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Non-alcoholic fatty liver disease (NAFLD) has emerged as a global health concern, lacking specific therapeutic strategies. Time-restricted feeding (TRF) regimen demonstrated beneficial effects in NAFLD; however, the underlying mechanisms remain unclear. In this study, we established a NAFLD mouse model through a high-fat diet (HFD) and implemented the 16:8 TRF regimen for a duration of 6 weeks. We demonstrated that TRF remarkably alleviated hepatic steatosis in HFD mice. Of note, aldehyde oxidase 1 (AOX1), a key enzyme in hepatic nicotinamide (NAM) catabolism, exhibited apparent upregulation in response to HFD, leading to abnormal accumulation of N-Methyl-6-pyridone-3-carboxamide (N-Me-6-PY, also known as 2PY) and N-Methyl-4-pyridone-5-carboxamide (N-Me-4-PY, also known as 4PY), whereas it was almost restored by TRF. Both N-Me-6-PY and N-Me-4-PY promoted de novo lipogenesis and fatty acid uptake capacities in hepatocyte, and aggravated hepatic steatosis in mice either fed chow diet or HFD. In contrast, pharmacological inhibition of AOX1 was sufficient to ameliorate the hepatic steatosis and lipid metabolic dysregulation induced by HFD. Moreover, transplantation of fecal microbiota efficiently mimicked the modulatory effect of TRF on NAM metabolism, thus mitigating hepatic steatosis and lipid metabolic disturbance, suggesting a gut microbiota-dependent manner. In conclusion, our study reveals the intricate relationship between host NAM metabolic modification and gut microbiota remodeling during the amelioration of NAFLD by TRF, providing promising insights into the prevention and treatment of NAFLD.

The organic expanded vermiculite (OEVMT) is a good anti-aging agent for asphalt binder due to its excellent heat and oxygen barrier properties. However, the application form of OEVMT is usually limited to being as a modifier for asphalt binder while seldom research takes it as an alternative to filler in asphalt mixture. Using the OEVMT as an alternative to filler has the potential to further improve the aging resistance of asphalt mixture in comparison with using the OEVMT as an asphalt binder modifier, because the amount of OEVMT in asphalt mixture can be largely increased in this case. In present study, different proportions of fillers in asphalt mixture were replaced by OEVMT to produce asphalt mixtures with better aging resistance. The effects of using OEVMT as an alternative to fillers on road performance and aging resistance of asphalt mixture were investigated. The results indicate that replacing a large proportion of fillers in asphalt mixture can lead to a poor moisture resistance of asphalt mixture. In comprehensive consideration of moisture, cracking and rutting resistances, the optimal proportion of filler that should be replaced by OEVMT is 12.5 %. In comparison with the form of using OEVMT as a modifier for asphalt binder, using an appropriate amount of OEVMT to replace limestone fillers in asphalt mixture can further enhance the aging resistance of asphalt mixture by increasing the amount of OEVMT in asphalt mixture.

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In order to solve the problem that the testbench stimulation and probe insertion debugging method of emulator requires extra hardware resources and has insufficient flexibility in software debugging, a virtual GDB remote debugging technology was researched to improve the debugging ability of the emulator. Firstly,JTAG proxy and JTAG transactor were used to support the connection between the workstation and the emulator. Then the signals between GDB and JTAG proxy were transmitted through VPI to complete the debugging of virtual GDB. Finally, the virtual GDB remote debugging system was applied in emulator for experiments. The results show that the virtual GDB remote debugging system can support breakpoint insertion, single step running, register reading and writing, and other functions. Compared with debugging by probe insertion, the virtual GDB system is almost hundred times faster. It greatly enriches the software debugging method and enhances the debugging ability of emulator, and improves the efficiency of the chip design and verification.

Abstract Falling from a height is the most common accident on construction sites. Vision‐based techniques can be used to automatically monitor the construction sites and give early warnings. In this study, a lightweight object detection method, Efficient‐YOLOv5, was proposed for detecting whether workers are wearing safety harnesses when working at height. Furthermore, a matching‐recheck strategy was proposed to improve the mean average precision (mAP). The safety status evaluation model was designed to evaluate the safety status of workers in different construction scenarios. An edge computing‐based security monitoring and alarm system suitable for deployment on construction sites was proposed to assist manual management. Efficient‐YOLOv5 was trained and evaluated on our newly created dataset. Experiments demonstrated that our proposed method outperformed other comparison methods, as the precision and recall rates were 97.7% and 89.3%, respectively. The mAP was 94%. The rate of frames per second (FPS) was 72, which met real‐time application requirements. Thus, the proposed method could easily be applied in the construction industry.

Atmospheric mercury plays a crucial role in the biogeochemical cycle of mercury. This study conducted an intensive measurement of atmospheric mercury from 2015 to 2018 at a regional site in eastern China. During this period, the concentration of particle-bound mercury (PBM) decreased by 13%, which was much lower than those of gaseous elemenral mercury (GEM, 30%) and reactive gaseous mercury (GOM, 62%). The gradual decrease in the correlation between PBM and CO, K, and Pb indicates that the influence of primary emissions on PBM concentration was weakening. Moreover, the value of the partitioning coefficient (Kp) increased gradually from 0.05 ± 0.076 m3/μg in 2015 to 0.16 ± 0.37 m3/μg in 2018, indicating that GOM was increasingly inclined to adsorb onto particulate matter. Excluding the influence of meteorological conditions and the primary emissions, the change in aerosol composition is designated as the main trigger factor for the increasing gas-particle partitioning of reactive mercury (RM). The increasing ratio of Cl−, NO3−, and organics (Org) in the chemical composition of particle matters (PM2.5), as well as the decrease in the proportion of SO42−, NH4+, and K+, are conducive to the adsorption of GOM onto particles, forming PBM, which led to an increase of Kp and a lag of PBM reduction compared to GEM and GOM under the continuous control measures of anthropogenic mercury emissions. The evolution of aerosol compositions in recent years affects the migration and transformation of atmospheric mercury, which in turn can affect the biogeochemical cycle of mercury.

To solve the problems of texture lacking and resolution coarseness in the detection of dim and small drone targets in infrared images, we propose a novel RetinaNet with an asymmetric attention fusion mechanism for dim and small drone detection. First, we propose a super-resolution texture-enhancement network as an effective solution for the lack of texture-related information on small infrared targets. The network generates super-resolution images and enhances the texture features of the targets. Second, considering the inadequacy of feature pyramids in the feature fusion stage, we use an asymmetric attention fusion mechanism to constitute an asymmetric attention fusion pyramid network for cross-layer feature fusion in a bidirectional manner; it achieves high-quality semantic and location detail information interaction between scale features. Third, a global average pooling layer is employed to capture global spatial-sensitive information, thus effectively identifying features and achieving classification. Experiments were conducted by using a publicly available infrared image dim-small drone target detection dataset; the results show that the proposed method achieves an AP of 95.43% and a recall of 80.6%, which is a significant improvement over the current mainstream target detection algorithms.

ObjectiveSpontaneous isolated abdominal aortic dissection (SIAAD) is a rare aortic emergency and not yet fully understood. This study aims to report the characteristics and treatments of 31 patients with SIAAD in the past 12 years.MethodsA total of 31 consecutive patients with SIAAD between 2010 and 2022 were included. The clinical manifestations, treatment strategies, and outcomes were reviewed. Following the SVS/STS reporting standard, we compared the clinical characteristics with different locations of primary entry, or different numbers of dissected zones. Furthermore, we compared the effects of surgical and conservative therapies on the outcome during the follow-up.ResultsAmong the 31 patients with SIAAD, 16 (51.6%) were in the acute phase on admission. The primary entry of SIAAD was mainly located in Zone 9 (67.7%). Most patient presented with dissection involving 1 or 2 aortic zones (61.3%). In addition, 35.5% and 64.5% of SIAADs involved the visceral and iliac arteries, respectively. Compared with asymptomatic SIAADs, the symptomatic ones had longer dissection lengths (P = 0.008) and tended to involve iliac artery more frequently (P = 0.098). There were differences in the number of dissected aortic zones (P = 0.005) among patients with primary entry located in Zone 5 (Supraceliac aorta), Zone 6–8 (Paravisceral aorta) and Zone 9 (Infrarenal aorta). The involvement of visceral artery (P = 0.039) and iliac artery (P = 0.006) was significantly different between the subgroups of SIAAD involving one, two, and three or more aortic zones. The cumulative incidence of adverse false lumen progression events was significantly lower (P = 0.000) and the rate of false lumen thrombogenesis or disappearance was higher in patients receiving surgery (P = 0.001). The cumulative all-cause mortality was 9.7% at 1-year, and 19.7% at 5-year, with no significant difference between surgical and conservative therapies.ConclusionsClinical features of SIAAD vary depending on the location of the primary entry and the number of dissected aortic zones. Although surgery was not associated with a lower all-cause mortality compared with conservative therapy, it was associated with a lower incidence of adverse false lumen progression and a higher rate of aortic remodeling.

Obesity is one of the most prevalent chronic metabolic diseases, and induction of apoptosis in preadipocytes and adipocytes is a potential strategy to treat obesity. Celastrol represents one of the most robust anti-obesity phytochemicals so far, yet its direct binding target remains elusive. Here, we determined that celastrol could induce apoptosis in preadipocytes via mitochondrial mediated pathway. Further study clarified that celastrol inhibited the fusion of autophagosome and lysosome to prohibit autophagy, leading to cell apoptosis. By conducting virtual screening and genetic manipulation, we verified that overexpression of VAMP7 and RAB7 could block the effects of celastrol on inhibiting autophagy and inducing apoptosis. The Surface Plasmon Resonance study confirmed the direct binding of celastrol with VAMP7 and RAB7. The functional study illustrated the inhibition of RAB7 GTPase activity after celastrol treatment. Moreover, celastrol induced comparable apoptosis in murine epididymal adipose tissue, human preadipocytes and adipocytes, but not in human hepatocytes. An inhibitory effect on differentiation of human primary visceral preadipocytes was also observed. In conclusion, celastrol exhibited inhibitory effect of autophagy via direct binding with VAMP7 and RAB7, leading to an increase in preadipocytes apoptosis. These results advance our understanding in the potential application of celastrol in treating obesity.

SAR images play a crucial role in ship detection across diverse scenarios due to their all-day, all-weather characteristics. However, detecting SAR ship targets poses inherent challenges due to their small sizes, complex backgrounds, and dense ship scenes. Consequently, instances of missed detection and false detection are common issues. To address these challenges, we propose the DSF-Net, a novel framework specifically designed to enhance small SAR ship detection performance. Within this framework, we introduce the Pixel-wise Shuffle Attention module (PWSA) as a pivotal step to strengthen the feature extraction capability. To enhance long-range dependencies and facilitate information communication between channels, we propose a Non-Local Shuffle Attention (NLSA) module. Moreover, NLSA ensures the stability of the feature transfer structure and effectively addresses the issue of missed detection for small-sized targets. Secondly, we introduce a novel Triple Receptive Field-Spatial Pyramid Pooling (TRF-SPP) module designed to mitigate the issue of false detection in complex scenes stemming from inadequate contextual information. Lastly, we propose the R-tradeoff loss to augment the detection capability for small targets, expedite training convergence, and fortify resistance against false detection. Quantitative validation and qualitative visualization experiments are conducted to substantiate the proposed assumption of structural stability and evaluate the effectiveness of the proposed modules. On the LS-SSDDv1.0 dataset, the mAP50−95 demonstrates a remarkable improvement of 8.5% compared to the baseline model. The F1 score exhibits a notable enhancement of 6.9%, surpassing the performance of advanced target detection methods such as YOLO V8.

Ambient fine particulate matter (PM2.5) pollution is a major environmental and public health challenge in China. In the recent decade, the PM2.5 level has decreased mainly driven by reductions in particulate sulfate as a result of large-scale desulfurization efforts in coal-fired power plants and industrial facilities. Emerging evidence also points to the differential toxicity of particulate sulfate affecting human health. However, estimating the long-term spatiotemporal trend of sulfate is difficult because a ground monitoring network of PM2.5 constituents has not been established in China. Spaceborne sensors such as the Multi-angle Imaging SpectroRadiometer (MISR) instrument can provide complementary information on aerosol size and type. With the help of state-of-the-art machine learning techniques, we developed a sulfate prediction model under support from available ground measurements, MISR-retrieved aerosol microphysical properties, and atmospheric reanalysis data at a spatial resolution of 0.1°. Our sulfate model performed well with an out-of-bag cross-validation R2 of 0.68 at the daily level and 0.93 at the monthly level. We found that the national mean population-weighted sulfate concentration was relatively stable before the Air Pollution Prevention and Control Action Plan was enforced in 2013, ranging from 10.4 to 11.5 µg m−3. But the sulfate level dramatically decreased to 7.7 µg m−3 in 2018, with a change rate of −28.7 % from 2013 to 2018. Correspondingly, the annual mean total non-accidental and cardiopulmonary deaths attributed to sulfate decreased by 40.7 % and 42.3 %, respectively. The long-term, full-coverage sulfate level estimates will support future studies on evaluating air quality policies and understanding the adverse health effect of particulate sulfate.

Abstract Abnormal glucose and lipid metabolism in COVID-19 patients were recently reported with unclear mechanism. In this study, we retrospectively investigated a cohort of COVID-19 patients without pre-existing metabolic-related diseases, and found new-onset insulin resistance, hyperglycemia, and decreased HDL-C in these patients. Mechanistically, SARS-CoV-2 infection increased the expression of RE1-silencing transcription factor (REST), which modulated the expression of secreted metabolic factors including myeloperoxidase, apelin, and myostatin at the transcriptional level, resulting in the perturbation of glucose and lipid metabolism. Furthermore, several lipids, including (±)5-HETE, (±)12-HETE, propionic acid, and isobutyric acid were identified as the potential biomarkers of COVID-19-induced metabolic dysregulation, especially in insulin resistance. Taken together, our study revealed insulin resistance as the direct cause of hyperglycemia upon COVID-19, and further illustrated the underlying mechanisms, providing potential therapeutic targets for COVID-19-induced metabolic complications.

Summary: Air pollution is a major environmental and public health challenge in China and the Chinese government has implemented a series of strict air quality policies. However, particulate nitrate (NO3−) concentration remains high or even increases at monitoring sites despite the total PM2.5 concentration has decreased. Unfortunately, it has been difficult to estimate NO3− concentration across China due to the lack of a PM2.5 speciation monitoring network. Here, we use a machine learning model incorporating ground measurements and satellite data to characterize the spatiotemporal patterns of NO3−, thereby understanding the disease burden associated with long-term NO3− exposure in China. Our results show that existing air pollution control policies are effective, but increased NO3− of traffic emissions offset reduced NO3− of industrial emissions. In 2018, the national mean mortality burden attributable to NO3− was as high as 0.68 million, indicating that targeted regulations are needed to control NO3− pollution in China.

The high-energy-level dynamic compaction method is widely used in various foundation treatment projects, but its reinforcement mechanism still lags behind the practice. In view of this, a three-dimensional fluid–solid coupling dynamic analysis model was established on the basis of the FDM–DEM coupling method. The variation trends of crater depth, soil void ratio, vertical additional dynamic stress, and pore water pressure during the process of dynamic compaction were analyzed. The results indicate that the curvature of the crater depth fitting curve gradually decreases with the increase in strike times, tending to a stable value. The initial particle structure is altered by the huge dynamic stress induced by dynamic compaction. As strike times increase, the soil void ratio decreases gradually. The vertical additional dynamic stress is the fundamental reason resulting in foundation compaction. Precipitation preloading before dynamic compaction can improve the reinforcement effect of dynamic compaction, making up for the deficiency that the vertical additional dynamic stress attenuates rapidly along the depth direction. The simulated CPT results illustrate that the modulus of foundation soil can be increased by 3–5 times after dynamic compaction. The research results can provide important reference for similar projects.

BackgroundMetastatic breast cancer (MBC) remains incurable despite significant treatment advances. Coordinating care for patients with MBC can be challenging given the various treatment options, available clinical trials, and frequent need for ancillary services. To optimize MBC care, we designed a project for adapting and developing an academic and community practice collaborative care model for MBC care (Project ADAPT), based on the Ending Metastatic Breast Cancer for Everyone (EMBRACE) program developed at Dana Farber Cancer Institute. ObjectiveWe aim to describe the implementation science–based study design and innovative components of Project ADAPT. MethodsProject ADAPT uses the Dynamic Adaptation Process informed by the Exploration, Preparation, Implementation, Sustainment framework. Washington University School of Medicine (WUSM) partnered with 3 community hospitals in the St. Louis region covering rural and urban settings. The exploration and preparation phases provide patient and provider feedback on current referral practices to finalize the approach for the implementation phase. At the implementation phase, we will enroll patients with MBC at these 3 community sites to evaluate potential collaborative care at WUSM and assess the impact of this collaborative care model on referral satisfaction and acceptability for patients with MBC and their providers. Patients may then return to their community site for care or continue to receive part of their care at WUSM. We are incorporating virtual and digital health strategies to improve MBC care coordination in order to minimize patient burden. ResultsThe exploration phase is ongoing. As of August 2021, we have recruited 21 patient and provider participants to complete surveys of the current collaborative care process at WUSM. Using a 2-tailed paired t test, 44 patients (including 10 patients from the exploration phase) and 32 oncologists are required to detect an effect size of 0.5 with 80% power at a level of significance of .05. Throughout this phase and in preparation for the implementation phase, we have iteratively updated and refined our surveys for the implementation phase based on testing of our data collection instruments. Our partner sites are in various stages of the single institutional review board (IRB) approval process. We have ongoing engagement with all partner sites, which has helped solidify our participant recruitment strategies and design patient-friendly recruitment materials. In addition, we have included a patient advocate on the research team. Members of the research team have launched a single IRB Support Network at WUSM to create a repository of the single IRB procedures in order to streamline the partner site onboarding process and facilitate enhanced collaboration across institutions. ConclusionsWith this robust model, we expect that patients with MBC will receive optimal care regardless of geographical location and the model will improve patient and provider experiences when navigating the health system. International Registered Report Identifier (IRRID)DERR1-10.2196/35736

The primary cause for the limited shelf life of litchi fruit is rapid pericarp browning and decay. This study aims to evaluate the storability of 50 litchi varieties and establish a linear regression model for pericarp browning and decay based on 11 postharvest physical and chemical indices after 9 days of storage at room temperature. The results indicated that the average value of the browning index and decay rate significantly increased to 3.29% and 63.84% of 50 litchi varieties at day 9, respectively. Different litchi varieties showed different variations in appearance indicators, quality indicators, and physiological indicators. Furthermore, principal component analysis and cluster analysis revealed that Liu Li 2 Hao exhibited the highest resistance to storage, whereas Dong Long Mi Li, Jiao Pan Li, E Dan Li 2 Hao, and Ren Shan Li were not resistant. Stepwise multiple regression analysis further demonstrated that the factors were highly correlated with the decay index, with a partial correlation coefficient of 0.437 between the effective index and the decay index. Therefore, pericarp thickness, relative conductivity, pericarp laccase activity, and total soluble solids were significant indicators for the comprehensive evaluation of litchi browning and decay, and relative conductivity was the significant determinant causing fruit browning. These findings provide a new perspective on the sustainable development of the litchi industry.

Abstract Background Heart failure (HF) is a clinical syndrome characterized by left ventricular dysfunction or elevated intracardiac pressures. Research supports that microRNAs (miRs) participate in HF by regulating targeted genes. Hence, the current study set out to study the role of HDAC3-medaited miR-18a in HF by targeting ADRB3. Methods Firstly, HF mouse models were established by ligation of the left coronary artery at the lower edge of the left atrial appendage, and HF cell models were generated in the cardiomyocytes, followed by ectopic expression and silencing experiments. Numerous parameters including left ventricular posterior wall dimension (LVPWD), interventricular septal dimension (IVSD), left ventricular end diastolic diameter (LVEDD), left ventricular end systolic diameter (LVESD), left ventricular ejection fraction (LVEF), left ventricular fractional shortening (LVFS), left ventricular systolic pressure (LVSP), left ventricular end diastolic pressure (LEVDP), heart rate (HR), left ventricular pressure rise rate (+ dp/dt) and left ventricular pressure drop rate (-dp/dt) were measured in the mice. In addition, apoptosis in the mice was detected by means of TUNEL staining, while RT-qPCR and Western blot analysis were performed to detect miR-18a, HDAC3, ADRB3, cMyb, MMP-9, Collagen 1 and TGF-β1 expression patterns. Dual luciferase reporter assay validated the targeting relationship between ADRB3 and miR-18a. Cardiomyocyte apoptosis was determined by means of flow cytometry. Results HDAC3 and ADRB3 were up-regulated and miR-18a was down-regulated in HF mice and cardiomyocytes. In addition, HDAC3 could reduce the miR-18a expression, and ADRB3 was negatively-targeted by miR-18a. After down-regulation of HDAC3 or ADRB3 or over-expression of miR-18a, IVSD, LVEDD, LVESD and LEVDP were found to be decreased but LVPWD, LVEF, LVFS, LVSP, + dp/dt, and −dp/dt were all increased in the HF mice, whereas fibrosis, hypertrophy and apoptosis of HF cardiomyocytes were declined. Conclusion Collectively, our findings indicate that HDAC3 silencing confers protection against HF by inhibiting miR-18a-targeted ADRB3.

The method to determine the active earth pressure and critical width for finite soil behind the retaining wall in mountainous areas is one of the concerns of geotechnical engineering. In order to study the active earth pressure distribution of the finite soil against the retaining wall and determine the critical width of the boundary between the finite soil and the semi-infinite soil, this study focuses on investigating a retaining wall with finite cohesionless backfill. The shape of the failure surface is assumed to be a cycloid passing through the heel of the wall in the limit equilibrium state. Considering the deflection of soil principal stress induced by wall–soil friction effect, a calculation method of active earth pressure for finite soil is proposed by using an arc-shaped small principal stress trajectory, and the rationality of this method is verified. On this basis, a calculation formula of the critical width for finite soil is proposed. The influence of the internal friction angle and the wall–soil friction angle on the critical width of finite soil is examined. The results indicate that the active earth pressure of finite soil presents a nonlinear drum distribution along the height of the retaining wall under the failure mode of the cycloidal surface. The maximum value of active earth pressure is close to the bottom of the wall. The critical width of finite soil decreases with the increase of the internal friction angle, and its variation rate decreases gradually. The critical width of finite soil increases with the increase of the wall–soil friction angle, and its variation rate also increases gradually. Under different internal friction angles and wall–soil friction angles, the critical width values of finite soil calculated by the assumption of the cycloidal failure surface are smaller than those calculated by the Coulomb earth pressure calculation method.

Previous studies have reported that atmospheric elemental carbon (EC) may pose potentially elevated toxicity when compared to total ambient fine particulate matter (PM _2.5 ). However, most research on EC has been conducted in the US and Europe, whereas China experiences significantly higher EC pollution levels. Investigating the health impact of EC exposure in China presents considerable challenges due to the absence of a monitoring network to document long-term EC levels. Despite extensive studies on total PM _2.5 in China over the past decade and a significant decrease in its concentration, changes in EC levels and the associated mortality burden remain largely unknown. In our study, we employed a combination of satellite remote sensing, available ground observations, machine learning techniques, and atmospheric big data to predict ground EC concentrations across China for the period 2005–2018, achieving a spatial resolution of 10 km. Our findings reveal that the national average annual mean EC concentration has remained relatively stable since 2005, even as total PM _2.5 levels have substantially decreased. Furthermore, we calculated the all-cause non-accidental deaths attributed to long-term EC exposure in China using baseline mortality data and pooled mortality risk from a cohort study. This analysis unveiled significant regional disparities in the mortality burden resulting from long-term EC exposure in China. These variations can be attributed to varying levels of effectiveness in EC regulations across different regions. Specifically, our study highlights that these regulations have been effective in mitigating EC-related health risks in first-tier cities. However, in regions characterized by a highconcentration of coal-power plants and industrial facilities, additional efforts are necessary to control emissions. This observation underscores the importance of tailoring environmental policies and interventions to address the specific challenges posed by varying emission sources and regional contexts.

Vascular metabolic dysfunction presents in various diseases, such as atherosclerosis, hypertension, and diabetes mellitus. Due to the high prevalence of these diseases, it is important to explore treatment strategies to protect vascular function. Resveratrol (RSV), a natural polyphenolic phytochemical, is regarded as an agent to regulate metabolic pathways. Many studies have proven that RSV has beneficial effects on improving metabolism in endothelial cells (ECs) and vascular smooth muscle cells (VSMCs), which provide new directions to treat vascular metabolic diseases. Herein, we overviewed that RSV could regulate cell metabolism activity by inhibiting glucose uptake, suppressing glycolysis, preventing cells from fatty acid-related damages, reducing lipogenesis, increasing fatty acid oxidation, enhancing lipolysis, elevating uptake and synthesis of glutamine, and increasing NO release. Furthermore, in clinical trials, although the results from different studies remain controversial, we proposed that RSV had better therapeutic effects at high concentrations and for patients with metabolic disorders.

In synthetic aperture radar (SAR) images, ship targets are characterized by varying scales, large aspect ratios, dense arrangements, and arbitrary orientations. Current horizontal and rotation detectors fail to accurately recognize and locate ships due to the limitations of loss function, network structure, and training data. To overcome the challenge, we propose a unified framework combining triangle distance IoU loss (TDIoU loss), an attention-weighted feature pyramid network (AW-FPN), and a Rotated-SARShip dataset (RSSD) for arbitrary-oriented SAR ship detection. First, we propose a TDIoU loss as an effective solution to the loss-metric inconsistency and boundary discontinuity in rotated bounding box regression. Unlike recently released approximate rotational IoU losses, we derive a differentiable rotational IoU algorithm to enable back-propagation of the IoU loss layer, and we design a novel penalty term based on triangle distance to generate a more precise bounding box while accelerating convergence. Secondly, considering the shortage of feature fusion networks in connection pathways and fusion methods, AW-FPN combines multiple skip-scale connections and attention-weighted feature fusion (AWF) mechanism, enabling high-quality semantic interactions and soft feature selections between features of different resolutions and scales. Finally, to address the limitations of existing SAR ship datasets, such as insufficient samples, small image sizes, and improper annotations, we construct a challenging RSSD to facilitate research on rotated ship detection in complex SAR scenes. As a plug-and-play scheme, our TDIoU loss and AW-FPN can be easily embedded into existing rotation detectors with stable performance improvements. Experiments show that our approach achieves 89.18% and 95.16% AP on two SAR image datasets, RSSD and SSDD, respectively, and 90.71% AP on the aerial image dataset, HRSC2016, significantly outperforming the state-of-the-art methods.

Abstract Shape rolling is widely employed in the production of long workpieces with appropriate cross-section profiles for other industrial applications. In the development of shape rolling systems, roll pass design (RPD) plays an essential role on the quality control of products, service life of rolls, productivity of rolling systems, as well as energy consumption of rolling operations. This study attempts to establish a generic strategy based on hybrid modeling and an improved genetic algorithm, to support the optimizations of RPD and shape rolling operations at a systematic perspective. Objectives include improving the quality and efficiency of RPD, reducing energy consumption of shape rolling, as well as releasing the demands on costly trails and expert knowledge in RPD. Hybrid modeling based on cross-disciplinary knowledge is developed to overcome the limitations of isolated single-disciplinary models. And conventional genetic algorithm is improved for the implementation of optimal design. Targeting to integrate empirical data and published reliable solutions into optimizations, a parameters estimation method is proposed to transfer the initially misaligned models into a uniform pattern. A tool based on the Matlab platform is developed to demonstrate the optimal design operations, with case studies involved to validate the proposed methodology.

Early compressor trees based on carry-save adders and single-column parallel counters show good performance in ASIC design, but do not adapt well to modern field-programmable gate arrays (FPGAs). Recently, compressor trees built from generalized parallel counters (GPCs) were synthesized on FPGAs to address this issue. Despite the improved timing performance of GPC-based compressor trees, area reduction is not as significant as delay, and can be further optimized. In this paper, we propose improved GPC mappings as well as new approaches for GPC cascading and binding for Xilinx FPGAs. With these improvements, we develop an integer linear programming (ILP) method for FPGA synthesis of GPC-based compressor trees that supports cascading and binding between GPCs. Experimental results show that the single-cycle compressor trees produced by the proposed ILP can reduce the average area by 42.40% compared with those generated by existing heuristic method, but are 13.16% slower; the pipelined compressor trees produced by the proposed ILP can reduce the average area by 33.43% at the cost of an average 14.35% decrease in maximum clock frequency compared with those obtained by existing heuristic method.

Background Although glycoursodeoxycholic acid (GUDCA) has been associated with the improvement of metabolic disorders, its effect on atherosclerosis remains elusive. This study aimed to investigate the role of GUDCA in the development of atherosclerosis and its potential mechanisms. Methods and Results Human THP‐1 macrophages were used to investigate the effect of GUDCA on oxidized low‐density lipoprotein–induced foam cell formation in vitro. We found that GUDCA downregulated scavenger receptor A1 mRNA expression, reduced oxidized low‐density lipoprotein uptake, and inhibited macrophage foam cell formation. In an in vivo study, apolipoprotein E–deficient mice were fed a Western diet for 10 weeks to induce atherosclerosis, and then were gavaged once daily with or without GUDCA for 18 weeks. Parameters of systemic metabolism and atherosclerosis were detected. We found that GUDCA improved cholesterol homeostasis and protected against atherosclerosis progression as evidenced by reduced plaque area along with lipid deposition, ameliorated local chronic inflammation, and elevated plaque stability. In addition, 16S rDNA sequencing showed that GUDCA administration partially normalized the Western diet–associated gut microbiota dysbiosis. Interestingly, the changes of bacterial genera (Alloprevotella, Parabacteroides, Turicibacter, and Alistipes) modulated by GUDCA were correlated with the plaque area in mice aortas. Conclusions Our study for the first time indicates that GUDCA attenuates the development of atherosclerosis, probably attributable to the inhibition of foam cell formation, maintenance of cholesterol homeostasis, and modulation of gut microbiota.

Shield tunneling activities inevitably pass through pile foundations at close distance in densely urban areas. Various studies have investigated the interaction between newly constructed tunnels and existing pile foundations. However, the influence of different construction sequences of twin paralleled shield tunneling on single long pile is seldom considered. A case was found in the project of Changsha Metro Line 5, where the twin paralleled tunnels were constructed near the Wanjiali Viaduct piles. A three-dimensional finite element model was established to analyze the pier settlement, ground surface settlement trough, and the vertical and horizontal displacement of pile under different construction sequences in layered soil. The results show that the adjacent pile and surrounding environment are affected substantially with the change of construction sequence of twin paralleled tunnels. The construction sequence of condition (b), in which the tunnel closer to the pile foundation is first constructed and then the tunnel farther away from the pile foundation is second constructed, can reduce the settlement of pier by 13.1%, the maximum surface settlement by 7.0%, the maximum vertical displacement of pile foundation by 7.9%, and the maximum horizontal displacement by 6.9%. The present findings can provide reference for similar projects.

Shield tunnels will inevitably pass through viaduct piles at a close distance due to the extensive construction of subways and viaducts in the city. In order to understand the influence of shield tunneling on the deformation of existing pile foundation and grouting protection measures, based on an engineering case, Changsha Metro Line 5 (from South Gaoqiao station to Guitang station), a three-dimensional finite element model was established to analyze the deformation of bridge pile using grouting protection wall with different depths and shapes when the shield tunnel is under construction. The analytical results indicate that the grouting protection wall can effectively reduce the pile displacement; especially the grouting depth is 3 m below the bottom of the tunnel. Moreover, the L-shaped grouting protection wall can effectively reduce the longitudinal displacement of the piles. The present findings may provide a reference for the design and construction of shield tunnels passing through viaduct piles.

Isolation piles are widely used to control the influence of shield tunnelling on adjacent buildings as an effective protective measure. However, the restraint effect of isolation pile on surface settlement trough is rarely explored from the internal mechanism. Firstly, the restraint mechanism of isolation piles is investigated from the pile-soil-tunnel interaction mechanism. Secondly, based on the Melan solution and the Loganathan formula, the analytical solution of surface settlement trough under the influence of adjacent isolation piles is derived. Thirdly, in order to satisfy the engineering analysis scale and reflect the friction characteristics between isolation pile and soil particles simultaneously, the FDM-DEM coupling technique is introduced to establish a numerical model including discrete medium and continuum medium. Finally, the applicability and reliability of the analytical solution and the FDM-DEM coupling numerical solution are verified by comparing field measured data. The results indicate that the surface settlement trough under the influence of isolation piles will have an asymmetric distribution. Surface settlement tends to develop more to the opposite side of the tunnel when isolation piles are pre-installed on one side. The findings of the study have substantial theoretical significance and engineering reference value.

Abstract We firstly conducted a long-term in-situ field measurement at a marginal area (Hotan) of the southern Taklimakan Desert covering all four seasons. Detailed chemical characterization of dust aerosol over Hotan showed several unconventional features, including (1) ubiquity of high Na+ and Cl− abundances in the Taklimakan dust aerosol and its Cl−/Na+ ratio close to seawater; (2) high Ca content in the Taklimakan dust (7.4~8.0%) which was about two times of that in the natural crust; (3) high abundance of soluble sulfate concentrations and strong correlations between sulfate and Na+ and Cl− as well as typical mineral tracers such as Al and Ca. Our results collectively indicated that the dust aerosol from the Taklimakan Desert was characterized of evident paelo-oceanic signature as the Taklimakan Desert was found as an ocean in the ancient times from the perspective of paleogeology. It was estimated that primary sources dominated the total abundances of sulfate during the dust seasons while previous climate modeling works had seldom considered the cooling effects of sulfate from the Taklimakan Desert.

Critical limb ischemia (CLI) is a severe form of peripheral artery diseases (PAD) and seriously endangers the health of people. Therapeutic angiogenesis represents an important treatment strategy for CLI; various methods have been applied to enhance collateral circulation. However, the current development drug therapy to promote angiogenesis is limited. Resveratrol (RSV), a polyphenol compound extracted from plants, has various properties such as anti-oxidative, anti-inflammatory and anti-cancer effects. Whether RSV exerts protective effects on CLI remains elusive. In the current study, we demonstrated that oral intake of RSV significantly improved hind limb ischemia in mice, and increased the expression of phosphorylated Forkhead box class-O1 (FoxO1). RSV treatment in human umbilical vein endothelial cells (HUVECs) could increase the phosphorylation of FoxO1 and its cytoplasmic re-localization to promote angiogenesis. Then we manipulated FoxO1 in HUVECs to further verify that the effect of RSV on angiogenesis is in a FoxO1-dependent manner. Furthermore, we performed metabolomics to screen the metabolic pathways altered upon RSV intervention. We found that the pathways of pyrimidine metabolism, purine metabolism, as well as alanine, aspartate and glutamate metabolism, were highly correlated with the beneficial effects of RSV on the ischemic muscle. This study provides a novel direction for the medical therapy to CLI.

Topological interface states have attracted extensive research interest due to their unprecedented field confinement and enhancement at the interface between two one-dimensional phononic crystals with distinct topological characteristics. However, the realization of the contactless, nondestructive, and intelligent tunability of topological interface states, as the foundation for designing novel devices with unconventional functionalities, still remains a great challenge. Here, we introduce intelligent magnetoelastic materials to the topological system and realize magnetically tunable topological interface states for Lamb waves in one-dimensional phononic crystal slabs composed of alternating nonmagnetic and magnetoelastic layers. The properties of magnetoelastic layers can be tuned with noncontact, nondestruction, and intelligence by an external magnetic field. By changing the value of the external magnetic field applied on intercell and intracell magnetoelastic layers, the spatial variation of the properties of magnetoelastic layers is induced, resulting in an in situ topological phase transition. We demonstrate that topological interface states appear at the interface between two topologically different magnetoelastic phononic crystal slabs. Furthermore, based on the tunability of the external magnetic field, the existence of topological interface states can be switched and the frequency of topological interface states can be continuously tuned. In particular, the arbitrary positions of topological interface states can be dynamically achieved by varying the external magnetic field without altering the structure. Our tunable topological system can enable intelligent Lamb-wave devices with remarkable functionalities, which can lead to significant advances in intelligently controlled Lamb-wave switches, magnetically tunable frequency selectors, and magnetic control Lamb-wave communications.

As an important part of atmospheric aerosol, airborne bacteria have major impacts on human health. However, variations of airborne community structure due to human-induced activities and their possible impact on human health have not been well understood. In this study, we sampled atmospheric microbial aerosols in three Chinese cities (Shanghai, Xiamen, and Zhangzhou) with contrasting social-economic levels and analyzed the bacterial composition using high-throughput sequencing methods. A high similarity of the predominant phyla was observed in three cities but the relative abundances were quite different. At the genus level, the most dominant genus in Shanghai and Xiamen was Deinococcus while the most dominant genus in Zhangzhou was Clostridium. The different characteristics of airborne bacterial in the three cities above may be ascribed to the environmental variables affected by human over-activities such as the vehicle exhausts and coal-burning emissions in Shanghai, the tourist aggregation and construction works in Xiamen, the extensive uses of chemical fertilizers, and agricultural activities in Zhangzhou. The variation of the bacterial community and the pathogenic bacteria detected in three cities would have a potential threat to human health

Given the prejudicial environmental effects of fossil-fuel based energy production, renewable energy sources can contribute significantly to the sustainability of human society. As a clean, cost effective and inexhaustible renewable energy source, wind energy harvesting has found a wide application to replace conventional energy productions. However, concerns have been raised over the noise generated by turbine operating, which is helpful in fault diagnose but primarily identified for its adverse effects on the local ecosystems. Therefore, noise monitoring and separation is essential in wind turbine deployment. Recent developments in condition monitoring provide a solution for turbine noise and vibration analysis. However, the major component, aerodynamic noise is often distorted in modulation, which consequently affects the condition monitoring. This study is conducted to explore a novel approach to extract low-frequency elements from the aerodynamic noise background, and to improve the efficiency of online monitoring. A framework built on the spline envelope method and improved local mean decomposition has been developed for low-frequency noise extraction, and a case study with real near-field noises generated by a mountain-located wind turbine was employed to validate the proposed approach. Results indicate successful extractions with high resolution and efficiency. Findings of this research are also expected to further support the fault diagnosis and the improvement in condition monitoring of turbine systems.

Automatic estimation of salient object without any prior knowledge tends to greatly enhance many computer vision tasks. This paper proposes a novel bottom-up based framework for salient object detection by first modeling background and then separating salient objects from background. We model the background distribution based on feature clustering algorithm, which allows for fully exploiting statistical and structural information of the background. Then a coarse saliency map is generated according to the background distribution. To be more discriminative, the coarse saliency map is enhanced by a two-step refinement which is composed of edge-preserving element-level filtering and upsampling based on geodesic distance. We provide an extensive evaluation and show that our proposed method performs favorably against other outstanding methods on two most commonly used datasets. Most importantly, the proposed approach is demonstrated to be more effective in highlighting the salient object uniformly and robust to background noise.

In recent years, the outbreak of the pine shoot beetle (PSB), Tomicus spp., has caused serious shoots damage and the death of millions of trees in Yunnan pine forests in southwestern China. It is urgent to develop a convincing approach to accurately assess the shoot damage ratio (SDR) for monitoring the PSB insects at an early stage. Unmanned airborne vehicles (UAV)-based sensors, including hyperspectral imaging (HI) and lidar, have very high spatial and spectral resolutions, which are very useful to detect forest health. However, very few studies have utilized HI and lidar data to estimate SDRs and compare the predictive power for mapping PSB damage at the individual tree level. Additionally, the data fusion of HI and lidar may improve the detection accuracy, but it has not been well studied. In this study, UAV-based HI and lidar data were fused to detect PSB. We systematically evaluated the potential of a hyperspectral approach (only-HI data), a lidar approach (only-lidar data), and a combined approach (HI plus lidar data) to characterize PSB damage of individual trees using the Random Forest (RF) algorithm, separately. The most innovative point is the proposed new method to extract the three dimensional (3D) shadow distribution of each tree crown based on a lidar point cloud and the 3D radiative transfer model RAPID. The results show that: (1) for the accuracy of estimating the SDR of individual trees, the lidar approach (R2 = 0.69, RMSE = 12.28%) performed better than hyperspectral approach (R2 = 0.67, RMSE = 15.87%), and in addition, it was useful to detect dead trees with an accuracy of 70%; (2) the combined approach has the highest accuracy (R2 = 0.83, RMSE = 9.93%) for mapping PSB damage degrees; and (3) when combining HI and lidar data to predict SDRs, two variables have the most contributions, which are the leaf chlorophyll content (Cab) derived from hyperspectral data and the return intensity of the top of shaded crown (Int_Shd_top) from lidar metrics. This study confirms the high possibility to accurately predict SDRs at individual tree level if combining HI and lidar data. The 3D radiative transfer model can determine the 3D crown shadows from lidar, which is a key information to combine HI and lidar. Therefore, our study provided a guidance to combine the advantages of hyperspectral and lidar data to accurately measure the health of individual trees, enabling us to prioritize areas for forest health promotion. This method may also be used for other 3D land surfaces, like urban areas.

In this work, we report on the design of a wide-band digital lock-in amplifier (DLIA) of up to 65 MHz and its application for electrical impedance measurements in microfluidic devices. The DLIA is comprised of several dedicated technologies. First, it features a fully differential analog circuit, which includes a preamplifier with a low input noise of 4.4 nV/√Hz, a programmable-gain amplifier with a gain of 52 dB, and an anti-aliasing, fully differential low-pass filter with −76 dB stop-band attenuation. Second, the DLIA has an all-digital phase lock loop, which features a phase deviation of less than 0.02° throughout the frequency range. The phase lock loop utilizes an equally accurate period-frequency measurement, with a sub-ppm precision of frequency detection. Third, a modified clock link is implemented in the DLIA to improve the signal-to-noise ratio of the analog-to-digital converter affected by clock jitter of up to 20 dBc. A series of measurements were performed to characterize the DLIA, and the results showed an accurate performance. Additionally, impedance measurements of standard-size microparticles were performed by frequency sweep from 300 kHz to 30 MHz, using the DLIA in a microfluidic device. Different diameters of microparticle could be accurately distinguished according to the relative impedance at 2.5 MHz. The results confirm the promising applications of the DLIA in microfluidic electrical impedance measurements.

Gas flaring during oil extraction over the Arctic region is the primary source of warming-inducing aerosols (e.g. black carbon (BC)) with a strong potential to affect regional climate change. Despite continual BC emissions near the Arctic Ocean via gas flaring, the climatic impact of BC related to gas flaring remains uncertain. Here, we present simulations of potential gas flaring using an earth system model with comprehensive aerosol physics to show that increases in BC from gas flaring can potentially explain a significant fraction of Arctic warming. BC emissions from gas flaring over high latitudes contribute to locally confined warming over the source region, especially during the Arctic spring through BC-induced local albedo reduction. This local warming invokes remote and temporally lagging sea-ice melting feedback processes over the Arctic Ocean during winter. Our findings imply that a regional change in anthropogenic aerosol forcing is capable of changing Arctic temperatures in regions far from the aerosol source via time-lagged, sea-ice-related Arctic physical processes. We suggest that both energy consumption and production processes can increase Arctic warming.

Generation of ∼2200 Sanger sequence reads or ∼10,000 454 reads for seven Lour. DNA samples (five species) allowed identification of the highly repetitive DNA content in these genomes. The 14 most abundant repeats in these species were identified and partially assembled. Annotation indicated that they represent nine long terminal repeat (LTR) retrotransposon families, three tandem satellite repeats, one long interspersed element (LINE) retroelement, and one DNA transposon. All of these repeats are most closely related to repetitive elements in other closely related plants and are not products of horizontal transfer from their host species. These repeats were differentially abundant in each species, with the LTR retrotransposons and satellite repeats most responsible for variation in genome size. Each species had some repetitive elements that were more abundant and some less abundant than the other species examined, indicating that no single element or any unilateral growth or decrease trend in genome behavior was responsible for variation in genome size and composition. Genome sizes were determined by flow sorting, and the values of 615 Mb [ (L.) Kuntze], 1330 Mb [ (Willd.) Vatke], 1425 Mb [ (Delile) Benth.] and 2460 Mb ( Benth.) suggest a ploidy series, a prediction supported by repetitive DNA sequence analysis. Phylogenetic analysis using six chloroplast loci indicated the ancestral relationships of the five most agriculturally important species, with the unexpected result that the one parasite of dicotyledonous plants () was found to be more closely related to some of the grass parasites than many of the grass parasites are to each other.