the future links In this paper, we propose a new time series link prediction based on learning automata. In the proposed algorithm for each link that must be predicted there is one learning automaton and each learning automaton tries to predict the existence or non-existence of the corresponding link. To predict the link occurrence in time T, there is a chain consists of stages 1 through T - 1 and the learning automaton passes from these stages to learn the existence or non-existence of the corresponding link. Our preliminary link prediction experiments with co-authorship and email networks have provided satisfactory results when time series link occurrences are considered.

  18. Improving personalized link prediction by hybrid diffusion

    NASA Astrophysics Data System (ADS)

    Liu, Jin-Hu; Zhu, Yu-Xiao; Zhou, Tao

    2016-04-01

    Inspired by traditional link prediction and to solve the problem of recommending friends in social networks, we introduce the personalized link prediction in this paper, in which each individual will get equal number of diversiform predictions. While the performances of many classical algorithms are not satisfactory under this framework, thus new algorithms are in urgent need. Motivated by previous researches in other fields, we generalize heat conduction process to the framework of personalized link prediction and find that this method outperforms many classical similarity-based algorithms, especially in the performance of diversity. In addition, we demonstrate that adding one ground node that is supposed to connect all the nodes in the system will greatly benefit the performance of heat conduction. Finally, better hybrid algorithms composed of local random walk and heat conduction have been proposed. Numerical results show that the hybrid algorithms can outperform other algorithms simultaneously in all four adopted metrics: AUC, precision, recall and hamming distance. In a word, this work may shed some light on the in-depth understanding of the effect of physical processes in personalized link prediction.

  19. Specifying Links between Executive Functioning and Theory of Mind during Middle Childhood: Cognitive Flexibility Predicts Social Understanding

    ERIC Educational Resources Information Center

    Bock, Allison M.; Gallaway, Kristin C.; Hund, Alycia M.

    2015-01-01

    The purpose of this study was to specify the development of and links between executive functioning and theory of mind during middle childhood. One hundred four 7- to 12-year-old children completed a battery of age-appropriate tasks measuring working memory, inhibition, flexibility, theory of mind, and vocabulary. As expected, spatial working…

  20. Specifying Links between Executive Functioning and Theory of Mind during Middle Childhood: Cognitive Flexibility Predicts Social Understanding

    ERIC Educational Resources Information Center

    Bock, Allison M.; Gallaway, Kristin C.; Hund, Alycia M.

    2015-01-01

    The purpose of this study was to specify the development of and links between executive functioning and theory of mind during middle childhood. One hundred four 7- to 12-year-old children completed a battery of age-appropriate tasks measuring working memory, inhibition, flexibility, theory of mind, and vocabulary. As expected, spatial working…

  1. Exploiting Information Diffusion Feature for Link Prediction in Sina Weibo

    NASA Astrophysics Data System (ADS)

    Li, Dong; Zhang, Yongchao; Xu, Zhiming; Chu, Dianhui; Li, Sheng

    2016-01-01

    The rapid development of online social networks (e.g., Twitter and Facebook) has promoted research related to social networks in which link prediction is a key problem. Although numerous attempts have been made for link prediction based on network structure, node attribute and so on, few of the current studies have considered the impact of information diffusion on link creation and prediction. This paper mainly addresses Sina Weibo, which is the largest microblog platform with Chinese characteristics, and proposes the hypothesis that information diffusion influences link creation and verifies the hypothesis based on real data analysis. We also detect an important feature from the information diffusion process, which is used to promote link prediction performance. Finally, the experimental results on Sina Weibo dataset have demonstrated the effectiveness of our methods.

  2. Predicting link directions using local directed path

    NASA Astrophysics Data System (ADS)

    Wang, Xiaojie; Zhang, Xue; Zhao, Chengli; Xie, Zheng; Zhang, Shengjun; Yi, Dongyun

    2015-02-01

    Link prediction in directed network is attracting growing interest among many network scientists. Compared with predicting the existence of a link, determining its direction is more complicated. In this paper, we propose an efficient solution named Local Directed Path to predict link direction. By adding an extra ground node to the network, we solve the information loss problem in sparse network, which makes our method effective and robust. As a quasi-local method, our method can deal with large-scale networks in a reasonable time. Empirical analysis on real networks shows that our method can correctly predict link directions, which outperforms some local and global methods.

  3. Link prediction based on local community properties

    NASA Astrophysics Data System (ADS)

    Yang, Xu-Hua; Zhang, Hai-Feng; Ling, Fei; Cheng, Zhi; Weng, Guo-Qing; Huang, Yu-Jiao

    2016-09-01

    The link prediction algorithm is one of the key technologies to reveal the inherent rule of network evolution. This paper proposes a novel link prediction algorithm based on the properties of the local community, which is composed of the common neighbor nodes of any two nodes in the network and the links between these nodes. By referring to the node degree and the condition of assortativity or disassortativity in a network, we comprehensively consider the effect of the shortest path and edge clustering coefficient within the local community on node similarity. We numerically show the proposed method provide good link prediction results.

  4. Link prediction with node clustering coefficient

    NASA Astrophysics Data System (ADS)

    Wu, Zhihao; Lin, Youfang; Wang, Jing; Gregory, Steve

    2016-06-01

    Predicting missing links in incomplete complex networks efficiently and accurately is still a challenging problem. The recently proposed Cannistrai-Alanis-Ravai (CAR) index shows the power of local link/triangle information in improving link-prediction accuracy. Inspired by the idea of employing local link/triangle information, we propose a new similarity index with more local structure information. In our method, local link/triangle structure information can be conveyed by clustering coefficient of common-neighbors directly. The reason why clustering coefficient has good effectiveness in estimating the contribution of a common-neighbor is that it employs links existing between neighbors of a common-neighbor and these links have the same structural position with the candidate link to this common-neighbor. In our experiments, three estimators: precision, AUP and AUC are used to evaluate the accuracy of link prediction algorithms. Experimental results on ten tested networks drawn from various fields show that our new index is more effective in predicting missing links than CAR index, especially for networks with low correlation between number of common-neighbors and number of links between common-neighbors.

  5. Prediction of missing links and reconstruction of complex networks

    NASA Astrophysics Data System (ADS)

    Zhang, Cheng-Jun; Zeng, An

    2016-04-01

    Predicting missing links in complex networks is of great significance from both theoretical and practical point of view, which not only helps us understand the evolution of real systems but also relates to many applications in social, biological and online systems. In this paper, we study the features of different simple link prediction methods, revealing that they may lead to the distortion of networks’ structural and dynamical properties. Moreover, we find that high prediction accuracy is not definitely corresponding to a high performance in preserving the network properties when using link prediction methods to reconstruct networks. Our work highlights the importance of considering the feedback effect of the link prediction methods on network properties when designing the algorithms.

  6. Bounded link prediction in very large networks

    NASA Astrophysics Data System (ADS)

    Cui, Wei; Pu, Cunlai; Xu, Zhongqi; Cai, Shimin; Yang, Jian; Michaelson, Andrew

    2016-09-01

    Evaluating link prediction methods is a hard task in very large complex networks due to the prohibitive computational cost. However, if we consider the lower bound of node pairs' similarity scores, this task can be greatly optimized. In this paper, we study CN index in the bounded link prediction framework, which is applicable to enormous heterogeneous networks. Specifically, we propose a fast algorithm based on the parallel computing scheme to obtain all node pairs with CN values larger than the lower bound. Furthermore, we propose a general measurement, called self-predictability, to quantify the performance of similarity indices in link prediction, which can also indicate the link predictability of networks with respect to given similarity indices.

  7. An evidential link prediction method and link predictability based on Shannon entropy

    NASA Astrophysics Data System (ADS)

    Yin, Likang; Zheng, Haoyang; Bian, Tian; Deng, Yong

    2017-09-01

    Predicting missing links is of both theoretical value and practical interest in network science. In this paper, we empirically investigate a new link prediction method base on similarity and compare nine well-known local similarity measures on nine real networks. Most of the previous studies focus on the accuracy, however, it is crucial to consider the link predictability as an initial property of networks itself. Hence, this paper has proposed a new link prediction approach called evidential measure (EM) based on Dempster-Shafer theory. Moreover, this paper proposed a new method to measure link predictability via local information and Shannon entropy.

  8. Link prediction on evolving graphs using matrix and tensor factorizations.

    SciTech Connect

    Dunlavy, Daniel M.; Acar, Evrim; Kolda, Tamara Gibson

    2010-06-01

    The data in many disciplines such as social networks, web analysis, etc. is link-based, and the link structure can be exploited for many different data mining tasks. In this paper, we consider the problem of temporal link prediction: Given link data for time periods 1 through T, can we predict the links in time period T + 1? Specifically, we look at bipartite graphs changing over time and consider matrix- and tensor-based methods for predicting links. We present a weight-based method for collapsing multi-year data into a single matrix. We show how the well-known Katz method for link prediction can be extended to bipartite graphs and, moreover, approximated in a scalable way using a truncated singular value decomposition. Using a CANDECOMP/PARAFAC tensor decomposition of the data, we illustrate the usefulness of exploiting the natural three-dimensional structure of temporal link data. Through several numerical experiments, we demonstrate that both matrix- and tensor-based techniques are effective for temporal link prediction despite the inherent difficulty of the problem.

  9. A link prediction approach to cancer drug sensitivity prediction.

    PubMed

    Turki, Turki; Wei, Zhi

    2017-10-03

    Predicting the response to a drug for cancer disease patients based on genomic information is an important problem in modern clinical oncology. This problem occurs in part because many available drug sensitivity prediction algorithms do not consider better quality cancer cell lines and the adoption of new feature representations; both lead to the accurate prediction of drug responses. By predicting accurate drug responses to cancer, oncologists gain a more complete understanding of the effective treatments for each patient, which is a core goal in precision medicine. In this paper, we model cancer drug sensitivity as a link prediction, which is shown to be an effective technique. We evaluate our proposed link prediction algorithms and compare them with an existing drug sensitivity prediction approach based on clinical trial data. The experimental results based on the clinical trial data show the stability of our link prediction algorithms, which yield the highest area under the ROC curve (AUC) and are statistically significant. We propose a link prediction approach to obtain new feature representation. Compared with an existing approach, the results show that incorporating the new feature representation to the link prediction algorithms has significantly improved the performance.

  10. Toward link predictability of complex networks

    PubMed Central

    Lü, Linyuan; Pan, Liming; Zhou, Tao; Zhang, Yi-Cheng; Stanley, H. Eugene

    2015-01-01

    The organization of real networks usually embodies both regularities and irregularities, and, in principle, the former can be modeled. The extent to which the formation of a network can be explained coincides with our ability to predict missing links. To understand network organization, we should be able to estimate link predictability. We assume that the regularity of a network is reflected in the consistency of structural features before and after a random removal of a small set of links. Based on the perturbation of the adjacency matrix, we propose a universal structural consistency index that is free of prior knowledge of network organization. Extensive experiments on disparate real-world networks demonstrate that (i) structural consistency is a good estimation of link predictability and (ii) a derivative algorithm outperforms state-of-the-art link prediction methods in both accuracy and robustness. This analysis has further applications in evaluating link prediction algorithms and monitoring sudden changes in evolving network mechanisms. It will provide unique fundamental insights into the above-mentioned academic research fields, and will foster the development of advanced information filtering technologies of interest to information technology practitioners. PMID:25659742

  11. Toward link predictability of complex networks.

    PubMed

    Lü, Linyuan; Pan, Liming; Zhou, Tao; Zhang, Yi-Cheng; Stanley, H Eugene

    2015-02-24

    The organization of real networks usually embodies both regularities and irregularities, and, in principle, the former can be modeled. The extent to which the formation of a network can be explained coincides with our ability to predict missing links. To understand network organization, we should be able to estimate link predictability. We assume that the regularity of a network is reflected in the consistency of structural features before and after a random removal of a small set of links. Based on the perturbation of the adjacency matrix, we propose a universal structural consistency index that is free of prior knowledge of network organization. Extensive experiments on disparate real-world networks demonstrate that (i) structural consistency is a good estimation of link predictability and (ii) a derivative algorithm outperforms state-of-the-art link prediction methods in both accuracy and robustness. This analysis has further applications in evaluating link prediction algorithms and monitoring sudden changes in evolving network mechanisms. It will provide unique fundamental insights into the above-mentioned academic research fields, and will foster the development of advanced information filtering technologies of interest to information technology practitioners.

  12. Mixed-method Exploration of Social Network Links to Participation

    PubMed Central

    Kreider, Consuelo M.; Bendixen, Roxanna M.; Mann, William C.; Young, Mary Ellen; McCarty, Christopher

    2015-01-01

    The people who regularly interact with an adolescent form that youth's social network, which may impact participation. We investigated the relationship of social networks to participation using personal network analysis and individual interviews. The sample included 36 youth, age 11 – 16 years. Nineteen had diagnoses of learning disability, attention disorder, or high-functioning autism and 17 were typically developing. Network analysis yielded 10 network variables, of which 8 measured network composition and 2 measured network structure, with significant links to at least one measure of participation using the Children's Assessment of Participation and Enjoyment (CAPE). Interviews from youth in the clinical group yielded description of strategies used to negotiate social interactions, as well as processes and reasoning used to remain engaged within social networks. Findings contribute to understanding the ways social networks are linked to youth participation and suggest the potential of social network factors for predicting rehabilitation outcomes. PMID:26594737

  13. Influence of Reciprocal Links in Social Networks

    PubMed Central

    Zhu, Yu-Xiao; Zhang, Xiao-Guang; Sun, Gui-Quan; Tang, Ming; Zhou, Tao; Zhang, Zi-Ke

    2014-01-01

    How does reciprocal links affect the function of real social network? Does reciprocal link and non-reciprocal link play the same role? Previous researches haven't displayed a clear picture to us until now according to the best of our knowledge. Motivated by this, in this paper, we empirically study the influence of reciprocal links in two representative real datasets, Sina Weibo and Douban. Our results demonstrate that the reciprocal links play a more important role than non-reciprocal ones in information diffusion process. In particular, not only coverage but also the speed of the information diffusion can be significantly enhanced by considering the reciprocal effect. We give some possible explanations from the perspectives of network connectivity and efficiency. This work may shed some light on the in-depth understanding and application of the reciprocal effect in directed online social networks. PMID:25072242

  14. Influence of reciprocal links in social networks.

    PubMed

    Zhu, Yu-Xiao; Zhang, Xiao-Guang; Sun, Gui-Quan; Tang, Ming; Zhou, Tao; Zhang, Zi-Ke

    2014-01-01

    How does reciprocal links affect the function of real social network? Does reciprocal link and non-reciprocal link play the same role? Previous researches haven't displayed a clear picture to us until now according to the best of our knowledge. Motivated by this, in this paper, we empirically study the influence of reciprocal links in two representative real datasets, Sina Weibo and Douban. Our results demonstrate that the reciprocal links play a more important role than non-reciprocal ones in information diffusion process. In particular, not only coverage but also the speed of the information diffusion can be significantly enhanced by considering the reciprocal effect. We give some possible explanations from the perspectives of network connectivity and efficiency. This work may shed some light on the in-depth understanding and application of the reciprocal effect in directed online social networks.

  15. An efficient link prediction index for complex military organization

    NASA Astrophysics Data System (ADS)

    Fan, Changjun; Liu, Zhong; Lu, Xin; Xiu, Baoxin; Chen, Qing

    2017-03-01

    Quality of information is crucial for decision-makers to judge the battlefield situations and design the best operation plans, however, real intelligence data are often incomplete and noisy, where missing links prediction methods and spurious links identification algorithms can be applied, if modeling the complex military organization as the complex network where nodes represent functional units and edges denote communication links. Traditional link prediction methods usually work well on homogeneous networks, but few for the heterogeneous ones. And the military network is a typical heterogeneous network, where there are different types of nodes and edges. In this paper, we proposed a combined link prediction index considering both the nodes' types effects and nodes' structural similarities, and demonstrated that it is remarkably superior to all the 25 existing similarity-based methods both in predicting missing links and identifying spurious links in a real military network data; we also investigated the algorithms' robustness under noisy environment, and found the mistaken information is more misleading than incomplete information in military areas, which is different from that in recommendation systems, and our method maintained the best performance under the condition of small noise. Since the real military network intelligence must be carefully checked at first due to its significance, and link prediction methods are just adopted to purify the network with the left latent noise, the method proposed here is applicable in real situations. In the end, as the FINC-E model, here used to describe the complex military organizations, is also suitable to many other social organizations, such as criminal networks, business organizations, etc., thus our method has its prospects in these areas for many tasks, like detecting the underground relationships between terrorists, predicting the potential business markets for decision-makers, and so on.

  16. Effectiveness of Link Prediction for Face-to-Face Behavioral Networks

    PubMed Central

    Tsugawa, Sho; Ohsaki, Hiroyuki

    2013-01-01

    Research on link prediction for social networks has been actively pursued. In link prediction for a given social network obtained from time-windowed observation, new link formation in the network is predicted from the topology of the obtained network. In contrast, recent advances in sensing technology have made it possible to obtain face-to-face behavioral networks, which are social networks representing face-to-face interactions among people. However, the effectiveness of link prediction techniques for face-to-face behavioral networks has not yet been explored in depth. To clarify this point, here we investigate the accuracy of conventional link prediction techniques for networks obtained from the history of face-to-face interactions among participants at an academic conference. Our findings were (1) that conventional link prediction techniques predict new link formation with a precision of 0.30–0.45 and a recall of 0.10–0.20, (2) that prolonged observation of social networks often degrades the prediction accuracy, (3) that the proposed decaying weight method leads to higher prediction accuracy than can be achieved by observing all records of communication and simply using them unmodified, and (4) that the prediction accuracy for face-to-face behavioral networks is relatively high compared to that for non-social networks, but not as high as for other types of social networks. PMID:24339956

  17. Effectiveness of link prediction for face-to-face behavioral networks.

    PubMed

    Tsugawa, Sho; Ohsaki, Hiroyuki

    2013-01-01

    Research on link prediction for social networks has been actively pursued. In link prediction for a given social network obtained from time-windowed observation, new link formation in the network is predicted from the topology of the obtained network. In contrast, recent advances in sensing technology have made it possible to obtain face-to-face behavioral networks, which are social networks representing face-to-face interactions among people. However, the effectiveness of link prediction techniques for face-to-face behavioral networks has not yet been explored in depth. To clarify this point, here we investigate the accuracy of conventional link prediction techniques for networks obtained from the history of face-to-face interactions among participants at an academic conference. Our findings were (1) that conventional link prediction techniques predict new link formation with a precision of 0.30-0.45 and a recall of 0.10-0.20, (2) that prolonged observation of social networks often degrades the prediction accuracy, (3) that the proposed decaying weight method leads to higher prediction accuracy than can be achieved by observing all records of communication and simply using them unmodified, and (4) that the prediction accuracy for face-to-face behavioral networks is relatively high compared to that for non-social networks, but not as high as for other types of social networks.

  18. Predicting Social Functioning in Schizotypy

    PubMed Central

    McCleery, Amanda; Divilbiss, Marielle; St-Hilaire, Annie; Aakre, Jennifer M.; Seghers, James P.; Bell, Emily K.; Docherty, Nancy M.

    2015-01-01

    Theory of mind (ToM) is an aspect of social cognition that refers to the ability to make inferences about the thoughts, feelings, and intentions of other people. It is believed to be related to social functioning. Previous investigations of ToM in schizotypy have yielded mixed results. Using a correlational approach, the present study explored the relationship between schizotypal traits, ToM, neurocognition, depressed mood, and social functioning in a sample of 50 undergraduate students. Schizotypy was related to poor social functioning. Contrary to predictions, schizotypal traits were not associated with impaired ToM. In fact, schizotypal traits were associated with enhanced performance on a ToM task that involved detection of ironic statements. However, strong relationships emerged among schizotypy, depressed mood, and social functioning, highlighting the need to also examine depression when assessing the relations between elevated schizotypy and poor social functioning. PMID:22297312

  19. Drug Response Prediction as a Link Prediction Problem

    PubMed Central

    Stanfield, Zachary; Coşkun, Mustafa; Koyutürk, Mehmet

    2017-01-01

    Drug response prediction is a well-studied problem in which the molecular profile of a given sample is used to predict the effect of a given drug on that sample. Effective solutions to this problem hold the key for precision medicine. In cancer research, genomic data from cell lines are often utilized as features to develop machine learning models predictive of drug response. Molecular networks provide a functional context for the integration of genomic features, thereby resulting in robust and reproducible predictive models. However, inclusion of network data increases dimensionality and poses additional challenges for common machine learning tasks. To overcome these challenges, we here formulate drug response prediction as a link prediction problem. For this purpose, we represent drug response data for a large cohort of cell lines as a heterogeneous network. Using this network, we compute “network profiles” for cell lines and drugs. We then use the associations between these profiles to predict links between drugs and cell lines. Through leave-one-out cross validation and cross-classification on independent datasets, we show that this approach leads to accurate and reproducible classification of sensitive and resistant cell line-drug pairs, with 85% accuracy. We also examine the biological relevance of the network profiles. PMID:28067293

  20. Link prediction based on temporal similarity metrics using continuous action set learning automata

    NASA Astrophysics Data System (ADS)

    Moradabadi, Behnaz; Meybodi, Mohammad Reza

    2016-10-01

    Link prediction is a social network research area that tries to predict future links using network structure. The main approaches in this area are based on predicting future links using network structure at a specific period, without considering the links behavior through different periods. For example, a common traditional approach in link prediction calculates a chosen similarity metric for each non-connected link and outputs the links with higher similarity scores as the prediction result. In this paper, we propose a new link prediction method based on temporal similarity metrics and Continuous Action set Learning Automata (CALA). The proposed method takes advantage of using different similarity metrics as well as different time periods. In the proposed algorithm, we try to model the link prediction problem as a noisy optimization problem and use a team of CALAs to solve the noisy optimization problem. CALA is a reinforcement based optimization tool which tries to learn the optimal behavior from the environment feedbacks. To determine the importance of different periods and similarity metrics on the prediction result, we define a coefficient for each of different periods and similarity metrics and use a CALA for each coefficient. Each CALA tries to learn the true value of the corresponding coefficient. Final link prediction is obtained from a combination of different similarity metrics in different times based on the obtained coefficients. The link prediction results reported here show satisfactory of the proposed method for some social network data sets.

  1. Brain structure links loneliness to social perception.

    PubMed

    Kanai, Ryota; Bahrami, Bahador; Duchaine, Brad; Janik, Agnieszka; Banissy, Michael J; Rees, Geraint

    2012-10-23

    Loneliness is the distressing feeling associated with the perceived absence of satisfying social relationships. Loneliness is increasingly prevalent in modern societies and has detrimental effects on health and happiness. Although situational threats to social relationships can transiently induce the emotion of loneliness, susceptibility to loneliness is a stable trait that varies across individuals [6-8] and is to some extent heritable. However, little is known about the neural processes associated with loneliness (but see [12-14]). Here, we hypothesized that individual differences in loneliness might be reflected in the structure of the brain regions associated with social processes. To test this hypothesis, we used voxel-based morphometry and showed that lonely individuals have less gray matter in the left posterior superior temporal sulcus (pSTS)--an area implicated in basic social perception. As this finding predicted, we further confirmed that loneliness was associated with difficulty in processing social cues. Although other sociopsychological factors such as social network size, anxiety, and empathy independently contributed to loneliness, only basic social perception skills mediated the association between the pSTS volume and loneliness. Taken together, our results suggest that basic social perceptual abilities play an important role in shaping an individual's loneliness. Copyright © 2012 Elsevier Ltd. All rights reserved.

  2. Genetic variants linked to education predict longevity

    PubMed Central

    Marioni, Riccardo E.; Ritchie, Stuart J.; Joshi, Peter K.; Hagenaars, Saskia P.; Fischer, Krista; Adams, Mark J.; Hill, W. David; Davies, Gail; Nagy, Reka; Amador, Carmen; Läll, Kristi; Metspalu, Andres; Liewald, David C.; Wilson, James F.; Hayward, Caroline; Esko, Tõnu; Porteous, David J.; Gale, Catharine R.; Deary, Ian J.

    2016-01-01

    Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members’ polygenic profile score for education to predict their parents’ longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total ndeaths = 79,702) and ∼2.4% lower risk for fathers (total ndeaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity. PMID:27799538

  3. Genetic variants linked to education predict longevity.

    PubMed

    Marioni, Riccardo E; Ritchie, Stuart J; Joshi, Peter K; Hagenaars, Saskia P; Okbay, Aysu; Fischer, Krista; Adams, Mark J; Hill, W David; Davies, Gail; Nagy, Reka; Amador, Carmen; Läll, Kristi; Metspalu, Andres; Liewald, David C; Campbell, Archie; Wilson, James F; Hayward, Caroline; Esko, Tõnu; Porteous, David J; Gale, Catharine R; Deary, Ian J

    2016-11-22

    Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members' polygenic profile score for education to predict their parents' longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total ndeaths = 79,702) and ∼2.4% lower risk for fathers (total ndeaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity.

  4. Mixed-Method Exploration of Social Network Links to Participation.

    PubMed

    Kreider, Consuelo M; Bendixen, Roxanna M; Mann, William C; Young, Mary Ellen; McCarty, Christopher

    2015-07-01

    The people who regularly interact with an adolescent form that youth's social network (SN), which may impact participation. We investigated the relationship of SNs to participation using personal network analysis and individual interviews. The sample included 36 youth, aged 11 to 16 years. Nineteen had diagnoses of learning disability, attention disorder, or high-functioning autism, and 17 were typically developing. Network analysis yielded 10 network variables, of which 8 measured network composition and 2 measured network structure, with significant links to at least I measure of participation using the Children's Assessment of Participation and Enjoyment (CAPE). Interviews from youth in the clinical group yielded description of strategies used to negotiate social interactions, as well as processes and reasoning used to remain engaged within SNs. Findings contribute to understanding the ways SNs are linked to youth participation and suggest the potential of SN factors for predicting rehabilitation outcomes.

  5. Predicting missing links via structural similarity

    NASA Astrophysics Data System (ADS)

    Lyu, Guo-Dong; Fan, Chang-Jun; Yu, Lian-Fei; Xiu, Bao-Xin; Zhang, Wei-Ming

    2015-04-01

    Predicting missing links in networks plays a significant role in modern science. On the basis of structural similarity, our paper proposes a new node-similarity-based measure called biased resource allocation (BRA), which is motivated by the resource allocation (RA) measure. Comparisons between BRA and nine well-known node-similarity-based measures on five real networks indicate that BRA performs no worse than RA, which was the best node-similarity-based index in previous researches. Afterwards, based on localPath (LP) and Katz measure, we propose another two improved measures, named Im-LocalPath and Im-Katz respectively. Numerical results show that the prediction accuracy of both Im-LP and Im-Katz measure improve compared with the original LP and Katz measure. Finally, a new path-similarity-based measure and its improved measure, called LYU and Im-LYU measure, are proposed and especially, Im-LYU measure is shown to perform more remarkably than other mentioned measures.

  6. Co-rumination buffers the link between social anxiety and depressive symptoms in early adolescence.

    PubMed

    Van Zalk, Nejra; Tillfors, Maria

    2017-01-01

    We examined whether co-rumination with online friends buffered the link between social anxiety and depressive symptoms over time in a community sample. In a sample of 526 participants (358 girls; Mage  = 14.05) followed at three time points, we conducted a latent cross-lagged model with social anxiety, depressive symptoms, and co-rumination, controlling for friendship stability and friendship quality, and adding a latent interaction between social anxiety and co-rumination predicting depressive symptoms. Social anxiety predicted depressive symptoms, but no direct links between social anxiety and co-rumination emerged. Instead, co-rumination buffered the link between social anxiety and depressive symptoms for adolescents with higher but not lower levels of social anxiety. These findings indicate that co-rumination exerted a positive influence on interpersonal relationships by diminishing the influence from social anxiety on depressive symptoms over time.

  7. Gender Differences in Predicting Loneliness from Social Network Variables.

    ERIC Educational Resources Information Center

    Stokes, Joseph; Levin, Ira

    Recent research suggesting a link between loneliness and social networks and a difference between males and females in both the quantity and quality of relationships support the view that loneliness can be predicted by gender from social network variables. In one study, two samples were used to explore gender differences. Sample 1, 97 males and 82…

  8. Psychosocial mechanisms linking the social environment to mental health in African Americans

    USDA-ARS?s Scientific Manuscript database

    Resource-poor social environments predict poor health, but the mechanisms and processes linking the social environment to psychological health and well-being remain unclear. This study explored psychosocial mediators of the association between the social environment and mental health in African Amer...

  9. Utility-Based Link Recommendation in Social Networks

    ERIC Educational Resources Information Center

    Li, Zhepeng

    2013-01-01

    Link recommendation, which suggests links to connect currently unlinked users, is a key functionality offered by major online social networking platforms. Salient examples of link recommendation include "people you may know"' on Facebook and "who to follow" on Twitter. A social networking platform has two types of stakeholder:…

  10. Utility-Based Link Recommendation in Social Networks

    ERIC Educational Resources Information Center

    Li, Zhepeng

    2013-01-01

    Link recommendation, which suggests links to connect currently unlinked users, is a key functionality offered by major online social networking platforms. Salient examples of link recommendation include "people you may know"' on Facebook and "who to follow" on Twitter. A social networking platform has two types of stakeholder:…

  11. Predicting top-L missing links with node and link clustering information in large-scale networks

    NASA Astrophysics Data System (ADS)

    Wu, Zhihao; Lin, Youfang; Wan, Huaiyu; Jamil, Waleed

    2016-08-01

    Networks are mathematical structures that are universally used to describe a large variety of complex systems, such as social, biological, and technological systems. The prediction of missing links in incomplete complex networks aims to estimate the likelihood of the existence of a link between a pair of nodes. Various topological features of networks have been applied to develop link prediction methods. However, the exploration of features of links is still limited. In this paper, we demonstrate the power of node and link clustering information in predicting top -L missing links. In the existing literature, link prediction algorithms have only been tested on small-scale and middle-scale networks. The network scale factor has not attracted the same level of attention. In our experiments, we test the proposed method on three groups of networks. For small-scale networks, since the structures are not very complex, advanced methods cannot perform significantly better than classical methods. For middle-scale networks, the proposed index, combining both node and link clustering information, starts to demonstrate its advantages. In many networks, combining both node and link clustering information can improve the link prediction accuracy a great deal. Large-scale networks with more than 100 000 links have rarely been tested previously. Our experiments on three large-scale networks show that local clustering information based methods outperform other methods, and link clustering information can further improve the accuracy of node clustering information based methods, in particular for networks with a broad distribution of the link clustering coefficient.

  12. Community detection, link prediction, and layer interdependence in multilayer networks.

    PubMed

    De Bacco, Caterina; Power, Eleanor A; Larremore, Daniel B; Moore, Cristopher

    2017-04-01

    Complex systems are often characterized by distinct types of interactions between the same entities. These can be described as a multilayer network where each layer represents one type of interaction. These layers may be interdependent in complicated ways, revealing different kinds of structure in the network. In this work we present a generative model, and an efficient expectation-maximization algorithm, which allows us to perform inference tasks such as community detection and link prediction in this setting. Our model assumes overlapping communities that are common between the layers, while allowing these communities to affect each layer in a different way, including arbitrary mixtures of assortative, disassortative, or directed structure. It also gives us a mathematically principled way to define the interdependence between layers, by measuring how much information about one layer helps us predict links in another layer. In particular, this allows us to bundle layers together to compress redundant information and identify small groups of layers which suffice to predict the remaining layers accurately. We illustrate these findings by analyzing synthetic data and two real multilayer networks, one representing social support relationships among villagers in South India and the other representing shared genetic substring material between genes of the malaria parasite.

  13. Community detection, link prediction, and layer interdependence in multilayer networks

    NASA Astrophysics Data System (ADS)

    De Bacco, Caterina; Power, Eleanor A.; Larremore, Daniel B.; Moore, Cristopher

    2017-04-01

    Complex systems are often characterized by distinct types of interactions between the same entities. These can be described as a multilayer network where each layer represents one type of interaction. These layers may be interdependent in complicated ways, revealing different kinds of structure in the network. In this work we present a generative model, and an efficient expectation-maximization algorithm, which allows us to perform inference tasks such as community detection and link prediction in this setting. Our model assumes overlapping communities that are common between the layers, while allowing these communities to affect each layer in a different way, including arbitrary mixtures of assortative, disassortative, or directed structure. It also gives us a mathematically principled way to define the interdependence between layers, by measuring how much information about one layer helps us predict links in another layer. In particular, this allows us to bundle layers together to compress redundant information and identify small groups of layers which suffice to predict the remaining layers accurately. We illustrate these findings by analyzing synthetic data and two real multilayer networks, one representing social support relationships among villagers in South India and the other representing shared genetic substring material between genes of the malaria parasite.

  14. Lateral orbitofrontal cortex links social impressions to political choices.

    PubMed

    Xia, Chenjie; Stolle, Dietlind; Gidengil, Elisabeth; Fellows, Lesley K

    2015-06-03

    Recent studies of political behavior suggest that voting decisions can be influenced substantially by "first-impression" social attributions based on physical appearance. Separate lines of research have implicated the orbitofrontal cortex (OFC) in the judgment of social traits on the one hand and economic decision-making on the other, making this region a plausible candidate for linking social attributions to voting decisions. Here, we asked whether OFC lesions in humans disrupted the ability to judge traits of political candidates or affected how these judgments influenced voting decisions. Seven patients with lateral OFC damage, 18 patients with frontal damage sparing the lateral OFC, and 53 matched healthy participants took part in a simulated election paradigm, in which they voted for real-life (but unknown) candidates based only on photographs of their faces. Consistent with previous work, attributions of "competence" and "attractiveness" based on candidate appearance predicted voting behavior in the healthy control group. Frontal damage did not affect substantially the ability to make competence or attractiveness judgments, but patients with damage to the lateral OFC differed from other groups in how they applied this information when voting. Only attractiveness ratings had any predictive power for voting choices after lateral OFC damage, whereas other frontal patients and healthy controls relied on information about both competence and attractiveness in making their choice. An intact lateral OFC may not be necessary for judgment of social traits based on physical appearance, but it seems to be crucial in applying this information in political decision-making.

  15. The missing link: leadership, identity, and the social brain.

    PubMed

    van Vugt, Mark

    2012-05-01

    How the cohesion of a social network is being maintained in spite of having different layers of social interaction is an important question. I argue that the evolution of both (political) hierarchy and social identity play a crucial role in scaling up and bonding social networks. Together they are missing links in the social brain hypothesis, and further research is needed to understand the functions of leadership and social identity.

  16. Measuring the robustness of link prediction algorithms under noisy environment

    PubMed Central

    Zhang, Peng; Wang, Xiang; Wang, Futian; Zeng, An; Xiao, Jinghua

    2016-01-01

    Link prediction in complex networks is to estimate the likelihood of two nodes to interact with each other in the future. As this problem has applications in a large number of real systems, many link prediction methods have been proposed. However, the validation of these methods is so far mainly conducted in the assumed noise-free networks. Therefore, we still miss a clear understanding of how the prediction results would be affected if the observed network data is no longer accurate. In this paper, we comprehensively study the robustness of the existing link prediction algorithms in the real networks where some links are missing, fake or swapped with other links. We find that missing links are more destructive than fake and swapped links for prediction accuracy. An index is proposed to quantify the robustness of the link prediction methods. Among the twenty-two studied link prediction methods, we find that though some methods have low prediction accuracy, they tend to perform reliably in the “noisy” environment. PMID:26733156

  17. Predicting links based on knowledge dissemination in complex network

    NASA Astrophysics Data System (ADS)

    Zhou, Wen; Jia, Yifan

    2017-04-01

    Link prediction is the task of mining the missing links in networks or predicting the next vertex pair to be connected by a link. A lot of link prediction methods were inspired by evolutionary processes of networks. In this paper, a new mechanism for the formation of complex networks called knowledge dissemination (KD) is proposed with the assumption of knowledge disseminating through the paths of a network. Accordingly, a new link prediction method-knowledge dissemination based link prediction (KDLP)-is proposed to test KD. KDLP characterizes vertex similarity based on knowledge quantity (KQ) which measures the importance of a vertex through H-index. Extensive numerical simulations on six real-world networks demonstrate that KDLP is a strong link prediction method which performs at a higher prediction accuracy than four well-known similarity measures including common neighbors, local path index, average commute time and matrix forest index. Furthermore, based on the common conclusion that an excellent link prediction method reveals a good evolving mechanism, the experiment results suggest that KD is a considerable network evolving mechanism for the formation of complex networks.

  18. Social goals, aggression, peer preference, and popularity: longitudinal links during middle school.

    PubMed

    Ojanen, Tiina; Findley-Van Nostrand, Danielle

    2014-08-01

    Social goals are associated with behaviors and adjustment among peers. However, it remains unclear whether goals predict adolescent social development. We examined prospective associations among goals, physical and relational aggression, social preference, and popularity during middle school (N = 384 participants, ages 12-14 years). Agentic (status, power) goals predicted increased relational aggression and communal (closeness) goals predicted decreased physical aggression. Popularity predicted increases and preference predicted decreases in both forms of aggression. Goals moderated longitudinal links between aggression and popularity: Aggression predicted increases in popularity and vice versa for youth with higher agentic goals, and popularity predicted increases in physical aggression for youth with higher agentic and lower communal goals. Implications for research on social goals, aggression, and popularity are discussed.

  19. Meta-path based heterogeneous combat network link prediction

    NASA Astrophysics Data System (ADS)

    Li, Jichao; Ge, Bingfeng; Yang, Kewei; Chen, Yingwu; Tan, Yuejin

    2017-09-01

    The combat system-of-systems in high-tech informative warfare, composed of many interconnected combat systems of different types, can be regarded as a type of complex heterogeneous network. Link prediction for heterogeneous combat networks (HCNs) is of significant military value, as it facilitates reconfiguring combat networks to represent the complex real-world network topology as appropriate with observed information. This paper proposes a novel integrated methodology framework called HCNMP (HCN link prediction based on meta-path) to predict multiple types of links simultaneously for an HCN. More specifically, the concept of HCN meta-paths is introduced, through which the HCNMP can accumulate information by extracting different features of HCN links for all the six defined types. Next, an HCN link prediction model, based on meta-path features, is built to predict all types of links of the HCN simultaneously. Then, the solution algorithm for the HCN link prediction model is proposed, in which the prediction results are obtained by iteratively updating with the newly predicted results until the results in the HCN converge or reach a certain maximum iteration number. Finally, numerical experiments on the dataset of a real HCN are conducted to demonstrate the feasibility and effectiveness of the proposed HCNMP, in comparison with 30 baseline methods. The results show that the performance of the HCNMP is superior to those of the baseline methods.

  20. The role of prediction in social neuroscience

    PubMed Central

    Brown, Elliot C.; Brüne, Martin

    2012-01-01

    Research has shown that the brain is constantly making predictions about future events. Theories of prediction in perception, action and learning suggest that the brain serves to reduce the discrepancies between expectation and actual experience, i.e., by reducing the prediction error. Forward models of action and perception propose the generation of a predictive internal representation of the expected sensory outcome, which is matched to the actual sensory feedback. Shared neural representations have been found when experiencing one's own and observing other's actions, rewards, errors, and emotions such as fear and pain. These general principles of the “predictive brain” are well established and have already begun to be applied to social aspects of cognition. The application and relevance of these predictive principles to social cognition are discussed in this article. Evidence is presented to argue that simple non-social cognitive processes can be extended to explain complex cognitive processes required for social interaction, with common neural activity seen for both social and non-social cognitions. A number of studies are included which demonstrate that bottom-up sensory input and top-down expectancies can be modulated by social information. The concept of competing social forward models and a partially distinct category of social prediction errors are introduced. The evolutionary implications of a “social predictive brain” are also mentioned, along with the implications on psychopathology. The review presents a number of testable hypotheses and novel comparisons that aim to stimulate further discussion and integration between currently disparate fields of research, with regard to computational models, behavioral and neurophysiological data. This promotes a relatively new platform for inquiry in social neuroscience with implications in social learning, theory of mind, empathy, the evolution of the social brain, and potential strategies for treating

  1. The role of prediction in social neuroscience.

    PubMed

    Brown, Elliot C; Brüne, Martin

    2012-01-01

    Research has shown that the brain is constantly making predictions about future events. Theories of prediction in perception, action and learning suggest that the brain serves to reduce the discrepancies between expectation and actual experience, i.e., by reducing the prediction error. Forward models of action and perception propose the generation of a predictive internal representation of the expected sensory outcome, which is matched to the actual sensory feedback. Shared neural representations have been found when experiencing one's own and observing other's actions, rewards, errors, and emotions such as fear and pain. These general principles of the "predictive brain" are well established and have already begun to be applied to social aspects of cognition. The application and relevance of these predictive principles to social cognition are discussed in this article. Evidence is presented to argue that simple non-social cognitive processes can be extended to explain complex cognitive processes required for social interaction, with common neural activity seen for both social and non-social cognitions. A number of studies are included which demonstrate that bottom-up sensory input and top-down expectancies can be modulated by social information. The concept of competing social forward models and a partially distinct category of social prediction errors are introduced. The evolutionary implications of a "social predictive brain" are also mentioned, along with the implications on psychopathology. The review presents a number of testable hypotheses and novel comparisons that aim to stimulate further discussion and integration between currently disparate fields of research, with regard to computational models, behavioral and neurophysiological data. This promotes a relatively new platform for inquiry in social neuroscience with implications in social learning, theory of mind, empathy, the evolution of the social brain, and potential strategies for treating social

  2. Predicting the Trends of Social Events on Chinese Social Media.

    PubMed

    Zhou, Yang; Zhang, Lei; Liu, Xiaoqian; Zhang, Zhen; Bai, Shuotian; Zhu, Tingshao

    2017-09-01

    Growing interest in social events on social media came along with the rapid development of the Internet. Social events that occur in the "real" world can spread on social media (e.g., Sina Weibo) rapidly, which may trigger severe consequences and thus require the government's timely attention and responses. This article proposes to predict the trends of social events on Sina Weibo, which is currently the most popular social media in China. Based on the theories of social psychology and communication sciences, we extract an unprecedented amount of comprehensive and effective features that relate to the trends of social events on Chinese social media, and we construct the trends of prediction models by using three classical regression algorithms. We found that lasso regression performed better with the precision 0.78 and the recall 0.88. The results of our experiments demonstrated the effectiveness of our proposed approach.

  3. Preschoolers Use Social Allegiances to Predict Behavior

    ERIC Educational Resources Information Center

    Chalik, Lisa; Rhodes, Marjorie

    2014-01-01

    Developing mechanisms for predicting human action is a critical task of early conceptual development. Three studies examined whether 4-year-old children (N = 149) use social allegiances to predict behavior, by testing whether they expect the experiences of social partners to influence individual action. After being exposed to a conflict between…

  4. Predicted Social Drinking and the Need for Social Approval.

    ERIC Educational Resources Information Center

    Mitchell, Jennifer L.; McAndrew, Francis T.

    Research has indicated that alcohol consumption is strongly affected by situational factors, especially social factors. To explore the relevance to drinking of the need for social approval in social situations, 36 male college students were asked to predict how much they would drink in several situations varying in how certain they were of their…

  5. Revealing how network structure affects accuracy of link prediction

    NASA Astrophysics Data System (ADS)

    Yang, Jin-Xuan; Zhang, Xiao-Dong

    2017-08-01

    Link prediction plays an important role in network reconstruction and network evolution. The network structure affects the accuracy of link prediction, which is an interesting problem. In this paper we use common neighbors and the Gini coefficient to reveal the relation between them, which can provide a good reference for the choice of a suitable link prediction algorithm according to the network structure. Moreover, the statistical analysis reveals correlation between the common neighbors index, Gini coefficient index and other indices to describe the network structure, such as Laplacian eigenvalues, clustering coefficient, degree heterogeneity, and assortativity of network. Furthermore, a new method to predict missing links is proposed. The experimental results show that the proposed algorithm yields better prediction accuracy and robustness to the network structure than existing currently used methods for a variety of real-world networks.

  6. Link Prediction in Weighted Networks: A Weighted Mutual Information Model

    PubMed Central

    Zhu, Boyao; Xia, Yongxiang

    2016-01-01

    The link-prediction problem is an open issue in data mining and knowledge discovery, which attracts researchers from disparate scientific communities. A wealth of methods have been proposed to deal with this problem. Among these approaches, most are applied in unweighted networks, with only a few taking the weights of links into consideration. In this paper, we present a weighted model for undirected and weighted networks based on the mutual information of local network structures, where link weights are applied to further enhance the distinguishable extent of candidate links. Empirical experiments are conducted on four weighted networks, and results show that the proposed method can provide more accurate predictions than not only traditional unweighted indices but also typical weighted indices. Furthermore, some in-depth discussions on the effects of weak ties in link prediction as well as the potential to predict link weights are also given. This work may shed light on the design of algorithms for link prediction in weighted networks. PMID:26849659

  7. Link prediction in the network of global virtual water trade

    NASA Astrophysics Data System (ADS)

    Tuninetti, Marta; Tamea, Stefania; Laio, Francesco; Ridolfi, Luca

    2016-04-01

    Through the international food-trade, water resources are 'virtually' transferred from the country of production to the country of consumption. The international food-trade, thus, implies a network of virtual water flows from exporting to importing countries (i.e., nodes). Given the dynamical behavior of the network, where food-trade relations (i.e., links) are created and dismissed every year, link prediction becomes a challenge. In this study, we propose a novel methodology for link prediction in the virtual water network. The model aims at identifying the main factors (among 17 different variables) driving the creation of a food-trade relation between any two countries, along the period between 1986 and 2011. Furthermore, the model can be exploited to investigate the network configuration in the future, under different possible (climatic and demographic) scenarios. The model grounds the existence of a link between any two nodes on the link weight (i.e., the virtual water flow): a link exists when the nodes exchange a minimum (fixed) volume of virtual water. Starting from a set of potential links between any two nodes, we fit the associated virtual water flows (both the real and the null ones) by means of multivariate linear regressions. Then, links with estimated flows higher than a minimum value (i.e., threshold) are considered active-links, while the others are non-active ones. The discrimination between active and non-active links through the threshold introduces an error (called link-prediction error) because some real links are lost (i.e., missed links) and some non-existing links (i.e., spurious links) are inevitably introduced in the network. The major drivers are those significantly minimizing the link-prediction error. Once the structure of the unweighted virtual water network is known, we apply, again, linear regressions to assess the major factors driving the fluxes traded along (modelled) active-links. Results indicate that, on the one hand

  8. Predicting brain network changes in Alzheimer's disease with link prediction algorithms.

    PubMed

    Sulaimany, Sadegh; Khansari, Mohammad; Zarrineh, Peyman; Daianu, Madelaine; Jahanshad, Neda; Thompson, Paul M; Masoudi-Nejad, Ali

    2017-03-28

    Link prediction is a promising research area for modeling various types of networks and has mainly focused on predicting missing links. Link prediction methods may be valuable for describing brain connectivity, as it changes in Alzheimer's disease (AD) and its precursor, mild cognitive impairment (MCI). Here, we analyzed 3-tesla whole-brain diffusion-weighted images from 202 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) - 50 healthy controls, 72 with earlyMCI (eMCI) and 38 with lateMCI (lMCI) and 42 AD patients. We introduce a novel approach for Mixed Link Prediction (MLP) to test and define the percent of predictability of each heightened stage of dementia from its previous, less impaired stage, in the simplest case. Using well-known link prediction algorithms as the core of MLP, we propose a new approach that predicts stages of cognitive impairment by simultaneously adding and removing links in the brain networks of elderly individuals. We found that the optimal algorithm, called "Adamic and Adar", had the best fit and most accurately predicted the stages of AD from their previous stage. When compared to the other link prediction algorithms, that mainly only predict the added links, our proposed approach can more inclusively simulate the brain changes during disease by both adding and removing links of the network. Our results are also in line with computational neuroimaging and clinical findings and can be improved for better results.

  9. Linking scientific disciplines: Hydrology and social sciences

    NASA Astrophysics Data System (ADS)

    Seidl, R.; Barthel, R.

    2017-07-01

    The integration of interdisciplinary scientific and societal knowledge plays an increasing role in sustainability science and more generally, in global change research. In the field of water resources, interdisciplinarity has long been recognized as crucial. Recently, new concepts and ideas about how to approach water resources management more holistically have been discussed. The emergence of concepts such as socio-hydrology indicates the growing relevance of connections between social and hydrological disciplines. In this paper, we determine how well social sciences are integrated with hydrological research by using two approaches. First, we conducted a questionnaire survey with a sample of hydrology researchers and professionals (N = 353) to explore current opinions and developments related to interdisciplinary collaboration between hydrologists and social scientists. Second, we analyzed the disciplinary composition of author teams and the reference lists of articles pertaining to the socio-hydrology concept. We conclude that interdisciplinarity in water resources research is on a promising track but may need to mature further in terms of its aims and methods of integration. We find that current literature pays little attention to the following questions: What kind of interdisciplinarity do different scholars want? What are social scientists' preferred roles and knowledge from a hydrology perspective?

  10. IDPredictor: predict database links in biomedical database.

    PubMed

    Mehlhorn, Hendrik; Lange, Matthias; Scholz, Uwe; Schreiber, Falk

    2012-06-26

    Knowledge found in biomedical databases, in particular in Web information systems, is a major bioinformatics resource. In general, this biological knowledge is worldwide represented in a network of databases. These data is spread among thousands of databases, which overlap in content, but differ substantially with respect to content detail, interface, formats and data structure. To support a functional annotation of lab data, such as protein sequences, metabolites or DNA sequences as well as a semi-automated data exploration in information retrieval environments, an integrated view to databases is essential. Search engines have the potential of assisting in data retrieval from these structured sources, but fall short of providing a comprehensive knowledge except out of the interlinked databases. A prerequisite of supporting the concept of an integrated data view is to acquire insights into cross-references among database entities. This issue is being hampered by the fact, that only a fraction of all possible cross-references are explicitely tagged in the particular biomedical informations systems. In this work, we investigate to what extend an automated construction of an integrated data network is possible. We propose a method that predicts and extracts cross-references from multiple life science databases and possible referenced data targets. We study the retrieval quality of our method and report on first, promising results. The method is implemented as the tool IDPredictor, which is published under the DOI 10.5447/IPK/2012/4 and is freely available using the URL: http://dx.doi.org/10.5447/IPK/2012/4.

  11. Prediction of Links and Weights in Networks by Reliable Routes

    PubMed Central

    Zhao, Jing; Miao, Lili; Yang, Jian; Fang, Haiyang; Zhang, Qian-Ming; Nie, Min; Holme, Petter; Zhou, Tao

    2015-01-01

    Link prediction aims to uncover missing links or predict the emergence of future relationships from the current network structure. Plenty of algorithms have been developed for link prediction in unweighted networks, but only a few have been extended to weighted networks. In this paper, we present what we call a “reliable-route method” to extend unweighted local similarity indices to weighted ones. Using these indices, we can predict both the existence of links and their weights. Experiments on various real-world networks suggest that our reliable-route weighted resource-allocation index performs noticeably better than others with respect to weight prediction. For existence prediction it is either the highest or very close to the highest. Further analysis shows a strong positive correlation between the clustering coefficient and prediction accuracy. Finally, we apply our method to the prediction of missing protein-protein interactions and their confidence scores from known PPI networks. Once again, our reliable-route method shows the highest accuracy. PMID:26198206

  12. Predicting Social Trust with Binary Logistic Regression

    ERIC Educational Resources Information Center

    Adwere-Boamah, Joseph; Hufstedler, Shirley

    2015-01-01

    This study used binary logistic regression to predict social trust with five demographic variables from a national sample of adult individuals who participated in The General Social Survey (GSS) in 2012. The five predictor variables were respondents' highest degree earned, race, sex, general happiness and the importance of personally assisting…

  13. Dysregulated Fear Predicts Social Wariness and Social Anxiety Symptoms during Kindergarten

    PubMed Central

    Buss, Kristin A.; Davis, Elizabeth L.; Kiel, Elizabeth J.; Brooker, Rebecca J.; Beekman, Charles; Early, Martha C.

    2013-01-01

    Fearful temperament is associated with risk for the development of social anxiety disorder in childhood; however, not all fearful children become anxious. Identifying maladaptive trajectories is thus important for clarifying which fearful children are at risk. In an unselected sample of 111 two-year-olds (55% male, 95% Caucasian), Buss (2011) identified a pattern of fearful behavior, dysregulated fear, characterized by high fear in low threat situations. This pattern of behavior predicted parent- and teacher-reported withdrawn/anxious behaviors in preschool and at kindergarten entry. The current study extended original findings and examined whether dysregulated fear predicted observed social wariness with adults and peers, and social anxiety symptoms at age 6. We also examined prosocial adjustment during kindergarten as a moderator of the link between dysregulated fear and social wariness. Consistent with predictions, children with greater dysregulated fear at age 2 were more socially wary of adults and unfamiliar peers in the laboratory, were reported as having more social anxiety symptoms, and were nearly four times more likely to manifest social anxiety symptoms than other children with elevated wariness in kindergarten. Results demonstrated stability in the dysregulated fear profile and increased risk for social anxiety symptom development. Dysregulated fear predicted more social wariness with unfamiliar peers only when children became less prosocial during kindergarten. Findings are discussed in relation to the utility of the dysregulated fear construct for specifying maladaptive trajectories of risk for anxiety disorder development. PMID:23458273

  14. Dysregulated fear predicts social wariness and social anxiety symptoms during kindergarten.

    PubMed

    Buss, Kristin A; Davis, Elizabeth L; Kiel, Elizabeth J; Brooker, Rebecca J; Beekman, Charles; Early, Martha C

    2013-01-01

    Fearful temperament is associated with risk for the development of social anxiety disorder in childhood; however, not all fearful children become anxious. Identifying maladaptive trajectories is thus important for clarifying which fearful children are at risk. In an unselected sample of 111 two-year-olds (55% male, 95% Caucasian), Buss ( 2011 ) identified a pattern of fearful behavior, dysregulated fear, characterized by high fear in low threat situations. This pattern of behavior predicted parent- and teacher-reported withdrawn/anxious behaviors in preschool and at kindergarten entry. The current study extended original findings and examined whether dysregulated fear predicted observed social wariness with adults and peers, and social anxiety symptoms at age 6. We also examined prosocial adjustment during kindergarten as a moderator of the link between dysregulated fear and social wariness. Consistent with predictions, children with greater dysregulated fear at age 2 were more socially wary of adults and unfamiliar peers in the laboratory, were reported as having more social anxiety symptoms, and were nearly 4 times more likely to manifest social anxiety symptoms than other children with elevated wariness in kindergarten. Results demonstrated stability in the dysregulated fear profile and increased risk for social anxiety symptom development. Dysregulated fear predicted more social wariness with unfamiliar peers only when children became less prosocial during kindergarten. Findings are discussed in relation to the utility of the dysregulated fear construct for specifying maladaptive trajectories of risk for anxiety disorder development.

  15. Cold-start link prediction in multi-relational networks

    NASA Astrophysics Data System (ADS)

    Wu, Shun-yao; Zhang, Qi; Wu, Mei

    2017-10-01

    During the last decade, interaction data have accumulated exponentially in many fields and provide a new opportunity for cold start link prediction. It seems necessarily to take full advantages of diversified information. However, correlation between different interactions has to be pre-tested. Therefore, this paper abstracts complex systems as multi-relational networks, and employs latent space network model to extract low-dimensional factors of sub-networks and adopts likelihood ratio test to examine correlation between factors. Then, regression between target sub-networks and correlated auxiliary sub-networks could be established for cold start link prediction. Experiments on 8 bioinformatic data sets validate the effectiveness and potential of our strategy for network correlation analysis and cold-start link prediction.

  16. Entropy-based link prediction in weighted networks

    NASA Astrophysics Data System (ADS)

    Xu, Zhongqi; Pu, Cunlai; Ramiz Sharafat, Rajput; Li, Lunbo; Yang, Jian

    2017-01-01

    Information entropy has been proved to be an effective tool to quantify the structural importance of complex networks. In the previous work (Xu et al, 2016 \\cite{xu2016}), we measure the contribution of a path in link prediction with information entropy. In this paper, we further quantify the contribution of a path with both path entropy and path weight, and propose a weighted prediction index based on the contributions of paths, namely Weighted Path Entropy (WPE), to improve the prediction accuracy in weighted networks. Empirical experiments on six weighted real-world networks show that WPE achieves higher prediction accuracy than three typical weighted indices.

  17. Link prediction based on local weighted paths for complex networks

    NASA Astrophysics Data System (ADS)

    Yao, Yabing; Zhang, Ruisheng; Yang, Fan; Yuan, Yongna; Hu, Rongjing; Zhao, Zhili

    As a significant problem in complex networks, link prediction aims to find the missing and future links between two unconnected nodes by estimating the existence likelihood of potential links. It plays an important role in understanding the evolution mechanism of networks and has broad applications in practice. In order to improve prediction performance, a variety of structural similarity-based methods that rely on different topological features have been put forward. As one topological feature, the path information between node pairs is utilized to calculate the node similarity. However, many path-dependent methods neglect the different contributions of paths for a pair of nodes. In this paper, a local weighted path (LWP) index is proposed to differentiate the contributions between paths. The LWP index considers the effect of the link degrees of intermediate links and the connectivity influence of intermediate nodes on paths to quantify the path weight in the prediction procedure. The experimental results on 12 real-world networks show that the LWP index outperforms other seven prediction baselines.

  18. Toward Predicting Social Support Needs in Online Health Social Networks.

    PubMed

    Choi, Min-Je; Kim, Sung-Hee; Lee, Sukwon; Kwon, Bum Chul; Yi, Ji Soo; Choo, Jaegul; Huh, Jina

    2017-08-02

    While online health social networks (OHSNs) serve as an effective platform for patients to fulfill their various social support needs, predicting the needs of users and providing tailored information remains a challenge. The objective of this study was to discriminate important features for identifying users' social support needs based on knowledge gathered from survey data. This study also provides guidelines for a technical framework, which can be used to predict users' social support needs based on raw data collected from OHSNs. We initially conducted a Web-based survey with 184 OHSN users. From this survey data, we extracted 34 features based on 5 categories: (1) demographics, (2) reading behavior, (3) posting behavior, (4) perceived roles in OHSNs, and (5) values sought in OHSNs. Features from the first 4 categories were used as variables for binary classification. For the prediction outcomes, we used features from the last category: the needs for emotional support, experience-based information, unconventional information, and medical facts. We compared 5 binary classifier algorithms: gradient boosting tree, random forest, decision tree, support vector machines, and logistic regression. We then calculated the scores of the area under the receiver operating characteristic (ROC) curve (AUC) to understand the comparative effectiveness of the used features. The best performance was AUC scores of 0.89 for predicting users seeking emotional support, 0.86 for experience-based information, 0.80 for unconventional information, and 0.83 for medical facts. With the gradient boosting tree as our best performing model, we analyzed the strength of individual features in predicting one's social support need. Among other discoveries, we found that users seeking emotional support tend to post more in OHSNs compared with others. We developed an initial framework for automatically predicting social support needs in OHSNs using survey data. Future work should involve nonsurvey

  19. Similarity indices based on link weight assignment for link prediction of unweighted complex networks

    NASA Astrophysics Data System (ADS)

    Liu, Shuxin; Ji, Xinsheng; Liu, Caixia; Bai, Yi

    2017-01-01

    Many link prediction methods have been proposed for predicting the likelihood that a link exists between two nodes in complex networks. Among these methods, similarity indices are receiving close attention. Most similarity-based methods assume that the contribution of links with different topological structures is the same in the similarity calculations. This paper proposes a local weighted method, which weights the strength of connection between each pair of nodes. Based on the local weighted method, six local weighted similarity indices extended from unweighted similarity indices (including Common Neighbor (CN), Adamic-Adar (AA), Resource Allocation (RA), Salton, Jaccard and Local Path (LP) index) are proposed. Empirical study has shown that the local weighted method can significantly improve the prediction accuracy of these unweighted similarity indices and that in sparse and weakly clustered networks, the indices perform even better.

  20. Psychosocial Mechanisms Linking the Social Environment to Mental Health in African Americans.

    PubMed

    Mama, Scherezade K; Li, Yisheng; Basen-Engquist, Karen; Lee, Rebecca E; Thompson, Deborah; Wetter, David W; Nguyen, Nga T; Reitzel, Lorraine R; McNeill, Lorna H

    2016-01-01

    Resource-poor social environments predict poor health, but the mechanisms and processes linking the social environment to psychological health and well-being remain unclear. This study explored psychosocial mediators of the association between the social environment and mental health in African American adults. African American men and women (n = 1467) completed questionnaires on the social environment, psychosocial factors (stress, depressive symptoms, and racial discrimination), and mental health. Multiple-mediator models were used to assess direct and indirect effects of the social environment on mental health. Low social status in the community (p < .001) and U.S. (p < .001) and low social support (p < .001) were associated with poor mental health. Psychosocial factors significantly jointly mediated the relationship between the social environment and mental health in multiple-mediator models. Low social status and social support were associated with greater perceived stress, depressive symptoms, and perceived racial discrimination, which were associated with poor mental health. Results suggest the relationship between the social environment and mental health is mediated by psychosocial factors and revealed potential mechanisms through which social status and social support influence the mental health of African American men and women. Findings from this study provide insight into the differential effects of stress, depression and discrimination on mental health. Ecological approaches that aim to improve the social environment and psychosocial mediators may enhance health-related quality of life and reduce health disparities in African Americans.

  1. Psychosocial Mechanisms Linking the Social Environment to Mental Health in African Americans

    PubMed Central

    Basen-Engquist, Karen; Lee, Rebecca E.; Thompson, Deborah; Wetter, David W.; Reitzel, Lorraine R.

    2016-01-01

    Resource-poor social environments predict poor health, but the mechanisms and processes linking the social environment to psychological health and well-being remain unclear. This study explored psychosocial mediators of the association between the social environment and mental health in African American adults. African American men and women (n = 1467) completed questionnaires on the social environment, psychosocial factors (stress, depressive symptoms, and racial discrimination), and mental health. Multiple-mediator models were used to assess direct and indirect effects of the social environment on mental health. Low social status in the community (p < .001) and U.S. (p < .001) and low social support (p < .001) were associated with poor mental health. Psychosocial factors significantly jointly mediated the relationship between the social environment and mental health in multiple-mediator models. Low social status and social support were associated with greater perceived stress, depressive symptoms, and perceived racial discrimination, which were associated with poor mental health. Results suggest the relationship between the social environment and mental health is mediated by psychosocial factors and revealed potential mechanisms through which social status and social support influence the mental health of African American men and women. Findings from this study provide insight into the differential effects of stress, depression and discrimination on mental health. Ecological approaches that aim to improve the social environment and psychosocial mediators may enhance health-related quality of life and reduce health disparities in African Americans. PMID:27119366

  2. Prospective Links between Social Anxiety and Adolescent Peer Relations

    ERIC Educational Resources Information Center

    Tillfors, Maria; Persson, Stefan; Willen, Maria; Burk, William J.

    2012-01-01

    This study examines bi-directional links between social anxiety and multiple aspects of peer relations (peer acceptance, peer victimization, and relationship quality) in a longitudinal sample of 1528 adolescents assessed twice with one year between (754 females and 774 males; M = 14.7 years of age). Lower levels of peer acceptance predicted…

  3. Introduction: Links between Social Interaction and Executive Function

    ERIC Educational Resources Information Center

    Lewis, Charlie; Carpendale, Jeremy I. M.

    2009-01-01

    The term executive function is used increasingly within developmental psychology and is often taken to refer to unfolding brain processes. We trace the origins of research on executive function to show that the link with social interaction has a long history. We suggest that a recent frenzy of research exploring methods for studying individual…

  4. Prospective Links between Social Anxiety and Adolescent Peer Relations

    ERIC Educational Resources Information Center

    Tillfors, Maria; Persson, Stefan; Willen, Maria; Burk, William J.

    2012-01-01

    This study examines bi-directional links between social anxiety and multiple aspects of peer relations (peer acceptance, peer victimization, and relationship quality) in a longitudinal sample of 1528 adolescents assessed twice with one year between (754 females and 774 males; M = 14.7 years of age). Lower levels of peer acceptance predicted…

  5. Introduction: Links between Social Interaction and Executive Function

    ERIC Educational Resources Information Center

    Lewis, Charlie; Carpendale, Jeremy I. M.

    2009-01-01

    The term executive function is used increasingly within developmental psychology and is often taken to refer to unfolding brain processes. We trace the origins of research on executive function to show that the link with social interaction has a long history. We suggest that a recent frenzy of research exploring methods for studying individual…

  6. Do bonding, bridging, and linking social capital affect preventable hospitalizations?

    PubMed

    Derose, Kathryn Pitkin

    2008-10-01

    To examine the relationship between social capital and preventable hospitalizations (PHs). Administrative and secondary data for Florida (hospital discharge, U.S. Census, voting, nonprofits, faith-based congregations, uninsured, safety net and primary care providers, and hospital beds). Cross-sectional, zip code-level multivariate analyses to examine the associations among social capital, primary care resources, and adult PHs and pediatric asthma hospitalizations. Data were merged at the zip code-level (n=837). Few of the social capital measures were independently associated with PHs: longer mean commute times (reduced bonding social capital) were related to higher adult rates; more racial and ethnic diversity (increased bridging social capital) was related to lower nonelderly adult rates but higher pediatric rates; more faith-based organizations (linking social capital) were associated with higher nonelderly adult rates. Having a safety net clinic within 20 miles was associated with lower adult rates, while general internists were associated with higher rates. More pediatricians per capita were related to higher pediatric rates. The importance of social capital for health care access is unclear. Some bonding and bridging ties were related to PHs, but differentially across age groups; more work is needed to operationalize linking ties. © Health Research and Educational Trust.

  7. Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks

    NASA Astrophysics Data System (ADS)

    Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo

    2015-11-01

    Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Unveiling physical principles, building theories and suggesting physical models to predict bipartite links such as product-consumer connections in recommendation systems or drug-target interactions in molecular networks can provide priceless information to improve e-commerce or to accelerate pharmaceutical research. The prediction of nonobserved connections starting from those already present in the topology of a network is known as the link-prediction problem. It represents an important subject both in many-body interaction theory in physics and in new algorithms for applied tools in computer science. The rationale is that the existing connectivity structure of a network can suggest where new connections can appear with higher likelihood in an evolving network, or where nonobserved connections are missing in a partially known network. Surprisingly, current complex network theory presents a theoretical bottle-neck: a general framework for local-based link prediction directly in the bipartite domain is missing. Here, we overcome this theoretical obstacle and present a formal definition of common neighbour index and local-community-paradigm (LCP) for bipartite networks. As a consequence, we are able to introduce the first node-neighbourhood-based and LCP-based models for topological link prediction that utilize the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks because they exploit local physical driving-forces that participate in the formation and organization of many real-world bipartite networks. Furthermore, we present a local-based formalism that allows to intuitively

  8. Social neuroscience and health: neurophysiological mechanisms linking social ties with physical health.

    PubMed

    Eisenberger, Naomi I; Cole, Steve W

    2012-04-15

    Although considerable research has shown the importance of social connection for physical health, little is known about the higher-level neurocognitive processes that link experiences of social connection or disconnection with health-relevant physiological responses. Here we review the key physiological systems implicated in the link between social ties and health and the neural mechanisms that may translate social experiences into downstream health-relevant physiological responses. Specifically, we suggest that threats to social connection may tap into the same neural and physiological 'alarm system' that responds to other critical survival threats, such as the threat or experience of physical harm. Similarly, experiences of social connection may tap into basic reward-related mechanisms that have inhibitory relationships with threat-related responding. Indeed, the neurocognitive correlates of social disconnection and connection may be important mediators for understanding the relationships between social ties and health.

  9. Social Trust Prediction Using Heterogeneous Networks.

    PubMed

    Huang, Jin; Nie, Feiping; Huang, Heng; Tu, Yi-Cheng; Lei, Yu

    2013-11-01

    Along with increasing popularity of social websites, online users rely more on the trustworthiness information to make decisions, extract and filter information, and tag and build connections with other users. However, such social network data often suffer from severe data sparsity and are not able to provide users with enough information. Therefore, trust prediction has emerged as an important topic in social network research. Traditional approaches are primarily based on exploring trust graph topology itself. However, research in sociology and our life experience suggest that people who are in the same social circle often exhibit similar behaviors and tastes. To take advantage of the ancillary information for trust prediction, the challenge then becomes what to transfer and how to transfer. In this article, we address this problem by aggregating heterogeneous social networks and propose a novel joint social networks mining (JSNM) method. Our new joint learning model explores the user-group-level similarity between correlated graphs and simultaneously learns the individual graph structure; therefore, the shared structures and patterns from multiple social networks can be utilized to enhance the prediction tasks. As a result, we not only improve the trust prediction in the target graph but also facilitate other information retrieval tasks in the auxiliary graphs. To optimize the proposed objective function, we use the alternative technique to break down the objective function into several manageable subproblems. We further introduce the auxiliary function to solve the optimization problems with rigorously proved convergence. The extensive experiments have been conducted on both synthetic and real- world data. All empirical results demonstrate the effectiveness of our method.

  10. Social Trust Prediction Using Heterogeneous Networks

    PubMed Central

    HUANG, JIN; NIE, FEIPING; HUANG, HENG; TU, YI-CHENG; LEI, YU

    2014-01-01

    Along with increasing popularity of social websites, online users rely more on the trustworthiness information to make decisions, extract and filter information, and tag and build connections with other users. However, such social network data often suffer from severe data sparsity and are not able to provide users with enough information. Therefore, trust prediction has emerged as an important topic in social network research. Traditional approaches are primarily based on exploring trust graph topology itself. However, research in sociology and our life experience suggest that people who are in the same social circle often exhibit similar behaviors and tastes. To take advantage of the ancillary information for trust prediction, the challenge then becomes what to transfer and how to transfer. In this article, we address this problem by aggregating heterogeneous social networks and propose a novel joint social networks mining (JSNM) method. Our new joint learning model explores the user-group-level similarity between correlated graphs and simultaneously learns the individual graph structure; therefore, the shared structures and patterns from multiple social networks can be utilized to enhance the prediction tasks. As a result, we not only improve the trust prediction in the target graph but also facilitate other information retrieval tasks in the auxiliary graphs. To optimize the proposed objective function, we use the alternative technique to break down the objective function into several manageable subproblems. We further introduce the auxiliary function to solve the optimization problems with rigorously proved convergence. The extensive experiments have been conducted on both synthetic and real- world data. All empirical results demonstrate the effectiveness of our method. PMID:24729776

  11. Processes Linking Social Class and Racial Socialization in African American Dual-Earner Families

    PubMed Central

    Crouter, Ann C.; Baril, Megan E.; Davis, Kelly; McHale, Susan M.

    2011-01-01

    We examined the links between social class, occupational self-direction, self-efficacy, and racial socialization in a sample of 128 two-parent African American couples raising adolescents. A series of multivariate, multilevel models revealed that mothers’ SES was connected to self-efficacy via its association with occupational self-direction; in turn, self-efficacy partially explained the association between occupational self-direction and racial socialization. The link between maternal self-efficacy and racial socialization depended on whether or not children had experienced discrimination. For fathers, a strong link between SES and occupational self-direction emerged, but significant associations were not found between occupational self-direction and self-efficacy, or self-efficacy and racial socialization. The discussion focuses on mother-father differences and the role of child effects in racial socialization. PMID:21709729

  12. Processes Linking Social Class and Racial Socialization in African American Dual-Earner Families.

    PubMed

    Crouter, Ann C; Baril, Megan E; Davis, Kelly; McHale, Susan M

    2008-12-01

    We examined the links between social class, occupational self-direction, self-efficacy, and racial socialization in a sample of 128 two-parent African American couples raising adolescents. A series of multivariate, multilevel models revealed that mothers' SES was connected to self-efficacy via its association with occupational self-direction; in turn, self-efficacy partially explained the association between occupational self-direction and racial socialization. The link between maternal self-efficacy and racial socialization depended on whether or not children had experienced discrimination. For fathers, a strong link between SES and occupational self-direction emerged, but significant associations were not found between occupational self-direction and self-efficacy, or self-efficacy and racial socialization. The discussion focuses on mother-father differences and the role of child effects in racial socialization.

  13. Mutual information model for link prediction in heterogeneous complex networks

    PubMed Central

    Shakibian, Hadi; Moghadam Charkari, Nasrollah

    2017-01-01

    Recently, a number of meta-path based similarity indices like PathSim, HeteSim, and random walk have been proposed for link prediction in heterogeneous complex networks. However, these indices suffer from two major drawbacks. Firstly, they are primarily dependent on the connectivity degrees of node pairs without considering the further information provided by the given meta-path. Secondly, most of them are required to use a single and usually symmetric meta-path in advance. Hence, employing a set of different meta-paths is not straightforward. To tackle with these problems, we propose a mutual information model for link prediction in heterogeneous complex networks. The proposed model, called as Meta-path based Mutual Information Index (MMI), introduces meta-path based link entropy to estimate the link likelihood and could be carried on a set of available meta-paths. This estimation measures the amount of information through the paths instead of measuring the amount of connectivity between the node pairs. The experimental results on a Bibliography network show that the MMI obtains high prediction accuracy compared with other popular similarity indices. PMID:28344326

  14. Predicting the Social Commitments of College Students.

    ERIC Educational Resources Information Center

    Lavelle, Ellen; O'Ryan, Leslie W.

    2001-01-01

    Investigates the nature of social beliefs and commitments during the college years in relation to developmental orientations as measured by the Dakota Inventory of Student Orientations. Results support Creative-Reflective scale scores as predictive of commitment to the more humanitarian issues such as race and women's rights, whereas…

  15. Predicting Bullying: Maladjustment, Social Skills and Popularity

    ERIC Educational Resources Information Center

    Postigo, Silvia; Gonzalez, Remedios; Mateu, Carmen; Montoya, Inmaculada

    2012-01-01

    In order to prevent bullying, research has characterised the adolescents involved in terms of their social skills, maladjustment and popularity. However, there is a lack of knowledge concerning the relationships between these variables and how these relationships predict bullying involvement. Moreover, the literature has focused on pure bullies…

  16. Predicting Bullying: Maladjustment, Social Skills and Popularity

    ERIC Educational Resources Information Center

    Postigo, Silvia; Gonzalez, Remedios; Mateu, Carmen; Montoya, Inmaculada

    2012-01-01

    In order to prevent bullying, research has characterised the adolescents involved in terms of their social skills, maladjustment and popularity. However, there is a lack of knowledge concerning the relationships between these variables and how these relationships predict bullying involvement. Moreover, the literature has focused on pure bullies…

  17. Toward Predicting Popularity of Social Marketing Messages

    NASA Astrophysics Data System (ADS)

    Yu, Bei; Chen, Miao; Kwok, Linchi

    Popularity of social marketing messages indicates the effectiveness of the corresponding marketing strategies. This research aims to discover the characteristics of social marketing messages that contribute to different level of popularity. Using messages posted by a sample of restaurants on Facebook as a case study, we measured the message popularity by the number of "likes" voted by fans, and examined the relationship between the message popularity and two properties of the messages: (1) content, and (2) media type. Combining a number of text mining and statistics methods, we have discovered some interesting patterns correlated to "more popular" and "less popular" social marketing messages. This work lays foundation for building computational models to predict the popularity of social marketing messages in the future.

  18. Mitochondrial function in the brain links anxiety with social subordination.

    PubMed

    Hollis, Fiona; van der Kooij, Michael A; Zanoletti, Olivia; Lozano, Laura; Cantó, Carles; Sandi, Carmen

    2015-12-15

    Dominance hierarchies are integral aspects of social groups, yet whether personality traits may predispose individuals to a particular rank remains unclear. Here we show that trait anxiety directly influences social dominance in male outbred rats and identify an important mediating role for mitochondrial function in the nucleus accumbens. High-anxious animals that are prone to become subordinate during a social encounter with a low-anxious rat exhibit reduced mitochondrial complex I and II proteins and respiratory capacity as well as decreased ATP and increased ROS production in the nucleus accumbens. A causal link for these findings is indicated by pharmacological approaches. In a dyadic contest between anxiety-matched animals, microinfusion of specific mitochondrial complex I or II inhibitors into the nucleus accumbens reduced social rank, mimicking the low probability to become dominant observed in high-anxious animals. Conversely, intraaccumbal infusion of nicotinamide, an amide form of vitamin B3 known to enhance brain energy metabolism, prevented the development of a subordinate status in high-anxious individuals. We conclude that mitochondrial function in the nucleus accumbens is crucial for social hierarchy establishment and is critically involved in the low social competitiveness associated with high anxiety. Our findings highlight a key role for brain energy metabolism in social behavior and point to mitochondrial function in the nucleus accumbens as a potential marker and avenue of treatment for anxiety-related social disorders.

  19. Link prediction based on local information considering preferential attachment

    NASA Astrophysics Data System (ADS)

    Zeng, Shan

    2016-02-01

    Link prediction in complex networks has attracted much attention in many fields. In this paper, a common neighbors plus preferential attachment index is presented to estimate the likelihood of the existence of a link between two nodes based on local information of the nearest neighbors. Numerical experiments on six real networks demonstrated the high effectiveness and efficiency of the new index compared with five well-known and widely accepted indices: the common neighbors, resource allocation index, preferential attachment index, local path index and Katz index. The new index provides competitively accurate prediction with local path index and Katz index while has less computational complexity and is more accurate than the other two indices.

  20. Processes Linking Social Class and Racial Socialization in African American Dual-Earner Families

    ERIC Educational Resources Information Center

    Crouter, Ann C.; Baril, Megan E.; Davis, Kelly D.; McHale, Susan M.

    2008-01-01

    We examined the links between social class, occupational self-direction, self-efficacy, and racial socialization in a sample of 128 two-parent African American couples raising adolescents. A series of multivariate, multilevel models revealed that mothers' SES was connected to self-efficacy via its association with occupational self-direction; in…

  1. Neural responses to exclusion predict susceptibility to social influence.

    PubMed

    Falk, Emily B; Cascio, Christopher N; O'Donnell, Matthew Brook; Carp, Joshua; Tinney, Francis J; Bingham, C Raymond; Shope, Jean T; Ouimet, Marie Claude; Pradhan, Anuj K; Simons-Morton, Bruce G

    2014-05-01

    Social influence is prominent across the lifespan, but sensitivity to influence is especially high during adolescence and is often associated with increased risk taking. Such risk taking can have dire consequences. For example, in American adolescents, traffic-related crashes are leading causes of nonfatal injury and death. Neural measures may be especially useful in understanding the basic mechanisms of adolescents' vulnerability to peer influence. We examined neural responses to social exclusion as potential predictors of risk taking in the presence of peers in recently licensed adolescent drivers. Risk taking was assessed in a driving simulator session occurring approximately 1 week after the neuroimaging session. Increased activity in neural systems associated with the distress of social exclusion and mentalizing during an exclusion episode predicted increased risk taking in the presence of a peer (controlling for solo risk behavior) during a driving simulator session outside the neuroimaging laboratory 1 week later. These neural measures predicted risky driving behavior above and beyond self-reports of susceptibility to peer pressure and distress during exclusion. These results address the neural bases of social influence and risk taking; contribute to our understanding of social and emotional function in the adolescent brain; and link neural activity in specific, hypothesized, regions to risk-relevant outcomes beyond the neuroimaging laboratory. Results of this investigation are discussed in terms of the mechanisms underlying risk taking in adolescents and the public health implications for adolescent driving. Copyright © 2014 Society for Adolescent Health and Medicine. All rights reserved.

  2. Linking Social Anxiety with Social Competence in Early Adolescence: Physiological and Coping Moderators.

    PubMed

    Kaeppler, Alexander K; Erath, Stephen A

    2017-02-01

    Despite relatively universal feelings of discomfort in social situations, there is considerable evidence for diversity in the social behaviors and peer experiences of socially anxious youth. However, to date, very little research has been conducted with the aim of identifying factors that differentiate socially anxious youth who are more socially competent from those who are less socially competent. The present study addresses this gap in the literature by examining whether physiological and cognitive coping responses to social stress moderate the association between social anxiety and social competence. Participants were a community sample of 123 fifth and sixth graders (Mage = 12.03). Social anxiety was measured globally and in the context of a lab-based peer evaluation situation, and social competence was assessed via teacher-reports. Physiological (i.e., skin conductance level reactivity, SCLR, and respiratory sinus arrhythmia reactivity, RSAR) and coping (i.e., disengaged) responses to social stressors were also assessed. Results indicated that SCLR and disengaged coping with peer victimization moderated associations linking global and context-specific social anxiety with social competence, such that social anxiety was associated with lower social competence at lower levels of SCLR and higher levels of disengaged coping with peer victimization. Thus, whether socially anxious preadolescents exhibit more or less competent social behavior may depend, in part, on how they respond to peer-evaluative stress. Inflexible physiological responses and disengaged coping responses may undermine social competence, whereas engaged responses may counteract socially anxious preadolescents' tendency to withdraw from social interactions or focus primarily on threat cues.

  3. Predicting Social Security numbers from public data

    PubMed Central

    Acquisti, Alessandro; Gross, Ralph

    2009-01-01

    Information about an individual's place and date of birth can be exploited to predict his or her Social Security number (SSN). Using only publicly available information, we observed a correlation between individuals' SSNs and their birth data and found that for younger cohorts the correlation allows statistical inference of private SSNs. The inferences are made possible by the public availability of the Social Security Administration's Death Master File and the widespread accessibility of personal information from multiple sources, such as data brokers or profiles on social networking sites. Our results highlight the unexpected privacy consequences of the complex interactions among multiple data sources in modern information economies and quantify privacy risks associated with information revelation in public forums. PMID:19581585

  4. The Power of Implicit Social Relation in Rating Prediction of Social Recommender Systems

    PubMed Central

    Reafee, Waleed; Salim, Naomie; Khan, Atif

    2016-01-01

    The explosive growth of social networks in recent times has presented a powerful source of information to be utilized as an extra source for assisting in the social recommendation problems. The social recommendation methods that are based on probabilistic matrix factorization improved the recommendation accuracy and partly solved the cold-start and data sparsity problems. However, these methods only exploited the explicit social relations and almost completely ignored the implicit social relations. In this article, we firstly propose an algorithm to extract the implicit relation in the undirected graphs of social networks by exploiting the link prediction techniques. Furthermore, we propose a new probabilistic matrix factorization method to alleviate the data sparsity problem through incorporating explicit friendship and implicit friendship. We evaluate our proposed approach on two real datasets, Last.Fm and Douban. The experimental results show that our method performs much better than the state-of-the-art approaches, which indicates the importance of incorporating implicit social relations in the recommendation process to address the poor prediction accuracy. PMID:27152663

  5. Neighborhood linguistic diversity predicts infants' social learning.

    PubMed

    Howard, Lauren H; Carrazza, Cristina; Woodward, Amanda L

    2014-11-01

    Infants' direct interactions with caregivers have been shown to powerfully influence social and cognitive development. In contrast, little is known about the cognitive influence of social contexts beyond the infant's immediate interactions with others, for example, the communities in which infants live. The current study addressed this issue by asking whether neighborhood linguistic diversity predicts infants' propensity to learn from diverse social partners. Data were taken from a series of experiments in which 19-month-old infants from monolingual, English-speaking homes were tested in paradigms that assessed their tendency to imitate the actions of an adult who spoke either English or Spanish. Infants who lived in more linguistically diverse neighborhoods imitated more of the Spanish speaker's actions. This relation was observed in two separate datasets and found to be independent from variation in infants' general imitative abilities, age, median family income and population density. These results provide novel evidence suggesting that infants' social learning is predicted by the diversity of the communities in which they live.

  6. Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis

    PubMed Central

    Berlusconi, Giulia; Calderoni, Francesco; Parolini, Nicola; Verani, Marco; Piccardi, Carlo

    2016-01-01

    The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities. PMID:27104948

  7. Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis.

    PubMed

    Berlusconi, Giulia; Calderoni, Francesco; Parolini, Nicola; Verani, Marco; Piccardi, Carlo

    2016-01-01

    The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities.

  8. Perceived social support predicts increased conscientiousness during older adulthood.

    PubMed

    Hill, Patrick L; Payne, Brennan R; Jackson, Joshua J; Stine-Morrow, Elizabeth A L; Roberts, Brent W

    2014-07-01

    This study examined whether perceived social support predicted adaptive personality change in older adulthood, focusing on the trait of conscientiousness. We tested this hypothesis both at the broad domain level and with respect to the specific lower order facets that comprise conscientiousness: order, self-control, industriousness, responsibility, and traditionalism. A sample of 143 older adults (aged 60-91) completed measures of conscientiousness and social support during 2 assessments 7 months apart. Social support and conscientiousness were positively correlated among older adults. Moreover, older adults who perceived greater social support at baseline were more likely to gain in conscientiousness over time. The magnitude of this effect was relatively similar across the order, self-control, and industriousness facets. Perceived social support provides multiple benefits later in life, and the current results add to this literature by showing that it also promotes conscientiousness. As conscientiousness is linked to a variety of positive outcomes later in life, including health, future research should examine whether conscientiousness change may be an important mechanism through which social support enhances resilience in older adulthood. © The Author 2013. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  9. Link-Prediction Enhanced Consensus Clustering for Complex Networks.

    PubMed

    Burgess, Matthew; Adar, Eytan; Cafarella, Michael

    2016-01-01

    Many real networks that are collected or inferred from data are incomplete due to missing edges. Missing edges can be inherent to the dataset (Facebook friend links will never be complete) or the result of sampling (one may only have access to a portion of the data). The consequence is that downstream analyses that "consume" the network will often yield less accurate results than if the edges were complete. Community detection algorithms, in particular, often suffer when critical intra-community edges are missing. We propose a novel consensus clustering algorithm to enhance community detection on incomplete networks. Our framework utilizes existing community detection algorithms that process networks imputed by our link prediction based sampling algorithm and merges their multiple partitions into a final consensus output. On average our method boosts performance of existing algorithms by 7% on artificial data and 17% on ego networks collected from Facebook.

  10. Predictability of Extreme Events in Social Media

    PubMed Central

    Miotto, José M.; Altmann, Eduardo G.

    2014-01-01

    It is part of our daily social-media experience that seemingly ordinary items (videos, news, publications, etc.) unexpectedly gain an enormous amount of attention. Here we investigate how unexpected these extreme events are. We propose a method that, given some information on the items, quantifies the predictability of events, i.e., the potential of identifying in advance the most successful items. Applying this method to different data, ranging from views in YouTube videos to posts in Usenet discussion groups, we invariantly find that the predictability increases for the most extreme events. This indicates that, despite the inherently stochastic collective dynamics of users, efficient prediction is possible for the most successful items. PMID:25369138

  11. Design and Implementation of Davis Social Links OSN Kernel

    NASA Astrophysics Data System (ADS)

    Tran, Thomas; Chan, Kelcey; Ye, Shaozhi; Bhattacharyya, Prantik; Garg, Ankush; Lu, Xiaoming; Wu, S. Felix

    Social network popularity continues to rise as they broaden out to more users. Hidden away within these social networks is a valuable set of data that outlines everyone’s relationships. Networks have created APIs such as the Facebook Development Platform and OpenSocial that allow developers to create applications that can leverage user information. However, at the current stage, the social network support for these new applications is fairly limited in its functionality. Most, if not all, of the existing internet applications such as email, BitTorrent, and Skype cannot benefit from the valuable social network among their own users. In this paper, we present an architecture that couples two different communication layers together: the end2end communication layer and the social context layer, under the Davis Social Links (DSL) project. Our proposed architecture attempts to preserve the original application semantics (i.e., we can use Thunderbird or Outlook, unmodified, to read our SMTP emails) and provides the communicating parties (email sender and receivers) a social context for control and management. For instance, the receiver can set trust policy rules based on the social context between the pair, to determine how a particular email in question should be prioritized for delivery to the SMTP layer. Furthermore, as our architecture includes two coupling layers, it is then possible, as an option, to shift some of the services from the original applications into the social context layer. In the context of email, for example, our architecture allows users to choose operations, such as reply, reply-all, and forward, to be realized in either the application layer or the social network layer. And, the realization of these operations under the social network layer offers powerful features unavailable in the original applications. To validate our coupling architecture, we have implemented a DSL kernel prototype as a Facebook application called CyrusDSL (currently about

  12. Extended resource allocation index for link prediction of complex network

    NASA Astrophysics Data System (ADS)

    Liu, Shuxin; Ji, Xinsheng; Liu, Caixia; Bai, Yi

    2017-08-01

    Recently, a number of similarity-based methods have been proposed to predict the missing links in complex network. Among these indices, the resource allocation index performs very well with lower time complexity. However, it ignores potential resources transferred by local paths between two endpoints. Motivated by the resource exchange taking places between endpoints, an extended resource allocation index is proposed. Empirical study on twelve real networks and three synthetic dynamic networks has shown that the index we proposed can achieve a good performance, compared with eight mainstream baselines.

  13. Social Support Predicts Hearing Aid Satisfaction.

    PubMed

    Singh, Gurjit; Lau, Sin-Tung; Pichora-Fuller, M Kathleen

    2015-01-01

    The goals of the current research were to determine: (1) whether there is a relationship between perceived social support and hearing aid satisfaction, and (2) how well perceived social support predicts hearing aid satisfaction relative to other correlates previously identified in the literature. In study 1, 173 adult ((Equation is included in full-text article.)age = 68.9 years; SD = 13.4) users of hearing aids completed a survey assessing attitudes toward health, hearing, and hearing aids, as well as a questionnaire assessing Big-Five personality factors (Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism) either using paper and pencil or the Internet. In a follow-up study designed to replicate and extend the results from study 1, 161 adult ((Equation is included in full-text article.)age = 32.8 years; SD = 13.3) users of hearing aids completed a similar survey on the Internet. In study 2, participants also completed a measure of hearing aid benefit and reported the style of their hearing aid. In studies 1 and 2, perceived social support was significantly correlated with hearing aid satisfaction (respectively, r = 0.34, r = 0.51, ps < 0.001). The results of a regression analysis revealed that in study 1, 22% of the variance in hearing aid satisfaction scores was predicted by perceived social support, satisfaction with one's hearing health care provider, duration of daily hearing aid use, and openness. In study 2, 43% of the variance in hearing aid satisfaction was predicted by perceived social support, hearing aid benefit, neuroticism, and hearing aid style. Overall, perceived social support was the best predictor of hearing aid satisfaction in both studies. After controlling for response style (i.e., acquiescence or the tendency to respond positively), the correlation between perceived social support and hearing aid satisfaction remained the same in study 1 (r = 0.34, p < 0.001) and was lower in study 2 (r = 0.39, p < 0

  14. Ethical and social aspects of risk predictions.

    PubMed

    Fletcher, J C

    1984-01-01

    This paper reviews past, present and future social and ethical considerations of screening carriers of autosomal disorders and other heterozygotes. A body of ethical and social guidance has evolved in the 1970's and 1980's for screening. The values of voluntaristic participation and informed consent are high. The goal of programs should be to provide couples, families, and individuals with knowledge respecting their reproductive choices. The dangers are coercive strategies, stigmatization, and careless communication of risk information. It is assumed that the number of autosomal carrier states that are screenable will undoubtedly increase as will states of heterozygosity that cause susceptibility to common diseases. Before the end of the century, something approaching a "biopsy of the human genome" will be a practical reality. To balance the potential for harmful psychological and social effects of so much new genetic knowledge, new efforts must be made to find treatments for progeny affected by recessive disorders. Maternal and paternal screening, prenatal diagnosis and treatment will be increasingly linked in the future. This paper will report on a case of fetal therapy for congenital adrenal hyperplasia as a paradigm for the future. The argument will be made that society ought to put a higher priority on prenatal care and prevention of disorders of prematurity than genetic disorders with a low frequency, lest genetic screening be distorted by unfounded concern about eugenics.

  15. Radio link design framework for WSN deployment and performance prediction

    NASA Astrophysics Data System (ADS)

    Saponara, Sergio; Giannetti, Filippo

    2017-05-01

    For an easy implementation of wireless sensor and actuator networks (WSAN), the state-of-the-art is offering single-chip solutions embedding in the same device a microcontroller core with a wireless transceiver. These internet-on-chip devices support different protocols (Bluetooth, ZigBee, Bluetooth Low Energy, sub- GHz links), from about 300 MHz to 6 GHz, with max. sustained bit-rates from 250 kb/s (sub-GHz links) to 4 Mb/s (Wi-Fi), and different trade-offs between RX sensitivity (from -74 to -100 dBm), RX noise figure (few dB to 10 dB), maximum TX power (from 0 to 22 dBm), link distances, power consumption levels (from few mW to several hundreds of mW). One limit for their successful application is the missing of an easy-to-use modeling and simulation environment to plan their deployment. The need is to predict, before installing a network, at which distances the sensors can be deployed, the real achievable bit-rate, communication latency, outage probability, power consumption, battery duration. To this aim, this paper presents the H2AWKS (Harsh environment and Hardware Aware Wireless linK Simulator) simulator, which allows the planning of a WSAN taking into account environment constraints and hardware parameters. Applications of H2AWKS to real WSAN case studies prove that it is an easy to use simulation environment, which allows design exploration of the system performance of a WSAN as a function of the operating environment and of the hardware parameters of the used devices.

  16. Disrupted Prediction Error Links Excessive Amygdala Activation to Excessive Fear.

    PubMed

    Sengupta, Auntora; Winters, Bryony; Bagley, Elena E; McNally, Gavan P

    2016-01-13

    Basolateral amygdala (BLA) is critical for fear learning, and its heightened activation is widely thought to underpin a variety of anxiety disorders. Here we used chemogenetic techniques in rats to study the consequences of heightened BLA activation for fear learning and memory, and to specifically identify a mechanism linking increased activity of BLA glutamatergic neurons to aberrant fear. We expressed the excitatory hM3Dq DREADD in rat BLA glutamatergic neurons and showed that CNO acted selectively to increase their activity, depolarizing these neurons and increasing their firing rates. This chemogenetic excitation of BLA glutamatergic neurons had no effect on the acquisition of simple fear learning, regardless of whether this learning led to a weak or strong fear memory. However, in an associative blocking task, chemogenetic excitation of BLA glutamatergic neurons yielded significant learning to a blocked conditioned stimulus, which otherwise should not have been learned about. Moreover, in an overexpectation task, chemogenetic manipulation of BLA glutamatergic neurons prevented use of negative prediction error to reduce fear learning, leading to significant impairments in fear inhibition. These effects were not attributable to the chemogenetic manipulation enhancing arousal, increasing asymptotic levels of fear learning or fear memory consolidation. Instead, chemogenetic excitation of BLA glutamatergic neurons disrupted use of prediction error to regulate fear learning. Several neuropsychiatric disorders are characterized by heightened activation of the amygdala. This heightened activation has been hypothesized to underlie increased emotional reactivity, fear over generalization, and deficits in fear inhibition. Yet the mechanisms linking heightened amygdala activation to heightened emotional learning are elusive. Here we combined chemogenetic excitation of rat basolateral amygdala glutamatergic neurons with a variety of behavioral approaches to show that

  17. CD-Based Indices for Link Prediction in Complex Network

    PubMed Central

    Wang, Tao; Wang, Hongjue; Wang, Xiaoxia

    2016-01-01

    Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks. PMID:26752405

  18. CD-Based Indices for Link Prediction in Complex Network.

    PubMed

    Wang, Tao; Wang, Hongjue; Wang, Xiaoxia

    2016-01-01

    Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks.

  19. Linking Individual and Collective Behavior in Adaptive Social Networks

    NASA Astrophysics Data System (ADS)

    Pinheiro, Flávio L.; Santos, Francisco C.; Pacheco, Jorge M.

    2016-03-01

    Adaptive social structures are known to promote the evolution of cooperation. However, up to now the characterization of the collective, population-wide dynamics resulting from the self-organization of individual strategies on a coevolving, adaptive network has remained unfeasible. Here we establish a (reversible) link between individual (micro)behavior and collective (macro)behavior for coevolutionary processes. We demonstrate that an adaptive network transforms a two-person social dilemma locally faced by individuals into a collective dynamics that resembles that associated with an N -person coordination game, whose characterization depends sensitively on the relative time scales between the entangled behavioral and network evolutions. In particular, we show that the faster the relative rate of adaptation of the network, the smaller the critical fraction of cooperators required for cooperation to prevail, thus establishing a direct link between network adaptation and the evolution of cooperation. The framework developed here is general and may be readily applied to other dynamical processes occurring on adaptive networks, notably, the spreading of contagious diseases or the diffusion of innovations.

  20. Link prediction boosted psychiatry disorder classification for functional connectivity network

    NASA Astrophysics Data System (ADS)

    Li, Weiwei; Mei, Xue; Wang, Hao; Zhou, Yu; Huang, Jiashuang

    2017-02-01

    Functional connectivity network (FCN) is an effective tool in psychiatry disorders classification, and represents cross-correlation of the regional blood oxygenation level dependent signal. However, FCN is often incomplete for suffering from missing and spurious edges. To accurate classify psychiatry disorders and health control with the incomplete FCN, we first `repair' the FCN with link prediction, and then exact the clustering coefficients as features to build a weak classifier for every FCN. Finally, we apply a boosting algorithm to combine these weak classifiers for improving classification accuracy. Our method tested by three datasets of psychiatry disorder, including Alzheimer's Disease, Schizophrenia and Attention Deficit Hyperactivity Disorder. The experimental results show our method not only significantly improves the classification accuracy, but also efficiently reconstructs the incomplete FCN.

  1. The SAIL databank: linking multiple health and social care datasets.

    PubMed

    Lyons, Ronan A; Jones, Kerina H; John, Gareth; Brooks, Caroline J; Verplancke, Jean-Philippe; Ford, David V; Brown, Ginevra; Leake, Ken

    2009-01-16

    Vast amounts of data are collected about patients and service users in the course of health and social care service delivery. Electronic data systems for patient records have the potential to revolutionise service delivery and research. But in order to achieve this, it is essential that the ability to link the data at the individual record level be retained whilst adhering to the principles of information governance. The SAIL (Secure Anonymised Information Linkage) databank has been established using disparate datasets, and over 500 million records from multiple health and social care service providers have been loaded to date, with further growth in progress. Having established the infrastructure of the databank, the aim of this work was to develop and implement an accurate matching process to enable the assignment of a unique Anonymous Linking Field (ALF) to person-based records to make the databank ready for record-linkage research studies. An SQL-based matching algorithm (MACRAL, Matching Algorithm for Consistent Results in Anonymised Linkage) was developed for this purpose. Firstly the suitability of using a valid NHS number as the basis of a unique identifier was assessed using MACRAL. Secondly, MACRAL was applied in turn to match primary care, secondary care and social services datasets to the NHS Administrative Register (NHSAR), to assess the efficacy of this process, and the optimum matching technique. The validation of using the NHS number yielded specificity values > 99.8% and sensitivity values > 94.6% using probabilistic record linkage (PRL) at the 50% threshold, and error rates were < 0.2%. A range of techniques for matching datasets to the NHSAR were applied and the optimum technique resulted in sensitivity values of: 99.9% for a GP dataset from primary care, 99.3% for a PEDW dataset from secondary care and 95.2% for the PARIS database from social care. With the infrastructure that has been put in place, the reliable matching process that has been

  2. Siderophore production and biofilm formation as linked social traits.

    PubMed

    Harrison, Freya; Buckling, Angus

    2009-05-01

    The virulence of pathogenic microbes can depend on individual cells cooperating in the concerted production of molecules that facilitate host colonization or exploitation. However, cooperating groups can be exploited by social defectors or 'cheats'. Understanding the ecology and evolution of cooperation is therefore relevant to clinical microbiology. We studied two genetically linked cooperative traits involved in host exploitation by the opportunistic human pathogen Pseudomonas aeruginosa. Clones that defected from cooperative production of iron-scavenging siderophores were deficient in biofilm formation. The presence of such clones in mixed biofilms with a wild-type clone led to reduced biofilm mass. The fitness advantage of siderophore-deficient mutants in the presence of wild-type bacteria was no greater in biofilm than in planktonic culture, suggesting that these mutants did not gain an additional advantage by exploiting wild-type biofilm polymer. Reduced biofilm formation therefore represents a pleiotropic cost of defection from siderophore production.

  3. Hyperscanning: simultaneous fMRI during linked social interactions.

    PubMed

    Montague, P Read; Berns, Gregory S; Cohen, Jonathan D; McClure, Samuel M; Pagnoni, Giuseppe; Dhamala, Mukesh; Wiest, Michael C; Karpov, Igor; King, Richard D; Apple, Nathan; Fisher, Ronald E

    2002-08-01

    "Plain question and plain answer make the shortest road out of most perplexities." Mark Twain-Life on the Mississippi. A new methodology for the measurement of the neural substrates of human social interaction is described. This technology, termed "Hyperscan," embodies both the hardware and the software necessary to link magnetic resonance scanners through the internet. Hyperscanning allows for the performance of human behavioral experiments in which participants can interact with each other while functional MRI is acquired in synchrony with the behavioral interactions. Data are presented from a simple game of deception between pairs of subjects. Because people may interact both asymmetrically and asynchronously, both the design and the analysis must accommodate this added complexity. Several potential approaches are described.

  4. Aggression and Anxiety: Social Context and Neurobiological Links

    PubMed Central

    Neumann, Inga D.; Veenema, Alexa H.; Beiderbeck, Daniela I.

    2009-01-01

    Psychopathologies such as anxiety- and depression-related disorders are often characterized by impaired social behaviours including excessive aggression and violence. Excessive aggression and violence likely develop as a consequence of generally disturbed emotional regulation, such as abnormally high or low levels of anxiety. This suggests an overlap between brain circuitries and neurochemical systems regulating aggression and anxiety. In this review, we will discuss different forms of male aggression, rodent models of excessive aggression, and neurobiological mechanisms underlying male aggression in the context of anxiety. We will summarize our attempts to establish an animal model of high and abnormal aggression using rats selected for high (HAB) vs. low (LAB) anxiety-related behaviour. Briefly, male LAB rats and, to a lesser extent, male HAB rats show high and abnormal forms of aggression compared with non-selected (NAB) rats, making them a suitable animal model for studying excessive aggression in the context of extremes in innate anxiety. In addition, we will discuss differences in the activity of the hypothalamic–pituitary–adrenal axis, brain arginine vasopressin, and the serotonin systems, among others, which contribute to the distinct behavioural phenotypes related to aggression and anxiety. Further investigation of the neurobiological systems in animals with distinct anxiety phenotypes might provide valuable information about the link between excessive aggression and disturbed emotional regulation, which is essential for understanding the social and emotional deficits that are characteristic of many human psychiatric disorders. PMID:20407578

  5. Clarifying the links between social support and health: culture, stress, and neuroticism matter.

    PubMed

    Park, Jiyoung; Kitayama, Shinobu; Karasawa, Mayumi; Curhan, Katherine; Markus, Hazel R; Kawakami, Norito; Miyamoto, Yuri; Love, Gayle D; Coe, Christopher L; Ryff, Carol D

    2013-02-01

    Although it is commonly assumed that social support positively predicts health, the empirical evidence has been inconsistent. We argue that three moderating factors must be considered: (1) support-approving norms (cultural context); (2) support-requiring situations (stressful events); and (3) support-accepting personal style (low neuroticism). Our large-scale cross-cultural survey of Japanese and US adults found significant associations between perceived support and health. The association was more strongly evident among Japanese (from a support-approving cultural context) who reported high life stress (in a support-requiring situation). Moreover, the link between support and health was especially pronounced if these Japanese were low in neuroticism.

  6. Does social class predict diet quality?

    PubMed

    Darmon, Nicole; Drewnowski, Adam

    2008-05-01

    A large body of epidemiologic data show that diet quality follows a socioeconomic gradient. Whereas higher-quality diets are associated with greater affluence, energy-dense diets that are nutrient-poor are preferentially consumed by persons of lower socioeconomic status (SES) and of more limited economic means. As this review demonstrates, whole grains, lean meats, fish, low-fat dairy products, and fresh vegetables and fruit are more likely to be consumed by groups of higher SES. In contrast, the consumption of refined grains and added fats has been associated with lower SES. Although micronutrient intake and, hence, diet quality are affected by SES, little evidence indicates that SES affects either total energy intakes or the macronutrient composition of the diet. The observed associations between SES variables and diet-quality measures can be explained by a variety of potentially causal mechanisms. The disparity in energy costs ($/MJ) between energy-dense and nutrient-dense foods is one such mechanism; easy physical access to low-cost energy-dense foods is another. If higher SES is a causal determinant of diet quality, then the reported associations between diet quality and better health, found in so many epidemiologic studies, may have been confounded by unobserved indexes of social class. Conversely, if limited economic resources are causally linked to low-quality diets, some current strategies for health promotion, based on recommending high-cost foods to low-income people, may prove to be wholly ineffective. Exploring the possible causal relations between SES and diet quality is the purpose of this review.

  7. Linking Social Media Reports to Network Indicators of DoS Attacks

    DTIC Science & Technology

    2015-02-15

    reporting in fast-paced social media such as Twitter, but these reports are rarely linked to quantiable network behavior. A data set of network-based...FEB 2015 2. REPORT TYPE N/A 3. DATES COVERED 4. TITLE AND SUBTITLE Linking Social Media Reports to Network Indicators of DoS Attacks 5a...Random sample of 30 (D, E) pairs yielding 21 unique entities (E) Linking Social Media Reports to Network Indicators of DoS Attacks Evan Wright

  8. Anticipatory smiling: Linking early affective communication and social outcome

    PubMed Central

    Parlade, Meaghan Venezia; Messinger, Daniel S.; Delgado, Christine E.F.; Kaiser, Marygrace Yale; Van Hecke, Amy Vaughan; Mundy, Peter C.

    2009-01-01

    In anticipatory smiles, infants appear to communicate pre-existing positive affect by smiling at an object and then turning the smile toward an adult. We report two studies in which the precursors, development, and consequences of anticipatory smiling were investigated. Study 1 revealed a positive correlation between infant smiling at 6 months and the level of anticipatory smiling at 8 and 10 months during joint attention episodes, as well as a positive correlation between anticipatory smiling and parent-rated social expressivity scores at 30 months. Study 2 confirmed a developmental increase in the number of infants using anticipatory smiles between 9 and 12 months that had been initially documented in the Study 1 sample [Venezia, M., Messinger, D. S., Thorp, D., & Mundy, P. (2004). The development of anticipatory smiling. Infancy, 6(3), 397–406]. Additionally, anticipatory smiling at 9 months positively predicted parent-rated social competence scores at 30 months. Findings are discussed with regard to the importance of anticipatory smiling in early socioemotional development. PMID:19004500

  9. Expectancy bias mediates the link between social anxiety and memory bias for social evaluation

    PubMed Central

    Caouette, Justin D.; Ruiz, Sarah K.; Lee, Clinton C.; Anbari, Zainab; Schriber, Roberta A.; Guyer, Amanda E.

    2014-01-01

    Social anxiety (SA) involves a multitude of cognitive symptoms related to fear of evaluation, including expectancy and memory biases. We examined whether memory biases are influenced by expectancy biases for social feedback in SA. We hypothesized that, faced with a socially evaluative event, people with higher SA would show a negative expectancy bias for future feedback. Furthermore, we predicted that memory bias for feedback in SA would be mediated by expectancy bias. Ninety-four undergraduate students (55 women, mean age = 19.76 years) underwent a two-visit task that measured expectations about (Visit 1) and memory of (Visit 2) feedback from unknown peers. Results showed that higher levels of SA were associated with negative expectancy bias. An indirect relationship was found between SA and memory bias that was mediated by expectancy bias. The results suggest that expectancy biases are in the causal path from SA to negative memory biases for social evaluation. PMID:25252925

  10. Linking social and pathogen transmission networks using microbial genetics in giraffe (Giraffa camelopardalis).

    PubMed

    VanderWaal, Kimberly L; Atwill, Edward R; Isbell, Lynne A; McCowan, Brenda

    2014-03-01

    Although network analysis has drawn considerable attention as a promising tool for disease ecology, empirical research has been hindered by limitations in detecting the occurrence of pathogen transmission (who transmitted to whom) within social networks. Using a novel approach, we utilize the genetics of a diverse microbe, Escherichia coli, to infer where direct or indirect transmission has occurred and use these data to construct transmission networks for a wild giraffe population (Giraffe camelopardalis). Individuals were considered to be a part of the same transmission chain and were interlinked in the transmission network if they shared genetic subtypes of E. coli. By using microbial genetics to quantify who transmits to whom independently from the behavioural data on who is in contact with whom, we were able to directly investigate how the structure of contact networks influences the structure of the transmission network. To distinguish between the effects of social and environmental contact on transmission dynamics, the transmission network was compared with two separate contact networks defined from the behavioural data: a social network based on association patterns, and a spatial network based on patterns of home-range overlap among individuals. We found that links in the transmission network were more likely to occur between individuals that were strongly linked in the social network. Furthermore, individuals that had more numerous connections or that occupied 'bottleneck' positions in the social network tended to occupy similar positions in the transmission network. No similar correlations were observed between the spatial and transmission networks. This indicates that an individual's social network position is predictive of transmission network position, which has implications for identifying individuals that function as super-spreaders or transmission bottlenecks in the population. These results emphasize the importance of association patterns in

  11. Attention Biases to Threat Link Behavioral Inhibition to Social Withdrawal over Time in Very Young Children

    PubMed Central

    Reeb-Sutherland, Bethany C.; McDermott, Jennifer Martin; White, Lauren K.; Henderson, Heather A.; Degnan, Kathryn A.; Hane, Amie A.; Pine, Daniel S.; Fox, Nathan A.

    2013-01-01

    Behaviorally inhibited children display a temperamental profile characterized by social withdrawal and anxious behaviors. Previous research, focused largely on adolescents, suggests that attention biases to threat may sustain high levels of behavioral inhibition (BI) over time, helping link early temperament to social outcomes. However, no prior studies examine the association between attention bias and BI before adolescence. The current study examined the interrelations among BI, attention biases to threat, and social withdrawal already manifest in early childhood. Children (N=187, 83 Male, Mage=61.96 months) were characterized for BI in toddlerhood (24 & 36 months). At 5 years, they completed an attention bias task and concurrent social withdrawal was measured. As expected, BI in toddlerhood predicted high levels of social withdrawal in early childhood. However, this relation was moderated by attention bias. The BI-withdrawal association was only evident for children who displayed an attention bias toward threat. The data provide further support for models associating attention with socioemotional development and the later emergence of clinical anxiety. PMID:21318555

  12. UAV field demonstration of social media enabled tactical data link

    NASA Astrophysics Data System (ADS)

    Olson, Christopher C.; Xu, Da; Martin, Sean R.; Castelli, Jonathan C.; Newman, Andrew J.

    2015-05-01

    This paper addresses the problem of enabling Command and Control (C2) and data exfiltration functions for missions using small, unmanned, airborne surveillance and reconnaissance platforms. The authors demonstrated the feasibility of using existing commercial wireless networks as the data transmission infrastructure to support Unmanned Aerial Vehicle (UAV) autonomy functions such as transmission of commands, imagery, metadata, and multi-vehicle coordination messages. The authors developed and integrated a C2 Android application for ground users with a common smart phone, a C2 and data exfiltration Android application deployed on-board the UAVs, and a web server with database to disseminate the collected data to distributed users using standard web browsers. The authors performed a mission-relevant field test and demonstration in which operators commanded a UAV from an Android device to search and loiter; and remote users viewed imagery, video, and metadata via web server to identify and track a vehicle on the ground. Social media served as the tactical data link for all command messages, images, videos, and metadata during the field demonstration. Imagery, video, and metadata were transmitted from the UAV to the web server via multiple Twitter, Flickr, Facebook, YouTube, and similar media accounts. The web server reassembled images and video with corresponding metadata for distributed users. The UAV autopilot communicated with the on-board Android device via on-board Bluetooth network.

  13. Cognitive Biases and the Link between Shyness and Social Anxiety in Early Adolescence

    ERIC Educational Resources Information Center

    Weeks, Murray; Ooi, Laura L.; Coplan, Robert J.

    2016-01-01

    Shy children display wariness in unfamiliar social situations and often experience feelings of social anxiety. This study explored the potential mediating role of cognitive biases in the link between shyness and social anxiety in early adolescence. In particular, we focused on judgments of the probability and cost of negative social situations…

  14. Cognitive Biases and the Link between Shyness and Social Anxiety in Early Adolescence

    ERIC Educational Resources Information Center

    Weeks, Murray; Ooi, Laura L.; Coplan, Robert J.

    2016-01-01

    Shy children display wariness in unfamiliar social situations and often experience feelings of social anxiety. This study explored the potential mediating role of cognitive biases in the link between shyness and social anxiety in early adolescence. In particular, we focused on judgments of the probability and cost of negative social situations…

  15. Social Factors That Predict Fear of Academic Success

    ERIC Educational Resources Information Center

    Gore, Jonathan S.; Thomas, Jessica; Jones, Stevy; Mahoney, Lauren; Dukes, Kristina; Treadway, Jodi

    2016-01-01

    Fear of academic success is ultimately a fear of social exclusion. Therefore, various forms of social inclusion may alleviate this fear. Three studies tested the hypothesis that social inclusion variables negatively predict fear of success. In Study 1, middle and high school students (n = 129) completed surveys of parental involvement, parental…

  16. Social Factors That Predict Fear of Academic Success

    ERIC Educational Resources Information Center

    Gore, Jonathan S.; Thomas, Jessica; Jones, Stevy; Mahoney, Lauren; Dukes, Kristina; Treadway, Jodi

    2016-01-01

    Fear of academic success is ultimately a fear of social exclusion. Therefore, various forms of social inclusion may alleviate this fear. Three studies tested the hypothesis that social inclusion variables negatively predict fear of success. In Study 1, middle and high school students (n = 129) completed surveys of parental involvement, parental…

  17. Social support predicts inflammation, pain, and depressive symptoms: longitudinal relationships among breast cancer survivors.

    PubMed

    Hughes, Spenser; Jaremka, Lisa M; Alfano, Catherine M; Glaser, Ronald; Povoski, Stephen P; Lipari, Adele M; Agnese, Doreen M; Farrar, William B; Yee, Lisa D; Carson, William E; Malarkey, William B; Kiecolt-Glaser, Janice K

    2014-04-01

    Pain and depressive symptoms are commonly experienced by cancer survivors. Lower social support is linked to a variety of negative mental and physical health outcomes among survivors. Immune dysregulation may be one mechanism linking low social support to the development of pain and depressive symptoms over time. Accordingly, the goal of the present study was to examine the relationships among survivors' social support, pain, depressive symptoms, and inflammation. Breast cancer survivors (N=164, stages 0-IIIA) completed two study visits, one before any cancer treatment and the other 6 months after the completion of surgery, radiation, or chemotherapy, whichever came last. Women completed self-report questionnaires assessing social support, pain, and depressive symptoms, and provided a blood sample at both visits. Survivors with lower social support prior to treatment experienced higher levels of pain and depressive symptoms over time than their more socially supported counterparts. Furthermore, women with lower pretreatment social support had higher levels of IL-6 over time, and these elevations in IL-6 predicted marginally larger increases in depressive symptoms. The results of this study suggest that social support at the time of diagnosis predicts the post-treatment development of pain, depressive symptoms, and inflammation. Consequently, early interventions targeting survivors' social networks could improve quality of life during survivorship. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Social support predicts inflammation, pain, and depressive symptoms: Longitudinal relationships among breast cancer survivors

    PubMed Central

    Hughes, Spenser; Jaremka, Lisa M.; Alfano, Catherine M.; Glaser, Ronald; Povoski, Stephen P.; Lipari, Adele M.; Agnese, Doreen M.; Farrar, William B.; Yee, Lisa D.; Carson, William E.; Malarkey, William B.; Kiecolt-Glaser, Janice K.

    2014-01-01

    Objective Pain and depressive symptoms are commonly experienced by cancer survivors. Lower social support is linked to a variety of negative mental and physical health outcomes among survivors. Immune dysregulation may be one mechanism linking low social support to the development of pain and depressive symptoms over time. Accordingly, the goal of the present study was to examine the relationships among survivors’ social support, pain, depressive symptoms, and inflammation. Methods Breast cancer survivors (N = 164, stages 0-IIIA) completed two study visits, one before any cancer treatment and the other 6 months after the completion of surgery, radiation, or chemotherapy, whichever came last. Women completed self-report questionnaires assessing social support, pain, and depressive symptoms, and provided a blood sample at both visits. Results Survivors with lower social support prior to treatment experienced higher levels of pain and depressive symptoms over time than their more socially supported counterparts. Furthermore, women with lower pretreatment social support had higher levels of IL-6 over time, and these elevations in IL-6 predicted marginally larger increases in depressive symptoms. Conclusions The results of this study suggest that social support at the time of diagnosis predicts the post-treatment development of pain, depressive symptoms, and inflammation. Consequently, early interventions targeting survivors’ social networks could improve quality of life during survivorship. PMID:24636499

  19. Playing the role of weak clique property in link prediction: A friend recommendation model

    NASA Astrophysics Data System (ADS)

    Ma, Chuang; Zhou, Tao; Zhang, Hai-Feng

    2016-07-01

    An important fact in studying link prediction is that the structural properties of networks have significant impacts on the performance of algorithms. Therefore, how to improve the performance of link prediction with the aid of structural properties of networks is an essential problem. By analyzing many real networks, we find a typical structural property: nodes are preferentially linked to the nodes with the weak clique structure (abbreviated as PWCS to simplify descriptions). Based on this PWCS phenomenon, we propose a local friend recommendation (FR) index to facilitate link prediction. Our experiments show that the performance of FR index is better than some famous local similarity indices, such as Common Neighbor (CN) index, Adamic-Adar (AA) index and Resource Allocation (RA) index. We then explain why PWCS can give rise to the better performance of FR index in link prediction. Finally, a mixed friend recommendation index (labelled MFR) is proposed by utilizing the PWCS phenomenon, which further improves the accuracy of link prediction.

  20. Playing the role of weak clique property in link prediction: A friend recommendation model.

    PubMed

    Ma, Chuang; Zhou, Tao; Zhang, Hai-Feng

    2016-07-21

    An important fact in studying link prediction is that the structural properties of networks have significant impacts on the performance of algorithms. Therefore, how to improve the performance of link prediction with the aid of structural properties of networks is an essential problem. By analyzing many real networks, we find a typical structural property: nodes are preferentially linked to the nodes with the weak clique structure (abbreviated as PWCS to simplify descriptions). Based on this PWCS phenomenon, we propose a local friend recommendation (FR) index to facilitate link prediction. Our experiments show that the performance of FR index is better than some famous local similarity indices, such as Common Neighbor (CN) index, Adamic-Adar (AA) index and Resource Allocation (RA) index. We then explain why PWCS can give rise to the better performance of FR index in link prediction. Finally, a mixed friend recommendation index (labelled MFR) is proposed by utilizing the PWCS phenomenon, which further improves the accuracy of link prediction.

  1. Disrupted prediction errors index social deficits in autism spectrum disorder

    PubMed Central

    Apps, Matthew A. J.; Bolis, Dimitris; Lehner, Rea; Gallagher, Louise; Wenderoth, Nicole

    2017-01-01

    Abstract Social deficits are a core symptom of autism spectrum disorder; however, the perturbed neural mechanisms underpinning these deficits remain unclear. It has been suggested that social prediction errors—coding discrepancies between the predicted and actual outcome of another’s decisions—might play a crucial role in processing social information. While the gyral surface of the anterior cingulate cortex signalled social prediction errors in typically developing individuals, this crucial social signal was altered in individuals with autism spectrum disorder. Importantly, the degree to which social prediction error signalling was aberrant correlated with diagnostic measures of social deficits. Effective connectivity analyses further revealed that, in typically developing individuals but not in autism spectrum disorder, the magnitude of social prediction errors was driven by input from the ventromedial prefrontal cortex. These data provide a novel insight into the neural substrates underlying autism spectrum disorder social symptom severity, and further research into the gyral surface of the anterior cingulate cortex and ventromedial prefrontal cortex could provide more targeted therapies to help ameliorate social deficits in autism spectrum disorder. PMID:28031223

  2. Disrupted prediction errors index social deficits in autism spectrum disorder.

    PubMed

    Balsters, Joshua H; Apps, Matthew A J; Bolis, Dimitris; Lehner, Rea; Gallagher, Louise; Wenderoth, Nicole

    2017-01-01

    Social deficits are a core symptom of autism spectrum disorder; however, the perturbed neural mechanisms underpinning these deficits remain unclear. It has been suggested that social prediction errors-coding discrepancies between the predicted and actual outcome of another's decisions-might play a crucial role in processing social information. While the gyral surface of the anterior cingulate cortex signalled social prediction errors in typically developing individuals, this crucial social signal was altered in individuals with autism spectrum disorder. Importantly, the degree to which social prediction error signalling was aberrant correlated with diagnostic measures of social deficits. Effective connectivity analyses further revealed that, in typically developing individuals but not in autism spectrum disorder, the magnitude of social prediction errors was driven by input from the ventromedial prefrontal cortex. These data provide a novel insight into the neural substrates underlying autism spectrum disorder social symptom severity, and further research into the gyral surface of the anterior cingulate cortex and ventromedial prefrontal cortex could provide more targeted therapies to help ameliorate social deficits in autism spectrum disorder.

  3. Early adolescent depressive symptoms: prediction from clique isolation, loneliness, and perceived social acceptance.

    PubMed

    Witvliet, Miranda; Brendgen, Mara; van Lier, Pol A C; Koot, Hans M; Vitaro, Frank

    2010-11-01

    This study examined whether clique isolation predicted an increase in depressive symptoms and whether this association was mediated by loneliness and perceived social acceptance in 310 children followed from age 11-14 years. Clique isolation was identified through social network analysis, whereas depressive symptoms, loneliness, and perceived social acceptance were assessed using self ratings. While accounting for initial levels of depressive symptoms, peer rejection, and friendlessness at age 11 years, a high probability of being isolated from cliques from age 11 to 13 years predicted depressive symptoms at age 14 years. The link between clique isolation and depressive symptoms was mediated by loneliness, but not by perceived social acceptance. No sex differences were found in the associations between clique isolation and depressive symptoms. These results suggest that clique isolation is a social risk factor for the escalation of depressive symptoms in early adolescence. Implications for research and prevention are discussed.

  4. Neural pathways link social support to attenuated neuroendocrine stress responses.

    PubMed

    Eisenberger, Naomi I; Taylor, Shelley E; Gable, Shelly L; Hilmert, Clayton J; Lieberman, Matthew D

    2007-05-01

    It is well established that a lack of social support constitutes a major risk factor for morbidity and mortality, comparable to risk factors such as smoking, obesity, and high blood pressure. Although it has been hypothesized that social support may benefit health by reducing physiological reactivity to stressors, the mechanisms underlying this process remain unclear. Moreover, to date, no studies have investigated the neurocognitive mechanisms that translate experiences of social support into the health outcomes that follow. To investigate these processes, thirty participants completed three tasks in which daily social support, neurocognitive reactivity to a social stressor, and neuroendocrine responses to a social stressor were assessed. Individuals who interacted regularly with supportive individuals across a 10-day period showed diminished cortisol reactivity to a social stressor. Moreover, greater social support and diminished cortisol responses were associated with diminished activity in the dorsal anterior cingulate cortex (dACC) and Brodmann's area (BA) 8, regions previously associated with the distress of social separation. Lastly, individual differences in dACC and BA 8 reactivity mediated the relationship between high daily social support and low cortisol reactivity, such that supported individuals showed reduced neurocognitive reactivity to social stressors, which in turn was associated with reduced neuroendocrine stress responses. This study is the first to investigate the neural underpinnings of the social support-health relationship and provides evidence that social support may ultimately benefit health by diminishing neural and physiological reactivity to social stressors.

  5. Neural pathways link social support to attenuated neuroendocrine stress responses

    PubMed Central

    Eisenberger, Naomi I.; Taylor, Shelley E.; Gable, Shelly L.; Hilmert, Clayton J.; Lieberman, Matthew D.

    2009-01-01

    It is well established that a lack of social support constitutes a major risk factor for morbidity and mortality, comparable to risk factors such as smoking, obesity, and high blood pressure. Although it has been hypothesized that social support may benefit health by reducing physiological reactivity to stressors, the mechanisms underlying this process remain unclear. Moreover, to date, no studies have investigated the neurocognitive mechanisms that translate experiences of social support into the health outcomes that follow. To investigate these processes, thirty participants completed three tasks in which daily social support, neurocognitive reactivity to a social stressor, and neuroendocrine responses to a social stressor were assessed. Individuals who interacted regularly with supportive individuals across a ten-day period showed diminished cortisol reactivity to a social stressor. Moreover, greater social support and diminished cortisol responses were associated with diminished activity in the dorsal anterior cingulate cortex (dACC) and Brodmann's area (BA) 8, regions previously associated with the distress of social separation. Lastly, individual differences in dACC and BA 8 reactivity mediated the relationship between high daily social support and low cortisol reactivity, such that supported individuals showed reduced neurocognitive reactivity to social stressors, which in turn was associated with reduced neuroendocrine stress responses. This study is the first to investigate the neural underpinnings of the social support-health relationship and provides evidence that social support may ultimately benefit health by diminishing neural and physiological reactivity to social stressors. PMID:17395493

  6. Pain tolerance predicts human social network size

    PubMed Central

    Johnson, Katerina V.-A.; Dunbar, Robin I. M.

    2016-01-01

    Personal social network size exhibits considerable variation in the human population and is associated with both physical and mental health status. Much of this inter-individual variation in human sociality remains unexplained from a biological perspective. According to the brain opioid theory of social attachment, binding of the neuropeptide β-endorphin to μ-opioid receptors in the central nervous system (CNS) is a key neurochemical mechanism involved in social bonding, particularly amongst primates. We hypothesise that a positive association exists between activity of the μ-opioid system and the number of social relationships that an individual maintains. Given the powerful analgesic properties of β-endorphin, we tested this hypothesis using pain tolerance as an assay for activation of the endogenous μ-opioid system. We show that a simple measure of pain tolerance correlates with social network size in humans. Our results are in line with previous studies suggesting that μ-opioid receptor signalling has been elaborated beyond its basic function of pain modulation to play an important role in managing our social encounters. The neuroplasticity of the μ-opioid system is of future research interest, especially with respect to psychiatric disorders associated with symptoms of social withdrawal and anhedonia, both of which are strongly modulated by endogenous opioids. PMID:27121297

  7. Epigenetics, linking social and environmental exposures to preterm birth

    PubMed Central

    Burris, Heather H; Baccarelli, Andrea A; Wright, Robert O; Wright, Rosalind J

    2015-01-01

    Preterm birth remains a leading cause of infant mortality and morbidity. Despite decades of research, marked racial and socioeconomic disparities in preterm birth persist. In the US, more than 16% of African American infants are born before 37 weeks of gestation compared to less than 11% of white infants. While income and education differences predict a portion of these racial disparities, income and education are proxies of the underlying causes rather than the true cause. How these differences lead to the pathophysiology remains unknown. Beyond tobacco smoke exposure, most preterm birth investigators overlook environment exposures that often correlate with poverty. Environmental exposures to industrial contaminants track along both socioeconomic and racial/ethnic lines due to cultural variation in personal product use, diet and residential geographical separation. Emerging evidence suggests that environmental exposure to metals and plasticizers contribute to preterm birth and epigenetic modifications. The extent to which disparities in preterm birth result from interactions between the social and physical environments that produce epigenetic modifications remains unclear. In this review, we highlight studies that report associations between environmental exposures and preterm birth as well as perinatal epigenetic sensitivity to environmental contaminants and socioeconomic stressors. PMID:26460521

  8. Mechanisms linking the social environment to health in African Americans

    USDA-ARS?s Scientific Manuscript database

    The social environment may influence health directly or indirectly through psychosocial factors, such as perceived stress, depressive symptoms and discrimination. This study explored potential psychosocial mediators of the associations between the social environment and physical and mental health in...

  9. Antiretroviral Drug Diversion Links Social Vulnerability to Poor Medication Adherence in Substance Abusing Populations

    PubMed Central

    Tsuyuki, Kiyomi; Surratt, Hilary L.

    2015-01-01

    Antiretroviral (ARV) medication diversion to the illicit market has been documented in South Florida, and linked to sub-optimal adherence in people living with HIV. ARV diversion reflects an unmet need for care in vulnerable populations that have difficulty engaging in consistent HIV care due to competing needs and co-morbidities. This study applies the Gelberg-Andersen Behavioral Model of Health Care Utilization for Vulnerable Populations to understand how social vulnerability is linked to ARV diversion and adherence. Cross-sectional data were collected from a targeted sample of vulnerable people living with HIV in South Florida between 2010 and 2012 (n=503). Structured interviews collected quantitative data on ARV diversion, access and utilization of care, and ARV adherence. Logistic regression was used to estimate the goodness-of-fit of additive models that test domain fit. Linear regression was used to estimate the effects of social vulnerability and ARV diversion on ARV adherence. The best fitting model to predict ARV diversion identifies having a low monthly income and unstable HIV care as salient enabling factors that promote ARV diversion. Importantly, health care need factors did not protect against ARV diversion, evidence that immediate competing needs are prioritized even in the face of poor health for this sample. We also find that ARV diversion provides a link between social vulnerability and sub-optimal ARV adherence, with ARV diversion and domains from the Behavioral Model explaining 25% of the variation in ARV adherence. Our analyses reveal great need to improve engagement in HIV care for vulnerable populations by strengthening enabling factors (e.g. patient-provider relationship) to improve retention in HIV care and ARV adherence for vulnerable populations. PMID:25893656

  10. Antiretroviral drug diversion links social vulnerability to poor medication adherence in substance abusing populations.

    PubMed

    Tsuyuki, Kiyomi; Surratt, Hilary L

    2015-05-01

    Antiretroviral (ARV) medication diversion to the illicit market has been documented in South Florida, and linked to sub-optimal adherence in people living with HIV. ARV diversion reflects an unmet need for care in vulnerable populations that have difficulty engaging in consistent HIV care due to competing needs and co-morbidities. This study applies the Gelberg-Andersen behavioral model of health care utilization for vulnerable populations to understand how social vulnerability is linked to ARV diversion and adherence. Cross-sectional data were collected from a targeted sample of vulnerable people living with HIV in South Florida between 2010 and 2012 (n = 503). Structured interviews collected quantitative data on ARV diversion, access and utilization of care, and ARV adherence. Logistic regression was used to estimate the goodness-of-fit of additive models that test domain fit. Linear regression was used to estimate the effects of social vulnerability and ARV diversion on ARV adherence. The best fitting model to predict ARV diversion identifies having a low monthly income and unstable HIV care as salient enabling factors that promote ARV diversion. Importantly, health care need factors did not protect against ARV diversion, evidence that immediate competing needs are prioritized even in the face of poor health for this sample. We also find that ARV diversion provides a link between social vulnerability and sub-optimal ARV adherence, with ARV diversion and domains from the Behavioral Model explaining 25 % of the variation in ARV adherence. Our analyses reveal great need to improve engagement in HIV care for vulnerable populations by strengthening enabling factors (e.g. patient-provider relationship) to improve retention in HIV care and ARV adherence for vulnerable populations.

  11. Developmental stress predicts social network position

    PubMed Central

    Boogert, Neeltje J.; Farine, Damien R.; Spencer, Karen A.

    2014-01-01

    The quantity and quality of social relationships, as captured by social network analysis, can have major fitness consequences. Various studies have shown that individual differences in social behaviour can be due to variation in exposure to developmental stress. However, whether these developmental differences translate to consistent differences in social network position is not known. We experimentally increased levels of the avian stress hormone corticosterone (CORT) in nestling zebra finches in a fully balanced design. Upon reaching nutritional independence, we released chicks and their families into two free-flying rooms, where we measured daily social networks over five weeks using passive integrated transponder tags. Developmental stress had a significant effect on social behaviour: despite having similar foraging patterns, CORT chicks had weaker associations to their parents than control chicks. Instead, CORT chicks foraged with a greater number of flock mates and were less choosy with whom they foraged, resulting in more central network positions. These findings highlight the importance of taking developmental history into account to understand the drivers of social organization in gregarious species. PMID:25354917

  12. Developmental stress predicts social network position.

    PubMed

    Boogert, Neeltje J; Farine, Damien R; Spencer, Karen A

    2014-10-01

    The quantity and quality of social relationships, as captured by social network analysis, can have major fitness consequences. Various studies have shown that individual differences in social behaviour can be due to variation in exposure to developmental stress. However, whether these developmental differences translate to consistent differences in social network position is not known. We experimentally increased levels of the avian stress hormone corticosterone (CORT) in nestling zebra finches in a fully balanced design. Upon reaching nutritional independence, we released chicks and their families into two free-flying rooms, where we measured daily social networks over five weeks using passive integrated transponder tags. Developmental stress had a significant effect on social behaviour: despite having similar foraging patterns, CORT chicks had weaker associations to their parents than control chicks. Instead, CORT chicks foraged with a greater number of flock mates and were less choosy with whom they foraged, resulting in more central network positions. These findings highlight the importance of taking developmental history into account to understand the drivers of social organization in gregarious species.

  13. Rescripting Early Memories Linked to Negative Images in Social Phobia: A Pilot Study

    ERIC Educational Resources Information Center

    Wild, Jennifer; Hackmann, Ann; Clark, David M.

    2008-01-01

    Negative self-images are a maintaining factor in social phobia. A retrospective study (Hackmann, A., Clark, D.M., McManus, F. (2000). Recurrent images and early memories in social phobia. Behaviour Research and Therapy, 38, 601-610) suggested that the images may be linked to early memories of unpleasant social experiences. This preliminary study…

  14. Rescripting Early Memories Linked to Negative Images in Social Phobia: A Pilot Study

    ERIC Educational Resources Information Center

    Wild, Jennifer; Hackmann, Ann; Clark, David M.

    2008-01-01

    Negative self-images are a maintaining factor in social phobia. A retrospective study (Hackmann, A., Clark, D.M., McManus, F. (2000). Recurrent images and early memories in social phobia. Behaviour Research and Therapy, 38, 601-610) suggested that the images may be linked to early memories of unpleasant social experiences. This preliminary study…

  15. Understanding the links between ecosystem health and social system well-being: an annotated bibliography.

    Treesearch

    Dawn M. Elmer; Harriet H. Christensen; Ellen M. Donoghue; [Compilers].

    2002-01-01

    This bibliography focuses on the links between social system well-being and ecosystem health. It is intended for public land managers and scientists and students of social and natural sciences. Multidisciplinary science that addresses the interconnections between the social system and the ecosystem is presented. Some of the themes and strategies presented are policy...

  16. Linking social complexity and vocal complexity: a parid perspective

    PubMed Central

    Krams, Indrikis; Krama, Tatjana; Freeberg, Todd M.; Kullberg, Cecilia; Lucas, Jeffrey R.

    2012-01-01

    The Paridae family (chickadees, tits and titmice) is an interesting avian group in that species vary in important aspects of their social structure and many species have large and complex vocal repertoires. For this reason, parids represent an important set of species for testing the social complexity hypothesis for vocal communication—the notion that as groups increase in social complexity, there is a need for increased vocal complexity. Here, we describe the hypothesis and some of the early evidence that supported the hypothesis. Next, we review literature on social complexity and on vocal complexity in parids, and describe some of the studies that have made explicit tests of the social complexity hypothesis in one parid—Carolina chickadees, Poecile carolinensis. We conclude with a discussion, primarily from a parid perspective, of the benefits and costs of grouping and of physiological factors that might mediate the relationship between social complexity and changes in signalling behaviour. PMID:22641826

  17. Linking social complexity and vocal complexity: a parid perspective.

    PubMed

    Krams, Indrikis; Krama, Tatjana; Freeberg, Todd M; Kullberg, Cecilia; Lucas, Jeffrey R

    2012-07-05

    The Paridae family (chickadees, tits and titmice) is an interesting avian group in that species vary in important aspects of their social structure and many species have large and complex vocal repertoires. For this reason, parids represent an important set of species for testing the social complexity hypothesis for vocal communication--the notion that as groups increase in social complexity, there is a need for increased vocal complexity. Here, we describe the hypothesis and some of the early evidence that supported the hypothesis. Next, we review literature on social complexity and on vocal complexity in parids, and describe some of the studies that have made explicit tests of the social complexity hypothesis in one parid--Carolina chickadees, Poecile carolinensis. We conclude with a discussion, primarily from a parid perspective, of the benefits and costs of grouping and of physiological factors that might mediate the relationship between social complexity and changes in signalling behaviour.

  18. Measurements and predictions of multipath dispersion for troposcatter links

    NASA Astrophysics Data System (ADS)

    Larsen, R.

    1984-10-01

    Multipath dispersion measurements made on several 4.5 GHz paths in the United Kingdom are presented. Beamwidth and scatter angle dependence and several features of dispersion in angle and space diversity are discussed. These measurements and other from the literature are compared with predictions of dispersion. The predictions considerably underestimated the measured dispersion, but the inclusion of a beam broadening factor in the calculations gave a significant improvement in accuracy.

  19. Personality and prosocial behavior: linking basic traits and social value orientations.

    PubMed

    Hilbig, Benjamin E; Glöckner, Andreas; Zettler, Ingo

    2014-09-01

    Concerning the dispositional determinants of prosocial behavior and cooperation, work based on the classic 5 personality factors, and especially Agreeableness, has turned out somewhat inconsistent. A clearer picture has emerged from consideration of the HEXACO model of personality--though supported entirely by hypothetical behavior as criterion, so far. Thus, in 2 studies and a reanalysis, we investigated "actual behavior" in the form of individually and socially consequential distribution decisions. As expected, HEXACO Honesty-Humility consistently predicted prosocial behavior, including a theory-consistent pattern on the facet level. Importantly, this pattern might explain why five-factor Agreeableness has only sometimes been found to account for prosocial behavior. Indeed, further results indicate that five-factor Agreeableness comprises some aspects that are predictive of prosocial behavior--aspects well covered by HEXACO Honesty-Humility--but also others that play no role for this criterion. As such, the links between five-factor Agreeableness and prosocial behavior are well-covered by HEXACO Honesty-Humility, but not vice versa. Taken together, these findings hint that especially HEXACO Honesty-Humility (and certain aspects of five-factor Agreeableness) account for prosocial behavior--thus explaining previous inconsistencies and providing a more nuanced understanding of the links between basic personality and prosocial or cooperative behavior. 2014 APA, all rights reserved

  20. Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs

    SciTech Connect

    Zhang, Baichuan; Choudhury, Sutanay; Al-Hasan, Mohammad; Ning, Xia; Agarwal, Khushbu; Purohit, Sumit; Pesantez, Paola

    2016-02-01

    Estimating the confidence for a link is a critical task for Knowledge Graph construction. Link prediction, or predicting the likelihood of a link in a knowledge graph based on prior state is a key research direction within this area. We propose a Latent Feature Embedding based link recommendation model for prediction task and utilize Bayesian Personalized Ranking based optimization technique for learning models for each predicate. Experimental results on large-scale knowledge bases such as YAGO2 show that our approach achieves substantially higher performance than several state-of-art approaches. Furthermore, we also study the performance of the link prediction algorithm in terms of topological properties of the Knowledge Graph and present a linear regression model to reason about its expected level of accuracy.

  1. Predicting Positive and Negative Relationships in Large Social Networks.

    PubMed

    Wang, Guan-Nan; Gao, Hui; Chen, Lian; Mensah, Dennis N A; Fu, Yan

    2015-01-01

    In a social network, users hold and express positive and negative attitudes (e.g. support/opposition) towards other users. Those attitudes exhibit some kind of binary relationships among the users, which play an important role in social network analysis. However, some of those binary relationships are likely to be latent as the scale of social network increases. The essence of predicting latent binary relationships have recently began to draw researchers' attention. In this paper, we propose a machine learning algorithm for predicting positive and negative relationships in social networks inspired by structural balance theory and social status theory. More specifically, we show that when two users in the network have fewer common neighbors, the prediction accuracy of the relationship between them deteriorates. Accordingly, in the training phase, we propose a segment-based training framework to divide the training data into two subsets according to the number of common neighbors between users, and build a prediction model for each subset based on support vector machine (SVM). Moreover, to deal with large-scale social network data, we employ a sampling strategy that selects small amount of training data while maintaining high accuracy of prediction. We compare our algorithm with traditional algorithms and adaptive boosting of them. Experimental results of typical data sets show that our algorithm can deal with large social networks and consistently outperforms other methods.

  2. Predicting Positive and Negative Relationships in Large Social Networks

    PubMed Central

    Wang, Guan-Nan; Gao, Hui; Chen, Lian; Mensah, Dennis N. A.; Fu, Yan

    2015-01-01

    In a social network, users hold and express positive and negative attitudes (e.g. support/opposition) towards other users. Those attitudes exhibit some kind of binary relationships among the users, which play an important role in social network analysis. However, some of those binary relationships are likely to be latent as the scale of social network increases. The essence of predicting latent binary relationships have recently began to draw researchers' attention. In this paper, we propose a machine learning algorithm for predicting positive and negative relationships in social networks inspired by structural balance theory and social status theory. More specifically, we show that when two users in the network have fewer common neighbors, the prediction accuracy of the relationship between them deteriorates. Accordingly, in the training phase, we propose a segment-based training framework to divide the training data into two subsets according to the number of common neighbors between users, and build a prediction model for each subset based on support vector machine (SVM). Moreover, to deal with large-scale social network data, we employ a sampling strategy that selects small amount of training data while maintaining high accuracy of prediction. We compare our algorithm with traditional algorithms and adaptive boosting of them. Experimental results of typical data sets show that our algorithm can deal with large social networks and consistently outperforms other methods. PMID:26075404

  3. Civic Ecology: Linking Social and Ecological Approaches in Extension

    ERIC Educational Resources Information Center

    Krasny, Marianne E.; Tidball, Keith G.

    2010-01-01

    Civic ecology refers to the philosophy and science of community forestry, community gardening, watershed enhancement, and other volunteer-driven restoration practices in cities and elsewhere. Such practices, although often viewed as initiatives to improve a degraded environment, also foster social attributes of resilient social-ecological systems,…

  4. Linking Children's Literature with Social Studies in the Elementary Curriculum

    ERIC Educational Resources Information Center

    Almerico, Gina M.

    2013-01-01

    The author shares information related to integrating quality literature written for children into the teaching of social studies at the elementary school level. Research within the past decade informs educators of the strong impact of curriculum standards for the social studies as developed by professional organizations. Teachers today are…

  5. A Direct Link between Gaze Perception and Social Attention

    ERIC Educational Resources Information Center

    Bayliss, Andrew P.; Bartlett, Jessica; Naughtin, Claire K.; Kritikos, Ada

    2011-01-01

    How information is exchanged between the cognitive mechanisms responsible for gaze perception and social attention is unclear. These systems could be independent; the "gaze cueing" effect could emerge from the activation of a general-purpose attentional mechanism that is ignorant of the social nature of the gaze cue. Alternatively, orienting to…

  6. Civic Ecology: Linking Social and Ecological Approaches in Extension

    ERIC Educational Resources Information Center

    Krasny, Marianne E.; Tidball, Keith G.

    2010-01-01

    Civic ecology refers to the philosophy and science of community forestry, community gardening, watershed enhancement, and other volunteer-driven restoration practices in cities and elsewhere. Such practices, although often viewed as initiatives to improve a degraded environment, also foster social attributes of resilient social-ecological systems,…

  7. Universal-Diverse Orientation: Linking Social Attitudes with Wellness

    ERIC Educational Resources Information Center

    Miville, Marie L.; Romans, John S. C.; Johnson, Daniel; Lone, Robert

    2004-01-01

    The current study focused on examining the relationships of positive social attitudes with aspects of well-functioning. "Universal-diverse orientation" (UDO), a social attitude characterized by awareness and acceptance of both the similarities and differences among people, was measured with the Miville-Guzman Universality-Diversity…

  8. Language, Minority Education and Gender: Linking Social Justice and Power.

    ERIC Educational Resources Information Center

    Corson, David

    Injustices in language policy and practice in education are examined, focusing on three groups that appear to be most affected by unfair language policies in education; women and girls; minority social groups; and minority cultural groups, distinguished from minority social groups in that the former usually possess or identify with a language that…

  9. Social Anxiety Predicts Aggression in Children with ASD: Clinical Comparisons with Socially Anxious and Oppositional Youth

    ERIC Educational Resources Information Center

    Pugliese, Cara E.; White, Bradley A.; White, Susan W.; Ollendick, Thomas H.

    2013-01-01

    The present study examined the degree to which social anxiety predicts aggression in children with high functioning autism spectrum disorders (HFASD, n = 20) compared to children with Social Anxiety Disorder (SAD, n = 20) or with Oppositional Defiant Disorder or Conduct Disorder (ODD/CD, n = 20). As predicted, children with HFASD reported levels…

  10. Social Anxiety Predicts Aggression in Children with ASD: Clinical Comparisons with Socially Anxious and Oppositional Youth

    ERIC Educational Resources Information Center

    Pugliese, Cara E.; White, Bradley A.; White, Susan W.; Ollendick, Thomas H.

    2013-01-01

    The present study examined the degree to which social anxiety predicts aggression in children with high functioning autism spectrum disorders (HFASD, n = 20) compared to children with Social Anxiety Disorder (SAD, n = 20) or with Oppositional Defiant Disorder or Conduct Disorder (ODD/CD, n = 20). As predicted, children with HFASD reported levels…

  11. Predicting Drop-Out from Social Behaviour of Students

    ERIC Educational Resources Information Center

    Bayer, Jaroslav; Bydzovska, Hana; Geryk, Jan; Obsivac, Tomas; Popelinsky, Lubomir

    2012-01-01

    This paper focuses on predicting drop-outs and school failures when student data has been enriched with data derived from students social behaviour. These data describe social dependencies gathered from e-mail and discussion board conversations, among other sources. We describe an extraction of new features from both student data and behaviour…

  12. Which Social Skills Predict Academic Performance of Elementary School Students

    ERIC Educational Resources Information Center

    Sung, Youngji Y.; Chang, Mido

    2010-01-01

    The study explored various aspects of students' social skills in an attempt to identify specific aspect that has significance in predicting their academic performance and examined the longitudinal relationship of these social skills with academic performance. The study used two models that applied advanced statistical tools to a nationally…

  13. Links between emotion perception and social participation restriction following stroke.

    PubMed

    Cooper, Clare L; Phillips, Louise H; Johnston, Marie; Radlak, Bogumila; Hamilton, Steven; McLeod, Mary Joan

    2014-01-01

    Stroke can cause impairment in emotion perception, but the social consequences of these problems have not been explored to date. In a group of patients with stroke, this study investigated whether difficulties in emotion perception related to social participation and quality-of-life. It also assessed whether these relationships remained significant when controlling for activity limitations. Individuals 1 year post-stroke (n = 28) and control participants (n = 40) were assessed on emotion perception across different modalities. Activity limitations, social participation, and multiple domains of quality-of-life were assessed in patients. Participants with stroke were impaired on emotion perception compared to controls. Emotion perception problems in stroke were significantly correlated with social participation and psychological aspects of QoL, but not with activity limitations. The strong relationships of emotion perception with social participation and psychological aspects of QoL following stroke may have implications for post-stroke outcomes.

  14. A class-based link prediction using Distance Dependent Chinese Restaurant Process

    NASA Astrophysics Data System (ADS)

    Andalib, Azam; Babamir, Seyed Morteza

    2016-08-01

    One of the important tasks in relational data analysis is link prediction which has been successfully applied on many applications such as bioinformatics, information retrieval, etc. The link prediction is defined as predicting the existence or absence of edges between nodes of a network. In this paper, we propose a novel method for link prediction based on Distance Dependent Chinese Restaurant Process (DDCRP) model which enables us to utilize the information of the topological structure of the network such as shortest path and connectivity of the nodes. We also propose a new Gibbs sampling algorithm for computing the posterior distribution of the hidden variables based on the training data. Experimental results on three real-world datasets show the superiority of the proposed method over other probabilistic models for link prediction problem.

  15. Social Complexity Predicts Transitive Reasoning in Prosimian Primates.

    PubMed

    Maclean, Evan L; Merritt, Dustin J; Brannon, Elizabeth M

    2008-08-01

    Transitive Inference is a form of deductive reasoning that has been suggested as one cognitive mechanism by which animals could learn the many relationships within their group's dominance hierarchy. This process thus bears relevance to the social intelligence hypothesis which posits evolutionary links between various forms of social and nonsocial cognition. Recent evidence corroborates the link between social complexity and transitive inference and indicates that highly social animals may show superior transitive reasoning even in nonsocial contexts. We examined the relationship between social complexity and transitive inference in two species of prosimians, a group of primates that diverged from the common ancestor of monkeys, apes, and humans over 50 million years ago. In Experiment 1, highly social ring-tailed lemurs, Lemur catta, outperformed the less social mongoose lemurs, Eulemur mongoz, in tests of transitive inference and showed more robust representations of the underlying ordinal relationships between the stimuli. In Experiment 2, after training under a correction procedure that emphasized the underlying linear dimension of the series, both species showed similar transitive inference. This finding suggests that the two lemur species differ not in their fundamental ability to make transitive inferences, but rather in their predisposition to mentally organize information along a common underlying dimension. Together, these results support the hypothesis that social complexity is an important selective pressure for the evolution of cognitive abilities relevant to transitive reasoning.

  16. Social networks predict gut microbiome composition in wild baboons.

    PubMed

    Tung, Jenny; Barreiro, Luis B; Burns, Michael B; Grenier, Jean-Christophe; Lynch, Josh; Grieneisen, Laura E; Altmann, Jeanne; Alberts, Susan C; Blekhman, Ran; Archie, Elizabeth A

    2015-03-16

    Social relationships have profound effects on health in humans and other primates, but the mechanisms that explain this relationship are not well understood. Using shotgun metagenomic data from wild baboons, we found that social group membership and social network relationships predicted both the taxonomic structure of the gut microbiome and the structure of genes encoded by gut microbial species. Rates of interaction directly explained variation in the gut microbiome, even after controlling for diet, kinship, and shared environments. They therefore strongly implicate direct physical contact among social partners in the transmission of gut microbial species. We identified 51 socially structured taxa, which were significantly enriched for anaerobic and non-spore-forming lifestyles. Our results argue that social interactions are an important determinant of gut microbiome composition in natural animal populations-a relationship with important ramifications for understanding how social relationships influence health, as well as the evolution of group living.

  17. Adoption: biological and social processes linked to adaptation.

    PubMed

    Grotevant, Harold D; McDermott, Jennifer M

    2014-01-01

    Children join adoptive families through domestic adoption from the public child welfare system, infant adoption through private agencies, and international adoption. Each pathway presents distinctive developmental opportunities and challenges. Adopted children are at higher risk than the general population for problems with adaptation, especially externalizing, internalizing, and attention problems. This review moves beyond the field's emphasis on adoptee-nonadoptee differences to highlight biological and social processes that affect adaptation of adoptees across time. The experience of stress, whether prenatal, postnatal/preadoption, or during the adoption transition, can have significant impacts on the developing neuroendocrine system. These effects can contribute to problems with physical growth, brain development, and sleep, activating cascading effects on social, emotional, and cognitive development. Family processes involving contact between adoptive and birth family members, co-parenting in gay and lesbian adoptive families, and racial socialization in transracially adoptive families affect social development of adopted children into adulthood.

  18. Translating upwards: linking the neural and social sciences via neuroeconomics.

    PubMed

    Levallois, Clement; Clithero, John A; Wouters, Paul; Smidts, Ale; Huettel, Scott A

    2012-11-01

    The social and neural sciences share a common interest in understanding the mechanisms that underlie human behaviour. However, interactions between neuroscience and social science disciplines remain strikingly narrow and tenuous. We illustrate the scope and challenges for such interactions using the paradigmatic example of neuroeconomics. Using quantitative analyses of both its scientific literature and the social networks in its intellectual community, we show that neuroeconomics now reflects a true disciplinary integration, such that research topics and scientific communities with interdisciplinary span exert greater influence on the field. However, our analyses also reveal key structural and intellectual challenges in balancing the goals of neuroscience with those of the social sciences. To address these challenges, we offer a set of prescriptive recommendations for directing future research in neuroeconomics.

  19. A perturbation-based framework for link prediction via non-negative matrix factorization

    NASA Astrophysics Data System (ADS)

    Wang, Wenjun; Cai, Fei; Jiao, Pengfei; Pan, Lin

    2016-12-01

    Many link prediction methods have been developed to infer unobserved links or predict latent links based on the observed network structure. However, due to network noises and irregular links in real network, the performances of existed methods are usually limited. Considering random noises and irregular links, we propose a perturbation-based framework based on Non-negative Matrix Factorization to predict missing links. We first automatically determine the suitable number of latent features, which is inner rank in NMF, by Colibri method. Then, we perturb training set of a network by perturbation sets many times and get a series of perturbed networks. Finally, the common basis matrix and coefficients matrix of these perturbed networks are obtained via NMF and form similarity matrix of the network for link prediction. Experimental results on fifteen real networks show that the proposed framework has competitive performances compared with state-of-the-art link prediction methods. Correlations between the performances of different methods and the statistics of networks show that those methods with good precisions have similar consistence.

  20. A perturbation-based framework for link prediction via non-negative matrix factorization

    PubMed Central

    Wang, Wenjun; Cai, Fei; Jiao, Pengfei; Pan, Lin

    2016-01-01

    Many link prediction methods have been developed to infer unobserved links or predict latent links based on the observed network structure. However, due to network noises and irregular links in real network, the performances of existed methods are usually limited. Considering random noises and irregular links, we propose a perturbation-based framework based on Non-negative Matrix Factorization to predict missing links. We first automatically determine the suitable number of latent features, which is inner rank in NMF, by Colibri method. Then, we perturb training set of a network by perturbation sets many times and get a series of perturbed networks. Finally, the common basis matrix and coefficients matrix of these perturbed networks are obtained via NMF and form similarity matrix of the network for link prediction. Experimental results on fifteen real networks show that the proposed framework has competitive performances compared with state-of-the-art link prediction methods. Correlations between the performances of different methods and the statistics of networks show that those methods with good precisions have similar consistence. PMID:27976672

  1. Teacher's sleep quality: linked to social job characteristics?

    PubMed

    Kottwitz, Maria U; Gerhardt, Christin; Pereira, Diana; Iseli, Lionel; Elfering, Achim

    2017-08-11

    Besides dealing with high workload, being a teacher is challenging with respect to the social context. There is increasing evidence that adverse social job characteristics challenge sleep quality. The current study tests whether restraint sleep quality (defined as worse sleep quality before than during vacation) is related to time-related job stressors, job resources, and social job characteristics.Forty-eight elementary school teachers (42% female) participated both during the last week before and the first week after vacation. Before vacation, teachers were asked for demographics and working conditions with reference to the last 30 days, and sleep quality with reference to the last 7 days. After vacation sleep quality during vacation was assessed and used as reference for working time sleep quality.Results showed mean levels of sleep quality increased during vacation. In teachers with restrained working time sleep quality (38%), experiences of failure at work, social exclusion, and emotional dissonance were more frequent than in teachers with unrestrained working time sleep quality (Ps < .05). Groups did not differ in time-related stressors, time control and social support from supervisors.Emotion work, social exclusion and individual experience of failure seem to challenge sleep quality in teachers.

  2. The evolution of social interactions changes predictions about interacting phenotypes.

    PubMed

    Kazancıoğlu, Erem; Klug, Hope; Alonzo, Suzanne H

    2012-07-01

    In many traits involved in social interactions, such as courtship and aggression, the phenotype is an outcome of interactions between individuals. Such traits whose expression in an individual is partly determined by the phenotype of its social partner are called "interacting phenotypes." Quantitative genetic models suggested that interacting phenotypes can evolve much faster than nonsocial traits. Current models, however, consider the interaction between phenotypes of social partners as a fixed phenotypic response rule, represented by an interaction coefficient (ψ). Here, we extend existing theoretical models and incorporate the interaction coefficient as a trait that can evolve. We find that the evolution of the interaction coefficient can change qualitatively the predictions about the rate and direction of evolution of interacting phenotypes. We argue that it is crucial to determine whether and how the phenotypic response of an individual to its social partner can evolve to make accurate predictions about the evolution of traits involved in social interactions. © 2012 The Author(s).

  3. Neuronal activity in primate dorsal anterior cingulate cortex signals task conflict and predicts adjustments in pupil-linked arousal.

    PubMed

    Ebitz, R Becket; Platt, Michael L

    2015-02-04

    Whether driving a car, shopping for food, or paying attention in a classroom of boisterous teenagers, it's often hard to maintain focus on goals in the face of distraction. Brain imaging studies in humans implicate the dorsal anterior cingulate cortex (dACC) in regulating the conflict between goals and distractors. Here we show that single dACC neurons signal conflict between task goals and distractors in the rhesus macaque, particularly for biologically relevant social stimuli. For some neurons, task conflict signals predicted subsequent changes in pupil size-a peripheral index of arousal linked to noradrenergic tone-associated with reduced distractor interference. dACC neurons also responded to errors, and these signals predicted adjustments in pupil size. These findings provide the first neurophysiological endorsement of the hypothesis that dACC regulates conflict, in part, via modulation of pupil-linked processes such as arousal. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. Neuronal activity in primate dorsal anterior cingulate cortex signals task conflict and predicts adjustments in pupil-linked arousal

    PubMed Central

    Ebitz, R. Becket; Platt, Michael L.

    2014-01-01

    Summary Whether driving a car, shopping for food, or paying attention in a classroom of boisterous teenagers, it’s often hard to maintain focus on goals in the face of distraction. Brain imaging studies in humans implicate the dorsal anterior cingulate cortex (dACC) in regulating the conflict between goals and distractors. Here we show for the first time that single dACC neurons signal conflict between task goals and distractors in the rhesus macaque, particularly for biologically-relevant social stimuli. For some neurons, task conflict signals predicted subsequent changes in pupil size—a peripheral index of arousal linked to noradrenergic tone—associated with reduced distractor interference. dACC neurons also responded to errors and these signals predicted adjustments in pupil size. These findings provide the first neurophysiological endorsement of the hypothesis that dACC regulates conflict, in part, via modulation of pupil-linked processes such as arousal. PMID:25654259

  5. The role of attitudes toward White privilege and religious beliefs in predicting social justice interest and commitment.

    PubMed

    Todd, Nathan R; McConnell, Elizabeth A; Suffrin, Rachael L

    2014-03-01

    The current study examines links among attitudes toward White privilege, religious beliefs, and social justice interest and commitment for White Christian students. Two distinct patterns of results emerged from a path analysis of 500 White Christian students. First, a willingness to confront White privilege was positively associated with the sanctification of social justice (i.e., attributing spiritual significance to working for social justice) and both were positively associated with social justice interest and commitment. Second, awareness of White privilege was negatively associated with religious conservatism, and religious conservatism was negatively associated with social justice interest. These patterns show that White privilege attitudes directly (i.e., willingness to confront White privilege) and indirectly (i.e., awareness of White privilege through religious conservatism) predicted social justice interest and commitment. Moreover, religious beliefs demonstrated opposite patterns of association with social justice interest and commitment such that the sanctification of social justice positively predicted social justice interest and commitment whereas religious conservatism negatively predicted social justice interest. Overall, findings demonstrate direct and indirect links between White privilege attitudes, religious beliefs, and social justice interest and commitment. Limitations and implications for future community psychology research and collaboration also are discussed.

  6. Predicting national suicide numbers with social media data.

    PubMed

    Won, Hong-Hee; Myung, Woojae; Song, Gil-Young; Lee, Won-Hee; Kim, Jong-Won; Carroll, Bernard J; Kim, Doh Kwan

    2013-01-01

    Suicide is not only an individual phenomenon, but it is also influenced by social and environmental factors. With the high suicide rate and the abundance of social media data in South Korea, we have studied the potential of this new medium for predicting completed suicide at the population level. We tested two social media variables (suicide-related and dysphoria-related weblog entries) along with classical social, economic and meteorological variables as predictors of suicide over 3 years (2008 through 2010). Both social media variables were powerfully associated with suicide frequency. The suicide variable displayed high variability and was reactive to celebrity suicide events, while the dysphoria variable showed longer secular trends, with lower variability. We interpret these as reflections of social affect and social mood, respectively. In the final multivariate model, the two social media variables, especially the dysphoria variable, displaced two classical economic predictors - consumer price index and unemployment rate. The prediction model developed with the 2-year training data set (2008 through 2009) was validated in the data for 2010 and was robust in a sensitivity analysis controlling for celebrity suicide effects. These results indicate that social media data may be of value in national suicide forecasting and prevention.

  7. Predicting National Suicide Numbers with Social Media Data

    PubMed Central

    Won, Hong-Hee; Song, Gil-Young; Lee, Won-Hee; Kim, Jong-Won; Carroll, Bernard J.

    2013-01-01

    Suicide is not only an individual phenomenon, but it is also influenced by social and environmental factors. With the high suicide rate and the abundance of social media data in South Korea, we have studied the potential of this new medium for predicting completed suicide at the population level. We tested two social media variables (suicide-related and dysphoria-related weblog entries) along with classical social, economic and meteorological variables as predictors of suicide over 3 years (2008 through 2010). Both social media variables were powerfully associated with suicide frequency. The suicide variable displayed high variability and was reactive to celebrity suicide events, while the dysphoria variable showed longer secular trends, with lower variability. We interpret these as reflections of social affect and social mood, respectively. In the final multivariate model, the two social media variables, especially the dysphoria variable, displaced two classical economic predictors – consumer price index and unemployment rate. The prediction model developed with the 2-year training data set (2008 through 2009) was validated in the data for 2010 and was robust in a sensitivity analysis controlling for celebrity suicide effects. These results indicate that social media data may be of value in national suicide forecasting and prevention. PMID:23630615

  8. Predictive Non-Equilibrium Social Science

    DTIC Science & Technology

    2012-12-01

    structural balance theory ( SBT ) may be useful for edge-sign prediction. Briefly, SBT posits that if w∈V forms a triad with edge (u,v), then the sign of (u...my friend is my friend”, “the friend of my enemy is my enemy”, and so on (Heider 1946). Thus SBT suggests that knowledge of the signs of the edges...directly motivated by SBT . For example, if (u,v) belongs to many triads with one positive and one negative edge, it may be likely that the sign of (u

  9. Pretend and Physical Play: Links to Preschoolers' Affective Social Competence

    ERIC Educational Resources Information Center

    Lindsey, Eric W.; Colwell, Malinda J.

    2013-01-01

    This study investigated different forms of pretend and physical play as predictors of preschool children's "affective social competence" (ASC). Data were collected from 122 preschool children (57 boys, 65 girls; 86 European American, 9 African American, 17 Hispanic, and 10 other ethnicity) over a 2-year period. Children participated in…

  10. Linking ecological and social scales for natural resource management

    Treesearch

    Kristiina A. Vogt; Morgan Grove; Heidi Asjornsen; Keely B. Maxwell; Daniel J. Vogt; Ragnhildur Sigurdardottir; Bruce C. Larson; Leo Schibli; Michael Dove

    2002-01-01

    Natural resource management has moved from a single disciplinary and one resource management approach to an interdisciplinary and ecosystem-based approach. Many conceptual models are being developed to understand and implement ecosystem management and forest certification initiatives that require an integration of data from both the social and natural systems (Vogt...

  11. Social Goals, Aggression, Peer Preference, and Popularity: Longitudinal Links during Middle School

    ERIC Educational Resources Information Center

    Ojanen, Tiina; Findley-Van Nostrand, Danielle

    2014-01-01

    Social goals are associated with behaviors and adjustment among peers. However, it remains unclear whether goals predict adolescent social development. We examined prospective associations among goals, physical and relational aggression, social preference, and popularity during middle school (N = 384 participants, ages 12-14 years). Agentic…

  12. Social Goals, Aggression, Peer Preference, and Popularity: Longitudinal Links during Middle School

    ERIC Educational Resources Information Center

    Ojanen, Tiina; Findley-Van Nostrand, Danielle

    2014-01-01

    Social goals are associated with behaviors and adjustment among peers. However, it remains unclear whether goals predict adolescent social development. We examined prospective associations among goals, physical and relational aggression, social preference, and popularity during middle school (N = 384 participants, ages 12-14 years). Agentic…

  13. From the mouths of social media users: A focus group study exploring the social casino gaming–online gambling link

    PubMed Central

    Kim, Hyoun S.; Wohl, Michael J. A.; Gupta, Rina; Derevensky, Jeffrey

    2016-01-01

    Background and aims The potential link between social casino gaming and online gambling has raised considerable concerns among clinicians, researchers and policy makers. Unfortunately, however, there is a paucity of research examining this potential link, especially among young adults. This represents a significant gap given young adults are frequently exposed to and are players of social casino games. Methods To better understand the potential link between social casino games and online gambling, we conducted three focus groups (N = 30) at two large Canadian Universities with college students who were avid social media users (who are regularly exposed to social casino games). Results Many participants spontaneously mentioned that social casino games were a great opportunity to build gambling skills before playing for real money. Importantly, some participants expressed a belief that there is a direct progression from social casino gaming to online gambling. Conversely, others believed the transition to online gambling depended on a person’s personality, rather than mere exposure to social casino games. While many young adults in our focus groups felt immune to the effects of social casino games, there was a general consensus that social casino games may facilitate the transition to online gambling among younger teenagers (i.e., 12–14 yr olds), due to the ease of accessibility and early exposure. Discussion The results of the present research point to the need for more study on the effects of social casino gambling as well as a discussion concerning regulation of social casino games in order to minimize their potential risks. PMID:28092197

  14. From the mouths of social media users: A focus group study exploring the social casino gaming-online gambling link.

    PubMed

    Kim, Hyoun S; Wohl, Michael J A; Gupta, Rina; Derevensky, Jeffrey

    2016-03-01

    Background and aims The potential link between social casino gaming and online gambling has raised considerable concerns among clinicians, researchers and policy makers. Unfortunately, however, there is a paucity of research examining this potential link, especially among young adults. This represents a significant gap given young adults are frequently exposed to and are players of social casino games. Methods To better understand the potential link between social casino games and online gambling, we conducted three focus groups (N = 30) at two large Canadian Universities with college students who were avid social media users (who are regularly exposed to social casino games). Results Many participants spontaneously mentioned that social casino games were a great opportunity to build gambling skills before playing for real money. Importantly, some participants expressed a belief that there is a direct progression from social casino gaming to online gambling. Conversely, others believed the transition to online gambling depended on a person's personality, rather than mere exposure to social casino games. While many young adults in our focus groups felt immune to the effects of social casino games, there was a general consensus that social casino games may facilitate the transition to online gambling among younger teenagers (i.e., 12-14 yr olds), due to the ease of accessibility and early exposure. Discussion The results of the present research point to the need for more study on the effects of social casino gambling as well as a discussion concerning regulation of social casino games in order to minimize their potential risks.

  15. Socialization instances linked to cannabis experimentation among French teenagers.

    PubMed

    Jovic, Sonia; Genolini, Christophe; Delpierre, Cyrille; Spilka, Stanislas; Ehlinger, Virginie; Ross, Jim; Arnaud, Catherine; Godeau, Emmanuelle

    2014-11-01

    France presents one of the highest prevalence of teenagers aged 15-year-olds who report they already have experienced cannabis in Europe. Data from the French 2010 Health Behavior in School-aged Children (HSBC) survey and environmental parameters typifying schools' neighborhoods were used to study cannabis experimentation. We conducted a two-level logistic regression (clusters being schools) on 4,175 French 8th-10th graders from 156 schools. Several individual parameters were linked to cannabis experimentation. Living in a non-intact family, feeling insufficiently monitored, having poor communication with mother and being from a family with a high socio-economic status (SES) were all associated with increased risk of cannabis experimentation. At environmental level, only being in a priority education area was linked to this behavior, without explaining differences among schools.

  16. Hypoperfusion predicts lesion progression in cerebral X-linked adrenoleukodystrophy.

    PubMed

    Musolino, Patricia Leonor; Rapalino, Otto; Caruso, Paul; Caviness, Verne Strudwick; Eichler, Florian Sebald

    2012-09-01

    Magnetic resonance imaging sequences such as diffusion and spectroscopy have been well studied in X-linked adrenoleukodystrophy, but no data exist on magnetic resonance perfusion imaging. Since inflammation is known to modulate the microcirculation, we investigated the hypothesis that changes in the local perfusion might be one of the earliest signs of lesion development. Twenty patients with different phenotypes of adrenoleukodystrophy and seven age-matched controls were evaluated between 2006 and 2011. Fluid attenuated inversion recovery, post-contrast T(1)-weighted and normalized dynamic susceptibility contrast magnetic resonance perfusion cerebral blood volume maps were co-registered, segmented when cerebral lesion was present, and normalized cerebral blood volume values were analysed using a Food and Drug Association approved magnetic resonance perfusion software (NordicICE). Clinical and imaging data were reviewed to determine phenotype and status of progression. All eight patients with cerebral adrenoleukodystrophy had an average 80% decrease in normalized cerebral blood volume at the core of the lesion (P < 0.0001). Beyond the leading edge of contrast enhancement cerebral perfusion varied, patients with progressive lesions showed an average 60% decrease in normalized cerebral blood volume (adults P < 0.05; children P < 0.001), while one child with arrested progression normalized cerebral blood volume in this region. In six of seven patients with cerebral adrenoleukodystrophy lesions and follow-up imaging (2-24 month interval period), we found progression of contrast enhancement into the formerly hypoperfused perilesional zone. Asymptomatic, adrenomyeloneuropathy and female heterozygote patients had no significant changes in cerebral perfusion. Our data indicate that decreased brain magnetic resonance perfusion precedes leakage of the blood-brain barrier as demonstrated by contrast enhancement in cerebral adrenoleukodystrophy and is an early sign of lesion

  17. Hypoperfusion predicts lesion progression in cerebral X-linked adrenoleukodystrophy

    PubMed Central

    Musolino, Patricia Leonor; Rapalino, Otto; Caruso, Paul; Caviness, Verne Strudwick

    2012-01-01

    Magnetic resonance imaging sequences such as diffusion and spectroscopy have been well studied in X-linked adrenoleukodystrophy, but no data exist on magnetic resonance perfusion imaging. Since inflammation is known to modulate the microcirculation, we investigated the hypothesis that changes in the local perfusion might be one of the earliest signs of lesion development. Twenty patients with different phenotypes of adrenoleukodystrophy and seven age-matched controls were evaluated between 2006 and 2011. Fluid attenuated inversion recovery, post-contrast T1-weighted and normalized dynamic susceptibility contrast magnetic resonance perfusion cerebral blood volume maps were co-registered, segmented when cerebral lesion was present, and normalized cerebral blood volume values were analysed using a Food and Drug Association approved magnetic resonance perfusion software (NordicICE). Clinical and imaging data were reviewed to determine phenotype and status of progression. All eight patients with cerebral adrenoleukodystrophy had an average 80% decrease in normalized cerebral blood volume at the core of the lesion (P < 0.0001). Beyond the leading edge of contrast enhancement cerebral perfusion varied, patients with progressive lesions showed an average 60% decrease in normalized cerebral blood volume (adults P < 0.05; children P < 0.001), while one child with arrested progression normalized cerebral blood volume in this region. In six of seven patients with cerebral adrenoleukodystrophy lesions and follow-up imaging (2–24 month interval period), we found progression of contrast enhancement into the formerly hypoperfused perilesional zone. Asymptomatic, adrenomyeloneuropathy and female heterozygote patients had no significant changes in cerebral perfusion. Our data indicate that decreased brain magnetic resonance perfusion precedes leakage of the blood–brain barrier as demonstrated by contrast enhancement in cerebral adrenoleukodystrophy and is an early sign of lesion

  18. Genetic influences can protect against unresponsive parenting in the prediction of child social competence.

    PubMed

    Van Ryzin, Mark J; Leve, Leslie D; Neiderhiser, Jenae M; Shaw, Daniel S; Natsuaki, Misaki N; Reiss, David

    2015-01-01

    Although social competence in children has been linked to the quality of parenting, prior research has typically not accounted for genetic similarities between parents and children, or for interactions between environmental (i.e., parental) and genetic influences. In this article, the possibility of a Gene x Environment (G × E) interaction in the prediction of social competence in school-age children is evaluated. Using a longitudinal, multimethod data set from a sample of children adopted at birth (N = 361), a significant interaction was found between birth parent sociability and sensitive, responsive adoptive parenting when predicting child social competence at school entry (age 6), even when controlling for potential confounds. An analysis of the interaction revealed that genetic strengths can buffer the effects of unresponsive parenting.

  19. Genetic Influences Can Protect Against Unresponsive Parenting in the Prediction of Child Social Competence

    PubMed Central

    Van Ryzin, Mark J.; Leve, Leslie D.; Neiderhiser, Jenae M.; Shaw, Daniel S.; Natsuaki, Misaki N.; Reiss, David

    2014-01-01

    Although social competence in children has been linked to the quality of parenting, prior research has typically not accounted for genetic similarities between parents and children, or for interactions between environmental (i.e., parental) and genetic influences. In this paper, we evaluate the possibility of a gene-by-environment (GxE) interaction in the prediction of social competence in school-age children. Using a longitudinal, multi-method dataset from a sample of children adopted at birth (N = 361), we found a significant interaction between birth parent sociability and sensitive, responsive adoptive parenting when predicting child social competence at school entry (age 6), even when controlling for potential confounds. An analysis of the interaction revealed that genetic strengths can buffer the effects of unresponsive parenting. PMID:25581124

  20. Precision and negative predictive value of links between ClinicalTrials.gov and PubMed.

    PubMed

    Huser, Vojtech; Cimino, James J

    2012-01-01

    One of the goals of translational science is to shorten the time from discovery to clinical use. Clinical trial registries were established to increase transparency in completed and ongoing clinical trials, and they support linking trials with resulting publications. We set out to investigate precision and negative predictive value (NPV) of links between ClinicalTrials.gov (CT.gov) and PubMed. CT.gov has been established to increase transparency in clinical trials and the link to PubMed is crucial for supporting a number of important functions, including ascertaining publication bias. We drew a random sample of trials downloaded from CT.gov and performed manual review of retrieved publications. We characterize two types of links between trials and publications (NCT-link originating from MEDLINE and PMID-link originating from CT.gov).The link precision is different based on type (NCT-link: 100%; PMID-link: 63% to 96%). In trials with no linked publication, we were able to find publications 44% of the time (NPV=56%) by searching PubMed. This low NPV shows that there are potentially numerous publications that should have been formally linked with the trials. Our results indicate that existing trial registry and publisher policies may not be fully enforced. We suggest some automated methods for improving link quality.

  1. Precision and Negative Predictive Value of Links between ClinicalTrials.gov and PubMed

    PubMed Central

    Huser, Vojtech; Cimino, James J.

    2012-01-01

    One of the goals of translational science is to shorten the time from discovery to clinical use. Clinical trial registries were established to increase transparency in completed and ongoing clinical trials, and they support linking trials with resulting publications. We set out to investigate precision and negative predictive value (NPV) of links between ClinicalTrials.gov (CT.gov) and PubMed. CT.gov has been established to increase transparency in clinical trials and the link to PubMed is crucial for supporting a number of important functions, including ascertaining publication bias. We drew a random sample of trials downloaded from CT.gov and performed manual review of retrieved publications. We characterize two types of links between trials and publications (NCT-link originating from MEDLINE and PMID-link originating from CT.gov).The link precision is different based on type (NCT-link: 100%; PMID-link: 63% to 96%). In trials with no linked publication, we were able to find publications 44% of the time (NPV=56%) by searching PubMed. This low NPV shows that there are potentially numerous publications that should have been formally linked with the trials. Our results indicate that existing trial registry and publisher policies may not be fully enforced. We suggest some automated methods for improving link quality. PMID:23304310

  2. Not Just Another Single Issue: Teen Pregnancy Prevention's Link to Other Critical Social Issues.

    ERIC Educational Resources Information Center

    National Campaign To Prevent Teen Pregnancy, Washington, DC.

    This report discusses critical social issues linked to teen pregnancy, explaining that teen pregnancy prevention should be viewed as working to improve these social issues. After providing general background on teen pregnancy, the report offers five fact sheets: (1) "Teen Pregnancy, Welfare Dependency, and Poverty" (continuing to reduce…

  3. Depression and Social Anxiety in Children: Differential Links with Coping Strategies

    ERIC Educational Resources Information Center

    Wright, Mark; Banerjee, Robin; Hoek, Willemijn; Rieffe, Carolien; Novin, Sheida

    2010-01-01

    Strategies that children use for coping with stressors are known to be related to emotional adjustment, but not enough is understood about specific links with social anxiety and depression. The present investigation tested differentiated associations of social anxiety and depression with specific types of coping strategies, and evaluated the…

  4. Attention Biases to Threat Link Behavioral Inhibition to Social Withdrawal over Time in Very Young Children

    ERIC Educational Resources Information Center

    Perez-Edgar, Koraly; Reeb-Sutherland, Bethany C.; McDermott, Jennifer Martin; White, Lauren K.; Henderson, Heather A.; Degnan, Kathryn A.; Hane, Amie A.; Pine, Daniel S.; Fox, Nathan A.

    2011-01-01

    Behaviorally inhibited children display a temperamental profile characterized by social withdrawal and anxious behaviors. Previous research, focused largely on adolescents, suggests that attention biases to threat may sustain high levels of behavioral inhibition (BI) over time, helping link early temperament to social outcomes. However, no prior…

  5. What Have We Learned about the Social Context-Student Engagement Link?

    ERIC Educational Resources Information Center

    Boekaerts, Monique

    2011-01-01

    The author explores how each author contributes to our understanding of the social context--self-regulation link. She also describes how the articles collectively enhance our insights into the social embeddedness of regulation strategies in the classroom and lists some of the challenges that remain.

  6. Social Networks: A Link between Psychiatric Epidemiology and Community Mental Health.

    ERIC Educational Resources Information Center

    Llamas, Robert; And Others

    1981-01-01

    Examines the concept of social network as a mediating construct linking psychiatric epidemiology and community mental health. Presents a selective review of studies investigating the structural and interactional features of the social networks of psychiatrically impaired persons. Implications of results are discussed. (Author)

  7. Depression and Social Anxiety in Children: Differential Links with Coping Strategies

    ERIC Educational Resources Information Center

    Wright, Mark; Banerjee, Robin; Hoek, Willemijn; Rieffe, Carolien; Novin, Sheida

    2010-01-01

    Strategies that children use for coping with stressors are known to be related to emotional adjustment, but not enough is understood about specific links with social anxiety and depression. The present investigation tested differentiated associations of social anxiety and depression with specific types of coping strategies, and evaluated the…

  8. Who is good at this game? Linking an activity to a social category undermines children's achievement.

    PubMed

    Cimpian, Andrei; Mu, Yan; Erickson, Lucy C

    2012-05-01

    Children's achievement-related theories have a profound impact on their academic success. Children who adopt entity theories believe that their ability to perform a task is dictated by the amount of natural talent they possess for that task--a belief that has well-documented adverse consequences for their achievement (e.g., lowered persistence, impaired performance). It is thus important to understand what leads children to adopt entity theories. In the experiments reported here, we hypothesized that the mere act of linking success at an unfamiliar, challenging activity to a social group gives rise to entity beliefs that are so powerful as to interfere with children's ability to perform the activity. Two experiments showed that, as predicted, the performance of 4- to 7-year-olds (N = 192) was impaired by exposure to information that associated success in the task at hand with membership in a certain social group (e.g., "boys are good at this game"), regardless of whether the children themselves belonged to that group.

  9. Encoded exposure to tobacco use in social media predicts subsequent smoking behavior.

    PubMed

    Depue, Jacob B; Southwell, Brian G; Betzner, Anne E; Walsh, Barbara M

    2015-01-01

    Assessing the potential link between smoking behavior and exposure to mass media depictions of smoking on social networking Web sites. A representative longitudinal panel of 200 young adults in Connecticut. Telephone surveys were conducted by using computer assisted telephone interviewing technology and electronic dialing for random digit dialing and listed samples. Connecticut residents aged 18 to 24 years. To measure encoded exposure, respondents were asked whether or not they had smoked a cigarette in the past 30 days and about how often they had seen tobacco use on television, in movies, and in social media content. Respondents were also asked about cigarette use in the past 30 days, and a series of additional questions that have been shown to be predictive of tobacco use. Logistic regression was used to test for our main prediction that reported exposure to social media tobacco depictions at time 1 would influence time 2 smoking behavior. Encoded exposure to social media tobacco depictions (B = .47, p < .05) was a significant predictor of time 2 smoking, even after controlling for all the aforementioned predictors. Our results suggest that social media depictions of tobacco use predict future smoking tendency, over and above the influence of TV and movie depictions of smoking. This is the first known study to specifically assess the role of social media in informing tobacco behavior.

  10. Preserving and maintaining vital Ecosystem Services: the importance of linking knowledge from Geosciences and social-ecological System analysis

    NASA Astrophysics Data System (ADS)

    Finger, David; Petursdottir, Thorunn

    2013-04-01

    Human kind has always been curios and motivated to understand and quantify environmental processes in order to predict and anticipate the evolution of vital ecosystem services. Even the very first civilizations used empirical correlations to predict outcomes of rains and subsequent harvest efficiencies. Along with the insights into the functioning of ecosystems, humans also became aware that their anthropogenic activities can have positive and negative impact on ecosystem services. In recent years, geosciences have brought forward new sophisticated observations and modeling tools, with the aim to improve predictions of ecological developments. At the same time, the added value of linking ecological factors to the surrounding social structure has received a growing acceptance among scientists. A social-ecological system approach brings in a holistic understanding of how these systems are inevitably interlinked and how their sustainability can be better maintained. We claim that the biggest challenge for geoscience in the coming decades will be to link these two disciplines in order to establish adequate strategies to preserve natural ecosystems and their services, parallel to their utilization. We will present various case studies from more than a decade of research, ranging from water quality in mountain lakes, climate change impacts on water availability and declining fishing yields in freshwaters and discuss how the studies outcomes could be given added value by interpreting them via social-ecological system analysis. For instance, sophisticated field investigations revealed that deep water mixing in lake Issyk-Kul, Kirgizstan, is intensively distributing pollutants in the entire lake. Although fishery is an important sector in the region, the local awareness of the importance of water quality is low. In Switzerland, strict water protection laws led to ologotrophication of alpine lakes, reducing fishing yields. While local fishermen argued that local fishery is

  11. The conceptual link between social desirability and cultural normativity.

    PubMed

    Bou Malham, Philippe; Saucier, Gerard

    2016-12-01

    Psychologists have a recurrent concern that socially desirable responding (SDR) is a form of response distortion that compromises the validity of self-report measures, especially in high-stakes situations where participants are motivated to make a good impression. Psychologists have used various strategies to minimise SDR or its impact, for example, forced choice responding, ipsatization, and direct measures of social desirability. However, empirical evidence suggests that SDR is a robust phenomenon existing in many cultures and a substantive variable with meaningful associations with other psychological variables and outcomes. Here, we review evidence of the occurrence of SDR across cultures and tie SDR to the study of cultural normativity and cultural consonance in anthropology. We suggest that cultural normativity is an important component of SDR, which may partly explain the adaptiveness of SDR and its association with positive outcomes.

  12. Leveraging Social Links for Trust and Privacy in Networks

    NASA Astrophysics Data System (ADS)

    Cutillo, Leucio Antonio; Molva, Refik; Strufe, Thorsten

    Existing on-line social networks (OSN) such as Facebook suffer from several weaknesses regarding privacy and security due to their inherent handling of personal data. As pointed out in [4], a preliminary analysis of existing OSNs shows that they are subject to a number of vulnerabilities, ranging from cloning legitimate users to sybil attacks through privacy violations. Starting from these OSN vulnerabilities as the first step of a broader research activity, we came up with a new approach that is very promising in re-visiting security and privacy problems in distributed systems and networks. We suggest a solution that both aims at avoiding any centralized control and leverages on the real life trust between users, that is part of the social network application itself. An anonymization technique based on multi-hop routing among trusted nodes guarantees privacy in data access and, generally speaking, in all the OSN operations.

  13. Efficient network disintegration under incomplete information: the comic effect of link prediction.

    PubMed

    Tan, Suo-Yi; Wu, Jun; Lü, Linyuan; Li, Meng-Jun; Lu, Xin

    2016-03-10

    The study of network disintegration has attracted much attention due to its wide applications, including suppressing the epidemic spreading, destabilizing terrorist network, preventing financial contagion, controlling the rumor diffusion and perturbing cancer networks. The crux of this matter is to find the critical nodes whose removal will lead to network collapse. This paper studies the disintegration of networks with incomplete link information. An effective method is proposed to find the critical nodes by the assistance of link prediction techniques. Extensive experiments in both synthetic and real networks suggest that, by using link prediction method to recover partial missing links in advance, the method can largely improve the network disintegration performance. Besides, to our surprise, we find that when the size of missing information is relatively small, our method even outperforms than the results based on complete information. We refer to this phenomenon as the "comic effect" of link prediction, which means that the network is reshaped through the addition of some links that identified by link prediction algorithms, and the reshaped network is like an exaggerated but characteristic comic of the original one, where the important parts are emphasized.

  14. Efficient network disintegration under incomplete information: the comic effect of link prediction

    NASA Astrophysics Data System (ADS)

    Tan, Suo-Yi; Wu, Jun; Lü, Linyuan; Li, Meng-Jun; Lu, Xin

    2016-03-01

    The study of network disintegration has attracted much attention due to its wide applications, including suppressing the epidemic spreading, destabilizing terrorist network, preventing financial contagion, controlling the rumor diffusion and perturbing cancer networks. The crux of this matter is to find the critical nodes whose removal will lead to network collapse. This paper studies the disintegration of networks with incomplete link information. An effective method is proposed to find the critical nodes by the assistance of link prediction techniques. Extensive experiments in both synthetic and real networks suggest that, by using link prediction method to recover partial missing links in advance, the method can largely improve the network disintegration performance. Besides, to our surprise, we find that when the size of missing information is relatively small, our method even outperforms than the results based on complete information. We refer to this phenomenon as the “comic effect” of link prediction, which means that the network is reshaped through the addition of some links that identified by link prediction algorithms, and the reshaped network is like an exaggerated but characteristic comic of the original one, where the important parts are emphasized.

  15. Efficient network disintegration under incomplete information: the comic effect of link prediction

    PubMed Central

    Tan, Suo-Yi; Wu, Jun; Lü, Linyuan; Li, Meng-Jun; Lu, Xin

    2016-01-01

    The study of network disintegration has attracted much attention due to its wide applications, including suppressing the epidemic spreading, destabilizing terrorist network, preventing financial contagion, controlling the rumor diffusion and perturbing cancer networks. The crux of this matter is to find the critical nodes whose removal will lead to network collapse. This paper studies the disintegration of networks with incomplete link information. An effective method is proposed to find the critical nodes by the assistance of link prediction techniques. Extensive experiments in both synthetic and real networks suggest that, by using link prediction method to recover partial missing links in advance, the method can largely improve the network disintegration performance. Besides, to our surprise, we find that when the size of missing information is relatively small, our method even outperforms than the results based on complete information. We refer to this phenomenon as the “comic effect” of link prediction, which means that the network is reshaped through the addition of some links that identified by link prediction algorithms, and the reshaped network is like an exaggerated but characteristic comic of the original one, where the important parts are emphasized. PMID:26960247

  16. Playing the role of weak clique property in link prediction: A friend recommendation model

    PubMed Central

    Ma, Chuang; Zhou, Tao; Zhang, Hai-Feng

    2016-01-01

    An important fact in studying link prediction is that the structural properties of networks have significant impacts on the performance of algorithms. Therefore, how to improve the performance of link prediction with the aid of structural properties of networks is an essential problem. By analyzing many real networks, we find a typical structural property: nodes are preferentially linked to the nodes with the weak clique structure (abbreviated as PWCS to simplify descriptions). Based on this PWCS phenomenon, we propose a local friend recommendation (FR) index to facilitate link prediction. Our experiments show that the performance of FR index is better than some famous local similarity indices, such as Common Neighbor (CN) index, Adamic-Adar (AA) index and Resource Allocation (RA) index. We then explain why PWCS can give rise to the better performance of FR index in link prediction. Finally, a mixed friend recommendation index (labelled MFR) is proposed by utilizing the PWCS phenomenon, which further improves the accuracy of link prediction. PMID:27439697

  17. A group evolving-based framework with perturbations for link prediction

    NASA Astrophysics Data System (ADS)

    Si, Cuiqi; Jiao, Licheng; Wu, Jianshe; Zhao, Jin

    2017-06-01

    Link prediction is a ubiquitous application in many fields which uses partially observed information to predict absence or presence of links between node pairs. The group evolving study provides reasonable explanations on the behaviors of nodes, relations between nodes and community formation in a network. Possible events in group evolution include continuing, growing, splitting, forming and so on. The changes discovered in networks are to some extent the result of these events. In this work, we present a group evolving-based characterization of node's behavioral patterns, and via which we can estimate the probability they tend to interact. In general, the primary aim of this paper is to offer a minimal toy model to detect missing links based on evolution of groups and give a simpler explanation on the rationality of the model. We first introduce perturbations into networks to obtain stable cluster structures, and the stable clusters determine the stability of each node. Then fluctuations, another node behavior, are assumed by the participation of each node to its own belonging group. Finally, we demonstrate that such characteristics allow us to predict link existence and propose a model for link prediction which outperforms many classical methods with a decreasing computational time in large scales. Encouraging experimental results obtained on real networks show that our approach can effectively predict missing links in network, and even when nearly 40% of the edges are missing, it also retains stationary performance.

  18. Predicting missing links in complex networks based on common neighbors and distance

    PubMed Central

    Yang, Jinxuan; Zhang, Xiao-Dong

    2016-01-01

    The algorithms based on common neighbors metric to predict missing links in complex networks are very popular, but most of these algorithms do not account for missing links between nodes with no common neighbors. It is not accurate enough to reconstruct networks by using these methods in some cases especially when between nodes have less common neighbors. We proposed in this paper a new algorithm based on common neighbors and distance to improve accuracy of link prediction. Our proposed algorithm makes remarkable effect in predicting the missing links between nodes with no common neighbors and performs better than most existing currently used methods for a variety of real-world networks without increasing complexity. PMID:27905526

  19. Predicting Comorbid Conditions and Trajectories using Social Health Records.

    PubMed

    Ji, Xiang; Ae Chun, Soon; Geller, James

    2016-05-05

    Many patients suffer from comorbidity conditions, for example, obese patients often develop type-2 diabetes and hypertension. In the US, 80% of Medicare spending is for managing patients with these multiple coexisting conditions. Predicting potential comorbidity conditions for an individual patient can promote preventive care and reduce costs. Predicting possible comorbidity progression paths can provide important insights into population heath and aid with decisions in public health policies. Discovering the comorbidity relationships is complex and difficult, due to limited access to Electronic Health Records by privacy laws. In this paper, we present a collaborative comorbidity prediction method to predict likely comorbid conditions for individual patients, and a trajectory prediction graph model to reveal progression paths of comorbid conditions. Our prediction approaches utilize patient generated health reports on online social media, called Social Health Records (SHR). The experimental results based on one SHR source show that our method is able to predict future comorbid conditions for a patient with coverage values of 48% and 75% for a top-20 and a top-100 ranked list, respectively. For risk trajectory prediction, our approach is able to reveal each potential progression trajectory between any two conditions and infer the confidence of the future trajectory, given any observed condition. The predicted trajectories are validated with existing comorbidity relations from the medical literature.

  20. What measure of interpersonal dependency predicts changes in social support?

    PubMed

    Shahar, Golan

    2008-01-01

    One of the most intriguing characteristics of interpersonal dependency is its ability to predict elevated levels of social support. Yet studies of interpersonal dependency use various measures to assess this effect. In this study, I compared 3 commonly used measures of interpersonal dependency in terms of their prediction of social support: Hirschfield's Interpersonal Dependency Inventory (IDI; Hirschfeld et al., 1977), the dependency factor of the Depressive Experiences Questionnaire (DEQ; Blatt, D'Afflitti, & Quinlan, 1976), and the Dependency subscale of the Personal Style Inventory (PSI; Robins et al., 1994). A total of 152 undergraduates were administered these measures as well as measures of depressive symptoms and social support a week prior to their first exam period and a week after this period (interval time = 8 weeks). DEQ-dependency predicted an increase in social support, whereas PSI-Dependency and IDI predicted a decrease in social support over time. DEQ-dependency appears to capture better than the other 2 measures the dialectic tension between risk and resilience in interpersonal dependency.

  1. OXTR polymorphism predicts social relationships through its effects on social temperament.

    PubMed

    Creswell, Kasey G; Wright, Aidan G C; Troxel, Wendy M; Ferrell, Robert E; Flory, Janine D; Manuck, Stephen B

    2015-06-01

    Humans have a fundamental need for strong interpersonal bonds, yet individuals differ appreciably in their degree of social integration. That these differences are also substantially heritable has spurred interest in biological mechanisms underlying the quality and quantity of individuals' social relationships. We propose that polymorphic variation in the oxytocin receptor gene (OXTR) associates with complex social behaviors and social network composition through intermediate effects on negative affectivity and the psychological processing of socially relevant information. We tested a hypothesized social cascade from the molecular level (OXTR variation) to the social environment, through negative affectivity and inhibited sociality, in a sample of 1295 men and women of European American (N = 1081) and African American (N = 214) ancestry. Compared to European Americans having any T allele of rs1042778, individuals homozygous for the alternate G allele reported significantly lower levels of negative affectivity and inhibited sociality, which in turn predicted significantly higher levels of social support and a larger/more diverse social network. Moreover, the effect of rs1042778 variation on social support was fully accounted for by associated differences in negative affectivity and inhibited sociality. Results replicated in the African American sample. Findings suggest that OXTR variation modulates levels of social support via proximal impacts on individual temperament. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  2. OXTR polymorphism predicts social relationships through its effects on social temperament

    PubMed Central

    Wright, Aidan G. C.; Troxel, Wendy M.; Ferrell, Robert E.; Flory, Janine D.; Manuck, Stephen B.

    2015-01-01

    Humans have a fundamental need for strong interpersonal bonds, yet individuals differ appreciably in their degree of social integration. That these differences are also substantially heritable has spurred interest in biological mechanisms underlying the quality and quantity of individuals’ social relationships. We propose that polymorphic variation in the oxytocin receptor gene (OXTR) associates with complex social behaviors and social network composition through intermediate effects on negative affectivity and the psychological processing of socially relevant information. We tested a hypothesized social cascade from the molecular level (OXTR variation) to the social environment, through negative affectivity and inhibited sociality, in a sample of 1295 men and women of European American (N = 1081) and African American (N = 214) ancestry. Compared to European Americans having any T allele of rs1042778, individuals homozygous for the alternate G allele reported significantly lower levels of negative affectivity and inhibited sociality, which in turn predicted significantly higher levels of social support and a larger/more diverse social network. Moreover, the effect of rs1042778 variation on social support was fully accounted for by associated differences in negative affectivity and inhibited sociality. Results replicated in the African American sample. Findings suggest that OXTR variation modulates levels of social support via proximal impacts on individual temperament. PMID:25326040

  3. Social networks predict selective observation and information spread in ravens

    PubMed Central

    Rubenstein, Daniel I.; Bugnyar, Thomas; Hoppitt, William; Mikus, Nace; Schwab, Christine

    2016-01-01

    Animals are predicted to selectively observe and learn from the conspecifics with whom they share social connections. Yet, hardly anything is known about the role of different connections in observation and learning. To address the relationships between social connections, observation and learning, we investigated transmission of information in two raven (Corvus corax) groups. First, we quantified social connections in each group by constructing networks on affiliative interactions, aggressive interactions and proximity. We then seeded novel information by training one group member on a novel task and allowing others to observe. In each group, an observation network based on who observed whose task-solving behaviour was strongly correlated with networks based on affiliative interactions and proximity. Ravens with high social centrality (strength, eigenvector, information centrality) in the affiliative interaction network were also central in the observation network, possibly as a result of solving the task sooner. Network-based diffusion analysis revealed that the order that ravens first solved the task was best predicted by connections in the affiliative interaction network in a group of subadult ravens, and by social rank and kinship (which influenced affiliative interactions) in a group of juvenile ravens. Our results demonstrate that not all social connections are equally effective at predicting the patterns of selective observation and information transmission. PMID:27493780

  4. Social networks predict selective observation and information spread in ravens.

    PubMed

    Kulahci, Ipek G; Rubenstein, Daniel I; Bugnyar, Thomas; Hoppitt, William; Mikus, Nace; Schwab, Christine

    2016-07-01

    Animals are predicted to selectively observe and learn from the conspecifics with whom they share social connections. Yet, hardly anything is known about the role of different connections in observation and learning. To address the relationships between social connections, observation and learning, we investigated transmission of information in two raven (Corvus corax) groups. First, we quantified social connections in each group by constructing networks on affiliative interactions, aggressive interactions and proximity. We then seeded novel information by training one group member on a novel task and allowing others to observe. In each group, an observation network based on who observed whose task-solving behaviour was strongly correlated with networks based on affiliative interactions and proximity. Ravens with high social centrality (strength, eigenvector, information centrality) in the affiliative interaction network were also central in the observation network, possibly as a result of solving the task sooner. Network-based diffusion analysis revealed that the order that ravens first solved the task was best predicted by connections in the affiliative interaction network in a group of subadult ravens, and by social rank and kinship (which influenced affiliative interactions) in a group of juvenile ravens. Our results demonstrate that not all social connections are equally effective at predicting the patterns of selective observation and information transmission.

  5. Individual differences in response of dorsomedial prefrontal cortex predict daily social behavior

    PubMed Central

    Chavez, Robert S.; Heatherton, Todd F.

    2016-01-01

    The capacity to accurately infer the thoughts and intentions of other people is critical for effective social interaction, and neural activity in dorsomedial prefrontal cortex (dmPFC) has long been linked with the extent to which people engage in mental state attribution. In this study, we combined functional neuroimaging and experience sampling methodologies to test the predictive value of this neural response for daily social behaviors. We found that individuals who displayed greater activity in dmPFC when viewing social scenes spent more time around other people on a daily basis. These findings suggest a specific role for the neural mechanisms that support the capacity to mentalize in guiding individuals toward situations containing valuable social outcomes. PMID:26206505

  6. Predicting the behavior of techno-social systems.

    PubMed

    Vespignani, Alessandro

    2009-07-24

    We live in an increasingly interconnected world of techno-social systems, in which infrastructures composed of different technological layers are interoperating within the social component that drives their use and development. Examples are provided by the Internet, the World Wide Web, WiFi communication technologies, and transportation and mobility infrastructures. The multiscale nature and complexity of these networks are crucial features in understanding and managing the networks. The accessibility of new data and the advances in the theory and modeling of complex networks are providing an integrated framework that brings us closer to achieving true predictive power of the behavior of techno-social systems.

  7. Working memory dysfunctions predict social problem solving skills in schizophrenia.

    PubMed

    Huang, Jia; Tan, Shu-ping; Walsh, Sarah C; Spriggens, Lauren K; Neumann, David L; Shum, David H K; Chan, Raymond C K

    2014-12-15

    The current study aimed to examine the contribution of neurocognition and social cognition to components of social problem solving. Sixty-seven inpatients with schizophrenia and 31 healthy controls were administrated batteries of neurocognitive tests, emotion perception tests, and the Chinese Assessment of Interpersonal Problem Solving Skills (CAIPSS). MANOVAs were conducted to investigate the domains in which patients with schizophrenia showed impairments. Correlations were used to determine which impaired domains were associated with social problem solving, and multiple regression analyses were conducted to compare the relative contribution of neurocognitive and social cognitive functioning to components of social problem solving. Compared with healthy controls, patients with schizophrenia performed significantly worse in sustained attention, working memory, negative emotion, intention identification and all components of the CAIPSS. Specifically, sustained attention, working memory and negative emotion identification were found to correlate with social problem solving and 1-back accuracy significantly predicted the poor performance in social problem solving. Among the dysfunctions in schizophrenia, working memory contributed most to deficits in social problem solving in patients with schizophrenia. This finding provides support for targeting working memory in the development of future social problem solving rehabilitation interventions.

  8. Gene-environment interplay in the link of friends' and nonfriends' behaviors with children's social reticence in a competitive situation.

    PubMed

    Guimond, Fanny-Alexandra; Brendgen, Mara; Vitaro, Frank; Forget-Dubois, Nadine; Dionne, Ginette; Tremblay, Richard E; Boivin, Michel

    2014-03-01

    This study used a genetically informed design to assess the effects of friends' and nonfriends' reticent and dominant behaviors on children's observed social reticence in a competitive situation. Potential gene-environment correlations (rGE) and gene-environment interactions (GxE) in the link between (a) friends' and nonfriends' behaviors and (b) children's social reticence were examined. The sample comprised 466 twin children (i.e., the target children), each of whom was assessed in kindergarten together with a same-sex friend and two nonfriend classmates of either sex. Multilevel regression analyses revealed that children with a genetic disposition for social reticence showed more reticent behavior in the competitive situation and were more likely to affiliate with reticent friends (i.e., rGE). Moreover, a higher level of children's reticent behavior was predicted by their friends' higher social reticence (particularly for girls) and their friends' higher social dominance, independently of children's genetic disposition. Children's social reticence was also predicted by their nonfriends' behaviors. Specifically, children were less reticent when male nonfriends showed high levels of social reticence in the competitive situation, and this was particularly true for children with a genetic disposition for social reticence (i.e., GxE). Moreover, children genetically vulnerable for social reticence seemed to foster dominant behavior in their female nonfriend peers (i.e., rGE). In turn, male nonfriends seemed to be more dominant as soon as the target children were reticent, even if the target children did not have a stable genetic disposition for this behavior. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  9. Social Support Indirectly Predicts Problem Drinking Through Reduced Psychological Distress.

    PubMed

    Segrin, Chris; McNelis, Melissa; Swiatkowski, Paulina

    2016-01-01

    The experience of psychological distress can contribute to problem drinking in young adults. Social support can protect against the development of distress and thus may indirectly minimize problem drinking. To test a model of problem drinking in young adults based on the concepts of social support and psychological distress. A two-wave panel study was conducted over the course of one year, during 2014-15, with 211 university students (M age = 21.06 years, SD = 1.60 years) who completed online survey measures of problem drinking, various indicators of social support, and various indicators of psychological distress. The data were analyzed with structural equation modeling. After controlling for concurrent problem drinking and psychological distress, there was no direct prospective effect of social support on problem drinking. However, social support predicted reductions in psychological distress over time, and this reduced psychological distress predicted reductions in problem drinking over time. Therefore, social support exhibited a significant indirect effect on problem drinking. Social support from friends, emotional support, and informational support combine to form a protective factor that mitigates the risk of problem drinking in young adults through reduced psychological distress.

  10. The Predictive Analysis of Adjustment Difficulties from Loneliness, Social Support, and Social Connectedness

    ERIC Educational Resources Information Center

    Duru, Erdinc

    2008-01-01

    The purpose of the study was to examine direct and indirect effects of social support, social connectedness, and loneliness in predicting adjustment difficulties. The sample of the study was 404 university students (212 females and 192 males) studying in different departments of the Faculty of Education at Pamukkale University. The ages of the…

  11. Aberrant link between empathy and social attribution style in borderline personality disorder.

    PubMed

    Homan, Philipp; Reddan, Marianne C; Brosch, Tobias; Koenigsberg, Harold W; Schiller, Daniela

    2017-07-14

    In social interactions, we often need to quickly infer why other people do what they do. More often than not, we infer that behavior is a result of personality rather than circumstances. It is unclear how the tendency itself may contribute to psychopathology and interpersonal dysfunction. Borderline personality disorder (BPD) is characterized by severe interpersonal dysfunction. Here, we investigated if this dysfunction is related to the tendency to over-attribute behaviors to personality traits. Healthy controls and patients with BPD judged positive and negative behaviors presented within a situational constraint during functional magnetic resonance imaging. Before the experiment, we measured trait levels of empathy, paranoia, and need for cognition. Behaviorally, we found that empathy levels predicted the tendency to attribute behavior to traits in healthy controls, whereas in patients with BPD this relationship was significantly weakened. Whole brain analysis of group-by-empathy interaction revealed that when participants judged the behavior during the attribution phase, several brain regions implicated in mentalizing distinguished patients from controls: In healthy controls, neural activity scaled negatively with empathy, but this relationship was reversed in BPD patients. Due to the cross-sectional study design we cannot establish a causal link between empathy and social attributions. These findings indicate that the self-reported tendency to feel for others is related to the tendency to integrate situational information beyond personality. In BPD patients, by contrast, the association between empathy and attribution was significantly weaker, rendering empathy less informative in predicting the overall attribution style. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Measuring Social Capital Investment: Scale Development and Examination of Links to Social Capital and Perceived Stress

    PubMed Central

    Wegner, Rhiana; Gong, Jie; Fang, Xiaoyi; Kaljee, Linda

    2014-01-01

    Individuals with greater social capital have better health outcomes. Investment in social capital likely increases one’s own social capital, bearing great implications for disease prevention and health promotion. In this study, the authors developed and validated the Social Capital Investment Inventory (SCII). Direct effects of social capital investment on perceived stress, and indirect effects through social capital were examined. 397 Participants from Beijing and Wuhan, China completed surveys. Analyses demonstrated that the SCII has a single factor structure and strong internal consistency. Structural equation modeling showed that individuals who invested more in social capital had greater bonding social capital, and subsequently less perceived stress. Results suggest that disease prevention and health promotion programs should consider approaches to encourage social capital investment; individuals may be able to reduce stress by increasing their investment in social capital. Future research is needed to provide additional empirical support for the SCII and observed structural relationships. PMID:25648725

  13. Measuring Social Capital Investment: Scale Development and Examination of Links to Social Capital and Perceived Stress.

    PubMed

    Chen, Xinguang; Wang, Peigang; Wegner, Rhiana; Gong, Jie; Fang, Xiaoyi; Kaljee, Linda

    2015-02-01

    Individuals with greater social capital have better health outcomes. Investment in social capital likely increases one's own social capital, bearing great implications for disease prevention and health promotion. In this study, the authors developed and validated the Social Capital Investment Inventory (SCII). Direct effects of social capital investment on perceived stress, and indirect effects through social capital were examined. 397 Participants from Beijing and Wuhan, China completed surveys. Analyses demonstrated that the SCII has a single factor structure and strong internal consistency. Structural equation modeling showed that individuals who invested more in social capital had greater bonding social capital, and subsequently less perceived stress. Results suggest that disease prevention and health promotion programs should consider approaches to encourage social capital investment; individuals may be able to reduce stress by increasing their investment in social capital. Future research is needed to provide additional empirical support for the SCII and observed structural relationships.

  14. Dynamic Socialized Gaussian Process Models for Human Behavior Prediction in a Health Social Network.

    PubMed

    Shen, Yelong; Phan, NhatHai; Xiao, Xiao; Jin, Ruoming; Sun, Junfeng; Piniewski, Brigitte; Kil, David; Dou, Dejing

    2016-11-01

    Modeling and predicting human behaviors, such as the level and intensity of physical activity, is a key to preventing the cascade of obesity and helping spread healthy behaviors in a social network. In our conference paper, we have developed a social influence model, named Socialized Gaussian Process (SGP), for socialized human behavior modeling. Instead of explicitly modeling social influence as individuals' behaviors influenced by their friends' previous behaviors, SGP models the dynamic social correlation as the result of social influence. The SGP model naturally incorporates personal behavior factor and social correlation factor (i.e., the homophily principle: Friends tend to perform similar behaviors) into a unified model. And it models the social influence factor (i.e., an individual's behavior can be affected by his/her friends) implicitly in dynamic social correlation schemes. The detailed experimental evaluation has shown the SGP model achieves better prediction accuracy compared with most of baseline methods. However, a Socialized Random Forest model may perform better at the beginning compared with the SGP model. One of the main reasons is the dynamic social correlation function is purely based on the users' sequential behaviors without considering other physical activity-related features. To address this issue, we further propose a novel "multi-feature SGP model" (mfSGP) which improves the SGP model by using multiple physical activity-related features in the dynamic social correlation learning. Extensive experimental results illustrate that the mfSGP model clearly outperforms all other models in terms of prediction accuracy and running time.

  15. Effects of active links on epidemic transmission over social networks

    NASA Astrophysics Data System (ADS)

    Zhu, Guanghu; Chen, Guanrong; Fu, Xinchu

    2017-02-01

    A new epidemic model with two infection periods is developed to account for the human behavior in social network, where newly infected individuals gradually restrict most of future contacts or are quarantined, causing infectivity change from a degree-dependent form to a constant. The corresponding dynamics are formulated by a set of ordinary differential equations (ODEs) via mean-field approximation. The effects of diverse infectivity on the epidemic dynamics ​are examined, with a behavioral interpretation of the basic reproduction number. Results show that such simple adaptive reactions largely determine the impact of network structure on epidemics. Particularly, a theorem proposed by Lajmanovich and Yorke in 1976 is generalized, so that it can be applied for the analysis of the epidemic models with multi-compartments especially network-coupled ODE systems.

  16. The "weakest link" as an indicator of cognitive vulnerability differentially predicts symptom dimensions of anxiety in adolescents in China.

    PubMed

    Wang, Junyi; Wang, Danyang; Cui, Lixia; McWhinnie, Chad M; Wang, Li; Xiao, Jing

    2017-08-01

    This multiwave longitudinal study examined the cognitive vulnerability-stress component of hopelessness theory to differentially predict symptom dimensions of anxiety using a "weakest link" approach in a sample of adolescents from Hunan Province, China. Baseline and 6-month follow-up data were obtained from 553 middle-school students. During an initial assessment, participants completed measures of assessing their weakest links, anxious symptoms, and the occurrence of stress. Participants subsequently completed measures assessing stress, and anxious symptoms one a month for six months. Higher weakest link scores were associated with greater increases in the harm avoidance and separation anxiety/panic dimensions, but not the physical or social anxiety dimension, of anxious symptoms following stress in Chinese adolescents. These results support the applicability of the "weakest link" approach, derived from hopelessness theory, in Chinese adolescents. Weakest link scores as cognitive vulnerability factors may play a role in the development of anxious symptoms, especially in the cognitive dimensions (e.g., harm avoidance and separation anxiety/panic). Our findings also have potential value in explaining the effectiveness of cognitive relevant therapy in treating the cognitive dimensions of anxious symptoms. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Demystifying internalization and socialization: linking conceptions of how development happens to organismic-developmental theory.

    PubMed

    Raeff, Catherine

    2014-01-01

    Internalization and socialization are central constructs in developmental psychology for explaining and investigating how development happens through social interaction. There has been and continues to be much debate about how to conceptualize and investigate these processes. The ways in which internalization and socialization promote development have also been difficult to identify. The goal of this chapter is to offer a way of clarifying what happens during internalization and socialization by linking them to a clear conceptualization of development. The chapter first provides an overview of internalization and socialization theory and research. This review indicates that the focus on how development happens through social interaction has taken attention away from specifying the developmental changes that occur through social interaction. It is argued that understanding internalization and socialization can be enhanced by linking them to a clear definition of development, such as the one provided by organismic-developmental theory. According to organismic-developmental theory, developmental change is distinguished from any change that may occur over time. Rather, development is defined in terms of the differentiation and integration of action components in relation to cultural values and expectations for development. After explicating organismic-developmental theory's key claims, some implications of utilizing it for advancing an understanding of internalization and socialization are discussed. The chapter ends with suggestions for future research on internalization, socialization, and development.

  18. Prediction of First Grade Social-Emotional and Intellectual Functioning.

    ERIC Educational Resources Information Center

    Kohn, Martin; And Others

    In order to determine the longitudinal persistence of two major personality dimensions, namely Apathy-Withdrawal versus Interest-Participation (Factor 1) and Anger-Defiance versus Conformity-Compliance (Factor 2), and to test the hypothesis that the social-emotional functioning of the preschool child is predictive of later intellectual-academic…

  19. A Social Psychological Model for Predicting Sexual Harassment.

    ERIC Educational Resources Information Center

    Pryor, John B.; And Others

    1995-01-01

    Presents a Person X Situation (PXS) model of sexual harassment suggesting that sexually harassing behavior may be predicted from an analysis of social situational and personal factors. Research on sexual harassment proclivities in men is reviewed, and a profile of men who have a high a likelihood to sexually harass is discussed. Possible PXS…

  20. Health Communication in Social Media: Message Features Predicting User Engagement on Diabetes-Related Facebook Pages.

    PubMed

    Rus, Holly M; Cameron, Linda D

    2016-10-01

    Social media provides unprecedented opportunities for enhancing health communication and health care, including self-management of chronic conditions such as diabetes. Creating messages that engage users is critical for enhancing message impact and dissemination. This study analyzed health communications within ten diabetes-related Facebook pages to identify message features predictive of user engagement. The Common-Sense Model of Illness Self-Regulation and established health communication techniques guided content analyses of 500 Facebook posts. Each post was coded for message features predicted to engage users and numbers of likes, shares, and comments during the week following posting. Multi-level, negative binomial regressions revealed that specific features predicted different forms of engagement. Imagery emerged as a strong predictor; messages with images had higher rates of liking and sharing relative to messages without images. Diabetes consequence information and positive identity predicted higher sharing while negative affect, social support, and crowdsourcing predicted higher commenting. Negative affect, crowdsourcing, and use of external links predicted lower sharing while positive identity predicted lower commenting. The presence of imagery weakened or reversed the positive relationships of several message features with engagement. Diabetes control information and negative affect predicted more likes in text-only messages, but fewer likes when these messages included illustrative imagery. Similar patterns of imagery's attenuating effects emerged for the positive relationships of consequence information, control information, and positive identity with shares and for positive relationships of negative affect and social support with comments. These findings hold promise for guiding communication design in health-related social media.

  1. Optimizing Cross-Sectional Prediction of Social Functioning in Youth Referred for Neuropsychological Testing

    PubMed Central

    Lerner, Matthew D.; Potthoff, Lauren M.; Hunter, Scott J.

    2015-01-01

    The current study aimed to establish a fine-grained, efficient characterization of the concurrent neuropsychological contributions to social functioning in neuropsychologically-referred youth. A secondary aim was to demonstrate a useful statistic approach for such investigations (Partial Least Squares Regression; PLSR), which is underutilized in this field. Forty-five participants (70 – 164 months; Mage = 110.89; 34 male) were recruited from a large neuropsychological assessment clinic. Participants completed subtests from the NEPSY-II focusing on neuropsychological constructs that have been linked to social functioning (affect decoding, social memory, motor skills, visuomotor skills, response inhibition, attention and set-shifting, and verbal comprehension). Mothers completed the BASC-2, from which Atypicality and Social Skills scales were analyzed. PLSR revealed that difficulty with social memory, sensorimotor integration, and the ability to attend to and accurately discriminate auditory stimuli combine to best predict atypical or “odd” behavior. In terms of social skills, two factors emerged. The first factor indicated that, counterintuitively, greater emotional perception, visuospatial perception, ability to attend to and accurately discriminate auditory stimuli, and understand instructions was related to poorer social skills. The second factor indicated that a pattern of better facial memory, and sensorimotor ability (execution & integration) characterized a distinct profile of greater social ability. PLSR results were compared to traditional OLS and Backwards Stepwise regression approaches to demonstrate utility. Results also suggested that these findings were consistent across age, gender, and diagnostic group, indicating common neuropsychological substrates of social functioning in this sample of referred youth. Overall, this study provides the first characterization of optimized combinations of neuropsychological variables in predicting social

  2. Optimizing cross-sectional prediction of social functioning in youth referred for neuropsychological testing.

    PubMed

    Lerner, Matthew D; Potthoff, Lauren M; Hunter, Scott J

    2015-01-01

    The current study aimed to establish a fine-grained, efficient characterization of the concurrent neuropsychological contributions to social functioning in neuropsychologically-referred youth. A secondary aim was to demonstrate a useful statistic approach for such investigations (Partial Least Squares Regression; PLSR), which is underutilized in this field. Forty-five participants (70 - 164 months; Mage = 110.89; 34 male) were recruited from a large neuropsychological assessment clinic. Participants completed subtests from the NEPSY-II focusing on neuropsychological constructs that have been linked to social functioning (affect decoding, social memory, motor skills, visuomotor skills, response inhibition, attention and set-shifting, and verbal comprehension). Mothers completed the BASC-2, from which Atypicality and Social Skills scales were analyzed. PLSR revealed that difficulty with social memory, sensorimotor integration, and the ability to attend to and accurately discriminate auditory stimuli combine to best predict atypical or "odd" behavior. In terms of social skills, two factors emerged. The first factor indicated that, counterintuitively, greater emotional perception, visuospatial perception, ability to attend to and accurately discriminate auditory stimuli, and understand instructions was related to poorer social skills. The second factor indicated that a pattern of better facial memory, and sensorimotor ability (execution & integration) characterized a distinct profile of greater social ability. PLSR results were compared to traditional OLS and Backwards Stepwise regression approaches to demonstrate utility. Results also suggested that these findings were consistent across age, gender, and diagnostic group, indicating common neuropsychological substrates of social functioning in this sample of referred youth. Overall, this study provides the first characterization of optimized combinations of neuropsychological variables in predicting social functioning

  3. Boldness predicts social status in zebrafish (Danio rerio).

    PubMed

    Dahlbom, S Josefin; Lagman, David; Lundstedt-Enkel, Katrin; Sundström, L Fredrik; Winberg, Svante

    2011-01-01

    This study explored if boldness could be used to predict social status. First, boldness was assessed by monitoring individual zebrafish behaviour in (1) an unfamiliar barren environment with no shelter (open field), (2) the same environment when a roof was introduced as a shelter, and (3) when the roof was removed and an unfamiliar object (Lego® brick) was introduced. Next, after a resting period of minimum one week, social status of the fish was determined in a dyadic contest and dominant/subordinate individuals were determined as the winner/loser of two consecutive contests. Multivariate data analyses showed that males were bolder than females and that the behaviours expressed by the fish during the boldness tests could be used to predict which fish would later become dominant and subordinate in the ensuing dyadic contest. We conclude that bold behaviour is positively correlated to dominance in zebrafish and that boldness is not solely a consequence of social dominance.

  4. Boldness Predicts Social Status in Zebrafish (Danio rerio)

    PubMed Central

    Dahlbom, S. Josefin; Lagman, David; Lundstedt-Enkel, Katrin; Sundström, L. Fredrik; Winberg, Svante

    2011-01-01

    This study explored if boldness could be used to predict social status. First, boldness was assessed by monitoring individual zebrafish behaviour in (1) an unfamiliar barren environment with no shelter (open field), (2) the same environment when a roof was introduced as a shelter, and (3) when the roof was removed and an unfamiliar object (Lego® brick) was introduced. Next, after a resting period of minimum one week, social status of the fish was determined in a dyadic contest and dominant/subordinate individuals were determined as the winner/loser of two consecutive contests. Multivariate data analyses showed that males were bolder than females and that the behaviours expressed by the fish during the boldness tests could be used to predict which fish would later become dominant and subordinate in the ensuing dyadic contest. We conclude that bold behaviour is positively correlated to dominance in zebrafish and that boldness is not solely a consequence of social dominance. PMID:21858168

  5. Virality Prediction and Community Structure in Social Networks

    NASA Astrophysics Data System (ADS)

    Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

    2013-08-01

    How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.

  6. Virality prediction and community structure in social networks.

    PubMed

    Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

    2013-01-01

    How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.

  7. Virality Prediction and Community Structure in Social Networks

    PubMed Central

    Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

    2013-01-01

    How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications. PMID:23982106

  8. Social anxiety and the accuracy of predicted affect.

    PubMed

    Martin, Shannon M; Quirk, Stuart W

    2015-01-01

    Social anxiety is theorised to arise from sustained over-activation of a mammalian evolved system for detecting and responding to social threat with corresponding diminished opportunities for attaining the pleasure of safe attachments. Emotional forecasting data from two holidays were used to test the hypothesis that greater social anxiety would be associated with decreased expectations of positive affect (PA) and greater anticipated negative affect (NA) on a holiday marked by group celebration (St. Patrick's Day) while being associated with greater predicted PA for daters on a romantic holiday (Valentine's Day). Participants completed symptom reports, made affective forecasts and provided multiple affect reports throughout each holiday. Higher levels of social anxiety were associated with greater anticipated PA for Valentine's Day daters, but lower experienced PA on the holiday; this was not found for trait anxiety and depression. Alternatively, trait anxiety, depression and social anxiety were associated with less predicted PA for St. Patrick's Day, greater anticipated NA and diminished experienced PA/greater NA during the holiday. Results are discussed in light of perceived hope for rewarding safe emotional contact for those daters in contrast to the greater possibility for social threat associated with group celebration typical of St. Patrick's Day.

  9. Linking social and ecological systems to sustain coral reef fisheries.

    PubMed

    Cinner, Joshua E; McClanahan, Timothy R; Daw, Tim M; Graham, Nicholas A J; Maina, Joseph; Wilson, Shaun K; Hughes, Terence P

    2009-02-10

    The ecosystem goods and services provided by coral reefs are critical to the social and economic welfare of hundreds of millions of people, overwhelmingly in developing countries [1]. Widespread reef degradation is severely eroding these goods and services, but the socioeconomic factors shaping the ways that societies use coral reefs are poorly understood [2]. We examine relationships between human population density, a multidimensional index of socioeconomic development, reef complexity, and the condition of coral reef fish populations in five countries across the Indian Ocean. In fished sites, fish biomass was negatively related to human population density, but it was best explained by reef complexity and a U-shaped relationship with socioeconomic development. The biomass of reef fishes was four times lower at locations with intermediate levels of economic development than at locations with both low and high development. In contrast, average biomass inside fishery closures was three times higher than in fished sites and was not associated with socioeconomic development. Sustaining coral reef fisheries requires an integrated approach that uses tools such as protected areas to quickly build reef resources while also building capacities and capital in societies over longer time frames to address the complex underlying causes of reef degradation.

  10. PREDICTING INDIVIDUAL WELL-BEING THROUGH THE LANGUAGE OF SOCIAL MEDIA.

    PubMed

    Schwartz, H Andrew; Sap, Maarten; Kern, Margaret L; Eichstaedt, Johannes C; Kapelner, Adam; Agrawal, Megha; Blanco, Eduardo; Dziurzynski, Lukasz; Park, Gregory; Stillwell, David; Kosinski, Michal; Seligman, Martin E P; Ungar, Lyle H

    2016-01-01

    We present the task of predicting individual well-being, as measured by a life satisfaction scale, through the language people use on social media. Well-being, which encompasses much more than emotion and mood, is linked with good mental and physical health. The ability to quickly and accurately assess it can supplement multi-million dollar national surveys as well as promote whole body health. Through crowd-sourced ratings of tweets and Facebook status updates, we create message-level predictive models for multiple components of well-being. However, well-being is ultimately attributed to people, so we perform an additional evaluation at the user-level, finding that a multi-level cascaded model, using both message-level predictions and userlevel features, performs best and outperforms popular lexicon-based happiness models. Finally, we suggest that analyses of language go beyond prediction by identifying the language that characterizes well-being.

  11. Link prediction in a MeSH co-occurrence network: preliminary results.

    PubMed

    Kastrin, Andrej; Rindflesch, Thomas C; Hristovski, Dimitar

    2014-01-01

    Literature-based discovery (LBD) refers to automatic discovery of implicit relations from the scientific literature. Co-occurrence associations between biomedical concepts are commonly used in LBD. These co-occurrences can be represented as a network that consists of a set of nodes representing concepts and a set of edges representing their relationships (or links). In this paper we propose and evaluate a methodology for link prediction of implicit connections in a network of co-occurring Medical Subject Headings (MeSH®). The proposed approach is complementary to, and may augment, existing LBD methods. Link prediction was performed using Jaccard and Adamic-Adar similarity measures. The preliminary results showed high prediction performance, with area under the ROC curve of 0.78 and 0.82 for the two similarity measures, respectively.

  12. The Ecology of Social Learning in Animals and its Link with Intelligence.

    PubMed

    van Schaik, Carel; Graber, Sereina; Schuppli, Caroline; Burkart, Judith

    2017-01-09

    Classical ethology and behavioral ecology did not pay much attention to learning. However, studies of social learning in nature reviewed here reveal the near-ubiquity of reliance on social information for skill acquisition by developing birds and mammals. This conclusion strengthens the plausibility of the cultural intelligence hypothesis for the evolution of intelligence, which assumes that selection on social learning abilities automatically improves individual learning ability. Thus, intelligent species will generally be cultural species. Direct tests of the cultural intelligence hypothesis require good estimates of the amount and kind of social learning taking place in nature in a broad variety of species. These estimates are lacking so far. Here, we start the process of developing a functional classification of social learning, in the form of the social learning spectrum, which should help to predict the mechanisms of social learning involved. Once validated, the categories can be used to estimate the cognitive demands of social learning in the wild.

  13. Feature and motion-based gaze cuing is linked with reduced social competence.

    PubMed

    Hayward, Dana A; Ristic, Jelena

    2017-03-10

    Gaze following is a fundamental ability that plays an important role in human social function. However, the link between these two processes remains elusive. On the one hand, typically developing persons show robust gaze following in laboratory cuing tasks. On the other hand, investigations with individuals with autism suggest that reduced social competence in this population may partly reflect an atypical access to social information through attending to perceptual changes that normally accompany gaze shifts, like luminance or motion transients. Here we investigated if gaze cuing in typically developing individuals was modulated by similar task-irrelevant perceptual changes. In Experiment 1, a social gaze cue was presented with or without a luminance change. In Experiment 2, a social gaze cue was presented together with a motion cue. Both experiments indicated reduced magnitudes of gaze cuing in persons with low social competence on trials containing an irrelevant perceptual change. This suggests that similarly to individuals with autism, typically developing persons with low social competence also utilize idiosyncratic perceptual changes in the environment to access social content, revealing strong links between basic gaze following abilities and a range of social competence within typical individuals.

  14. Feature and motion-based gaze cuing is linked with reduced social competence

    PubMed Central

    Hayward, Dana A.; Ristic, Jelena

    2017-01-01

    Gaze following is a fundamental ability that plays an important role in human social function. However, the link between these two processes remains elusive. On the one hand, typically developing persons show robust gaze following in laboratory cuing tasks. On the other hand, investigations with individuals with autism suggest that reduced social competence in this population may partly reflect an atypical access to social information through attending to perceptual changes that normally accompany gaze shifts, like luminance or motion transients. Here we investigated if gaze cuing in typically developing individuals was modulated by similar task-irrelevant perceptual changes. In Experiment 1, a social gaze cue was presented with or without a luminance change. In Experiment 2, a social gaze cue was presented together with a motion cue. Both experiments indicated reduced magnitudes of gaze cuing in persons with low social competence on trials containing an irrelevant perceptual change. This suggests that similarly to individuals with autism, typically developing persons with low social competence also utilize idiosyncratic perceptual changes in the environment to access social content, revealing strong links between basic gaze following abilities and a range of social competence within typical individuals. PMID:28281642

  15. Emotion, rationality, and decision-making: how to link affective and social neuroscience with social theory.

    PubMed

    Verweij, Marco; Senior, Timothy J; Domínguez D, Juan F; Turner, Robert

    2015-01-01

    In this paper, we argue for a stronger engagement between concepts in affective and social neuroscience on the one hand, and theories from the fields of anthropology, economics, political science, and sociology on the other. Affective and social neuroscience could provide an additional assessment of social theories. We argue that some of the most influential social theories of the last four decades-rational choice theory, behavioral economics, and post-structuralism-contain assumptions that are inconsistent with key findings in affective and social neuroscience. We also show that another approach from the social sciences-plural rationality theory-shows greater compatibility with these findings. We further claim that, in their turn, social theories can strengthen affective and social neuroscience. The former can provide more precise formulations of the social phenomena that neuroscientific models have targeted, can help neuroscientists who build these models become more aware of their social and cultural biases, and can even improve the models themselves. To illustrate, we show how plural rationality theory can be used to further specify and test the somatic marker hypothesis. Thus, we aim to accelerate the much-needed merger of social theories with affective and social neuroscience.

  16. Emotion, rationality, and decision-making: how to link affective and social neuroscience with social theory

    PubMed Central

    Verweij, Marco; Senior, Timothy J.; Domínguez D., Juan F.; Turner, Robert

    2015-01-01

    In this paper, we argue for a stronger engagement between concepts in affective and social neuroscience on the one hand, and theories from the fields of anthropology, economics, political science, and sociology on the other. Affective and social neuroscience could provide an additional assessment of social theories. We argue that some of the most influential social theories of the last four decades—rational choice theory, behavioral economics, and post-structuralism—contain assumptions that are inconsistent with key findings in affective and social neuroscience. We also show that another approach from the social sciences—plural rationality theory—shows greater compatibility with these findings. We further claim that, in their turn, social theories can strengthen affective and social neuroscience. The former can provide more precise formulations of the social phenomena that neuroscientific models have targeted, can help neuroscientists who build these models become more aware of their social and cultural biases, and can even improve the models themselves. To illustrate, we show how plural rationality theory can be used to further specify and test the somatic marker hypothesis. Thus, we aim to accelerate the much-needed merger of social theories with affective and social neuroscience. PMID:26441506

  17. Social Influences on Executive Functions Development in Children and Adolescents: Steps Toward a Social Neuroscience of Predictive Adaptive Responses.

    PubMed

    Dishion, Thomas J

    2016-01-01

    This commentary discusses the findings and implications of four empirical papers that establish a reciprocal, longitudinal link between the social environment and executive functions from childhood to adolescence. Two future directions are suggested by this work. The first is a call for measurement research to clarify the nomological network of various measurements of self-regulation and executive functions across a variety of methods and procedures. The second new direction is to broaden the analysis of executive function to include a wider array of predictive adaptive responses to various environmental conditions, including those where youth are chronically marginalized or otherwise stressed. Findings from these studies suggest that the executive functions within the brain guide adaptation in both deviant as well as competent responses to the social environment. Understanding various forms of adaptation will enhance the potential for prevention as well as avoid iatrogenic intervention strategies with misinformed targets.

  18. Offspring social network structure predicts fitness in families.

    PubMed

    Royle, Nick J; Pike, Thomas W; Heeb, Philipp; Richner, Heinz; Kölliker, Mathias

    2012-12-22

    Social structures such as families emerge as outcomes of behavioural interactions among individuals, and can evolve over time if families with particular types of social structures tend to leave more individuals in subsequent generations. The social behaviour of interacting individuals is typically analysed as a series of multiple dyadic (pair-wise) interactions, rather than a network of interactions among multiple individuals. However, in species where parents feed dependant young, interactions within families nearly always involve more than two individuals simultaneously. Such social networks of interactions at least partly reflect conflicts of interest over the provision of costly parental investment. Consequently, variation in family network structure reflects variation in how conflicts of interest are resolved among family members. Despite its importance in understanding the evolution of emergent properties of social organization such as family life and cooperation, nothing is currently known about how selection acts on the structure of social networks. Here, we show that the social network structure of broods of begging nestling great tits Parus major predicts fitness in families. Although selection at the level of the individual favours large nestlings, selection at the level of the kin-group primarily favours families that resolve conflicts most effectively.

  19. Social networks predict gut microbiome composition in wild baboons

    PubMed Central

    Tung, Jenny; Barreiro, Luis B; Burns, Michael B; Grenier, Jean-Christophe; Lynch, Josh; Grieneisen, Laura E; Altmann, Jeanne; Alberts, Susan C; Blekhman, Ran; Archie, Elizabeth A

    2015-01-01

    Social relationships have profound effects on health in humans and other primates, but the mechanisms that explain this relationship are not well understood. Using shotgun metagenomic data from wild baboons, we found that social group membership and social network relationships predicted both the taxonomic structure of the gut microbiome and the structure of genes encoded by gut microbial species. Rates of interaction directly explained variation in the gut microbiome, even after controlling for diet, kinship, and shared environments. They therefore strongly implicate direct physical contact among social partners in the transmission of gut microbial species. We identified 51 socially structured taxa, which were significantly enriched for anaerobic and non-spore-forming lifestyles. Our results argue that social interactions are an important determinant of gut microbiome composition in natural animal populations—a relationship with important ramifications for understanding how social relationships influence health, as well as the evolution of group living. DOI: http://dx.doi.org/10.7554/eLife.05224.001 PMID:25774601

  20. Offspring social network structure predicts fitness in families

    PubMed Central

    Royle, Nick J.; Pike, Thomas W.; Heeb, Philipp; Richner, Heinz; Kölliker, Mathias

    2012-01-01

    Social structures such as families emerge as outcomes of behavioural interactions among individuals, and can evolve over time if families with particular types of social structures tend to leave more individuals in subsequent generations. The social behaviour of interacting individuals is typically analysed as a series of multiple dyadic (pair-wise) interactions, rather than a network of interactions among multiple individuals. However, in species where parents feed dependant young, interactions within families nearly always involve more than two individuals simultaneously. Such social networks of interactions at least partly reflect conflicts of interest over the provision of costly parental investment. Consequently, variation in family network structure reflects variation in how conflicts of interest are resolved among family members. Despite its importance in understanding the evolution of emergent properties of social organization such as family life and cooperation, nothing is currently known about how selection acts on the structure of social networks. Here, we show that the social network structure of broods of begging nestling great tits Parus major predicts fitness in families. Although selection at the level of the individual favours large nestlings, selection at the level of the kin-group primarily favours families that resolve conflicts most effectively. PMID:23097505

  1. Stock Price Change Rate Prediction by Utilizing Social Network Activities

    PubMed Central

    Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

    Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques. PMID:24790586

  2. Stock price change rate prediction by utilizing social network activities.

    PubMed

    Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

    Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

  3. Motivated malleability: Frontal cortical asymmetry predicts the susceptibility to social influence.

    PubMed

    Schnuerch, Robert; Pfattheicher, Stefan

    2017-07-16

    Humans, just as many other animals, regulate their behavior in terms of approaching stimuli associated with pleasure and avoiding stimuli linked to harm. A person's current and chronic motivational direction - that is, approach versus avoidance orientation - is reliably reflected in the asymmetry of frontal cortical low-frequency oscillations. Using resting electroencephalography (EEG), we show that frontal asymmetry is predictive of the tendency to yield to social influence: Stronger right- than left-side frontolateral activation during a resting-state session prior to the experiment was robustly associated with a stronger inclination to adopt a peer group's judgments during perceptual decision-making (Study 1). We posit that this reflects the role of a person's chronic avoidance orientation in socially adjusted behavior. This claim was strongly supported by additional survey investigations (Studies 2a, 2b, 2c), all of which consistently revealed that trait avoidance was positively linked to the susceptibility to social influence. The present contribution thus stresses the relevance of chronic avoidance orientation in social conformity, refining (yet not contradicting) the longstanding view that socially influenced behavior is motivated by approach-related goals. Moreover, our findings valuably underscore and extend our knowledge on the association between frontal cortical asymmetry and a variety of psychological variables.

  4. Social network models predict movement and connectivity in ecological landscapes

    USGS Publications Warehouse

    Fletcher, R.J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, W.M.

    2011-01-01

    Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

  5. Social network models predict movement and connectivity in ecological landscapes

    PubMed Central

    Fletcher, Robert J.; Acevedo, Miguel A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, Wiley M.

    2011-01-01

    Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data. PMID:22084081

  6. [Aggregation of social deficits and psychiatric disorders in parents of children with autism: toward a temperamental link?].

    PubMed

    Goussé, V; Galéra, C; Bouvard, M; Michel, G

    2011-04-01

    ), consistent with the hypothesis that there is a link between the broad phenotype and psychopathological problems. This paper reviews this issue in the two domains of study described and presents a hypothesis to account for the possible link between the presence of the broad phenotype - or more specifically, of social deficits - and the more frequent occurrence of psychological problems in the families of autistic individuals. The notion of temperament (Garon et al., 2009) is proposed and considered to present essential characteristics that might account for this relationship: indeed, temperament is associated with notions of IQ, psychopathology and social function and could potentially be used as a predictive variable in affected individuals. Finally, the link between temperament and psychopathology in the relatives of affected individuals may be reflected in the presence of cognitive peculiarities more specifically linked to socioemotional dysfunction (Losh and Piven, 2007). Copyright © 2010. Published by Elsevier Masson SAS.

  7. DNA methylation of the oxytocin receptor gene predicts neural response to ambiguous social stimuli

    PubMed Central

    Jack, Allison; Connelly, Jessica J.; Morris, James P.

    2012-01-01

    Oxytocin and its receptor (OXTR) play an important role in a variety of social perceptual and affiliative processes. Individual variability in social information processing likely has a strong heritable component, and as such, many investigations have established an association between common genetic variants of OXTR and variability in the social phenotype. However, to date, these investigations have primarily focused only on changes in the sequence of DNA without considering the role of epigenetic factors. DNA methylation is an epigenetic mechanism by which cells control transcription through modification of chromatin structure. DNA methylation of OXTR decreases expression of the gene and high levels of methylation have been associated with autism spectrum disorders (ASD). This link between epigenetic variability and social phenotype allows for the possibility that social processes are under epigenetic control. We hypothesized that the level of DNA methylation of OXTR would predict individual variability in social perception. Using the brain's sensitivity to displays of animacy as a neural endophenotype of social perception, we found significant associations between the degree of OXTR methylation and brain activity evoked by the perception of animacy. Our results suggest that consideration of DNA methylation may substantially improve our ability to explain individual differences in imaging genetic association studies. PMID:23087634

  8. Change in BMI Accurately Predicted by Social Exposure to Acquaintances

    PubMed Central

    Oloritun, Rahman O.; Ouarda, Taha B. M. J.; Moturu, Sai; Madan, Anmol; Pentland, Alex (Sandy); Khayal, Inas

    2013-01-01

    Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO) method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC) and R2. This study found a model that explains 68% (p<0.0001) of the variation in change in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as close friends. PMID

  9. Change in BMI accurately predicted by social exposure to acquaintances.

    PubMed

    Oloritun, Rahman O; Ouarda, Taha B M J; Moturu, Sai; Madan, Anmol; Pentland, Alex Sandy; Khayal, Inas

    2013-01-01

    Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO) method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC) and R(2). This study found a model that explains 68% (p<0.0001) of the variation in change in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as close friends.

  10. Investigation of Performance Prediction Methods for a Short-Range Over-the-Horizon Radio Link.

    DTIC Science & Technology

    Many techniques are available that predict the median received signal level (RSL) for a long-range diffraction propagation mode or troposcatter ...tactical troposcatter radio set AN/TRC-97A. A 46.2 kilometer radio link, using the AN/TRC-97A, from Oxford, Ohio to Blue Ash, Ohio was used to...investigate the different performance prediction methods. Three diffraction propagation modesl and five troposcatter propagation models were investigated

  11. Linking Socioeconomic Status to Social Cognitive Career Theory Factors: A Partial Least Squares Path Modeling Analysis

    ERIC Educational Resources Information Center

    Huang, Jie-Tsuen; Hsieh, Hui-Hsien

    2011-01-01

    The purpose of this study was to investigate the contributions of socioeconomic status (SES) in predicting social cognitive career theory (SCCT) factors. Data were collected from 738 college students in Taiwan. The results of the partial least squares (PLS) analyses indicated that SES significantly predicted career decision self-efficacy (CDSE);…

  12. Predicting childhood obesity prevention behaviors using social cognitive theory.

    PubMed

    Sharma, Manoj; Wagner, Donald I; Wilkerson, Janice

    Four commonly suggested public health strategies to combat childhood obesity are limiting television viewing, encouraging daily physical activity, increasing fruit and vegetable intake, and increasing water consumption. This study examined the extent to which selected social cognitive theory constructs can predict these four behaviors in upper elementary children. A 52-item valid and reliable scale was administered to 159 fifth graders. Minutes of physical activity was predicted by self-efficacy to exercise and number of times taught at school (R2 = 0.072). Hours of TV watching were predicted by number of times taught about healthy eating at school and self-control through goal setting (R2 = 0.055). Glasses of water consumed were predicted by expectations for drinking water (R2 = 0.091). Servings of fruits and vegetables consumed were predicted by self-efficacy of eating fruits and vegetables (R2 = 0.137). Social cognitive theory offers a practically useful framework for designing primary prevention interventions to reduce childhood obesity.

  13. Linking communities to formal health care providers through village health teams in rural Uganda: lessons from linking social capital.

    PubMed

    Musinguzi, Laban Kashaija; Turinawe, Emmanueil Benon; Rwemisisi, Jude T; de Vries, Daniel H; Mafigiri, David K; Muhangi, Denis; de Groot, Marije; Katamba, Achilles; Pool, Robert

    2017-01-11

    Community-based programmes, particularly community health workers (CHWs), have been portrayed as a cost-effective alternative to the shortage of health workers in low-income countries. Usually, literature emphasises how easily CHWs link and connect communities to formal health care services. There is little evidence in Uganda to support or dispute such claims. Drawing from linking social capital framework, this paper examines the claim that village health teams (VHTs), as an example of CHWs, link and connect communities with formal health care services. Data were collected through ethnographic fieldwork undertaken as part of a larger research program in Luwero District, Uganda, between 2012 and 2014. The main methods of data collection were participant observation in events organised by VHTs. In addition, a total of 91 in-depth interviews and 42 focus group discussions (FGD) were conducted with adult community members as part of the larger project. After preliminary analysis of the data, we conducted an additional six in-depth interviews and three FGD with VHTs and four FGD with community members on the role of VHTs. Key informant interviews were conducted with local government staff, health workers, local leaders, and NGO staff with health programs in Luwero. Thematic analysis was used during data analysis. The ability of VHTs to link communities with formal health care was affected by the stakeholders' perception of their roles. Community members perceive VHTs as working for and under instructions of "others", which makes them powerless in the formal health care system. One of the challenges associated with VHTs' linking roles is support from the government and formal health care providers. Formal health care providers perceived VHTs as interested in special recognition for their services yet they are not "experts". For some health workers, the introduction of VHTs is seen as a ploy by the government to control people and hide its inability to provide health

  14. Use of social indices to predict reproductive success in canvasbacks

    USGS Publications Warehouse

    Serie, J.R.; Cowardin, L.M.

    1990-01-01

    We correlated temporal changes in social groupings of canvasbacks (Aythya valisineria) breeding near Minnedosa, Manitoba, with an independent estimate of hen success during 1974-80. Roadside counts of pairs, lone males, and flocked males were made along transects at 5-day intervals, normalized to percentages to allow comparisons among years, and plotted to obtain measurements of selected areas between and under the curves. An estimate of hen success was regressed on these selected graph areas each year to derive a predictive equation. Graph areas (social indices) determined from temporal changes in the proportion of pairs, lone males, and flocked males correlated (ri?? = 0.69-0.93) with hen success. This technique avoids the need for pair counts, nest searches, and brood counts and provides managers with a useful index to evaluate local management practices and to predict yearly production in time for setting hunting regulations.

  15. When opportunity meets motivation: Neural engagement during social approach is linked to high approach motivation.

    PubMed

    Radke, Sina; Seidel, Eva-Maria; Eickhoff, Simon B; Gur, Ruben C; Schneider, Frank; Habel, Ute; Derntl, Birgit

    2016-02-15

    Social rewards are processed by the same dopaminergic-mediated brain networks as non-social rewards, suggesting a common representation of subjective value. Individual differences in personality and motivation influence the reinforcing value of social incentives, but it remains open whether the pursuit of social incentives is analogously supported by the neural reward system when positive social stimuli are connected to approach behavior. To test for a modulation of neural activation by approach motivation, individuals with high and low approach motivation (BAS) completed implicit and explicit social approach-avoidance paradigms during fMRI. High approach motivation was associated with faster implicit approach reactions as well as a trend for higher approach ratings, indicating increased approach tendencies. Implicit and explicit positive social approach was accompanied by stronger recruitment of the nucleus accumbens, middle cingulate cortex, and (pre-)cuneus for individuals with high compared to low approach motivation. These results support and extend prior research on social reward processing, self-other distinctions and affective judgments by linking approach motivation to the engagement of reward-related circuits during motivational reactions to social incentives. This interplay between motivational preferences and motivational contexts might underlie the rewarding experience during social interactions.

  16. Improving link prediction in complex networks by adaptively exploiting multiple structural features of networks

    NASA Astrophysics Data System (ADS)

    Ma, Chuang; Bao, Zhong-Kui; Zhang, Hai-Feng

    2017-10-01

    So far, many network-structure-based link prediction methods have been proposed. However, these methods only highlight one or two structural features of networks, and then use the methods to predict missing links in different networks. The performances of these existing methods are not always satisfied in all cases since each network has its unique underlying structural features. In this paper, by analyzing different real networks, we find that the structural features of different networks are remarkably different. In particular, even in the same network, their inner structural features are utterly different. Therefore, more structural features should be considered. However, owing to the remarkably different structural features, the contributions of different features are hard to be given in advance. Inspired by these facts, an adaptive fusion model regarding link prediction is proposed to incorporate multiple structural features. In the model, a logistic function combing multiple structural features is defined, then the weight of each feature in the logistic function is adaptively determined by exploiting the known structure information. Last, we use the "learnt" logistic function to predict the connection probabilities of missing links. According to our experimental results, we find that the performance of our adaptive fusion model is better than many similarity indices.

  17. Accurate similarity index based on activity and connectivity of node for link prediction

    NASA Astrophysics Data System (ADS)

    Li, Longjie; Qian, Lvjian; Wang, Xiaoping; Luo, Shishun; Chen, Xiaoyun

    2015-05-01

    Recent years have witnessed the increasing of available network data; however, much of those data is incomplete. Link prediction, which can find the missing links of a network, plays an important role in the research and analysis of complex networks. Based on the assumption that two unconnected nodes which are highly similar are very likely to have an interaction, most of the existing algorithms solve the link prediction problem by computing nodes' similarities. The fundamental requirement of those algorithms is accurate and effective similarity indices. In this paper, we propose a new similarity index, namely similarity based on activity and connectivity (SAC), which performs link prediction more accurately. To compute the similarity between two nodes, this index employs the average activity of these two nodes in their common neighborhood and the connectivities between them and their common neighbors. The higher the average activity is and the stronger the connectivities are, the more similar the two nodes are. The proposed index not only commendably distinguishes the contributions of paths but also incorporates the influence of endpoints. Therefore, it can achieve a better predicting result. To verify the performance of SAC, we conduct experiments on 10 real-world networks. Experimental results demonstrate that SAC outperforms the compared baselines.

  18. Participatory research with youth: idealising safe social spaces or building transformative links in difficult environments?

    PubMed

    Vaughan, Cathy

    2014-01-01

    Freire's theory of social change informs analysis of youth-focused participatory research, with researchers describing links between participation and young people's critical thinking. There is less analysis of how youth move from the safe social space of a participatory research project to take health-promoting action in difficult real-world contexts. This article analyses a project conducted with Papua New Guinean youth, disrupting assumptions that critical thinking inevitably leads to critical action on health. Findings suggest the need to shift the focus of participatory research from supporting 'safe social spaces' to supporting 'transformative action in context' to concretely contribute to improving youth health.

  19. Learning to Predict Social Influence in Complex Networks

    DTIC Science & Technology

    2012-03-29

    information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and...maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect...important steps to construct basic methods for learning to predict social influence in complex networks. All of them have been published in

  20. Childhood Social Anxiety and Social Support-Seeking: Distinctive Links with Perceived Support from Teachers

    ERIC Educational Resources Information Center

    Leeves, Sylvia; Banerjee, Robin

    2014-01-01

    Social support-seeking is recognised as an important strategy used by children to cope with negative emotions. However, there are important gaps in our knowledge about children's perceptions of different sources of social support, and the associations that these perceptions have with individual differences in socio-emotional functioning. The…

  1. Childhood Social Anxiety and Social Support-Seeking: Distinctive Links with Perceived Support from Teachers

    ERIC Educational Resources Information Center

    Leeves, Sylvia; Banerjee, Robin

    2014-01-01

    Social support-seeking is recognised as an important strategy used by children to cope with negative emotions. However, there are important gaps in our knowledge about children's perceptions of different sources of social support, and the associations that these perceptions have with individual differences in socio-emotional functioning. The…

  2. Cognitive conflict links behavioral inhibition and social problem solving during social exclusion in childhood.

    PubMed

    Lahat, Ayelet; Walker, Olga L; Lamm, Connie; Degnan, Kathryn A; Henderson, Heather A; Fox, Nathan A

    2014-01-01

    Behavioral inhibition (BI) is a temperament characterized by heightened negative affect and social reticence to unfamiliar peers. In a longitudinal study, 291 infants were assessed for BI at 24 and 36 months of age. At age 7, N2 amplitude was measured during a Flanker task. Also at age 7, children experienced social exclusion in the lab during an interaction with an unfamiliar peer and an experimenter. Our findings indicate that children characterized as high in BI, relative to those low in BI, had larger (i.e., more negative) N2 amplitudes. Additionally, among children with a large N2, BI was positively related to withdrawal and negatively related to assertiveness during social exclusion. These findings suggest that variations in conflict detection among behaviorally inhibited children plays a role in their social behavior during stressful social situations.

  3. Social learning through prediction error in the brain

    NASA Astrophysics Data System (ADS)

    Joiner, Jessica; Piva, Matthew; Turrin, Courtney; Chang, Steve W. C.

    2017-06-01

    Learning about the world is critical to survival and success. In social animals, learning about others is a necessary component of navigating the social world, ultimately contributing to increasing evolutionary fitness. How humans and nonhuman animals represent the internal states and experiences of others has long been a subject of intense interest in the developmental psychology tradition, and, more recently, in studies of learning and decision making involving self and other. In this review, we explore how psychology conceptualizes the process of representing others, and how neuroscience has uncovered correlates of reinforcement learning signals to explore the neural mechanisms underlying social learning from the perspective of representing reward-related information about self and other. In particular, we discuss self-referenced and other-referenced types of reward prediction errors across multiple brain structures that effectively allow reinforcement learning algorithms to mediate social learning. Prediction-based computational principles in the brain may be strikingly conserved between self-referenced and other-referenced information.

  4. Web-Based Knowledge Exchange through Social Links in the Workplace

    ERIC Educational Resources Information Center

    Filipowski, Tomasz; Kazienko, Przemyslaw; Brodka, Piotr; Kajdanowicz, Tomasz

    2012-01-01

    Knowledge exchange between employees is an essential feature of recent commercial organisations on the competitive market. Based on the data gathered by various information technology (IT) systems, social links can be extracted and exploited in knowledge exchange systems of a new kind. Users of such a system ask their queries and the system…

  5. Trait and Social Influences in the Links among Adolescent Attachment, Depressive Symptoms, and Coping

    ERIC Educational Resources Information Center

    Merlo, Lisa J.; Lakey, Brian

    2007-01-01

    Attachment insecurity and maladaptive coping are associated with depression in adolescence; however, it is unclear whether these links primarily reflect stable individual differences among teens (trait influences), experiential differences in their interactions with relationship partners (social influences) or both. In this study, teens (ages…

  6. Linking Teacher Socialization Research with a PETE Program: Insights from Beginning and Experienced Teachers

    ERIC Educational Resources Information Center

    MacPhail, Ann; Hartley, Therese

    2016-01-01

    The purpose of this study is to explore the extent to which beginning and experienced teachers differed in their perceptions of shaping school forces and their being shaped by school forces. The findings allow the authors to examine the link between teacher socialization research and practice in a physical education teacher education (PETE)…

  7. The Link between Emotion Regulation, Social Functioning, and Depression in Boys with ASD

    ERIC Educational Resources Information Center

    Pouw, Lucinda B. C.; Rieffe, Carolien; Stockmann, Lex; Gadow, Kenneth D.

    2013-01-01

    Purpose: Symptoms of depression are common in children and adolescents with an autism spectrum disorder (ASD), but information about underlying developmental factors is limited. Depression is often linked to aspects of emotional functioning such as coping strategies, but in children with ASD difficulties with social interactions are also a likely…

  8. A Dual-Process Model of the Alcohol-Behavior Link for Social Drinking

    ERIC Educational Resources Information Center

    Moss, Antony C.; Albery, Ian P.

    2009-01-01

    A dual-process model of the alcohol-behavior link is presented, synthesizing 2 of the major social-cognitive approaches: expectancy and myopia theories. Substantial evidence has accrued to support both of these models, and recent neurocognitive models of the effects of alcohol on thought and behavior have provided evidence to support both as well.…

  9. Web-Based Knowledge Exchange through Social Links in the Workplace

    ERIC Educational Resources Information Center

    Filipowski, Tomasz; Kazienko, Przemyslaw; Brodka, Piotr; Kajdanowicz, Tomasz

    2012-01-01

    Knowledge exchange between employees is an essential feature of recent commercial organisations on the competitive market. Based on the data gathered by various information technology (IT) systems, social links can be extracted and exploited in knowledge exchange systems of a new kind. Users of such a system ask their queries and the system…

  10. Trait and Social Influences in the Links among Adolescent Attachment, Depressive Symptoms, and Coping

    ERIC Educational Resources Information Center

    Merlo, Lisa J.; Lakey, Brian

    2007-01-01

    Attachment insecurity and maladaptive coping are associated with depression in adolescence; however, it is unclear whether these links primarily reflect stable individual differences among teens (trait influences), experiential differences in their interactions with relationship partners (social influences) or both. In this study, teens (ages…

  11. A Dual-Process Model of the Alcohol-Behavior Link for Social Drinking

    ERIC Educational Resources Information Center

    Moss, Antony C.; Albery, Ian P.

    2009-01-01

    A dual-process model of the alcohol-behavior link is presented, synthesizing 2 of the major social-cognitive approaches: expectancy and myopia theories. Substantial evidence has accrued to support both of these models, and recent neurocognitive models of the effects of alcohol on thought and behavior have provided evidence to support both as well.…

  12. Linking Teacher Socialization Research with a PETE Program: Insights from Beginning and Experienced Teachers

    ERIC Educational Resources Information Center

    MacPhail, Ann; Hartley, Therese

    2016-01-01

    The purpose of this study is to explore the extent to which beginning and experienced teachers differed in their perceptions of shaping school forces and their being shaped by school forces. The findings allow the authors to examine the link between teacher socialization research and practice in a physical education teacher education (PETE)…

  13. Linking Academic Social Environments, Ego-Identity Formation, Ego Virtues, and Academic Success

    ERIC Educational Resources Information Center

    Good, Marie; Adams, Gerald R.

    2008-01-01

    This study used Structural Equation Modeling to test an Eriksonian conceptual model linking academic social environments (relationships with faculty and fellow students), ego-identity formation, ego virtues, and academic success. Participants included 765 first-year students at a university in southern Ontario, Canada. Results indicated that…

  14. The Link between Emotion Regulation, Social Functioning, and Depression in Boys with ASD

    ERIC Educational Resources Information Center

    Pouw, Lucinda B. C.; Rieffe, Carolien; Stockmann, Lex; Gadow, Kenneth D.

    2013-01-01

    Purpose: Symptoms of depression are common in children and adolescents with an autism spectrum disorder (ASD), but information about underlying developmental factors is limited. Depression is often linked to aspects of emotional functioning such as coping strategies, but in children with ASD difficulties with social interactions are also a likely…

  15. Proposed parameters of specific rain attenuation prediction for Free Space Optics link operating in tropical region

    NASA Astrophysics Data System (ADS)

    Suriza, A. Z.; Md Rafiqul, Islam; Wajdi, A. K.; Naji, A. W.

    2013-03-01

    As the demand for higher and unlimited bandwidth for communication channel is increased, Free Space Optics (FSO) is a good alternative solution. As it is protocol transparent, easy to install, cost effective and have capabilities like fiber optics, its demand rises very fast. Weather condition, however is the limiting factor for FSO link. In the temperate region the major blockage for FSO link feasibility is fog. In the tropical region high rainfall rate is expected to be the major drawback of FSO link availability. Rain attenuation is the most significant to influence FSO link availability in tropical region. As for now the available k and α values are developed using data from temperate regions. Therefore, the objective of this paper is to propose new parameters for specific rain attenuation prediction model that represents tropical weather condition. The proposed values are derived from data measured in Malaysia and using methods recommended by ITU-R.

  16. Performance prediction of a synchronization link for distributed aerospace wireless systems.

    PubMed

    Wang, Wen-Qin; Shao, Huaizong

    2013-01-01

    For reasons of stealth and other operational advantages, distributed aerospace wireless systems have received much attention in recent years. In a distributed aerospace wireless system, since the transmitter and receiver placed on separated platforms which use independent master oscillators, there is no cancellation of low-frequency phase noise as in the monostatic cases. Thus, high accurate time and frequency synchronization techniques are required for distributed wireless systems. The use of a dedicated synchronization link to quantify and compensate oscillator frequency instability is investigated in this paper. With the mathematical statistical models of phase noise, closed-form analytic expressions for the synchronization link performance are derived. The possible error contributions including oscillator, phase-locked loop, and receiver noise are quantified. The link synchronization performance is predicted by utilizing the knowledge of the statistical models, system error contributions, and sampling considerations. Simulation results show that effective synchronization error compensation can be achieved by using this dedicated synchronization link.

  17. Performance Prediction of a Synchronization Link for Distributed Aerospace Wireless Systems

    PubMed Central

    Shao, Huaizong

    2013-01-01

    For reasons of stealth and other operational advantages, distributed aerospace wireless systems have received much attention in recent years. In a distributed aerospace wireless system, since the transmitter and receiver placed on separated platforms which use independent master oscillators, there is no cancellation of low-frequency phase noise as in the monostatic cases. Thus, high accurate time and frequency synchronization techniques are required for distributed wireless systems. The use of a dedicated synchronization link to quantify and compensate oscillator frequency instability is investigated in this paper. With the mathematical statistical models of phase noise, closed-form analytic expressions for the synchronization link performance are derived. The possible error contributions including oscillator, phase-locked loop, and receiver noise are quantified. The link synchronization performance is predicted by utilizing the knowledge of the statistical models, system error contributions, and sampling considerations. Simulation results show that effective synchronization error compensation can be achieved by using this dedicated synchronization link. PMID:23970828

  18. Linking social drivers of marine debris with actual marine debris on beaches.

    PubMed

    Slavin, Chris; Grage, Anna; Campbell, Marnie L

    2012-08-01

    The drivers (social) and pressures (physical) of marine debris have typically been examined separately. We redress this by using social and beach surveys at nine Tasmanian beaches, across three coastlines and within three categories of urbanisation, to examine whether people acknowledge that their actions contribute to the issue of marine debris, and whether these social drivers are reflected in the amount of marine debris detected on beaches. A large proportion (75%) of survey participants do not litter at beaches; with age, gender, income and residency influencing littering behaviour. Thus, participants recognise that littering at beaches is a problem. This social trend was reflected in the small amounts of debris that were detected. Furthermore, the amount of debris was not statistically influenced by the degree of beach urbanisation, the coastline sampled, or the proximity to beach access points. By linking social and physical aspects of this issue, management outcomes can be improved. Copyright © 2012 Elsevier Ltd. All rights reserved.

  19. Bechstein's bats maintain individual social links despite a complete reorganisation of their colony structure

    NASA Astrophysics Data System (ADS)

    Baigger, A.; Perony, N.; Reuter, M.; Leinert, V.; Melber, M.; Grünberger, S.; Fleischmann, D.; Kerth, G.

    2013-09-01

    Several social mammals, including elephants and some primates, whales and bats, live in multilevel societies that form temporary subgroups. Despite these fission-fusion dynamics, group members often maintain long-term bonds. However, it is unclear whether such individual links and the resulting stable social subunits continue to exist after a complete reorganisation of a society, e.g. following a population crash. Here, we employed a weighted network analysis on 7,109 individual roosting records collected over 4 years in a wild Bechstein's bat colony. We show that, in response to a strong population decline, the colony's two stable social subunits fused into a non-modular social network. Nevertheless, in the first year after the crash, long-term bonds were still detectable, suggesting that the bats remembered previous individual relationships. Our findings are important for understanding the flexibility of animal societies in the face of dramatic changes and for the conservation of social mammals with declining populations.

  20. Variation in the X-Linked EFHC2 Gene Is Associated with Social Cognitive Abilities in Males

    PubMed Central

    Startin, Carla M.; Fiorentini, Chiara; de Haan, Michelle; Skuse, David H.

    2015-01-01

    Females outperform males on many social cognitive tasks. X-linked genes may contribute to this sex difference. Males possess one X chromosome, while females possess two X chromosomes. Functional variations in X-linked genes are therefore likely to impact more on males than females. Previous studies of X-monosomic women with Turner syndrome suggest a genetic association with facial fear recognition abilities at Xp11.3, specifically at a single nucleotide polymorphism (SNP rs7055196) within the EFHC2 gene. Based on a strong hypothesis, we investigated an association between variation at SNP rs7055196 and facial fear recognition and theory of mind abilities in males. As predicted, males possessing the G allele had significantly poorer facial fear detection accuracy and theory of mind abilities than males possessing the A allele (with SNP variant accounting for up to 4.6% of variance). Variation in the X-linked EFHC2 gene at SNP rs7055196 is therefore associated with social cognitive abilities in males. PMID:26107779

  1. Variation in the X-linked EFHC2 gene is associated with social cognitive abilities in males.

    PubMed

    Startin, Carla M; Fiorentini, Chiara; de Haan, Michelle; Skuse, David H

    2015-01-01

    Females outperform males on many social cognitive tasks. X-linked genes may contribute to this sex difference. Males possess one X chromosome, while females possess two X chromosomes. Functional variations in X-linked genes are therefore likely to impact more on males than females. Previous studies of X-monosomic women with Turner syndrome suggest a genetic association with facial fear recognition abilities at Xp11.3, specifically at a single nucleotide polymorphism (SNP rs7055196) within the EFHC2 gene. Based on a strong hypothesis, we investigated an association between variation at SNP rs7055196 and facial fear recognition and theory of mind abilities in males. As predicted, males possessing the G allele had significantly poorer facial fear detection accuracy and theory of mind abilities than males possessing the A allele (with SNP variant accounting for up to 4.6% of variance). Variation in the X-linked EFHC2 gene at SNP rs7055196 is therefore associated with social cognitive abilities in males.

  2. Conceptual disorganization weakens links in cognitive pathways: Disentangling neurocognition, social cognition, and metacognition in schizophrenia.

    PubMed

    Minor, Kyle S; Marggraf, Matthew P; Davis, Beshaun J; Luther, Lauren; Vohs, Jenifer L; Buck, Kelly D; Lysaker, Paul H

    2015-12-01

    Disentangling links between neurocognition, social cognition, and metacognition offers the potential to improve interventions for these cognitive processes. Disorganized symptoms have shown promise for explaining the limiting relationship that neurocognition holds with both social cognition and metacognition. In this study, primary aims included: 1) testing whether conceptual disorganization, a specific disorganized symptom, moderated relationships between cognitive processes, and 2) examining the level of conceptual disorganization necessary for links between cognitive processes to break down. To accomplish these aims, comprehensive assessments of conceptual disorganization, neurocognition, social cognition, and metacognition were administered to 67 people with schizophrenia-spectrum disorders. We found that conceptual disorganization significantly moderated the relationship between neurocognition and metacognition, with links between cognitive processes weakening when conceptual disorganization is present even at minimal levels of severity. There was no evidence that conceptual disorganization-or any other specific disorganized symptom-drove the limiting relationship of neurocognition on social cognition. Based on our findings, conceptual disorganization appears to be a critical piece of the puzzle when disentangling the relationship between neurocognition and metacognition. Roles of specific disorganized symptoms in the neurocognition - social cognition relationship were less clear. Findings from this study suggest that disorganized symptoms are an important treatment consideration when aiming to improve cognitive impairments.

  3. Social isolation induces autophagy in the mouse mammary gland: link to increased mammary cancer risk.

    PubMed

    Sumis, Allison; Cook, Katherine L; Andrade, Fabia O; Hu, Rong; Kidney, Emma; Zhang, Xiyuan; Kim, Dominic; Carney, Elissa; Nguyen, Nguyen; Yu, Wei; Bouker, Kerrie B; Cruz, Idalia; Clarke, Robert; Hilakivi-Clarke, Leena

    2016-10-01

    Social isolation is a strong predictor of early all-cause mortality and consistently increases breast cancer risk in both women and animal models. Because social isolation increases body weight, we compared its effects to those caused by a consumption of obesity-inducing diet (OID) in C57BL/6 mice. Social isolation and OID impaired insulin and glucose sensitivity. In socially isolated, OID-fed mice (I-OID), insulin resistance was linked to reduced Pparg expression and increased neuropeptide Y levels, but in group-housed OID fed mice (G-OID), it was linked to increased leptin and reduced adiponectin levels, indicating that the pathways leading to insulin resistance are different. Carcinogen-induced mammary tumorigenesis was significantly higher in I-OID mice than in the other groups, but cancer risk was also increased in socially isolated, control diet-fed mice (I-C) and G-OID mice compared with that in controls. Unfolded protein response (UPR) signaling (GRP78; IRE1) was upregulated in the mammary glands of OID-fed mice, but not in control diet-fed, socially isolated I-C mice. In contrast, expression of BECLIN1, ATG7 and LC3II were increased, and p62 was downregulated by social isolation, indicating increased autophagy. In the mammary glands of socially isolated mice, but not in G-OID mice, mRNA expressions of p53 and the p53-regulated autophagy inducer Dram1 were upregulated, and nuclear p53 staining was strong. Our findings further indicated that autophagy and tumorigenesis were not increased in Atg7(+/-) mice kept in social isolation and fed OID. Thus, social isolation may increase breast cancer risk by inducing autophagy, independent of changes in body weight.

  4. Full Scale Rotor Aeroacoustic Predictions and the Link to Model Scale Rotor Data

    NASA Technical Reports Server (NTRS)

    Boyd, D. Douglas, Jr.; Burley, Casey L.; Conner, David A.

    2004-01-01

    The NASA Aeroacoustic Prediction System (NAPS) is used to establish a link between model-scale and full-scale rotor predictions and is partially validated against measured wind tunnel and flight aeroacoustic data. The prediction approach of NAPS couples a comprehensive rotorcraft analysis with acoustic source noise and propagation codes. The comprehensive analysis selected for this study is CAMRAD-II, which provides the performance/trim/wake solution for a given rotor or flight condition. The post-trim capabilities of CAMRAD-II are used to compute high-resolution sectional airloads for the acoustic tone noise analysis, WOPMOD. The tone noise is propagated to observers on the ground with the propagation code, RNM (Rotor Noise Model). Aeroacoustic predictions are made with NAPS for an isolated rotor and compared to results of the second Harmonic Aeroacoustic Rotor Test (HART-II) program, which tested a 40% dynamically and Mach-scaled BO-105 main rotor at the DNW. The NAPS is validated with comparisons for three rotor conditions: a baseline condition and two Higher Harmonic Control (HHC) conditions. To establish a link between model and full-scale rotor predictions, a full-scale BO-105 main rotor input deck for NAPS is created from the 40% scale rotor input deck. The full-scale isolated rotor predictions are then compared to the model predictions. The comparisons include aerodynamic loading, acoustic levels, and acoustic pressure time histories for each of the three conditions. With this link established, full-scale predictions are made for a range of descent flight conditions and compared with measured trends from the recent Rotorcraft Operational Noise Abatement Procedures (RONAP) flight test conducted by DLR and ONERA. Additionally, the effectiveness of two HHC conditions from the HART-II program is demonstrated for the full-scale rotor in flight.

  5. Social/Ethical Issues in Predictive Insider Threat Monitoring

    SciTech Connect

    Greitzer, Frank L.; Frincke, Deborah A.; Zabriskie, Mariah

    2011-01-01

    Combining traditionally monitored cybersecurity data with other kinds of organizational data is one option for inferring the motivations of individuals, which may in turn allow early prediction and mitigation of insider threats. While unproven, some researchers believe that this combination of data may yield better results than either cybersecurity or organizational data would in isolation. However, this nontraditional approach creates a potential conflict between goals, such as conflicts between organizational security improvements and individual privacy considerations. There are many facets to debate. Should warning signs of a potential malicious insider be addressed before a malicious event has occurred to prevent harm to the organization and discourage the insider from violating the organization’s rules? Would intervention violate employee trust or legal guidelines? What about the possibilities of misuse? Predictive approaches cannot be validated a priori; false accusations can affect the career of the accused; and collection/monitoring of certain types of data may affect employee morale. In this chapter, we explore some of the social and ethical issues stemming from predictive insider threat monitoring and discuss ways that a predictive modeling approach brings to the forefront social and ethical issues that should be considered and resolved by stakeholders and communities of interest.

  6. Personality predicts social dominance in male domestic fowl.

    PubMed

    Favati, Anna; Leimar, Olof; Løvlie, Hanne

    2014-01-01

    Individuals in social species commonly form dominance relationships, where dominant individuals enjoy greater access to resources compared to subordinates. A range of factors such as sex, age, body size and prior experiences has to varying degrees been observed to affect the social status an individual obtains. Recent work on animal personality (i.e. consistent variation in behavioural responses of individuals) demonstrates that personality can co-vary with social status, suggesting that also behavioural variation can play an important role in establishment of status. We investigated whether personality could predict the outcome of duels between pairs of morphologically matched male domestic fowl (Gallus gallus domesticus), a species where individuals readily form social hierarchies. We found that males that more quickly explored a novel arena, or remained vigilant for a longer period following the playback of a warning call were more likely to obtain a dominant position. These traits were uncorrelated to each other and were also uncorrelated to aggression during the initial part of the dominance-determining duel. Our results indicate that several behavioural traits independently play a role in the establishment of social status, which in turn can have implications for the reproductive success of different personality types.

  7. Predicting fate from early connectivity in a social network.

    PubMed

    McDonald, David B

    2007-06-26

    In the long-tailed manakin (Chiroxiphia linearis), a long-lived tropical bird, early connectivity within a social network predicts male success an average of 4.8 years later. Long-tailed manakins have an unusual lek mating system in which pairs of unrelated males, at the top of complex overlapping teams of as many as 15 males, cooperate for obligate dual-male song and dance courtship displays. For as long as 8 years before forming stable "alpha-beta" partnerships, males interact with many other males in complex, temporally dynamic social networks. "Information centrality" is a network connectivity metric that accounts for indirect as well as shortest (geodesic) paths among interactors. The odds that males would rise socially rose by a factor of five for each one-unit increase in their early information centrality. Connectivity of males destined to rise did not change over time but increased in males that failed to rise socially. The results suggest that network connectivity is important for young males (ages 1-6) but less so for older males of high status (ages 10-15) and that it is difficult to explain present success without reference to social history.

  8. Understanding social anxiety as a risk for alcohol use disorders: fear of scrutiny, not social interaction fears, prospectively predicts alcohol use disorders.

    PubMed

    Buckner, Julia D; Schmidt, Norman B

    2009-01-01

    Increasing evidence indicates that social anxiety may be a premorbid risk factor for alcohol use disorders (AUD). The aim of this study was to replicate and extend previous work examining whether social anxiety is a risk factor for AUD by evaluating both the temporal antecedence and non-spuriousness of this relationship. We also examined whether social anxiety first-order factors (social interaction anxiety, observation anxieties) served as specific predictors of AUD. A non-referred sample of 404 psychologically healthy young adults (i.e. free from current or past Axis I psychopathology) was prospectively followed over approximately two years. Social anxiety (but not depression or trait anxiety) at baseline significantly predicted subsequent AUD onset. The relationship between social anxiety and AUD remained even after controlling for relevant variables (gender, depression, trait anxiety). Further, social anxiety first-order factors differentially predicted AUD onset, such that observation anxieties (but not social interaction anxiety) were prospectively linked to AUD onset. This study provides further support that social anxiety (and fear of scrutiny specifically) appears to serve as an important and potentially specific AUD-related variable that deserves serious attention as a potential vulnerability factor.

  9. Understanding the Link between Social Organization and Crime in Rural Communities.

    PubMed

    Chilenski, Sarah M; Syvertsen, Amy K; Greenberg, Mark T

    Rural communities make up much of America's heartland, yet we know little about their social organization, and how elements of their social organization relate to crime rates. The current study sought to remedy this gap by examining the associations between two measures of social organization - collective efficacy and social trust - with a number of structural community characteristics, local crime rates, and perceptions of safety in a sample of 27 rural and small town communities in two states. Measures of collective efficacy, social trust, and perceived safety, were gathered from key community members in 2006; other measures were drawn from the 2000 Census and FBI Uniform Crime Reporting system. A series of competing hypotheses were tested to examine the relative importance of social trust and collective efficacy in predicting local crime rates. Results do not support the full generalization of the social disorganization model. Correlational analyses showed that neither collective efficacy nor social trust had a direct association with community crime, nor did they mediate the associations between community structural characteristics and crime. However, perceived safety mediated the association between community crime and both measures of social organization. Analyses suggest that social trust may be more important than collective efficacy when understanding the effect of crime on a community's culture in rural areas. Understanding these associations in rural settings can aid decision makers in shaping policies to reduce crime and juvenile delinquency.

  10. Understanding the Link between Social Organization and Crime in Rural Communities

    PubMed Central

    Chilenski, Sarah M.; Syvertsen, Amy K.; Greenberg, Mark T.

    2015-01-01

    Rural communities make up much of America's heartland, yet we know little about their social organization, and how elements of their social organization relate to crime rates. The current study sought to remedy this gap by examining the associations between two measures of social organization – collective efficacy and social trust – with a number of structural community characteristics, local crime rates, and perceptions of safety in a sample of 27 rural and small town communities in two states. Measures of collective efficacy, social trust, and perceived safety, were gathered from key community members in 2006; other measures were drawn from the 2000 Census and FBI Uniform Crime Reporting system. A series of competing hypotheses were tested to examine the relative importance of social trust and collective efficacy in predicting local crime rates. Results do not support the full generalization of the social disorganization model. Correlational analyses showed that neither collective efficacy nor social trust had a direct association with community crime, nor did they mediate the associations between community structural characteristics and crime. However, perceived safety mediated the association between community crime and both measures of social organization. Analyses suggest that social trust may be more important than collective efficacy when understanding the effect of crime on a community's culture in rural areas. Understanding these associations in rural settings can aid decision makers in shaping policies to reduce crime and juvenile delinquency. PMID:26120326

  11. Emotionally biased cognitive processes: the weakest link predicts prospective changes in depressive symptom severity.

    PubMed

    Everaert, Jonas; Duyck, Wouter; Koster, Ernst H W

    2015-01-01

    Emotional biases in attention, interpretation, and memory are predictive of future depressive symptoms. It remains unknown, however, how these biased cognitive processes interact to predict depressive symptom levels in the long-term. In the present study, we tested the predictive value of two integrative approaches to model relations between multiple biased cognitive processes, namely the additive (i.e., cognitive processes have a cumulative effect) vs. the weakest link (i.e., the dominant pathogenic process is important) model. We also tested whether these integrative models interacted with perceived stress to predict prospective changes in depressive symptom severity. At Time 1, participants completed measures of depressive symptom severity and emotional biases in attention, interpretation, and memory. At Time 2, one year later, participants were reassessed to determine depressive symptom levels and perceived stress. Results revealed that the weakest link model had incremental validity over the additive model in predicting prospective changes in depressive symptoms, though both models explained a significant proportion of variance in the change in depressive symptoms from Time 1 to Time 2. None of the integrative models interacted with perceived stress to predict changes in depressive symptomatology. These findings suggest that the best cognitive marker of the evolution in depressive symptoms is the cognitive process that is dominantly biased toward negative material, which operates independent from experienced stress. This highlights the importance of considering idiographic cognitive profiles with multiple cognitive processes for understanding and modifying effects of cognitive biases in depression.

  12. Avoidant decision-making in social anxiety disorder: A laboratory task linked to in vivo anxiety and treatment outcome.

    PubMed

    Pittig, Andre; Alpers, Georg W; Niles, Andrea N; Craske, Michelle G

    2015-10-01

    Recent studies on reward-based decision-making in the presence of anxiety-related stimuli demonstrated that approach-avoidance conflicts can be assessed under controlled laboratory conditions. However, the clinical relevance of these decision conflicts has not been demonstrated. To this end, the present study investigated avoidant decisions in treatment-seeking individuals with social anxiety disorder (SAD). In a gambling task, advantageous choices to maximize gains were associated with task-irrelevant angry faces and disadvantageous choices with happy faces. The clinical relevance of avoidant decisions for in vivo anxiety in a social stress situation (public speaking) were examined (n = 44). In a subsample (n = 20), the predictive value for a reduction of avoidance following behavioral therapy was also evaluated. Results indicated a close link between more frequent avoidant decisions and elevated in vivo anxiety. Moreover, individuals who showed a deficit in the goal-directed adjustment of their decisions also showed higher and sustained distress during the social stressor and reported less decrease of avoidance following treatment. The findings highlight the importance of an avoidant decision-making style for the experience of acute distress and the maintenance of avoidance in SAD. Assessing avoidant decision-making may help to predict the response to behavioral treatments.

  13. Predicting Externalizing and Internalizing Behavior in Kindergarten: Examining the Buffering Role of Early Social Support

    PubMed Central

    Heberle, Amy E.; Krill, Sarah C.; Briggs-Gowan, Margaret J.; Carter, Alice S.

    2014-01-01

    Objective This study tested an ecological model predicting children’s behavior problems in kindergarten from risk and protective factors (parent psychological distress, parenting behavior, and social support) during early childhood. Method Study participants were 1161 socio-demographically diverse mother-child pairs who participated in a longitudinal birth cohort study. The predictor variables were collected at two separate time points and based on parent reports; children were an average of two years old at Time 1 and three years old at Time 2. The outcome measures were collected when children reached Kindergarten and were six years old on average. Results Our results show that early maternal psychological distress, mediated by sub-optimal parenting behavior, predicts children’s externalizing and internalizing behaviors in kindergarten. Moreover, early social support buffers the relations between psychological distress and later sub-optimal parenting behaviors and between sub-optimal parenting behavior and later depressive/withdrawn behavior. Conclusions Our findings have several implications for early intervention and prevention efforts. Of note, informal social support appears to play an important protective role in the development of externalizing and internalizing behavior problems, weakening the link between psychological distress and less optimal parenting behavior and between sub-optimal parenting behavior and children’s withdrawal/depression symptoms. Increasing social support may be a productive goal for family and community-level intervention. PMID:24697587

  14. Is social engagement linked to body image and depression among aging women?

    PubMed

    Sabik, Natalie J

    2017-01-01

    Maintaining an active and engaged social life is a critical component of aging well, and women are generally more socially active than men. However, as women age their self-perceptions of their bodies may reduce social behaviors and consequently, increase depressive symptoms. Because little is known about how body image is associated with social engagement and depressive symptoms among aging women, four aspects of body image: satisfaction with cosmetic features, body function, physical appearance, and weight were assessed among women aged 65 and older (n = 123). Regression analyses indicated that cosmetic appearance, body function, and physical appearance were associated with depressive symptoms, whereas satisfaction with weight was unrelated. Further, both greater satisfaction with cosmetic features and body function were associated with higher levels of social engagement, and social engagement mediated the association between these aspects of body satisfaction and depressive symptoms. The findings indicate that specific age-relevant aspects of body satisfaction are linked to social behavior and depression among aging women, and reduced body satisfaction may lead to lower social engagement, and consequently aging women's health and well-being may be diminished.

  15. Trait and social influences in the links among adolescent attachment, depressive symptoms, and coping.

    PubMed

    Merlo, Lisa J; Lakey, Brian

    2007-01-01

    Attachment insecurity and maladaptive coping are associated with depression in adolescence; however, it is unclear whether these links primarily reflect stable individual differences among teens (trait influences), experiential differences in their interactions with relationship partners (social influences) or both. In this study, teens (ages 14-18; N = 150) completed questionnaires to assess their attachment security, depressive symptoms, and coping strategies with different attachment figures. Measures were completed three times, based on experiences with a maternal figure, paternal figure, and closest peer. Generalizability analyses were used to separate each construct into trait and social influence components. Next, multivariate g correlations were computed to examine the correlations among the constructs for the trait component as well as the social component. Correlation magnitudes differed depending on whether the trait or social influence components were examined.

  16. How social and genetic factors predict friendship networks

    PubMed Central

    Boardman, Jason D.; Domingue, Benjamin W.; Fletcher, Jason M.

    2012-01-01

    Recent research suggests that the genotype of one individual in a friendship pair is predictive of the genotype of his/her friend. These results provide tentative support for the genetic homophily perspective, which has important implications for social and genetic epidemiology because it substantiates a particular form of gene–environment correlation. This process may also have important implications for social scientists who study the social factors related to health and health-related behaviors. We extend this work by considering the ways in which school context shapes genetically similar friendships. Using the network, school, and genetic information from the National Longitudinal Study of Adolescent Health, we show that genetic homophily for the TaqI A polymorphism within the DRD2 gene is stronger in schools with greater levels of inequality. Our results suggest that individuals with similar genotypes may not actively select into friendships; rather, they may be placed into these contexts by institutional mechanisms outside of their control. Our work highlights the fundamental role played by broad social structures in the extent to which genetic factors explain complex behaviors, such as friendships. PMID:23045663

  17. Direct social perception, mindreading and Bayesian predictive coding.

    PubMed

    de Bruin, Leon; Strijbos, Derek

    2015-11-01

    Mindreading accounts of social cognition typically claim that we cannot directly perceive the mental states of other agents and therefore have to exercise certain cognitive capacities in order to infer them. In recent years this view has been challenged by proponents of the direct social perception (DSP) thesis, who argue that the mental states of other agents can be directly perceived. In this paper we show, first, that the main disagreement between proponents of DSP and mindreading accounts has to do with the so-called 'sandwich model' of social cognition. Although proponents of DSP are critical of this model, we argue that they still seem to accept the distinction between perception, cognition and action that underlies it. Second, we contrast the sandwich model of social cognition with an alternative theoretical framework that is becoming increasingly popular in the cognitive neurosciences: Bayesian Predictive Coding (BPC). We show that the BPC framework renders a principled distinction between perception, cognition and action obsolete, and can accommodate elements of both DSP and mindreading accounts. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Linking social anxiety and adolescent romantic relationship functioning: indirect effects and the importance of peers.

    PubMed

    Hebert, Karen R; Fales, Jessica; Nangle, Douglas W; Papadakis, Alison A; Grover, Rachel L

    2013-11-01

    Peer relationships undergo dramatic shifts in form and function during adolescence, at the same time the incidence of socially evaluative fears sharply rises. Despite well-established links between social anxiety and broader interpersonal functioning, there is a dearth of research evaluating the impact of social anxiety on functioning in close relationships during this developmental stage. The present study examines the impact of social anxiety on functioning in close friendships and romantic relationships during adolescence. From a developmental psychopathology perspective, it was expected that social anxiety would influence functioning (quality, length, satisfaction) in romantic relationships through its influence on functioning in same- and other-sex friendships. Participants included 314 adolescents (60.5% female, 14-19 years of age) with a prior or current history of romantic relationship involvement. Structural equation modeling was used to test a mediation model positing an indirect pathway from social anxiety to romantic relationship functioning through functioning in close same- and other-sex friendships. Given known gender differences in social anxiety and relationship functioning, gender also was explored as a potential moderator. Results supported the hypothesized indirect pathway whereby social anxiety was associated with impairment in same-sex friendships; functioning in same-sex friendships was associated with functioning in other-sex friendships, which was associated, in turn, with functioning in romantic relationships. While the hypothesized indirect pathway was significant among both boys and girls, there was greater continuity of functioning between same- and other-sex friendships for girls. These findings highlight the importance of examining the multiple downstream effects of social anxiety on perceived social functioning in adolescence, and suggest that continuity may exist for maladaptive patterns of socialization, particularly across

  19. [Predictive factors in social adaptation disorders in anorexic and bulimic patients].

    PubMed

    Godart, N T; Flament, M F; Perdereau, F; Jeammet, P

    2003-01-01

    , & Kraaij Kamp, 1990). For each of the two outcome variables regarding disability, the Social role and the Occupational role, all subsets logistic regression analysis was performed in accordance to Hosmer and Lemeshow's guidelines (Hosmer and Lemeshow, 1989). Our total sample of 63 subjects included 29 subjects with AN restricting type (27 women, 2 men; 7% with a past history of BN) and 34 subjects with BN purging type (all women; 53% with history of a previous episode of AN). On the Groningen Social Disabilities Schedule, 86% of the anorexics and 65% of the bulimics had disability regarding the "social role", and 86% and 61%, respectively, disability regarding the "occupational role". Using all subsets logistic regression analyses, predictive factors of disability were: 1) for the social role, social avoidance symptom score (p < 0.002) and diagnosis of separation anxiety disorder (p < 0.01); 2) for the occupational role, number of lifetime anxiety disorders (p < 0.01) and diagnosis of separation anxiety disorder (p < 0.06). The present study clearly demonstrates that social avoidance and anxiety disorders are common and important features in the clinical presentation of subjects with AN or BN, and that they can have a negative impact on both their social and their occupational adaptation. Chronicity is a major risk in the ED, in terms of medical and sometimes lethal complications, but also because of the social consequences of these disorders. It is therefore important, in subjects with ED, to identify comorbid conditions linked to social disability, in order to improve global outcome. Recognizing and treating comorbid anxiety disorders in subjects with AN or BN could give better results than treating only the ED, in terms of social as well as global psychopathological outcome.

  20. Predicting anxious response to a social challenge: the predictive utility of the social interaction anxiety scale and the social phobia scale in a college population.

    PubMed

    Gore, K L; Carter, M M; Parker, S

    2002-06-01

    Trait anxiety is believed to be a hierarchical construct composed of several lower-order factors (Adv. Behav. Res. Therapy, 15 (1993) 147; J. Anxiety Disorders, 9 (1995) 163). Assessment devices such as the Social Interaction Anxiety Scale, the Social Phobia Scale (SIAS and SPS; Behav. Res. Therapy, 36 (4) (1998) 455), and the Anxiety Sensitivity Index (ASI; Behav. Res. Therapy, 24 (1986) 1) are good measures of the presumably separate lower-order factors. This study compared the effectiveness of the SIAS, SPS, ASI-physical scale and STAI-T (State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press (1970)) as predictors of anxious response to a social challenge (asking an aloof confederate out on a date). Consistent with the hierarchical model of anxiety, the measures of trait anxiety were moderately correlated with each other and each was a significant predictor of anxious response. The specific measures of trait social anxiety were slightly better predictors of anxious response to the social challenge than was either the ASI-physical scale or the STAI-T. The results provide evidence of the predictive validity of these social trait measures and some support for their specificity in the prediction of anxious response to a social challenge.

  1. Adaptive nonlinear model predictive control design of a flexible-link manipulator with uncertain parameters

    NASA Astrophysics Data System (ADS)

    Schnelle, Fabian; Eberhard, Peter

    2017-06-01

    This paper presents a novel adaptive nonlinear model predictive control design for trajectory tracking of flexible-link manipulators consisting of feedback linearization, linear model predictive control, and unscented Kalman filtering. Reducing the nonlinear system to a linear system by feedback linearization simplifies the optimization problem of the model predictive controller significantly, which, however, is no longer linear in the presence of parameter uncertainties and can potentially lead to an undesired dynamical behaviour. An unscented Kalman filter is used to approximate the dynamics of the prediction model by an online parameter estimation, which leads to an adaptation of the optimization problem in each time step and thus to a better prediction and an improved input action. Finally, a detailed fuzzy-arithmetic analysis is performed in order to quantify the effect of the uncertainties on the control structure and to derive robustness assessments. The control structure is applied to a serial manipulator with two flexible links containing uncertain model parameters and acting in three-dimensional space.

  2. The degree-related clustering coefficient and its application to link prediction

    NASA Astrophysics Data System (ADS)

    Liu, Yangyang; Zhao, Chengli; Wang, Xiaojie; Huang, Qiangjuan; Zhang, Xue; Yi, Dongyun

    2016-07-01

    Link prediction plays a significant role in explaining the evolution of networks. However it is still a challenging problem that has been addressed only with topological information in recent years. Based on the belief that network nodes with a great number of common neighbors are more likely to be connected, many similarity indices have achieved considerable accuracy and efficiency. Motivated by the natural assumption that the effect of missing links on the estimation of a node's clustering ability could be related to node degree, in this paper, we propose a degree-related clustering coefficient index to quantify the clustering ability of nodes. Unlike the classical clustering coefficient, our new coefficient is highly robust when the observed bias of links is considered. Furthermore, we propose a degree-related clustering ability path (DCP) index, which applies the proposed coefficient to the link prediction problem. Experiments on 12 real-world networks show that our proposed method is highly accurate and robust compared with four common-neighbor-based similarity indices (Common Neighbors(CN), Adamic-Adar(AA), Resource Allocation(RA), and Preferential Attachment(PA)), and the recently introduced clustering ability (CA) index.

  3. Function and structure in social brain regions can link oxytocin-receptor genes with autistic social behavior.

    PubMed

    Yamasue, Hidenori

    2013-02-01

    Difficulties in appropriate social and communicative behaviors are the most prevalent and core symptoms of autism spectrum disorders (ASDs). Although recent intensive research has focused on the neurobiological background of these difficulties, many aspects of them were not yet elucidated. Recent studies have employed multimodal magnetic resonance imaging (MRI) indices as intermediate phenotypes of this behavioral phenotype to link candidate genes with the autistic social difficulty. As MRI indices, functional MRI (fMRI), structural MRI, and MR-spectroscopy have been examined in subjects with autism spectrum disorders. As candidate genes, this mini-review has much interest in oxytocin-receptor genes (OXTR), since recent studies have repeatedly reported their associations with normal variations in social cognition and behavior as well as with their extremes, autistic social dysfunction. Through previous increasing studies, medial prefrontal cortex, hypothalamus and amygdala have repeatedly been revealed as neural correlates of autistic social behavior by MRI multimodalities and their relationship to OXTR. For further development of this research area, this mini-review integrates recent accumulating evidence about human behavioral and neural correlates of OXTR.

  4. Structural social support predicts functional social support in an online weight loss programme.

    PubMed

    Hwang, Kevin O; Etchegaray, Jason M; Sciamanna, Christopher N; Bernstam, Elmer V; Thomas, Eric J

    2014-06-01

    Online weight loss programmes allow members to use social media tools to give and receive social support for weight loss. However, little is known about the relationship between the use of social media tools and the perception of specific types of support. To test the hypothesis that the frequency of using social media tools (structural support) is directly related to perceptions of Encouragement, Information and Shared Experiences support (functional support). Online survey. Members of an online weight loss programme. The outcome was the perception of Encouragement (motivation, congratulations), Information (advice, tips) and Shared Experiences (belonging to a group) social support. The predictor was a social media scale based on the frequency of using forums and blogs within the online weight loss programme (alpha = 0.91). The relationship between predictor and outcomes was evaluated with structural equation modelling (SEM) and logistic regression, adjusted for sociodemographic characteristics, BMI and duration of website membership. The 187 participants were mostly female (95%) and white (91%), with mean (SD) age 37 (12) years and mean (SD) BMI 31 (8). SEM produced a model in which social media use predicted Encouragement support, but not Information or Shared Experiences support. Participants who used the social media tools at least weekly were almost five times as likely to experience Encouragement support compared to those who used the features less frequently [adjusted OR 4.8 (95% CI 1.8-12.8)]. Using the social media tools of an online weight loss programme at least once per week is strongly associated with receiving Encouragement for weight loss behaviours. © 2011 John Wiley & Sons Ltd.

  5. Exploring the Link between Genetic Relatedness r and Social Contact Structure k in Animal Social Networks.

    PubMed

    Wolf, Jochen B W; Traulsen, Arne; James, Richard

    2011-01-01

    Our understanding of how cooperation can arise in a population of selfish individuals has been greatly advanced by theory. More than one approach has been used to explore the effect of population structure. Inclusive fitness theory uses genetic relatedness r to express the role of population structure. Evolutionary graph theory models the evolution of cooperation on network structures and focuses on the number of interacting partners k as a quantity of interest. Here we use empirical data from a hierarchically structured animal contact network to examine the interplay between independent, measurable proxies for these key parameters. We find strong inverse correlations between estimates of r and k over three levels of social organization, suggesting that genetic relatedness and social contact structure capture similar structural information in a real population.

  6. Predicting Social Anxiety Treatment Outcome Based on Therapeutic Email Conversations.

    PubMed

    Hoogendoorn, Mark; Berger, Thomas; Schulz, Ava; Stolz, Timo; Szolovits, Peter

    2017-09-01

    Predicting therapeutic outcome in the mental health domain is of utmost importance to enable therapists to provide the most effective treatment to a patient. Using information from the writings of a patient can potentially be a valuable source of information, especially now that more and more treatments involve computer-based exercises or electronic conversations between patient and therapist. In this paper, we study predictive modeling using writings of patients under treatment for a social anxiety disorder. We extract a wealth of information from the text written by patients including their usage of words, the topics they talk about, the sentiment of the messages, and the style of writing. In addition, we study trends over time with respect to those measures. We then apply machine learning algorithms to generate the predictive models. Based on a dataset of 69 patients, we are able to show that we can predict therapy outcome with an area under the curve of 0.83 halfway through the therapy and with a precision of 0.78 when using the full data (i.e., the entire treatment period). Due to the limited number of participants, it is hard to generalize the results, but they do show great potential in this type of information.

  7. Ophthalmology on social networking sites: an observational study of Facebook, Twitter, and LinkedIn

    PubMed Central

    Micieli, Jonathan A; Tsui, Edmund

    2015-01-01

    Background The use of social media in ophthalmology remains largely unknown. Our aim was to evaluate the extent and involvement of ophthalmology journals, professional associations, trade publications, and patient advocacy and fundraising groups on social networking sites. Methods An archived list of 107 ophthalmology journals from SCImago, trade publications, professional ophthalmology associations, and patient advocacy organizations were searched for their presence on Facebook, Twitter, and LinkedIn. Activity and popularity of each account was quantified by using the number of “likes” on Facebook, the number of followers on Twitter, and members on LinkedIn. Results Of the 107 journals ranked by SCImago, 21.5% were present on Facebook and 18.7% were present on Twitter. Journal of Community Eye Health was the most popular on Facebook and JAMA Ophthalmology was most popular on Twitter. Among the 133 members of the International Council of Ophthalmology, 17.3% were present on Facebook, 12.8% were present on Twitter, and 7.5% were present on LinkedIn. The most popular on Facebook was the International Council of Ophthalmology, and the American Academy of Ophthalmology was most popular on Twitter and LinkedIn. Patient advocacy organizations were more popular on all sites compared with journals, professional association, and trade publications. Among the top ten most popular pages in each category, patient advocacy groups were most active followed by trade publications, professional associations, and journals. Conclusion Patient advocacy groups lead the way in social networking followed by professional organizations and journals. Although some journals use social media, most have yet to engage its full potential and maximize the number of potential interested individuals. PMID:25709390

  8. Social Media - DoD’s Greatest Information Sharing Tool or Weakest Security Link?

    DTIC Science & Technology

    2010-04-15

    13 . SUPPLEMENTARY NOTES 14. ABSTRACT This paper will consider the current use of Social Media in the Department of Defense (DoD): review current...OR WEAKEST SECURITY LINK? Introduction For many years there has been continual debate regarding the security of, and access to, the...and blogs. Over the past year (2009), the DoD has been reviewing the use of, access to, and impact on both the information network and the work

  9. Ophthalmology on social networking sites: an observational study of Facebook, Twitter, and LinkedIn.

    PubMed

    Micieli, Jonathan A; Tsui, Edmund

    2015-01-01

    The use of social media in ophthalmology remains largely unknown. Our aim was to evaluate the extent and involvement of ophthalmology journals, professional associations, trade publications, and patient advocacy and fundraising groups on social networking sites. An archived list of 107 ophthalmology journals from SCImago, trade publications, professional ophthalmology associations, and patient advocacy organizations were searched for their presence on Facebook, Twitter, and LinkedIn. Activity and popularity of each account was quantified by using the number of "likes" on Facebook, the number of followers on Twitter, and members on LinkedIn. Of the 107 journals ranked by SCImago, 21.5% were present on Facebook and 18.7% were present on Twitter. Journal of Community Eye Health was the most popular on Facebook and JAMA Ophthalmology was most popular on Twitter. Among the 133 members of the International Council of Ophthalmology, 17.3% were present on Facebook, 12.8% were present on Twitter, and 7.5% were present on LinkedIn. The most popular on Facebook was the International Council of Ophthalmology, and the American Academy of Ophthalmology was most popular on Twitter and LinkedIn. Patient advocacy organizations were more popular on all sites compared with journals, professional association, and trade publications. Among the top ten most popular pages in each category, patient advocacy groups were most active followed by trade publications, professional associations, and journals. Patient advocacy groups lead the way in social networking followed by professional organizations and journals. Although some journals use social media, most have yet to engage its full potential and maximize the number of potential interested individuals.

  10. Using of CBA Method for Evaluation of the Investments in the Link with Social Responsible Business

    NASA Astrophysics Data System (ADS)

    Mrvová, Ľubica; Vaňová, Jaromíra

    2012-12-01

    The paper presents knowledge from the area of economic efficiency assessment of the environmental investments, in the link with environmental management with context of social responsible business and their mutual connection, on the base of CBA method. CBA method creates basis for the software CBA1.1, which was created for the needs of business practise for the small and medium enterprises in the Slovak Republic.

  11. Framework for Smart Electronic Health Record-Linked Predictive Models to Optimize Care for Complex Digestive Diseases

    DTIC Science & Technology

    2012-06-01

    Regueiro MD, Krasinskas AM, Saul M, Sapienza D, Binion DG, Hartman D. Mucosal IgG4 Cell Infiltration in Ulcerative Colitis (UC) is Linked to Disease ...Record-Linked Predictive Models to Optimize Care for Complex Digestive Diseases PRINCIPAL INVESTIGATOR: Michael A. Dunn, MD CONTRACTING...Framework for Smart Electronic Health Record-Linked Predictive Models to Optimize Care for Complex Digestive Diseases 5b. GRANT NUMBER W81XWH11-2

  12. Trait aggressiveness does not predict social dominance of rats in the Visible Burrow System.

    PubMed

    Buwalda, Bauke; Koolhaas, Jaap M; de Boer, Sietse F

    2017-09-01

    Hierarchical social status greatly influences health and well-being in mammals, including humans. The social rank of an individual is established during competitive encounters with conspecifics. Intuitively, therefore, social dominance and aggressiveness may seem intimately linked. Yet, whether an aggressive personality trait may predispose individuals to a particular rank in a social colony setting remains largely unclear. Here we tested the hypothesis that high trait aggressiveness in Wildtype Groningen (WTG) rats, as assessed in a classic resident-intruder offensive aggression paradigm predicts social dominance in a mixed-sex colony housing using the Visible Burrow System (VBS). We also hypothesized that hierarchical steepness, as reflected in the number and intensity of the social conflicts, positively correlates with the average level of trait aggressiveness of the male subjects in the VBS. Clear and stable hierarchical ranking was formed within a few days in VBS colonies as indicated and reflected by a rapid loss of body weight in subordinates which stabilized after 2-3days. Social conflicts, that occurred mainly during these first few days, also resulted in bite wounds in predominantly subordinate males. Data clearly showed that trait aggressiveness does not predict dominance status. The most aggressive male in a mixed sex group of conspecifics living in a closed VBS environment does not always become the dominant male. In addition, data did not convincingly indicate that in colonies with only highly aggressive males, agonistic interactions were more intense. Number of bite wounds and body weight loss did not positively correlate with trait-aggressiveness of subordinates. In this study, rats from this wild-derived rat strain behave differently from Long-Evans laboratory rats that have been studied up till now in many experiments using the VBS. Strain dependent differences in the capacity to display appropriate social behavior fitting an adaptive strategy to

  13. Major histocompatibility complex linked databases and prediction tools for designing vaccines.

    PubMed

    Singh, Satarudra Prakash; Mishra, Bhartendu Nath

    2016-03-01

    Presently, the major histocompatibility complex (MHC) is receiving considerable interest owing to its remarkable role in antigen presentation and vaccine design. The specific databases and prediction approaches related to MHC sequences, structures and binding/nonbinding peptides have been aggressively developed in the past two decades with their own benchmarks and standards. Before using these databases and prediction tools, it is important to analyze why and how the tools are constructed along with their strengths and limitations. The current review presents insights into web-based immunological bioinformatics resources that include searchable databases of MHC sequences, epitopes and prediction tools that are linked to MHC based vaccine design, including population coverage analysis. In T cell epitope forecasts, MHC class I binding predictions are very accurate for most of the identified MHC alleles. However, these predictions could be further improved by integrating proteasome cleavage (in conjugation with transporter associated with antigen processing (TAP) binding) prediction, as well as T cell receptor binding prediction. On the other hand, MHC class II restricted epitope predictions display relatively low accuracy compared to MHC class I. To date, pan-specific tools have been developed, which not only deliver significantly improved predictions in terms of accuracy, but also in terms of the coverage of MHC alleles and supertypes. In addition, structural modeling and simulation systems for peptide-MHC complexes enable the molecular-level investigation of immune processes. Finally, epitope prediction tools, and their assessments and guidelines, have been presented to immunologist for the design of novel vaccine and diagnostics. Copyright © 2015 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

  14. Personality moderates the links of social identity with work motivation and job searching.

    PubMed

    Baay, Pieter E; van Aken, Marcel A G; van der Lippe, Tanja; de Ridder, Denise T D

    2014-01-01

    Work motivation is critical for successful school-to-work transitions, but little is known about its determinants among labor market entrants. Applying a social identity framework, we examined whether work motivation and job searching are social-contextually determined. We expected that some job seekers are more sensitive to contextual influence, depending on their personality. Mediation analyses on 591 Dutch vocational training students indicate that the perception of more positive work norms in someone's social context was related to higher levels of intrinsic motivation, which in turn predicted higher preparatory job search behavior and job search intentions. Multi-group analysis shows that perceived work norms more strongly predict work motivation among overcontrollers compared to resilients and undercontrollers. In conclusion, work motivation and job searching appear contextually determined: especially among those sensitive to contextual influence, people seem to work when they believe that is what people like them do.

  15. Exploring context and content links in social media: a latent space method.

    PubMed

    Qi, Guo-Jun; Aggarwal, Charu; Tian, Qi; Ji, Heng; Huang, Thomas S

    2012-05-01

    Social media networks contain both content and context-specific information. Most existing methods work with either of the two for the purpose of multimedia mining and retrieval. In reality, both content and context information are rich sources of information for mining, and the full power of mining and processing algorithms can be realized only with the use of a combination of the two. This paper proposes a new algorithm which mines both context and content links in social media networks to discover the underlying latent semantic space. This mapping of the multimedia objects into latent feature vectors enables the use of any off-the-shelf multimedia retrieval algorithms. Compared to the state-of-the-art latent methods in multimedia analysis, this algorithm effectively solves the problem of sparse context links by mining the geometric structure underlying the content links between multimedia objects. Specifically for multimedia annotation, we show that an effective algorithm can be developed to directly construct annotation models by simultaneously leveraging both context and content information based on latent structure between correlated semantic concepts. We conduct experiments on the Flickr data set, which contains user tags linked with images. We illustrate the advantages of our approach over the state-of-the-art multimedia retrieval techniques.

  16. Attachment's Links With Adolescents' Social Emotions: The Roles of Negative Emotionality and Emotion Regulation.

    PubMed

    Murphy, Tia Panfile; Laible, Deborah J; Augustine, Mairin; Robeson, Lindsay

    2015-01-01

    Recent research has attempted to explain the mechanisms through which parental attachment affects social and emotional outcomes (e.g., Burnette, Taylor, Worthington, & Forsyth, 2007 ; Panfile & Laible, 2012 ). The authors' goal was to examine negative emotionality and emotion regulation as mediators of the associations that attachment has with empathy, forgiveness, guilt, and jealousy. One hundred forty-eight adolescents reported their parental attachment security, general levels of negative emotionality and abilities to regulate emotional responses, and tendencies to feel empathy, forgiveness, guilt, and jealousy. Results revealed that attachment security was associated with higher levels of empathy, forgiveness, and guilt, but lower levels of jealousy. In addition, emotion regulation mediated the links attachment shared with both empathy and guilt, such that higher levels of attachment security were linked with greater levels of emotion regulation, which led to greater levels of empathy and guilt. Alternatively, negative emotionality mediated the links attachment shared with both forgiveness and jealousy, such that higher levels of attachment security were associated with lower levels of negative emotionality, which in turn was linked to lower levels of forgiveness and higher levels of jealousy. This study provides a general picture of how attachment security may play a role in shaping an individual's levels of social emotions.

  17. Use of social network analysis to describe service links for farmers' mental health.

    PubMed

    Fuller, Jeffrey; Kelly, Brian; Sartore, Gina; Fragar, Lynne; Tonna, Anne; Pollard, Georgia; Hazell, Trevor

    2007-04-01

    The primary mental health care needs of farmers require that service innovations incorporate rural support workers into a local service network. This component of the FarmLink pilot sought to develop a social network analysis method that would describe local mental health-related human service networks. The purpose is to inform improvements in this network and to serve as a baseline against which such improvements can be evaluated. A pilot survey of rural human service providers who deal with mental health-related issues among farmers about their self-reported links between each other. Service delivery agencies associated with a small rural town in New South Wales. Twenty-five agents from a range of human services involved in rural human support services to farmers, such as from agricultural and drought support, welfare, primary health care and education. Telephone interview prior to the conduct of a Mental Health First Aid seminar and a Farmers Mental Health and Wellbeing workshop. Agent self-reported service links over the past three months for information exchange, client referrals and working together in relation to helping farmers for mental health, emotional health or stress-related problems. Analysis trialled on the 'made referrals' link shows the network influence, prominence and intermediary status of the rural financial counsellor. Within the limitations of recalled self-report data, social network analysis provides a useful network description for informing and evaluating service network improvements.

  18. Perceived Social Competence, Negative Social Interactions and Negative Cognitive Style Predict Depressive Symptoms during Adolescence

    PubMed Central

    Lee, Adabel; Hankin, Benjamin L.; Mermelstein, Robin J.

    2010-01-01

    The current study examined whether negative interactions with parents and peers would mediate the longitudinal association between perceived social competence and depressive symptoms and whether a negative cognitive style would moderate the longitudinal association between negative interactions with parents and increases in depressive symptoms. Youth (N=350; 6th-10th graders) completed self-report measures of perceived social competence, negative interactions with parents and peers, negative cognitive style, and depressive symptoms at three time points. Results indicated that the relationship between perceived social competence and depressive symptoms was partially mediated by negative interactions with parents but not peers. Further, baseline negative cognitive style interacted with greater negative parent interactions to predict later depressive symptoms. PMID:20706914

  19. Social carry-over effects underpin trans-seasonally linked structure in a wild bird population.

    PubMed

    Firth, Josh A; Sheldon, Ben C

    2016-11-01

    Spatial structure underpins numerous population processes by determining the environment individuals' experience and which other individuals they encounter. Yet, how the social landscape influences individuals' spatial decisions remains largely unexplored. Wild great tits (Parus major) form freely moving winter flocks, but choose a single location to establish a breeding territory over the spring. We demonstrate that individuals' winter social associations carry-over into their subsequent spatial decisions, as individuals breed nearer to those they were most associated with during winter. Further, they also form territory boundaries with their closest winter associates, irrespective of breeding distance. These findings were consistent across years, and among all demographic classes, suggesting that such social carry-over effects may be general. Thus, prior social structure can shape the spatial proximity, and fine-scale arrangement, of breeding individuals. In this way, social networks can influence a wide range of processes linked to individuals' breeding locations, including other social interactions themselves. © 2016 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

  20. Social networks and links to isolation and loneliness among elderly HCBS clients.

    PubMed

    Medvene, Louis J; Nilsen, Kari M; Smith, Rachel; Ofei-Dodoo, Samuel; DiLollo, Anthony; Webster, Noah; Graham, Annette; Nance, Anita

    2016-01-01

    The purpose of this study was to explore the network types of HCBS clients based on the structural characteristics of their social networks. We also examined how the network types were associated with social isolation, relationship quality and loneliness. Forty personal interviews were carried out with HCBS clients to assess the structure of their social networks as indicated by frequency of contact with children, friends, family and participation in religious and community organizations. Hierarchical cluster analysis was conducted to identify network types. Four network types were found including: family (n = 16), diverse (n = 8), restricted (n = 8) and religious (n = 7). Family members comprised almost half of participants' social networks, and friends comprised less than one-third. Clients embedded in family, diverse and religious networks had significantly more positive relationships than clients embedded in restricted networks. Clients embedded in restricted networks had significantly higher social isolation scores and were lonelier than clients in diverse and family networks. The findings suggest that HCBS clients' isolation and loneliness are linked to the types of social networks in which they are embedded. The findings also suggest that clients embedded in restricted networks are at high risk for negative outcomes.

  1. Oxytocin and vasopressin: linking pituitary neuropeptides and their receptors to social neurocircuits

    PubMed Central

    Baribeau, Danielle A.; Anagnostou, Evdokia

    2015-01-01

    Oxytocin and vasopressin are pituitary neuropeptides that have been shown to affect social processes in mammals. There is growing interest in these molecules and their receptors as potential precipitants of, and/or treatments for, social deficits in neurodevelopmental disorders, including autism spectrum disorder. Numerous behavioral-genetic studies suggest that there is an association between these peptides and individual social abilities; however, an explanatory model that links hormonal activity at the receptor level to complex human behavior remains elusive. The following review summarizes the known associations between the oxytocin and vasopressin neuropeptide systems and social neurocircuits in the brain. Following a micro- to macro- level trajectory, current literature on the synthesis and secretion of these peptides, and the structure, function and distribution of their respective receptors is first surveyed. Next, current models regarding the mechanism of action of these peptides on microcircuitry and other neurotransmitter systems are discussed. Functional neuroimaging evidence on the acute effects of exogenous administration of these peptides on brain activity is then reviewed. Overall, a model in which the local neuromodulatory effects of pituitary neuropeptides on brainstem and basal forebrain regions strengthen signaling within social neurocircuits proves appealing. However, these findings are derived from animal models; more research is needed to clarify the relevance of these mechanisms to human behavior and treatment of social deficits in neuropsychiatric disorders. PMID:26441508

  2. Atypical Modulations of N170 Component during Emotional Processing and Their Links to Social Behaviors in Ex-combatants.

    PubMed

    Trujillo, Sandra P; Valencia, Stella; Trujillo, Natalia; Ugarriza, Juan E; Rodríguez, Mónica V; Rendón, Jorge; Pineda, David A; López, José D; Ibañez, Agustín; Parra, Mario A

    2017-01-01

    Emotional processing (EP) is crucial for the elaboration and implementation of adaptive social strategies. EP is also necessary for the expression of social cognition and behavior (SCB) patterns. It is well-known that war contexts induce socio-emotional atypical functioning, in particular for those who participate in combats. Thus, ex-combatants represent an ideal non-clinical population to explore EP modulation and to evaluate its relation with SCB. The aim of this study was to explore EP and its relation with SCB dimensions such as empathy, theory of mind and social skills in a sample of 50 subjects, of which 30 were ex-combatants from illegally armed groups in Colombia, and 20 controls without combat experience. We adapted an Emotional Recognition Task for faces and words and synchronized it with electroencephalographic recording. Ex-combatants presented with higher assertion skills and showed more pronounced brain responses to faces than Controls. They did not show the bias toward anger observed in control participants whereby the latter group was more likely to misclassify neutral faces as angry. However, ex-combatants showed an atypical word valence processing. That is, words with different emotions yielded no differences in N170 modulations. SCB variables were successfully predicted by neurocognitive variables. Our results suggest that in ex-combatants the links between EP and SCB functions are reorganized. This may reflect neurocognitive modulations associated to chronic exposure to war experiences.

  3. Atypical Modulations of N170 Component during Emotional Processing and Their Links to Social Behaviors in Ex-combatants

    PubMed Central

    Trujillo, Sandra P.; Valencia, Stella; Trujillo, Natalia; Ugarriza, Juan E.; Rodríguez, Mónica V.; Rendón, Jorge; Pineda, David A.; López, José D.; Ibañez, Agustín; Parra, Mario A.

    2017-01-01

    Emotional processing (EP) is crucial for the elaboration and implementation of adaptive social strategies. EP is also necessary for the expression of social cognition and behavior (SCB) patterns. It is well-known that war contexts induce socio-emotional atypical functioning, in particular for those who participate in combats. Thus, ex-combatants represent an ideal non-clinical population to explore EP modulation and to evaluate its relation with SCB. The aim of this study was to explore EP and its relation with SCB dimensions such as empathy, theory of mind and social skills in a sample of 50 subjects, of which 30 were ex-combatants from illegally armed groups in Colombia, and 20 controls without combat experience. We adapted an Emotional Recognition Task for faces and words and synchronized it with electroencephalographic recording. Ex-combatants presented with higher assertion skills and showed more pronounced brain responses to faces than Controls. They did not show the bias toward anger observed in control participants whereby the latter group was more likely to misclassify neutral faces as angry. However, ex-combatants showed an atypical word valence processing. That is, words with different emotions yielded no differences in N170 modulations. SCB variables were successfully predicted by neurocognitive variables. Our results suggest that in ex-combatants the links between EP and SCB functions are reorganized. This may reflect neurocognitive modulations associated to chronic exposure to war experiences. PMID:28588462

  4. The role of social support, family identification, and family constraints in predicting posttraumatic stress after cancer.

    PubMed

    Swartzman, Samantha; Sani, Fabio; Munro, Alastair J

    2017-09-01

    We compared social support with other potential psychosocial predictors of posttraumatic stress after cancer. These included family identification, or a sense of belonging to and commonality with family members, and family constraints, or the extent to which family members are closed, judgmental, or unreceptive in conversations about cancer. We also tested the hypothesis that family constraints mediate the relationship between family identification and cancer-related posttraumatic stress. We used a cross-sectional design. Surveys were collected from 205 colorectal cancer survivors in Tayside, Scotland. Both family identification and family constraints were stronger independent predictors of posttraumatic stress than social support. In multivariate analyses, social support was not a significant independent predictor of posttraumatic stress. In addition, there was a significant indirect effect of family identification on posttraumatic stress through family constraints. Numerous studies demonstrate a link between social support and posttraumatic stress. However, experiences within the family may be more important in predicting posttraumatic stress after cancer. Furthermore, a sense of belonging to and commonality with the family may reduce the extent to which cancer survivors experience constraints on conversations about cancer; this may, in turn, reduce posttraumatic stress. Copyright © 2016 John Wiley & Sons, Ltd.

  5. Statistical prediction of the atmospheric behavior for free space optical link

    NASA Astrophysics Data System (ADS)

    Hajek, Lukas; Vitasek, Jan; Vanderka, Ales; Latal, Jan; Perecar, Frantisek; Vasinek, Vladimir

    2015-09-01

    The atmosphere is unstable and unpredictable environment, where are continual changes of the air refractive index. These changes cause fluctuation of optical power at the receiver site. The prediction of behavior of the atmosphere and effect of this behavior on the FSO link is very complicated or even impossible. Aim of this article is focused on statistical analysis of measured level signal RSSI of the FSO link and atmospheric properties measured by hydro-meteorological station. For measured data the statistical analysis tools were used. Next part of article is focused on determination of the linear regression model to calculate level of RSSI depending on the atmospheric properties. Two empirical equations are result for day and night time. These equations describe behavior of signal RSSI in 30 days interval. Finally, comparison of the obtained mathematical model with real measured data of RSSI was introduced for one week before and one week after the analyzed time interval.

  6. Methods Linking Predictive Weather and Fine-scale Soil Moisture to Crop and Irrigation Decision Tools

    NASA Astrophysics Data System (ADS)

    Jones, A. S.; Andales, A.; Niemann, J. D.; Cammarere, M.; Fletcher, S. J.; Corbett, J.

    2016-12-01

    More than 30% of all irrigated US agricultural output comes from the lands sustained by the Ogallala Aquifer in the western Great Plains. The agricultural production practices in six states (CO, KS, NE, NM, OK, and TX) affect water usage and the interactive multi-scale phytobiome processes of the individual crop types. Tested methods to optimize water use and crop production at the field-scale are needed as the Ogallala water resources undergo change. This work presents methods used to link predictive weather and downscaled soil moisture at 10-30 m scales for use in crop and irrigation applications, and other decision tools. Our focus is on the CSU Water Irrigation Scheduler for Efficient (WISE) Application tool, crop yield models, and remote soil moisture characterization as a demonstration of how complex fine-scale phytobiome processes and methods can be linked to weather and environmental remote sensing data sets in near real-time using scalable technologies.

  7. Social and economic ideologies differentially predict prejudice across the political spectrum, but social issues are most divisive.

    PubMed

    Crawford, Jarret T; Brandt, Mark J; Inbar, Yoel; Chambers, John R; Motyl, Matt

    2017-03-01

    Liberals and conservatives both express prejudice toward ideologically dissimilar others (Brandt et al., 2014). Previous work on ideological prejudice did not take advantage of evidence showing that ideology is multidimensional, with social and economic ideologies representing related but separable belief systems. In 5 studies (total N = 4912), we test 3 competing hypotheses of a multidimensional account of ideological prejudice. The dimension-specific symmetry hypothesis predicts that social and economic ideologies differentially predict prejudice against targets who are perceived to vary on the social and economic political dimensions, respectively. The social primacy hypothesis predicts that such ideological worldview conflict is experienced more strongly along the social than economic dimension. The social-specific asymmetry hypothesis predicts that social conservatives will be more prejudiced than social liberals, with no specific hypotheses for the economic dimension. Using multiple target groups, multiple prejudice measures (e.g., global evaluations, behavior), and multiple social and economic ideology measures (self-placement, issue positions), we found relatively consistent support for the dimension-specific symmetry and social primacy hypotheses, and no support for the social-specific asymmetry hypothesis. These results suggest that worldview conflict and negative intergroup attitudes and behaviors are dimension-specific, but that the social dimension appears to inspire more political conflict than the economic dimension. (PsycINFO Database Record

  8. Predictive decision making driven by multiple time-linked reward representations in the anterior cingulate cortex

    PubMed Central

    Wittmann, Marco K.; Kolling, Nils; Akaishi, Rei; Chau, Bolton K. H.; Brown, Joshua W.; Nelissen, Natalie; Rushworth, Matthew F. S.

    2016-01-01

    In many natural environments the value of a choice gradually gets better or worse as circumstances change. Discerning such trends makes predicting future choice values possible. We show that humans track such trends by comparing estimates of recent and past reward rates, which they are able to hold simultaneously in the dorsal anterior cingulate cortex (dACC). Comparison of recent and past reward rates with positive and negative decision weights is reflected by opposing dACC signals indexing these quantities. The relative strengths of time-linked reward representations in dACC predict whether subjects persist in their current behaviour or switch to an alternative. Computationally, trend-guided choice can be modelled by using a reinforcement-learning mechanism that computes a longer-term estimate (or expectation) of prediction errors. Using such a model, we find a relative predominance of expected prediction errors in dACC, instantaneous prediction errors in the ventral striatum and choice signals in the ventromedial prefrontal cortex. PMID:27477632

  9. Perceived social support moderates the link between attachment anxiety and health outcomes.

    PubMed

    Stanton, Sarah C E; Campbell, Lorne

    2014-01-01

    Two literatures have explored some of the effects intimate relationships can have on physical and mental health outcomes. Research investigating health through the lens of attachment theory has demonstrated that more anxiously attached individuals in particular consistently report poorer health. Separate research on perceived social support (e.g., partner or spousal support) suggests that higher support has salutary influences on various health outcomes. Little to no research, however, has explored the interaction of attachment anxiety and perceived social support on health outcomes. The present study examined the attachment-health link and the moderating role of perceived social support in a community sample of married couples. Results revealed that more anxious persons reported poorer overall physical and mental health, more bodily pain, more medical symptoms, and impaired daily functioning, even after controlling for age, relationship length, neuroticism, and marital quality. Additionally, perceived social support interacted with attachment anxiety to influence health; more anxious individuals' health was poorer even when perceived social support was high, whereas less anxious individuals' health benefited from high support. Possible mechanisms underlying these findings and the importance of considering attachment anxiety in future studies of poor health in adulthood are discussed.

  10. Perceived social support moderates the link between threat-related amygdala reactivity and trait anxiety.

    PubMed

    Hyde, Luke W; Gorka, Adam; Manuck, Stephen B; Hariri, Ahmad R

    2011-03-01

    Several lines of research have illustrated that negative environments can precipitate psychopathology, particularly in the context of relatively increased biological risk, while social resources can buffer the effects of these environments. However, little research has examined how social resources might buffer proximal biological risk for psychopathology or the neurobiological pathways through which such buffering may be mediated. Here we report that the expression of trait anxiety as a function of threat-related amygdala reactivity is moderated by perceived social support, a resource for coping with adversity. A significant positive correlation between amygdala reactivity and trait anxiety was evident in individuals reporting below average levels of support but not in those reporting average or above average levels. These results were consistent across multiple measures of trait anxiety and were specific to anxiety in that they did not extend to measures of broad negative or positive affect. Our findings illuminate a biological pathway, namely moderation of amygdala-related anxiety, through which social support may confer resilience to psychopathology. Moreover, our results indicate that links between neural reactivity and behavior are not static but rather may be contingent on social resources. Copyright © 2010 Elsevier Ltd. All rights reserved.

  11. Perceived Social Support Moderates the Link between Threat-Related Amygdala Reactivity and Trait Anxiety

    PubMed Central

    Hyde, Luke W.; Gorka, Adam; Manuck, Stephen B.; Hariri, Ahmad R.

    2010-01-01

    Several lines of research have illustrated that negative environments can precipitate psychopathology, particularly in the context of relatively increased biological risk, while social resources can buffer the effects of these environments. However, little research has examined how social resources might buffer proximal biological risk for psychopathology or the neurobiological pathways through which such buffering may be mediated. Here we report that the expression of trait anxiety as a function of threat-related amygdala reactivity is moderated by perceived social support, a resource for coping with adversity. A significant positive correlation between amygdala reactivity and trait anxiety was evident in individuals reporting below-average levels of support but not in those reporting average or above-average levels. These results were consistent across multiple measures of trait anxiety and were specific to anxiety in that they did not extend to measures of broad negative or positive affect. Our findings illuminate a biological pathway, namely moderation of amygdala-related anxiety, through which social support may confer resilience to psychopathology. Moreover, our results indicate that links between neural reactivity and behavior are not static but rather may be contingent on social resources. PMID:20813118

  12. Hierarchical prediction errors in midbrain and septum during social learning

    PubMed Central

    Mathys, Christoph; Weber, Lilian A. E.; Kasper, Lars; Mauer, Jan; Stephan, Klaas E.

    2017-01-01

    Abstract Social learning is fundamental to human interactions, yet its computational and physiological mechanisms are not well understood. One prominent open question concerns the role of neuromodulatory transmitters. We combined fMRI, computational modelling and genetics to address this question in two separate samples (N = 35, N = 47). Participants played a game requiring inference on an adviser’s intentions whose motivation to help or mislead changed over time. Our analyses suggest that hierarchically structured belief updates about current advice validity and the adviser’s trustworthiness, respectively, depend on different neuromodulatory systems. Low-level prediction errors (PEs) about advice accuracy not only activated regions known to support ‘theory of mind’, but also the dopaminergic midbrain. Furthermore, PE responses in ventral striatum were influenced by the Met/Val polymorphism of the Catechol-O-Methyltransferase (COMT) gene. By contrast, high-level PEs (‘expected uncertainty’) about the adviser’s fidelity activated the cholinergic septum. These findings, replicated in both samples, have important implications: They suggest that social learning rests on hierarchically related PEs encoded by midbrain and septum activity, respectively, in the same manner as other forms of learning under volatility. Furthermore, these hierarchical PEs may be broadcast by dopaminergic and cholinergic projections to induce plasticity specifically in cortical areas known to represent beliefs about others. PMID:28119508

  13. Fearfulness moderates the link between childhood social withdrawal and adolescent reward response

    PubMed Central

    Shaw, Daniel S.; Forbes, Erika E.

    2015-01-01

    Withdrawal from peers during childhood may reflect disruptions in reward functioning that heighten vulnerability to affective disorders during adolescence. The association between socially withdrawn behavior and reward functioning may depend on traits that influence this withdrawal, such as fearfulness or unsociability. In a study of 129 boys, we evaluated how boys’ fearfulness and sociability at age 5 and social withdrawal at school at ages 6 to 10 and during a summer camp at age 9/10 were associated with their neural response to reward at age 20. Greater social withdrawal during childhood was associated with heightened striatal and mPFC activation when anticipating rewards at age 20. Fearfulness moderated this effect to indicate that social withdrawal was associated with heightened reward-related response in the striatum for boys high on fearfulness. Altered striatal response associated with social withdrawal and fearfulness predicted greater likelihood to have a lifetime history of depression and social phobia at age 20. These findings add greater specificity to previous findings that children high in traits related to fear of novelty show altered reward responses, by identifying fearfulness (but not low levels of sociability) as a potential underlying mechanism that contributes to reward alterations in withdrawn children. PMID:25193948

  14. Individual differences in the perception of biological motion: links to social cognition and motor imagery.

    PubMed

    Miller, Luke E; Saygin, Ayse P

    2013-08-01

    Biological motion perception is often claimed to support social cognition, and to rely upon embodied representations and motor imagery. Are people with higher levels of social traits or more vivid motor imagery better at biological motion perception? We administered four experiments measuring sensitivity in using (global) form and (local) motion cues in biological motion, plus well-established measures of social cognition (e.g., empathy) and motor imagery (e.g., kinesthetic motor imagery). This first systematic investigation of individual variability in biological motion processing demonstrated significant relationships between these domains, along with a dissociation. Sensitivity for using form cues in biological motion processing was correlated with social (and not the imagery) measures; sensitivity for using motion cues was correlated with motor imagery (and not the social) measures. These results could not be explained by performance on non-biological control stimuli. We thus show that although both social cognition and motor imagery predict sensitivity to biological motion, these skills likely tap into different aspects of perception. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. Global sensitivity analysis, probabilistic calibration, and predictive assessment for the data assimilation linked ecosystem carbon model

    SciTech Connect

    Safta, C.; Ricciuto, Daniel M.; Sargsyan, Khachik; Debusschere, B.; Najm, H. N.; Williams, M.; Thornton, Peter E.

    2015-07-01

    In this paper we propose a probabilistic framework for an uncertainty quantification (UQ) study of a carbon cycle model and focus on the comparison between steady-state and transient simulation setups. A global sensitivity analysis (GSA) study indicates the parameters and parameter couplings that are important at different times of the year for quantities of interest (QoIs) obtained with the data assimilation linked ecosystem carbon (DALEC) model. We then employ a Bayesian approach and a statistical model error term to calibrate the parameters of DALEC using net ecosystem exchange (NEE) observations at the Harvard Forest site. The calibration results are employed in the second part of the paper to assess the predictive skill of the model via posterior predictive checks.

  16. Global sensitivity analysis, probabilistic calibration, and predictive assessment for the data assimilation linked ecosystem carbon model

    DOE PAGES

    Safta, C.; Ricciuto, Daniel M.; Sargsyan, Khachik; ...

    2015-07-01

    In this paper we propose a probabilistic framework for an uncertainty quantification (UQ) study of a carbon cycle model and focus on the comparison between steady-state and transient simulation setups. A global sensitivity analysis (GSA) study indicates the parameters and parameter couplings that are important at different times of the year for quantities of interest (QoIs) obtained with the data assimilation linked ecosystem carbon (DALEC) model. We then employ a Bayesian approach and a statistical model error term to calibrate the parameters of DALEC using net ecosystem exchange (NEE) observations at the Harvard Forest site. The calibration results are employedmore » in the second part of the paper to assess the predictive skill of the model via posterior predictive checks.« less

  17. Prediction of three social cognitive-motivational structure types.

    PubMed

    Malerstein, A J; Ahern, M M; Pulos, S

    2001-10-01

    Previously, using interviews from Baumrind's longitudinal study, three cognitive-motivational structures (CMSs) were predicted in 68 adolescents from caregiving settings and from the CMS types of their mothers, based on the mothers' interviews elicited six years earlier. CMS theory proposes that during Piaget's Concrete Operational Period care-receiving influences the child's adoption of a social cognitive style, which corresponds to one of Piaget's stages of cognitive development. One who is classified as an Operational experiences the caregiving setting as tuned to the child's long-term interests, becomes focused on function and control of function and grasps the distinctions between and gradations of social attributes. One classified as future Intuitive experiences the caregiving as insufficient or unreliable and becomes focused on getting and having, and assesses social situations based on current striking dimensions. A person classified as being future Symbolic experiences the caregiving as out of tune with the self or the world, becomes focused on identity and emotional closeness, and may define self or object by a single attribute. This previous study did not distinguish between the influence of caregiving (including mothers' CMS) on the formation of adolescent CMS type and the possible constancy of CMS type from ages 9 to 15 years. The current study was designed to distinguish between these two possibilities, using data from 67 of the same mothers. Mothers' interviews were purged of descriptions of her child's behavior. Another interview was composed of the purged descriptions of child behavior. This was also done for interviews held when the child was 4 and 15 as well as at 9. From interviews with descriptions of child behavior purged, mother's CMS type at the child's age of 4 and 9 yr. agreed with her adolescent's previously assigned CMS type (p<.05), and caregiving setting at 9 years predicted the adolescent's CMS type (p<.05). From interviews composed

  18. Socially organized sentiments: Exploring the link between religious density and protest mobilization, 1960-1995.

    PubMed

    Kim, Hyun Woo; McCarthy, John D

    2016-11-01

    Extensive research has shown individual religiosity to have an impact upon U.S. protest participation. But very little work has examined the role of religious density in a community on the likelihood of protest mobilization. Our research links the religious density across 62 counties in New York State to various protest mobilization issues during the period of 1960-1995. In this research, we develop a theory of socially organized sentiments to examine religious influences on overall protest event mobilizations in local communities, a specific example of a more general theory that can link community structure to multiple forms of civic engagement. The impact of various religious traditions is assessed by using measures for the density of religious population per congregation of three religious traditions-Mainline Protestantism, Evangelical Protestantism and Catholicism. The analysis also assesses the likelihood of mobilization concerning four specific issues-African-American civil rights, gender, anti-nuclear/peace, and anti-poverty movements.

  19. What Factors Predict Who Will Have a Strong Social Network Following a Stroke?

    ERIC Educational Resources Information Center

    Northcott, Sarah; Marshall, Jane; Hilari, Katerina

    2016-01-01

    Purpose: Measures of social networks assess the number and nature of a person's social contacts, and strongly predict health outcomes. We explored how social networks change following a stroke and analyzed concurrent and baseline predictors of social networks 6 months poststroke. Method: We conducted a prospective longitudinal observational study.…

  20. What Factors Predict Who Will Have a Strong Social Network Following a Stroke?

    ERIC Educational Resources Information Center

    Northcott, Sarah; Marshall, Jane; Hilari, Katerina

    2016-01-01

    Purpose: Measures of social networks assess the number and nature of a person's social contacts, and strongly predict health outcomes. We explored how social networks change following a stroke and analyzed concurrent and baseline predictors of social networks 6 months poststroke. Method: We conducted a prospective longitudinal observational study.…

  1. Linking parental socialization about discrimination to intergroup attitudes: The role of social dominance orientation and cultural identification.

    PubMed

    Su, Jenny C; Gries, Peter H; Lee, I-Ching; Tran, Alisia G T T

    2017-07-01

    This study investigated the interaction of parental socialization about discrimination and social dominance orientation (SDO) in predicting the cultural identity and intergroup attitudes of the Minnanese, an ethnic group in Taiwan that faced systematic discrimination during the early decades of Chinese Nationalist rule. Because high SDO individuals tend to support group-based dominance, we hypothesized that under high preparation for bias, which may reinforce narratives that place the historically disadvantaged Taiwanese in a subordinate position, Minnanese high in SDO would identify less with Taiwanese and more with Chinese (the historically high-status outgroup) compared with their low SDO counterparts. We examined our hypotheses using a sample of Minnanese (N = 365; 183 women, 182 men; average age = 44.35) who participated in a nationally representative survey of Taiwanese adults. As predicted, among Minnanese exposed to high levels of preparation for bias, those with high SDO expressed greater levels of Chinese identification and more favorable attitudes toward Chinese than their low SDO counterparts (no difference was found in attitudes toward Taiwanese). Among Minnanese exposed to low levels of preparation for bias, SDO predicted neither Chinese nor Taiwanese identity. Moreover, the interaction effect of preparation for bias and SDO on attitudes toward Chinese was mediated by Chinese identity. Using a unique, non-Western sample, this study demonstrated the role that parental socialization about past discrimination, in combination with belief in group-based dominance, plays in the construction of group identity and intergroup attitudes among members of historically disadvantaged ethnic groups. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  2. Time development in the early history of social networks: link stabilization, group dynamics, and segregation.

    PubMed

    Bruun, Jesper; Bearden, Ian G

    2014-01-01

    Studies of the time development of empirical networks usually investigate late stages where lasting connections have already stabilized. Empirical data on early network history are rare but needed for a better understanding of how social network topology develops in real life. Studying students who are beginning their studies at a university with no or few prior connections to each other offers a unique opportunity to investigate the formation and early development of link patterns and community structure in social networks. During a nine week introductory physics course, first year physics students were asked to identify those with whom they communicated about problem solving in physics during the preceding week. We use these students' self reports to produce time dependent student interaction networks. We investigate these networks to elucidate possible effects of different student attributes in early network formation. Changes in the weekly number of links show that while roughly half of all links change from week to week, students also reestablish a growing number of links as they progress through their first weeks of study. Using the Infomap community detection algorithm, we show that the networks exhibit community structure, and we use non-network student attributes, such as gender and end-of-course grade to characterize communities during their formation. Specifically, we develop a segregation measure and show that students structure themselves according to gender and pre-organized sections (in which students engage in problem solving and laboratory work), but not according to end-of-coure grade. Alluvial diagrams of consecutive weeks' communities show that while student movement between groups are erratic in the beginning of their studies, they stabilize somewhat towards the end of the course. Taken together, the analyses imply that student interaction networks stabilize quickly and that students establish collaborations based on who is immediately

  3. Linking academic social environments, ego-identity formation, ego virtues, and academic success.

    PubMed

    Good, Marie; Adams, Gerald R

    2008-01-01

    This study used Structural Equation Modeling to test an Eriksonian conceptual model linking academic social environments (relationships with faculty and fellow students), ego-identity formation, ego virtues, and academic success. Participants included 765 first-year students at a university in southern Ontario, Canada. Results indicated that supportive relationships with faculty was directly related to higher average grades and perceived academic ability, whereas positive relationships with fellow students was indirectly related to academic success through ego virtues. Positive ego-identity formation (identity achievement) was also indirectly related to academic success through ego virtues.

  4. Telecare and Social Link Solution for Ambient Assisted Living Using a Robot Companion with Visiophony

    NASA Astrophysics Data System (ADS)

    Varène, Thibaut; Hillereau, Paul; Simonnet, Thierry

    An increasing number of people are in need of help at home (elderly, isolated and/or disabled persons; people with mild cognitive impairment). Several solutions can be considered to maintain a social link while providing tele-care to these people. Many proposals suggest the use of a robot acting as a companion. In this paper we will look at an environment constrained solution, its drawbacks (such as latency) and its advantages (flexibility, integration…). A key design choice is to control the robot using a unified Voice over Internet Protocol (VoIP) solution, while addressing bandwidth limitations, providing good communication quality and reducing transmission latency

  5. Predictive statistical models linking antecedent meteorological conditions and waterway bacterial contamination in urban waterways.

    PubMed

    Farnham, David J; Lall, Upmanu

    2015-06-01

    Although the relationships between meteorological conditions and waterway bacterial contamination are being better understood, statistical models capable of fully leveraging these links have not been developed for highly urbanized settings. We present a hierarchical Bayesian regression model for predicting transient fecal indicator bacteria contamination episodes in urban waterways. Canals, creeks, and rivers of the New York City harbor system are used to examine the model. The model configuration facilitates the hierarchical structure of the underlying system with weekly observations nested within sampling sites, which in turn were nested inside of the harbor network. Models are compared using cross-validation and a variety of Bayesian and classical model fit statistics. The uncertainty of predicted enterococci concentration values is reflected by sampling from the posterior predictive distribution. Issuing predictions with the uncertainty reasonably reflected allows a water manager or a monitoring agency to issue warnings that better reflect the underlying risk of exposure. A model using only antecedent meteorological conditions is shown to correctly classify safe and unsafe levels of enterococci with good accuracy. The hierarchical Bayesian regression approach is most valuable where transient fecal indicator bacteria contamination is problematic and drainage network data are scarce.

  6. Predicted Molecular Effects of Sequence Variants Link to System Level of Disease

    PubMed Central

    Bromberg, Yana; Rost, Burkhard

    2016-01-01

    Developments in experimental and computational biology are advancing our understanding of how protein sequence variation impacts molecular protein function. However, the leap from the micro level of molecular function to the macro level of the whole organism, e.g. disease, remains barred. Here, we present new results emphasizing earlier work that suggested some links from molecular function to disease. We focused on non-synonymous single nucleotide variants, also referred to as single amino acid variants (SAVs). Building upon OMIA (Online Mendelian Inheritance in Animals), we introduced a curated set of 117 disease-causing SAVs in animals. Methods optimized to capture effects upon molecular function often correctly predict human (OMIM) and animal (OMIA) Mendelian disease-causing variants. We also predicted effects of human disease-causing variants in the mouse model, i.e. we put OMIM SAVs into mouse orthologs. Overall, fewer variants were predicted with effect in the model organism than in the original organism. Our results, along with other recent studies, demonstrate that predictions of molecular effects capture some important aspects of disease. Thus, in silico methods focusing on the micro level of molecular function can help to understand the macro system level of disease. PMID:27536940

  7. Explaining the pathway from familial and peer social support to disordered eating: Is body dissatisfaction the link for male and female adolescents?

    PubMed

    Kirsch, Alexandra C; Shapiro, Jenna B; Conley, Colleen S; Heinrichs, Gretchen

    2016-08-01

    This study examined if familial and peer social support longitudinally predicted disordered eating for late adolescents in the transitional first year of college, and if body dissatisfaction mediated this relation. Gender differences between support types and disordered eating, and body dissatisfaction as a mediator, were also examined. 651 late adolescent males and females (Mage=18.47) completed measures of social support at the end of the first semester of college and of disordered eating and body image approximately five months later, at the end of the first year. Lower levels of familial social support prospectively predicted greater disordered eating, but not greater body dissatisfaction, and lower levels of peer social support prospectively predicted greater body dissatisfaction but not greater disordered eating, above and beyond the other type of social support type, prior levels of body dissatisfaction, disordered eating, and BMI. Body dissatisfaction did not mediate the relation between familial social support and disordered eating; however, it did significantly mediate the non-significant relation between peer social support and disordered eating, which was further moderated by gender. These findings suggest that parental social support remains a significant predictor of disordered eating for late adolescents even after they transition to college, and has a stronger relation to disordered eating than peer support. In contrast, peer social support seems to be especially linked to feelings of body dissatisfaction and may be an avenue for intervention of this type of negative self-perception that is a risk factor for later disordered eating. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Molecular dynamics simulations of highly cross-linked polymer networks: prediction of thermal and mechanical properties

    NASA Astrophysics Data System (ADS)

    Shenogina, Natalia; Tsige, Mesfin; Mukhopadhyay, Sharmila; Patnaik, Soumya

    2012-02-01

    We use all-atom molecular dynamics (MD) simulations to predict the mechanical and thermal properties of thermosetting polymers. Atomistic simulation is a promising tool which can provide detailed structure-property relationships of densely cross-linked polymer networks. In this work we study the thermo-mechanical properties of thermosetting polymers based on amine curing agents and epoxy resins and have focused on the DGEBA/DETDA epoxy system. At first we describe the modeling approach to construction of realistic all-atom models of densely cross-linked polymer matrices. Subsequently, a series of atomistic simulations was carried out to examine the simulation cell size effect as well as the role of cross-linking density and chain length of the resin strands on thermo-mechanical properties at different temperatures. Two different methods were used to deform the polymer networks. Both static and dynamic approaches to calculating the mechanical properties were considered and the thermo-mechanical properties obtained from our simulations were found in reasonable agreement with experimental values.

  9. Link functions in multi-locus genetic models: implications for testing, prediction, and interpretation.

    PubMed

    Clayton, David

    2012-05-01

    "Complex" diseases are, by definition, influenced by multiple causes, both genetic and environmental, and statistical work on the joint action of multiple risk factors has, for more than 40 years, been dominated by the generalized linear model (GLM). In genetics, models for dichotomous traits have traditionally been approached via the model of an underlying, normally distributed, liability. This corresponds to the GLM with binomial errors and a probit link function. Elsewhere in epidemiology, however, the logistic regression model, a GLM with logit link function, has been the tool of choice, largely because of its convenient properties in case-control studies. The choice of link function has usually been dictated by mathematical convenience, but it has some important implications in (a) the choice of association test statistic in the presence of existing strong risk factors, (b) the ability to predict disease from genotype given its heritability, and (c) the definition, and interpretation of epistasis (or epistacy). These issues are reviewed, and a new association test proposed.

  10. Microbial functional diversity enhances predictive models linking environmental parameters to ecosystem properties.

    PubMed

    Powell, Jeff R; Welsh, Allana; Hallin, Sara

    2015-07-01

    Microorganisms drive biogeochemical processes, but linking these processes to real changes in microbial communities under field conditions is not trivial. Here, we present a model-based approach to estimate independent contributions of microbial community shifts to ecosystem properties. The approach was tested empirically, using denitrification potential as our model process, in a spatial survey of arable land encompassing a range of edaphic conditions and two agricultural production systems. Soil nitrate was the most important single predictor of denitrification potential (the change in Akaike's information criterion, corrected for sample size, ΔAIC(c) = 20.29); however, the inclusion of biotic variables (particularly the evenness and size of denitrifier communities [ΔAIC(c) = 12.02], and the abundance of one denitrifier genotype [ΔAIC(c) = 18.04]) had a substantial effect on model precision, comparable to the inclusion of abiotic variables (biotic R2 = 0.28, abiotic R2 = 0.50, biotic + abiotic R2 = 0.76). This approach provides a valuable tool for explicitly linking microbial communities to ecosystem functioning. By making this link, we have demonstrated that including aspects of microbial community structure and diversity in biogeochemical models can improve predictions of nutrient cycling in ecosystems and enhance our understanding of ecosystem functionality.

  11. A five year review of paediatric burns and social deprivation: Is there a link?

    PubMed

    Richards, Helen; Kokocinska, Maria; Lewis, Darren

    2017-09-01

    To establish if there is a correlation between burn incidence and social deprivation in order to formulate a more effective burns prevention strategy. A quantitative retrospective review of International Burn Injury Database (IBID) was carried out over a period from 2006 to 2011 to obtain data for children referred to our burns centre in West Midlands. Social deprivation scores for geographical areas were obtained from Office of National Statistics (ONS). Statistical analysis was carried out using Graphpad Prism. 1688 children were reviewed at our burns centre. Statistical analysis using Pearson correlation coefficient showed a slight association between social deprivation and increasing burn incidence r(2)=0.1268, 95% confidence interval 0.018-0.219, p value<0.0001. There was a slight male preponderance (58%). The most common mechanism of injury was scalding (61%). The most commonly affected age group were 1-2 year olds (38%). There were statistically significant differences in the ethnicity of children with significantly more children from Asian and African backgrounds being referred compared to Caucasian children. We found that appropriate first aid was administered in 67% of cases overall. We did not find a statistically significant link between first aid provision and social deprivation score. There was only a slight positive correlation between social deprivation and burn incidence. However, there did not seem to be any change in mechanism of burn in the most deprived groups compared to overall pattern, nor was there a significant difference in appropriate first aid provision. It would seem that dissemination of burn prevention strategies and first aid advice need to be improved across all geographical areas as this was uniformly lacking and the increased burn incidence in more socially deprived groups, although present, was not statistically significant. Copyright © 2017 Elsevier Ltd and ISBI. All rights reserved.

  12. Links between inflammation, amygdala reactivity, and social support in breast cancer survivors.

    PubMed

    Muscatell, Keely A; Eisenberger, Naomi I; Dutcher, Janine M; Cole, Steven W; Bower, Julienne E

    2016-03-01

    Psychosocial stress can affect inflammatory processes that have important consequences for cancer outcomes and the behavioral side effects of cancer treatment. To date, however, little is known about the upstream neural processes that may link psychosocial stressors and inflammation in cancer patients and survivors. To address this issue, 15 women who had been diagnosed with early-stage breast cancer and completed cancer treatment and 15 age- and ethnicity-matched women with no cancer history were recruited for a neuroimaging study. Participants provided a blood sample for levels of circulating inflammatory markers (CRP and IL-6), underwent an fMRI scan in which they completed a threat reactivity task designed to elicit activity in the amygdala, and reported their levels of perceived social attachment/support. There were no significant differences between cancer survivors and controls in levels of CRP or IL-6, in amygdala reactivity to the socially threatening images, or in levels of perceived social support. However, results showed a strong, positive correlation between CRP concentration and left amygdala reactivity in the survivor group that was not apparent in controls. Higher levels of social support in the survivor group were also associated with reduced amygdala reactivity and CRP. These data suggest the possibility of a stronger "neural-immune pipeline" among breast cancer survivors, such that peripheral inflammation is more strongly associated with neural activity in threat-related brain regions.

  13. Social and Built Environmental Correlates of Predicted Blood Lead Levels in the Flint Water Crisis.

    PubMed

    Sadler, Richard Casey; LaChance, Jenny; Hanna-Attisha, Mona

    2017-05-01

    To highlight contextual factors tied to increased blood lead level (BLL) risk following the lead-in-water contamination in Flint, Michigan. Using geocoded BLL data collected in 2013 and 2015 and areal interpolation, we predicted BLLs at every residential parcel in the city. We then spatially joined social and built environmental variables to link the parcels with neighborhood-level factors that may influence BLLs. When we compared levels before and during the water crisis, we saw the highest estimates of predicted BLLs during the water crisis and the greatest changes in BLLs in neighborhoods with the longest water residence time in pipes (μ = 2.30 µg/dL; Δ = 0.45 µg/dL), oldest house age (μ = 2.22 µg/dL; Δ = 0.37 µg/dL), and poorest average neighborhood housing condition (μ = 2.18 µg/dL; Δ = 0.44 µg/dL). Key social and built environmental variables correlate with BLL; such information can continue to guide response by prioritizing older, deteriorating neighborhoods with the longest water residence time in pipes.

  14. Predicting aggression in adolescence: The interrelation between (a lack of) empathy and social goals.

    PubMed

    van Hazebroek, Babette C M; Olthof, Tjeert; Goossens, Frits A

    2017-04-01

    In an attempt to explain the inconsistent findings and overall weak relation between empathy and aggression, we focused on the role of emotional empathy (emotions of concern, compassion or sympathy toward a (potential) victim), agentic goals (the desire to be dominant during social interaction with peers) and their interplay (mediation or moderation) in the prediction of proactive aggression (learned instrumental behavior) in adolescence. Data were collected from 550 young Dutch adolescents, who filled out multiple questionnaires. Findings showed that the link between a lack of empathic concern and proactive aggression is partly mediated and moderated by agentic goals. The moderation analyses showed that the predictive value of a lack of empathic concern with regard to proactive aggression was greater when adolescents reported a stronger desire to be dominant in social situations with peers. In addition, the findings supported the assumption that the relation between empathic concern and reactive aggression (a hostile and angry response to perceived provocation) is not mediated or moderated by agentic goals. Findings were discussed in terms of their implications for future research. Aggr. Behav. 43:204-214, 2017. © 2016 Wiley Periodicals, Inc.

  15. Using Social Identity to Explore the Link between a Decline in Adolescent Smoking and an Increase in Mobile Phone Use

    ERIC Educational Resources Information Center

    Cassidy, Simon

    2006-01-01

    Purpose--The study seeks to further explore the hypothesised link between the increase in mobile phone ownership and use and the reported decline in adolescent smoking. Evidence for the link was gathered by examining perceptions of mobile phone use in the context of social identity and adolescent smoking. Design/methodology/approach--The study…

  16. Using Social Identity to Explore the Link between a Decline in Adolescent Smoking and an Increase in Mobile Phone Use

    ERIC Educational Resources Information Center

    Cassidy, Simon

    2006-01-01

    Purpose--The study seeks to further explore the hypothesised link between the increase in mobile phone ownership and use and the reported decline in adolescent smoking. Evidence for the link was gathered by examining perceptions of mobile phone use in the context of social identity and adolescent smoking. Design/methodology/approach--The study…

  17. Linking Local Food Systems and the Social Economy? Future Roles for Farmers' Markets in Alberta and British Columbia

    ERIC Educational Resources Information Center

    Wittman, Hannah; Beckie, Mary; Hergesheimer, Chris

    2012-01-01

    Often organized as grassroots, nonprofit organizations, many farmers' markets serve as strategic venues linking producers and consumers of local food while fulfilling multiple social, economic, and environmental objectives. This article examines the potential of farmers' markets to play a catalyst role in linking local food systems to the social…

  18. Linking Local Food Systems and the Social Economy? Future Roles for Farmers' Markets in Alberta and British Columbia

    ERIC Educational Resources Information Center

    Wittman, Hannah; Beckie, Mary; Hergesheimer, Chris

    2012-01-01

    Often organized as grassroots, nonprofit organizations, many farmers' markets serve as strategic venues linking producers and consumers of local food while fulfilling multiple social, economic, and environmental objectives. This article examines the potential of farmers' markets to play a catalyst role in linking local food systems to the social…

  19. Librarians as Advocates of Social Media for Researchers: A Social Media Project Initiated by Linköping University Library, Sweden

    ERIC Educational Resources Information Center

    Persson, Sassa; Svenningsson, Maria

    2016-01-01

    Librarians at Linköping University help researchers keep abreast of developments in their fields and to increase the visibility of their work. Strategic, professional use of social media ought to be an essential part of a researcher's communication strategy. This article investigates the level of awareness of the professional use of social media…

  20. Librarians as Advocates of Social Media for Researchers: A Social Media Project Initiated by Linköping University Library, Sweden

    ERIC Educational Resources Information Center

    Persson, Sassa; Svenningsson, Maria

    2016-01-01

    Librarians at Linköping University help researchers keep abreast of developments in their fields and to increase the visibility of their work. Strategic, professional use of social media ought to be an essential part of a researcher's communication strategy. This article investigates the level of awareness of the professional use of social media…

  1. Using LinkedIn in the Marketing Classroom: Exploratory Insights and Recommendations for Teaching Social Media/Networking

    ERIC Educational Resources Information Center

    McCorkle, Denny E.; McCorkle, Yuhua Li

    2012-01-01

    With the rapid growth of social networking and media comes their consideration for use in the marketing classroom. Social networking skills are becoming essential for personal branding (e.g., networking, self-marketing) and corporate/product branding (e.g., marketing communication). This paper addresses the use of LinkedIn (i.e., an online…

  2. Core dimensions of personality broadly account for the link from perceived social support to symptoms of depression and anxiety.

    PubMed

    Lewis, Gary J; Bates, Timothy C; Posthuma, Danielle; Polderman, Tinca J C

    2014-08-01

    Specific personality traits and poor social support are risk factors for anxiety and depression. Little work, however, has considered the effects of social support and personality on these aspects of psychopathology simultaneously. We examined whether perceived social support mediates the effects of core personality domains on symptoms of anxiety and depression. Measures of personality (based on the Five-Factor Model [FFM]), perceived social support, and symptoms of depression and anxiety were collected in a large Dutch adult population-based sample (n = 555), and, except for depression symptoms, in an independent U.S. adult population-based sample (n = 511). Path modeling was used to test the effects of FFM traits on symptoms of depression and anxiety, with and without the mediation of perceived social support. Social support showed no link to symptoms of anxiety and only modest links to symptoms of depression when controlling for the FFM traits. Neuroticism had the strongest effect on symptoms of both depression and anxiety, with Extraversion also showing links to symptoms of depression. Social support has limited influence on symptoms of depression, and no effects on anxiety, over and above the effects of personality. Links between social support and anxiety/depression may largely reflect influences of Neuroticism and Extraversion.

  3. Links between Local Language Competence and Peer Relations among Swiss and Immigrant Children: The Mediating Role of Social Behavior

    ERIC Educational Resources Information Center

    von Grunigen, Renate; Kochenderfer-Ladd, Becky; Perren, Sonja; Alsaker, Francoise D.

    2012-01-01

    The primary aim of this investigation was to evaluate a model in which children's social behaviors, including prosocial behavior, setting limits, and social withdrawal, were hypothesized to mediate the links between local language competence (LLC) and peer acceptance and victimization. Longitudinal data were collected via teacher and peer reports…

  4. Managing Threat: Do Social-Cognitive Processes Mediate the Link between Peer Victimization and Adjustment Problems in Early Adolescence?

    ERIC Educational Resources Information Center

    Hoglund, Wendy L.; Leadbeater, Bonnie J.

    2007-01-01

    Peer victimization has been linked concurrently and over time with multiple adjustment problems. However, the reasons for this multi-finality in victimization are not well understood. The current study examines social-cognitive processes (hostile attributions, social perspective awareness, and interpersonal skills) as mediators of the relations…

  5. Links between Social and Linguistic Processing of Speech in Preschool Children with Autism: Behavioral and Electrophysiological Measures

    ERIC Educational Resources Information Center

    Kuhl, Patricia K.; Coffey-Corina, Sharon; Padden, Denise; Dawson, Geraldine

    2005-01-01

    Data on typically developing children suggest a link between social interaction and language learning, a finding of interest both to theories of language and theories of autism. In this study, we examined social and linguistic processing of speech in preschool children with autism spectrum disorder (ASD) and typically developing chronologically…

  6. Links between Local Language Competence and Peer Relations among Swiss and Immigrant Children: The Mediating Role of Social Behavior

    ERIC Educational Resources Information Center

    von Grunigen, Renate; Kochenderfer-Ladd, Becky; Perren, Sonja; Alsaker, Francoise D.

    2012-01-01

    The primary aim of this investigation was to evaluate a model in which children's social behaviors, including prosocial behavior, setting limits, and social withdrawal, were hypothesized to mediate the links between local language competence (LLC) and peer acceptance and victimization. Longitudinal data were collected via teacher and peer reports…

  7. Executive Function as a Mediator in the Link between Attention-Deficit/Hyperactivity Disorder and Social Problems

    ERIC Educational Resources Information Center

    Tseng, Wan-Ling; Gau, Susan Shur-Fen

    2013-01-01

    Background: Cognitive processes and mechanisms underlying the strong link between attention-deficit/hyperactivity disorder (ADHD) and social problems remain unclear. Limited knowledge also exists regarding a subgroup of youth with ADHD who do not have social problems. This study investigated the extent to which executive function (EF) mediated the…

  8. Using LinkedIn in the Marketing Classroom: Exploratory Insights and Recommendations for Teaching Social Media/Networking

    ERIC Educational Resources Information Center

    McCorkle, Denny E.; McCorkle, Yuhua Li

    2012-01-01

    With the rapid growth of social networking and media comes their consideration for use in the marketing classroom. Social networking skills are becoming essential for personal branding (e.g., networking, self-marketing) and corporate/product branding (e.g., marketing communication). This paper addresses the use of LinkedIn (i.e., an online…

  9. Executive Function as a Mediator in the Link between Attention-Deficit/Hyperactivity Disorder and Social Problems

    ERIC Educational Resources Information Center

    Tseng, Wan-Ling; Gau, Susan Shur-Fen

    2013-01-01

    Background: Cognitive processes and mechanisms underlying the strong link between attention-deficit/hyperactivity disorder (ADHD) and social problems remain unclear. Limited knowledge also exists regarding a subgroup of youth with ADHD who do not have social problems. This study investigated the extent to which executive function (EF) mediated the…

  10. Are emotion and mind understanding differently linked to young children's social adjustment? Relationships between behavioral consequences of emotions, false belief, and SCBE.

    PubMed

    Deneault, Joane; Ricard, Marcelle

    2013-01-01

    According to empirical findings, emotional knowledge and false belief understanding seem to be differently linked to social adjustment. However, whereas false belief is assessed through the capacity to identify its behavioral consequences, emotion tasks usually rely on the comprehension of facial expressions and of the situational causes of emotions. The authors examined if the documented relationship between social adjustment and emotion knowledge in children extends to the understanding of behavioral consequences of emotions. Eighty French-speaking preschoolers undertook false belief and consequence-of-emotion tasks. Their social adjustment was measured by the Social Competence and Behavior Evaluation. Children's language ability, their parent's level of education, and the familial socioeconomic score were taken into account. Results showed that children's social adjustment was significantly predicted by their knowledge of emotion, but not by their understanding of false belief. The findings confirm the special status of emotion among mental states for social adaptation and specify which dimensions of adaptation to peers and adults are predicted by the child's emotion understanding. They also suggest that the distinction between mind and emotion understanding may be conceptual rather than methodological.

  11. Predicting link directionality in gene regulation from gene expression profiles using volatility-constrained correlation.

    PubMed

    Ochiai, Tomoshiro; Nacher, Jose C

    2016-07-01

    To uncover potential disease molecular pathways and signaling networks, we do not only need undirected maps but also we need to infer the directionality of functional or physical interactions between cellular components. A wide range of methods for identifying functional interactions between genes relies on correlations between experimental gene expression measurements to some extent. However, the standard Pearson or Spearman correlation-based approaches can only determine undirected correlations between cellular components. Here, we apply a volatility-constrained correlation method for gene expression profiles that offers a new metric to capture directionality of interactions between genes. To evaluate the predictions we used four datasets distributed by the DREAM5 network inference challenge including an in silico-constructed network and three organisms such as S. aureus, E. coli and S. cerevisiae. The predictions performed by our proposed method were compared to a gold standard of experimentally verified directionality of genetic regulatory links. Our findings show that our method successfully predicts the genetic interaction directionality with a success rate higher than 0.5 with high statistical significance. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  12. Links between Family Gender Socialization Experiences in Childhood and Gendered Occupational Attainment in Young Adulthood

    PubMed Central

    Lawson, Katie M.; Crouter, Ann C.; McHale, Susan M.

    2015-01-01

    Gendered occupational segregation remains prevalent across the world. Although research has examined factors contributing to the low number of women in male-typed occupations – namely science, technology, engineering, and math – little longitudinal research has examined the role of childhood experiences in both young women’s and men’s later gendered occupational attainment. This study addressed this gap in the literature by examining family gender socialization experiences in middle childhood – namely parents’ attitudes and work and family life – as contributors to the gender typicality of occupational attainment in young adulthood. Using data collected from mothers, fathers, and children over approximately 15 years, the results revealed that the associations between childhood socialization experiences (∼10 years old) and occupational attainment (∼26 years old) depended on the sex of the child. For sons but not daughters, mothers’ more traditional attitudes towards women’s roles predicted attaining more gender-typed occupations. In addition, spending more time with fathers in childhood predicted daughters attaining less and sons acquiring more gender-typed occupations in young adulthood. Overall, evidence supports the idea that childhood socialization experiences help to shape individuals’ career attainment and thus contribute to gender segregation in the labor market. PMID:26977112

  13. Processes linking cultural ingroup bonds and mental health: the roles of social connection and emotion regulation

    PubMed Central

    Roberts, Nicole A.; Burleson, Mary H.

    2013-01-01

    Cultural and ethnic identities influence the relationships individuals seek out and how they feel and behave in these relationships, which can strongly affect mental and physical health through their impacts on emotions, physiology, and behavior. We proposed and tested a model in which ethnocultural identifications and ingroup affiliations were hypothesized explicitly to enhance social connectedness, which would in turn promote expectancy for effective regulation of negative emotions and reduce self-reported symptoms of depression and anxiety. Our sample comprised women aged 18–30 currently attending college in the Southwestern US, who self-identified as Hispanic of Mexican descent (MAs; n = 82) or as non-Hispanic White/European American (EAs; n = 234) and who completed an online survey. In the full sample and in each subgroup, stronger ethnocultural group identity and greater comfort with mainstream American culture were associated with higher social connectedness, which in turn was associated with expectancy for more effective regulation of negative emotions, fewer depressive symptoms, and less anxiety. Unexpectedly, preference for ingroup affiliation predicted lower social connectedness in both groups. In addition to indirect effects through social connection, direct paths from mainstream comfort and preference for ingroup affiliation to emotion regulation expectancy were found for EAs. Models of our data underscore that social connection is a central mechanism through which ethnocultural identities—including with one's own group and the mainstream cultural group—relate to mental health, and that emotion regulation may be a key aspect of this linkage. We use the term ethnocultural social connection to make explicit a process that, we believe, has been implied in the ethnic identity literature for many years, and that may have consequential implications for mental health and conceptualizations of processes underlying mental disorders. PMID:23450647

  14. Psychological pathways linking social support to health outcomes: a visit with the "ghosts" of research past, present, and future.

    PubMed

    Uchino, Bert N; Bowen, Kimberly; Carlisle, McKenzie; Birmingham, Wendy

    2012-04-01

    Contemporary models postulate the importance of psychological mechanisms linking perceived and received social support to physical health outcomes. In this review, we examine studies that directly tested the potential psychological mechanisms responsible for links between social support and health-relevant physiological processes (1980s-2010). Inconsistent with existing theoretical models, no evidence was found that psychological mechanisms such as depression, perceived stress, and other affective processes are directly responsible for links between support and health. We discuss the importance of considering statistical/design issues, emerging conceptual perspectives, and limitations of our existing models for future research aimed at elucidating the psychological mechanisms responsible for links between social support and physical health outcomes. Copyright © 2012 Elsevier Ltd. All rights reserved.

  15. The alliance relationship analysis of international terrorist organizations with link prediction

    NASA Astrophysics Data System (ADS)

    Fang, Ling; Fang, Haiyang; Tian, Yanfang; Yang, Tinghong; Zhao, Jing

    2017-09-01

    Terrorism is a huge public hazard of the international community. Alliances of terrorist organizations may cause more serious threat to national security and world peace. Understanding alliances between global terrorist organizations will facilitate more effective anti-terrorism collaboration between governments. Based on publicly available data, this study constructed a alliance network between terrorist organizations and analyzed the alliance relationships with link prediction. We proposed a novel index based on optimal weighted fusion of six similarity indices, in which the optimal weight is calculated by genetic algorithm. Our experimental results showed that this algorithm could achieve better results on the networks than other algorithms. Using this method, we successfully digged out 21 real terrorist organizations alliance from current data. Our experiment shows that this approach used for terrorist organizations alliance mining is effective and this study is expected to benefit the form of a more powerful anti-terrorism strategy.

  16. Array Simulations Platform (ASP) predicts NASA Data Link Module (NDLM) performance

    NASA Technical Reports Server (NTRS)

    Snook, Allen David

    1993-01-01

    Through a variety of imbedded theoretical and actual antenna patterns, the array simulation platform (ASP) enhanced analysis of the array antenna pattern effects for the KTx (Ku-Band Transmit) service of the NDLM (NASA Data Link Module). The ASP utilizes internally stored models of the NDLM antennas and can develop the overall pattern of antenna arrays through common array calculation techniques. ASP expertly assisted in the diagnosing of element phase shifter errors during KTx testing and was able to accurately predict the overall array pattern from combinations of the four internally held element patterns. This paper provides an overview of the use of the ASP software in the solving of array mis-phasing problems.

  17. Link prediction in complex networks based on an information allocation index

    NASA Astrophysics Data System (ADS)

    Pei, Panpan; Liu, Bo; Jiao, Licheng

    2017-03-01

    An important issue in link prediction of complex networks is to make full use of different kinds of available information simultaneously. To tackle this issue, recently, an information-theoretic model has been proposed and a novel Neighbor Set Information Index (NSI) has been designed. Motivated by this work, we proposed a more general information-theoretic model by further distinguishing the contributions from different variables of the available features. Then, by introducing the resource allocation process into the model, we designed a new index based on neighbor sets with a virtual information allocation process: Neighbor Set Information Allocation Index(NSIA). Experimental studies on real world networks from disparate fields indicate that NSIA performs well compared with NSI as well as other typical proximity indices.

  18. Bonding, Bridging, and Linking Social Capital and Self-Rated Health among Chinese Adults: Use of the Anchoring Vignettes Technique

    PubMed Central

    Chen, He; Meng, Tianguang

    2015-01-01

    Three main opposing camps exist over how social capital relates to population health, namely the social support perspective, the inequality thesis, and the political economy approach. The distinction among bonding, bridging, and linking social capital probably helps close the debates between these three camps, which is rarely investigated in existing literatures. Moreover, although self-rated health is a frequently used health indicator in studies on the relationship between social capital and health, the interpersonal incomparability of this measure has been largely neglected. This study has two main objectives. Firstly, we aim to investigate the relationship between bonding, bridging, and linking social capital and self-rated health among Chinese adults. Secondly, we aim to improve the interpersonal comparability in self-rated health measurement. We use data from a nationally representative survey in China. Self-rated health was adjusted using the anchoring vignettes technique to improve comparability. Two-level ordinal logistic regression was performed to model the association between social capital and self-rated health at both individual and community levels. The interaction between residence and social capital was included to examine urban/rural disparities in the relationship. We found that most social capital indicators had a significant relationship with adjusted self-rated health of Chinese adults, but the relationships were mixed. Individual-level bonding, linking social capital, and community-level bridging social capital were positively related with health. Significant urban/rural disparities appeared in the association between community-level bonding, linking social capital, and adjusted self-rated health. For example, people living in communities with higher bonding social capital tended to report poorer adjusted self-rated health in urban areas, but the opposite tendency held for rural areas. Furthermore, the comparison between multivariate analyses

  19. Do Social Network Characteristics Predict Mammography Screening Practices?

    ERIC Educational Resources Information Center

    Allen, Jennifer D.; Stoddard, Anne M.; Sorensen, Glorian

    2008-01-01

    Background: Many breast cancer outreach programs assume that dissemination of information through social networks and provision of social support will promote screening. The authors prospectively examined the relationship between social network characteristics and adherence to screening guidelines. Method: Employed women age 40 years and older…

  20. Social Emotional Learning and Educational Stress: A Predictive Model

    ERIC Educational Resources Information Center

    Arslan, Serhat

    2015-01-01

    The purpose of this study is to examine the relationship between social emotional learning and educational stress. Participants were 321 elementary students. Social emotional learning and educational stress scale were used as measures. The relationships between social emotional learning and educational stress were examined using correlation…

  1. Ways that Social Change Predicts Personal Quality of Life

    ERIC Educational Resources Information Center

    Cheung, Chau-Kiu; Leung, Kwok

    2010-01-01

    A notable way that social change affects personal quality of life would rely on the person's experience with social change. This experience may influence societal quality of life and quality of work life, which may in turn affect personal quality of life. Additionally, the experience of social change is possibly less detrimental to personal…

  2. Ways that Social Change Predicts Personal Quality of Life

    ERIC Educational Resources Information Center

    Cheung, Chau-Kiu; Leung, Kwok

    2010-01-01

    A notable way that social change affects personal quality of life would rely on the person's experience with social change. This experience may influence societal quality of life and quality of work life, which may in turn affect personal quality of life. Additionally, the experience of social change is possibly less detrimental to personal…

  3. Do Social Network Characteristics Predict Mammography Screening Practices?

    ERIC Educational Resources Information Center

    Allen, Jennifer D.; Stoddard, Anne M.; Sorensen, Glorian

    2008-01-01

    Background: Many breast cancer outreach programs assume that dissemination of information through social networks and provision of social support will promote screening. The authors prospectively examined the relationship between social network characteristics and adherence to screening guidelines. Method: Employed women age 40 years and older…

  4. Social Emotional Learning and Educational Stress: A Predictive Model

    ERIC Educational Resources Information Center

    Arslan, Serhat

    2015-01-01

    The purpose of this study is to examine the relationship between social emotional learning and educational stress. Participants were 321 elementary students. Social emotional learning and educational stress scale were used as measures. The relationships between social emotional learning and educational stress were examined using correlation…

  5. Predicting anxious response to a social challenge and hyperventilation: comparison of the ASI and ASI-3.

    PubMed

    Carter, Michele M; Sbrocco, Tracy; Ayati, Firouzeh

    2009-09-01

    This study compared the predictive ability of the original ASI to the ASI-3 and measures of trait and social anxiety in two challenge conditions; hyperventilation or a social challenge. During hyperventilation, the ASI-3 social concerns subscale was a better predictor than the subscales of the original ASI and measures of general trait and social anxiety. During the social manipulation, results indicated the ASI-3 social concerns subscale and the social anxiety measure were significant predictors of anxious response. Results provide evidence that the ASI-3 is an improvement over the original ASI and is a sound overall measure of response to challenge procedures.

  6. Social workers as "experts" in the family court system: is evidence-based practice a missing link or host-created knowledge?

    PubMed

    Prescott, Dana E

    2013-10-01

    The graduate school curriculum for social workers requires that students learn to critically distinguish between opinion-based knowledge and evidence-based practices, or empirically-supported interventions. Once graduated, licensed social workers are often called upon to offer diagnostic and predictive opinions as experts in a variety of macro-environments. When the family courts are that "host" environment, social workers proffer expert opinions that may categorize and label parents or children for purposes of a judge's allocation of physical or legal custody. In this article, it is suggested that the social work profession, within all three domains of education, practice, and research, should more precisely link the design and fidelity of an evidence-based practice (EBP) with its potential misapplication or warping when proffered as science in "host" environments like family courts. As Foucault and other scholars warn, the failure to verify that an intervention is applied correctly may actually enhance the risk of social injustice by interpreting and translating EBP knowledge in the non-empirical form of authority-by-license. This article, therefore, proposes that the social work profession, from the classroom to the field, has an obligation to thoroughly understand and engage interdisciplinary practices that assure respect for the strengths and limits of social work knowledge.

  7. Links between depressive symptoms and unmet health and social care needs among older prisoners

    PubMed Central

    O'Hara, Kate; Forsyth, Katrina; Webb, Roger; Senior, Jane; Hayes, Adrian Jonathan; Challis, David; Fazel, Seena; Shaw, Jenny

    2016-01-01

    Background: absolute numbers of older prisoners and their proportion of the total prison population are increasing. They have multiple health and social care needs that are prominent on entry into prison. No previous studies have identified older prisoners' health and social care needs at this crucial point. Objective: to examine unmet health and social care needs among older men entering prison and their links with depressive symptoms. Methods: a cross-sectional survey across nine prisons in the North of England was completed. One hundred male prisoners aged between 60 and 81 were interviewed, using the Camberwell Assessment of Need—Forensic short version (CANFOR-S) and Geriatric Depression Scale—Short Form (GDS-15). Descriptive statistics were generated and χ2 tests performed. Results: participants reported high levels of unmet needs as measured with the CANFOR-S, notably in the domains of knowledge about their condition and treatment (38%); psychological distress (34%); daytime activities (29%); benefits (28%); food (22%) and physical health (21%). The mean total number of unmet needs was 2.74, with a median of 2.0. More than half the sample (56%, 95% CI 45–66%) exhibited clinical signs of depression. A significant association between depressive symptomology and an unmet physical health need, as measured by the CANFOR-S, was detected (χ2 = 6.76, df = 1, P < 0.01). Conclusions: high levels of depressive symptoms were experienced by older prisoners on entry into prison. Personalised health and social care needs assessment and discrete depression screening are required on prison entry to facilitate effective management of unmet needs. PMID:26764402

  8. Links between depressive symptoms and unmet health and social care needs among older prisoners.

    PubMed

    O'Hara, Kate; Forsyth, Katrina; Webb, Roger; Senior, Jane; Hayes, Adrian Jonathan; Challis, David; Fazel, Seena; Shaw, Jenny

    2016-01-01

    absolute numbers of older prisoners and their proportion of the total prison population are increasing. They have multiple health and social care needs that are prominent on entry into prison. No previous studies have identified older prisoners' health and social care needs at this crucial point. to examine unmet health and social care needs among older men entering prison and their links with depressive symptoms. a cross-sectional survey across nine prisons in the North of England was completed. One hundred male prisoners aged between 60 and 81 were interviewed, using the Camberwell Assessment of Need-Forensic short version (CANFOR-S) and Geriatric Depression Scale-Short Form (GDS-15). Descriptive statistics were generated and χ(2) tests performed. participants reported high levels of unmet needs as measured with the CANFOR-S, notably in the domains of knowledge about their condition and treatment (38%); psychological distress (34%); daytime activities (29%); benefits (28%); food (22%) and physical health (21%). The mean total number of unmet needs was 2.74, with a median of 2.0. More than half the sample (56%, 95% CI 45-66%) exhibited clinical signs of depression. A significant association between depressive symptomology and an unmet physical health need, as measured by the CANFOR-S, was detected (χ(2) = 6.76, df = 1, P < 0.01). high levels of depressive symptoms were experienced by older prisoners on entry into prison. Personalised health and social care needs assessment and discrete depression screening are required on prison entry to facilitate effective management of unmet needs. © The Author 2016. Published by Oxford University Press on behalf of the British Geriatrics Society.

  9. Using Social Cognitive Theory to Predict Physical Activity and Fitness in Underserved Middle School Children

    ERIC Educational Resources Information Center

    Martin, Jeffrey J.; McCaughtry, Nate; Flory, Sara; Murphy, Anne; Wisdom, Kimberlydawn

    2011-01-01

    Few researchers have used social cognitive theory and environment-based constructs to predict physical activity (PA) and fitness in underserved middle-school children. Hence, we evaluated social cognitive variables and perceptions of the school environment to predict PA and fitness in middle school children (N = 506, ages 10-14 years). Using…

  10. Perceived morningness-eveningness predicts academic adjustment and substance use across university, but social jetlag is not to blame.

    PubMed

    Tavernier, Royette; Munroe, Melanie; Willoughby, Teena

    2015-01-01

    academic adjustment and substance use, indicating that social jetlag did not explain the link between perceived morningness-eveningness and negative psychosocial adjustment. An important finding was the significant predictive effect of higher substance use on social jetlag over time. Results of the present study highlight the importance of employing a longitudinal framework within which to specifically determine the direction of effects among the study variables in order to validate proposed theoretical models that aim to guide our understanding of how perceived morningness-eveningness, social jetlag, academic adjustment and substance use relate to each other.

  11. Closing the loop: a spatial analysis to link observed environmental damage to predicted heavy metal emissions.

    PubMed

    Colgan, Anja; Hankard, Peter K; Spurgeon, David J; Svendsen, Claus; Wadsworth, Richard A; Weeks, Jason M

    2003-05-01

    In many cases, the link between industrial emissions and damage to the environment can only be inferred. The Environment Agency of the United Kingdom imposes emissions limits on industrial sites so that predicted concentrations and deposition rates remain below standard thresholds. Estimates of appropriate critical levels and loads are usually based on laboratory results and rarely estimate synergistic effects between pollutants or consider biological adaptation or selection in the target receptor organisms. The Avonmouth smelter has been emitting zinc and other heavy metals since 1929. It has been the subject of a number of detailed and synoptic studies, especially the impact on soil invertebrates. Damage was assessed using both physiological and ecological measurements. Two methods of spatial analysis were investigated, namely interpolation using standard geographical information system (GIS) operators and atmospheric dispersal modeling using an off-the-shelf model. Both methods can be used to compute contours (isolines) of predicted biological effect. Correlation results show that dispersal modeling is at least as good as kriging but requires much less data. This article demonstrates the usefulness of GIS and dispersal models as tools in decision making to determine the most suitable sampling sites in the assessment and monitoring of the impact of contamination around major point sources.

  12. Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks.

    PubMed

    Staniczenko, Phillip P A; Sivasubramaniam, Prabu; Suttle, K Blake; Pearson, Richard G

    2017-06-01

    Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub-disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species' presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change. © 2017 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

  13. Disorganized symptoms and executive functioning predict impaired social functioning in subjects at risk for psychosis.

    PubMed

    Eslami, Ali; Jahshan, Carol; Cadenhead, Kristin S

    2011-01-01

    Predictors of social functioning deficits were assessed in 22 individuals "at risk" for psychosis. Disorganized symptoms and executive functioning predicted social functioning at follow-up. Early intervention efforts that focus on social and cognitive skills are indicated in this vulnerable population.

  14. Genetic links, family ties, and social bonds: rights and responsibilities in the face of genetic knowledge.

    PubMed

    Rhodes, R

    1998-02-01

    Currently, some of the most significant moral issues involving genetic links relate to genetic knowledge. In this paper, instead of looking at the frequently addressed issues of responsibilities professionals or institutions have to individuals, I take up the question of what responsibilities individuals have to one another with respect to genetic knowledge. I address the questions of whether individuals have a moral right to pursue their own goals without contributing to society's knowledge of population genetics, without adding to their family's knowledge of its genetic history, and without discovering genetic information about themselves and their offspring. These questions lead to an examination of the presumed right to genetic ignorance and an exploration of a variety of social bonds. Analyzing cases in light of these considerations leads to a surprising conclusion about a widely accepted precept of genetic counseling, to some ethical insights into typical problems, and to some further unanswered questions about personal responsibility in the face of genetic knowledge.

  15. The chameleon effect: the perception-behavior link and social interaction.

    PubMed

    Chartrand, T L; Bargh, J A

    1999-06-01

    The chameleon effect refers to nonconscious mimicry of the postures, mannerisms, facial expressions, and other behaviors of one's interaction partners, such that one's behavior passively and unintentionally changes to match that of others in one's current social environment. The authors suggest that the mechanism involved is the perception-behavior link, the recently documented finding (e.g., J. A. Bargh, M. Chen, & L. Burrows, 1996) that the mere perception of another's behavior automatically increases the likelihood of engaging in that behavior oneself. Experiment 1 showed that the motor behavior of participants unintentionally matched that of strangers with whom they worked on a task. Experiment 2 had confederates mimic the posture and movements of participants and showed that mimicry facilitates the smoothness of interactions and increases liking between interaction partners. Experiment 3 showed that dispositionally empathic individuals exhibit the chameleon effect to a greater extent than do other people.

  16. Social Cognitive and Emotional Mediators Link Violence Exposure and Parental Nurturance to Adolescent Aggression

    PubMed Central

    Su, Wei; Mrug, Sylvie; Windle, Michael

    2013-01-01

    This study examined aggressive fantasies, violence-approving attitudes, and empathy as mediators of the effects of violence exposure and parental nurturance on aggression. A total of 603 early adolescents participated in a two-wave study, reporting on violence exposure and parental nurturance at Wave 1 and the three mediators and aggression at Wave 2. Violence-approving attitudes mediated the effects of both violence exposure and low parental nurturance on aggression. Aggressive fantasies also mediated the effects of violence exposure and empathy mediated the effects of parental nurturance. The mediation pathways via which parental nurturance was linked to aggression differed across levels of violence exposure. In the context of high violence exposure, parental nurturance was related to lower aggression through higher social emotional empathy, but under low violence exposure, the effect was mediated by greater disapproval of violence. PMID:21058128

  17. Diversity policy, social dominance, and intergroup relations: predicting prejudice in changing social and political contexts.

    PubMed

    Guimond, Serge; Crisp, Richard J; De Oliveira, Pierre; Kamiejski, Rodolphe; Kteily, Nour; Kuepper, Beate; Lalonde, Richard N; Levin, Shana; Pratto, Felicia; Tougas, Francine; Sidanius, Jim; Zick, Andreas

    2013-06-01

    In contrast to authors of previous single-nation studies, we propose that supporting multiculturalism (MC) or assimilation (AS) is likely to have different effects in different countries, depending on the diversity policy in place in a particular country and the associated norms. A causal model of intergroup attitudes and behaviors, integrating both country-specific factors (attitudes and perceived norms related to a particular diversity policy) and general social-psychological determinants (social dominance orientation), was tested among participants from countries where the pro-diversity policy was independently classified as low, medium, or high (N = 1,232). Results showed that (a) anti-Muslim prejudice was significantly reduced when the pro-diversity policy was high; (b) countries differed strongly in perceived norms related to MC and AS, in ways consistent with the actual diversity policy in each country and regardless of participants' personal attitudes toward MC and AS; (c) as predicted, when these norms were salient, due to subtle priming, structural equation modeling with country included as a variable provided support for the proposed model, suggesting that the effect of country on prejudice can be successfully accounted by it; and (d) consistent with the claim that personal support for MC and AS played a different role in different countries, within-country mediation analyses provided evidence that personal attitudes toward AS mediated the effect of social dominance orientation on prejudice when pro-diversity policy was low, whereas personal attitudes toward MC was the mediator when pro-diversity policy was high. Thus, the critical variables shaping prejudice can vary across nations.

  18. Mixed Methodology to Predict Social Meaning for Decision Support

    DTIC Science & Technology

    2013-09-01

    structures in posts without style features boosted results for this group as well. We indicate how this approach may extend to popular social media sites...learning, social media 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES 30 19a...be applied to code-switched African language social media data in Zulu and Swahili to support the Army’s needs and to understand how identity in

  19. Neonatal imitation and early social experience predict gaze following abilities in infant monkeys.

    PubMed

    Simpson, Elizabeth A; Miller, Grace M; Ferrari, Pier F; Suomi, Stephen J; Paukner, Annika

    2016-02-01

    Individuals vary in their social skills and motivation, the causes of which remain largely unknown. Here we investigated whether an individual's propensity to interact with others measured within days after birth, and differences in infants' early social environment, may predict a later social skill. Specifically, we tested whether neonatal imitation--newborns' capacity to match modelled actions--and social experience in the first months of life predict gaze following (directing attention to locations where others look), in infant macaques (Macaca mulatta; n = 119). Facial gesture imitation in the first week of life predicted gaze following at 7 months of age. Imitators were better at gaze following than non-imitators, suggesting neonatal imitation may be an early marker predicting socio-cognitive functioning. In addition, infants with rich social environments outperformed infants with less socialization, suggesting early social experiences also support the development of infants' gaze following competence. The present study offers compelling evidence that an individual difference present from birth predicts a functional social cognitive skill in later infancy. In addition, this foundational skill--gaze following--is plastic, and can be improved through social interactions, providing infants with a strong foundation for later social interaction and learning.

  20. Role of Social Performance in Predicting Learning Problems: Prediction of Risk Using Logistic Regression Analysis

    ERIC Educational Resources Information Center

    Del Prette, Zilda Aparecida Pereira; Prette, Almir Del; De Oliveira, Lael Almeida; Gresham, Frank M.; Vance, Michael J.

    2012-01-01

    Social skills are specific behaviors that individuals exhibit in order to successfully complete social tasks whereas social competence represents judgments by significant others that these social tasks have been successfully accomplished. The present investigation identified the best sociobehavioral predictors obtained from different raters…

  1. Role of Social Performance in Predicting Learning Problems: Prediction of Risk Using Logistic Regression Analysis

    ERIC Educational Resources Information Center

    Del Prette, Zilda Aparecida Pereira; Prette, Almir Del; De Oliveira, Lael Almeida; Gresham, Frank M.; Vance, Michael J.

    2012-01-01

    Social skills are specific behaviors that individuals exhibit in order to successfully complete social tasks whereas social competence represents judgments by significant others that these social tasks have been successfully accomplished. The present investigation identified the best sociobehavioral predictors obtained from different raters…

  2. Performances and reliability predictions of optical data transmission links using a system simulator for aerospace applications

    NASA Astrophysics Data System (ADS)

    Bechou, L.; Deshayes, Y.; Aupetit-Berthelemot, C.; Guerin, A.; Tronche, C.

    Space missions for Earth Observation are called upon to carry a growing number of instruments in their payload, whose performances are increasing. Future space systems are therefore intended to generate huge amounts of data and a key challenge in coming years will therefore lie in the ability to transmit that significant quantity of data to ground. Thus very high data rate Payload Telemetry (PLTM) systems will be required to face the demand of the future Earth Exploration Satellite Systems and reliability is one of the major concern of such systems. An attractive approach associated with the concept of predictive modeling consists in analyzing the impact of components malfunctioning on the optical link performances taking into account the network requirements and experimental degradation laws. Reliability estimation is traditionally based on life-testing and a basic approach is to use Telcordia requirements (468GR) for optical telecommunication applications. However, due to the various interactions between components, operating lifetime of a system cannot be taken as the lifetime of the less reliable component. In this paper, an original methodology is proposed to estimate reliability of an optical communication system by using a dedicated system simulator for predictive modeling and design for reliability. At first, we present frameworks of point-to-point optical communication systems for space applications where high data rate (or frequency bandwidth), lower cost or mass saving are needed. Optoelectronics devices used in these systems can be similar to those found in terrestrial optical network. Particularly we report simulation results of transmission performances after introduction of DFB Laser diode parameters variations versus time extrapolated from accelerated tests based on terrestrial or submarine telecommunications qualification standards. Simulations are performed to investigate and predict the consequence of degradations of the Laser diode (acting as a

  3. Prediction and validation of gene-disease associations using methods inspired by social network analyses.

    PubMed

    Singh-Blom, U Martin; Natarajan, Nagarajan; Tewari, Ambuj; Woods, John O; Dhillon, Inderjit S; Marcotte, Edward M

    2013-01-01

    Correctly identifying associations of genes with diseases has long been a goal in biology. With the emergence of large-scale gene-phenotype association datasets in biology, we can leverage statistical and machine learning methods to help us achieve this goal. In this paper, we present two methods for predicting gene-disease associations based on functional gene associations and gene-phenotype associations in model organisms. The first method, the Katz measure, is motivated from its success in social network link prediction, and is very closely related to some of the recent methods proposed for gene-disease association inference. The second method, called Catapult (Combining dATa Across species using Positive-Unlabeled Learning Techniques), is a supervised machine learning method that uses a biased support vector machine where the features are derived from walks in a heterogeneous gene-trait network. We study the performance of the proposed methods and related state-of-the-art methods using two different evaluation strategies, on two distinct data sets, namely OMIM phenotypes and drug-target interactions. Finally, by measuring the performance of the methods using two different evaluation strategies, we show that even though both methods perform very well, the Katz measure is better at identifying associations between traits and poorly studied genes, whereas Catapult is better suited to correctly identifying gene-trait associations overall [corrected].

  4. Peer Victimization and Social Dominance as Intervening Variables of the Link between Peer Liking and Relational Aggression

    ERIC Educational Resources Information Center

    Adams, Ryan E.; Bartlett, Nancy H.; Bukowski, William M.

    2010-01-01

    The current study examined social dominance and peer victimization as possible intervening and moderating variables of the association between peer liking and relational aggression because previous findings suggest that social dominance and peer victimization are important for predicting the acceptableness and success of aggression. A total of 367…

  5. Peer Victimization and Social Dominance as Intervening Variables of the Link between Peer Liking and Relational Aggression

    ERIC Educational Resources Information Center

    Adams, Ryan E.; Bartlett, Nancy H.; Bukowski, William M.

    2010-01-01

    The current study examined social dominance and peer victimization as possible intervening and moderating variables of the association between peer liking and relational aggression because previous findings suggest that social dominance and peer victimization are important for predicting the acceptableness and success of aggression. A total of 367…

  6. Differential evolution based prediction of rain attenuation over a LOS terrestrial link situated in the southern United Kingdom

    NASA Astrophysics Data System (ADS)

    Develi, Ibrahim

    2007-06-01

    The principal objective of a rain attenuation prediction method is to achieve acceptable estimates of the attenuation incurred on the signal due to rain. In this paper, a differential evolution (DE) based model for predicting rain attenuation in a terrestrial point-to-point line of sight (LOS) link at 97 GHz is proposed using previously available experimental data obtained in the southern United Kingdom. Rainfall rate and percentage of time are used as input data in the proposed prediction model. Excellent agreement between the experimental data and the model output indicates that the presented DE based method may efficiently be used for accurate prediction of the rain attenuation levels.

  7. Attention/processing speed prospectively predicts social impairment 18 years later in mood disorders.

    PubMed

    Sarapas, Casey; Shankman, Stewart A; Harrow, Martin; Faull, Robert N

    2013-09-01

    Cross-sectional studies suggest that cognitive deficits contribute to psychosocial impairment among individuals with mood disorders. However, studies examining whether cognition prospectively predicts psychosocial outcome are few, have used short follow-up periods, and have not demonstrated incremental validity (i.e., that cognition predicts future functioning even when controlling for baseline functioning). In a sample of 51 individuals with unipolar depression or bipolar disorder, we investigated whether attention/processing speed (APS) performance predicted social functioning 18 years later. Baseline APS predicted 18-year social functioning even after controlling for baseline social functioning and depressive symptoms, demonstrating incremental validity. Individuals with high baseline APS had stable social functioning over 18 years, whereas functioning deteriorated among those with low APS. This finding helps clarify the temporal order of cognitive and psychosocial deficits associated with mood disorders and suggests the clinical utility of cognitive measures in identifying those at risk of deterioration in social functioning.

  8. Links between local language competence and peer relations among Swiss and immigrant children: the mediating role of social behavior.

    PubMed

    von Grünigen, Renate; Kochenderfer-Ladd, Becky; Perren, Sonja; Alsaker, Françoise D

    2012-04-01

    The primary aim of this investigation was to evaluate a model in which children's social behaviors, including prosocial behavior, setting limits, and social withdrawal, were hypothesized to mediate the links between local language competence (LLC) and peer acceptance and victimization. Longitudinal data were collected via teacher and peer reports on 541 (286 boys and 255 girls) immigrant and Swiss native 5-to-6 year-old kindergarteners. Results showed the immigrant children were less fluent in the local language compared to native Swiss classmates. Moreover, results from structural equation models, with bootstrap tests of indirect effects, indicated that social behaviors mediated the link between LLC and the quality of children's peer relationships. Implications of these findings for school professionals are discussed, such as the need to help immigrant children make a smoother transition to their host communities by providing additional language and social supports while children acculturate and acclimate to their new surroundings and peer group.

  9. Attentional bias to alcohol stimuli predicts elevated cue-induced craving in young adult social drinkers.

    PubMed

    Manchery, Linda; Yarmush, Devorah E; Luehring-Jones, Peter; Erblich, Joel

    2017-07-01

    Considerable evidence has identified biased cognitive processing of alcohol-related stimuli as an important factor in the maintenance of alcohol-seeking and relapse among individuals suffering from alcohol use-disorders (AUDs). In addition, a large body of research has demonstrated that exposure to alcohol cues can elicit powerful alcohol cravings. Little is known, however, about the possible relationship between attentional bias and cue-induced cravings, and even less is known about these processes in social drinkers without a personal history of AUDs. The goal of this study was to examine the possibility that attentional biases toward alcohol-related stimuli would predict elevated cue-induced alcohol craving in this population. Young adult social drinkers (N=30, Mean age=22.8±1.9, 61% female) recruited from an urban university population completed a visual dot probe task in which they were presented with alcohol and neutral stimulus pictures that were immediately followed by a visual probe replacing one of the pictures. Attentional bias was measured by calculating reaction times to probes that replaced alcohol stimuli vs. neutral stimuli. Participants then completed a classic alcohol cue-exposure task and reported cravings immediately before and after alcohol and neutral cue-exposures. Not surprisingly, exposure to alcohol cues elicited significant cravings. Consistent with the study hypothesis, larger attentional biases toward alcohol stimuli predicted higher levels of alcohol craving. Findings demonstrate that heightened attention to alcohol stimuli can significantly impact motivation to consume in healthy young adults, and suggest a possible pathway linking cognitive processes early in the drinking trajectory to the later development of AUDs. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Multivariate Brain Prediction of Heart Rate and Skin Conductance Responses to Social Threat.

    PubMed

    Eisenbarth, Hedwig; Chang, Luke J; Wager, Tor D

    2016-11-23

    Psychosocial stressors induce autonomic nervous system (ANS) responses in multiple body systems that are linked to health risks. Much work has focused on the common effects of stress, but ANS responses in different body systems are dissociable and may result from distinct patterns of cortical-subcortical interactions. Here, we used machine learning to develop multivariate patterns of fMRI activity predictive of heart rate (HR) and skin conductance level (SCL) responses during social threat in humans (N = 18). Overall, brain patterns predicted both HR and SCL in cross-validated analyses successfully (rHR = 0.54, rSCL = 0.58, both p < 0.0001). These patterns partly reflected central stress mechanisms common to both responses because each pattern predicted the other signal to some degree (rHR→SCL = 0.21 and rSCL→HR = 0.22, both p < 0.01), but they were largely physiological response specific. Both patterns included positive predictive weights in dorsal anterior cingulate and cerebellum and negative weights in ventromedial PFC and local pattern similarity analyses within these regions suggested that they encode common central stress mechanisms. However, the predictive maps and searchlight analysis suggested that the patterns predictive of HR and SCL were substantially different across most of the brain, including significant differences in ventromedial PFC, insula, lateral PFC, pre-SMA, and dmPFC. Overall, the results indicate that specific patterns of cerebral activity track threat-induced autonomic responses in specific body systems. Physiological measures of threat are not interchangeable, but rather reflect specific interactions among brain systems. We show that threat-induced increases in heart rate and skin conductance share some common representations in the brain, located mainly in the vmPFC, temporal and parahippocampal cortices, thalamus, and brainstem. However, despite these similarities, the brain patterns that predict these two autonomic responses are

  11. Genotyping Oral Commensal Bacteria to Predict Social Contact and Structure

    PubMed Central

    Wallace, Amelia D.; Riley, Lee W.

    2016-01-01

    Social network structure is a fundamental determinant of human health, from infectious to chronic diseases. However, quantitative and unbiased approaches to measuring social network structure are lacking. We hypothesized that genetic relatedness of oral commensal bacteria could be used to infer social contact between humans, just as genetic relatedness of pathogens can be used to determine transmission chains of pathogens. We used a traditional, questionnaire survey-based method to characterize the contact network of the School of Public Health at a large research university. We then collected saliva from a subset of individuals to analyze their oral microflora using a modified deep sequencing multilocus sequence typing (MLST) procedure. We examined micro-evolutionary changes in the S. viridans group to uncover transmission patterns reflecting social network structure. We amplified seven housekeeping gene loci from the Streptococcus viridans group, a group of ubiquitous commensal bacteria, and sequenced the PCR products using next-generation sequencing. By comparing the generated S. viridans reads between pairs of individuals, we reconstructed the social network of the sampled individuals and compared it to the network derived from the questionnaire survey-based method. The genetic relatedness significantly (p-value < 0.001) correlated with social distance in the questionnaire-based network, and the reconstructed network closely matched the network derived from the questionnaire survey-based method. Oral commensal bacterial are thus likely transmitted through routine physical contact or shared environment. Their genetic relatedness can be used to represent a combination of social contact and shared physical space, therefore reconstructing networks of contact. This study provides the first step in developing a method to measure direct social contact based on commensal organism genotyping, potentially capable of unmasking hidden social networks that contribute to

  12. The genetic basis of individual differences in reward processing and the link to addictive behavior and social cognition.

    PubMed

    Yacubian, J; Büchel, C

    2009-11-24

    Dopaminergic neurotransmission is widely recognized to be critical to the neurobiology of reward, motivation and addiction. Interestingly, social interactions and related behavior also activate the same neuronal system. Consequently, genetic variations of dopamine neurotransmission are thought influence reward processing that in turn may affect distinctive social behavior and susceptibility to addiction. This review focuses on advances made to date in an effort to link genetic individual variations and reward processing as a possible basis for addictive behaviors.

  13. [Links and effects of globalization on social and economic organization and malaria prevalence in the Coastal Region of Livingston, Guatemala].

    PubMed

    Nelson, Caro Méndez

    2007-01-01

    As a result of Guatemala's growing involvement in international markets and policies favoring industrial and export-oriented efforts, the population has experienced substantial changes in its economic and social organization, with consequences for the health and well-being of marginal groups. The article discusses various links between global processes, national policies and priorities, social and economic strategies, and malaria prevalence, with the Coastal Region of Livingston, Guatemala as the case study carried out between 2001 and 2003.

  14. Interactions of adolescent social experiences and dopamine genes to predict physical intimate partner violence perpetration

    PubMed Central

    Parker, Edith A.; Peek-Asa, Corinne

    2017-01-01

    Objectives We examined the interactions between three dopamine gene alleles (DAT1, DRD2, DRD4) previously associated with violent behavior and two components of the adolescent environment (exposure to violence, school social environment) to predict adulthood physical intimate partner violence (IPV) perpetration among white men and women. Methods We used data from Wave IV of the National Longitudinal Study of Adolescent to Adult Health, a cohort study following individuals from adolescence to adulthood. Based on the prior literature, we categorized participants as at risk for each of the three dopamine genes using this coding scheme: two 10-R alleles for DAT1; at least one A-1 allele for DRD2; at least one 7-R or 8-R allele for DRD4. Adolescent exposure to violence and school social environment was measured in 1994 and 1995 when participants were in high school or middle school. Intimate partner violence perpetration was measured in 2008 when participants were 24 to 32 years old. We used simple and multivariable logistic regression models, including interactions of genes and the adolescent environments for the analysis. Results Presence of risk alleles was not independently associated with IPV perpetration but increasing exposure to violence and disconnection from the school social environment was associated with physical IPV perpetration. The effects of these adolescent experiences on physical IPV perpetration varied by dopamine risk allele status. Among individuals with non-risk dopamine alleles, increased exposure to violence during adolescence and perception of disconnection from the school environment were significantly associated with increased odds of physical IPV perpetration, but individuals with high risk alleles, overall, did not experience the same increase. Conclusion Our results suggested the effects of adolescent environment on adulthood physical IPV perpetration varied by genetic factors. This analysis did not find a direct link between risk alleles

  15. Predicting Adolescents' Bullying Participation from Developmental Trajectories of Social Status and Behavior.

    PubMed

    Pouwels, J Loes; Salmivalli, Christina; Saarento, Silja; van den Berg, Yvonne H M; Lansu, Tessa A M; Cillessen, Antonius H N

    2017-03-28

    The aim of this study was to determine how trajectory clusters of social status (social preference and perceived popularity) and behavior (direct aggression and prosocial behavior) from age 9 to age 14 predicted adolescents' bullying participant roles at age 16 and 17 (n = 266). Clusters were identified with multivariate growth mixture modeling (GMM). The findings showed that participants' developmental trajectories of social status and social behavior across childhood and early adolescence predicted their bullying participant role involvement in adolescence. Practical implications and suggestions for further research are discussed.

  16. Predicting symptoms of depression from social anhedonia and emotion regulation.

    PubMed

    Atherton, Brennan D; Nevels, Robert M; Moore, Michael T

    2015-03-01

    The literature examining social anhedonia, emotion regulation, and symptoms of depression in psychiatric inpatients has been limited. However, some studies have shown that difficulties in emotion regulation and social anhedonia were independently associated with depression. The current study attempted to examine the effects of these two potential predictors of unipolar depressed mood. Fifty-nine (73% female) psychiatric inpatients were given the measures of emotion regulation, symptoms of anxiety and depression, and social anhedonia. Results showed that difficulties in emotion regulation, specifically dysfunctional emotion regulation strategies and emotional clarity, served as significant predictors of depressive symptoms above and beyond contributions from social anhedonia. These results highlight the importance of attending to emotion regulation in the study and treatment of depression in inpatient samples.

  17. Unsupervised Group Discovery and LInk Prediction in Relational Datasets: a nonparametric Bayesian approach

    SciTech Connect

    Koutsourelakis, P

    2007-05-03

    Clustering represents one of the most common statistical procedures and a standard tool for pattern discovery and dimension reduction. Most often the objects to be clustered are described by a set of measurements or observables e.g. the coordinates of the vectors, the attributes of people. In a lot of cases however the available observations appear in the form of links or connections (e.g. communication or transaction networks). This data contains valuable information that can in general be exploited in order to discover groups and better understand the structure of the dataset. Since in most real-world datasets, several of these links are missing, it is also useful to develop procedures that can predict those unobserved connections. In this report we address the problem of unsupervised group discovery in relational datasets. A fundamental issue in all clustering problems is that the actual number of clusters is unknown a priori. In most cases this is addressed by running the model several times assuming a different number of clusters each time and selecting the value that provides the best fit based on some criterion (ie Bayes factor in the case of Bayesian techniques). It is easily understood that it would be preferable to develop techniques that are able to number of clusters is essentially learned from that data along with the rest of model parameters. For that purpose, we adopt a nonparametric Bayesian framework which provides a very flexible modeling environment in which the size of the model i.e. the number of clusters, can adapt to the available data and readily accommodate outliers. The latter is particularly important since several groups of interest might consist of a small number of members and would most likely be smeared out by traditional modeling techniques. Finally, the proposed framework combines all the advantages of standard Bayesian techniques such as integration of prior knowledge in a principled manner, seamless accommodation of missing data

  18. Social insect genomes exhibit dramatic evolution in gene composition and regulation while preserving regulatory features linked to sociality

    PubMed Central

    Simola, Daniel F.; Wissler, Lothar; Donahue, Greg; Waterhouse, Robert M.; Helmkampf, Martin; Roux, Julien; Nygaard, Sanne; Glastad, Karl M.; Hagen, Darren E.; Viljakainen, Lumi; Reese, Justin T.; Hunt, Brendan G.; Graur, Dan; Elhaik, Eran; Kriventseva, Evgenia V.; Wen, Jiayu; Parker, Brian J.; Cash, Elizabeth; Privman, Eyal; Childers, Christopher P.; Muñoz-Torres, Monica C.; Boomsma, Jacobus J.; Bornberg-Bauer, Erich; Currie, Cameron R.; Elsik, Christine G.; Suen, Garret; Goodisman, Michael A.D.; Keller, Laurent; Liebig, Jürgen; Rawls, Alan; Reinberg, Danny; Smith, Chris D.; Smith, Chris R.; Tsutsui, Neil; Wurm, Yannick; Zdobnov, Evgeny M.; Berger, Shelley L.; Gadau, Jürgen

    2013-01-01

    Genomes of eusocial insects code for dramatic examples of phenotypic plasticity and social organization. We compared the genomes of seven ants, the honeybee, and various solitary insects to examine whether eusocial lineages share distinct features of genomic organization. Each ant lineage contains ∼4000 novel genes, but only 64 of these genes are conserved among all seven ants. Many gene families have been expanded in ants, notably those involved in chemical communication (e.g., desaturases and odorant receptors). Alignment of the ant genomes revealed reduced purifying selection compared with Drosophila without significantly reduced synteny. Correspondingly, ant genomes exhibit dramatic divergence of noncoding regulatory elements; however, extant conserved regions are enriched for novel noncoding RNAs and transcription factor–binding sites. Comparison of orthologous gene promoters between eusocial and solitary species revealed significant regulatory evolution in both cis (e.g., Creb) and trans (e.g., fork head) for nearly 2000 genes, many of which exhibit phenotypic plasticity. Our results emphasize that genomic changes can occur remarkably fast in ants, because two recently diverged leaf-cutter ant species exhibit faster accumulation of species-specific genes and greater divergence in regulatory elements compared with other ants or Drosophila. Thus, while the “socio-genomes” of ants and the honeybee are broadly characterized by a pervasive pattern of divergence in gene composition and regulation, they preserve lineage-specific regulatory features linked to eusociality. We propose that changes in gene regulation played a key role in the origins of insect eusociality, whereas changes in gene composition were more relevant for lineage-specific eusocial adaptations. PMID:23636946

  19. Social insect genomes exhibit dramatic evolution in gene composition and regulation while preserving regulatory features linked to sociality.

    PubMed

    Simola, Daniel F; Wissler, Lothar; Donahue, Greg; Waterhouse, Robert M; Helmkampf, Martin; Roux, Julien; Nygaard, Sanne; Glastad, Karl M; Hagen, Darren E; Viljakainen, Lumi; Reese, Justin T; Hunt, Brendan G; Graur, Dan; Elhaik, Eran; Kriventseva, Evgenia V; Wen, Jiayu; Parker, Brian J; Cash, Elizabeth; Privman, Eyal; Childers, Christopher P; Muñoz-Torres, Monica C; Boomsma, Jacobus J; Bornberg-Bauer, Erich; Currie, Cameron R; Elsik, Christine G; Suen, Garret; Goodisman, Michael A D; Keller, Laurent; Liebig, Jürgen; Rawls, Alan; Reinberg, Danny; Smith, Chris D; Smith, Chris R; Tsutsui, Neil; Wurm, Yannick; Zdobnov, Evgeny M; Berger, Shelley L; Gadau, Jürgen

    2013-08-01

    Genomes of eusocial insects code for dramatic examples of phenotypic plasticity and social organization. We compared the genomes of seven ants, the honeybee, and various solitary insects to examine whether eusocial lineages share distinct features of genomic organization. Each ant lineage contains ∼4000 novel genes, but only 64 of these genes are conserved among all seven ants. Many gene families have been expanded in ants, notably those involved in chemical communication (e.g., desaturases and odorant receptors). Alignment of the ant genomes revealed reduced purifying selection compared with Drosophila without significantly reduced synteny. Correspondingly, ant genomes exhibit dramatic divergence of noncoding regulatory elements; however, extant conserved regions are enriched for novel noncoding RNAs and transcription factor-binding sites. Comparison of orthologous gene promoters between eusocial and solitary species revealed significant regulatory evolution in both cis (e.g., Creb) and trans (e.g., fork head) for nearly 2000 genes, many of which exhibit phenotypic plasticity. Our results emphasize that genomic changes can occur remarkably fast in ants, because two recently diverged leaf-cutter ant species exhibit faster accumulation of species-specific genes and greater divergence in regulatory elements compared with other ants or Drosophila. Thus, while the "socio-genomes" of ants and the honeybee are broadly characterized by a pervasive pattern of divergence in gene composition and regulation, they preserve lineage-specific regulatory features linked to eusociality. We propose that changes in gene regulation played a key role in the origins of insect eusociality, whereas changes in gene composition were more relevant for lineage-specific eusocial adaptations.

  20. Predicting post-event processing in social anxiety disorder following two prototypical social situations: state variables and dispositional determinants.

    PubMed

    Kiko, Sonja; Stevens, Stephan; Mall, Anna Katharina; Steil, Regina; Bohus, Martin; Hermann, Christiane

    2012-10-01

    This study investigated self-reported state (anxiety, physical symptoms, cognitions, internally focused attention, safety behaviors, social performance) and trait (social anxiety, depressive symptoms, dysfunctional self-consciousness) predictors of post-event processing (PEP) subsequent to two social situations (interaction, speech) in participants with a primary diagnosis of social anxiety disorder (SAD) and healthy controls (HC). The speech triggered significantly more intense PEP, especially in SAD. Regardless of the type of social situation, PEP was best predicted by situational anxiety and dysfunctional cognitions among the state variables. If only trait variables were considered, PEP following both situations was accounted for by trait social anxiety. In addition, dysfunctional self-consciousness contributed to PEP-speech. If state and trait variables were jointly considered, for both situations, situational anxiety and dysfunctional cognitions were confirmed as the most powerful PEP predictors above and beyond trait social anxiety (interaction) and dysfunctional self-consciousness (speech). Hence, PEP as assessed on the day after a social situation seems to be mainly determined by state variables. Trait social anxiety and dysfunctional self-consciousness also significantly contribute to PEP depending on the type of social situation. The present findings support dysfunctional cognitions as a core cognitive mechanism for the maintenance of SAD. Implications for treatment are discussed.

  1. Linking social change and developmental change: shifting pathways of human development.

    PubMed

    Greenfield, Patricia M

    2009-03-01

    P. M. Greenfield's new theory of social change and human development aims to show how changing sociodemographic ecologies alter cultural values and learning environments and thereby shift developmental pathways. Worldwide sociodemographic trends include movement from rural residence, informal education at home, subsistence economy, and low-technology environments to urban residence, formal schooling, commerce, and high-technology environments. The former ecology is summarized by the German term Gemeinschaft ("community") and the latter by the German term Gesellschaft ("society"; Tönnies, 1887/1957). A review of empirical research demonstrates that, through adaptive processes, movement of any ecological variable in a Gesellschaft direction shifts cultural values in an individualistic direction and developmental pathways toward more independent social behavior and more abstract cognition--to give a few examples of the myriad behaviors that respond to these sociodemographic changes. In contrast, the (much less frequent) movement of any ecological variable in a Gemeinschaft direction is predicted to move cultural values and developmental pathways in the opposite direction. In conclusion, sociocultural environments are not static either in the developed or the developing world and therefore must be treated dynamically in developmental research.

  2. Brain hyper-connectivity in children with autism and its links to social deficits

    PubMed Central

    Supekar, Kaustubh; Uddin, Lucina Q.; Khouzam, Amirah; Phillips, Jennifer; Gaillard, William D.; Kenworthy, Lauren E.; Yerys, Benjamin E.; Vaidya, Chandan J.; Menon, Vinod

    2013-01-01

    Summary Autism spectrum disorder (ASD), a neurodevelopmental disorder affecting nearly 1 in 88 children, is thought to result from aberrant brain connectivity. Remarkably, there have been no systematic attempts to characterize whole-brain connectivity in children with ASD. Here, we use neuroimaging to show there are more instances of greater functional connectivity in the brains of children with ASD compared with typically developing children. Hyper-connectivity in ASD was observed at the whole-brain and subsystems level, across long- and short-range connections, and was associated with higher levels of fluctuations in regional brain signals. Brain hyper-connectivity predicted symptom severity in ASD such that children with greater functional connectivity exhibited more severe social deficits. We replicated these findings in two additional independent cohorts, demonstrating again that at earlier ages, the brain in ASD is largely functionally hyper-connected in ways that contribute to social dysfunction. Our findings provide novel insights into brain mechanisms underlying childhood autism. PMID:24210821

  3. What can animal research tell us about the link between androgens and social competition in humans?

    PubMed

    Fuxjager, Matthew J; Trainor, Brian C; Marler, Catherine A

    2016-12-01

    The relationship between androgenic hormones, like testosterone (T), and aggression is extensively studied in human populations. Yet, while this work has illuminated a variety of principals regarding the behavioral and phenotypic effects of T, it is also hindered by inherent limitations of performing research on people. In these instances, animal research can be used to gain further insight into the complex mechanisms by which T influences aggression. Here, we explore recent studies on T and aggression in numerous vertebrate species, although we focus primarily on males and on a New World rodent called the California mouse (Peromyscus californicus). This species is highly territorial and monogamous, resembling the modern human social disposition. We review (i) how baseline and dynamic T levels predict and/or impact aggressive behavior and disposition; (ii) how factors related to social and physical context influence T and aggression; (iii) the reinforcing or "rewarding" aspects of aggressive behavior; and (iv) the function of T on aggression before and during a combative encounter. Included are areas that may need further research. We argue that animal studies investigating these topics fill in gaps to help paint a more complete picture of how androgenic steroids drive the output of aggressive behavior in all animals, including humans.

  4. Day-care treatment for multiple drug abusing adolescents: social factors linked with completing treatment.

    PubMed

    Feigelman, W

    1987-01-01

    By identifying some of the social correlates linked with completing day-care drug abuse treatment, the present study has sought to broaden understanding of how drug rehabilitations are effected. As the findings have demonstrated, completing care is a result of a complex array of causes and their interaction. The disposition of the entering patient (i.e., their determination and other strengths) has a great bearing on treatment outcome. It is also a result of the patient's family, their motivations, resources and perseverance in enduring a long course of demanding therapeutic interventions. In addition, it is the product of meanings shared and transmitted between the patient's family and the treatment staff. Patients and their families project positive attitudes about the value of the therapeutic enterprise as well as a compliant demeanor. As staff recognize that patients and parents are acting cooperatively, then such perceptions tend to create self-fulfilling prophecies. The data has established that older adolescent patients are more likely to possess the motivational resources needed for program completion than younger patients. Apparently, self-referred patients are also more inclined to meet the demands of program requirements than those referred by the courts or other outside social agencies, although the differences fell short of the .05 level of statistical significance. Those completing the program are less likely to be diagnosed as depressed at intake. Parental characteristics comprise another group of variables that are related to treatment completion. Parents of higher occupational rank, who have had mental health care for themselves, and who are of Jewish ethnicity appear to possess useful strengths for meeting program challenges. The pattern of spouse mutuality in dealing with a child's needs as it exists preceding and during treatment seems to be another useful asset for successfully getting through this form of treatment. While parents with the

  5. Individual personalities predict social behaviour in wild networks of great tits (Parus major).

    PubMed

    Aplin, L M; Farine, D R; Morand-Ferron, J; Cole, E F; Cockburn, A; Sheldon, B C

    2013-11-01

    Social environments have an important effect on a range of ecological processes, and form a crucial component of selection. However, little is known of the link between personality, social behaviour and population structure. We combine a well-understood personality trait with large-scale social networks in wild songbirds, and show that personality underpins multiple aspects of social organisation. First, we demonstrate a relationship between network centrality and personality with 'proactive' (fast-exploring) individuals associating weakly with greater numbers of conspecifics and moving between flocks. Second, temporal stability of associations relates to personality: 'reactive' (slow-exploring) birds form synergistically stable relationships. Finally, we show that personality influences social structure, with males non-randomly distributed across groups. These results provide strong evidence that songbirds follow alternative social strategies related to personality. This has implications not only for the causes of social network structure but also for the strength and direction of selection on personality in natural populations.

  6. Do perceived social stress and resilience influence the effects of psychopathy-linked narcissism and CU traits on adolescent aggression?

    PubMed

    Kauten, Rebecca; Barry, Christopher T; Leachman, Lacey

    2013-01-01

    The current study explored the influences of social stress and resilience on the relation between psychopathy-linked personality characteristics (i.e., narcissism, dimensions of CU traits) and aggression with the expectation that social stress would exacerbate the relation, whereas resilience would mitigate it. In a sample of 154 at-risk adolescents (ages 16-18; 84% male), contrary to expectations, high social stress attenuated the relations of narcissism and callousness with aggression. Self-reported resilience attenuated the relation between callousness and aggression. The implications for understanding the role that these moderators might play in the association between adolescent psychopathic tendencies, particularly callousness, and aggression are discussed.

  7. The role of attachment dimensions and perceived social support in predicting adjustment to cancer.

    PubMed

    Cicero, Viviana; Lo Coco, Gianluca; Gullo, Salvatore; Lo Verso, Girolamo

    2009-10-01

    Several studies carried out over the last years show that patients' adjustment is very important to the past experiences of people with cancer. In our study of 96 subjects with cancer, we examined whether patient's working model of attachment anxiety/avoidance and perceptions of social support predicts adjustment to cancer. All participants filled in a demographic questionnaire, the Relationship Scale Questionnaire (RSQ), the Multidimensional Scale of Perceived Social Support (MSPSS), and the Mental Adjustment to Cancer (MAC). Anxious attachment predicted psychological adjustment: patients with high levels of anxious attachment showed high levels of helplessness/hopelessness and anxious preoccupation (p<0.01, and p<0.05, respectively). With regard to the function of perceived social support, the patient's perception of social support from friends was predictive of both fighting spirit and stoic acceptance (p=0.01, and p<0.001, respectively). Conversely, the patient's perception of support from family members was not predictive of adjustment to cancer. Patients in the advanced stages of the illness showed higher levels of helplessness/hopelessness (p<0.05). Anxious attachment and perceived social support predicted different domains of psychological adjustment to cancer. Perceived support from friends may predict the patient's tendency to consider cancer as a challenge and to take an active role in therapy and recovery, whereas social support from family was not predictive of various states of adjustment to cancer.

  8. Emotional engagements predict and enhance social cognition in young chimpanzees

    PubMed Central

    Bard, Kim A; Bakeman, Roger; Boysen, Sarah T; Leavens, David A

    2014-01-01

    Social cognition in infancy is evident in coordinated triadic engagements, that is, infants attending jointly with social partners and objects. Current evolutionary theories of primate social cognition tend to highlight species differences in cognition based on human-unique cooperative motives. We consider a developmental model in which engagement experiences produce differential outcomes. We conducted a 10-year-long study in which two groups of laboratory-raised chimpanzee infants were given quantifiably different engagement experiences. Joint attention, cooperativeness, affect, and different levels of cognition were measured in 5- to 12-month-old chimpanzees, and compared to outcomes derived from a normative human database. We found that joint attention skills significantly improved across development for all infants, but by 12 months, the humans significantly surpassed the chimpanzees. We found that cooperativeness was stable in the humans, but by 12 months, the chimpanzee group given enriched engagement experiences significantly surpassed the humans. Past engagement experiences and concurrent affect were significant unique predictors of both joint attention and cooperativeness in 5- to 12-month-old chimpanzees. When engagement experiences and concurrent affect were statistically controlled, joint attention and cooperation were not associated. We explain differential social cognition outcomes in terms of the significant influences of previous engagement experiences and affect, in addition to cognition. Our study highlights developmental processes that underpin the emergence of social cognition in support of evolutionary continuity. PMID:24410843

  9. Linking Contextual Affordances: Examining Racial-Ethnic Socialization and Parental Career Support among African American College Students

    ERIC Educational Resources Information Center

    Blackmon, Sha'Kema M.; Thomas, Anita Jones

    2014-01-01

    This exploratory investigation examined the link between self-reported racial-ethnic socialization experiences and perceived parental career support among African American undergraduate and graduate students. The results of two separate multivariate multiple regression analyses found that messages about coping with racism positively predicted…

  10. Personal Values as Mitigating Factors in the Link between Income and Life Satisfaction: Evidence from the European Social Survey

    ERIC Educational Resources Information Center

    Georgellis, Yannis; Tsitsianis, Nicholas; Yin, Ya Ping

    2009-01-01

    Using data from the first two rounds of the European Social Survey, we examine the link between income, reference income and life satisfaction across Western Europe. We find that whilst there is a strong positive relationship between income and life satisfaction, reference or comparison income exerts a strong negative influence. Interestingly, our…

  11. Linking Contextual Affordances: Examining Racial-Ethnic Socialization and Parental Career Support among African American College Students

    ERIC Educational Resources Information Center

    Blackmon, Sha'Kema M.; Thomas, Anita Jones

    2014-01-01

    This exploratory investigation examined the link between self-reported racial-ethnic socialization experiences and perceived parental career support among African American undergraduate and graduate students. The results of two separate multivariate multiple regression analyses found that messages about coping with racism positively predicted…

  12. Linking Affective Commitment, Career Self-Efficacy, and Outcome Expectations: A Test of Social Cognitive Career Theory

    ERIC Educational Resources Information Center

    Conklin, Amanda M.; Dahling, Jason J.; Garcia, Pablo A.

    2013-01-01

    The authors tested a model based on the satisfaction model of social cognitive career theory (SCCT) that links college students' affective commitment to their major (the emotional identification that students feel toward their area of study) with career decision self-efficacy (CDSE) and career outcome expectations. Results indicate that CDSE…

  13. Personal Values as Mitigating Factors in the Link between Income and Life Satisfaction: Evidence from the European Social Survey

    ERIC Educational Resources Information Center

    Georgellis, Yannis; Tsitsianis, Nicholas; Yin, Ya Ping

    2009-01-01

    Using data from the first two rounds of the European Social Survey, we examine the link between income, reference income and life satisfaction across Western Europe. We find that whilst there is a strong positive relationship between income and life satisfaction, reference or comparison income exerts a strong negative influence. Interestingly, our…

  14. Links between Parent-Teacher Relationships and Kindergartners' Social Skills: Do Child Ethnicity and Family Income Matter?

    ERIC Educational Resources Information Center

    Iruka, Iheoma U.; Winn, Donna-Marie C.; Kingsley, Susan J.; Orthodoxou, Yannick J.

    2011-01-01

    This study uses National Center for Early Development and Learning (NCEDL) data to examine the moderating effects of child ethnicity and family income on the links between parent-teacher relationships and kindergartners' social skills. This study includes 481 Caucasian, African American, and Latino children from low-income households. Overall,…

  15. Linking Affective Commitment, Career Self-Efficacy, and Outcome Expectations: A Test of Social Cognitive Career Theory

    ERIC Educational Resources Information Center

    Conklin, Amanda M.; Dahling, Jason J.; Garcia, Pablo A.

    2013-01-01

    The authors tested a model based on the satisfaction model of social cognitive career theory (SCCT) that links college students' affective commitment to their major (the emotional identification that students feel toward their area of study) with career decision self-efficacy (CDSE) and career outcome expectations. Results indicate that CDSE…

  16. Necessary, but not sufficient: links between neurocognition, social cognition, and metacognition in schizophrenia are moderated by disorganized symptoms.

    PubMed

    Minor, Kyle S; Lysaker, Paul H

    2014-10-01

    Intact neurocognition has been posited as a necessary, but not sufficient prerequisite for efficient social cognition and metacognition in schizophrenia. Disorganized symptoms likely play a prominent role in these cognitive processes, given the detrimental effects of disorganization on one's ability to synthesize discrete information into an organized whole. However, the relationship between disorganized symptoms and cognitive processes remains unclear. In this study, we examined whether disorganized symptoms: 1) exhibited stronger inverse relationships with cognitive processes than other symptoms, and 2) moderated links between neurocognition and a) social cognition, and b) metacognition. Trained raters assessed psychotic symptoms, neurocognition, social cognition, and metacognition in patients with schizophrenia from a Midwestern VA Medical Center (n=68) using validated, clinician-rated instruments. We observed significantly greater inverse associations with cognitive processes for disorganized compared to reality distortion symptoms; inverse associations with neurocognition and social cognition were significantly greater for disorganized than negative symptoms. Our hypotheses that disorganized symptoms would moderate relationships between neurocognition and a) social cognition, and b) metacognition were also supported. These findings highlight the importance of disorganized symptoms in elucidating links between neurocognition and social cognitive and metacognitive abilities. Future work should assess whether similar findings occur across the schizophrenia-spectrum, and investigate if targeting disorganization can ameliorate social cognitive and metacognitive impairments in schizophrenia. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. Framework for Smart Electronic Health Record-Linked Predictive Models to Optimize Care for Complex Digestive Diseases

    DTIC Science & Technology

    2013-06-01

    AD_________________ Award Number: W81XWH-11-2-0133 TITLE: Framework for Smart Electronic Health...NUMBER Framework for Smart Electronic Health Record-Linked Predictive Models to Optimize Care for Complex Digestive Diseases 5b. GRANT NUMBER...an intelligent workspace , by displaying annotation forms and de-identified reports with the same view, automatic report queuing and providing easy

  18. Brief report: difficulty in understanding social acting (but not false beliefs) mediates the link between autistic traits and ingroup relationships.

    PubMed

    Yang, Daniel Y-J; Baillargeon, Renée

    2013-09-01

    Why do individuals with more autistic traits experience social difficulties? Here we examined the hypothesis that these difficulties stem in part from a challenge in understanding social acting, the prosocial pretense that adults routinely produce to maintain positive relationships with their ingroup. In Study 1, we developed a self-administered test of social-acting understanding: participants read stories in which a character engaged in social acting and rated the appropriateness of the character's response. Adults who scored 26 or higher on the Autism Spectrum Quotient (AQ) questionnaire gave significantly lower ratings than comparison participants (AQ < 26). Study 2 found that difficulty in understanding social acting, but not false beliefs, mediated the link between autistic traits and perceived ingroup relationships.

  19. An interpersonal circumplex model of children's social goals: links with peer-reported behavior and sociometric status.

    PubMed

    Ojanen, Tiina; Grönroos, Matti; Salmivalli, Christina

    2005-09-01

    The objective of the present research was to develop an assessment model for children's social goals. The aims were (a) to fit children's social goals to a circumplex model and to examine links between goals and peer-reported social behaviors (aggression, withdrawal, and prosocial behavior) in a sample of 276 participants (134 girls, 11- to 12-year-olds) and (b) to replicate these findings and examine whether social behavior mediates the relationship between goals and sociometric status in an independent cross-validation sample of 310 participants (143 girls, 11- to 13-year-olds). Results showed a satisfactory fit to the circumplex model and adequate psychometric properties of the goal scales of the new measure, the Interpersonal Goals Inventory for Children. Other findings included significant and meaningful relations between goals and peer-reported behavior. Social behavior mediated the relations between goals and sociometric status.

  20. Low perceived social support predicts later depression but not social phobia in middle adolescence

    PubMed Central

    Väänänen, Juha-Matti; Marttunen, Mauri; Helminen, Mika; Kaltiala-Heino, Riittakerttu

    2014-01-01

    Social phobia and depression are common and highly comorbid disorders in adolescence. There is a lack of studies on possible psychosocial shared risk factors for these disorders. The current study examined if low social support is a shared risk factor for both disorders among adolescent girls and boys. This study is a part of the Adolescent Mental Health Cohort Study's two-year follow-up. We studied cross-sectional and longitudinal associations of perceived social support with social phobia, depression, and comorbid social phobia and depression among girls and boys. The study sample consisted of 2070 15-year-old adolescents at baseline. Depression was measured by the 13-item Beck Depression Inventory, social phobia by the Social Phobia Inventory (SPIN), and perceived social support by the Perceived Social Support Scale-Revised (PSSS-R). Girls reported higher scores on the PSSS-R than boys in total scores and in friend and significant other subscales. Cross-sectional PSSS-R scores were lower among adolescents with social phobia, depression, and comorbid disorder than among those without these disorders. Low PSSS-R total score and significant other subscale were risk factors for depression among both genders, and low support from friends among girls only. Low perceived social support from any source was not a risk factor for social phobia or comorbid social phobia and depression. As conclusion of the study, low perceived social support was a risk factor for depression, but not a shared risk factor for depression and social phobia. Interventions enhancing perceived social support should be an important issue in treatment of depression. PMID:25750832

  1. Linking Big and Small Data Across the Social, Engineering, and Earth Sciences

    NASA Astrophysics Data System (ADS)

    Chen, R. S.; de Sherbinin, A. M.; Levy, M. A.; Downs, R. R.

    2014-12-01

    The challenges of sustainable development cut across the social, health, ecological, engineering, and Earth sciences, across a wide range of spatial and temporal scales, and across the spectrum from basic to applied research and decision making. The rapidly increasing availability of data and information in digital form from a variety of data repositories, networks, and other sources provides new opportunities to link and integrate both traditional data holdings as well as emerging "big data" resources in ways that enable interdisciplinary research and facilitate the use of objective scientific data and information in society. Taking advantage of these opportunities not only requires improved technical and scientific data interoperability across disciplines, scales, and data types, but also concerted efforts to bridge gaps and barriers between key communities, institutions, and networks. Given the long time perspectives required in planning sustainable approaches to development, it is also imperative to address user requirements for long-term data continuity and stewardship by trustworthy repositories. We report here on lessons learned by CIESIN working on a range of sustainable development issues to integrate data across multiple repositories and networks. This includes CIESIN's roles in developing policy-relevant climate and environmental indicators, soil data for African agriculture, and exposure and risk measures for hazards, disease, and conflict, as well as CIESIN's participation in a range of national and international initiatives related both to sustainable development and to open data access, interoperability, and stewardship.

  2. A Chinese cave links climate change, social impacts, and human adaptation over the last 500 years

    PubMed Central

    Tan, Liangcheng; Cai, Yanjun; An, Zhisheng; Cheng, Hai; Shen, Chuan-Chou; Breitenbach, Sebastian F. M.; Gao, Yongli; Edwards, R. Lawrence; Zhang, Haiwei; Du, Yajuan

    2015-01-01

    The collapse of some pre-historical and historical cultures, including Chinese dynasties were presumably linked to widespread droughts, on the basis of synchronicities of societal crises and proxy-based climate events. Here, we present a comparison of ancient inscriptions in Dayu Cave from Qinling Mountains, central China, which described accurate times and detailed impacts of seven drought events during the period of 1520–1920 CE, with high-resolution speleothem records from the same cave. The comparable results provide unique and robust tests on relationships among speleothem δ18O changes, drought events, and societal unrest. With direct historical evidences, our results suggest that droughts and even modest events interrupting otherwise wet intervals can cause serious social crises. Modeling results of speleothem δ18O series suggest that future precipitation in central China may be below the average of the past 500 years. As Qinling Mountain is the main recharge area of two large water transfer projects and habitats of many endangered species, it is imperative to explore an adaptive strategy for the decline in precipitation and/or drought events. PMID:26270656

  3. First empirical evaluation of the link between attachment, social cognition and borderline features in adolescents.

    PubMed

    Sharp, Carla; Venta, Amanda; Vanwoerden, Salome; Schramm, Andrew; Ha, Carolyn; Newlin, Elizabeth; Reddy, Radhika; Fonagy, Peter

    2016-01-01

    Several developmental models of borderline personality disorder (BPD) emphasize the role of disrupted interpersonal relationships or insecure attachment. As yet, attachment quality and the mechanisms by which insecure attachment relates to borderline features in adolescents have not been investigated. In this study, we used a multiple mediational approach to examine the cross-sectional interplay between attachment, social cognition (in particular hypermentalizing), emotion dysregulation, and borderline features in adolescence, controlling for internalizing and externalizing symptoms. The sample included 259 consecutive admissions to an adolescent inpatient unit (Mage=15.42, SD=1.43; 63.1% female). The Child Attachment Interview (CAI) was used to obtain a dimensional index of overall coherence of the attachment narrative. An experimental task was used to assess hypermentalizing, alongside self-report measures of emotion dyregulation and BPD. Our findings suggested that, in a multiple mediation model, hypermentalizing and emotion dysregulation together mediated the relation between attachment coherence and borderline features, but that this effect was driven by hypermentalizing; that is, emotion dysregulation failed to mediate the link between attachment coherence and borderline features while hypermentalizing demonstrated mediational effects. The study provides the first empirical evidence of well-established theoretical approaches to the development of BPD. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. A Chinese cave links climate change, social impacts, and human adaptation over the last 500 years.

    PubMed

    Tan, Liangcheng; Cai, Yanjun; An, Zhisheng; Cheng, Hai; Shen, Chuan-Chou; Breitenbach, Sebastian F M; Gao, Yongli; Edwards, R Lawrence; Zhang, Haiwei; Du, Yajuan

    2015-08-13

    The collapse of some pre-historical and historical cultures, including Chinese dynasties were presumably linked to widespread droughts, on the basis of synchronicities of societal crises and proxy-based climate events. Here, we present a comparison of ancient inscriptions in Dayu Cave from Qinling Mountains, central China, which described accurate times and detailed impacts of seven drought events during the period of 1520-1920 CE, with high-resolution speleothem records from the same cave. The comparable results provide unique and robust tests on relationships among speleothem δ(18)O changes, drought events, and societal unrest. With direct historical evidences, our results suggest that droughts and even modest events interrupting otherwise wet intervals can cause serious social crises. Modeling results of speleothem δ(18)O series suggest that future precipitation in central China may be below the average of the past 500 years. As Qinling Mountain is the main recharge area of two large water transfer projects and habitats of many endangered species, it is imperative to explore an adaptive strategy for the decline in precipitation and/or drought events.

  5. A Chinese cave links climate change, social impacts, and human adaptation over the last 500 years

    NASA Astrophysics Data System (ADS)

    Tan, Liangcheng; Cai, Yanjun; An, Zhisheng; Cheng, Hai; Shen, Chuan-Chou; Breitenbach, Sebastian F. M.; Gao, Yongli; Edwards, R. Lawrence; Zhang, Haiwei; Du, Yajuan

    2015-08-01

    The collapse of some pre-historical and historical cultures, including Chinese dynasties were presumably linked to widespread droughts, on the basis of synchronicities of societal crises and proxy-based climate events. Here, we present a comparison of ancient inscriptions in Dayu Cave from Qinling Mountains, central China, which described accurate times and detailed impacts of seven drought events during the period of 1520-1920 CE, with high-resolution speleothem records from the same cave. The comparable results provide unique and robust tests on relationships among speleothem δ18O changes, drought events, and societal unrest. With direct historical evidences, our results suggest that droughts and even modest events interrupting otherwise wet intervals can cause serious social crises. Modeling results of speleothem δ18O series suggest that future precipitation in central China may be below the average of the past 500 years. As Qinling Mountain is the main recharge area of two large water transfer projects and habitats of many endangered species, it is imperative to explore an adaptive strategy for the decline in precipitation and/or drought events.

  6. Social embeddedness as a mechanism for linking social cohesion to well-being among older adults: moderating effect of gender

    PubMed Central

    Momtaz, Yadollah Abolfathi; Haron, Sharifah Azizah; Ibrahim, Rahimah; Hamid, Tengku Aizan

    2014-01-01

    Background The positive effect of social cohesion on well-being in older adults has been well documented. However, relatively few studies have attempted to understand the mechanisms by which social cohesion influences well-being. The main aim of the current study is to identify social pathways in which social cohesion may contribute to well-being. Methods The data for this study (taken from 1,880 older adults, aged 60 years and older) were drawn from a national survey conducted during 2008–2009. The survey employed a two-stage stratified sampling process for data collection. Structural equation modeling was used to test mediating and moderating analyses. Results The proposed model documented a good fit to the data (GFI =98; CFI =0.99; RMSEA =0.04). The findings from bootstrap analysis and the Sobel test revealed that the impact of social cohesion on well-being is significantly mediated by social embeddedness (Z=5.62; P<0.001). Finally, the results of a multigroup analysis test showed that social cohesion influences well-being through the social embeddedness mechanism somewhat differently for older men than women. Conclusion The findings of this study, in addition to supporting the importance of neighborhood social cohesion for the well-being of older adults, also provide evidence that the impact of social cohesion towards well-being is mediated through the mechanism of social embeddedness. PMID:24904206

  7. Social embeddedness as a mechanism for linking social cohesion to well-being among older adults: moderating effect of gender.

    PubMed

    Momtaz, Yadollah Abolfathi; Haron, Sharifah Azizah; Ibrahim, Rahimah; Hamid, Tengku Aizan

    2014-01-01

    The positive effect of social cohesion on well-being in older adults has been well documented. However, relatively few studies have attempted to understand the mechanisms by which social cohesion influences well-being. The main aim of the current study is to identify social pathways in which social cohesion may contribute to well-being. The data for this study (taken from 1,880 older adults, aged 60 years and older) were drawn from a national survey conducted during 2008-2009. The survey employed a two-stage stratified sampling process for data collection. Structural equation modeling was used to test mediating and moderating analyses. The proposed model documented a good fit to the data (GFI =98; CFI =0.99; RMSEA =0.04). The findings from bootstrap analysis and the Sobel test revealed that the impact of social cohesion on well-being is significantly mediated by social embeddedness (Z=5.62; P<0.001). Finally, the results of a multigroup analysis test showed that social cohesion influences well-being through the social embeddedness mechanism somewhat differently for older men than women. The findings of this study, in addition to supporting the importance of neighborhood social cohesion for the well-being of older adults, also provide evidence that the impact of social cohesion towards well-being is mediated through the mechanism of social embeddedness.

  8. The predictive nature of individual differences in early associative learning and emerging social behavior.

    PubMed

    Reeb-Sutherland, Bethany C; Levitt, Pat; Fox, Nathan A

    2012-01-01

    Across the first year of life, infants achieve remarkable success in their ability to interact in the social world. The hierarchical nature of circuit and skill development predicts that the emergence of social behaviors may depend upon an infant's early abilities to detect contingencies, particularly socially-relevant associations. Here, we examined whether individual differences in the rate of associative learning at one month of age is an enduring predictor of social, imitative, and discriminative behaviors measured across the human infant's first year. One-month learning rate was predictive of social behaviors at 5, 9, and 12 months of age as well as face-evoked discriminative neural activity at 9 months of age. Learning was not related to general cognitive abilities. These results underscore the importance of early contingency learning and suggest the presence of a basic mechanism underlying the ontogeny of social behaviors.

  9. Neighborhood linking social capital as a predictor of psychiatric medication prescription in the elderly: a Swedish national cohort study

    PubMed Central

    Sundquist, Jan; Hamano, Tsuyoshi; Li, Xinjun; Kawakami, Naomi; Shiwaku, Kuninori; Sundquist, Kristina

    2014-01-01

    Objectives Little is known about the association between neighborhood linking social capital and psychiatric medication in the elderly. The present study analyzes whether there is an association between linking social capital (a theoretical concept describing the amount of trust between individuals and societal institutions) and prescription of antipsychotics, anxiolytics, hypnotics/sedatives, antidepressants, or anti-dementia drugs. Design, Setting, Participants and Measurements The entire Swedish population aged 65+, a total of 1,292,816 individuals, were followed from 1 July 2005 until first prescription of psychiatric medication, death, emigration, or the end of the study on 31 December 2010. Small geographic units were used to define neighborhoods. The definition of linking social capital was based on mean voting participation in each neighborhood unit, categorized in three groups. Multilevel logistic regression was used to estimate odds ratios (ORs) and between-neighborhood variance in three different models. Results There was an inverse association between the level of linking social capital and prescription of psychiatric medications (except for anti-dementia drugs). The associations decreased, but remained significant, after accounting for age, sex, family income, marital status, country of birth, and education level (except for antidepressants). The OR for prescription of antipsychotics in the crude model was 1.65 (95% CI 1.53–1.78) and decreased, but remained significant (OR = 1.26; 95% CI 1.17–1.35), after adjustment for the individual-level sociodemographic variables. Conclusions Decision-makers should take into account the potentially negative effect of linking social capital on psychiatric disorders when planning sites of primary care centers and psychiatric clinics, as well as other kinds of community support for elderly patients with such disorders. PMID:24831853

  10. Social Indicators Predicting Postsecondary Success. Publication #2014-21

    ERIC Educational Resources Information Center

    Princiotta, Daniel; Lippman, Laura; Ryberg, Renee; Schmitz, Hannah; Murphey, David; Cooper, Mae

    2014-01-01

    Only about 59 percent of full-time, first-time students at four-year institutions complete such a degree within six years at the same school. Completion rates are even lower for those starting part-time, or at less than four-year schools (and planning to transfer). Which social indicators--such as student engagement, enrollment status, and family…

  11. Does human presynaptic striatal dopamine function predict social conformity?

    PubMed

    Stokes, Paul R A; Benecke, Aaf; Puraite, Julita; Bloomfield, Michael A P; Shotbolt, Paul; Reeves, Suzanne J; Lingford-Hughes, Anne R; Howes, Oliver; Egerton, Alice

    2014-03-01

    Socially desirable responding (SDR) is a personality trait which reflects either a tendency to present oneself in an overly positive manner to others, consistent with social conformity (impression management (IM)), or the tendency to view one's own behaviour in an overly positive light (self-deceptive enhancement (SDE)). Neurochemical imaging studies report an inverse relationship between SDR and dorsal striatal dopamine D₂/₃ receptor availability. This may reflect an association between SDR and D₂/₃ receptor expression, synaptic dopamine levels or a combination of the two. In this study, we used a [¹⁸F]-DOPA positron emission tomography (PET) image database to investigate whether SDR is associated with presynaptic dopamine function. Striatal [¹⁸F]-DOPA uptake, (k(i)(cer), min⁻¹), was determined in two independent healthy participant cohorts (n=27 and 19), by Patlak analysis using a cerebellar reference region. SDR was assessed using the revised Eysenck Personality Questionnaire (EPQ-R) Lie scale, and IM and SDE were measured using the Paulhus Deception Scales. No significant associations were detected between Lie, SDE or IM scores and striatal [¹⁸F]-DOPA k(i)(cer). These results indicate that presynaptic striatal dopamine function is not associated with social conformity and suggests that social conformity may be associated with striatal D₂/₃ receptor expression rather than with synaptic dopamine levels.

  12. Social Indicators Predicting Postsecondary Success. Publication #2014-21

    ERIC Educational Resources Information Center

    Princiotta, Daniel; Lippman, Laura; Ryberg, Renee; Schmitz, Hannah; Murphey, David; Cooper, Mae

    2014-01-01

    Only about 59 percent of full-time, first-time students at four-year institutions complete such a degree within six years at the same school. Completion rates are even lower for those starting part-time, or at less than four-year schools (and planning to transfer). Which social indicators--such as student engagement, enrollment status, and family…

  13. Social Interest, Stress, and the Prediction of Health Status.

    ERIC Educational Resources Information Center

    Zarski, John J.; And Others

    1986-01-01

    The stress and illness paradigm is expanded by empirically testing social interest as a personality variable influencing somatic health. Examines stress using an instrument that measures daily hassles. Compares the usefulness of this measure to the life experiences methodology. Findings related to these variables are not consistent with previous…

  14. Social Structure Predicts Genital Morphology in African Mole-Rats

    PubMed Central

    Seney, Marianne L.; Kelly, Diane A.; Goldman, Bruce D.; Šumbera, Radim; Forger, Nancy G.

    2009-01-01

    Background African mole-rats (Bathyergidae, Rodentia) exhibit a wide range of social structures, from solitary to eusocial. We previously found a lack of sex differences in the external genitalia and morphology of the perineal muscles associated with the phallus in the eusocial naked mole-rat. This was quite surprising, as the external genitalia and perineal muscles are sexually dimorphic in all other mammals examined. We hypothesized that the lack of sex differences in naked mole-rats might be related to their unusual social structure. Methodology/Principal Findings We compared the genitalia and perineal muscles in three African mole-rat species: the naked mole-rat, the solitary silvery mole-rat, and the Damaraland mole-rat, a species considered to be eusocial, but with less reproductive skew than naked mole-rats. Our findings support a relationship between social structure, mating system, and sexual differentiation. Naked mole-rats lack sex differences in genitalia and perineal morphology, silvery mole-rats exhibit sex differences, and Damaraland mole-rats are intermediate. Conclusions/Significance The lack of sex differences in naked mole-rats is not an attribute of all African mole-rats, but appears to have evolved in relation to their unusual social structure and reproductive biology. PMID:19829697

  15. Perceived support from a caregiver's social ties predicts subsequent care-recipient health.

    PubMed

    Kelley, Dannielle E; Lewis, Megan A; Southwell, Brian G

    2017-12-01

    Most social support research has examined support from an individual patient perspective and does not model the broader social context of support felt by caregivers. Understanding how social support networks may complement healthcare services is critical, considering the aging population, as social support networks may be a valuable resource to offset some of the demands placed on the healthcare system. We sought to identify how caregivers' perceived organizational and interpersonal support from their social support network influences care-recipient health. We created a dyadic dataset of care-recipient and caregivers from the first two rounds of the National Health and Aging Trends survey (2011, 2012) and the first round of the associated National Study of Caregivers survey (2011). Using structural equation modeling, we explored how caregivers' perceived social support is associated with caregiver confidence to provide care, and is associated with care-recipient health outcomes at two time points. All data were analyzed in 2016. Social engagement with members from caregivers' social support networks was positively associated with caregiver confidence, and social engagement and confidence were positively associated with care-recipient health at time 1. Social engagement positively predicted patient health at time 2 controlling for time 1. Conversely, use of organizational support negatively predicted care-recipient health at time 2. Care-recipients experience better health outcomes when caregivers are able to be more engaged with members of their social support network.

  16. How Homes Influence Schools: Early Parenting Predicts African American Children's Classroom Social-Emotional Functioning

    ERIC Educational Resources Information Center

    Baker, Claire E.; Rimm-Kaufman, Sara E.

    2014-01-01

    Data from the Early Childhood Longitudinal Study, Kindergarten Cohort were used to examine the extent to which early parenting predicted African American children's kindergarten social-emotional functioning. Teachers rated children's classroom social-emotional functioning in four areas (i.e., approaches to learning, self-control, interpersonal…

  17. Predicting South Korean University Students' Happiness through Social Support and Efficacy Beliefs

    ERIC Educational Resources Information Center

    Lee, Diane Sookyoung; Padilla, Amado M.

    2016-01-01

    This study investigated the adversity and coping experiences of 198 South Korean university students and takes a cultural lens in understanding how social and individual factors shape their happiness. Hierarchical linear regression analyses suggest that Korean students' perceptions of social support significantly predicted their happiness,…

  18. Right Temporoparietal Gray Matter Predicts Accuracy of Social Perception in the Autism Spectrum

    ERIC Educational Resources Information Center

    David, Nicole; Schultz, Johannes; Milne, Elizabeth; Schunke, Odette; Schöttle, Daniel; Münchau, Alexander; Siegel, Markus; Vogeley, Kai; Engel, Andreas K.

    2014-01-01

    Individuals with an autism spectrum disorder (ASD) show hallmark deficits in social perception. These difficulties might also reflect fundamental deficits in integrating visual signals. We contrasted predictions of a social perception and a spatial-temporal integration deficit account. Participants with ASD and matched controls performed two…

  19. Pathways to School Readiness: Executive Functioning Predicts Academic and Social-Emotional Aspects of School Readiness

    ERIC Educational Resources Information Center

    Mann, Trisha D.; Hund, Alycia M.; Hesson-McInnis, Matthew S.; Roman, Zachary J.

    2017-01-01

    The current study specified the extent to which hot and cool aspects of executive functioning predicted academic and social-emotional indicators of school readiness. It was unique in focusing on positive aspects of social-emotional readiness, rather than problem behaviors. One hundred four 3-5-year-old children completed tasks measuring executive…

  20. Right Temporoparietal Gray Matter Predicts Accuracy of Social Perception in the Autism Spectrum

    ERIC Educational Resources Information Center

    David, Nicole; Schultz, Johannes; Milne, Elizabeth; Schunke, Odette; Schöttle, Daniel; Münchau, Alexander; Siegel, Markus; Vogeley, Kai; Engel, Andreas K.

    2014-01-01

    Individuals with an autism spectrum disorder (ASD) show hallmark deficits in social perception. These difficulties might also reflect fundamental deficits in integrating visual signals. We contrasted predictions of a social perception and a spatial-temporal integration deficit account. Participants with ASD and matched controls performed two…

  1. Prediction of treatment outcome in social phobia: a cross-validation.

    PubMed

    Scholing, A; Emmelkamp, P M

    1999-07-01

    This study was a replication of a study on the prediction of treatment outcome in social phobic patients [Chambless, D. L., Tran, G. Q. Glass, C.R. (1997). Predictors of response to cognitive-behavioral group therapy for social phobia. Journal of Anxiety Disorders, 11 221-240]. Results at the posttest and the 18-months follow-up were analyzed for DSM-III-R social phobic patients, with either a generalized social phobia (n = 50) or a nongeneralized fear, i.e. fear of blushing, trembling or sweating in social situations (n = 26). Predictors were pretreatment depression, personality disorder traits, clinician rated severity of impairment and frequency of negative self-statements during social interactions. The criterium variable was (the residual gain score of) self-reported avoidance of social situations. In line with Chambless et al., pretreatment depression showed some predictive value, but smaller and only at the posttest. Change in the frequency of negative self-statements paralleled, but did not predict, change in social phobia symptoms. In contrast with Chambless et al., clinician rated severity was (slightly) predictive for treatment outcome, whereas avoidant personality traits had reverse correlations with outcome in both subgroups. The results are discussed and directions for further research are given.

  2. Early Adolescent Depressive Symptoms: Prediction from Clique Isolation, Loneliness, and Perceived Social Acceptance

    ERIC Educational Resources Information Center

    Witvliet, Miranda; Brendgen, Mara; van Lier, Pol A. C.; Koot, Hans M.; Vitaro, Frank

    2010-01-01

    This study examined whether clique isolation predicted an increase in depressive symptoms and whether this association was mediated by loneliness and perceived social acceptance in 310 children followed from age 11-14 years. Clique isolation was identified through social network analysis, whereas depressive symptoms, loneliness, and perceived…

  3. How Homes Influence Schools: Early Parenting Predicts African American Children's Classroom Social-Emotional Functioning

    ERIC Educational Resources Information Center

    Baker, Claire E.; Rimm-Kaufman, Sara E.

    2014-01-01

    Data from the Early Childhood Longitudinal Study, Kindergarten Cohort were used to examine the extent to which early parenting predicted African American children's kindergarten social-emotional functioning. Teachers rated children's classroom social-emotional functioning in four areas (i.e., approaches to learning, self-control, interpersonal…

  4. Pathways to School Readiness: Executive Functioning Predicts Academic and Social-Emotional Aspects of School Readiness

    ERIC Educational Resources Information Center

    Mann, Trisha D.; Hund, Alycia M.; Hesson-McInnis, Matthew S.; Roman, Zachary J.

    2017-01-01

    The current study specified the extent to which hot and cool aspects of executive functioning predicted academic and social-emotional indicators of school readiness. It was unique in focusing on positive aspects of social-emotional readiness, rather than problem behaviors. One hundred four 3-5-year-old children completed tasks measuring executive…

  5. Early Adolescent Depressive Symptoms: Prediction from Clique Isolation, Loneliness, and Perceived Social Acceptance

    ERIC Educational Resources Information Center

    Witvliet, Miranda; Brendgen, Mara; van Lier, Pol A. C.; Koot, Hans M.; Vitaro, Frank

    2010-01-01

    This study examined whether clique isolation predicted an increase in depressive symptoms and whether this association was mediated by loneliness and perceived social acceptance in 310 children followed from age 11-14 years. Clique isolation was identified through social network analysis, whereas depressive symptoms, loneliness, and perceived…

  6. Predicting South Korean University Students' Happiness through Social Support and Efficacy Beliefs

    ERIC Educational Resources Information Center

    Lee, Diane Sookyoung; Padilla, Amado M.

    2016-01-01

    This study investigated the adversity and coping experiences of 198 South Korean university students and takes a cultural lens in understanding how social and individual factors shape their happiness. Hierarchical linear regression analyses suggest that Korean students' perceptions of social support significantly predicted their happiness,…

  7. Ontology-based Deep Learning for Human Behavior Prediction with Explanations in Health Social Networks.

    PubMed

    Phan, Nhathai; Dou, Dejing; Wang, Hao; Kil, David; Piniewski, Brigitte

    2017-04-01

    Human behavior modeling is a key component in application domains such as healthcare and social behavior research. In addition to accurate prediction, having the capacity to understand the roles of human behavior determinants and to provide explanations for the predicted behaviors is also important. Having this capacity increases trust in the systems and the likelihood that the systems actually will be adopted, thus driving engagement and loyalty. However, most prediction models do not provide explanations for the behaviors they predict. In this paper, we study the research problem, human behavior prediction with explanations, for healthcare intervention systems in health social networks. We propose an ontology-based deep learning model (ORBM(+)) for human behavior prediction over undirected and nodes-attributed graphs. We first propose a bottom-up algorithm to learn the user representation from health ontologies. Then the user representation is utilized to incorporate self-motivation, social influences, and environmental events together in a human behavior prediction model, which extends a well-known deep learning method, the Restricted Boltzmann Machine. ORBM(+) not only predicts human behaviors accurately, but also, it generates explanations for each predicted behavior. Experiments conducted on both real and synthetic health social networks have shown the tremendous effectiveness of our approach compared with conventional methods.

  8. Finite element based model predictive control for active vibration suppression of a one-link flexible manipulator.

    PubMed

    Dubay, Rickey; Hassan, Marwan; Li, Chunying; Charest, Meaghan

    2014-09-01

    This paper presents a unique approach for active vibration control of a one-link flexible manipulator. The method combines a finite element model of the manipulator and an advanced model predictive controller to suppress vibration at its tip. This hybrid methodology improves significantly over the standard application of a predictive controller for vibration control. The finite element model used in place of standard modelling in the control algorithm provides a more accurate prediction of dynamic behavior, resulting in enhanced control. Closed loop control experiments were performed using the flexible manipulator, instrumented with strain gauges and piezoelectric actuators. In all instances, experimental and simulation results demonstrate that the finite element based predictive controller provides improved active vibration suppression in comparison with using a standard predictive control strategy. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  9. Developmental Trajectories of Social Skills during Early Childhood and Links to Parenting Practices in a Japanese Sample

    PubMed Central

    Takahashi, Yusuke; Okada, Kensuke; Hoshino, Takahiro; Anme, Tokie

    2015-01-01

    This study used data from a nationwide survey in Japan to model the developmental course of social skills during early childhood. The goals of this study were to identify longitudinal profiles of social skills between 2 and 5 years of age using a group-based trajectory approach, and to investigate whether and to what extent parenting practices at 2 years of age predicted developmental trajectories of social skills during the preschool period. A relatively large sample of boys and girls (N > 1,000) was assessed on three social skill dimensions (Cooperation, Self-control, and Assertion) at four time points (ages 2, 3, 4, and 5), and on four parenting practices (cognitive and emotional involvement, avoidance of restriction and punishment, social stimulation, and social support for parenting) at age 2. The results indicated that for each social skill dimension, group-based trajectory models identified three distinct trajectories: low, moderate, and high. Multinomial regression analysis revealed that parenting practice variables showed differential contributions to development of child social skills. Specifically, Cooperation and Assertion were promoted by cognitive and emotional involvement, Self-control by social stimulation, and Assertion by avoidance of restriction and punishment. Abundant social support for parenting was not associated with higher child social skills trajectories. We found heterogeneity in developmental profiles of social skills during the preschool ages, and we identified parenting practices that contributed to different patterns of social skills development. We discussed the implications of higher-quality parenting practices on the improvement of child social skills across early childhood. PMID:26267439

  10. Developmental Trajectories of Social Skills during Early Childhood and Links to Parenting Practices in a Japanese Sample.

    PubMed

    Takahashi, Yusuke; Okada, Kensuke; Hoshino, Takahiro; Anme, Tokie

    2015-01-01

    This study used data from a nationwide survey in Japan to model the developmental course of social skills during early childhood. The goals of this study were to identify longitudinal profiles of social skills between 2 and 5 years of age using a group-based trajectory approach, and to investigate whether and to what extent parenting practices at 2 years of age predicted developmental trajectories of social skills during the preschool period. A relatively large sample of boys and girls (N > 1,000) was assessed on three social skill dimensions (Cooperation, Self-control, and Assertion) at four time points (ages 2, 3, 4, and 5), and on four parenting practices (cognitive and emotional involvement, avoidance of restriction and punishment, social stimulation, and social support for parenting) at age 2. The results indicated that for each social skill dimension, group-based trajectory models identified three distinct trajectories: low, moderate, and high. Multinomial regression analysis revealed that parenting practice variables showed differential contributions to development of child social skills. Specifically, Cooperation and Assertion were promoted by cognitive and emotional involvement, Self-control by social stimulation, and Assertion by avoidance of restriction and punishment. Abundant social support for parenting was not associated with higher child social skills trajectories. We found heterogeneity in developmental profiles of social skills during the preschool ages, and we identified parenting practices that contributed to different patterns of social skills development. We discussed the implications of higher-quality parenting practices on the improvement of child social skills across early childhood.

  11. Social dominance orientation predicts drive for muscularity among British men.

    PubMed

    Swami, Viren; Neofytou, Rudolfos-Valentino; Jablonska, Joanna; Thirlwell, Holly; Taylor, Donna; McCreary, Donald R

    2013-09-01

    The present study tested the hypothesis that men's drive for muscularity would be associated with their valuation of domination, power, status, and aggression over others. A community sample of 359 men from London, UK, completed measures of drive for muscularity, social dominance orientation, right-wing authoritarianism, trait aggression, and need for power, as well as their demographic details. Bivariate correlations showed that greater drive for muscularity was significantly correlated with most of the measures and their subscales. However, in a multiple regression analysis, the only significant predictor of drive for muscularity was support for group-based dominance hierarchies (Adj. R(2)=.17). These results suggest that men's drive for muscularity is associated with a socio-political ideology that favours social dominance.

  12. Myopic social prediction and the solo comparison effect.

    PubMed

    Moore, Don A; Kim, Tai Gyu

    2003-12-01

    Four experiments explored the psychological processes by which people make comparative social judgments. Each participant chose how much money to wager on beating an opponent on either a difficult or a simple trivia quiz. Quiz difficulty did not influence the average person's probability of winning, yet participants bet more on a simple quiz than on a difficult quiz in the first 3 experiments. The results suggest that this effect results from a tendency to attend more closely to a focal actor than to others. Experiment 4 directly manipulated focusing; when participants were led to focus on the opponent instead of themselves, the effect was reversed. The discussion relates the results to other literatures including overly optimistic self-evaluation, false consensus, overconfidence, and social comparison.

  13. Social Inclusion Predicts Lower Blood Glucose and Low-Density Lipoproteins in Healthy Adults.

    PubMed

    Floyd, Kory; Veksler, Alice E; McEwan, Bree; Hesse, Colin; Boren, Justin P; Dinsmore, Dana R; Pavlich, Corey A

    2016-07-27

    Loneliness has been shown to have direct effects on one's personal well-being. Specifically, a greater feeling of loneliness is associated with negative mental health outcomes, negative health behaviors, and an increased likelihood of premature mortality. Using the neuroendocrine hypothesis, we expected social inclusion to predict decreases in both blood glucose levels and low-density lipoproteins (LDLs) and increases in high-density lipoproteins (HDLs). Fifty-two healthy adults provided self-report data for social inclusion and blood samples for hematological tests. Results indicated that higher social inclusion predicted lower levels of blood glucose and LDL, but had no effect on HDL. Implications for theory and practice are discussed.

  14. Does workplace social capital protect against long-term sickness absence? Linking workplace aggregated social capital to sickness absence registry data.

    PubMed

    Hansen, Anne-Sophie K; Madsen, Ida E H; Thorsen, Sannie Vester; Melkevik, Ole; Bjørner, Jakob Bue; Andersen, Ingelise; Rugulies, Reiner

    2017-08-01

    Most previous prospective studies have examined workplace social capital as a resource of the individual. However, literature suggests that social capital is a collective good. In the present study we examined whether a high level of workplace aggregated social capital (WASC) predicts a decreased risk of individual-level long-term sickness absence (LTSA) in Danish private sector employees. A sample of 2043 employees (aged 18-64 years, 38.5% women) from 260 Danish private-sector companies filled in a questionnaire on workplace social capital and covariates. WASC was calculated by assigning the company-averaged social capital score to all employees of each company. We derived LTSA, defined as sickness absence of more than three weeks, from a national register. We examined if WASC predicted employee LTSA using multilevel survival analyses, while excluding participants with LTSA in the three months preceding baseline. We found no statistically significant association in any of the analyses. The hazard ratio for LTSA in the fully adjusted model was 0.93 (95% CI 0.77-1.13) per one standard deviation increase in WASC. When using WASC as a categorical exposure we found a statistically non-significant tendency towards a decreased risk of LTSA in employees with medium WASC (fully adjusted model: HR 0.78 (95% CI 0.48-1.27)). Post hoc analyses with workplace social capital as a resource of the individual showed similar results. WASC did not predict LTSA in this sample of Danish private-sector employees.

  15. Does the Social Working Environment Predict Beginning Teachers' Self-Efficacy and Feelings of Depression?

    ERIC Educational Resources Information Center

    Devos, Christelle; Dupriez, Vincent; Paquay, Leopold

    2012-01-01

    We investigate how the social working environment predicts beginning teachers' self-efficacy and feelings of depression. Two quantitative studies are presented. The results show that the goal structure of the school culture (mastery or performance orientation) predicts both outcomes. Frequent collaborative interactions with colleagues are related…

  16. Right temporoparietal gray matter predicts accuracy of social perception in the autism spectrum.

    PubMed

    David, Nicole; Schultz, Johannes; Milne, Elizabeth; Schunke, Odette; Schöttle, Daniel; Münchau, Alexander; Siegel, Markus; Vogeley, Kai; Engel, Andreas K

    2014-06-01

    Individuals with an autism spectrum disorder (ASD) show hallmark deficits in social perception. These difficulties might also reflect fundamental deficits in integrating visual signals. We contrasted predictions of a social perception and a spatial-temporal integration deficit account. Participants with ASD and matched controls performed two tasks: the first required spatiotemporal integration of global motion signals without social meaning, the second required processing of socially relevant local motion. The ASD group only showed differences to controls in social motion evaluation. In addition, gray matter volume in the temporal-parietal junction correlated positively with accuracy in social motion perception in the ASD group. Our findings suggest that social-perceptual difficulties in ASD cannot be reduced to deficits in spatial-temporal integration.

  17. Family and peer social support and their links to psychological distress among hurricane-exposed minority youth.

    PubMed

    Banks, Donice M; Weems, Carl F

    2014-07-01

    Experiencing a disaster such as a hurricane places youth at a heightened risk for psychological distress such as symptoms of posttraumatic stress disorder (PTSD), anxiety, and depression. Social support may contribute to resilience following disasters, but the interrelations of different types of support, level of exposure, and different symptoms among youth is not well understood. This study examined associations among family and peer social support, level of hurricane exposure, and their links to psychological distress using both a large single-time assessment sample (N = 1,098) as well as a longitudinal sample followed over a 6-month period (n = 192). Higher levels of hurricane exposure were related to lower levels of social support from family and peers. Higher levels of family and peer social support demonstrated both concurrent and longitudinal associations with lower levels of psychological distress, with associations varying by social support source and psychological distress outcome. Findings also suggested that the protective effects of high peer social support may be diminished by high hurricane exposure. The results of this study further our understanding of the role of social support in hurricane-exposed youths' emotional functioning and point to the potential importance of efforts to bolster social support following disasters.

  18. For Tests That Are Predictively Powerful and without Social Prejudice

    ERIC Educational Resources Information Center

    Soares, Joseph A.

    2012-01-01

    In Philip Pullman's dark matter sci-fi trilogy, there is a golden compass that in the hands of the right person is predictively powerful; the same was supposed to be true of the SAT/ACT--the statistically indistinguishable standardized tests for college admissions. They were intended to be reliable mechanisms for identifying future trajectories,…

  19. Predicting Social Competence: The Validity of the PIPS.

    ERIC Educational Resources Information Center

    Turner, Ralph R.; Boulter, Linda K.

    The validity of the interpersonal cognitive problem solving (ICPS) skills model of children's adjustment was investigated (1) by determining whether ICPS skills demonstrated during preschool predicted teacher ratings of adjustment in school during the next two years and (2) by assessing the objectivity of teacher ratings of adjustment through the…

  20. Communication abnormalities predict functional outcomes in chronic schizophrenia: differential associations with social and adaptive functions.

    PubMed

    Bowie, Christopher R; Harvey, Philip D

    2008-08-01

    Communication abnormalities are hallmark features of schizophrenia. Despite the prevalence and persistence of these symptoms, little is known about their functional implications. In this study, we examined, in a sample of chronically institutionalized schizophrenia patients (N=317), whether two types of communication abnormalities (i.e., verbal underproductivity and disconnected speech) had differential relationships with social and adaptive outcomes. Baseline ratings of verbal underproductivity, disconnected speech, global cognitive performance, and clinical symptoms, were entered into stepwise regression analyses to examine their relationship with 2.5 year social and adaptive outcomes. At baseline, disconnected speech was significantly associated with socially impolite behavior, while verbal underproductivity was associated with social disengagement and impaired friendships. Both types of communication abnormalities were significantly associated with other types of social skills. Verbal underproductivity predicted follow-up social skills, social engagement, and friendships, accounting for more variance than. cognition or symptoms. In contrast to social outcomes, adaptive outcomes were predicted by baseline neurocognition and clinical symptoms, but not communication abnormalities. These findings provide evidence for specific relationships of communication disorder subtypes with diverse impairments in social functions. In this chronically institutionalized sample, communication disorder was a stronger predictor of social, but not adaptive, outcomes than neurocognition or clinical symptoms.