evidence for a moderator effect

Background: While ethnic discrimination emphasizes boundaries between different cultures, the concept of transculturality focuses on the fact that cultures can merge and that individuals integrate novel cultural elements into their identity. This is an exploratory study that investigates the interplay between perceived ethnic discrimination, psychological adjustment and transcultural identity. Methods: Structured interviews were conducted using a sample of 46 adolescents with a Turkish migratory background and 45 adolescents who were native born Germans. Results: Correlational and multiple regression analyses revealed that perceived discrimination was clearly associated with a poorer psychological adjustment among adolescents with a migratory background. Transcultural identity moderated this relationship. That is, adolescents who showed higher levels of transcultural identity displayed a better psychological adjustment when compared to adolescents who showed lower levels of transcultural identity—provided that they did not feel discriminated against. This is congruent with the idea that transcultural identity can involve considerable benefits for personality. However, when adolescents perceived higher rates of discrimination, higher levels of transcultural identity came attached to a poorer psychological adjustment. Conclusions: The findings suggest that perceived discrimination has negative effects on the well-being of immigrant adolescents—particularly for those who describe their identity as transcultural. The findings are discussed considering specific characteristics of transcultural identity, and how they stand in opposition to discrimination

Magnetism and magnetotransport in sputtered Co-doped FeSi films

FeSi is a non-magnetic narrow-gap semiconductor that can be doped n-type by Co, which also gives rise to magnetic order. Here we report on the growth of sputtered thin films of Fe 0.8 Co 0.2 Si, which are predominantlyphase (B20 lattice structure), and possess that phase's characteristic magnetotransport properties. The ordinary Hall coefficient shows that each Co atom donates roughly one electron, whilst the magnetometry suggests that each gives rise to close to one Bohr magneton of moment. These results indicate that a highly spinpolarised electron gas persists despite the inevitable disorder in these thin films, suitable for spintronic devices

Periodicity staircase in a Fe/Gd magnetic thin film

Presence of multiple competing periodicities may result in a system to go through states with modulated periodicities, an example of which is the self-similar staircase-like structure called the Devil's staircase. Herein we report on a novel staircase structure of domain periodicity in an amorphous and achiral Fe/Gd magnetic thin film wherein the reciprocal space wavevector \textbf{Q} due to the ordered stripe domains does not evolve continuously, rather exhibits a staircase structure. Resonant X-ray scattering experiments show jumps in the periodicity of the stripe domains as a function of an external magnetic field. When resolved in components, the step change along Q$_x$ was found to be an integral multiple of a minimum step height of 7 nm, which resembles closely to the exchange length of the system. Modeling the magnetic texture in the Fe/Gd thin film as an achiral spin arrangement, we have been able to reproduce the steps in the magnetization using a Landau-Lifshitz spin dynamics calculation. Our results indicate that anisotropy and not the dipolar interaction is the dominant cause for the staircase pattern, thereby revealing the effect of achiral magnetism.Comment: 9 pages, 5 figure

Antiferromagnetic real-space configuration probed by x-ray orbital angular momentum phase dichroism

X-ray beams with orbital angular momentum (OAM) are an up-and-coming tool for x-ray characterization techniques. Beams with OAM have an azimuthally varying phase that leads to a gradient of the light field. New material properties can be probed by utilizing the unique phase structure of an OAM beam. Here, we demonstrate a novel type of phase dichroism in resonant diffraction from an artificial antiferromagnet with a topological defect. The scattered OAM beam has circular dichroism whose sign is coupled to the phase of the beam, which reveals the real-space configuration of the antiferromagnetic ground state. Thermal cycling of the artificial antiferromagnet can change the ground state, as indicated by the changing phase dichroism. These results exemplify the potential of OAM beams to probe matter in a way that is inaccessible using typical x-ray techniques

Relational resolutions: digital encounters in ethnographic fieldwork

The articles in this special issue highlight the relationality existing between researchers, participants, cameras and images, with each article bringing complementary perspectives on the use of digital images in ethnographic fieldwork. These include reactivating archives through their digitization for visual repatriation, facilitating dialogue and understanding between participant and researcher, analysing the relation between participants and the virtual spaces of their self-representations and exploring the range of capacities for new research methodologies afforded by digital technologies. Individually and through their juxtaposition, the articles highlight the complexity of the interactions between researchers and participants in their digital encounters and open dialogical spaces, in ethnographic fieldwork and in visual anthropology, about access, participation and transparency in representational practices

A randomized controlled trial on the effectiveness of strength training on clinical and muscle cellular outcomes in patients with prostate cancer during androgen deprivation therapy: rationale and design

Background Studies indicate that strength training has beneficial effects on clinical health outcomes in prostate cancer patients during androgen deprivation therapy. However, randomized controlled trials are needed to scientifically determine the effectiveness of strength training on the muscle cell level. Furthermore, close examination of the feasibility of a high-load strength training program is warranted. The Physical Exercise and Prostate Cancer (PEPC) trial is designed to determine the effectiveness of strength training on clinical and muscle cellular outcomes in non-metastatic prostate cancer patients after high-dose radiotherapy and during ongoing androgen deprivation therapy. Methods/design Patients receiving androgen deprivation therapy for 9-36 months combined with external high-dose radiotherapy for locally advanced prostate cancer are randomized to an exercise intervention group that receives a 16 week high-load strength training program or a control group that is encouraged to maintain their habitual activity level. In both arms, androgen deprivation therapy is continued until the end of the intervention period. Clinical outcomes are body composition (lean body mass, bone mineral density and fat mass) measured by Dual-energy X-ray Absorptiometry, serological outcomes, physical functioning (muscle strength and cardio-respiratory fitness) assessed with physical tests and psycho-social functioning (mental health, fatigue and health-related quality of life) assessed by questionnaires. Muscle cellular outcomes are a) muscle fiber size b) regulators of muscle fiber size (number of myonuclei per muscle fiber, number of satellite cells per muscle fiber, number of satellite cells and myonuclei positive for androgen receptors and proteins involved in muscle protein degradation and muscle hypertrophy) and c) regulators of muscle fiber function such as proteins involved in cellular stress and mitochondrial function. Muscle cellular outcomes are measured on muscle cross sections and muscle homogenate from muscle biopsies obtained from muscle vastus lateralis. Discussion The findings from the PEPC trial will provide new knowledge on the effects of high-load strength training on clinical and muscle cellular outcomes in prostate cancer patients during androgen deprivation therapy. Trial registration ClinicalTrials.gov: NCT0065822

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages