113 research outputs found

    FEM Analysis of Spring-backs in Age Forming of Aluminum Alloy Plates

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    AbstractThe age forming technology, characterized by huge spring-backs, has been developed to manufacture large integral wing-skin panel parts, which necessitates devising a method of predicting spring-backs. A 7B04-T7451 aluminum alloy creep test in tension is accomplished at 155 °C, and the creep curves are obtained. The material constants of the mechanism-based creep constitutive equations are determined through experiments. The age forming process and the spring-backs of 7B04 aluminum alloy plates are analyzed using the commercial finite element software ABAQUS. The effects of plate thickness and forming time on spring-backs are researched. The spring-backs decrease with the increase of plate thickness and forming time. The test results verify the reliability of the finite element method (FEM) analysis

    Structural and optical properties of PVP-capped nanocrystalline ZnxCd1−xS solid solutions

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    Nanocrystalline ZnxCd1−xS solid solutions were prepared in a microwave-assisted hydrothermal process with gradient distribution of components (x = 0.1, 0.3, 0.5, 0.7, and 0.9). The growth of the cubic-structured quantum dots was observed for all component stoichiometries with the crystallite size between 4.5 and 5.7 nm. The obvious peak shifts have been found in the XRD patterns and the lattice parameters showed linear variation with x increasing. The evolution of the optical properties of obtained solid solutions including absorption and photoemission was also monitored in detail. The solid solutions show a considerable shift in the nanoparticle optical absorption edge from 482 to 343 nm with the increasing of Zn fraction. The band gaps of the solid solutions were estimated to be between 2.94 and 3.40 eV and the position of conduction band was shifted toward more negative potential with x increasing. The photoluminescence spectra showed a broad blue-green emission spreading up to 600 nm with emergence of three dominant peaks belong to sulfur, zinc, and cadmium vacancies

    Risk and protective factors of depression in the general population during the COVID-19 epidemic in Korea

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    Background: The risk of depression has risen in the general population during the COVID-19 epidemic. This study was conducted to explore risk and protective factors associated with depression among the general population uninfected by COVID-19. Methods: A cross-sectional study was conducted with 1,500 representative South Korean citizens aged 19–65 years through an anonymous online survey. Depression was defined as a Patient Health Questionnaire-9 score of 10 or higher. Other questionnaires included one measuring psycho-behavioural and social changes, and stress, due to COVID-19, a six-item version of the Gratitude Questionnaire (GQ-6), and a three-item version of the UCLA loneliness scale. Results: Of the 1492 participants not infected by COVID-19, 312 (20.9%) exhibited depression. Multiple logistic regression analysis revealed that depression was positively associated with COVID-19-related stress and psycho-behavioural variables such as disturbances in eating and sleeping, younger age, smoking, underlying mental illness, and loneliness scale scores. In contrast, exercise three or more times per week and GQ-6 scale scores were inversely associated with depression. Conclusion: During the COVID-19 pandemic, maintaining daily routines including eating, sleeping, and regular exercise and focusing on gratitude may be important for the prevention of depression. In addition, more attention should be paid to vulnerable populations, including young people, those with mental illnesses, and smokers, who might be more susceptible to depression

    Accelerated Discovery of 3D Printing Materials Using Data-Driven Multi-Objective Optimization

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    Additive manufacturing has become one of the forefront technologies in fabrication, enabling new products impossible to manufacture before. Although many materials exist for additive manufacturing, they typically suffer from performance trade-offs preventing them from replacing traditional manufacturing techniques. Current materials are designed with inefficient human-driven intuition-based methods, leaving them short of optimal solutions. We propose a machine learning approach to accelerate the discovery of additive manufacturing materials with optimal trade-offs in mechanical performance. A multi-objective optimization algorithm automatically guides the experimental design by proposing how to mix primary formulations to create better-performing materials. The algorithm is coupled with a semi-autonomous fabrication platform to significantly reduce the number of performed experiments and overall time to solution. Without any prior knowledge of the primary formulations, the proposed methodology autonomously uncovers twelve optimal composite formulations and enlarges the discovered performance space 288 times after only 30 experimental iterations. This methodology could easily be generalized to other material formulation problems and enable completely automated discovery of a wide variety of material designs

    Fetal programming of neuropsychiatric disorders by maternal pregnancy depression: a systematic mini review

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    BACKGROUND: Maternal depression complicates a large proportion of pregnancies. Current evidence shows numerous harmful effects on the offspring. Reviews, which include depression, concluded that stress has harmful effects on the offspring's outcomes neuro-cognitive development, temperament traits, and mental disorders. OBJECTIVE: This mini review of recent studies, sought to narrow the scope of exposure and identify studies specifically assessing prenatal depression and offspring neuropsychiatric outcomes. STUDY ELIGIBILITY CRITERIA: The review included longitudinal, cohort, cross-sectional, clinical, quasi-experimental, epidemiological, or intervention study designs published in English from 2014 to 2018. PARTICIPANTS: Study populations included mother-child dyads, mother-father-child triads, mother-alternative caregiver-child triads, and family studies utilizing sibling comparisons. METHODS: We searched PubMED and Web of Science. Study inclusion and data extraction were based on standardized templates. The quality of evidence was assessed using the Newcastle-Ottawa Scale (NOS). RESULTS: Thirteen studies examining neuropsychiatric outcomes were included. We judged the evidence to be moderate to high quality. CONCLUSIONS: Our review supports that maternal prenatal depression is associated with neuropsychiatric adversities in children.Peer reviewe

    Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.

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    Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction

    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

    New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS)

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    GEMS will monitor air quality over Asia at unprecedented spatial and temporal resolution from GEO for the first time, providing column measurements of aerosol, ozone and their precursors (nitrogen dioxide, sulfur dioxide and formaldehyde). Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled for launch in late 2019 - early 2020 to monitor Air Quality (AQ) at an unprecedented spatial and temporal resolution from a Geostationary Earth Orbit (GEO) for the first time. With the development of UV-visible spectrometers at sub-nm spectral resolution and sophisticated retrieval algorithms, estimates of the column amounts of atmospheric pollutants (O3, NO2, SO2, HCHO, CHOCHO and aerosols) can be obtained. To date, all the UV-visible satellite missions monitoring air quality have been in Low Earth orbit (LEO), allowing one to two observations per day. With UV-visible instruments on GEO platforms, the diurnal variations of these pollutants can now be determined. Details of the GEMS mission are presented, including instrumentation, scientific algorithms, predicted performance, and applications for air quality forecasts through data assimilation. GEMS will be onboard the GEO-KOMPSAT-2 satellite series, which also hosts the Advanced Meteorological Imager (AMI) and Geostationary Ocean Color Imager (GOCI)-2. These three instruments will provide synergistic science products to better understand air quality, meteorology, the long-range transport of air pollutants, emission source distributions, and chemical processes. Faster sampling rates at higher spatial resolution will increase the probability of finding cloud-free pixels, leading to more observations of aerosols and trace gases than is possible from LEO. GEMS will be joined by NASA's TEMPO and ESA's Sentinel-4 to form a GEO AQ satellite constellation in early 2020s, coordinated by the Committee on Earth Observation Satellites (CEOS)
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