Videobeobachtung zwischen Skepsis und Akzeptanz : soziodemografische Einflüsse auf die Einstellung zur polizeilichen Videobeobachtung im öffentlichen Raum

Manuskriptversio

Analyse der Entwicklung der Kriminalität von zugewanderten Personen in Schleswig-Holstein zwischen 2013 und 2019

ANALYSE DER ENTWICKLUNG DER KRIMINALITÄT VON ZUGEWANDERTEN PERSONEN IN SCHLESWIG-HOLSTEIN ZWISCHEN 2013 UND 2019 Analyse der Entwicklung der Kriminalität von zugewanderten Personen in Schleswig-Holstein zwischen 2013 und 2019 / Neumann, Merten (Rights reserved) ( -

Legalbewährung nach Entlassung aus dem offenen Vollzug: Eine Vergleichsstudie

Bisher mangelt es an kontrollierten Untersuchungen zum Effekt des offenen Vollzugs auf die Legalbewährung, da vorherige Studien unterschiedliche Gruppen von Inhaftierten miteinander verglichen. Um diesem Selektionseffekt entgegenzuwirken, wurden in der vorliegenden Studie mittels Matching-Verfahren vergleichbare Gruppen von Gefangenen gebildet. Mit Hilfe von Bundeszentralregisterdaten konnten die Rückfallquote, -geschwindigkeit und -schwere untersucht sowie individuelle Risiko- und Schutzfaktoren der Gefangenen kontrolliert werden. Die Ergebnisse zeigen, dass die Unterbringung im offenen Vollzug über die Positivauswahl von Gefangenen hinaus einen eigenständigen Effekt hat und das Risiko einer erneuten Inhaftierung signifikant reduziert.Until now, there has been a lack of research on the effect of being incarcerated in an open prison on legal probation. Previous studies have mostly compared quite different groups of prisoners. In order to counteract this selection bias, this study forms comparable groups of prisoners from the open and closed prison systems using matching procedures. Data from the Federal Central Criminal Register were used to examine the rates, speed and severity of recidivism, while individual risk and protection factors were statistically checked. The results show that incarceration in an open prison has an independent effect on legal probation - beyond the effect of positive selection of prisoners - and significantly reduces reincarceration

App-Based Coaching to Prevent Addictive Behaviors among Young Adults

Abstract: Background: Vocational students have an increased risk to engage in health-risk behaviors compared to same-aged peers. To date, evidence-based digital prevention approaches that address multiple health-risk behaviors are rare. Method: The randomized-controlled trial (RCT) “Prevention of at-risk substance and Internet use disorders among vocational students” (PARI) investigates the efficacy of an app-based prevention approach compared to a waitlist-control condition. The aim is to prevent substance-related and behavioral addictions and improve life skills. An existing app (ready4life) was adapted under consideration of focus groups with teachers, prevention experts, and students. A Delphi expert group rated the quality of the approach. The efficacy of the modified ready4life app is currently being tested in a RCT. The proactive recruitment takes place in German vocational schools. After participating in an app-based screening (T0), participants get individualized feedback and will be cluster-randomized per class to the intervention group (IG; n=1.250) or control group (CG; n=1.250). The IG chooses two out of six modules: Social competence, stress management, cannabis, tobacco, alcohol, social media/gaming. The CG receives information on how to improve health behaviors. Follow-ups are conducted after 6 months (T1) and 12 months (T2). Conclusion: This RCT provides data on a multibehavioral prevention approach for vocational students. Final results are expected in 2023

App-Based Addiction Prevention at German Vocational Schools: Implementation and Reach for a Cluster-Randomized Controlled Trial

This article examines the implementation, participation rates, and potential determinants of participation in the digital addiction prevention program “ready4life.” A two-arm cluster-randomized trial recruited German vocational students via class-based strategies. Intervention group received 16 weeks of in-app coaching; the control group received health behavior information, with coaching offered after 12 months. Potential determinants of participation were analyzed based on class and individual characteristics. Out of 525 contacted schools, 35 participated, enrolling 376 classes. Implementation during the pandemic required flexible adjustments, with 49.7% of introductions conducted in person, 43.1% digitally via online streaming, and 7.2% received a video link via email. Despite challenges, 72.3% of the vocational students downloaded the app, and 46.7% gave informed consent. Participation rates were highest among (associate) professionals, vocational grammar school classes, classes introduced by females, younger individuals, members of the project team, and classes introduced face-to-face. Female gender, lower social competencies, lifetime cannabis use, higher problematic internet use, and higher perceived stress were associated with higher individual participation. The study highlights the importance of proactive outreach and personalized interventions for addiction prevention programs in vocational schools. While reached students aligned with the aims of the app, tailored recruitment strategies could enhance engagement among under-represented groups

Lensing and x-ray mass estimates of clusters (simulations)

We present a comparison between weak-lensing and x-ray mass estimates of a sample of numerically simulated clusters. The sample consists of the 20 most massive objects at redshift z = 0.25 and M_vir > 5 × 10^(14) M_☉ h^(−1). They were found in a cosmological simulation of volume 1 h^(−3) Gpc^3, evolved in the framework of a WMAP-7 normalized cosmology. Each cluster has been resimulated at higher resolution and with more complex gas physics. We processed it through Skylens and X-MAS to generate optical and x-ray mock observations along three orthogonal projections. The final sample consists of 60 cluster realizations. The optical simulations include lensing effects on background sources. Standard observational tools and methods of analysis are used to recover the mass profiles of each cluster projection from the mock catalogue. The resulting mass profiles from lensing and x-ray are individually compared to the input mass distributions. Given the size of our sample, we could also investigate the dependence of the results on cluster morphology, environment, temperature inhomogeneity and mass. We confirm previous results showing that lensing masses obtained from the fit of the cluster tangential shear profiles with Navarro–Frenk–White functionals are biased low by ~5–10% with a large scatter (~10–25%). We show that scatter could be reduced by optimally selecting clusters either having regular morphology or living in substructure-poor environment. The x-ray masses are biased low by a large amount (~25–35%), evidencing the presence of both non-thermal sources of pressure in the intra-cluster medium (ICM) and temperature inhomogeneity, but they show a significantly lower scatter than weak-lensing-derived masses. The x-ray mass bias grows from the inner to the outer regions of the clusters. We find that both biases are weakly correlated with the third-order power ratio, while a stronger correlation exists with the centroid shift. Finally, the x-ray bias is strongly connected with temperature inhomogeneities. Comparison with a previous analysis of simulations leads to the conclusion that the values of x-ray mass bias from simulations are still uncertain, showing dependences on the ICM physical treatment and, possibly, on the hydrodynamical scheme adopted

Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their simulation, analysis, and data resources. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.Comment: 60 pages, 14 figures; comments welcom