Low-light imaging on mobile devices is typically challenging due to insufficient incident light coming through the relatively small aperture, resulting in low image quality. Most of the previous ...works on low-light imaging focus either only on a single task such as illumination adjustment, color enhancement, or noise removal; or on a joint illumination adjustment and denoising task that heavily relies on short-long exposure image pairs from specific camera models. These approaches are less practical and generalizable in real-world settings where camera-specific joint enhancement and restoration is required. In this paper, we propose a low-light imaging framework that performs joint illumination adjustment, color enhancement, and denoising to tackle this problem. Considering the difficulty in model-specific data collection and the ultra-high definition of the captured images, we design two branches: a coefficient estimation branch and a joint operation branch. The coefficient estimation branch works in a low-resolution space and predicts the coefficients for enhancement via bilateral learning, whereas the joint operation branch works in a full-resolution space and progressively performs joint enhancement and denoising. In contrast to existing methods, our framework does not need to recollect massive data when adapted to another camera model, which significantly reduces the efforts required to fine-tune our approach for practical usage. Through extensive experiments, we demonstrate its great potential in real-world low-light imaging applications.
Skin cancer is a deadly disease, and its early diagnosis enhances the chances of survival. Deep learning algorithms for skin cancer detection have become popular in recent years. A novel framework ...based on deep learning is proposed in this study for the multiclassification of skin cancer types such as Melanoma, Melanocytic Nevi, Basal Cell Carcinoma and Benign Keratosis. The proposed model is named as SCDNet which combines Vgg16 with convolutional neural networks (CNN) for the classification of different types of skin cancer. Moreover, the accuracy of the proposed method is also compared with the four state-of-the-art pre-trained classifiers in the medical domain named Resnet 50, Inception v3, AlexNet and Vgg19. The performance of the proposed SCDNet classifier, as well as the four state-of-the-art classifiers, is evaluated using the ISIC 2019 dataset. The accuracy rate of the proposed SDCNet is 96.91% for the multiclassification of skin cancer whereas, the accuracy rates for Resnet 50, Alexnet, Vgg19 and Inception-v3 are 95.21%, 93.14%, 94.25% and 92.54%, respectively. The results showed that the proposed SCDNet performed better than the competing classifiers.
Although the association between childhood socioeconomic status (SES) and late-life cognition is well-established, the mechanisms underlying this association are less clear. One important potential ...mediator seldom examined is adolescent cognitive ability. To address this gap, we examined 5,880 respondents from the Wisconsin Longitudinal Study, which follows a random sample of high school students who graduated from Wisconsin high schools in 1957. Structural equation models were used to examine the direct and indirect effects of childhood SES on cognition in late midlife through adolescent cognitive ability, educational attainment, midlife economic condition, and midlife health. Cognitive function was measured as a latent variable composed of scores from 6 cognitive assessments including immediate and delayed recall, digit ordering, letter and category fluency, and a subset of the Wechsler Adult Intelligence Scale similarities test. We found that childhood SES predicts cognition in late midlife, and this association is largely mediated by adolescent cognitive ability and educational attainment and to a lesser extent by midlife economic condition and health. The findings underscore the long-arm of childhood SES in cognitive function in later life and highlight the complex life-course pathways underlying the association between childhood SES and cognition.
•Applies SEM technique to examine pathways linking childhood SES and cognition in late midlife.•Adolescent cognitive ability partially mediates the association between childhood SES and cognition in late midlife.•Educational attainment, midlife economic condition, and midlife health are also important mediators.
Research on grandparenting (i.e., caring for grandchildren) and mental health in Asian contexts has been limited, despite the rapid growth of older adults who take care of grandchildren. This study ...aims to investigate how grandparenting influences depressive symptoms in China. Using the China Health and Retirement Longitudinal Study (2011–2015, N = 4354), we conducted fixed effects regression models to examine the association between various types of grandparenting and depressive symptoms among older adults between the ages of 45 and 80. The results show that for grandparents, providing care to their grandchildren in skipped-generation households (i.e., grandparent-grandchildren families without adult children) is associated with a lower level of depressive symptoms compared to providing no care, after controlling for socioeconomic status, health behaviors, social support, and basic demographic characteristics. Other types of care (i.e., multigenerational household grandparenting, and part-time and full-time noncoresident grandparenting) are not significantly linked to caregiving grandparents’ depressive symptoms. Overall, our findings suggest that sociocultural contexts need to be considered in explaining the different mental health implications of grandparenting.
•We examine the association between grandparenting and mental health.•We used fixed effects models to test the association.•Skipped-generation household grandparenting is related to few depressive symptoms.•The relationship above holds, even after controlling for time-varying covariates.
We provide one of the first population-based studies of variation in dementia by marital status in the United States.
We analyzed data from the Health and Retirement Study (2000-2014). The sample ...included 15,379 respondents (6,650 men and 8,729 women) aged 52 years and older in 2000 who showed no evidence of dementia at the baseline survey. Dementia was assessed using either the modified version of the Telephone Interview for Cognitive Status (TICS) or the proxy's assessment. Discrete-time hazard regression models were estimated to predict odds of dementia.
All unmarried groups, including the cohabiting, divorced/separated, widowed, and never married, had significantly higher odds of developing dementia over the study period than their married counterparts; economic resources and, to a lesser degree, health-related factors accounted for only part of the marital status variation in dementia. For divorced/separated and widowed respondents, the differences in the odds of dementia relative to married respondents were greater among men than among women.
These findings will be helpful for health policy makers and practitioners who seek to better identify vulnerable subpopulations and to design effective intervention strategies to reduce dementia risk.
It is important to understand the fragmentation processes and mechanisms of plastic litter to predict microplastic production in the marine environment. In this study, accelerated weathering ...experiments were performed in the laboratory, with ultraviolet (UV) exposure for up to 12 months followed by mechanical abrasion (MA) with sand for 2 months. Fragmentation of low-density polyethylene (PE), polypropylene (PP), and expanded polystyrene (EPS) was evaluated under conditions that simulated a beach environment. PE and PP were minimally fragmented by MA without photooxidation by UV (8.7 ± 2.5 and 10.7 ± 0.7 particles/pellet, respectively). The rate of fragmentation by UV exposure duration increased more for PP than PE. A 12-month UV exposure and 2-month MA of PP and PE produced 6084 ± 1061 and 20 ± 8.3 particles/pellet, respectively. EPS pellets were susceptible to MA alone (4220 ± 33 particles/pellet), while the combination of 6 months of UV exposure followed by 2 months of MA produced 12,152 ± 3276 particles/pellet. The number of fragmented polymer particles produced by UV exposure and mechanical abrasion increased with decreasing size in all polymer types. The size-normalized abundance of the fragmented PE, PP, and EPS particles according to particle size after UV exposure and MA was predictable. Up to 76.5% of the initial EPS volume was unaccounted for in the final volume of pellet produced particle fragments, indicating that a large proportion of the particles had fragmented into undetectable submicron particles.
Despite the excellent photoelectronic properties of the all‐inorganic cesium lead iodide (CsPbI3) perovskite, which does not contain volatile and hygroscopic organic components, only a few CsPbI3 ...devices are developed mainly owing to the frequent formation of an undesirable yellow δ‐phase at room temperature. Herein, it is demonstrated that a small quantity of poly(ethylene oxide) (PEO) added to the precursor solution effectively inhibits the formation of the yellow δ‐phase during film preparation, and promotes the development of a black α‐phase at a low crystallization temperature. A systematic study reveals that a thin, dense, pinhole‐free CsPbI3 film is produced in the α‐phase and is stabilized with PEO that effectively reduces the grain size during crystallization. A thin α‐phase CsPbI3 film with excellent photoluminescence is successfully employed in a light‐emitting diode with an inverted configuration of glass substrate/indium tin oxide/zinc oxide/poly(ethyleneimine)/α‐CsPbI3/poly(4‐butylphenyl‐diphenyl‐amine)/WO3/Al, yielding the characteristic red emission of the perovskite film at 695 nm with brightness, external quantum efficiency, and emission band width of ≈101 cd m−2, 1.12%, and 32 nm, respectively.
A small quantity of a poly(ethylene oxide) added in the precursor solution is beneficial for the development of all‐inorganic CsPbI3 perovskite in black α‐phase with significantly improved ambient stability. Dense, uniform, and pinhole‐free CsPbI3 thin films consisting of tens of nanometers black α‐phase crystals are successfully fabricated with excellent photophysical properties, leading to high performance light‐emitting diodes.
In this paper, we present an adaptive joint trilateral filter (AJTF), which consists of domain, range, and depth filters. The AJTF is used for the joint enhancement of images and depth maps, which is ...achieved by suppressing the noise and sharpening the edges simultaneously. For improving the sharpness of the image and depth map, the AJTF parameters, the offsets, and the standard deviations of the range and depth filters are determined in such a way that image edges that match well with depth edges are emphasized. To this end, pattern matching between local patches in the image and depth map is performed and the matching result is utilized to adjust the AJTF parameters. Experimental results show that the AJTF produces sharpness-enhanced images and depth maps without overshoot and undershoot artifacts, while successfully reducing noise as well. A comparison of the performance of the AJTF with those of conventional image and depth enhancement algorithms shows that the proposed algorithm is effective.
Due to the rich histopathological information of nuclei in whole slide images, nuclei segmentation becomes essential for medical analysis. Since collecting sufficient pixel-wise annotations for ...supervised training of nuclei segmentation networks is challenging, semi-supervised nuclei segmentation methods have been extensively studied. In particular, many of them use pseudo-labels generated from unlabeled images for training the segmentation model. In this Letter, we propose a new pseudo-label handling method for semi-supervised nuclei segmentation. Specifically, based on our observation that nuclear features within the same image share high similarities, we define confidence maps for pseudo-labels and use them to adapt consistency regularization and contrastive loss measures. From extensive experiments on three public datasets, we demonstrate the effectiveness of the proposed method compared with other semi-supervised training methods.
The human gut microbiome is closely linked to mental health and sleep. We aimed to verify the efficacy and safety of probiotic NVP-1704, a mixture of Lactobacillus reuteri NK33 and Bifidobacterium ...adolescentis NK98, in improving stress, depression, anxiety, and sleep disturbances, along with the measurement of some blood biomarkers. A total of 156 healthy adults with subclinical symptoms of depression, anxiety, and insomnia were retrospectively registered and randomly assigned to receive either NVP-1704 (n = 78) or a placebo (n = 78) for eight weeks. Participants completed the Stress Response Inventory, Beck’s Depression and Anxiety Inventory, Pittsburg Sleep Quality Index, and Insomnia Severity Index at baseline, at four and eight weeks of treatment. Pre- and post-treatment blood tests for biomarkers were conducted. After intervention, gut microbiota composition was quantified by pyrosequencing the bacterial 16S rRNA gene. The NVP-1704 group had a more significant reduction in depressive symptoms at four and eight weeks of treatment, and anxiety symptoms at four weeks compared to the placebo group. Those receiving NVP-1704 also experienced an improvement in sleep quality. NVP-1704 treatment led to a decrease in serum interleukin-6 levels. Furthermore, NVP-1704 increased Bifidobacteriaceae and Lactobacillacea, whereas it decreased Enterobacteriaceae in the gut microbiota composition. Our findings suggest that probiotic NVP-1704 could be beneficial for mental health and sleep.
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