An Underwater Image Enhancement Method for a Preprocessing Framework Based on Generative Adversarial Network.

This paper presents an efficient underwater image enhancement method, named ECO-GAN, to address the challenges of color distortion, low contrast, and motion blur in underwater robot photography. The proposed method is built upon a preprocessing framework using a generative adversarial network. ECO-GAN incorporates a convolutional neural network that specifically targets three underwater issues: motion blur, low brightness, and color deviation. To optimize computation and inference speed, an encoder is employed to extract features, whereas different enhancement tasks are handled by dedicated decoders. Moreover, ECO-GAN employs cross-stage fusion modules between the decoders to strengthen the connection and enhance the quality of output images. The model is trained using supervised learning with paired datasets, enabling blind image enhancement without additional physical knowledge or prior information. Experimental results demonstrate that ECO-GAN effectively achieves denoising, deblurring, and color deviation removal simultaneously. Compared with methods relying on individual modules or simple combinations of multiple modules, our proposed method achieves superior underwater image enhancement and offers the flexibility for expansion into multiple underwater image enhancement functions.

The association between low carbohydrate diet scores and cardiometabolic risk factors in Chinese adults.

Epidemiological studies on the association between the low carbohydrate diet (LCD) score and cardiovascular disease risk factors have limited and inconsistent results. Data are from the baseline survey of Community-based Cohort Study on Nervous System Diseases. A total of 4609 adults aged ≥18 years were included in the study. Dietary data were assessed using a validated semi-quantitative Food Frequency Questionnaire. Multivariable logistic regression analyses were used to estimate relationships of three LCD scores with low high-density lipoprotein cholesterol (HDL-C), high low-density lipoprotein cholesterol (LDL-C), hypercholesterolemia, hypertriglyceridemia, impaired fasting glucose (IFG), high blood pressure, and hyperuricemia after adjusting for potential confounders. A higher LCD score was negatively associated with low HDL-C [OR (95%CI): 0.65 (0.50, 0.83), P=0.0001] and IFG [OR (95%CI): 0.65 (0.51, 0.81), P=0.001] after the final adjustment. However, there are gender differences in this result. Males in the highest quintile of the animal-based or plant-based LCD scores showed a decreased risk of low HDL-C, and females in the highest quintile of the animal-based or plant-based LCD scores showed a decreased risk of IFG than those in the lowest quintile of the LCD scores. These results suggest that gender differences should be considered when using LCD to treat dyslipidemia and reduce fasting blood glucose.

Procyanidins inhibit fine particulate matter-induced vascular smooth muscle cells apoptosis via the activation of the Nrf2 signaling pathway.

The functional role of procyanidins (PC) in PM2.5-induced cardiovascular diseases (CVD) is largely unexplored. This study aimed to explore the protective effect of PC against PM2.5-induced vascular smooth muscle cells (VSMCs) apoptosis and underlying mechanisms. Sprague Dawley rats were pretreated with three doses of PC (50, 100, and 200 mg/kg) and exposed to 10 mg/kg PM2.5 by intratracheal instillation three times a week. VSMCs were exposed to 5, 10, and 20 µM PC before the addition of 100 µg/mL PM2.5. In vivo, the PM2.5 exposure induced apoptosis in the thoracic aorta of rats. The PM2.5 exposure significantly elevated the reactive oxygen species (ROS) and malondialdehyde (MDA) levels and decreased the superoxide dismutase activity. Also, PC supplementation increased the expression of nuclear factor erythroid 2-related factor 2 (Nrf2), and its downstream antioxidant genes, i.e., NAD(P)H dehydrogenase (quinine) 1 and heme oxygenase 1, attenuated oxidative stress and vascular apoptosis. In vitro, PM2.5 induced cytotoxicity in VSMCs in a dose-dependent manner. Besides, PC abolished the PM2.5-induced cytotoxicity by activating the Nrf2 signal pathway, alleviating oxidative stress, and decreasing apoptosis. In conclusion, this work is the first study to demonstrate that PC can suppress the PM2.5-induced VSMCs apoptosis via the activation of the Nrf2 signal pathway.

A Marine Organism Detection Framework Based on the Joint Optimization of Image Enhancement and Object Detection.

Underwater vision-based detection plays an increasingly important role in underwater security, ocean exploration and other fields. Due to the absorption and scattering effects of water on light, as well as the movement of the carrier, underwater images generally have problems such as noise pollution, color cast and motion blur, which seriously affect the performance of underwater vision-based detection. To address these problems, this study proposes an end-to-end marine organism detection framework that can jointly optimize the image enhancement and object detection. The framework uses a two-stage detection network with dynamic intersection over union (IoU) threshold as the backbone and adds an underwater image enhancement module (UIEM) composed of denoising, color correction and deblurring sub-modules to greatly improve the framework's ability to deal with severely degraded underwater images. Meanwhile, a self-built dataset is introduced to pre-train the UIEM, so that the training of the entire framework can be performed end-to-end. The experimental results show that compared with the existing end-to-end models applied to marine organism detection, the detection precision of the proposed framework can improve by at least 6%, and the detection speed has not been significantly reduced, so that it can complete the high-precision real-time detection of marine organisms.

Lack of CUL4B leads to increased abundance of GFAP-positive cells that is mediated by PTGDS in mouse brain.

Astrocytes are the most abundant cell type in the mammalian brain and are important for the functions of the central nervous system. Glial fibrillary acidic protein (GFAP) is regarded as a hallmark of mature astrocytes, though some GFPA-positive cells may act as neural stem cells. Missense heterozygous mutations in GFAP cause Alexander disease that manifests leukodystrophy and intellectual disability. Here, we show that CUL4B, a scaffold protein that assembles E3 ubiquitin ligase, represses the expression of GFAP in neural progenitor cells (NPCs) during brain development. Lack of Cul4b in NPCs in cultures led to increased generation of astrocytes, marked by GFAP and S100ß. The GFAP+ cells were also found to be more abundant in the brains of nervous system-specific Cul4b knockout mice in vivo. Moreover, we demonstrated that the increased generation of GFAP+ cells from Cul4b-null NPCs was mediated by an upregulation of prostaglandin D2 synthase PTGDS. We showed that the increased GFAP expression can be attenuated by pharmacological inhibition of the PTGDS enzymatic activity or by shRNA-mediated knockdown of Ptgds. Importantly, exogenously added PTGDS could promote the generation of GFAP+ cells from wild-type NPCs. We further observed that Ptgds is targeted and repressed by the CUL4B/PRC2 complex. Together, our results demonstrate CUL4B as a negative regulator of GFAP expression during neural development.

Copper-Catalyzed TBHP-Mediated Radical Cross-Coupling Reaction of Sulfonylhydrazides with Thiols Leading to Thiosulfonates.

A tert-butyl hydroperoxide (TBHP)-mediated coupling of sulfonylhydrazides with thiols catalyzed by CuBr2 to afford thiosulfonates via a radical process is described.

The Evolutions of Microstructure, Texture and Hardness of A1050 Deformed by HPT at the Transition Area.

High-pressure torsion (HPT) is an effective severe plastic deformation method to produce ultrafine-grained (UFG) and nanocrystalline (NC) materials. In the past, most studies have focused on the evolutions in the microstructure, texture and mechanical properties of HPT-deformed materials at peripheral regions. The corresponding evolutions at a special area were observed in this study to reveal the potential plastic deformation mechanism for face-centred cubic (FCC) material with high stacking fault energy. A decreasing trend was found in grain size, and the final grain size was less than 1 µm. However, close observation revealed that the general trend could be divided into different sub-stages, in which grain elongation and grain fragmentation were dominant, respectively. Additionally, microhardness demonstrated a non-linear increase with the development of plastic deformation. Finally, the microhardness reached a high level of ~64 HV. At the early stages of HPT, the C component was transformed into a cube component, suggesting the material flows around the shear plane normal (SPN) axis at these stages. However, finally they will be replaced by ideal simple shear orientations.

Effect of Different Hot-Pressing Pressure and Temperature on the Performance of Titanium Mesh-Based MEA for DMFC.

The hot-pressing process of the membrane electrode assembly (MEA) is one of the research hotspots in the field of the fuel cell. To obtain suitable titanium mesh-based MEA hot pressing process parameters, titanium mesh was used as electrode substrate material. The anode and cathode of MEA were prepared by the drip-coated method, and the titanium mesh-based MEA was prepared under different hot-pressing pressure and temperature, respectively. The performance of titanium mesh-based MEA was studied by morphological observation, elemental analysis, thickness measurement, single cell test and numerical fitting analysis. The results demonstrated that: with increasing hot-pressing pressure from 0 MPa to 10 MPa, the forming thickness of titanium mesh-based MEA is getting thin gradually, and the peak power density of titanium mesh-based MEA first increased and then gradually decreased; with increasing hot-pressing temperature from 115 °C to 155 °C, the peak power density of titanium mesh-based MEA enhanced at the beginning and then also gradually decreased. Under the premise of a hot-pressing time of 180 s and the optimal operating temperature of DMFC of 60 °C, the appropriate hot-pressing process conditions of titanium mesh-based MEA are a hot-pressing pressure of 5 MPa and a hot-pressing temperature of 135 °C. The results can provide a technological reference for the preparation of titanium mesh MEA for DMFC.

Research on the Morphology Reconstruction of Deep Cryogenic Treatment on PtRu/nitrogen-Doped Graphene Composite Carbon Nanofibers.

To improve the performance of PtRu/nitrogen-doped graphene composite carbon nanofibers, the composite carbon nanofibers were thermally compensated by deep cryogenic treatment (DCT), which realized the morphology reconstruction of composite carbon nanofibers. The effects of different DCT times were compared: 12 h, 18 h, and 24 h. The morphology reconstruction mechanism was explored by combining the change of inner chain structure and material group. The results showed that the fibers treated for 12 h had better physical and chemical properties, where the diameter is evenly distributed between 500 and 800 nm. Combined with Fourier infrared analysis, the longer the cryogenic time, the more easily the water vapor and nitrogen enter polymerization reaction, causing changes of chain structure and degradation performance. With great performance of carbonization and group transformation, the PtRu/nitrogen-doped graphene composite carbon nanofibers can be used as an efficient direct alcohol fuel cell catalyst and promote its commercialization.

Associations between Dietary Inflammatory Index (DII) and bone health among postmenopausal women in the United States.

OBJECTIVE: The purpose of this study was to determine the relationship between the Dietary Inflammatory Index (DII® ) score and the bone health of menopausal women. METHODS: A total of 2461 participants were included in the analysis from the NHANES database 2009-2018 and 2005-2006. The association between the DII and Bone mineral density (BMD) and bone mineral content (BMC) was evaluated through a multiple linear regression model. RESULTS: The mean DII in this study was +0.89 (SD 0.18) and the scores ranged from -5.46 (most anti-inflammatory) to +4.58 (most pro-inflammatory). After adjusting for confounding factors, higher DII is associated with an increased risk of decreased total bone density (Model III, ß -0.012; 95% CI -0.023, -0.001). There is a similar correlation found in bone density content and other indicators of bone mineral density. At the same time, we used BMI as a stratified variable for subgroup analysis, we found that higher DII (continuous) was associated with a significantly higher risk of decreased total bone density in overweight/obese postmenopausal women (ß -0.018; 95% CI -0.025, -0.006). CONCLUSION: A higher DII score is significantly associated with lower bone density and bone density in postmenopausal women, especially women who are overweight/obese.

Randomized controlled trial for time-restricted eating in overweight and obese young adults.

Time-restricted eating (TRE) is known to improve metabolic health, whereas very few studies have compared the effects of early and late TRE (eTRE and lTRE) on metabolic health. Overweight and obese young adults were randomized to 6-h eTRE (eating from 7 a.m. to 1 p.m.) (n = 21), 6-h lTRE (eating from 12 p.m. to 6 p.m.) (n = 20), or a control group (ad libitum intake in a day) (n = 19). After 8 weeks, 6-h eTRE and lTRE produced comparable body weight loss compared with controls. Compared with control, 6-h eTRE reduced systolic blood pressure, mean glucose, fasting insulin, insulin resistance, leptin, and thyroid axis activity, whereas lTRE only reduced leptin. These findings shed light on the promise of 6-h eTRE and lTRE for weight loss. Larger studies are needed to assess the promise of eTRE to yield better thyroid axis modulation and overall cardiometabolic health improvement.

Role of BMI in the Relationship Between Dietary Inflammatory Index and Depression: An Intermediary Analysis.

Introduction: This study investigated this association and the role of BMI in the inflammatory process in a large population-based observational study. Methods: A total of 1,865 elderly people (≥55 years) were followed from the Community Cohort Study of Nervous System Diseases (CCSNSD) cohort study from 2018 to 2019 (Mean [SD] age, 66.31 [0.32] years; 716 [38.4%] males). The semi-quantitative FFQ and geriatric depression scale (GDS) were used to evaluate the diet and depressive symptoms of the elderly, respectively. The multivariable logistic regression model estimated the OR and 95% CI between Empirical Dietary Inflammatory Index (E-DII) and depression. The interaction of E-DII and BMI on depressive events was tested, and the mediation analysis of BMI was performed. Results: As measured by E-DII, the mean (SE) value of the inflammatory potential of the diet in our study was 1.56 (0.12). E-DII ranged from 5.23 to 5.58. In comparison with the first quartile, the elderly from the second quartile (OR: 1.15 [95% CI: 1.09, 1.28]) to the fourth quartile (OR: 1.31 [95% CI: 1.16, 1.42]) have a higher risk of depression before adjustment for BMI. An interaction was observed between E-DII and BMI in terms of the risk of depression (PInteraction < 0.001). The whole related part is mediated by BMI (31.06%). Conclusion: Our findings indicate that the higher pro-inflammatory potential of diet is associated with a higher risk of depression, and this association may be mediated by BMI. Further research is needed to verify our findings and clarify the latent mechanism.

Association of Dietary Inflammatory Index (DII) and Depressive Disorders.

A lot of evidence shows that inflammation is related to the development of depression. However, the heterogeneity of depression hinders efforts to understand, prevent and treat this disease. The purpose of this comprehensive review is to summarize the links between inflammation and the established core features of depression, which show more homogeneity than the syndrome itself: overreaction to negative information, changes in reward processing, and cognitive control decline, and somatic syndrome. For each core feature, we first briefly outline its relevance to depression and neurobiological basis, and then review the evidence to investigate the potential role of inflammation. We mainly focus on the discovery of the experimental paradigm of exogenous inflammation. We concluded that inflammation may play a role in overreaction to negative information, altered reward responses, and physical symptoms. There is less evidence to support the effect of inflammation on cognitive control by standard neuropsychological measures. Finally, we discussed the implications for future research and recommendations on how to test the role of inflammation in the pathogenesis of heterogeneous mental illness.

GBDT-Based Fall Detection with Comprehensive Data from Posture Sensor and Human Skeleton Extraction.

Since fall is happening with increasing frequency, it has been a major public health problem in an aging society. There are considerable demands to distinguish fall down events of seniors with the characteristics of accurate detection and real-time alarm. However, some daily activities are erroneously signaled as falls and there are too many false alarms in actual application. In order to resolve this problem, this paper designs and implements a comprehensive fall detection framework on the basis of inertial posture sensors and surveillance cameras. In the proposed system framework, data sources representing behavior characteristics to indicate potential fall are derived from wearable triaxial accelerometers and monitoring videos of surveillance cameras. Moreover, the NB-IoT based communication mode is adopted to transmit wearable sensory data to the Internet for subsequent analysis. Furthermore, a Gradient Boosting Decision Tree (GBDT) classifier-based fall detection algorithm (GBDT-FD in short) with comprehensive data fusion of posture sensor and human video skeleton is proposed to improve detection accuracy. Experimental results verify the good performance of the proposed GBDT-FD algorithm compared to six kinds of existing fall detection algorithms, including SVM-based fall detection, NN-based fall detection, etc. Finally, we implement the proposed integrated systems including wearable posture sensors and monitoring software on the Cloud Server.