Analysis of epidemic propagation using mean field theory on signed graphs

Over the past few decades, the study of epidemic propagation has caught widespread attention from many areas. The field of graphs contains a wide body of research, yet only a few studies explore epidemic propagation’s dynamics in “signed” networks. Motivated by this problem, in this paper we propose a new epidemic propagation model for signed networks, denoted as S-SIS. To explain our analysis, we utilized the mean field theory to demonstrate the theoretical results. When we compare epidemic propagation through negative links to those only having positive links, we find that a higher proportion of infected nodes actually spreads at a relatively small infection rate. It is also found that when the infection rate is higher than a certain value, the overall spreading in a signed network begins showing signs of suppression. Finally, in order to verify our findings, we apply the S-SIS model on Erdös–Rényi random network and scale-free network, and the simulation results is well consist with the theoretical analysis.

Requirement to change of functional brain network across the lifespan

Many studies have focused on neural changes and neuroplasticity, while the signaling demand for neural modification needs to be explored. In this study, we traced this issue in the organization of brain functional links where the conflictual arrangement of signed links makes a request to change. We introduced the number of frustrations (unsatisfied closed triadic interactions) as a measure for assessing "requirement to change" of functional brain network. We revealed that the requirement to change of the resting-state network has a u-shape functionality over the lifespan with a minimum in early adulthood, and it’s correlated with the presence of negative links. Also, we discovered that brain negative subnetwork has a special topology with a log-normal degree distribution in all stages, however, its global measures are altered by adulthood. Our results highlight the study of collective behavior of functional negative links as the source of the brain’s between-regions conflicts and we propose exploring the attribute of the requirement to change besides other neural change factors.

Social Media Addiction and Personality: A Review of Research

Social networks are taking up more and more place in the daily life of modern people, becoming an integral part of our existence. At the same time, the role of social networks is constantly growing along with the rapid growth in the number of their active users. As online interaction for many has become more used than face-to-face communication, social networks have begun to seriously affect the way of life, communication, interests and psychology of people. The use of social networks is growing exponentially and has covered more than a third of the worlds population; therefore, researchers from different countries are actively studying social networks. Considerable empirical data has been accumulated that requires generalization and understanding, which is the purpose of this review. We found positive links between social media addiction and depression, anxiety, stress, neuroticism, emotional problems, low self-esteem, cyber-victimization, physical health problems, mental disorders, loneliness, procrastination, smartphone and internet addiction, and infidelity in relationships. Negative links were revealed between social media addiction and life satisfaction, academic performance of schoolchildren and students, labor productivity and commitment to the organization of its employees, social capital, and age. The main reason for social media addiction is the need for communication, and women are generally more active in social networks than men. This review provides only those links of social media addiction that have been established in a number of studies conducted in different countries. The presented results were obtained abroad using foreign language questionnaires that determine social media addiction. The lack of such a reliable and valid tool among Russian-speaking psychologists has become a serious factor hindering the conduct of similar domestic research. With this in view, the author developed a specially designed social media addiction questionnaire.

Microbial communities network structure across strong environmental gradients: How do they compare to macroorganisms?

The way strong environmental gradients shape multispecific assemblages has allowed us to examine a suite of ecological and evolutionary hypotheses about structure, regulation, and community responses to fluctuating environments. But whether the highly diverse co-occurring, free-living microorganisms are shaped in similar ways as macroscopic organisms, across the same gradients, has yet to be addressed in most ecosystems. The everything is everywhere hypothesis suggests they are not, at least not to the same extent. Here we characterize the structure of intertidal microbial biofilm communities and compare the intensity of zonation at the species-level, changes in taxonomic diversity and composition at the community level, and network attributes, with those observed in co-occurring macroalgae and invertebrates. At the level of species and OTUs, for dominant macro and microorganisms respectively, microbes showed less variability across the tidal gradient than macroorganisms. At the community-level, however, microbes and macro-organisms showed similarly strong patterns of tidal zonation, with major changes in composition and relative abundances across tides. Moreover, the proportion of environmental specialists in different tidal zones was remarkably similar in micro and macroscopic communities, and taxonomic richness and diversity followed similar trends, with lower values in the high intertidal zone. Network analyses showed similar connectivity and transitivity, despite the large differences in absolute richness between the groups. A high proportion of positive co-occurrences within all tidal zones and mostly negative links between the high and low tidal zones were observed among habitat specialist taxa of micro-and macro-organisms. Thus, our results provide partial support to the idea that microbes are less affected by environmental variability than macroscopic counterparts. At the species-level, the most common microbe species exhibit less variation across tides than most common macroscopic organisms, suggesting the former perceive a more homogeneous environment and/or are more resistant to the associated stress. At the community-level, most indicators of community and network structure across the gradient are similar between microbes and macro-organisms, suggesting that despite orders of magnitude differences in richness and size, these two systems respond to stress gradients, giving rise to zonation patterns.

Effect of long-term fertilizer type with film mulching on maize yield, soil aggregation and bacteria on the Loess Plateau of China

Both PU and PC increased maize yield, water use efficiency (WUE), and partial factor productivity from applied N (PFPN), relative to CK. PC increased maize yield more than PU, and had higher soil organic carbon (SOC) content than PU, which was mainly due to the decline in SOC stocks in the 250–2000, 53–250, and <53 μm soil aggregates. The soil bacterial community structure was driven by SOC, C: N ratio, total nitrogen (TN), pH, microaggregates, clay and silt in CK, and by larger macroaggregates and mean weight diameter in PC and PU. Both PC and PU significantly changed soil bacterial community beta diversity, and decreased both positive and negative links of the co-occurrence network, relative to CK. Better soil nutrient conditions in PC explained the small number of positive and negative links between soil bacteria. Our results suggest PM improves maize yield, water and nitrogen use efficiency, and soil aggregate stability while alleviating bacterial competition. However, the reduction of SOC and pH caused by PM still needs our attention. PC alleviates the decline of soil fertility and soil acidification and has higher yield relative to PU. Therefore, we proposed PC is a potential agricultural measure that can replace PU on the Loess Plateau.

Emotional Intelligence Supports Transformational LeadershipStyle: A Survey of Local Government District D.I. Khan Khyber Pakhtunkhwa Pakistan

In the contemporary world of stress and insecurity in developing countries like Pakistan, emotional intelligence has earned critical importance as an effective tool for organizational leadership. Literature suggests that when human devotion, motivation and commitment are the keys to organizational success, transformational leadership with sufficient command over emotional intelligence is the only package that can help successful operations of the organization. This study tests the same model of positive relations between EI & TRFLS and negative links of EI with TRSLS in the 'local government' work environment using local government leaders as the unit of analysis. Literature and field surveys for data collection and statistical tools for data analysis have been applied to serve the purposes of this study. The results confirm the hypothesized relationships between predictor and criterion variables with specific 'statistics' warranting further work on strengthening the interactions between TRFLS and EI.

Heterogeneity in spontaneous sleep arousals: positive and negative links with early amyloid-beta and cognition

Recent literature is pointing towards a tight relationship between sleep quality and amyloid-beta (Aβ) accumulation, a hallmark of Alzheimer’s disease (AD). Sleep arousals are considered to induce sleep disruption, and though their heterogeneity has been suggested, their correlates remain to be established. We classified arousals in sleep of 100 healthy older individuals according to their association with muscular tone increase (E+/E-) and sleep stage transition (T+/T-), and show differences in EEG oscillatory compositions across arousal types. We found that T + E- arousals, which interrupt sleep stability, were positively correlated with Aβ burden in brain regions earliest affected by AD neuropathology. By contrast, more prevalent T-E + arousals, upholding sleep continuity, were associated with lower cortical Aβ burden, and better cognition. We provide empirical evidence that spontaneous arousals are diverse and differently associated with brain integrity and cognition. Sleep arousals may offer opportunities to transiently synchronise distant brain areas, akin to sleep spindles.

PSYCHOLOGICAL INHIBITORS OF INTELLIGENCE OF FUTURE TEACHERS

The article presents the results of theoretical and empirical research aimed at studying the psychological inhibitors of intelligence of students who will work as teachers in the future. Analysis of the literature on the topic allowed to clarify the content of the main psychological phenomena being studied, to choose parameters that represent intelligence at the formal-dynamic and content-personal levels, as well as psychological properties that can hypothetically inhibit the intelligence of future teachers. Correlation analysis proved: 1) the complex and ambiguous nature of the relationships between the parameters under study; 2) the negative nature of the relationship of a number of indicators of general and social intelligence with indicators of anxiety and aggression, and positive one with indicators of conflict resilience; 3) only indicators of the style "field-dependence/field-independence" have significant negative links with hypothetical inhibitors of intelligence (indicator of personal anxiety) among a number of cognitive-stylistic indicators. Based on the purpose and research tasks, 6 groups of future teachers were created. The first group includes subjects with a low level of anxiety (LA) - 10 people, the second one with a high level of anxiety (HA) - 10 people, the third group - with a low level of aggression - 10 people (LA), the fourth - with a high level of aggression (HA) - 10 people, the fifth group - subjects with a high level of conflict resistance (HC), the sixth - with a low (LC). By means of the qualitative analysis the information on individual-typical features of intelligence of persons with various levels of the specified properties was received, their comparison was carried out. Future teachers with high anxiety, high aggression, low conflict resistance are inferior to colleagues with opposite characteristics in a number of parameters of general and social intelligence. As shown by the results of observations and conversations with these subjects, this leads to significant problems in their professional development, creates for them certain difficulties in various spheres of life. Qualitative analysis has shown that anxiety, aggression and conflict resilience can act as inhibitors of intelligence. However, firstly, it depends on their severity (high anxiety, high aggression and low conflict resistance can act as inhibitors) and secondly, if anxiety acts as an inhibitor, both at the cognitive-stylistic and content-personal levels of intelligence, aggression and conflict resistance act only on the latter one. In addition, their influence affects social intelligence and, unlike anxiety, does not extend to general intelligence.

Transaction Prediction in Blockchain: A Negative Link Prediction Algorithm Based on the Sentiment Analysis and Balance Theory

User relationship prediction in the transaction of Blockchain is to predict whether a transaction will occur between two users in the future, which can be abstracted into the link prediction problem. The link prediction can be categorized into the positive one and the negative one. However, the existing negative link prediction algorithms mainly consider the number of negative user interactions and lack the full use of emotion characteristics in user interactions. To solve this problem, this paper proposes a negative link prediction algorithm based on the sentiment analysis and balance theory. Firstly, the user interaction matrix is constructed based on calculating the intensity of emotion polarity for social network texts, and a reliability weight matrix (noted as RW-matrix) is constructed based on the user interaction matrix to measure the reliability of negative links. Secondly, with the RW-matrix, a negative link prediction algorithm is proposed based on the structural balance theory by constructing negative link sample sets and extracting sample features. To evaluate the performance of the negative link prediction algorithm proposed, the variable management method is used to analyze the influence of negative sample control error and other parameters on the accuracy of it. Compared with the existing prediction benchmark algorithms, the experimental results demonstrate that the proposed negative link prediction algorithm can improve the accuracy of prediction significantly and deliver good performances.

Topological impact of negative links on the stability of resting-state brain network

Stability is a physical attribute that stands opposite the change. However, it is still unclear how the arrangement of links called topology affects network stability. In this study, we tackled this issue in the resting-state brain network using structural balance. Structural balance theory employs the quality of triadic associations between signed links to determine the network stability. In this study, we showed that negative links of the resting-state network make hubs to reduce balance-energy and push the network into a more stable state compared to null-networks with trivial topologies. In this regard, we created a global measure entitled ‘tendency to make hub’ to assess the hubness of the network. Besides, we revealed nodal degrees of negative links have an exponential distribution that confirms the existence of negative hubs. Our findings indicate that the arrangement of negative links plays an important role in the balance (stability) of the resting-state brain network.