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Objective The molecular mechanism that triggers polycystic ovary syndrome (PCOS) is mysterious. Abnormal development of ovarian granulosa cells(GCs) is one of the causes of PCOSMethods The study was carried out by using RNA-seq to detect the different gene expression levels in ovarian GCs between 3 patients with PCOS and 4 normal controls. To further verify the above results, GCs from 22 patients with PCOS and 21 controls with normal ovulation were collected to perform the RT-PCR analysisResults The results found Hedgehog signaling pathway(Hh) members, Ihh and Ptch2 were abnormally highly expressed in the PT. The qPCR results also indicated that the expression levels of other Hh signaling pathway downstream members, Ptch1, Gli1, and Gli2 in the PCOS group (PT) were significantly higher than those in the control group (NT). Besides, the expression of TNF-α mRNA in PCOS patients was higher than that in the control group. Finally, the Hh signaling pathway inhibitor, cyclopamine, can decrease the apoptosis of PCOS ovarian granulosa cellsConclusions These results suggest that abnormally activated Hh signaling pathway, especially Ihh signal, may have a profound influence on PCOS.

In the present work, we intended to discuss how to achieve real-time structural topology optimization with a significantly higher accuracy. Ideally, with an adequate computation time cost requirement, the topology optimization design problem can be formulated and solved using a direct topology optimization process, such as moving morphable component (MMC). However, the direct optimization approaches are estimated over hundreds and even thousands of design iterations, costing an innegligible computational time. There is, therefore, a need for a different approach that will be able to optimize the topologies accurately and in real-time. In this study, a topology optimization mathematical model based on a convolutional neural network is developed to replace the iterative calculations in direct topology optimization methods. The network is constructed by introducing residual learning and attention schemes into the U-Net framework. The network is trained through a dataset generated from direct MMC method. By carefully tuning the parameters during the training stage of the neural network, the network can generate topologies in real-time without any further need of the direct MMC method. Compared with state-of-the-art machine learning driven topology optimization approaches, our model achieves a significantly higher accuracy.

BACKGROUND: Effective anticoagulation is a prerequisite of continuous renal replacement therapy (CRRT). During CRRT, prolonged anticoagulant therapy should be administered to prevent extracorporeal clotting. The purpose of our study was to evaluate whether a low concentration of plasma trisodium citrate (TCA) was effective as an anticoagulation treatment for continuous veno-venous hemofiltration (CVVH). We also retrospectively analyzed the complications of regional citrate anticoagulation (RCA) in our hospital. METHODS: We conducted this single-center retrospective study at a tertiary academic hospital. The study period was from July 1, 2019 to January 1, 2021. CVVH using the RCA protocol during the study period was performed. The RCA protocol and complications were included and analyzed. The concentrations of citrate in the blood and plasma were calculated. RESULTS: In the current study, we used low-dose TCA as an anticoagulant in 288 CVVH runs for 78 patients. The median whole blood and plasma citrate concentrations were 2.13 mmol/L and 2.84 mmol/L, respectively. Although only a low concentration of citrate was used, RCA achieved expected anticoagulation and ensured the life span of the hemofilter during CVVH therapy. Although hypocalcemia was common during RCA, serious consequences could be prevented by timely adjustment of the protocol. Citrate intoxication was rare in patients without relative contraindications for citric acid. We did not find RCA-associated hypernatremia. CONCLUSIONS: We recommend the use of a low concentration of TCA (2.5-3.0 mmol/L in plasma) in extracorporeal solution in the RCA protocol. Although RCA may cause some complications, serious complications can be prevented. Mild hypocalcemia and transient metabolic alkalosis can be corrected in a timely manner. We do not believe hypernatremia is a complication of RCA if the RCA protocol is appropriately applied.

It is hypothesized that vitamin B12 may prevent tumor initiation during the early stage of carcinogenesis such as esophageal precancerous lesions (EPL), whereas an excessive level may promote tumor progression during the later stages of carcinogenesis. This study aimed to determine the role of vitamin B12 in EPL by detecting vitamin B12-related markers in both blood and diet. This case–control study based on 3-day duplicated diet samples was conducted in a high-risk area of Huai'an, China. A 100 EPL cases and 100 healthy controls matched by gender, age (± 2 years) and villages were included. Dietary intake of vitamin B12 and cobalt, plasma cobalt level, the serum levels of vitamin B12 and transcobalamin II (TC II) were quantitatively analyzed. Dietary vitamin B12 intake (p for trend = 0.384) and plasma cobalt level (p for trend = 0.253) were not associated with EPL risk, but high dietary cobalt intake (p for trend = 0.034), increased serum levels of vitamin B12 (p for trend = 0.036) and TC II (p for trend

Vienna rectifiers are widely used because of their advantages of high power-factor, low voltage stress on the power semiconductor switches, high power density, stable output voltage, low current harmonic content, and good economics. And gradually applied to the front stage AC/DC part of the electric vehicle charger. Traditional Vienna rectifier control methods include double closed-loop control, hysteresis current control, and Sliding mode variable structure control strategy, but all strategies usually regulate DC-Voltage and keep the unity power factor. However, if it is used for the interface part of the electric vehicle charger with frequent load switching, it is necessary not only to ensure the stability of the output voltage and low THD of the current, but also to be able to respond to the fluctuation of the voltage and frequency of the power system and improve the inertia and damping at the interface. Thereby, the stability of the power grid is improved to a certain extent, and fast-charging is ensured while being grid-friendly. Therefore, this paper proposes to apply the virtual synchronous motor control to the Vienna rectifier to improve the adaptability of the grid to the large-scale access of electric vehicles. Build the topology of the Vienna rectifier in simlink and the modulation method using SVPWM to build a complete model on the basis of VSM.

Background and Aims Cigarette smoking worsens prognosis of Crohn’s disease [CD]. We conducted a systematic review and meta-analysis to examine the association between smoking and induction of clinical response or remission with anti-tumour necrosis factor [TNF] therapy. Methods MEDLINE, EMBASE, PubMed, and Cochrane CENTRAL [June 2019] were searched for studies reporting the effect of smoking on short-term clinical response and remission to anti-TNF therapy [≤16 weeks following the first treatment] in patients with CD. Risk ratios [RR] with 95% confidence intervals [CI] were calculated using random-effects models. Results Eighteen observational studies and three randomised controlled trials [RCT] were included. Current smokers and non-smokers [never or former] had similar rates of clinical response [observational studies RR: 0.96; 95% CI: 0.88, 1.05; RCTs RR: 1.09; 95% CI: 0.84, 1.41]. When restricted to studies clearly defining the smoking exposure, smokers treated with anti-TNF were less likely to achieve clinical response than non-smokers [smokers defined as having ≥5 cigarettes/day for ≥6 months RR: 0.63; 95% CI: 0.48, 0.83; lifetime never smokers vs ever smokers excluding former smokers RR: 0.81; 95% CI: 0.71, 0.93]. Current smokers were also less likely to achieve clinical remission in observational studies [RR: 0.75; 95% CI: 0.57, 0.98], though this association was not seen in RCTs [RR: 1.04; 95% CI: 0.89, 1.21]. Conclusions Smoking is significantly associated with a reduction in the ability of infliximab or adalimumab to induce short-term clinical response and remission when pooling studies where smoking status was clearly defined. When patients with CD are treated with highly effective therapy, including anti-TNF agents, concurrent smoking cessation may improve clinical outcomes.

To avoid crosstalk and suppress leakage currents in resistive random access memories (RRAMs), a resistive switch and a current rectifier (diode) are usually combined in series in a one diode–one resistor (1D–1R) RRAM. However, this complicates the design of next-generation RRAM, increases the footprint of devices and increases the operating voltage as the potential drops over two consecutive junctions1. Here, we report a molecular tunnel junction based on molecules that provide an unprecedented dual functionality of diode and variable resistor, resulting in a molecular-scale 1D–1R RRAM with a current rectification ratio of 2.5 × 104 and resistive on/off ratio of 6.7 × 103, and a low drive voltage of 0.89 V. The switching relies on dimerization of redox units, resulting in hybridization of molecular orbitals accompanied by directional ion migration. This electric-field-driven molecular switch operating in the tunnelling regime enables a class of molecular devices where multiple electronic functions are preprogrammed inside a single molecular layer with a thickness of only 2 nm. A multifunctional molecule acting both as diode and variable resistor is used to fabricate compact molecular switches with a thickness of 2 nm, good current rectification and resistive on/off ratio, and requiring a drive voltage as low as 0.89 V.

Endometriosis is a common gynecological disease affecting up to 10% of women at reproductive age. Prior combined studies implied that MYH8 mutations might exist in endometriosis. Here, 152 Han Chinese samples with ovarian endometriosis were analyzed for the presence of MYH8 mutations. Two heterozygous missense mutations in the MYH8 gene, c.1441A C (p.I481L) and c.4057G A (p.E1353K), were identified in our samples. These mutations were neither found in public databases nor detected in our 485 Han Chinese control women without endometriosis. The p.I481L-mutated sample belonged to 34-year-old, who had slightly elevated serum CA 125 (42.09 U/mL); while the sample with p.E1353K mutation belonged to 25 years old, who had a markedly increased serum CA125 (89.86 U/mL). The evolutionary conservation analysis results suggested that these MYH8 mutations caused highly conserved amino acid substitutions among vertebrate species. Both the mutations were predicted to be 'disease causing' by MutationTaster and SIFT programs. In addition, no association was observed between MYH8 mutations and the available clinical data. In summary, the present study identified two novel potential pathogenic mutations in the MYH8 gene in samples with ovarian endometriosis for the first time, implying that MYH8 mutations might play a positive role in the pathogenesis of endometriosis.

Background Non-alcoholic fatty liver disease (NAFLD) is currently the major cause of chronic liver disease globally. Bile acids (BAs) have emerged as relevant signaling molecules that are associated with NAFLD development. This study was aimed to examine the association of serum total bile acids (TBAs) with NAFLD in a large population of Chinese subjects. Methods This cross sectional study recruited 152,336 participants from the Second Xiangya Hospital, China. NAFLD was diagnosed based on the presence of hepatic steatosis on ultrasonography, without significant alcohol consumption and other known causes for chronic liver disease. A multivariate logistic regression model was used to test for the association of serum TBAs with NAFLD, adjusting for conventional risk factors of NAFLD. Results A total of 27.4% of the participants had NAFLD. Patients with NAFLD had slightly higher TBA levels than those without, 3.4 vs. 3.0 μmol/L (p p = 0.797). Conclusions We found that the serum TBA levels were not associated with NAFLD. Future studies in a large population, focusing on serum BA composition may improve the understating of the role of BAs in NAFLD.

To evaluate the effects of metformin on serum lipid profiles in nondiabetic adults through a comprehensive meta-analysis. In the present meta-analysis, randomized and controlled trials were collected by searching PubMed, Embase, and Cochrane Libraries from inception to April 2019. Compared with placebos, the effects of metformin treatment on lipid profiles in nondiabetic adults were evaluated. Forty-seven studies from 45 articles including 5731 participants were enrolled. Pooled results showed that metformin had significant effects on total cholesterol (mean change −6.57 mg/dl; 95% CI −9.66, −3.47; P = 0.000) and LDL-c (mean change −4.69 mg/dl; 95% CI −7.38, −2.00; P = 0.001), but insignificant effects on HDL-c (mean change −4.33 mg/dl; 95% CI −9.62, 0.96; P = 0.109) and triglyceride (mean change −0.85 mg/dl; 95% CI −0.36, 2.06; P = 0.169). Significant heterogeneities were found for all lipid profiles (HDL-c = 85.5%; LDL-c = 59.9%; total cholesterol = 75.3% and triglyceride = 67.1%). Different from the pooled data, in a subgroup analysis, the effect of metformin on triglyceride in patients with polycystic ovarian syndrome (PCOS) was significant with a mean reduction of 8.15 mg/dl. In addition, sensitivity analysis showed that the pooled effects of metformin on serum lipid profiles were stable. Publication bias derived from funnel plots or Begg’s tests (P = 0.933, 0.860, 0.904, and 0.567 for HDL-c, LDL-c, total cholesterol, and triglyceride, respectively) was not significant. This meta-analysis revealed that metformin could reduce total cholesterol and LDL-c in nondiabetic adults. In addition, metformin might exert a triglyceride-lowering effect in nondiabetics with PCOS status.

Phase-shifting 3D profilometry is of high precision, but its performance could be far below expectations due to its long exposure time in the measurement of dynamic objects, especially human faces. In this article, a new idea is proposed to improve the measuring speed by providing reference derived from the statistical characteristics of human faces for the reconstruction of faces measured. During the measurement, no Gray code or low-frequency fringe is required, which reduces the number of patterns projected and sharply shortens the measuring time. Assisted by face detection and point cloud clustering, several candidate faces of different orders can be generated from the wrapped phase. Afterwards, the most probable candidate is selected according to the probability model of human face to obtain the correct result. Furthermore, the applicable conditions of our method have been analyzed, and the validity has been proved by experiments on actual human faces as well.

At various temperatures, ranging from 25°C to 50°C, we characterized two types of photodetectors based on surface-state absorption in silicon: (1) contactless integrated photonic probes (CLIPPs) and (2) normal-incidence photoconductors. Both types of photodetectors exhibited temperature-dependent AC admittance without illumination. With illumination at telecommunication wavelengths near 1550 nm, in the temperature range we measured, the photoresponse of CLIPPs, i.e., the variance of admittance due to illumination, was relatively insensitive to temperature changes; in comparison, the temperature dependence of the photoresponse of normal-incidence photoconductors was more pronounced—their responsivity increased as temperature raised.

As a new service-oriented manufacturing paradigm, cloud manufacturing (CMfg) realizes the optimal allocation of resources in the product manufacturing process through the network. Task decomposition is a key problem of the CMfg system for resource scheduling. A high-quality task decomposition method can shorten product development time, reduce costs for resource service providers, and provide technical support for the application of CMfg. However, a cloud manufacturing system has to manage the allocation the correct amount of manufacturing resources, complex production processes, and highly dynamic production environments. At the same time, the tasks issued by service demanders are usually asymmetric and tightly coupled. We solve the complex task decomposition problem by using the traditional methods, that are hard to complete in CMfg. To overcome the shortcomings of CMfg, this paper proposed a task decomposition method based on the cloud platform. For achieving modular production, this approach creatively divides the product production process into four stages: design, manufacturing, transportation, and maintenance. Then a hybrid method, which combines with depth-first search algorithm, fast modular optimization algorithm, and artificial bee colony algorithm, is introduced. The method can obtain a multi-stage task optimization decomposition plan in CMfg. Simulation results demonstrate the proposed method can achieve complex task optimization decomposition in a CMfg environment.

As a marker of malignant tumors, miRNA is closely related to the occurrence and metastasis of tumors. How to achieve rapid and sensitive real-time detection is important for clinical prevention and treatment of cancer. In this study, an intelligent detection platform based on smartphone image processing technology made point-of-care testing a reality. This new smart approach could detect multiple targets simultaneously and sensitively. Hydrogel microparticles of different coding modes (shapes, numbers) were prepared by flow lithography to detect different miRNAs. After sandwich immunoassays, different shapes of hydrogels showed different fluorescence intensities depending on their targets. Images were captured by a smartphone and then analyzed by image recognition processing software installed on the smartphone. The concentration of miRNA was obtained within 10 s. The entire reaction process did not exceed 2 h. This intelligent and portable detection platform for miRNAs was reliable and the limit of detection reached the femtomole level. This work provided a demonstration of intelligent, portable, real-time detection of tumor markers.

How to create a portable and quick way to detect multiple coexisting toxins is closely related to everyone's health. In this paper, we have established a real-time mycotoxin detection system that combined shape-encoded hydrogel particle preparation technology and image processing technology with smartphone portable devices. First, hydrogel microparticles containing a specific recognition toxin aptamer were programmable synthesized by stop-flow lithography. The hydrogel particles prepared by us had clear, variable signals and high coding capacity. Then, the indirect competitive detection based on aptamers was simple and rapid; the total reaction time was no more than 1 h 45 min and the image processing process was no more than 10 s. Finally, images could be captured by cameras on portable devices and smartphones. The self-built Android app that used the image recognition program installed on the smartphone would analyze the image and return the results in real time. The results showed that the detection limit reached 0.1 ng/mL, which was lower than the standard. In summary, this platform provides a fast, portable, high-throughput detection solution for real-time detection of mycotoxins, with excellent application prospects.

We report on a normal-incidence infrared photoconductor based on surface-state absorption in silicon, featuring broad-spectrum photoresponse, sensitivity of − 46 d B m enabled by lock-in readouts, CMOS-compatible fabrication process, and near transparency to incident light. Its applications in infrared imaging and measuring the beam profiles are demonstrated and presented. Future extension from this single-pixel element to a many-pixel camera is discussed.

Natural killer/T-cell (NK/T-cell) lymphoma is a rare-type non-Hodgkin lymphoma derived from NK cells or cytotoxic T cells. Here, we present a case of a 40-year-old woman who experienced quick-developed global heart failure and then was diagnosed with NK/T-cell lymphoma through lymphoid biopsy. Neither transthoracic echocardiography nor any radiological images detected a mass in her heart or pericardium. Elevated plasma troponin level and diffused patchy areas of gadolinium late enhancement on cardiac magnetic resonance were compatible with myocarditis. Considering the persistently elevated cytokine level, systemic inflammation symptoms, acute respiratory distress syndrome, and cardiac dysfunction, a cytokine storm secondary to NK/T-cell lymphoma was considered. Due to the refractory malignant arrhythmia, the patient died soon after being admitted to our hospital.

In this paper, we propose a simple but effective encoder-decoder based network for fast and accurate depth estimation on mobile devices. Unlike other depth estimation methods using heavy context modeling modules, the encoder with a fast downsampling strategy is employed to obtain sufficient receptive field and contexts at a faster rate. To obtain dense prediction, a light decoder is adopted to recover back to the original resolution. Additionally, to improve the representative ability of the light network, we introduce a teacher-student strategy. It relies on a distillation process ensuring that the student (the proposed light network) learns from the teacher. The proposed method achieves a good trade-off between latency and accuracy. We evaluated the proposed algorithm on the MAI 2021 Monocular Depth Estimation Challenge and achieved a score of 129.41, ranked the first place, which wins the second by a large margin (129.41 v.s. 14.51). More specifically, the proposed method achieves a si-RMSE score of 0.28 with 97 ms on the Raspberry Pi 4.

Ischemic stroke is a common neurological disease that can lead to mortality and disability. The current curative effect remains unsatisfactory because drug accumulation in the diseased areas is insufficient as a result of the unique blood–brain barrier. Therefore, much attention has been paid to develop a novel therapeutic compound, paeonol-ozagrel conjugate (POC), for ischemic stroke. Then, POC was successfully synthesized by conjugating of paeonol and ozagrel as mutual prodrug. A series of in vitro characterizations and evaluations, including high - resolution mass spectroscopy, nuclear magnetic resonance spectroscopy, partition coefficient, and assessment of cytotoxicity against PC12 cells, were performed. Pharmacokinetic study demonstrated POC is eliminated quickly (t1/2 = 53.46 ± 19.64 min), which supported a short dosing interval. The neurological score, infarct volume, histopathological changes, oxidative stress, inflammatory cytokines levels, and TXA2 levels also were evaluated in vivo in middle cerebral artery occlusion (MCAO) rats. All results showed that POC had a significant curative and therapeutic effect on ischemic stroke, as evaluated by the middle cerebral artery occlusion. Overall, POC can be expected to become a new drug candidate for the treatment of ischemic stroke.

Based on design ideas of reconfigurable modular robotic arm, a reconfigurable modular robotic arm satisfying the strategic mission of China’s space station is studied. Based on the manipulator configuration of the space screw operation task, the kinematics and dynamics models for the non-redundant 6-DOF configuration and the redundant 9-DOF manipulator configuration containing linear modules are established, and the linear type is compared and analyzed. The influence of the linear module on the kinematics and dynamics of each manipulator configuration is compared and analyzed.

We characterized contactless integrated photonic probes on silicon waveguides in a temperature range from 293 K down to 12 K, and observed the oscillation of admittance and decrease of the sensitivity.

Depth estimation is an important computer vision problem with many practical applications to mobile devices. While many solutions have been proposed for this task, they are usually very computationally expensive and thus are not applicable for on-device inference. To address this problem, we introduce the first Mobile AI challenge, where the target is to develop an end-to-end deep learning-based depth estimation solutions that can demonstrate a nearly real-time performance on smartphones and IoT platforms. For this, the participants were provided with a new large-scale dataset containing RGB-depth image pairs obtained with a dedicated stereo ZED camera producing high-resolution depth maps for objects located at up to 50 meters. The runtime of all models was evaluated on the popular Raspberry Pi 4 platform with a mobile ARM-based Broadcom chipset. The proposed solutions can generate VGA resolution depth maps at up to 10 FPS on the Raspberry Pi 4 while achieving high fidelity results, and are compatible with any Android or Linux-based mobile devices. A detailed description of all models developed in the challenge is provided in this paper., Comment: Mobile AI 2021 Workshop and Challenges: https://ai-benchmark.com/workshops/mai/2021/. arXiv admin note: text overlap with arXiv:2105.07809

As a homologous material of both medicine and food, licorice is a famous traditional Chinese medicine. In the application process, different origins and different extraction methods have an impact on the intrinsic quality of licorice. In order to ensure the intrinsic quality of commercially available licorice products, and to explore the influence of origin and extraction methods on the quality of licorice, we put forward a simple and effective discriminatory method for “chemometrics analysis-based fingerprint establishment”. First, fingerprints of licorice ethanol extraction (LEE) and licorice water extraction (LWE) were established. Then, similarity analysis (SA), hierarchical clustering analysis (HCA), principal component analysis (PCA) and other chemometrics methods were used to select qualitative and quantitative markers. Besides, the quantitative determination of 7 compounds of licorice with statistical significance was carried out, which provided accurate and informative data for quality evaluation. Finally, discriminant analysis was used to trace the origin of licorice.

Point clouds-based networks have achieved great attention in 3D object classification, segmentation, and indoor scene semantic parsing, but its application to 3D face recognition is still underdeveloped owing to two main reasons: lack of large-scale 3D facial data and absence of deep neural network that can directly extract discriminative face representations from point clouds. To address these two problems, a PointNet++ based network is proposed in this paper to extract face features directly from point clouds facial scans and a statistical 3D Morphable Model based 3D face synthesizing strategy is established to generate large-scale unreal facial scans to train the proposed network from scratch. A curvature-aware point sampling technique is proposed to hierarchically down-sample feature-sensitive points which are crucial to pass and aggregate discriminative facial features deeply. In addition, a novel 3D face transfer learning method is proposed to ease the domain discrepancy between synthetic and ‘in-the-wild’ faces. Experimental results on two public 3D face benchmarks show that the network trained only on synthesized data can also be well generalized to ‘in-the-wild’ 3D face recognition. Our method achieves the state-of-the-art results by achieving an overall rank-1 identification rate of 99.46% and 99.65% on FRGCv2 and Bosphorus, respectively. Further, we evaluate on a self-collected dataset to demonstrate the robustness and application potential of our method.

Background It is well known that angiopoietin-like protein 8 (ANGPTL8) exerts its effects on lipid metabolism through the inhibition of lipoprotein lipase and subsequent elevation of plasma triglyceride. However, it is not clear whether ANGPTL8 could affect lipid metabolism via other pathways. The study was aimed to investigate the effects of ANGPTL8 on the function of high-density lipoprotein (HDL), which plays a protective role in atherosclerosis progression. Methods Two hundred and ten subjects were recruited. Plasma ANGPTL8 was measured by enzyme-linked immunosorbent assays. Cholesterol efflux capacity was chosen as the biomarker of HDL function and measured via H3-cholesterol loading THP-1 cell models. Results ANGPTL8 exhibited no significant difference between CAD group and nonCAD group, but ANGPTL8 in DM group was significantly higher than that in the nonDM group [568.3 (406.2–836.8) vs 458.2 (356.8–755.6), P = 0.023]. Compared to controls, subjects in CAD group and DM group exhibited significantly lower cholesterol efflux capacity [CAD: 14.58 ± 2.06 vs 12.51 ± 2.83%, P

The SARS-CoV-2 virus has infected hundreds of millions of people and caused millions of deaths worldwide. Reports of racial and ethnic disparities regarding both rates of infection of the SARS-CoV-2 virus and morbidity of the coronavirus disease-19 (COVID-19) contain profound differences depending on the population. A previous study found an independent and positive association between the Black/African American race and positive COVID-19 testing results in Milwaukee County, WI, while adjusting for age, sex, socioeconomic status, and comorbidities (Munoz-Price. et al, 2020, JAMA Network). Our previous study revealed that patients with COVID-19 who developed hypertriglyceridemia during their hospitalization were associated with a 2.3 times higher mortality rate, after adjusting for age, gender, body mass index, history of hypertension and diabetes (Dai. et al, 2021, manuscript accepted by Journal of Clinical Lipidology). Additionally, adverse blood clotting events is one of the major causes of death for patients with COVID-19. In this study, we investigated the correlation between racial/ethnic groups and mortality, along with potential correlations between hypertriglyceridemia and adverse blood clotting events in hospitalized patients with COVID-19 (ICD10CM:U07.1). De-identified data from 1,441 hospitalized patients diagnosed with COVID-19 between March 2020 and June 2021 were extracted using the Medical College of Wisconsin Clinical Research Data Warehouse. Vital, demographic, and diagnostic information were used for the statistical analysis, specifically: age, gender, body mass index (BMI), race/ethnicity, thrombosis diagnosis and laboratory test results for triglyceride. The thrombotic events included were presence of disseminated intravascular coagulopathy, deep vein thrombosis, myocardial infarction, pulmonary embolism, and stroke diagnosed during their hospitalization. Hypertriglyceridemia was characterized as triglyceride levels greater than 150 mg/dL, with a baseline variable being the first occurrence of hypertriglyceridemia (baseline), and the peak variable being the highest manifestation of hypertriglyceridemia during hospitalization (peak). A binary logistic regression model showed that non-white Hispanic and Asian patients both had a higher correlation with mortality than white patients, with odds ratios (OR) of 4.1 [95% CI (2.2-7.9), p < 0.001] and 4.2 [95% CI (1.8-9.8), p < 0.001], respectively, after adjusting for age, BMI, and sex (Figure A). Additionally, the regression analysis showed that peak hypertriglyceridemia developed during hospitalization was correlated with a 1.8 times higher mortality in the entire inpatient cohort [95% CI (1.2-2.9), p < 0.01], after adjusting for age, sex, and BMI and independent of obesity. Furthermore, myocardial infarction [OR = 1.5, 95% CI (1.-2.5), p < 0.05] and pulmonary embolism [OR = 2.0, 95% CI (1.1-4.1), p < 0.05] were also correlated with a higher mortality, after adjusting for age, BMI, and sex (Figure B). The peak hypertriglyceridemia developed during hospitalization correlates with the incidence of thrombotic events with a borderline significance [OR= 1.5, 95% CI (0.9-2.1), p = 0.05] after adjusting for BMI, age, and sex. Further analysis revealed that non-white Hispanic patients had the highest frequencies of peak hypertriglyceridemia (triglyceride > 150 mg/dL) occurrence during hospitalization than the other race/ethnicity groups (Figure C). On the other hand, 22% of non-white Hispanics had at least one diagnosis of thrombotic event during hospitalization, which was the lowest incidence of thrombosis among all race/ethnicity groups (Figure D). In our current retrospective study of inpatients with COVID-19, race/ethnicity, peak hypertriglyceridemia developed during hospitalization, and thrombosis are independently associated with mortality. The peak hypertriglyceridemia developed during hospitalization is positively correlated with the incidence of thrombosis. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Free-floating bike-sharing systems have rapidly gained popularity as a viable short-distance transportation mode. As users play a significant role in the movement of the bikes in such a system, the basis for evaluating bike usage is to predict the gap between the locking and unlocking behaviour in a specified grid, which is defined as the inflow and outflow gap. The Spatial-Temporal grid size, including its time and space dimensions, has a significant impact on the microscopic forecasting of the inflow and outflow gap. In this study, a flexible framework for testing the impact of the grid on inflow and outflow gap predictions is proposed. The performance of four algorithms, i.e., linear regression, support vector regression, random forest, and gradient boost machine, was compared for different grid sizes based on the dataset provided by the Shanghai Big Data Joint Innovation Laboratory. The results show that the proposed framework can be used to evaluate the impact of grid size on microscopic forecasts. A smaller grid helps to achieve better model prediction results, but it also involves longer calculation time. Comparisons of the four algorithms show that the larger the spatial dimensions of the grid, the worse the predicted results. Excluding random forest, the other algorithms tend to achieve better results when the temporal dimension of the grid is larger. The gradient boost machine algorithm provides the best results in most scenarios; the optimal spatial-temporal grid side length is 200 m, 24 h with 5 by 5 grid combination. Dispatchers or analysts in bike-sharing companies can refer to the proposed framework to select the bike delivery scale and management scope. In addition, this study will help researchers and practitioners quickly select the appropriate grid size and machine learning algorithms for bike-sharing analysis.

The composition of worldwide energy consumption is undergoing tremendous changes due to the consumption of non-renewable fossil energy and emerging global warming issues. Renewable energy is now the focus of energy development to replace traditional fossil energy. Energy storage system (ESS) is playing a vital role in power system operations for smoothing the intermittency of renewable energy generation and enhancing the system stability. We divide ESS technologies into five categories, mainly covering their development history, performance characteristics, and advanced materials. Biomass storage and gas storage are also discussed, which are not considered in most reviews. After detailed research, the rapid development of each technology in recent years is introduced, and some representative research works are surveyed. We comprehensively summarized the advantages and disadvantages of various ESS technologies and presented several evaluation indicators for quantitative analysis. Hybrid ESS is also considered based on the complex market demand. Then, we investigate the applications of various ESS technologies as short-term, medium-term, and long-term storages in power systems, covering the power generation, transmission and distribution, and end-user. Finally, this paper reviews global developing trends, and identifies critical challenges and promising opportunities.

The long-lived latent HIV-1 reservoir is the major barrier for complete cure of Acquired Immune Deficiency Syndrome (AIDS). Here we report that a novel bromodomain and extraterminal domain (BET) inhibitor bromosporine which can broadly target BETs, is able to potently reactivate HIV-1 replication in different latency models alone and more powerful when combined with prostratin or TNF-α. Furthermore, the treatment with bromosporine induced HIV-1 full-length transcripts in resting CD4+ T cells from infected individuals with suppressive antiretroviral therapy (ART) ex vivo, with no obvious cytotoxicity or global activation of T cell. Finally, our data suggest that Tat plays a critical role in the bromosporine-mediated reactivation of latent HIV-1, which involved the increase of CDK9 T-loop phosphorylation. In summary, we found that the BET inhibitor bromosporine, alone or with other activators, might be a candidate for future HIV-1 eradication strategies.

Memory capacity in GPGPUs is a major challenge for data-intensive applications with their ever increasing memory requirement. To fit a workload into the limited GPU memory space, a programmer needs to manually divide the workload by tiling the working set and perform user-level data migration. To relieve the programmer from this burden, Unified Virtual Memory (UVM) was developed to support on-demand paging and migration, transparent to the user. It further takes care of the memory over-subscription issue by automatically performing page replacement in an oversubscribed GPU memory situation. However, we found that naive handling of page faults can cause orders of magnitude slowdown in performance. Moreover, we observed that although prefetching of data from CPU to GPU can hide the page fault latency, the difference among various prefetching mechanisms can lead to drastically different performance results. To this end, we performed extensive experiments on GeForceGTX 1080ti GPUs with PCI-e 3.0 16x to discover that there exists an effective prefetch mechanism to enhance locality in GPU memory. However, as the GPU memory is filled to its capacity, such prefetching mechanism quickly proves to be counterproductive due to locality unaware eviction policy. This necessitates the design of new eviction policies that are aware of the hardware prefetcher semantics. We propose two new programmer-agnostic, locality-aware pre-eviction policies which leverage the mechanics of existing hardware prefetcher and thus incur no additional implementation and performance overhead. We demonstrate that combining the proposed tree-based pre-eviction policy with the hardware prefetcher provides an average of 93% and 18.5% performance speed-up compared to LRU based 4KB and 2MB page replacement strategies, respectively. We further examine the memory access pattern of GPU workloads under consideration to analyze the achieved performance speed-up.

Nuchal Translucency (NT) in ultrasound images are commonly used to detect genetic disorder in fetuses. Due to lack of distinctive local features around NT region, existing NT detection methods first model some other prominent body parts, such as the fetal head. However, explicit detection of other body parts requires additional annotation, development and processing costs. It may also introduce cascading error in cases of unclear head location or non-standard head-NT relations. In this work, we design a convolutional neural network with fully connected layers to detect NT region directly. Furthermore, we apply U-Net with customized architecture and loss function to obtain precise NT segmentation. Finally, NT thickness measurement is calculated using principal component analysis. A dataset containing 770 ultrasound images were used for training and evaluation. Extensive experimental results show that our direct approach automatically detects and measures NT with promising performance.

As a product of the shared economy, online car-hailing platforms can be used effectively to help maximize resources and alleviate traffic congestion. The driver's behavior is characterized by his or her driving style and plays an important role in traffic safety. This paper proposes a novel framework to classify driving styles (defined as aggressive, normal, and cautious) based on online car-hailing data to investigate the distinct characteristics of drivers when performing various driving tasks (defined as cruising, ride requests, and drop-off) and undergoing certain maneuvers (defined as turning, acceleration, and deceleration). The proposed model is constructed based on the detection and classification of driving maneuvers using a threshold-based endpoint detection approach, principal component analysis, and k-means clustering. The driving styles that the driver exhibits for the different driving tasks are compared and analyzed based on the classified maneuvers. The empirical results for Nanjing, China demonstrate that the proposed framework can detect driving maneuvers and classify driving styles accurately. Moreover, according to this framework, driving tasks lead to variations in driving style, and the variations in driving style during the different driving tasks differ significantly for turning, acceleration, and deceleration maneuvers.

A novel two-dimensional (2D) free standing and flexible MnO2/graphene film (MGF) supercapacitor electrode is successfully fabricated by a spin-coating and hydrothermal process. The MnO2 nano-sheets are successfully aligned vertically only on one side of the graphene thin film. Raw amphiphilic graphene oxide film is helpful in effectively promoting the dispersion of well-defined MnO2 nanosheets, which can form a porous network and cover the film surface. The graphene film acts as a substrate where MnO2 nano-sheets grow in situ, and meanwhile it is used as a base current collector with a large accessible surface area and without binders for electrochemical testing. The MGF exhibits excellent electrochemical performance in a three electrode configuration, including a high specific capacitance of up to 280 F g−1 and outstanding cycle stability (no obvious decay after 10 000 cycles). In addition, the symmetric MGF supercapacitor shows a specific capacitance of up to 77 F g−1 under a cell voltage of 1.0 V. After 10 000 cycles, the capacity retention rate is 91% at a current density of 1 A g−1. At the same time, the symmetric supercapacitor also has a high energy density of 10.7 W h kg−1 at a power density of 500 W kg−1.

Recovering correct or at least realistic colors of underwater scenes is a challenging issue for image processing due to the unknown imaging conditions including the optical water type, scene location, illumination, and camera settings. With the assumption that the illumination of the scene is uniform, a chromatic adaptation-based color correction technology is proposed in this paper to remove the color cast using a single underwater image without any other information. First, the underwater RGB image is first linearized to make its pixel values proportional to the light intensities arrived at the pixels. Second, the illumination is estimated in a uniform chromatic space based on the white-patch hypothesis. Third, the chromatic adaptation transform is implemented in the device-independent XYZ color space. Qualitative and quantitative evaluations both show that the proposed method outperforms the other test methods in terms of color restoration, especially for the images with severe color cast. The proposed method is simple yet effective and robust, which is helpful in obtaining the in-air images of underwater scenes.

Background The contributions of inflammation, triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C) to the residual risk of cardiovascular events have not been determined in a large cohort of Chinese population before. This study was aimed to investigate the association of serum levels of high sensitive C reactive protein (hs-CRP), TG and HDL-C with the residual risk of cardiovascular events in patients with stable coronary artery disease (CAD). Methods We enrolled 4090 patients with stable CAD from 13 hospitals in China. All participants received optimal medical treatment (OMT) for stable CAD suggested by guidelines and were followed. The endpoint measures were the first occurrence of a major adverse cardiovascular event (MACE), defined as cardiovascular death, non-fatal myocardial infarction, non-fatal stroke or unplanned coronary revascularization. Cox proportional regression analysis was conducted to identify independent predictors of MACE. Results We found that hs-CRP and HDL-C levels were associated with coronary lesion severity at baseline (both p

Generative Adversarial Nets (GANs) are very successful at modeling distributions from given samples, even in the high-dimensional case. However, their formulation is also known to be hard to optimize and often not stable. While this is particularly true for early GAN formulations, there has been significant empirically motivated and theoretically founded progress to improve stability, for instance, by using the Wasserstein distance rather than the Jenson-Shannon divergence. Here, we consider an alternative formulation for generative modeling based on random projections which, in its simplest form, results in a single objective rather than a saddle-point formulation. By augmenting this approach with a discriminator we improve its accuracy. We found our approach to be significantly more stable compared to even the improved Wasserstein GAN. Further, unlike the traditional GAN loss, the loss formulated in our method is a good measure of the actual distance between the distributions and, for the first time for GAN training, we are able to show estimates for the same., Accepted to CVPR 2018

Endometriosis is still a major problem in obstetrics and gynecology. While GZFLW (Gui Zhi Fu Ling Wan) has been originally used for treating gynecological diseases, however, the molecular mechanism that GZFLW acts on endometriosis is not clear. To investigate the molecular mechanism that GZFLW plays role on endometriosis, iTRAQ (isobaric tags for relative and absolute quantification) proteomics and human endometrial stromal cells (Y14) obtained from a patient with endometriosis were used in in vitro study. Our results demonstrated that GZFLW decreased Y14 cells proliferation while increased cells apoptosis. The differential expression protein VPS53 (Vacuolar protein sorting 53 homolog) was predicted by iTRAQ coupled LC-MS/MS and further identified by western blot. Besides, GZFLW induced VPS53 protein level by promoting its stabilization. Our findings highlight a novel role for VPS53 in gynecology and provide a potent therapeutic strategy against endometriosis.

Endometriosis is a potential premalignant disorder. The underlying molecular aberrations, however, are not fully understood. A recent exome sequencing study found that 25% (10/39) of deep infiltrating endometriosis harbored cancer driver gene mutations. However, it is unclear whether these mutations also exist in ovarian endometriosis. Here, a total of 101 ovarian endometriosis samples were analyzed for the presence of these gene mutations, including KRAS, PPP2R1A, PIK3CA and ARID1A. In addition, 6 other cancer-associated genes (BRAF, NRAS, HRAS, ERK1, ERK2 and PTEN) were also analyzed. In total, four somatic mutations were identified in three out of 101 ovarian endometriotic lesions (4%, 4/101), including a KRAS p.G12V, a PPP2R1A p.S256F and two ARID1A nonsense mutations (p.Q403* and p.G1926*); while no mutations were identified in the remaining 7 genes (BRAF, NRAS, HRAS, ERK1, ERK2, PTEN and PIK3CA). Note that the KRAS G12V and ARID1A Q403* mutations co-occurred in a 36-year-old sample who had a high serum CA125 (308.4 U/mL) and a late menarche age (18-year-old). Additionally, no mutations in any of the 10 genes were identified in either the healthy eutopic endometrial tissues from 85 control individuals without endometriosis, or in 62 healthy ovarian tissues from ovarian cysts samples (without endometriosis). Our study revealed, for the first time, the presence of classical cancer driver gene mutations in ovarian endometriosis. Furthermore, the co-occurrence of KRAS and ARID1A mutations was identified in a single individual for the first time. The observations of cancer driver gene mutations in our ovarian endometriosis samples, together with several prior observations, further support the notion that endometriosis is a premalignant disorder.

Developing an alternative method for fabricating microscale graphene patterns that overcomes the obstacles of organic contamination, linewidth resolution, and substrate damaging is paramount for applications in optoelectronics. Here we propose to pattern chemical vapor deposition grown graphene film through a stencil mask by magnetic-assisted ultraviolet (UV) ozonation under irradiation of a xenon excimer lamp. In this process, the paramagnetic oxygen molecules and photochemically generated oxygen radicals are magnetized and attracted in an inhomogenous external magnetic field. As a consequence, their random motions convert into directional, which can greatly modify or enhance the quality of graphene patterns. Using a ferromagnetic steel mask, an approximately vertical magnetic-field-assisted UV ozonation (BZ = 0.31 T, ∇BZ = 90 T · m−1) has a capability of patterning graphene microstructures with a line width of 29 μm and lateral under-oxidation less than 4 μm. Our approach is applicable to patterning graphene field-effect transistor arrays, and it can be a promising solution toward resist-free, substrate non-damaging, and cost effective microscale patterning of graphene film.

Generating diverse questions for given images is an important task for computational education, entertainment and AI assistants. Different from many conventional prediction techniques is the need for algorithms to generate a diverse set of plausible questions, which we refer to as "creativity". In this paper we propose a creative algorithm for visual question generation which combines the advantages of variational autoencoders with long short-term memory networks. We demonstrate that our framework is able to generate a large set of varying questions given a single input image., Accepted to CVPR 2017

Tendering and bidding is widely used in the construction market, and it is very important for the owner, the contractor and the construction industry to find the efficient method of evaluation of bids. In this paper, we take the project evaluation of bids as the theme, combined with the characteristics of the project, using the method which is aggressive generalized DEA model to build the index system and through the case simulation we draw the final results of the evaluation.

The goal of this paper is to perform 3D object detection from a single monocular image in the domain of autonomous driving. Our method first aims to generate a set of candidate class-specific object proposals, which are then run through a standard CNN pipeline to obtain highquality object detections. The focus of this paper is on proposal generation. In particular, we propose an energy minimization approach that places object candidates in 3D using the fact that objects should be on the ground-plane. We then score each candidate box projected to the image plane via several intuitive potentials encoding semantic segmentation, contextual information, size and location priors and typical object shape. Our experimental evaluation demonstrates that our object proposal generation approach significantly outperforms all monocular approaches, and achieves the best detection performance on the challenging KITTI benchmark, among published monocular competitors.

In this paper we tackle the problem of instance-level segmentation and depth ordering from a single monocular image. Towards this goal, we take advantage of convolutional neural nets and train them to directly predict instance-level segmentations where the instance ID encodes the depth ordering within image patches. To provide a coherent single explanation of an image we develop a Markov random field which takes as input the predictions of convolutional neural nets applied at overlapping patches of different resolutions, as well as the output of a connected component algorithm. It aims to predict accurate instance-level segmentation and depth ordering. We demonstrate the effectiveness of our approach on the challenging KITTI benchmark and show good performance on both tasks., International Conference on Computer Vision (ICCV), 2015

This paper presents a 240-output AMOLED display driver with white balance adjustment technique. In order to reproduce the original picture, the reference white point of AMOLED panel should be the same as that of pictures to be displayed. Considering the most common reference white points are D65 and D93, an AMOLED display driver for both D65 and D93 white point has been proposed in this paper. The experimental results show that the proposed display driver can reproduce pictures properly under both two conditions.

Our aim is to provide a pixel-wise instance-level labeling of a monocular image in the context of autonomous driving. We build on recent work [Zhang et al., ICCV15] that trained a convolutional neural net to predict instance labeling in local image patches, extracted exhaustively in a stride from an image. A simple Markov random field model using several heuristics was then proposed in [Zhang et al., ICCV15] to derive a globally consistent instance labeling of the image. In this paper, we formulate the global labeling problem with a novel densely connected Markov random field and show how to encode various intuitive potentials in a way that is amenable to efficient mean field inference [Kr\"ahenb\"uhl et al., NIPS11]. Our potentials encode the compatibility between the global labeling and the patch-level predictions, contrast-sensitive smoothness as well as the fact that separate regions form different instances. Our experiments on the challenging KITTI benchmark [Geiger et al., CVPR12] demonstrate that our method achieves a significant performance boost over the baseline [Zhang et al., ICCV15].

Nanocrystalline zinc oxide (nc-ZnO) films were prepared by a sol–gel process on p-type single-crystalline Si substrates to fabricate nc - ZnO/p-Si heterojunctions. The structure and morphology of ZnO films on Si substrates, which were analyzed by X-ray diffraction (XRD) spectroscopy and atomic force microscopy (AFM), showed that ZnO films consisted of 50–100 nm polycrystalline nanograins with hexagonal wurtzite structure. The electrical transport properties of the nc-ZnO/p-Si heterojunctions were investigated by temperature-dependent current–voltage ( I–V ) measurements and room temperature capacitance–voltage measurements. The temperature-dependent I–V characteristics revealed that the forward conduction was determined by multi-step tunneling current, and the activation energy of saturation current was about 0.26 eV. The 1/ C 2 – V plots indicated the junction was abrupt and the junction built-in potential was 1.49 V at room temperature.

Silver (Ag) doped and undoped ZnO films were grown on Si (100) substrates by the sol-gel process. Photoluminescence (PL) of two kinds of samples as a function of the excitation intensity has been measured, and PL intensities have been fitted by a power law. It is found that Ag doping increases the intensity of free emission from ZnO and does not change the position and the full width at half-maximum of the free exciton emission. In PL spectra of two kinds of samples under various excitation powers, no visible emission bands related to the deep levels were observed. These results reveal that doped Ag in ZnO films only enhances emission efficiency from free exciton recombination, not giving rise to new emissions.