Global Diversity and Local Consensus in Status Beliefs:The Role of Network Clustering and Resistance to Belief Change

Formal models of status construction theory suggest that beliefs about the relative social worth and competence of members of different social groups can emerge from face-to-face interactions in task-focused groups and eventually become consensual in large populations. We propose two extensions of earlier models. First, we incorporate the microlevel behavioral assumption of status construction theory that people can become resistant to belief change when a belief appears consensual in their local social environment. Second, we integrate the insight that the macro-level social structure of face-to-face interactions in large populations often is a clustered network structure. Computational experiments identify an outcome that was not anticipated by earlier formalizations. The combination of network clustering at the macrolevel and resistance to belief change at the microlevel can constrain the diffusion of status beliefs and generate regional variation in status beliefs. Further experiments identify conditions under which this outcome obtains

The importance of lithological heterogeneity of the Onaping Formation for understanding post-impact deformation of the Sudbury Impact Structure, Canada

The suevitic Onaping Formation overlies the layered Main Mass of the 1.85Ga Sudbury Igneous Complex (SIC) of the Sudbury Impact Structure, Ontario. The Formation consists of four Members, namely from top to bottom, the Black, the Green, the Gray and the Basal. Post-impact NWSE shortening during the Penokean Orogeny (ca. 1.9–1.75 Ga) affected the Onaping Formation and led to the lobate shape of the SIC in plan view. In order to investigate the possible fold origin of the NE-lobe of the SIC, a field-based structural analysis of the Onaping Formation was conducted in the Frenchman Lake area. The analysis is based on structural measurements at 580 stations and encompasses the orientation of mineral shape fabrics as well as their intensity. In addition to these quantities, lithological variation and metamorphic overprint of the Onaping Formation was examined. Special attention was paid thereby to the Green Member since previous workers stated that it forms a continuous unit at the base of the Black Member...conferenc

Assessment of the suitability of degradation models for the planning of CCTV inspections of sewer pipes

The degradation of sewer pipes poses significant economical, environmental and health concerns. The maintenance of such assets requires structured plans to perform inspections, which are more efficient when structural and environmental features are considered along with the results of previous inspection reports. The development of such plans requires degradation models that can be based on statistical and machine learning methods. This work proposes a methodology to assess their suitability to plan inspections considering three dimensions: accuracy metrics, ability to produce long-term degradation curves and explainability. Results suggest that although ensemble models yield the highest accuracy, they are unable to infer the long-term degradation of the pipes, whereas the Logistic Regression offers a slightly less accurate model that is able to produce consistent degradation curves with a high explainability. A use case is presented to demonstrate this methodology and the efficiency of model-based planning compared to the current inspection plan

Assessment of the suitability of degradation models for the planning of CCTV inspections of sewer pipes

The degradation of sewer pipes poses significant economical, environmental and health concerns. The maintenance of such assets requires structured plans to perform inspections, which are more efficient when structural and environmental features are considered along with the results of previous inspection reports. The development of such plans requires degradation models that can be based on statistical and machine learning methods. This work proposes a methodology to assess their suitability to plan inspections considering three dimensions: accuracy metrics, ability to produce long-term degradation curves and explainability. Results suggest that although ensemble models yield the highest accuracy, they are unable to infer the long-term degradation of the pipes, whereas the Logistic Regression offers a slightly less accurate model that is able to produce consistent degradation curves with a high explainability. A use case is presented to demonstrate this methodology and the efficiency of model-based planning compared to the current inspection plan

Software Engineering meets Artificial Intelligence

With the increasing use of AI in classic software systems, two worlds are coming closer and closer to each other that were previously rather alien to each other, namely the established discipline of software engineering and the world of AI. On the one hand, there are the data scientists, who try to extract as many insights as possible from the data using various tools, a lot of freedom and creativity. On the other hand, the software engineers, who have learned over years and decades to deliver the highest quality software possible and to manage release statuses. When developing software systems that include AI components, these worlds collide. This article shows which aspects come into play here, which problems can occur, and how solutions to these problems might look like. Beyond that, software engineering itself can benefit from the use of AI methods. Thus, we will also look at the emerging research area AI for software engineering

Collaborative production networks among unequal actors

We develop a model of strategic network formation of collaborations to analyze the consequences of an understudied but consequential form of heterogeneity: differences between actors in the form of their production functions. We also address how this interacts with resource heterogeneity, as a way to measure the impact actors have as potential partners on a collaborative project. Some actors (e.g., start-up firms) may exhibit increasing returns to their investment into collaboration projects, while others (e.g., established firms) may face decreasing returns. Our model provides insights into how actor heterogeneity can help explain well-observed collaboration patterns. We show that if there is a direct relation between increasing returns and resources, start-ups exclude mature firms and networks become segregated by types of production function, portraying dominant group architectures. On the other hand, if there is an inverse relation between increasing returns and resources, networks portray core-periphery architectures, where the mature firms form a core and start-ups with low-resources link to them

Mechanism of reduction of virus release and cell-cell fusion in persistent canine distemper virus infection

Canine distemper virus (CDV), a mobillivirus related to measles virus causes a chronic progressive demyelinating disease, associated with persistence of the virus in the central nervous system (CNS). CNS persistence of morbilliviruses has been associated with cell-to-cell spread, thereby limiting immune detection. The mechanism of cell-to-cell spread remains uncertain. In the present study we studied viral spread comparing a cytolytic (non-persistent) and a persistent CDV strain in cell cultures. Cytolytic CDV spread in a compact concentric manner with extensive cell fusion and destruction of the monolayer. Persistent CDV exhibited a heterogeneous cell-to-cell pattern of spread without cell fusion and 100-fold reduction of infectious viral titers in supernatants as compared to the cytolytic strain. Ultrastructurally, low infectious titers correlated with limited budding of persistent CDV as compared to the cytolytic strain, which shed large numbers of viral particles. The pattern of heterogeneous cell-to-cell viral spread can be explained by low production of infectious viral particles in only few areas of the cell membrane. In this way persistent CDV only spreads to a small proportion of the cells surrounding an infected one. Our studies suggest that both cell-to-cell spread and limited production of infectious virus are related to reduced expression of fusogenic complexes in the cell membrane. Such complexes consist of a synergistic configuration of the attachment (H) and fusion (F) proteins on the cell surface. F und H proteins exhibited a marked degree of colocalization in cytolytic CDV infection but not in persistent CDV as seen by confocal laser microscopy. In addition, analysis of CDV F protein expression using vaccinia constructs of both strains revealed an additional large fraction of uncleaved fusion protein in the persistent strain. This suggests that the paucity of active fusion complexes is due to restricted intracellular processing of the viral fusion protei

An Agent-Based Model of Status Construction in Task Focused Groups

Status beliefs link social distinctions, such as gender and race, to assumptions about competence and social worth. Recent modeling work in status construction theory suggests that interactions in small, task focused groups can lead to the spontaneous emergence and diffusion of such beliefs in larger populations. This earlier work has focused on dyads as the smallest possible groups in which status beliefs might emerge from face-to-face interaction. In today's societies, however, many task focused interactions take place in groups larger than dyads. In this article, we therefore develop an agent-based computational model that enables us to study the emergence of status beliefs in groups larger than dyads. With this model, we address questions such as: Do basic principles of task focused interaction systematically favor the emergence of status beliefs in groups larger than dyads? Does the time-frame over which small groups interact affect the likelihood with which status beliefs emerge? How does group size affect the emergence of status beliefs? Computational experimentation with the new model suggests that behavioral principles known to spontaneously create hierarchical differentiation between individual group members also tend to align these hierarchies with categorical differences and thereby facilitate the emergence of status beliefs. This tendency is stronger in smaller groups, and in groups that interact either for a very short or very long time

Using averaged models from 4D ultrasound strain imaging allows to signifcantly diferentiate local wall strains in calcifed regions of abdominal aortic aneurysms

Abdominal aortic aneurysms are a degenerative disease of the aorta associated with high mortality. To date, in vivo information to characterize the individual elastic properties of the aneurysm wall in terms of rupture risk is lacking. We have used time-resolved 3D ultrasound strain imaging to calculate spatially resolved in-plane strain distributions characterized by mean and local maximum strains, as well as indices of local variations in strains. Likewise, we here present a method to generate averaged models from multiple segmentations. Strains were then calculated for single segmentations and averaged models. After registration with aneurysm geometries based on CT-A imaging, local strains were divided into two groups with and without calcifications and compared. Geometry comparison from both imaging modalities showed good agreement with a root mean squared error of 1.22 ± 0.15 mm and Hausdorff Distance of 5.45 ± 1.56 mm (mean ± sd, respectively). Using averaged models, circumferential strains in areas with calcifications were 23.2 ± 11.7% (mean ± sd) smaller and significantly distinguishable at the 5% level from areas without calcifications. For single segmentations, this was possible only in 50% of cases. The areas without calcifications showed greater heterogeneity, larger maximum strains, and smaller strain ratios when computed by use of the averaged models. Using these averaged models, reliable conclusions can be made about the local elastic properties of individual aneurysm (and long-term observations of their change), rather than just group comparisons. This is an important prerequisite for clinical application and provides qualitatively new information about the change of an abdominal aortic aneurysm in the course of disease progression compared to the diameter criterion