168 research outputs found

    Towards green 3D-microfabrication of Bio-MEMS devices using ADEX dry film photoresists

    Get PDF
    Current trends in miniaturized diagnostics indicate an increasing demand for large quantities of mobile devices for health monitoring and point-of-care diagnostics. This comes along with a need for rapid but preferably also green microfabrication. Dry film photoresists (DFPs) promise low-cost and greener microfabrication and can partly or fully replace conventional silicon-technologies being associated with high-energy demands and the intense use of toxic and climate-active chemicals. Due to their mechanical stability and superior film thickness homogeneity, DFPs outperform conventional spin-on photoresists, such as SU-8, especially when three-dimensional architectures are required for micro-analytical devices (e.g. microfluidics). In this study, we utilize the commercial epoxy-based DFP ADEX to demonstrate various application scenarios ranging from the direct modification of microcantilever beams via the assembly of microfluidic channels to lamination-free patterning of DFPs, which employs the DFP directly as a substrate material. Finally, kinked, bottom-up grown silicon nanowires were integrated in this manner as prospective ion-sensitive field-effect transistors in a bio-probe architecture directly on ADEX substrates. Hence, we have developed the required set of microfabrication protocols for such an assembly comprising metal thin film deposition, direct burn-in of lithography alignment markers, and polymer patterning on top of the DFP

    Prevalence and severity of mental disorders in military personnel: a standardised comparison with civilians

    Get PDF
    Aims. Provision and need for mental health services among military personnel are a major concern across nations. Two recent comparisons suggest higher rates of mental disorders in US and UK military personnel compared with civilians. However, these findings may not apply to other nations. Previous studies have focused on the overall effects of military service rather than the separate effects of military service and deployment. This study compared German military personnel with and without a history of deployment to sociodemographically matched civilians regarding prevalence and severity of 12-month DSM-IV mental disorders. Method. 1439 deployed soldiers (DS), 779 never deployed soldiers (NS) and 1023 civilians were assessed with an adapted version of the Munich Composite International Diagnostic interview across the same timeframe. Data were weighted using propensity score methodology to assure comparability of the three samples. Results. Compared with adjusted civilians, the prevalence of any 12-month disorder was lower in NS (OR: 0.7, 95% CI: 0.5–0.99) and did not differ in DS. Significant differences between military personnel and civilians regarding prevalence and severity of individual diagnoses were only apparent for alcohol (DS: OR: 0.3, 95% CI: 0.1–0.6; NS: OR: 0.2, 95% CI: 0.1–0.6) and nicotine dependence (DS: OR: 0.5, 95% CI: 0.3–0.6; NS: OR: 0.5, 95% CI: 0.3–0.7) with lower values in both military samples. Elevated rates of panic/agoraphobia (OR: 2.7, 95% CI: 1.4–5.3) and posttraumatic stress disorder (OR: 3.2, 95% CI: 1.3–8.0) were observed in DS with high combat exposure compared with civilians. Conclusions. Rates and severity of mental disorders in the German military are comparable with civilians for internalising and lower for substance use disorders. A higher risk of some disorders is reduced to DS with high combat exposure. This finding has implications for mental health service provision and the need for targeted interventions. Differences to previous US and UK studies that suggest an overall higher prevalence in military personnel might result from divergent study methods, deployment characteristics, military structures and occupational factors. Some of these factors might yield valuable targets to improve military mental health

    Port-Hamiltonian Modeling of Hydraulics in 4th Generation District Heating Networks

    Get PDF
    In this paper, we use elements of graph theory and port-Hamiltonian systems to develop a modular dynamic model describing the hydraulic behavior of 4th generation district heating networks. In contrast with earlier generation networks with a single or few heat sources and pumps, newer installations will prominently feature distributed heat generation units, bringing about a number of challenges for the control and stable operation of these systems, e.g., flow reversals and interactions among pumps controllers, which may lead to severe oscillations. We focus thus on flexible system setups with an arbitrary number of distributed heat sources and end-users interconnected through a meshed, multi-layer distribution network of pipes. Moreover, differently from related works on the topic, we incorporate dynamic models for the pumps in the system and explicitly account for the presence of pressure holding units. By inferring suitable (power-preserving) interconnection ports, we provide a number of claims about the passivity properties of the overall, interconnected system, which proves to be highly beneficial in the design of decentralized control schemes and stability analyses

    Solution structure of the inner DysF domain of myoferlin and implications for limb girdle muscular dystrophy type 2b

    Get PDF
    Mutations in the protein dysferlin, a member of the ferlin family, lead to limb girdle muscular dystrophy type 2B and Myoshi myopathy. The ferlins are large proteins characterised by multiple C2 domains and a single C-terminal membrane-spanning helix. However, there is sequence conservation in some of the ferlin family in regions outside the C2 domains. In one annotation of the domain structure of these proteins, an unusual internal duplication event has been noted where a putative domain is inserted in between the N- and C-terminal parts of a homologous domain. This domain is known as the DysF domain. Here, we present the solution structure of the inner DysF domain of the dysferlin paralogue myoferlin, which has a unique fold held together by stacking of arginine and tryptophans, mutations that lead to clinical disease in dysferlin

    Patterns of alcohol consumption among individuals with alcohol use disorder during the COVID-19 pandemic and lockdowns in Germany

    Get PDF
    Objective: To examine whether lockdown measures are associated with AC and consumption-related temporal and psychological within-person mechanisms. Design, setting, and participants: This quantitative, intensive, longitudinal cohort study recruited 1743 participants from 3 sites from February 20, 2020, to February 28, 2021. Data were provided before and within the second lockdown of the COVID-19 pandemic in Germany: before lockdown (October 2 to November 1, 2020); light lockdown (November 2 to December 15, 2020); and hard lockdown (December 16, 2020, to February 28, 2021). Main outcomes and measures: Daily ratings of AC (main outcome) captured during 3 lockdown phases (main variable) and temporal (weekends and holidays) and psychological (social isolation and drinking intention) correlates. Results: Of the 1743 screened participants, 189 (119 [63.0%] male; median [IQR] age, 37 [27.5-52.0] years) with at least 2 alcohol use disorder (AUD) criteria according to the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) yet without the need for medically supervised alcohol withdrawal were included. These individuals provided 14 694 smartphone ratings from October 2020 through February 2021. Multilevel modeling revealed significantly higher AC (grams of alcohol per day) on weekend days vs weekdays (β = 11.39; 95% CI, 10.00-12.77; P < .001). Alcohol consumption was above the overall average on Christmas (β = 26.82; 95% CI, 21.87-31.77; P < .001) and New Year's Eve (β = 66.88; 95% CI, 59.22-74.54; P < .001). During the hard lockdown, perceived social isolation was significantly higher (β = 0.12; 95% CI, 0.06-0.15; P < .001), but AC was significantly lower (β = -5.45; 95% CI, -8.00 to -2.90; P = .001). Independent of lockdown, intention to drink less alcohol was associated with lower AC (β = -11.10; 95% CI, -13.63 to -8.58; P < .001). Notably, differences in AC between weekend and weekdays decreased both during the hard lockdown (β = -6.14; 95% CI, -9.96 to -2.31; P = .002) and in participants with severe AUD (β = -6.26; 95% CI, -10.18 to -2.34; P = .002). Conclusions and relevance: This 5-month cohort study found no immediate negative associations of lockdown measures with overall AC. Rather, weekend-weekday and holiday AC patterns exceeded lockdown effects. Differences in AC between weekend days and weekdays evinced that weekend drinking cycles decreased as a function of AUD severity and lockdown measures, indicating a potential mechanism of losing and regaining control. This finding suggests that temporal patterns and drinking intention constitute promising targets for prevention and intervention, even in high-risk individuals

    Measuring self-regulation in everyday life: Reliability and validity of smartphone-based experiments in alcohol use disorder

    Get PDF
    Self-regulation, the ability to guide behavior according to one's goals, plays an integral role in understanding loss of control over unwanted behaviors, for example in alcohol use disorder (AUD). Yet, experimental tasks that measure processes underlying self-regulation are not easy to deploy in contexts where such behaviors usually occur, namely outside the laboratory, and in clinical populations such as people with AUD. Moreover, lab-based tasks have been criticized for poor test-retest reliability and lack of construct validity. Smartphones can be used to deploy tasks in the field, but often require shorter versions of tasks, which may further decrease reliability. Here, we show that combining smartphone-based tasks with joint hierarchical modeling of longitudinal data can overcome at least some of these shortcomings. We test four short smartphone-based tasks outside the laboratory in a large sample (N = 488) of participants with AUD. Although task measures indeed have low reliability when data are analyzed traditionally by modeling each session separately, joint modeling of longitudinal data increases reliability to good and oftentimes excellent levels. We next test the measures' construct validity and show that extracted latent factors are indeed in line with theoretical accounts of cognitive control and decision-making. Finally, we demonstrate that a resulting cognitive control factor relates to a real-life measure of drinking behavior and yields stronger correlations than single measures based on traditional analyses. Our findings demonstrate how short, smartphone-based task measures, when analyzed with joint hierarchical modeling and latent factor analysis, can overcome frequently reported shortcomings of experimental tasks

    Measuring self-regulation in everyday life: reliability and validity of smartphone-based experiments in alcohol use disorder

    Get PDF
    Self-regulation, the ability to guide behavior according to one’s goals, plays an integral role in understanding loss of control over unwanted behaviors, for example in alcohol use disorder (AUD). Yet, experimental tasks that measure processes underlying self-regulation are not easy to deploy in contexts where such behaviors usually occur, namely outside the laboratory, and in clinical populations such as people with AUD. Moreover, lab-based tasks have been criticized for poor test–retest reliability and lack of construct validity. Smartphones can be used to deploy tasks in the field, but often require shorter versions of tasks, which may further decrease reliability. Here, we show that combining smartphone-based tasks with joint hierarchical modeling of longitudinal data can overcome at least some of these shortcomings. We test four short smartphone-based tasks outside the laboratory in a large sample (N = 488) of participants with AUD. Although task measures indeed have low reliability when data are analyzed traditionally by modeling each session separately, joint modeling of longitudinal data increases reliability to good and oftentimes excellent levels. We next test the measures’ construct validity and show that extracted latent factors are indeed in line with theoretical accounts of cognitive control and decision-making. Finally, we demonstrate that a resulting cognitive control factor relates to a real-life measure of drinking behavior and yields stronger correlations than single measures based on traditional analyses. Our findings demonstrate how short, smartphone-based task measures, when analyzed with joint hierarchical modeling and latent factor analysis, can overcome frequently reported shortcomings of experimental tasks
    • …
    corecore