Search

The inverse analysis of the deformation moduli of high arch dams based on displacement monitoring data is essential for structural safety assessment. In traditional inverse analysis methods, the deformation moduli are identified based on the single‐objective optimization and the hydrostatic component derived from the statistical model. This type of method has two main shortcomings: First, it treats the essential multi‐objective optimization problem as a single‐objective problem; second, the extracted hydrostatic component may be biased due to the multicollinearity of variables in the statistical model. This paper presents a methodology for the inverse analysis of the deformation moduli of high arch dams under a multi‐objective optimization strategy. The methodology employs empirical mode decomposition to extract the aging component from displacement monitoring data. Then, thermomechanical analysis is used to reconstruct the remaining hydrostatic and temperature components, thereby avoiding the biases encountered in solving the statistical model. The adaptive polynomial chaos expansion method is embedded in the NSGA‐III algorithm to establish and solve multi‐objective functions in the inverse analysis. Additionally, a composite decision index considering errors and test information is proposed to determine acceptable deformation moduli from the Pareto solution set. A high arch dam is selected to illustrate this methodology with static and dynamic monitoring data. The results show that the identified deformation moduli have errors of 3.8% and 7.2% in displacement and acceleration, respectively. The proposed methodology can yield deformation modulus values that are more consistent with the physical implications than those of the single‐objective optimization method. [ABSTRACT FROM AUTHOR]

The fourth-order governing equation of Euler-Bernoulli beams necessitates the employment of C1 Hermite shape functions in finite element analysis. However, unlike the C0 finite element shape functions that can be easily formulated as Lagrangian polynomials in a unified manner, the Hermite shape functions of Euler-Bernoulli beam elements are usually constructed case by case. In this work, a simple and unified meshfree path is proposed to develop arbitrary order Hermite shape functions of Euler-Bernoulli beam elements. This approach is realized by proving that the Hermite reproducing kernel meshfree shape functions degenerate to the interpolatory Hermite finite element shape functions under a proper choice of support sizes. The proposed approach provides an explicit formalism for Hermite finite element shape functions, which enables an easy construction of arbitrary order Hermite beam elements. Accordingly, in addition to the conventional cubic Hermite beam elements, explicit shape functions, mass and stiffness matrices for quintic and septic Hermite beam elements are presented. Meanwhile, the frequency errors and general higher order mass matrix formulation for these Hermite beam elements are elaborated as well. These theoretical results are consistently demonstrated by numerical examples with respect to both static and free vibration analysis. [ABSTRACT FROM AUTHOR]

Background: Cholesterol (CHO) is an essential component of the body. However, high CHO levels in the body can damage bone mass and promote osteoporosis. CHO accumulation can cause osteoblast apoptosis, which has a negative effect on bone formation. The pathogenesis of osteoporosis is a complicate process that includes oxidative stress, endoplasmic reticulum (ER) stress, and inflammation. Geniposide (GEN) is a natural compound with anti-osteoporotic effect. However, the roles of GEN in osteopathogenesis are still unclear. Our previous studies demonstrated that GEN could reduce the accumulation of CHO in osteoblasts and the activation of ER stress in osteoblasts. However, the molecular mechanism of GEN in inhibiting CHO-induced apoptosis in osteoblasts needs to be further investigated. Methods: MC3T3-E1 cells were treated with osteogenic induction medium (OIM). Ethanol-solubilized cholesterol (100 µM) was used as a stimulator, and 10 µM and 25 µM geniposide was added for treatment. The alterations of protein expression were detected by western blot, and the cell apoptosis was analyzed by a flow cytometer. Results: CHO promoted osteoblast apoptosis by activating ER stress in osteoblasts, while GEN alleviated the activation of ER stress and reduced osteoblast apoptosis by activating the GLP-1R/ABCA1 pathway. Inhibition of ABCA1 or GLP-1R could eliminate the protective activity of GEN against CHO-induced ER stress and osteoblast apoptosis. Conclusion: GEN alleviated CHO-induced ER stress and apoptosis in osteoblasts by mediating the GLP-1R/ABCA1 pathway. [ABSTRACT FROM AUTHOR]

The health of the trees in the forest affects the ecological environment, so timely detection of Standing Dead Trees (SDTs) plays an important role in forest management. However, due to the large spatial scope of forests, it is difficult to find SDTs through conventional approaches such as field inventories. In recent years, the development of deep learning and Unmanned Aerial Vehicle (UAV) has provided technical support for low-cost real-time monitoring of SDTs, but the inability to fully utilize global features and the difficulty of small-scale SDTs detection have brought challenges to the detection of SDTs in visible light images. Therefore, this paper proposes a multi-scale attention mechanism detection method for identifying SDTs in UAV RGB images. This method takes Faster-RCNN as the basic framework and uses Swin-Transformer as the backbone network for feature extraction, which can effectively obtain global information. Then, features of different scales are extracted through the feature pyramid structure and feature balance enhancement module. Finally, dynamic training is used to improve the quality of the model. The experimental results show that the algorithm proposed in this paper can effectively identify the SDTs in the visible light image of the UAV with an accuracy of 95.9%. This method of SDTs identification can not only improve the efficiency of SDTs exploration, but also help relevant departments to explore other forest species in the future. [ABSTRACT FROM AUTHOR]

It is indispensable to explore the appropriate level of surface residual stress to enhance the wear resistance of coated tools. TiAlSiN-coated carbide tools with dissimilar surface residual compressive stresses (− 300 ~ − 600 MPa) are acquired via micro-sandblasting, which are used in the high-speed sliding friction experiments and turning experiments. The influence of residual stress on the sliding wear and cutting wear performance of TiAlSiN coated tools is investigated. The results show that with the improvement of surface residual compressive stress (absolute value), the friction coefficient and wear rate are reduced. The sliding wear resistance of the coated tool is enhanced. In addition, the cutting performance of the tool is also improved with the increase of residual compressive stress (absolute value). However, the excessive surface residual compressive stresses (absolute value) can lead to severe coating peeling, which in turn impairs the capability of wear resistance. The TiAlSiN-coated carbide tool with the stress of − 500 MPa presents the best wear resistance in the high-speed sliding wear and cutting wear process. [ABSTRACT FROM AUTHOR]

Background: Hemoglobin glycation index (HGI), which is calculated by blood glucose and hemoglobin A1c(HbA1c), reflects the individual discrepancy in HbA1c. This study aimed to investigate the association between HGI/HbA1c and serum uric acid(SUA) stratified by sex and diabetes. Methods: The study recruited 33772 participants who underwent physical examinations between April 2016 and August 2021 in Beijing Chao-Yang Hospital. A random subsample of 3000 subjects was utilized to calculate the formula of HGI and data of the remaining 30772 participants were used for analysis. HGI and HbA1c were categorized according to quartiles (Q1, Q2, Q3, Q4), using Q1 as the reference. We used multiple linear regression and restricted cubic splines for data analysis. Results: 30772 participants with a mean age of 44.4 years old were included in the analysis, 48.6% (N = 14944) of which were female and 7.7% (N = 2363) with diabetes. Associations of HGI, HbA1c and SUA were modified by sex and diabetes. The relationship between SUA levels and HGI was positive in women without diabetes, with one unit increase in HGI associating with an 11.3 μmol/L increase in SUA (P < 0.001) after adjusting for other confounders. On average, each one-unit increase in HbA1c was associated with a 14.3 μmol/L decrease in SUA in women with diabetes, a 14.9 μmol/L decrease in SUA in men with diabetes, and a 16.5 μmol/L increase in SUA in women without diabetes (all P < 0.001). The SUA levels in men without diabetes showed a bell-shaped relation with HbA1c, increasing as the HbA1c rose to around 5.7% and then falling with a further increase of HbA1c (P < 0.001). Conclusions: SUA levels were inversely correlated with HbA1c in diabetic patients, also in men with prediabetes (HbA1c ≥ 5.7%), but positively correlated with HbA1c and HGI in women without diabetes. Glycemic control may help to reduce the risk of hyperuricemia in non-diabetes women. [ABSTRACT FROM AUTHOR]

In this study, steel fiber-reinforced concrete (SFRC) beam structures with regular oriented steel fibers are designed and prepared by using an assembled solenoid device. Fiber orientation is not arranged in a single direction but is similar to the direction of tensile stress of the beam in bending load conditions. With application of inductive test method and image processing technology, fiber orientation coefficient of SFRC was evaluated and increased from 0.5 to 0.7–0.8 after fiber alignment. To describe and analyze the flexural behavior of SFRC beams with regular oriented fibers and glass fiber-reinforced polymer (GFRP) rebars, 14 concrete beams with different parameters were fabricated and subjected to a four-point bending test. Specifically, the parameters included fiber content, fiber orientation, GFRP reinforcement ratio and different layer sections. The results showed that optimizing fiber orientations to the tension zone of the section led to a higher flexural strength and can well restrain the development of crack widths with comparison to randomly distributed fibers. The peak load and energy absorption increased by 7 % and 12.4 % after fiber alignment with a fiber volume fraction of 1.5 %. The combination of randomly and regularly distributed steel fibers in the form of two-layer composite members can be an efficient solution to improve the flexural performance for purpose of the optimum distribution and direction of steel fibers, and reduce the engineering cost. • A magnetic orientation device is designed for SFRC beams with regular oriented fibers. • Fibers had well arrangements with high fiber orientation coefficient. • A flexural test of the ASFRC beams was conducted and investigated. • ASFRC improved the first cracking load and initial stiffness of beams. • The experimental results indicated great flexural performance after aligning fibers to the tension zone. [ABSTRACT FROM AUTHOR]

Recent research advances in salient object detection (SOD) could largely be attributed to ever-stronger multi-scale feature representation empowered by the deep learning technologies. The existing SOD deep models extract multi-scale features via the off-the-shelf encoders and combine them smartly via various delicate decoders. However, the kernel sizes in this commonly-used thread are usually “fixed”. In our new experiments, we have observed that kernels of small size are preferable in scenarios containing tiny salient objects. In contrast, large kernel sizes could perform better for images with large salient objects. Inspired by this observation, we advocate the “dynamic” scale routing (as a brand-new idea) in this paper. It will result in a generic plug-in that could directly fit the existing feature backbone. This paper’s key technical innovations are two-fold. First, instead of using the vanilla convolution with fixed kernel sizes for the encoder design, we propose the dynamic pyramid convolution (DPConv), which dynamically selects the best-suited kernel sizes w.r.t. the given input. Second, we provide a self-adaptive bidirectional decoder design to accommodate the DPConv-based encoder best. The most significant highlight is its capability of routing between feature scales and their dynamic collection, making the inference process scale-aware. As a result, this paper continues to enhance the current SOTA performance. Both the code and dataset are publicly available at https://github.com/wuzhenyubuaa/DPNet. [ABSTRACT FROM AUTHOR]

With the continuous development of computer science and technology, the level of medical image processing and analysis technology has been significantly improved. In order to further optimize the medical imaging technology and provide assistance for medical diagnosis and treatment, this study will explore the head CT image segmentation technology and three-dimensional reconstruction technology based on human anatomy, using two morphological operation methods of image expansion and image corrosion, as well as the triangulation method based on surface contour, Optimize CT image segmentation technology and three-dimensional reconstruction technology. The results show that the CT image segmentation technology based on human anatomy can obtain the more essential morphology and features of the target image, and significantly improve the image quality. The size of the threshold can have a certain impact on the 3D reconstruction effect and reconstruction time to a certain extent. The larger the threshold, the shorter the reconstruction time, but the worse the 3D reconstruction effect. This shows that the target image after fitting has a good reconstruction effect, but the threshold level should be kept at a low level. The head CT image segmentation technology and three-dimensional reconstruction technology based on human anatomy have good application effects and can be popularized and applied in clinical diagnosis and treatment. [ABSTRACT FROM AUTHOR]

We develop a method to compute synthetic kilonova light curves that combine numerical relativity simulations of neutron star mergers and the SNEC radiation–hydrodynamics code. We describe our implementation of initial and boundary conditions, r-process heating, and opacities for kilonova simulations. We validate our approach by carefully checking that energy conservation is satisfied and by comparing the SNEC results with those of two semi-analytic light-curve models. We apply our code to the calculation of colour light curves for three binaries having different mass ratios (equal and unequal mass) and different merger outcome (short-lived and long-lived remnants). We study the sensitivity of our results to hydrodynamic effects, nuclear physics uncertainties in the heating rates, and duration of the merger simulations. We find that hydrodynamics effects are typically negligible and that homologous expansion is a good approximation in most cases. However, pressure forces can amplify the impact of uncertainties in the radioactive heating rates. We also study the impact of shocks possibly launched into the outflows by a relativistic jet. None of our models match AT2017gfo, the kilonova in GW170817. This points to possible deficiencies in our merger simulations and kilonova models that neglect non-LTE effects and possible additional energy injection from the merger remnant and to the need to go beyond the assumption of spherical symmetry adopted in this work. [ABSTRACT FROM AUTHOR]

Polyamines are critical metabolites involved in various cellular processes and often dysregulated in cancers. Kaposi's sarcoma-associated Herpesvirus (KSHV), a defined human oncogenic virus, leads to profound alterations of host metabolic landscape to favor development of KSHV-associated malignancies. In our studies, we identified that polyamine biosynthesis and eIF5A hypusination are dynamically regulated by KSHV infection through modulation of key enzymes (ODC1 and DHPS) of these pathways. During KSHV latency, ODC1 and DHPS are upregulated along with increase of hypusinated eIF5A (hyp-eIF5A), while hyp-eIF5A is further induced along with reduction of ODC1 and intracellular polyamines during KSHV lytic reactivation. In return these metabolic pathways are required for both KSHV lytic reactivation and de novo infection. Further analysis unraveled that synthesis of critical KSHV latent and lytic proteins (LANA, RTA) depends on hypusinated-eIF5A. We also demonstrated that KSHV infection can be efficiently and specifically suppressed by inhibitors targeting these pathways. Collectively, our results illustrated that the dynamic and profound interaction of a DNA tumor virus (KSHV) with host polyamine biosynthesis and eIF5A hypusination pathways promote viral propagation, thus defining new therapeutic targets to treat KSHV-associated malignancies. Author summary: Understanding virus-host interactions is crucial to develop and improve therapies. Kaposi's sarcoma associated Herpesvirus (KSHV) is a human gamma-herpesvirus which deeply modulates the host metabolism and is associated with various cancers of endothelial and lymphoid origin. Polyamines are critical metabolites often dysregulated in cancers. In this study we demonstrated KSHV dynamically modulates polyamine metabolism to favor eIF5A hypusination and translation of critical KSHV latent and lytic proteins (LANA, RTA). Consequently, we found KSHV lytic switch from latency and de novo infection were dependent on polyamines and hypusination and pharmacological inhibition efficiently and specifically restricted KSHV infection. Our study provides new insights into KSHV alteration of the host metabolism and describe new therapeutic targets to treat KSHV-associated malignancies. [ABSTRACT FROM AUTHOR]

We investigate privacy-preserving, video-based action recognition in deep learning, a problem with growing importance in smart camera applications. A novel adversarial training framework is formulated to learn an anonymization transform for input videos such that the trade-off between target utility task performance and the associated privacy budgets is explicitly optimized on the anonymized videos. Notably, the privacy budget, often defined and measured in task-driven contexts, cannot be reliably indicated using any single model performance because strong protection of privacy should sustain against any malicious model that tries to steal private information. To tackle this problem, we propose two new optimization strategies of model restarting and model ensemble to achieve stronger universal privacy protection against any attacker models. Extensive experiments have been carried out and analyzed. On the other hand, given few public datasets available with both utility and privacy labels, the data-driven (supervised) learning cannot exert its full power on this task. We first discuss an innovative heuristic of cross-dataset training and evaluation, enabling the use of multiple single-task datasets (one with target task labels and the other with privacy labels) in our problem. To further address this dataset challenge, we have constructed a new dataset, termed PA-HMDB51, with both target task labels (action) and selected privacy attributes (skin color, face, gender, nudity, and relationship) annotated on a per-frame basis. This first-of-its-kind video dataset and evaluation protocol can greatly facilitate visual privacy research and open up other opportunities. Our codes, models, and the PA-HMDB51 dataset are available at: https://github.com/VITA-Group/PA-HMDB51 [ABSTRACT FROM AUTHOR]

Bearing fault diagnosis suffers from unsatisfied accuracy under variant working conditions, due to class-imbalance and distribution discrepancy of faulty data. Class-imbalance will cause classification bias that makes the diagnostic model tend to misclassify faulty classes, while the distribution discrepancy caused by variant working conditions will further reduce the model's generalization. Thus, this paper is mainly focusing on solving the two challenges simultaneously, and an Iterative Resampling Deep Decoupling Domain Adaptation (IRDDDA) model is proposed. The model consists of a feature extractor, domain classifier, label classifier and feature resampler modules, and it adopts a decoupling two-stage training framework. In the first stage, the model learns domain invariant features from the source domain and target domain based on original class-imbalance datasets. In the second stage, the feature extractor is partially fixed, and the feature-based resampling method is used to adjust the biased classifier caused by the class-imbalance problem. An iterative training strategy is adopted to simultaneously update the upper-layers of the feature extractor and adjust the classifier till convergence. The method is verified on the CWRU open dataset and the dataset collected from our bearing test rig. The verification results show that our method can achieve a better fault diagnostic performance overall, especially in minority faulty classes. • Class-imbalance and distribution discrepancy problem are simultaneously considered. • Deep decoupling domain adaptation framework is proposed. • An iterative feature-based resampling training strategy is adopted. • The method learns transferable invariant features and the calibrated classifier. [ABSTRACT FROM AUTHOR]

The stable reliability analysis of dams is a challenging topic in geotechnical engineering safety. Because there are more complex system failure modes and high-dimensional parameters in large solid structures, it is difficult to calculate failure probability efficiently and accurately using general reliability analysis methods. Most methods suffer from complex iterative processes and the curse of dimensionality. In this study, an improved importance sampling method based on multi-objective optimization is proposed and applied to reliability analysis for dam sliding. The optimization function is constructed from the limit state surface and the original probability density. The optimal sampling center is selected from the optimization results by considering the dominant performance function as well as the coefficient of variation of the weight function. Four numerical examples and a case study of the sliding stability of a gravity dam demonstrate the accuracy and efficiency of the proposed method. The results show that the proposed method is not sensitive to the specific multi-objective optimization algorithm used. Simulations using multiple sampling centers perform better overall than simulations using a single sampling center. In particular, the proposed method remains applicable to parallel systems with 20 high-dimensional parameters that are virtually immune to the curse of dimensionality. [ABSTRACT FROM AUTHOR]

The failure mode is a dominant factor of mechanical performance of braided composite tube subjected to axial compression. The failure mode was modified by tailoring stack-up sequence of composite tubes hybridized by bi/tri-axial braided laminate. The thermal photographing and micro-CT scanning methods were employed to monitor the in-situ damage progression and post-mortem specimen, respectively. The results show that the delamination was easy to be induced at the interface nearby tri-axial braided laminate. It attributes to the combination between the crack caused by local buckling of the axial yarns and the crack caused by shear deformation of braiding yarns. By the illumination of this behavior, delamination is controlled to occur at the different position along thickness direction of braided tube by adjusting the stacking sequence of braided laminates. When delamination position transfer from the inner/outer sides to the middle of tube wall, the failure mode transfer from the progressive folding to splaying, which increase the specific energy absorption by 45.77%. [ABSTRACT FROM AUTHOR]

The powder immersion reaction assisted coating (PIRAC) method was used to fabricate a coating on the graphite surface. The graphite was immersed into Cr powder and annealed at 1173–1373 K. The iodine powder was admixed with the Cr powder to investigate the contribution of iodine to the growth and mechanical properties of the coating. After 4 h of PIRAC treatment with or without iodine, Cr7C3- and Cr23C6-based coatings were formed, respectively. The iodinated samples had a higher hardness and thickness, and the friction coefficient was slightly higher than that of the iodine-free sample. The mechanisms for the formation of PIRAC-chromium carbide coatings are explained, and the variations in the produced coatings are discussed. [ABSTRACT FROM AUTHOR]

Objective. To explore the effects of epidural anesthesia and general anesthesia on perioperative cognitive function and deep vein thrombosis (DVT) in patients undergoing total knee arthroplasty (TKA). Methods. Total of 68 patients undergoing TKA in our hospital from September 2019 to March 2021 were selected and divided into the control group under general anesthesia and the observation group under epidural anesthesia according to the different anesthesia methods, 34 patients in each group. TKA was selected in both groups and performed by the same group of physicians, anesthesiologists, and nursing staff. The mean arterial pressure (MAP), heart rate (HR), and blood oxygen saturation (SpO2) were observed immediately before anesthesia (T1), 30 min after anesthesia (T2), after surgery (T3), and 1 d after surgery (T4). The changes of platelet (PLC), fibrinogen (Fbg), prothrombin time (PT), activated partial thrombin time (APTT), and other coagulation indicators were recorded. The Montreal Cognitive Assessment (MoCA) scores before surgery and 1 d and 3 d after surgery were observed. The blood samples of the two groups were collected before surgery and 1 d and 3 d after surgery, and the levels of brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF) in the peripheral blood of the two groups were measured by ELISA. The number of postoperative mental disorders and DVT in the two groups was calculated. Results. The MAP and HR of T4 were lower than those of T1, T2, and T3. The MAP of T2, T3, and T4 in the observation group was lower than that in the control group (P < 0.05), and the SpO2 of T1–T4 in the two groups did not change significantly, and there was no significant difference between the two groups (P > 0.05). Compared with T1, there was no significant difference in PLC, Fbg, and PT in the observation group T4 (P > 0.05), and APTT was lower than T1 (P < 0.05). The PLC, PT, and APTT of T4 in the control group were all lower than those of T1 (P < 0.05), and there was no significant difference between Fbg and T1 (P > 0.05). The PLC, Fbg, and PT of T4 in the observation group were higher than those in the control group, while APTT was lower than that in the control group (P < 0.05). The MoCA scores of patients in both groups on the 1st and 3rd day after operation were lower than those before operation, and the observation group was higher than that in the control group (P < 0.05). The BDNF and NGF of patients in both groups were lower than those before operation on the 1st day after operation, and the BDNF and NGF in the observation group were higher than those in the control group on the 1st and 3rd day after operation (P < 0.05). The mental disorder (2.94%) and DVT incidence (2.94%) in the observation group were lower than those in the control group (29.41%, 26.47%) (P < 0.05). Conclusion. Epidural anesthesia for patients with TKA can obtain better clinical effects, maintain stable hemodynamic and coagulation states, reduce stress response of patients at the same time, and reduce perioperative cognitive dysfunction and the incidence of DVT in patients. [ABSTRACT FROM AUTHOR]

Background: Bladder cancer is the second most common malignant tumor in the urogenital system. The research investigated the prognostic role of immune‐related long non‐coding RNA (lncRNA) in bladder cancer. Methods: We extracted 411 bladder cancer samples from The Cancer Genome Atlas database. Single‐sample gene set enrichment analysis was employed to assess the immune cell infiltration of these samples. We recognized differentially expressed lncRNAs between tumors and paracancerous tissues, and differentially expressed lncRNAs between the high and low immune cell infiltration groups. Venn diagram analysis detected differentially expressed lncRNAs that intersected the above groups. LncRNAs with prognostic significance were identified by regression analysis. Multivariate Cox analysis was used to establish the risk score model. Then we established and evaluated the nomogram. Additionally, we performed gene set enrichment analysis to explore the potential functions of the screened lncRNAs in tumor pathogenesis. Results: Three hundred and twenty differentially expressed lncRNAs were recognized. We randomly divided patients into the training data set and the testing data set at a 2: 1 ratio. In the training data set, 9 immune‐related lncRNAs with prognostic significance were identified. The risk score model was constructed to classify patients as high‐ and low‐risk cohorts. Patients in the low‐risk cohort had better survival outcomes than those in the high‐risk cohort. The nomogram was established based on the indicators including age, gender, tumor‐node‐metastases stage, and risk score. The model's predictive performance was confirmed by the receiver operating characteristic curve analysis, concordance index method, calibration curve, and decision curve analysis. The testing data set also achieved similar results. Bioinformatics analysis suggested that the 9‐lncRNA signature was involved in the modulation of various immune responses, antigen processing and presentation, and T cell receptor signaling pathway. Conclusions: Our study uncovered the prognostic value of immune‐related lncRNAs for bladder cancer and showed that they may regulate tumor pathogenesis in various ways. [ABSTRACT FROM AUTHOR]

A new testing method (oscillating wave method) has been proposed as a solution to the problem of short maintenance time in the traction power supply system, which could complete tests of winding and insulation via one connection and improve the maintenance efficiency of the transformer. Through the method being proved highly sensitive to winding faults, the variation under different winding states, however, remains unclear. This article aims to analyze oscillating wave signatures in the occurrence of axial displacement (AD). First, the modeling method will be proposed that can simulate oscillating wave signatures in different winding states. Then, the time-domain feature and the new proposed frequency-domain feature are applied to analyze the fault extent and location of AD fault. The results show that this model accurately simulates oscillating wave signatures. Moreover, the time-domain feature [Euclidean distance (ED)] is closely related to fault extent. The combined use of the time-domain feature (ED) and the frequency-domain feature (W-Energy entropy in Z-Score) is effective in the identification of fault location. These features, therefore, can provide the reference for winding state evaluation. [ABSTRACT FROM AUTHOR]

Repetitive or ambiguous environment, where structures are highly similar and distinct geometric features are not sufficient, is one of the critical and challenging scenarios for mobile robots to perform global localization or simultaneous localization and mapping (SLAM) tasks. The robots are easy to get lost or mismatched to wrong places in such environments. The existing solutions either rely heavily on pre-installed infrastructures which are inflexible and expensive or rely on single sensor-based global localization methods whose initialization module is not capable enough to provide distinctive information. Thus, this article proposes a hierarchical probabilistic framework that addresses the problem of infrastructure-free mobile robot global localization in GPS-challenged repetitive environments by leveraging both the measured magnetic field (MF) and Light Detection and Ranging (LiDAR) information. The proposed hierarchical system mainly consists of: 1) coarse localization: MF-based localization and 2) fine localization: LiDAR-based localization (LBL). The ambient MF functions as a substitute for the GPS signal, which is considered not available or severely challenged in indoor/semi-indoor local environments. Based on the pre-built MF database, multiple coarse candidate robot poses can first be determined by the proposed initial pose estimation algorithm, which incorporates multivariate Gaussian observation model and random sample consensus (RANSAC) algorithm. Then, using the obtained multiple candidate poses as initialization, the robot can be localized more accurately by LiDAR-based fine localization. Extensive real-world experiments demonstrate that the proposed system achieves over 95% localization success rate and takes less than 2.0-m average traveling distance to localize the mobile robot. [ABSTRACT FROM AUTHOR]

Data-driven fault diagnostics of industrial systems suffer from class-imbalanced problems, which is a common challenge for machine learning algorithms as it is difficult to learn the features of the minority class samples. Synthetic oversampling methods are commonly used to tackle these problems by generating minority class samples to balance the majority and minority classes. Two major issues will influence the performance of oversampling methods which are how to choose the most appropriate existing minority seed samples, and how to synthesize new samples from seed samples effectively. However, many existing oversampling methods are not accurate and effective enough to generate new samples when dealing with high-dimensional faulty samples with different imbalanced ratios, since they do not take these two factors into consideration at the same time. This article develops a novel adaptive oversampling technique: expectation maximization (EM)-based local-weighted minority oversampling technique for industrial fault diagnostics. This method uses a local-weighted minority oversampling strategy to identify hard-to-learn informative minority fault samples and an EM-based imputation algorithm to generate fault samples based on the distribution of minority samples. To validate the performance of the developed method, experiments were conducted on two real-world datasets. The results show that the developed method can achieve better performances, in terms of F-measure, Matthews correlation coefficient (MCC), and Mean (average of F-measure and MCC) values, on multiclass imbalanced fault diagnostics in different imbalance ratios than state-of-arts’ baseline sampling techniques. [ABSTRACT FROM AUTHOR]

In this article, a new testing method for the diagnosis of winding faults based on the resonant frequency of the transformer is proposed. The system that consists of the high-voltage dc power and high-voltage insulated gate bipolar transistor (IGBT) could charge the transformer periodically. The response measured from the bushing of the winding is the oscillating wave that can be used for evaluating the status. Carrying out the new test on a 220-kV three-winding, three-phase transformer in the field, the tests of insulation and the winding have been completed in one test. The calculated frequency verifies the feasibility and applicability of the method in theory and the voltage does not affect the resonant frequency in the test. The three-winding, three-phase model transformer was built to simulate the various parameters of the power supply, which proves that the features of the oscillating waves are brought about by the properties of the transformer. Also, the new testing method provides a new opportunity to do parameter identification of axial displacement and short-circuit (SC) fault. The abovementioned research shows that the proposed method can conduct the test of winding and insulation in one test for a short time, which proves a reference in the field. [ABSTRACT FROM AUTHOR]

In this study, the performance of braided composite tubes under low-velocity transverse impact loading at mid-span was investigated using both numerical and experimental methods. Three types of braided composite tubes with different braiding angles (30°, 45°, and 60°) were manufactured. The transverse punch behavior of the tubes was examined on a low-velocity imspact test bench. A meso-level finite element model of the composite tube was also established for identifying the damage initiation and development. The numerical results showed a good correlation with the experimental data. The mechanical response including force–time histories, force–displacement histories, and fracture morphologies was compared between three types of composite tubes for analyzing the influence of braiding angle on the impact response and failure mode. Although suffering from the low bending stiffness depends on fiber volume fraction at initial impact stage, the braided tube with 30° angle engaged more portion to resist impact loading in subsequent process and thus presented higher peak loading than the one with large angle. In addition, there are distinct different failure modes between composite tubes with various braiding angles. Shear yarn breakage underneath the punch was prone to occur in 30° sample because the braiding yarn was closer to the axial direction of tube. In contrast, the resin was deboned severely from the braiding yarn and then the braiding yarn exhibits plastic deformation in 60° sample due to the stress concentration caused by the large braiding angle. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the effects and mechanisms of hematopoietic-substrate-1-associated protein X-1 (HAX-1) on liver cancer cells. Information on HAX-1 from liver cancer patients was analyzed by the Cancer Genome Atlas (TCGA) program. Cell migration and invasion abilities were respectively tested by scratch assay and transwell assay. Tube formation assay was applied to detect angiogenesis protein and mRNA was determined using quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot. We found that the median month survival of HAX-1 overexpressing liver cancer patients was shorter than that of HAX-1 normal liver cancer patients. HAX-1 was overexpressed in liver cancer tissues and cells, and HAX-1 overexpression promoted the liver cancer cells growth, migration, and invasion, whereas silencing HAX-1 produced the opposite results. Inhibition of Akt by LY294002 reversed the migration and invasion abilities of liver cancer cells, and inhibited the ability of cells growth and angiogenesis. Silencing PIK3CA enhanced the inhibitory effects of HAX-1 silencing on the viability, migration, and invasion of liver cancer cells. HAX-1 affected liver cancer cells metastasis and angiogenesis by affecting Akt phosphorylation and FOXO3A expression. [ABSTRACT FROM AUTHOR]

• The Si-O-Cs groups are identified as active sites. • The promotion of Brønsted acid sites in Cs dispersion was revealed. • The maximum MA production reaches up to 7.23 mmol·g Cat −1·h−1. • The deactivation behavior of catalyst was demonstrated. With the gradual depletion of petroleum resources and overcapacity of coal industry, the one-step synthesis of methyl acrylate (MA) from the coal-based methyl acetate (Ma) and formaldehyde via aldol condensation, regarded as a supplementary route for the petroleum-based propene selective oxidation, receives significant attention in decades. Herein, a series of Cs/Beta zeolite catalysts were developed for this transformative process using incipient wetness impregnation with varied Cs loading amount and SiO 2 /Al 2 O 3 ratio. The physicochemical properties of both prepared Cs/Beta zeolite catalyst series and Beta zeolite supports were characterized by using FT-IR, ICP, XRF, physical N 2 adsorption–desorption isotherms, NH 3 -TPD, Py-IR, 31P-MAS NMR, XRD and XPS, in combination with catalytic evaluation experiments. The effects of Brønsted acid sites, SiO 2 /Al 2 O 3 ratio and Cs loading on the catalytic performance and catalyst deactivation were systematically investigated. The Brønsted acid sites on Beta zeolite support showed promotional effects on the dispersion of loaded Cs species and formation of (Al-O)-Si-O-Cs groups which were crucial to the improvement of catalytic activity and selectivity. However, the excessive Brønsted acid sites on Cs/Beta or Beta zeolite would lead to the heavy side reactions, including the hydrolysis of Ma and dehydration and further aromatization of methanol (MeOH). As a result, the highest formation rate of 7.23 mmol·g Cat −1·h−1 for MA could be achieved with a relatively high selectivity of 85% on the optimal 17.5Cs/Beta40 catalyst. While the undesired catalytic deactivation behavior resulting from the accumulation of alkyl-substituted single-ring aromatic species in the micropores of catalyst was found during the reaction by employing FT-IR, GC–MS, TGA and UV–vis analysis, which could be easily regenerated by thermal treatment at 400 °C and air atmosphere. [ABSTRACT FROM AUTHOR]

The endoplasmic reticulum (ER) is the main site for protein synthesis, folding, and secretion, and accumulation of the unfolded/misfolded proteins in the ER may induce ER stress. ER stress is an important participant in various intracellular signaling pathways. Prolonged- or high-intensity ER stress may induce cell apoptosis. Osteoporosis, characterized by imbalanced bone remodeling, is a global disease caused by many factors, such as ER stress. ER stress stimulates osteoblast apoptosis, increases bone loss, and promotes osteoporosis development. Many factors, such as the drug's adverse effects, metabolic disorders, calcium ion imbalance, bad habits, and aging, have been reported to activate ER stress, resulting in the pathological development of osteoporosis. Increasing evidence shows that ER stress regulates osteogenic differentiation, osteoblast activity, and osteoclast formation and function. Various therapeutic agents have been developed to counteract ER stress and thereby suppress osteoporosis development. Thus, inhibition of ER stress has become a potential target for the therapeutic management of osteoporosis. However, the in-depth understanding of ER stress in the pathogenesis of osteoporosis still needs more effort. [Display omitted] • ER stress is implicated in bone remodeling. • ER stress mediates osteogenic differentiation and osteoblast activity. • ER stress regulates osteoclast formation and function. • ER stress has become a target for osteoporosis treatment. [ABSTRACT FROM AUTHOR]

To solve the problem that the individual differences and the measurement errors affect the accuracy of life estimation in accelerated degradation test, the inverse Gauss process with stochastic parameters is applied in the accelerated degradation test with the consideration of the influence of individual differences, and the analysis of measurement uncertainty is carried out. An inverse Gauss accelerated degradation model considering both individual differences and measurement errors is established. In the maximum likelihood estimation of parameters, Genetic Algorithm and Monte Carlo integral are used to solve the problems caused by complex integral and the unobservable measurement errors in the calculation process. Finally, the proposed method is verified by the Monte Carlo simulation under the constant accelerated stress and step accelerated stress and the illustrative example of electrical connectors under the constant acceleration stress, respectively. The results show that the modeling tool is useful for improving the accuracy of the life prediction and the reliability evaluation. [ABSTRACT FROM AUTHOR]

Highlights • A method for simulation of spatial variability of gravity dams was established. • Mean value of the tensile strength has a great influence on the plastic damage. • Research results can be used as a reference for gravity dams with similar profiles. Abstract A method to simulate the random field of the strength parameters of gravity dams considering their spatial variability based on the theory of random fields and the autocorrelation function is proposed. Taking a gravity dam project as an example, the elastic modulus and tensile strength are selected as random variables and the corresponding random fields are generated. Based on the concrete damage plasticity (CDP) model, the effects of the spatial variability of parameters on the dynamic response characteristics of gravity dams are expressed from the standpoints of damage development, residual displacement, and energy dissipation. The impacts of the mean value, coefficients of variation, autocorrelation distance, realizations of the tensile strength random field, and seismic inputs on the structural damage are also investigated. It is found that the spatial variability of parameters, especially the tensile strength, has a great influence on the dynamic damage of gravity dams, and that increasing the mean value of the tensile strength can improve their seismic performance. [ABSTRACT FROM AUTHOR]

An effective way to improve the flight capability and environmental adaptability of aerospace vehicles is to design a morphing aircraft structure, which can actively change their aerodynamic shape. During different physiological activities, the abdomens of bees are regularly deformed to improve the efficiency of movement. This was used as an inspiration for the design of a nose cone for aerospace vehicles. Based on the deformation mechanism of the bee abdomen, a bionic design of a variable configuration morphing nose cone (MNC) mechanism with high sensitivity is proposed, which can realize real-time reverse self-locking of the mechanism via auxiliary branch chains. Theoretical models for the kinematics and dynamics of the MNC mechanism under two configurations are derived, verifying that the proposed mechanism has good kinematic and dynamic characteristics. The theoretical models are validated through simulation studies. In addition, static finite element simulations are performed to verify that the auxiliary locking branch chain can significantly improve the bearing capacity of the proposed mechanism. Moreover, the force and thermal parameters of different configurations of the MNC under corresponding typical working conditions are analyzed, enabling the improvement of the aerospace vehicle aerodynamic characteristics by the morphing of its nose cone. Finally, based on the analytic hierarchy process, different drag and heat flux reduction schemes are comprehensively evaluated. [ABSTRACT FROM AUTHOR]

Livestock wastewater contains a large amount of nutrients that are available for recovery. In this study, a proof of concept process based on forward osmosis (FO) was proposed and investigated for in situ formation of struvite from digested swine wastewater. This FO system took advantage of a drawback – reverse solute flux (RSF) and used the reverse-fluxed Mg 2+ for struvite precipitation, thereby accomplishing recovery of both water and nutrient. With 0.5 M MgCl 2 as a draw solution, high-purity struvite formed spontaneously in the feed solution and the water flux through the FO membrane reached 3.12 LMH. The precipitated struvite was characterized and exhibited a similar composition to that of commercial struvite. The FO system achieve >50% water recovery and >93% ammonium nitrogen removal from the digested swine wastewater; in particular, it obtained >99% phosphate recovery, much higher than 60.7% removal via direct MgCl 2 addition (without FO treatment). The recovered products (both struvite and water) could potentially generate a value of 1.35 $ m −3 . The results of this study have demonstrated the feasibility of nutrient recovery from livestock wastewater promoted by FO treatment. [ABSTRACT FROM AUTHOR]

Most of the plasticizers used during poly (vinyl chloride) processing are typically toxic petroleum-based phthalates. Furthermore, large amount of edible oils become waste all over the world, fortunately, waste cooking oils have the potential to be an economic alternative for synthesizing different biomaterials. This study aimed to synthesis an improved properties and cost competitiveness cleaner bio-plasticizer using waste cooking oil methyl esters as staring raw materials. In this paper, waste cooking oil methyl esters were structurally modified i.e., transesterification and epoxidation reaction, to prepare epoxide waste cooking oil 2-ethylhexyl esters. The in-situ epoxidation was mainly studied by response surface methodology, with optimum conditions: reaction time was 7 h, molar ratio of C C bonds/FA/H 2 O 2 was 1.00/0.35/2.41, and reaction temperature was 65.84 °C with a maximum relative percentage conversion to oxirane of 92%. Also, the plasticizing effectiveness of epoxide waste cooking oil 2-ethylhexyl esters to substitute toxic plasticizer dioctyl phthalate were studied. Results showed that the mechanical and thermal performance of PVC samples was significantly improved with partial substitutions, while the migration resistance was slightly decreased. Comparison with conventional epoxy compound highlighted that epoxide waste cooking oil 2-ethylhexyl esters had superior low temperature property, oxidation stability, and remarkably reduced the glass transition temperature of PVC. In conclusion, the prepared epoxide via structural modification from waste cooking oil methyl esters proved to be an effective alternative to dioctyl phthalate, replacing about 40% of the total plasticizer. This may lead to the eco-development of waste cooking oil materials, and makes the plasticizing process more environmentally friendly. [ABSTRACT FROM AUTHOR]

A novel and facile post-grafting strategy, via a Schiff base chemical reaction between aldehyde and −NH 2 groups within NH 2 -MIL-125(Ti) has been developed to construct aromatic heterocycle-grafted metal organic frameworks (MOFs) photocatalysts. The improved conjugated system in MOFs showed lower band gaps and their excellent catalytic activities were manifested by selective oxidation of alcohols to corresponding aldehydes under visible light irradiation with high conversion and selectivity. Density functional theory (DFT) was applied for simulating the band gaps and electron orbits of heterocycle-grafted MOFs. The post-synthetic aromatic heterocycles in the MOFs network did not influence the original framework, but effectively expanded its π-delocalized system and promoted the separation and transfer of photo-excited charge carriers. As a result, the aromatic heterocycle-grafted MOFs exhibit significantly enhanced visible-light photo-catalytic activity for selective oxidation of alcohols over pristine NH 2 -MIL-125(Ti). Especially, the NH 2 -MIL-125(Ti) grafted by 2-quinolinecarboxaldehyde and 3-thiophenecarboxaldehyde showed better performance (more than 85% conversion of benzyl alcohol) due to the excellent photon adsorption and charge carriers transfer of aromatic heterocycles grafted on MOFs. This general grafting strategy can be utilized to graft large numbers of aromatic rings with different molecular structures onto NH 2 -MIL-125(Ti). [ABSTRACT FROM AUTHOR]

• The usage of correlation between maximum temperature and peak load. • The reconstruction of CT images identifies the debonding distribution and degree. • A novel inspection way of combing infrared imaging and micro CT reconstruction methods. • The role of axial yarns in axial crushing. In this work, the effect of axial yarns on damage behavior of two-dimensional triaxially braided composite(2DTBC) tubes subjected to axial compression was investigated. A novel damage detection method combining infrared thermography and CT scanning was presented. In the area without axial yarns, yarn crossovers were separated from each other due to interlacing patterns. Axial compression caused the braiding yarns to shear deformation like scissors. Inter-yarn de-bonding appeared in crossovers and could not connect. Consequently, it caused a progressively folding failure mode. In contrast, local buckling occurred on axial yarns because of their primary loading behavior. Cracks along the axial yarns formed, which would combine with debonding crossovers caused by the sheared braiding yarn. It resulted in significant inter-layer delamination and consequently splaying failure mode. The energy absorption of composites tube with 18 axial yarns increased by 79.9% at the cost of 27.8% fiber usage more than 3 axial yarns. [ABSTRACT FROM AUTHOR]

Influenza is active during the winter and spring in the city of Beijing, which has a typical temperate climate with four clear distinct seasons. The clinical and laboratory surveillance data for influenza have been used to construct critical indicators for influenza activities in the community, and previous studies have reported varying degrees of association between laboratory-confirmed influenza specimens and outpatient consultation rates of influenza-like illness in subtropical cities. However, few studies have reported on this issue for cities in temperate regions, especially in developing countries. Furthermore, the mechanism behind age-specific seasonal epidemics remains unresolved, although it has been widely discussed. We utilized a wavelet analysis method to monitor the coherence of weekly percentage of laboratory-confirmed influenza specimens with the weekly outpatient consultation rates of influenza-like illness in Beijing, China. We first examined the seasonal pattern of laboratory-confirmed cases of influenza A (subtyped into seasonal A(H1N1) and A(H3N2) and pandemic virus A(H1N1) pdm09) and influenza B separately within the period from 2008–2015; then, we detected the coherence of clinical and laboratory surveillance data in this district, specially examining weekly time series of age-specific epidemics of influenza-like illnesses in the whole study period for three age categories (age 0–5, 5–15 and 25–60). We found that influenza A and B were both active in winter but were not always seasonally synchronous in Beijing. Synchronization between age ranges was found in most epidemic peaks from 2008–2015. Our findings suggested that peaks of influenza-like illness in individuals aged 0–5 and 5–15 years consistently appeared ahead of those of adults, implying the possibility that schoolchildren may lead epidemic fluctuations. [ABSTRACT FROM AUTHOR]

Photochemical devices show great potential in applications ranging from electrical energy storage to future smart grids. Here, we report a metal-free composite film cell based on carbon dots (CDots) and polyaniline (PANI), which could achieve 24/7 discharge and photo-charging in seawater. CDots/PANI film cell has an open-circuit-voltage (OCV) of 0.95 V, a maximum power density of 380 mW m2, and the ability to discharge continuously for 40 h under solar irradiation of AM 1.5 G. It couples the reduction reaction of PANI, and the CDot-catalyzed oxygen reduction reactions (ORR) during discharge. While the light-induced CDot-catalyzed oxygen evolution reaction (OER) and the reduction reaction of PANI during charging. In particular, in-situ TPV tests were used to verify the effect of the light-induced OER and the kinetic properties of the catalyst on the charge transfer at the interface. We believe this research may provide new ideas for sustainable energy conversion and storage. Carbon dots-based film cell can achieve 24/7 discharge and photo-charging in seawater, is capable of storing energy and utilizes the redox reaction of polyaniline, the ORR/OER catalyzed by carbon dots for discharge and charging, and TPV tests were used to explore the OER process and catalytic mechanism during charging. [Display omitted] [ABSTRACT FROM AUTHOR]

It is very important to estimate the mechanical parameters based on monitoring data for investigating the operation behavior of concrete dams. In this paper, an advanced Bayesian parameter estimation method for concrete dams is proposed. The Empirical Mode Decomposition (EMD) is adopted to extract the aging component of the observed deformation sequence, and the hydrostatic component is separated from the remaining periodic term through the statistical regression model (SRM). A hybrid response surface method (HRSM) is proposed as a surrogate model for finite element method (FEM) simulation. The likelihood function, which reflects the error between the observed and simulated deformation, is constructed, then the Bayesian formula for parameter estimation is established. The transitional Markov chain Monte Carlo (TMCMC) algorithm is used to obtain the parameter posterior distribution. The proposed method is applied to estimate the elastic modulus of the GD concrete dam, the parameter posterior distribution is obtained through the fusion of monitoring information and parameter prior information. This method can also avoid the issues of multiple solutions and unreasonable parameter combinations, which may exist in traditional deterministic inversion methods. The case study shows that the proposed method has good applicability in the parameter estimation of concrete dams. [ABSTRACT FROM AUTHOR]

The health monitoring and operation behavior assessment of earth dams are research focuses in geotechnical engineering. Due to the limited monitoring data and the uncertainty of material properties, existing monitoring data-based interpolation methods and mechanism-based finite element method (FEM) can not accurately estimate the dam deformation field. Therefore, studying an accurate estimation method of the deformation field is important to guarantee the serviceability of earth dams. In this paper, a FEM-Bayesian kriging (FBK) method is proposed, in which the FEM is introduced into the Bayesian kriging framework as the source of soft data, taking the FEM results as a trend surface of the deformation field, the spatial distribution of the random residual is determined by the exact monitoring data, thereby the FEM results are corrected. In this method, data-rich but low-precision FEM results and limited but high-precision monitoring data are coupled to approach the real deformation field. A numerical experiment is designed to verify the accuracy of the proposed method, and the estimation error of the FBK is reduced by about 80% compared with traditional methods. The case study of an actual earth dam also shows that the proposed method can effectively characterize the deformation behavior of earth dams. [ABSTRACT FROM AUTHOR]

This study was designed to investigate the effect of Aurantii fructus immaturus flavonoid (AFIF) on the contraction of isolated gastric smooth muscle in rats and explore its underlying mechanisms. Isolated antral longitudinal smooth muscle strip (ALSMS) and pyloric circular smooth muscle strip (PCSMS) of rats were suspended in tissue chambers. The responses of ALSMS and PCSMS to administration of AFIF were observed. Cyclic guanosine monophosphate (cGMP) and protein kinase G (PKG) levels of PCSMS were measured by ELISA kits. In this study, AFIF showed no significant effect on ALSMS contraction, but it dose-dependently reduced the mean contraction amplitude of PCSMS. When the concentration of AFIF reached 3000 μg/mL, 6000 μg/mL, and 10000 μg/mL, its inhibitory effect on PCSMS contraction was significant. This effect of AFIF was weakened in Ca2+-rich environment. And Nω-nitro-L-arginine methyl (L-NAME), the inhibitor of nitric oxide synthase (NOS), significantly inhibited AFIF’s action in comparison with control (P<0.05). After incubation with AFIF for 30 min, levels of cGMP and PKG in PCSMS were significantly increased compared with control (P<0.05). Our results suggest that AFIF has a dose-dependent diastolic effect on PCSMS in rats, which may be related to the regulatory pathway of NO/cGMP/PKG/Ca2+. [ABSTRACT FROM AUTHOR]

A set of non-conforming quadratic basis functions is introduced to formulate the mass and stiffness matrices that enable a superior frequency accuracy for isogeometric free vibration analysis of thin beams and plates. The non-conforming basis functions are expressed as a simple combination of the original basis functions and their second-order derivatives with an adjustable parameter. By construction, these quadratic non-conforming basis functions only affect the mass matrices and do not alter the stiffness matrices. The adjustable parameter arising from the non-conforming basis functions are determined through optimizing the frequency accuracy. In the case of thin beams, the proposed non-conforming isogeometric formulation leads to an increase of frequency accuracy order or superconvergence. For thin plates, the frequency error of the proposed method is guaranteed to be no larger than that of the standard isogeometric approach. Numerical results for thin beams and plates consistently verify that the proposed formulation with non-conforming basis functions is quite robust and produces very favorable frequency accuracy for both uniform and non-uniform meshes. [ABSTRACT FROM AUTHOR]

• Data-based models with EMD are proposed for deformation monitoring of concrete dams. • The proposed models can well simulate the irreversible component of concrete dam deformation and significantly decrease the over-fitting levels. • A new model selection criterion, namely Over-fitting coefficient, is proposed for evaluating and selecting dam health monitoring models. • The Over-fitting coefficient can better reflect over-fitting levels of individual monitoring models compared to traditional model selection criteria. Data-based models are extensively applied in concrete dam health monitoring. In this paper, the Empirical Mode Decomposition (EMD) is adopted to extract and visualize the irreversible component of deformation monitoring sequence. Consequently proper mathematical formulation of the irreversible component of deformation monitoring model for concrete dams can be established, and the problem of improperly assuming the mathematical form of irreversible component when constructing data-based models is well addressed. The periodic component of the deformation time series is modelled by regression and three machine learning algorithms (i.e., Extreme learning machine, Support Vector Machine based on Grid search and Cross-Verification, and Back Propagation Neural Networks optimized by Genetic Algorithm and Simulated Annealing) respectively. The data-based models with the EMD are able to effectively improve the performance of formulating irreversible component of concrete dam deformation and decrease the over-fitting levels. A new model selection criterion, namely Over-fitting coefficient, is proposed for evaluating and selecting the optimum model among candidate monitoring models. The Over-fitting coefficient can better reflect over-fitting levels of individual monitoring models compared to traditional model selection criteria. As a case study, the displacement and strain monitoring data from the YL gravity dam are modeled by data-based models with the EMD and machine learning algorithms. It is shown that data-based models with the EMD are of higher prediction accuracy and lower rate of false alarm in deformation monitoring than traditional models. The Over-fitting coefficient can better reflect over-fitting levels of monitoring models compared to the error measurement criteria and information criteria. The case study highlights the merits of the proposed data-based models and the model selection criterion for health monitoring of concrete dams. [ABSTRACT FROM AUTHOR]

• Epoxidation was performed continuously in a packed bed reactor with orifice plates. • The periodical dynamic variation of droplet size was characterized. • Two phases were well mixed at a low flow velocity in the reactor. • Heat transfer was intensified significantly and no thermal runaway occurred. • The average reaction rate in the reactor was greatly increased. In this work, a packed bed reactor with orifice plates (PBR@OP) was designed and applied to Prileschajew epoxidation. The reactor performance such as mass/heat transfer and reaction characteristics were studied and compared with packed bed reactor (PBR) and stirred-tank reactor (STR). In PBR@OP, the periodical dynamic variation of droplet size was characterized. Liquid-liquid two phases were well mixed at a low flow velocity, resulting in a significant reduction of total reactor length and pressure drop as compared with PBR. The heat transfer coefficient and thermal stability of PBR@OP were analyzed and a method to determine the critical diameter of the reactor for the epoxidation was developed. The continuous epoxidation of fatty acid methyl ester (FAME) in PBR@OP was carried out with a simpler and safer process, and the rate of transfer process and reaction were greatly enhanced as compared with that in STR. This reactor presents an economic choice for the process intensification of continuous epoxidation. [Display omitted] [ABSTRACT FROM AUTHOR]

Photocatalytic water-splitting to generate hydrogen (H 2) and hydrogen peroxide (H 2 O 2) is a green and renewable method to convert solar energy into chemical energy. The water impurity in organic solvents is usually hard to be removed. Here, we firstly used an organic semiconductor (DAnTMS) synthesized from 9,10-dibromoanthracene and trimethylsilylacetylene to convert the water impurity in organic solvent into H 2 and H 2 O 2 by photocatalysis. Under visible light, for 300.0 μL water in 20.0 mL methyl cyanide (MeCN) system, the DAnTMS catalyst can produce H 2 and H 2 O 2 with rate of 245.9 μmol g−1 h−1 and 3923.4 μmol g−1 h−1, respectively. Furthermore, a practical photocatalytic experiment was performed in 20.0 mL commercially available MeCN (99.8%, H 2 O ≤ 0.01%) with 10.0 mg DAnTMS as catalyst, in which, the total 15.4 μmol H 2 and 176.7 μmol H 2 O 2 were generated after 12 h reaction, suggesting the water impurity in MeCN was completely removed. In present catalytic system, on DAnTMS, O 2 and H 2 O are reduced into H 2 O 2 and H 2 , respectively, while, H 2 O is oxidized into H 2 O 2 through a 2e- pathway. An organic semiconductor was used to convert the water impurity in MeCN (98%, H 2 O ≤ 0.01%) into H 2 and H 2 O 2 by photocatalysis. [Display omitted] • DAnTMS was used to convert the water impurity in organic solvent into H 2 and H 2 O 2 by photocatalysis. • TPV tests were used to explore the half-reaction process and catalytic mechanism. • The extrapolation was applied on the TPV curves. [ABSTRACT FROM AUTHOR]

Bearing fault diagnosis suffers from class imbalances and distributional discrepancies of fault data under different working conditions. The class imbalance of the fault class increases the difficulty of learning the classification boundary of the diagnostic model for the minority class. Furthermore, the diversities of feature distributions decrease the diagnostic model's generalizability under various working conditions. Thus, in this paper, a deep adversarial transfer learning model for imbalanced bearing fault diagnosis (deep Imba-DA) is proposed to overcome these problems. In the proposed method, a cost-sensitive deep classifier is used to solve the class imbalance problem, and the domain adversarial subnet with the intraclass maximum mean discrepancy (MMD) is used to minimize the marginal and conditional distributional discrepancy between the source (data under one working condition) and target domain (data under another working condition) simultaneously. The performance of deep Imba-DA is evaluated and analyzed on the Case Western Reserve University (CWRU) and Paderborn datasets. The results show that deep Imba-DA outperforms other baseline methods on bearing diagnostic tasks. • An imbalanced bearing fault diagnostic model under variant conditions is proposed. • A joint transfer network with marginal and conditional distribution is developed. • Pseudo label strategy guarantees a good accuracy and fast convergence. [ABSTRACT FROM AUTHOR]

Statistical analysis of SRAM has emerged as a challenging issue because the SRAM cell failure probability is extremely small. In this paper, we develop a novel efficient sampling, searching and estimating method to capture the probability of SRAM failure. Particularly, we propose an innovative Adaptive Multi-Level Sliding-Window (AMLSW) method to find the failure boundary in the parameter space with less computational cost. The proposed AMLSW method applies an integrated optimization engine to adaptively explore the failure boundary by sampling a sequence of parameter points and calculating the simulation result in sliding windows. Its key features include ellipsoid transformation, multi-level grid partition and sliding window algorithm to make our method efficient and accurate for finding the SRAM failure probability and failure boundary in parameter space. Furthermore, we provide theoretical analysis on our new AMLSW method. The experimental results of a commercial 65 nm SRAM cell demonstrate that the AMLSW method achieves 1.7–40× runtime speed-up over the existing methods without surrendering accuracy, and dramatically high speed-up over normal M-C sampling method. Moreover, this new method provides the failure boundary in the parameter space as shown in experiments. [ABSTRACT FROM AUTHOR]

In multimedia processing area, image/video frame resizing is recognized as one of the key techniques and has received more and more attention from the research community. It is necessary and very challenging for image/video distribution systems to be able to generate higher resolution video to meet high-end users’ requirements. In this paper, we analyze the bottleneck of hybrid DCT-Wiener scheme firstly and propose a w-norm signal reconstruction scheme from partial frequency coefficients for upsampling based on uncertainty principles. In the proposed scheme, we design a w-norm model to reconstruct up-sized image/video frames by solving convex optimization with constraints. The proposed scheme combines Wiener filter with compressive sensing (CS) theory seamlessly to automatically control the accuracy of both low- and high-frequency components. This scheme can efficiently avoid the fake contours and ringing effects which are the main defects of hybrid DCT-Wiener methods (hybrid methods). Experiments have been carried out to demonstrate that the proposed scheme can achieve significant PSNR and SSIM gains over typical CS schemes and original hybrid method. On the other hand, the proposed scheme controls the accuracy of both low- and high-frequency components by calculating the correlation between reconstructed signals and sampling matrixes during reconstruction which is a good solution to reduce fake contours and ringing effect. This scheme can also achieve noticeable visual quality improvement compared with hybrid methods and typical CS methods. [ABSTRACT FROM AUTHOR]

• Difference of damage modes caused by the boundary conditions of primary load-bearing yarns. • Straightening effect of braided yarns with undulations under low-velocity impact. • Variation of off-axial angles leading to the transition of failure modes. The sensitivity of off-axial angle on impact response was investigated by experimental and numerical methods in this work. Three types of braided laminates with different on/off-axial angles in terms of OA00, OA225 and OA45 were prepared and low-velocity impact tests with various energy levels were performed. Meso-level finite element model (FEM) was also developed to reveal impact damage initiation and development. We discovered that the boundary condition of primary load-bearing yarns depending on the off-axial angles caused the difference of structural deformation and stress distribution of braiding yarns during impact process. Due to the restriction of the pressurized tips, the straightening effect of primary load-bearing yarns with heavy waviness caused its out-of-plane movement and related main cracks in OA00 specimen. In addition, the matrix resin cracks were found at the edge of the specimen because of in-plane shear movement of braiding yarns. As for OA45 specimen, more evident bending deformation was observed, resulting in elevated tensile stress of braiding yarns on non-impact side. The variation of off-axial angle from 0 to 45 degree led to the failure mode transforming from the extensive matrix damage on specimen edge to the severe fiber breakage on non-impact side. As a medium off-axial angle, OA225 specimen exhibited a mixture failure mode to resist impact and achieved excellent performance with respect to higher peak force and delayed load dropping. [Display omitted] [ABSTRACT FROM AUTHOR]

We investigate r -process nucleosynthesis and kilonova emission resulting from binary neutron star (BNS) mergers based on a three-dimensional (3D) general-relativistic magnetohydrodynamic (GRMHD) simulation of a hypermassive neutron star (HMNS) remnant. The simulation includes a microphysical finite-temperature equation of state (EOS) and neutrino emission and absorption effects via a leakage scheme. We track the thermodynamic properties of the ejecta using Lagrangian tracer particles and determine its composition using the nuclear reaction network SkyNet. We investigate the impact of neutrinos on the nucleosynthetic yields by varying the neutrino luminosities during post-processing. The ejecta show a broad distribution with respect to their electron fraction Ye , peaking between ∼0.25–0.4 depending on the neutrino luminosity employed. We find that the resulting r -process abundance patterns differ from solar, with no significant production of material beyond the second r -process peak when using luminosities recorded by the tracer particles. We also map the HMNS outflows to the radiation hydrodynamics code SNEC and predict the evolution of the bolometric luminosity as well as broadband light curves of the kilonova. The bolometric light curve peaks on the timescale of a day and the brightest emission is seen in the infrared bands. This is the first direct calculation of the r -process yields and kilonova signal expected from HMNS winds based on 3D GRMHD simulations. For longer-lived remnants, these winds may be the dominant ejecta component producing the kilonova emission. [ABSTRACT FROM AUTHOR]

: A widespread application of integrin αvβ3 imaging has been emerging in both pre-clinical and clinical studies. But few studies reported its value as compared with 18F-FDG PET, especially for differentiated thyroid cancer (DTC). In this study, we compared the tracer uptake of 18F-AIF-NOTA-PRGD2 and 18F-FDG in lymph node metastasis of DTC to evaluate 18F-AIF-NOTA-PRGD2 as compared with 18F-FDG. Methods: 20 DTC patients with presumptive lymph node metastasis were examined with 18F-AIF-NOTA-PRGD2 and 18F-FDG PET/CT. 16 patients undergoing fine needle aspiration biopsy (FNAB) were evaluated by cytology results. For lesions without FNAB, the findings of clinical staging procedures served as the standard of reference (including neck ultrasound and serum thyroglobulin). Results: A total of 39 presumptive lymph node metastases were visualized on PET/CT images. 35 lesions were confirmed as malignant by FNAB and other clinical findings. The mean 18F-AIF-NOTA-PRGD2 in radioactive iodine-refractory (RAIR) lesions and benign lesions were 2.5±0.9 and 2.8±0.9 respectively. The mean SUV for 18F-FDG in all malignant lesions was 4.5±1.6 while in benign lesions it was 3.3±1.2. For all malignant lesions, the mean SUV for 18F-FDG was significantly higher than that for 18F-AIF-NOTA-PRGD2 (P<0.05). No significant correlation was found between the SUVs of 18F-AIF-NOTA-PRGD2 and 18F-FDG for 35 lesions (r = 0.114, P = 0.515). Moreover, 15 lesions of which the diameter larger than 1.5cm had higher 18F-AIF-NOTA-PRGD2 uptake as compared with the lesions smaller than 1.5cm. Conclusion: Although most lymph node metastases of DTC showed abnormal uptake of 18F-AIF-NOTA-PRGD2, its diagnostic value was inferior to 18F-FDG. No correlation was found between the uptake of 18F-AIF-NOTA-PRGD2 and 18F-FDG, which may suggest the two tracers provide complementary information in DTC lesions. [ABSTRACT FROM AUTHOR]