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The effects of N2 and O2:N2 (1:1) as ambient gases during activation annealing of Mg as p-type doping of GaN have been investigated. The purpose was to understand the mechanisms involved and especially the impact of O2 on the resulting hole concentration and hole mobility. The addition of O2 to the ambient gas during annealing is known to be very effective in reducing the H level of the Mg-doped GaN layer, but the maximum achievable hole concentration and mobility, as determined by Hall characterization, is still higher with pure N2. The difference is explained by an in-diffusion of O to the GaN layer acting as n-dopant and thus giving rise to a compensation effect.It is found that to a large degree only the Mg-H complexes at substitutional (MgGa), i.e., the electrically active acceptor sites that provide free holes, are activated by annealing with N2 only as ambient gas, while annealing with O2:N2 (1:1) also dissociates electrically inactive Mg-H complexes resulting in much less residual H. Thus, the residual H level in relation to the Mg level after activation annealing with N2 only may provide a representative measure of the resulting free hole concentration of the Mg-doped GaN layer.

The EIT Climate-KIC SATURN project deals with rural-urban territories, their landscapes and environmental challenges. The land of our cities and regions is fragmented and prone to several challenges in terms of ecology, governance and social coherence. As a result of unregulated overlapping of different land uses and complex governance patterns, landscape fragmentation creates severe challenges in the ways the land is perceived, identified and therefore managed. The SATURN consortium is working on different models to help address the governance and decision-making process and support on a policy level by applying holistic ideas of visioning and stakeholder engagement at a city scale. The diversity of the three hubs (Birmingham in central England, Gothenburg in western Sweden, and Trentino in northern Italy) is reflected by their approaches to stakeholders’ engagement and visioning processes as well as especially adopted activities in each location. Within the SATURN project, we are investigating how these approaches could change perceptions and impact on landscape strategic actions. Through a series of especially designed workshops on landscape visioning and stakeholder engagement, the project aims to create a toolbox supporting urban, peri-urban and regional planning. This paper reports on the visioning and stakeholder mapping and analysis tools, and shares examples where these processes were tested during the broader SATURN scheme. Results demonstrate how the visioning exercise has changed public perceptions about an area and how this has affected the decision-making process of each city towards a more effective planning of sustainable landscapes. The stakeholder engagement activity demonstrates the importance of “mapping and analysis” of the various actors involved in a city and the ways a landscape project can effectively engage with them and seek further collaboration. Questions on how the results differ in cases where the stakeholder engagement process focused on a broad policy level or targeted specific actions for a certain region are being explored. Both the visioning and stakeholder engagement tools are subject to a holistic approach and a collaborative and open process between the stakeholders and the trainers, allowing the participants to build a vision for their regions and be one-step closer to systemic change.

I Sociologisk Forskning har undervisning och lärande tidigare diskuterats på flera sätt. Ämnet har bland annat behandlats i forskningsartiklar som undersökt skolbarns välbefinnande och utbildningsresultat (Aytar & Mella 2012), hinder för tillgång till högre utbildning (Ismail 2011), professionsutmaningar inom gymnasieutbildningen (Bruno 2012) och strukturella bestämningsfaktorer för akademiska karriärer (Behtoui 2017). Den sociologiska forskningspraktikens nära koppling till ämnets pedagogiska praktik har också medfört att personliga undervisningserfarenheter behandlats i olika texter (se specialnumret ”Sociologi i tiden”: Hansen, Johansson, Kollind m.fl. 1997). Tidskriftens redaktion skulle framöver gärna se fler artiklar som behandlar frågor om undervisning och lärande inom sociologiämnet. Vi välkomnar därför sociologikollegor att inkomma med förslag till sådana artiklar eller färdiga manus. Det skulle kunna vara texter om hur vår praktik som sociologer påverkar vårt sätt att undervisa, hur sociologisk forskning omsätts i undervisning, hur olika pedagogiska metoder och material kan användas i sociologiundervisningen eller hur samhälleliga processer och strukturer påverkar vad som händer i klassrummet. Vi tror att sådana reflektioner med fördel skulle kunna ta sin utgångspunkt i utbildningssociologi och den svenska sociologins reflekterande tradition. Som ett första steg mot att ge utrymme åt denna typ av artiklar publicerar vi i detta nummer ett samtal om hur undervisningen i sociologi har påverkats av övergången till digital undervisning under covid-19-pandemin. Vi bad fyra sociologikollegor, verksamma vid olika svenska lärosäten, att svara på några frågor utifrån sina erfarenheter som lärare, utbildningssamordnare och forskare. De medverkande är Martin Berg, professor i medieteknik och docent i sociologi vid Malmö universitet, som forskar om digital sociologi med särskilt fokus på kritiska studier av algoritmer och automatiseringsprocesser; Ida Lidegran, docent i utbildningssociologi vid Uppsala universitet, som ingår i Forskningsgruppen för utbildnings- och kultursociologi (SEC) och forskar om elitutbildningar och familjers utbildningsstrategier, migranters möte med det svenska utbildningssystemet samt utbildning och covid-19; Ulrika Schmauch, lektor i sociologi vid Umeå universitet, vars forskning handlar om social ojämlikhet i allmänhet och om ras, plats och kön i synnerhet; samt Glenn Sjöstrand, prefekt för Institutionen för samhällsstudier vid Linnéuniversitetet i Växjö, vars forskning i huvudsak är inriktad mot professionsstudier och särskilt ingenjörers professionella utveckling, men som även forskar om digital transformation, miljö och välfärdsfrågor.

Abstract We present a case with a phototoxic reaction following topical use of NSAID. The phototoxic reaction was initially mistaken for cellulitis which led to treatment with dicloxacillin, which led to an exanthematous drug eruption. The patient was treated with topical clobetasol propionate and oral non‐sedating antihistamines. Follow‐up revealed post‐inflammatory hypopigmentation.

Abstract Introduction The 1-year PROspective sarilumab (preFILled syringe/pen) multinational, obsErvational (PROFILE) study evaluated the real-world effectiveness and safety of sarilumab in patients with moderate-to-severe rheumatoid arthritis (RA). Methods Safety endpoints included adverse events (AEs) and lab abnormalities. Effectiveness endpoints included the ACR core set. The primary endpoint was the change from baseline in Clinical Disease Activity Index (CDAI). All statistics are descriptive and p values were nominal. Results In total, 595 patients were treated, of whom 223 (37.5%) received sarilumab monotherapy and 372 (62.5%) received combination therapy. Upon initiation of sarilumab, an improvement in the mean (SD) CDAI score was observed at week 24 [11.4 (10.3)] and was maintained through week 52 [10.0 (10.5)], resulting in a mean [SD] reduction of −14.9 (12.7) and −14.4 (12.9), respectively. There were consistent improvements in disease activity that were similar for patients on monotherapy vs. combination therapy. An increase in the proportion of patients achieving remission and low disease activity was reported. By week 52, both groups had improved physical function and quality of life. There were no new safety signals. The proportions of any patients reporting a treatment-emergent adverse event (TEAE) or serious treatment-emergent AE (SAE) was 66.2% and 5.9%, respectively, and were similar between both treatment groups. Overall, 15.6% of patients discontinued sarilumab treatment due to TEAEs. The most commonly reported TEAE of interest was neutropenia (14.1%). Conclusions In this 1-year, observational real-world study, sarilumab therapy resulted in improved clinical outcomes. The safety profile was consistent with that observed in sarilumab randomized clinical trials. This study was entered on the German website (Paul Ehrlich Institute) on January 11, 2018, with NIS No.: 423.

Abstract Background Magnetic resonance imaging (MRI) followed by targeted biopsy (TBx) is utilized for prostate cancer (PCa) detection. However, the value of adding systematic biopsies (SBx) to targeted biopsy procedures (combined biopsy; CBx) in men with suspicious MRI findings has not been determined. Methods We analysed biopsy outcomes in 429 men with MRI lesions in the prospective multicenter STHLM3MRI pilot study, planned for prostate biopsy. Participants underwent 1.5T biparametric MRI without contrast enhancement, reported according to the PI-RADS v2, and with TBx plus SBx if the MRI lesion score was ≥ 3. The endpoints were clinically nonsignificant (nsPCa) and clinically significant PCa (csPCa), defined as ISUP grade groups 1 and ≥ 2, respectively. Results The median age was 65 years (59–70), and the median PSA 6.0 ng/ml (4.1–9.0). The detection rates of csPCa when using TBx or SBx combined were 18%, 46%, and 85% in men with PIRADS scores of 3 (n = 195), 4 (n = 121), and 5 (n = 113), respectively. This combined strategy detected csPCa in more men than TBx alone (43.6% vs 39.2%, p

Abstract Blood clot formation, a crucial process in hemostasis and thrombosis, has garnered substantial attention for its implications in various medical conditions. Microscopic examination of blood clots provides vital insights into their composition and structure, aiding in the understanding of clot pathophysiology and the development of targeted therapeutic strategies. This study explores the use of topological data analysis (TDA) to assess plasma clot characteristics microscopically, focusing on the identification of the elements components, holes and Wasserstein distances. This approach should enable researchers to objectively classify fibrin networks based on their topologic architecture. We tested this mathematical characterization approach on plasma clots formed in static conditions from porcine and human citrated plasma samples, where the effect of dilution and direct thrombin inhibition was explored. Confocal microscopy images showing fluorescence labeled fibrin networks were analyzed. Both treatments resulted in visual differences in plasma clot architecture, which could be quantified using TDA. Significant differences between baseline and diluted samples, as well as blood anticoagulated with argatroban, were detected mathematically. Therefore, TDA could be indicative of clots with compromised stability, providing a valuable tool for thrombosis risk assessment. In conclusion, microscopic examination of plasma clots, coupled with Topological Data Analysis, offers a promising avenue for comprehensive characterization of clot microstructure. This method could contribute to a deeper understanding of clot pathophysiology and thereby refine our ability to assess clot characteristics.

Background: The Capio Prostate Cancer Center (Capio PCC) in Stockholm, Sweden, adopts a comprehensive diagnostic approach, utilizing prostate-specific antigen (PSA), Stockholm3, and magnetic resonance imaging (MRI) for prostate cancer risk assessment, followed by targeted and systematic biopsies for high-risk cases. Objective: This study aims to elucidate the clinical process and real-world outcomes of the Capio PCC model for prostate cancer diagnosis at Capio S:t Göran Hospital. Design, setting, and participants: Between 2018 and 2022, a cohort of 12 406 men aged 45–75 yr underwent prostate cancer testing, adhering to Capio PCC's structured diagnostic protocol. Outcome measurements and statistical analysis: We provide a comprehensive description of the Capio PCC model and present results from its implementation, including assessments of PSA, Stockholm3, MRI scans, and biopsies. A comparative analysis is conducted between the diagnostic outcomes obtained at Capio PCC and those obtained at other regions in Sweden. Results and limitations: The median participant age was 61 yr (interquartile range [IQR]: 55–67), with PSA levels at 1.6 ng/ml (IQR: 0.8–3.3) and Stockholm3 scores at 4 (IQR: 3–11). Among 1064 men (8.6%) undergoing biopsies, 611 (57% of biopsied) were diagnosed with International Society of Urological Pathology grade ≥ 2 cancer. Notably, employing a Stockholm3 ≥ 15 cutoff for biopsy, in lieu of PSA ≥ 3 ng/ml, reduced biopsy recommendations by 43%. For men with PSA levels between 1.5 and 2.9 ng/ml, 360 (12%) exhibited Stockholm3 scores of ≥ 15, with 72 (56% of biopsied) diagnosed with clinically significant prostate cancer. A comparative analysis with national Swedish prostate cancer detection data indicated that the Capio PCC model (vs Sweden) revealed a distribution of 14% (vs 25%) low-risk, 59% (vs 42%) intermediate-risk, and 26% (vs 30%) high-risk and advanced cancers. Conclusions: This study underscores the effectiveness of the protocol-driven diagnostic process at Capio PCC, enabling earlier detection of intermediate-risk prostate cancer and reducing the need for MRI assessments compared with standard prostate cancer care in Sweden. Patient summary: At the Capio Prostate Cancer Center, a novel diagnostic approach incorporating prostate-specific antigen, Stockholm3, magnetic resonance imaging, and targeted biopsies has been implemented to enhance prostate cancer testing and diagnosis in Stockholm, Sweden.

The efficient processing of information plays a critical role in data-driven domains. Data acquisition pipelines, which act as the interface between data collection and subsequent processing, are central to this. Traditional software engineering methods form the foundation for the development of robust data acquisition pipelines, but agent-based systems hold great potential for realizing such pipelines, and this study presents an innovative architecture that uses agent-based components. This modular approach makes it possible to use specialized agents for individual tasks and to increase the effectiveness of the pipelines. The applicability and effectiveness of this architecture are demonstrated using a system for autonomous driving that collects and processes data from edge computers along roads. Our results are on GitHub (https://github.com/BenjaminAcar/Agent-based-Data-Acquisition-Pipeline).

Abstract Using material distribution-based topology optimization, we optimize the bandpass design of a loudspeaker cabinet targeting low frequencies. The objective is to maximize the loudspeaker’s output power for a single frequency as well as a range of frequencies. To model the loudspeaker’s performance, we combine a linear electromechanical transducer model with a computationally efficient hybrid 2D–3D model for sound propagation. The adjoint variable approach computes the gradients of the objective function with respect to the design variables, and the Method of Moving Asymptotes (MMA) solves the topology optimization problem. To manage intermediate values of the material indicator function, a quadratic penalty is added to the objective function, and a non-linear filter is used to obtain a mesh independent design. By carefully selecting the target frequency range, we can guide the optimization algorithm to successfully generate a loudspeaker design with the required bandpass character. To the best of our knowledge, this study constitutes the first successful attempt to design the interior structure of a loudspeaker cabinet using topology optimization.

Abstract Improving the quantum coherence of solid-state systems is a decisive factor in realizing solid-state quantum technologies. The key to optimize quantum coherence lies in reducing the detrimental influence of noise sources such as spin noise and charge noise. Here we demonstrate that we can utilize highly-excited Rydberg excitons to neutralize charged impurities in the semiconductor Cuprous Oxide - an effect we call purification. Purification reduces detrimental electrical stray fields drastically. We observe that the absorption of the purified crystal increases by up to 25% and that the purification effect is long-lived and may persist for hundreds of microseconds or even longer. We investigate the interaction between Rydberg excitons and impurities and find that it is long-ranged and based on charge-induced dipole interactions. Using a time-resolved pump-probe technique, we can discriminate purification from Rydberg blockade, which has been a long-standing goal in excitonic Rydberg systems.

Abstract Autologous Chimeric antigen receptor (CAR‐T) cell therapy has been highly successful in the treatment of aggressive hematological malignancies and is also being evaluated for the treatment of solid tumors as well as other therapeutic areas. A challenge, however, is that up to 60% of patients do not sustain a long‐term response. Low CAR‐T cell exposure has been suggested as an underlying factor for a poor prognosis. CAR‐T cell therapy is a novel therapeutic modality with unique kinetic and dynamic properties. Importantly, “clear” dose‐exposure relationships do not seem to exist for any of the currently approved CAR‐T cell products. In other words, dose increases have not led to a commensurate increase in the measurable in vivo frequency of transferred CAR‐T cells. Therefore, alternative approaches beyond dose titration are needed to optimize CAR‐T cell exposure. In this paper, we provide examples of actionable variables – design elements in CAR‐T cell discovery, development, and clinical practice, which can be modified to optimize autologous CAR‐T cell exposure. Most of these actionable variables can be assessed throughout the various stages of discovery and development as part of a well‐informed research and development program. Model‐informed drug development approaches can enable such study and program design choices from discovery through to clinical practice and can be an important contributor to cell therapy effectiveness and efficiency.

Peripheral myelin protein 2 (P2) is a fatty acid‐binding protein expressed in vertebrate peripheral nervous system myelin, as well as in human astrocytes. Suggested functions of P2 include membrane stacking and lipid transport. Mutations in the PMP2 gene, encoding P2, are associated with Charcot–Marie–Tooth disease (CMT). Recent studies have revealed three novel PMP2 mutations in CMT patients. To shed light on the structure and function of these P2 variants, we used X‐ray and neutron crystallography, small‐angle X‐ray scattering, circular dichroism spectroscopy, computer simulations and lipid binding assays. The crystal and solution structures of the I50del, M114T and V115A variants of P2 showed minor differences to the wild‐type protein, whereas their thermal stability was reduced. Vesicle aggregation assays revealed no change in membrane stacking characteristics, while the variants showed altered fatty acid binding. Time‐lapse imaging of lipid bilayers indicated formation of double‐membrane structures induced by P2, which could be related to its function in stacking of two myelin membrane surfaces in vivo. In order to better understand the links between structure, dynamics and function, the crystal structure of perdeuterated P2 was refined from room temperature data using neutrons and X‐rays, and the results were compared to simulations and cryocooled crystal structures. Our data indicate similar properties for all known human P2 CMT variants; while crystal structures are nearly identical, thermal stability and function of CMT variants are impaired. Our data provide new insights into the structure–function relationships and dynamics of P2 in health and disease. [ABSTRACT FROM AUTHOR]

A regular unranked tree folding consists of a regular unranked tree language and a folding operation that merges (i.e., folds) selected nodes of a tree to form a graph; the combination is a formal device for representing graph languages. If, in the process of folding, the order among edges is discarded so that the result is an unordered graph, then two applications of a fold operation are enough to make the associated parsing problem NP-complete. However, if the order is kept, then the problem is solvable in non-uniform polynomial time. In this paper, we address the remaining case, where only one fold operation is applied, but the order among the edges is discarded. We show that, under these conditions, the problem is solvable in non-uniform polynomial time.

In the traditions of thought of the Latin American lefts, elaborations on the forms of right-wing movements are not abundant. José Carlos Mariátegui constitutes one of the few exceptions in this general panorama. This essay, which deals with his approaches to Italian Fascism, is divided into two sections. First, three dimensions of analysis of Mariátegui's essays on the emerging right in post-war Europe stand out, particularly in the texts gathered in his “Biology of Fascism”. These three dimensions, it is argued, outlined problems that were later elaborated by authors who became references in contemporary historiography on fascism (this exercise does not think of Mariátegui in terms of the “antecedent” of this historiography, but simply seeks to highlight some of his intuitions). Secondly, it is postulated that Mariátegui made a non-prejudiced reading of fascism, which sought to understand it in its own logic and paying attention to its innovations. Despite placing fascism as a counterrevolutionary movement that was located in the enemy camp of socialism and the international proletariat, Mariátegui extracted elements that were in harmony with the cultural climate of the time and that could be readapted in a socialist project. Fascism was, ultimately, a practical laboratory that complemented his readings of Georges Sorel (in some cases anticipating them) for the elaboration of the theme of myth, a key factor in his political philosophy.

BackgroundCOVID-19 infection and its associated consequence, known as long-COVID, lead to a significant burden on the global healthcare system and limitations in people's personal and work lives. This study aims to provide further insight into the impact of acute and ongoing COVID-19 symptoms and investigates the role of patients' gender and vaccination status.Methods416 individuals (73.9% female) between the ages of 16 and 80 years (M = 44.18, SD = 12.90) with self-reported symptoms of long-COVID participated in an online survey conducted between March and May 2022.Results6.0%, 74.3%, and 19.7% of all respondents reported having had an asymptomatic, mild, or severe acute illness, respectively. Out of all participants, 7.8% required hospitalization. The most prevalent symptoms during the acute infection (Mdn = 23.50 symptoms, IQR = 13-39) included fatigue, exhaustion, cough, brain fog, and memory problems. The median long-COVID disease duration was 12.10 months (IQR = 2.8-17.4). Among 64 inquired long-COVID symptoms (Mdn = 17.00 symptoms, IQR = 9-27), participants reported fatigue, exhaustion, memory problems, brain fog, and dyspnea as the most common ongoing symptoms, which were generally experienced as fluctuating and deteriorating after physical or cognitive activity. Common consequences of long-COVID included financial losses (40.5%), changes in the participants' profession (41.0%), stress resistance (87.5%), sexual life (38.1%), and mood (72.1%), as well as breathing difficulties (41.3%), or an increased drug intake (e.g., medicine, alcohol; 44.6%). In addition, vaccinated individuals exhibited a shorter acute illness duration and an earlier onset of long-COVID symptoms. In general, women reported more long-COVID symptoms than men.ConclusionLong-COVID represents a heterogeneous disease and impacts multiple life aspects of those affected. Tailored rehabilitation programs targeting the plurality of physical and mental symptoms are needed.

IntroductionYouth placed in out-of-home care is a large and highly vulnerable group at high risk of negative developmental outcomes. Given the size and extent of negative developmental outcomes for youth placed in out-of-home care, interventions to help this vulnerable group navigate successfully towards independent living and promote wellbeing across a spectrum of outcome areas are needed. To date, there is a lack of such interventions, particularly in Sweden. Importing interventions from other societies and cultures is associated with difficulties. The aim of the research project is to implement, test, and evaluate interventions that have been recently developed in Swedish practice to close this gap.MethodsThe project has an ambitious and complex data collection and analysis strategy using qualitative, quantitative, and multiple information methods (hybrid effectiveness-implementation study) over the course of two years. Both the implementation and effectiveness of the interventions will be evaluated. The recently developed My Choice-My Way! leaving care program for youth aged 15+ will be the primary focus of the project and will be compared to usual services.ConclusionsThe project has the potential to offer novel insights into how society can promote wellbeing across a spectrum of outcome areas for the high-risk group of youth transitioning from out-of-home care to independent living. As such, the project will have important implications for both research and practice.Trial registrationClinicalTrials.gov Identifier: NCT05813197.

40 años de Comunidades Imaginadas. Vidas y sobrevidas de un clásico

The concentration of colored dissolved organic matter (CDOM) in lakes is strongly influenced by climate, land cover, and topographic settings, but it is not known how drought may affect the relative importance of these controls. Here, we evaluate the controls of CDOM during two summers with strongly contrasting values of the Palmer drought index (PDI), indicating wet vs. dry conditions. We hypothesized that lake CDOM during a wet summer season is regulated mainly by the surrounding land cover to which the lakes are hydrologically connected, while, during drought, the lakes are disconnected from the catchment and CDOM is regulated by climatic and morphometric factors that govern the internal turnover of CDOM in the lakes. A suite of climate, land cover, and morphometric variables was assembled and used to explain remotely sensed CDOM values for 255 boreal lakes distributed across broad environmental and geographic gradients in Sweden and Norway. We found that PDI explained the variability in CDOM among lakes in a dry year, but not in a wet year, and that severe drought strongly decreased CDOM during the dry year. Large lakes, especially, with a presumed high degree of catchment uncoupling, showed low CDOM during the dry year. However, in disagreement with our hypothesis, climate, land cover, and morphometry all showed a stronger impact on lake CDOM in wet vs. dry years. Thus, drought systematically weakened the predictability of CDOM variations at the same time as CDOM was offset toward lower values. Our results show that drought not only has a direct effect on CDOM, but also acts indirectly by changing the spatial regulation of CDOM in boreal lakes.

BackgroundEarly conduct problems and school failure are prominent risk factors for several adverse outcomes in later life. With the potential of reaching many children at early stages of their life, school-based interventions constitute a valuable approach to universal prevention. Good behavior game (GBG) is a promising school-based behavior management program, having shown immediate reductions in conduct problems along with several long-term positive effects. Adapting interventions to new contexts may however affect their effectiveness. The current study aims to evaluate the effectiveness of a Swedish adaption of GBG under pragmatic conditions. The intervention is hypothesized to reduce conduct problems in the classroom (primary outcome). Secondary analyses will investigate changes in conduct problems in common school areas, classroom climate, teacher collective efficacy, on-task behavior, as well as investigating behavioral management practices, implementation, and barriers to implementation.MethodsThis is a cluster-randomized trial with two parallel groups. Schools will be randomized (1,1, stratified by their areas sociodemographic index score) to be provided training in GBG or perform business-as-usual. The intervention and data collection lasts for a school year. Data will be collected at three time points: at baseline in the beginning of the school year (prior to training in GBG), after three months, and after nine months (at the end of the school year; primary endpoint). Data consists of teacher-rated measures of conduct problems, classroom climate, teacher collective efficacy, behavior management practices, and implementation factors, along with demographic factors. In addition, data will be collected by independent and blinded observers using corresponding measures in a subset of randomly chosen classrooms. Procedural fidelity will be rated and collected by GBG-trainers during nine observations throughout the school year. Statistical analysis will include frequentist intention-to-treat analysis, and comparisons of estimates with a corresponding Bayesian model using weakly informative priors. The study has currently completed data collection.DiscussionThis study will provide knowledge in universal prevention and school-based interventions with high reach, as well as specific knowledge concerning the effectiveness of an adapted version of GBG under real-world conditions, along with factors affecting its implementation and effects.Clinical trial registrationClinicalTrials.gov, identifier NCT05794893.

A new formulation is presented that extends the material distribution topology optimization method to address boundary-effect-dominated problems, where specific boundary conditions need to be imposed at solid–fluid interfaces. As an example of such a problem, we focus on the design of acoustic structures with significant viscous and thermal boundary losses. In various acoustic applications, especially for acoustically small devices, the main portion of viscothermal dissipation occurs in the so-called acoustic boundary layer. One way of accounting for these losses is through a generalized acoustic impedance boundary condition. This boundary condition has previously been proven to provide accurate results with significantly less computational effort compared to Navier–Stokes simulations. To incorporate this boundary condition into the optimization process at the solid–fluid interface, we introduce a mapping of jumps in densities between neighboring elements to an edge-based boundary indicator function. Two axisymmetric case studies demonstrate the effectiveness of the proposed design optimization method. In the first case, we enhance the absorption performance of a Helmholtz resonator in a narrow range of frequencies. In the second case, we consider an acoustically larger problem and achieve an almost-perfect broadband absorption. Our findings underscore the potential of our approach for the design optimization of boundary-effect-dominated problems.

Summary: Climate change is one of several drivers of recurrent outbreaks and geographical range expansion of infectious diseases in Europe. We propose a framework for the co-production of policy-relevant indicators and decision-support tools that track past, present, and future climate-induced disease risks across hazard, exposure, and vulnerability domains at the animal, human, and environmental interface. This entails the co-development of early warning and response systems and tools to assess the costs and benefits of climate change adaptation and mitigation measures across sectors, to increase health system resilience at regional and local levels and reveal novel policy entry points and opportunities. Our approach involves multi-level engagement, innovative methodologies, and novel data streams. We take advantage of intelligence generated locally and empirically to quantify effects in areas experiencing rapid urban transformation and heterogeneous climate-induced disease threats. Our goal is to reduce the knowledge-to-action gap by developing an integrated One Health—Climate Risk framework.

Abstract Background Machine learning (ML) algorithms have been trained to early predict critical in-hospital events from COVID-19 using patient data at admission, but little is known on how their performance compares with each other and/or with statistical logistic regression (LR). This prospective multicentre cohort study compares the performance of a LR and five ML models on the contribution of influencing predictors and predictor-to-event relationships on prediction model´s performance. Methods We used 25 baseline variables of 490 COVID-19 patients admitted to 8 hospitals in Germany (March–November 2020) to develop and validate (75/25 random-split) 3 linear (L1 and L2 penalty, elastic net [EN]) and 2 non-linear (support vector machine [SVM] with radial kernel, random forest [RF]) ML approaches for predicting critical events defined by intensive care unit transfer, invasive ventilation and/or death (composite end-point: 181 patients). Models were compared for performance (area-under-the-receiver-operating characteristic-curve [AUC], Brier score) and predictor importance (performance-loss metrics, partial-dependence profiles). Results Models performed close with a small benefit for LR (utilizing restricted cubic splines for non-linearity) and RF (AUC means: 0.763–0.731 [RF–L1]); Brier scores: 0.184–0.197 [LR–L1]). Top ranked predictor variables (consistently highest importance: C-reactive protein) were largely identical across models, except creatinine, which exhibited marginal (L1, L2, EN, SVM) or high/non-linear effects (LR, RF) on events. Conclusions Although the LR and ML models analysed showed no strong differences in performance and the most influencing predictors for COVID-19-related event prediction, our results indicate a predictive benefit from taking account for non-linear predictor-to-event relationships and effects. Future efforts should focus on leveraging data-driven ML technologies from static towards dynamic modelling solutions that continuously learn and adapt to changes in data environments during the evolving pandemic. Trial registration number: NCT04659187.

The advent of X-ray free-electron lasers (XFELs) has revolutionized fundamental science, from atomic to condensed matter physics, from chemistry to biology, giving researchers access to X-rays with unprecedented brightness, coherence and pulse duration. All XFEL facilities built until recently provided X-ray pulses at a relatively low repetition rate, with limited data statistics. Here, results from the first megahertz-repetition-rate X-ray scattering experiments at the Spectroscopy and Coherent Scattering (SCS) instrument of the European XFEL are presented. The experimental capabilities that the SCS instrument offers, resulting from the operation at megahertz repetition rates and the availability of the novel DSSC 2D imaging detector, are illustrated. Time-resolved magnetic X-ray scattering and holographic imaging experiments in solid state samples were chosen as representative, providing an ideal test-bed for operation at megahertz rates. Our results are relevant and applicable to any other non-destructive XFEL experiments in the soft X-ray range.

MotivationResults of simulations with climate models form the most important basis for research and statements about possible changes in the future global, regional and local climate. These output volumes are increasing at an exponential rate (Balaji et al. 2018, Stevens et al. 2019). Efficiently handling these amounts of data is a challenge for researchers, mainly because the development of novel data and workflow handling approaches have not proceeded at the same rate as data volume has been increasing. This problem will only become more pronounced with the ever increasing performance of High Performance Computing (HPC) - systems used to perform weather and climate simulations (Lawrence et al. 2018). For example, in the framework of the European Commission's Destination Earth program the Digital Twins (Bauer et al. 2021) are expected to produce hundreds of terabytes of model output data every day at the EuroHPC computing sites.The described data challenge can be dissected into several aspects, two of which we will focus on in this contribution. Available data in the Earth System Sciences (ESS) are increasingly made openly accessible by various institutions, such as universities, research centres and government agencies, in addition to subject-specific repositories. Further, the exploitability of weather and climate simulation output beyond the expert community by humans and automated agents (as described by the FAIR data principles (F-Findable, A-Accessable, I-Interoperable, R-Reusable), Wilkinson et al. 2016) is currently very limited if not impossible due to disorganized metadata or incomplete provenance information. Additionally, developments regarding globally available and FAIR workflows in the spirit of the FAIR Digital Object (FDO) framework (Schultes and Wittenburg 2019, Schwardmann 2020) are just at the beginning.Cultural ChangeIn order to address the challenges with respect to data mentioned above, current efforts at DKRZ (German Climate Computing Center) are aimed at a complete restructuring of the way research is performed in simulation-based climate research (Anders et al. 2022, Mozaffari et al. 2022, Weigel et al. 2020). DKRZ is perfectly suited for this endeavor, because researchers have the resources and services available to conduct the entire suite of their data-intensive workflows - ranging from planning and setting up of model simulations, analyzing the model output, reusing existing large-volume datasets to data publication and long-term archival. At the moment, DKRZ-users do not have the possibility to orchestrate their workflows via a central service, but rather use a plethora of different tools to piece them together.Framework Environment FrevaThe central element of the new workflow environment at DKRZ shall be represented by the Freva (Free Evaluation System Framework) software infrastructure, which offers standardized data and tool solutions in ESS and is optimized for use on high-performance computer systems (Kadow et al. 2021). Freva is designed to be very well suited to the use of the FDO framework. The crucial aspects here are:the standardisation of data objects as input for analysis and processing,the already implemented remote access to data via a Persisitent Identifier (PID),the currently still system-internal capture of analysis provenance andthe possibility of sharing results but also workflows by research groups up to large communities.It is planned to extend the functionality of Freva so that the system automatically determines the data required for a specific analysis from a researcher’s research question (provided to the system via some interface), enquires available databases (local disk or tape, cloud or federated resources) for that data and retrieves the data if possible. If data are not available (yet), Freva shall be able to automatically configure, set up and submit model simulations to the HPC-System, so that the required data is created and becomes available (cf. Fig. 1). These data will in turn be ingested into Freva’s data catalog for reuse. Next, Freva shall orchestrate and document the analysis performed. Results will be provided either as numerical fields, images or animations depending on the researcher’s need. As a final step, the applied workflow and/or underlying data are published in accordance with the FAIR data guiding principles.FDOs - towards a global integrated Data Space To make the process sketched out above a reality, application of the FDO concept is essential (Schwardmann 2020, Schultes and Wittenburg 2019). There is a long tradition in the ESS community of global dissemination and reuse of large-volume climate data sets. Community standards like those developed and applied in the framework of internationally coordinated model intercomparison studies (CMIP) allow for low-barrier reuse of data (Balaji et al. 2018). Globally resolvable PIDs are provided on a regular basis. Current community ESS standards and workflows are already close to being compatible with implementing FDOs, however, now we also have to work on open points in the FDO concept, which are:the clear definition of community-specific FDO requirements including PID Kernel Types specifications,the operation of data type registries andthe technical implementation requirements for global access to FDOs.With these in place and implemented in Freva following standardized implementation recommendations, automated data queries across spatially distributed or different types of local databases become possible.We introduce the concept of implementations in Freva and also use it to highlight the challenges we face. Using an example, we show the vision of the work of a scientist in earth system science.

Die Veröffentlichung von ChatGPT im Herbst 2022 hat das Thema Künstliche Intelligenz (KI) auch im Bildungsbereich in das Blickfeld der Aufmerksamkeit gerückt. In den medialen Hype und die verschiedenen Diskurse mit einer reichen Bandbreite von kompletter Ablehnung der Technologie bis hin zur Glorifizierung derselben gesellen sich nach und nach auch bildungspolitische Empfehlungen, die überwiegend einen zwar kritischen, aber auch konstruktiven und verantwortungsvollen Umgang mit KI in der Schule proklamieren, wofür allerdings Kompetenzen bei Schüler:innen wie Lehrer:innen notwendig sind – und zwar nicht nur in Fächern wie Informatik oder Digitale Grundbildung, sondern quer durch alle Unterrichtsgegenstände. Der vorliegende Beitrag greift im ersten Teil die aktuellen Diskurse im deutschsprachigen Raum zu KI in der Schule auf und stellt im zweiten Teil ein Projekt vor, in dessen Rahmen Lehr-/Lernszenarien für die Sekundarstufe I zu verschiedenen Teilbereichen des Themenfeldes KI ausgearbeitet und evaluiert wurden, die entsprechende Grundlagen vermitteln und fächerübergreifende Anknüpfungspunkte bieten.

Abstract Background In previous clinical trials, patients with active rheumatoid arthritis (RA) treated with upadacitinib (UPA) have improved patient-reported outcomes (PROs). This post hoc analysis of SELECT-CHOICE, a phase 3 clinical trial, evaluated the impact of UPA vs abatacept (ABA) with background conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) on PROs in patients with RA with inadequate response or intolerance to biologic disease-modifying antirheumatic drugs (bDMARD-IR). Methods Patients in SELECT-CHOICE received UPA (oral 15 mg/day) or ABA (intravenous). PROs evaluated included Patient Global Assessment of Disease Activity (PtGA) by visual analog scale (VAS), patient’s assessment of pain by VAS, Health Assessment Questionnaire Disability Index (HAQ-DI), morning stiffness duration and severity, 36-Item Short Form Health Survey (SF-36), Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F), Work Productivity and Activity Impairment (WPAI), and EQ-5D 5-Level (EQ-5D-5L) index score. Least squares mean (LSM) changes from baseline to weeks 12 and 24 were based on an analysis of covariance model. Proportions of patients reporting improvements ≥ minimal clinically important differences (MCID) were compared using chi-square tests. Results Data from 612 patients were analyzed (UPA, n=303; ABA, n=309). Mean age was 56 years and mean disease duration was 12 years. One-third received ≥2 prior bDMARDs and 72% received concomitant methotrexate at baseline. At week 12, UPA- vs ABA-treated patients had significantly greater improvements in PtGA, pain, HAQ-DI, morning stiffness severity, EQ-5D-5L, 2/4 WPAI domains, and 3/8 SF-36 domains and Physical Component Summary (PCS) scores (P

One of the outstanding analytical problems in X-ray single-particle imaging (SPI) is the classification of structural heterogeneity, which is especially difficult given the low signal-to-noise ratios of individual patterns and the fact that even identical objects can yield patterns that vary greatly when orientation is taken into consideration. Proposed here are two methods which explicitly account for this orientation-induced variation and can robustly determine the structural landscape of a sample ensemble. The first, termed common-line principal component analysis (PCA), provides a rough classification which is essentially parameter free and can be run automatically on any SPI dataset. The second method, utilizing variation auto-encoders (VAEs), can generate 3D structures of the objects at any point in the structural landscape. Both these methods are implemented in combination with the noise-tolerant expand–maximize–compress (EMC) algorithm and its utility is demonstrated by applying it to an experimental dataset from gold nanoparticles with only a few thousand photons per pattern. Both discrete structural classes and continuous deformations are recovered. These developments diverge from previous approaches of extracting reproducible subsets of patterns from a dataset and open up the possibility of moving beyond the study of homogeneous sample sets to addressing open questions on topics such as nanocrystal growth and dynamics, as well as phase transitions which have not been externally triggered.

Citizen Science (CS) projects targeting senior citizens and persons with functional impairments are rare, and interest among citizens to become involved in such remains uncertain. There is a lack of systematic analyses as to what distinguishes citizens’ willingness to contribute, and what such involvement could lead to in terms of acquired skills or changed attitudes. Based on a Swedish CS project on housing accessibility – the Housing Experiment (HX) – this study aimed to investigate: 1) the characteristics of senior citizens and persons with functional impairments involved in the HX; and 2) changes in attitudes and mobile digital literacy after completing the HX. Data were collected via online questionnaires before and after the HX (N = 147), and were analyzed statistically. The response rates were lower than anticipated. Study participants completing the HX reported high levels of mobile digital literacy and functional ability, and a higher education level than the general Swedish population. The only attitudinal change was that significantly more participants rated the importance of housing accessibility lower after their involvement in the HX compared with those rating it higher. This study confirms indications from previous studies that limitations in mobile digital literacy and functional ability affect the willingness and ability to get involved in research. Further research is warranted to investigate how similar CS projects could be designed to attract more participants and to create the conditions for greater gains for citizen scientists.

BackgroundIntravenous iron supplementation is an established therapy for patients with heart failure (HF) and concomitant iron deficiency reducing the risk of HF hospitalization. However, concerns persist regarding potential adverse vascular effects, since iron may induce oxidative stress, inflammation, and apoptosis of endothelial cells. To assess endothelial health following ferric carboxymaltose (FCM) administration, we analyzed the profile of circulating endothelial microvesicles (EMVs) and endothelial progenitor cells (EPCs) in a cohort of 23 HF patients using flow cytometry.ResultsCompared to healthy subjects, baseline levels of CD31+/CD41- EMVs were higher and EMVs featured a more apoptotic phenotype in HF patients. Following FCM administration, EMV levels showed a rapid but transient increase and displayed an altered phenotype profile with dominant augmentation of EMVs expressing inducible markers CD62E and CD54, indicating endothelial inflammatory activation and injury. Levels of circulating vasoregenerative CD45lowCD34+KDR+ EPCs were lower in HF patients and FCM application resulted in an early decrease of EPCs followed by substantial mobilization into the circulation after one week. Levels of EMVs and EPCs returned to baseline values within two and four weeks, respectively. HF patients with additional chronic kidney disease showed an elevated EMV/EPC ratio and diminished EPC mobilization, suggesting impaired vascular repair capacity. Providing a mechanistic link, in vitro experiments with cultured endothelial cells revealed that FCM dose-dependently promotes endothelial apoptosis, increases expression of adhesion molecules and CXCL12, and triggers generation of EMVs.ConclusionIntravenous iron supplementation with FCM in HF patients induces a biphasic response with initial increased release of CD62E+ and CD54+ enriched EMVs and subsequent mobilization of EPCs, indicating endothelial dysfunction upon FCM and suggesting consecutive engagement of a defense program aimed to reconstitute vascular health.

Developments in the field of automated mobility will greatly change our mobility and the possibilities to get from one place to another. This paper presents different scenarios for personal mobility in Austria, anticipating the possibilities and developments in the field of automated vehicles (AVs). The scenarios were developed using a systematically formalized scenario technique and expand the social and political discourse on automated mobility, which is currently characterized by a lack of experience and visibility as an established transport service. Using system dynamics modeling techniques, i.e., the Metropolitan Activity Relocation Simulator (MARS), impacts of the scenarios on the Austrian transportation system are estimated. The simulations show that, without suitable transport policy measures, automated mobility will lead to a significant increase in the volume of individual traffic and to modal shift effects with lower traffic volumes for public transport, walking and cycling. In addition, without a link between AVs and post-fossil propulsion systems, increases in pollutant emissions can also be expected. In contrast, the simulation results of an increased use of AVs in public transport show positive effects for the support of a more sustainable mobility. Hence, transport policy measures accompanying the introduction and development of automated vehicles will be needed in the future to reach a sustainable development.