Structural and Institutional Determinants of Influence Reputation: A Comparison of Collaborative and Adversarial Policy Networks in Decision Making and Implementation

The central assumption in the literature on collaborative networks and policy networks is that political outcomes are affected by a variety of state and nonstate actors. Some of these actors are more powerful than others and can therefore have a considerable effect on decision making. In this article, we seek to provide a structural and institutional explanation for these power differentials in policy networks and support the explanation with empirical evidence. We use a dyadic measure of influence reputation as a proxy for power, and posit that influence reputation over the political outcome is related to vertical integration into the political system by means of formal decision-making authority, and to horizontal integration by means of being well embedded into the policy network. Hence, we argue that actors are perceived as influential because of two complementary factors: (a) their institutional roles and (b) their structural positions in the policy network. Based on temporal and cross-sectional exponential random graph models, we compare five cases about climate, telecommunications, flood prevention, and toxic chemicals politics in Switzerland and Germany. The five networks cover national and local networks at different stages of the policy cycle. The results confirm that institutional and structural drivers seem to have a crucial impact on how an actor is perceived in decision making and implementation and, therefore, their ability to significantly shape outputs and service delivery.

Major differences in organization and availability of health care and medicines for HIV/TB coinfected patients across Europe

OBJECTIVES The aim of the study was to investigate the organization and delivery of HIV and tuberculosis (TB) health care and to analyse potential differences between treatment centres in Eastern (EE) and Western Europe (WE). METHODS Thirty-eight European HIV and TB treatment centres participating in the TB:HIV study within EuroCoord completed a survey on health care management for coinfected patients in 2013 (EE: 17 respondents; WE:21; 76% of all TB:HIV centres). Descriptive statistics were obtained for regional comparisons. The reported data on health care strategies were compared with actual clinical practice at patient level via data derived from the TB:HIV study. RESULTS Respondent centres in EE comprised: Belarus (n = 3), Estonia (1), Georgia (1), Latvia (1), Lithuania (1), Poland (4), Romania (1), the Russian Federation (4) and Ukraine (1); those in WE comprised: Belgium (1), Denmark (1), France (1), Italy (7), Spain (2), Switzerland (1) and UK (8). Compared with WE, treatment of HIV and TB in EE are less often located at the same site (47% in EE versus 100% in WE; P < 0.001) and less often provided by the same doctors (41% versus 90%, respectively; P = 0.002), whereas regular screening of HIV-infected patients for TB (80% versus 40%, respectively; P = 0.037) and directly observed treatment (88% versus 20%, respectively; P < 0.001) were more common in EE. The reported availability of rifabutin and second- and third-line anti-TB drugs was lower, and opioid substitution therapy (OST) was available at fewer centres in EE compared with WE (53% versus 100%, respectively; P < 0.001). CONCLUSIONS Major differences exist between EE and WE in relation to the organization and delivery of health care for HIV/TB-coinfected patients and the availability of anti-TB drugs and OST. Significant discrepancies between reported and actual clinical practices were found in EE.

Co-authorship Networks in Swiss Political Research

Co-authorship is an important indicator of scientific collaboration. Co-authorship networks are composed of sub-communities, and researchers can gain visibility by connecting these insulated subgroups. This article presents a comprehensive co-authorship network analysis of Swiss political science. Three levels are addressed: disciplinary cohesion and structure at large, communities, and the integrative capacity of individual researchers. The results suggest that collaboration exists across geographical and language borders even though different regions focus on complementary publication strategies. The subfield of public policy and administration has the highest integrative capacity. Co-authorship is a function of several factors, most importantly being in the same subfield. At the individual level, the analysis identifies researchers who belong to the “inner circle” of Swiss political science and who link different communities. In contrast to previous research, the analysis is based on the full set of publications of all political researchers employed in Switzerland in 2013, including past publications.

Spatial proteomic and phospho-proteomic organization in three prototypical cell migration modes

BACKGROUND Tight spatio-temporal signaling of cytoskeletal and adhesion dynamics is required for localized membrane protrusion that drives directed cell migration. Different ensembles of proteins are therefore likely to get recruited and phosphorylated in membrane protrusions in response to specific cues. RESULTS HERE, WE USE AN ASSAY THAT ALLOWS TO BIOCHEMICALLY PURIFY EXTENDING PROTRUSIONS OF CELLS MIGRATING IN RESPONSE TO THREE PROTOTYPICAL RECEPTORS: integrins, recepor tyrosine kinases and G-coupled protein receptors. Using quantitative proteomics and phospho-proteomics approaches, we provide evidence for the existence of cue-specific, spatially distinct protein networks in the different cell migration modes. CONCLUSIONS The integrated analysis of the large-scale experimental data with protein information from databases allows us to understand some emergent properties of spatial regulation of signaling during cell migration. This provides the cell migration community with a large-scale view of the distribution of proteins and phospho-proteins regulating directed cell migration.

Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks

Localization is information of fundamental importance to carry out various tasks in the mobile robotic area. The exact degree of precision required in the localization depends on the nature of the task. The GPS provides global position estimation but is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras are commonly used for position estimation, but these require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of vision. Currently, Wireless Networks (WN) are widely available in indoor environments and can allow efficient global localization that requires relatively low computing resources. However, the inherent instability in the wireless signal prevents it from being used for very accurate position estimation. The growth in the number of Access Points (AP) increases the overlap signals areas and this could be a useful means of improving the precision of the localization. In this paper we evaluate the impact of the number of Access Points in mobile nodes localization using Artificial Neural Networks (ANN). We use three to eight APs as a source signal and show how the ANNs learn and generalize the data. Added to this, we evaluate the robustness of the ANNs and evaluate a heuristic to try to decrease the error in the localization. In order to validate our approach several ANNs topologies have been evaluated in experimental tests that were conducted with a mobile node in an indoor space.