13,842 research outputs found
Quantifying and minimizing risk of conflict in social networks
Controversy, disagreement, conflict, polarization and opinion divergence in social networks have been the subject of much recent research. In particular, researchers have addressed the question of how such concepts can be quantified given people’s prior opinions, and how they can be optimized by influencing the opinion of a small number of people or by editing the network’s connectivity.
Here, rather than optimizing such concepts given a specific set of prior opinions, we study whether they can be optimized in the average case and in the worst case over all sets of prior opinions. In particular, we derive the worst-case and average-case conflict risk of networks, and we propose algorithms for optimizing these.
For some measures of conflict, these are non-convex optimization problems with many local minima. We provide a theoretical and empirical analysis of the nature of some of these local minima, and show how they are related to existing organizational structures.
Empirical results show how a small number of edits quickly decreases its conflict risk, both average-case and worst-case. Furthermore, it shows that minimizing average-case conflict risk often does not reduce worst-case conflict risk. Minimizing worst-case conflict risk on the other hand, while computationally more challenging, is generally effective at minimizing both worst-case as well as average-case conflict risk
On green routing and scheduling problem
The vehicle routing and scheduling problem has been studied with much
interest within the last four decades. In this paper, some of the existing
literature dealing with routing and scheduling problems with environmental
issues is reviewed, and a description is provided of the problems that have
been investigated and how they are treated using combinatorial optimization
tools
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A Dose Relationship Between Brain Functional Connectivity and Cumulative Head Impact Exposure in Collegiate Water Polo Players.
A growing body of evidence suggests that chronic, sport-related head impact exposure can impair brain functional integration and brain structure and function. Evidence of a robust inverse relationship between the frequency and magnitude of repeated head impacts and disturbed brain network function is needed to strengthen an argument for causality. In pursuing such a relationship, we used cap-worn inertial sensors to measure the frequency and magnitude of head impacts sustained by eighteen intercollegiate water polo athletes monitored over a single season of play. Participants were evaluated before and after the season using computerized cognitive tests of inhibitory control and resting electroencephalography. Greater head impact exposure was associated with increased phase synchrony [r (16) > 0.626, p < 0.03 corrected], global efficiency [r (16) > 0.601, p < 0.04 corrected], and mean clustering coefficient [r (16) > 0.625, p < 0.03 corrected] in the functional networks formed by slow-wave (delta, theta) oscillations. Head impact exposure was not associated with changes in performance on the inhibitory control tasks. However, those with the greatest impact exposure showed an association between changes in resting-state connectivity and a dissociation between performance on the tasks after the season [r (16) = 0.481, p = 0.043] that could also be attributed to increased slow-wave synchrony [F (4, 135) = 113.546, p < 0.001]. Collectively, our results suggest that athletes sustaining the greatest head impact exposure exhibited changes in whole-brain functional connectivity that were associated with altered information processing and inhibitory control
The normalized Friedkin-Johnsen model (a work-in-progress report)
The formation of opinions in a social context has long been studied by sociologists. A well-known model is due to Friedkin and Johnsen (further referenced as the FJ model), which assumes that individuals hold an immutable internal opinion while they express an opinion that may differ from it but is more in agreement with the expressed opinions of their friends. Formally, the expressed opinion is modeled as the weighted average of the individual's internal opinion and the expressed opinions of their neighbors. This model has been used in recent research originating from the computer science community, studying the origination and reduction of conflict on social networks, how echo chambers arise and can be burst, and more.
Yet, we argue that the FJ model in its elementary form is not suitable for some of these purposes. Indeed, the FJ model entails that the more friends one has, the less one's internal opinion matters in the formation of one's expressed opinion. Arguing that this may not be realistic, we propose a modification of the FJ model that normalizes the influence of one's friends and keeps the influence of one's internal opinion constant. This normalization was in fact suggested by Friedkin and Johnsen, but it has been ignored in much of the recent computer science literature.
In this work-in-progress report, we present the details of the normalized model, and investigate the consequences of this normalization, both theoretically and empirically
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Incorporating Human Beliefs and Behaviors into Wildlife Ecology
Like much of the global biosphere, wildlife species have experienced rapid declines during the Anthropocene. Wildlife ecologists have responded to these crises by developing a range of technologies, techniques, and large datasets, which together have revolutionized the field, provided novel insights into the movements and behaviors of animals, and identified new risks and impacts to wildlife in a human-dominated world. While these advances have been vitally important, wildlife ecology has been slower to recognize and incorporate humans themselves into its new research domains. The chapters of this dissertation explore methods for better incorporating human behaviors, beliefs, actions, and infrastructure into the theories and approaches in wildlife ecology that have flourished in the last two decades. The research presented here demonstrates the importance of linking human beliefs and behaviors to wildlife ecology both by presenting novel findings and by showing the opportunities missed when narrow approaches are applied to complex socio-ecological problems.In Chapter 1, I provide a general introduction on the theories underlying this research, contextualize the research questions in light of the loss and recovery of large predators, and describe the research site where I collected much of the data for this dissertation. In Chapter 2, I apply the methods of movement ecology to some of the first fine-scale telemetry data collected on rifle hunters. I draw conclusions about their individual, site-level, and regional-level hunting behaviors and discuss the broad implications of these findings for hunting management. In Chapter 3, I examine livestock-predator conflict using approaches from both ecology and the social sciences. I describe a form of selection bias that is likely widespread but unreported due to the omission of social data from ecological models of conflict, and I offer guidelines for combining and translating ecological and social research on conflict. In Chapter 4, I explore the ecological impacts of one of the most globally widespread human constructions, the fence. I show for the first time the potential extent of fencing at large scales and discuss the wide variety of ecological effects of fences for both humans and ecosystems. I further highlight biases and gaps in fence research that have thus far limited a complete understanding of the environmental effects of these features. In Chapter 5, I conclude by making recommendations regarding how research might better incorporate human perceptions, decisions, and actions into ecology
Oceans and the Sustainable Development Goals: Co-Benefits, Climate Change & Social Equity
Achieving ocean sustainability is paramount for coastal communities and marine industries, yet is also inextricably linked to much broader global sustainable development—including increased resilience to climate change and improved social equity—as envisioned by the UN 2030 Agenda for Sustainable Development. This report highlights the co-benefits from achieving each SDG 14 target: progress towards each of the other 161 SDG targets when ocean targets are met, given ten-year lag times between ocean targets and other SDG targets. The identification of co-benefits is based on input from more than 30 scientific experts in the Nereus Program. Below we highlight notable co-benefits of achieving each target within SDG 14
Personality cannot be predicted from the power of resting state EEG
In the present study we asked whether it is possible to decode personality
traits from resting state EEG data. EEG was recorded from a large sample of
subjects (N = 309) who had answered questionnaires measuring personality trait
scores of the 5 dimensions as well as the 10 subordinate aspects of the Big
Five. Machine learning algorithms were used to build a classifier to predict
each personality trait from power spectra of the resting state EEG data. The
results indicate that the five dimensions as well as their subordinate aspects
could not be predicted from the resting state EEG data. Finally, to demonstrate
that this result is not due to systematic algorithmic or implementation
mistakes the same methods were used to successfully classify whether the
subject had eyes open or eyes closed and whether the subject was male or
female. These results indicate that the extraction of personality traits from
the power spectra of resting state EEG is extremely noisy, if possible at all.Comment: 14 pages, 4 figure
Spatial optimization for land use allocation: accounting for sustainability concerns
Land-use allocation has long been an important area of research in regional science. Land-use patterns are fundamental to the functions of the biosphere, creating interactions that have substantial impacts on the environment. The spatial arrangement of land uses therefore has implications for activity and travel within a region. Balancing development, economic growth, social interaction, and the protection of the natural environment is at the heart of long-term sustainability. Since land-use patterns are spatially explicit in nature, planning and management necessarily must integrate geographical information system and spatial optimization in meaningful ways if efficiency goals and objectives are to be achieved. This article reviews spatial optimization approaches that have been relied upon to support land-use planning. Characteristics of sustainable land use, particularly compactness, contiguity, and compatibility, are discussed and how spatial optimization techniques have addressed these characteristics are detailed. In particular, objectives and constraints in spatial optimization approaches are examined
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