Polarization in Online Social Networks: A Review of Mechanisms and Dimensions

The extensive use of social media has sparked a controversial debate regarding interactions on social media platforms and their influence on network polarization. Still, the complex phenomenon lacks conceptual clarity. Conducting a systematic literature review on existing empirical findings, we take first steps to a more systematic conceptualization of polarization by identifying (a) the dimensions on which polarization is manifesting and (b) relevant influence factors associated with the emergence of polarization phenomena in online social networks. Further, we derive an integrated theory-driven framework offering a comprehensive set of mechanisms associated with polarization on social media and its concrete manifestation. We identified Attitude Extremity, Topic Diversity, Social Fragmentation, and Language Usage as four dimensions of how polarization is manifesting. The framework is a relevant starting point to attain coherence in future research on polarization phenomena in IS research and contributes to a more systematic discussion of unintended consequences of ICT usage

A Social Network Approach for Investigating Social Influences on Effective Use: Demonstration in Virtual Reality Collaboration

Merely using new collaboration technologies does not necessarily result in the desired benefits, which is why it is important to understand what constitutes effective use behavior. In information systems research, the affordance network approach has been developed as a methodological approach to investigate effective use behavior. The approach has already been applied to understand the effective use of electronic medical record systems and fitness wearables; however, it neglects how social influences foster or hinder effective use behavior in collaborative settings. Therefore, we supplemented the affordance network approach for collaborative contexts by using social network methods. We demonstrate our approach based on two university courses in which students carried out group work within the collaborative VR application Spatial. Thereby, we contribute a methodological approach that enables researchers to identify influential users who encourage their team members to actualize affordances leading to goal achievement

Prefrontal gamma oscillations reflect ongoing pain intensity in chronic back pain patients

Chronic pain is a major health care issue characterized by ongoing pain and a variety of sensory, cognitive, and affective abnormalities. The neural basis of chronic pain is still not completely understood. Previous work has implicated prefrontal brain areas in chronic pain. Furthermore, prefrontal neuronal oscillations at gamma frequencies (60–90 Hz) have been shown to reflect the perceived intensity of longer lasting experimental pain in healthy human participants. In contrast, noxious stimulus intensity has been related to alpha (8–13 Hz) and beta (14–29 Hz) oscillations in sensorimotor areas. However, it is not fully understood how the intensity of ongoing pain as the key symptom of chronic pain is represented in the human brain. Here, we asked 31 chronic back pain patients to continuously rate their ongoing pain while simultaneously recording electroencephalography (EEG). Time–frequency analyses revealed a positive association between ongoing pain intensity and prefrontal beta and gamma oscillations. No association was found between pain and alpha or beta oscillations in sensorimotor areas. These findings indicate that ongoing pain as the key symptom of chronic pain is reflected by neuronal oscillations implicated in the subjective perception of longer lasting pain rather than by neuronal oscillations related to the processing of objective nociceptive input. The findings, thus, support a dissociation of pain intensity from nociceptive processing in chronic back pain patients. Furthermore, although possible confounds by muscle activity have to be taken into account, they might be useful for defining a neurophysiological marker of ongoing pain in the human brain

Brain dysfunction in chronic pain patients assessed by resting-state electroencephalography

Chronic pain is a common and severely disabling disease whose treatment is often unsatisfactory. Insights into the brain mechanisms of chronic pain promise to advance the understanding of the underlying pathophysiology and might help to develop disease markers and novel treatments. Here, we systematically exploited the potential of electroencephalography to determine abnormalities of brain function during the resting state in chronic pain. To this end, we performed state-of-the-art analyses of oscillatory brain activity, brain connectivity, and brain networks in 101 patients of either sex suffering from chronic pain. The results show that global and local measures of brain activity did not differ between chronic pain patients and a healthy control group. However, we observed significantly increased connectivity at theta (4-8 Hz) and gamma (>60 Hz) frequencies in frontal brain areas as well as global network reorganization at gamma frequencies in chronic pain patients. Furthermore, a machine learning algorithm could differentiate between patients and healthy controls with an above-chance accuracy of 57%, mostly based on frontal connectivity. These results suggest that increased theta and gamma synchrony in frontal brain areas are involved in the pathophysiology of chronic pain. Although substantial challenges concerning the reproducibility of the findings and the accuracy, specificity, and validity of potential electroencephalography-based disease markers remain to be overcome, our study indicates that abnormal frontal synchrony at theta and gamma frequencies might be promising targets for noninvasive brain stimulation and/or neurofeedback approaches

Assessing the effects of climate and land use changes on the distribution and growth of important plants species for pollinators

Pollination is a key ecosystem service vital to the preservation of wild plant communities and good agricultural behaviour. However, pollinators are rapidly declining in Europe, primarily as a result of human activity and climate change. Therefore, there is growing concern that observed declines in insect pollinators may impact on production and revenues from pollinator-dependent crops. In the forest, the presence of pollinators depends strongly on the openness of the canopy and the presence of wild plants that attract pollinators. The distribution of such plants is, therefore, crucial for estimating the pollinators presence. In general, however, there is incomplete knowledge of where those wild plants occur and how well they grow. To overcome this issue, we developed a species distribution model to predict the potential presence of important plant species for pollinators under present and future climatic conditions. The result of the distribution model is then refined using the dynamic vegetation model CARAIB. By combining the results of the distribution model and CARAIB, we can determine where the plants are located and calculate their net primary productivities.Multisectoral analysis of climate and land use change impacts on pollinators, plant diversity and crops yield

What future for pollinators in the understorey vegetation under the impact of climate change ?

editorial reviewed<p>Although understorey biomass is negligible in comparison to overstorey biomass, understorey vegetation supports the majority of biodiversity within forests. The diversity of  plant species in the understorey is important for pollinators, such as bees and butterflies, which use the available resources for food and shelter. However, the future of understorey vegetation is uncertain due to the impact of climate change and human activities.  Climate change and forest management are known to be among the most important factors affecting the diversity and abundance of understorey plant species. Most studies on understorey vegetation has often been limited in scope, either focusing on a small number of specific plant species or large-scale studies of plant functional types. In this study, we take a more comprehensive approach by combining the results of a species distribution model with a dynamic vegetation model to simulate the evolution of understorey vegetation at the species level. We select a set of 30 species important for pollinators. In order to cover a large climatic gradient, simulations are performed over the Walloon region in Belgium and the Eisenwurzen region in Austria. The climate dataset is provided by the regional climate model COSMO-CLM, which has a 3 km spatial resolution and covers the period from 1980 to 2070 under different greenhouse gas concentration scenarios (RCP 2.6 and RCP 8.5). Additionally, we investigate the effect of different forest management practices (thinning and clear-cutting) on overstorey and how they impact understorey vegetation. Overall, the study aims to provide new insights into the current and future state of understorey vegetation with a focus on the impact of climate change and forest management on key pollinator resources.</p&gt

Diskriminierungsprozesse und Teilhabeperspektiven. Herausforderungen für die Praxis der Inklusion. Ausgewählte Master-Thesen 2018-2022 des Masterstudiengangs "Soziale Inklusion: Gesundheit und Bildung" der Evangelischen Hochschule Rheinland-Westfalen-Lippe

Der hier vorliegende vierte Sammelband mit Zusammenfassungen überdurchschnittlich bewerteter Masterthesen setzt eine Tradition des seit 2010 existierenden Studiengangs „Soziale Inklusion: Gesundheit und Bildung“ (SIGB) fort. Seit der Publikation des ersten Sammelbandes 2014 hat sich dieses Format bewährt: es bedeutet für die Absolvent_innen des Studiengangs die Möglichkeit, die Ergebnisse ihrer Masterthesen fokussiert zusammenzufassen und ein „peer-review“ durch die Herausgeber_innen zu erfahren. Der vierte Band erschient nun erstmals bei KiDoks und versammelt thematisch Fragen von Diskriminierungsprozessen, Teilhabeförderung und Sexualpädagogik aus den Jahren 2018 bis 2022

Longitudinal prevalence and determinants of pain in multiple sclerosis: results from the German National Multiple Sclerosis Cohort study

Pain is frequent in multiple sclerosis (MS) and includes different types, with neuropathic pain (NP) being most closely related to MS pathology. However, prevalence estimates vary largely, and causal relationships between pain and biopsychosocial factors in MS are largely unknown. Longitudinal studies might help to clarify the prevalence and determinants of pain in MS. To this end, we analyzed data from 410 patients with newly diagnosed clinically isolated syndrome or relapsing-remitting MS participating in the prospective multicenter German National MS Cohort Study (NationMS) at baseline and after 4 years. Pain was assessed by self-report using the PainDETECT Questionnaire. Neuropsychiatric assessment included tests for fatigue, depression, and cognition. In addition, sociodemographic and clinical data were obtained. Prevalence of pain of any type was 40% and 36% at baseline and after 4 years, respectively, whereas prevalence of NP was 2% and 5%. Pain of any type and NP were both strongly linked to fatigue, depression, and disability. This link was even stronger after 4 years than at baseline. Moreover, changes in pain, depression, and fatigue were highly correlated without any of these symptoms preceding the others. Taken together, pain of any type seems to be much more frequent than NP in early nonprogressive MS. Moreover, the close relationship between pain, fatigue, and depression in MS should be considered for treatment decisions and future research on a possible common pathophysiology