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BACKGROUND Many studies have examined associations between dietary isoflavones and atherosclerosis, but few used objective biomarkers. OBJECTIVES We examined the associations of isoflavone biomarkers (primary analyses) and equol production (secondary analyses) with the progression of carotid intima-media thickness (cIMT), and whether inflammation, systolic blood pressure (SBP), blood lipids, and sex hormone-binding globulin (SHBG) mediated these associations, in Chinese adults. METHODS This 8.8-y prospective study included 2572 subjects (40-75 y old) from the GNHS (Guangzhou Nutrition and Health Study; 2008-2019). The concentrations of daidzein, genistein, and equol were assayed by an HPLC-tandem MS in serum (n = 2572) at baseline and in urine (n = 2220) at 3-y intervals. The cIMT of the common carotid artery (CCA) and bifurcation segment were measured by B-mode ultrasound every 3 y, and the progressions of cIMT ( ∆cIMT) were estimated using the regression method. RESULTS Multivariable linear mixed-effects models (LMEMs) and ANCOVA revealed that subjects with higher serum isoflavones tended to have lower increases of CCA-cIMT. The mean ± SEM differences in 8.8-y ∆CCA-cIMT between extreme tertiles of serum isoflavones were -17.1 ± 8.4, -20.6 ± 8.3, and -23.3 ± 10.4 μm for daidzein, total isoflavone, and equol (P-trends

Recent years have witnessed the emergence of worldwide megalopolises and the accompanying public safety events, making urban safety a top priority in modern urban management. Among various threats, dangerous goods such as gas and hazardous chemicals transported through cities have bred repeated tragedies and become the deadly “bomb” we sleep with every day. While tremendous research efforts have been devoted to dealing with dangerous goods transportation (DGT) issues, further study is still in great need to quantify this problem and explore its intrinsic dynamics from a big data perspective. In this article, we present a novel system called DGeye , to feature a fusion between DGT trajectory data and residential population data for dangers perception and prediction. Specifically, DGeye first develops a probabilistic graphical model-based approach to mine spatio-temporally adjacent risk patterns from population-aware risk trajectories. Then, DGeye builds the novel causality network among risk patterns for risk pain-point identification, risk source attribution, and online risky state prediction. Experiments on both Beijing and Tianjin cities demonstrate the effectiveness of DGeye in real-life DGT risk management. As a case in point, our report powered by DGeye successfully drove the government to lay down gas pipelines for the famous Guijie food street in Beijing.

In recent years, short text topic modeling has drawn considerable attentions from interdisciplinary researchers. Various customized topic models have been proposed to tackle the semantic sparseness nature of short texts. Most (if not all) of them follow the bag-of-words assumption, which, however, is not adequate since word order and phrases are often critical to capturing the meaning of texts. On the other hand, while some existing topic models are sensitive to word order, they do not perform well on short texts due to the severe data sparseness. To address these issues, we propose the Pseudo-document-based Topical N-Grams model (PTNG), which alleviates the data sparsity problem of short texts while is sensitive to word order. Extensive experiments on three real-world data sets with state-of-the-art baselines demonstrate the high quality of topics learned by PTNG according to UCI coherence scores and more discriminative semantic representation of short texts according to classification results.

Employer Brand Evaluation (EBE) is to understand an employer’s unique characteristics to identify competitive edges. Traditional approaches rely heavily on employers’ financial information, including financial reports and filings submitted to the Securities and Exchange Commission (SEC), which may not be readily available for private companies. Fortunately, online recruitment services provide a variety of employers’ information from their employees’ online ratings and comments, which enables EBE from an employee’s perspective. To this end, in this article, we propose a method named Company Profiling–based Collaborative Topic Regression (CPCTR) to collaboratively model both textual (i.e., reviews) and numerical information (i.e., salaries and ratings) for learning latent structural patterns of employer brands. With identified patterns, we can effectively conduct both qualitative opinion analysis and quantitative salary benchmarking. Moreover, a Gaussian processes--based extension, GPCTR, is proposed to capture the complex correlation among heterogeneous information. Extensive experiments are conducted on three real-world datasets to validate the effectiveness and generalizability of our methods in real-life applications. The results clearly show that our methods outperform state-of-the-art baselines and enable a comprehensive understanding of EBE.

Background This study aimed to develop mortality-prediction models for patients with coronavirus disease-2019 (COVID-19). Methods The training cohort included consecutive COVID-19 patients at the First People’s Hospital of Jiangxia District in Wuhan, China, from 7 January 2020 to 11 February 2020. We selected baseline data through the stepwise Akaike information criterion and ensemble XGBoost (extreme gradient boosting) model to build mortality-prediction models. We then validated these models by randomly collected COVID-19 patients in Union Hospital, Wuhan, from 1 January 2020 to 20 February 2020. Results A total of 296 COVID-19 patients were enrolled in the training cohort; 19 died during hospitalization and 277 discharged from the hospital. The clinical model developed using age, history of hypertension, and coronary heart disease showed area under the curve (AUC), 0.88 (95% confidence interval [CI], .80–.95); threshold, −2.6551; sensitivity, 92.31%; specificity, 77.44%; and negative predictive value (NPV), 99.34%. The laboratory model developed using age, high-sensitivity C-reactive protein, peripheral capillary oxygen saturation, neutrophil and lymphocyte count, d-dimer, aspartate aminotransferase, and glomerular filtration rate had a significantly stronger discriminatory power than the clinical model (P = .0157), with AUC, 0.98 (95% CI, .92–.99); threshold, −2.998; sensitivity, 100.00%; specificity, 92.82%; and NPV, 100.00%. In the subsequent validation cohort (N = 44), the AUC (95% CI) was 0.83 (.68–.93) and 0.88 (.75–.96) for the clinical model and laboratory model, respectively. Conclusions We developed 2 predictive models for the in-hospital mortality of patients with COVID-19 in Wuhan that were validated in patients from another center.

The relationship of polyunsaturated fatty acids (PUFAs) with cardiovascular risk is still controversial. We aimed to determine whether erythrocyte n-3 and n-6 PUFAs are related to the risk of carotid atherosclerosis.From 2008 to 2019, baseline erythrocyte n-3 and n-6 PUFAs were determined in a cohort of 4040 Chinese adults (40-75 ys). The intima-media thickness (IMT) at the common carotid artery (CCA) and bifurcation of the carotid artery (BIF) and carotid plaque were assessed using ultrasonography at baseline and every 3 years.During a median follow-up of 8.8 years, we identified the following newly diagnosed cases: 535 cases of CCAIMT thickening, 654 cases of BIFIMT thickening, and 850 cases of carotid plaque. Higher erythrocyte docosahexaenoic acid (DHA) and arachidonic acid (ARA) and lower gamma-linolenic acid (GLA) were associated with decreased risks of BIFIMT thickening. N-3 eicosatrienoic acid (ETrA), docosapentaenoic acid (DPA), and n-6 dodecylthioacetic acid (DTA) presented a significant beneficial association with carotid IMT thickening in the short-term (2.8 y) follow-up (all p trend0.02), although the association was attenuated in the relatively long-term (8.8 y) follow-up. In addition, carotid plaque risk was found to be inversely associated with ETrA and DHA but positively associated with alpha-linolenic acid (ALA). N-6 linolenic acid (LA) and eicosadienoic acid (EDA) were not significantly associated with carotid atherosclerosis risk.Higher erythrocyte very-long-chain n-3 and n-6 PUFAs (especially DHA and ARA) and lower erythrocyte GLA are associated with lower carotid atherosclerosis risk, suggesting potential cardioprotective roles of very-long-chain PUFAs.

Fraud detection is usually compared to finding a needle in a haystack and remains a challenging task because fraudulent acts are buried in massive amounts of normal behavior and true intentions may be disguised in a single snapshot. Indeed, fraudulent incidents usually take place in consecutive time steps to gain illegal benefits, which provides unique clues for probing fraudulent behavior by considering a complete behavioral sequence rather than detecting fraud from a snapshot of behavior. Additionally, fraudulent behavior may involve different parties, such that the interaction patterns between sources and targets can help distinguish fraudulent acts from normal behavior. Therefore, in this paper, we model the attributed behavioral sequences generated from consecutive behaviors in order to capture the sequential patterns, while those that deviate from the pattern can be detected as fraudulence. Considering the characteristics of the behavioral sequence, we propose a novel model, NHA-LSTM, by augmenting the traditional LSTM with a modified forget gate, where the interval time between consecutive time steps is considered. Furthermore, we design a self-historical attention mechanism to allow for long time dependencies, which can help identify repeated or cyclical appearances. In addition, we propose an enhanced network embedding method, FraudWalk, to construct embeddings for the nodes in the interaction network with regard to higher-order interactions and particular time constraints for revealing potential group fraudulence. The node embeddings, along with the feature vectors, are fed into the model to capture the interactions between sources and targets. To validate the effectiveness of sequential behavior embeddings, we experiment on a real-world telecommunication dataset with prediction and classification tasks based on the learned embeddings. The experimental results show that the learned embeddings can better identify fraudulent behavior. Finally, we visualize the weights of the attention mechanism to provide a rational interpretation of human behavioral patterns.

Micro-service is a prevalent framework for Internet services. Its loosing coupling design has gained popularity recently. Loosing coupling services offer convenience, scalability and flexibility, however bring unexpected maintenance problems. This paper focuses on the problem where service administrations attempt to monitor the runtime services performance and status with mined service logs. To achieve it, we propose to extract unstructured logs as log patterns and visualise the services temporal relations using temporal graphs. Our analysis and data mining method can help to give new insights in system management area and non-trivial analysis process. The early experiments and analysis can clearly reveal inner structures of system and help to gain deep understanding.

In order to evaluate the performance of the slip critical bolted connection of HSS members, 30 specimens fabricated from high strength steel (HSS) (Q550, Q690 and Q890), are tested to investigate the slip factors of shot-blasted surface and rusted surface after blasting. For comparison, a group of specimens fabricated from mild steel Q345 are tested as well. In order to investigate the effect of the steel strength grade on slip factor, the values of hardness, roughness and capacity of plastic deformation of steels with different strength grades are also tested and analyzed. Based on experimental results and friction theory, it is found that with the same blasting treatment, the surface roughness tends to decrease with the increase of steel hardness, which induces the decreasing of the slip factor. Based on the friction mechanism, the slip factor is not only decided by surface roughness, but also can be affected by the capacity of plastic deformation of the contacting materials. With the increasing of plastic deformation capacity of the steel, the slip factor tends to be higher. According to the test results, the suggested slip factor of HSS specimens with blasted surfaces is 0.40. Moreover, for the specimens with rusted surface after blasting, there may be an increment in the slip factor owing to the increased surface roughness by rusting. However, the positive influence of rusting on the slip factor is not recommended to be considered in the connection design due to its instability. Therefore, the recommended slip factor of the specimen with rusted surface after blasting takes the value of 0.40 as well.

Background Several descriptive studies have reported that higher neutrophil count (NC) may be correlated with poor prognosis in patients with confirmed COVID‐19 infection. However, the findings from these studies are limited by methodology and data analysis. Methods This study is a cohort study. We non‐selectively and consecutively collected a total of 663 participants in a Chinese hospital from January 7 to February 28. Standardized and two‐piecewise Cox regression model were employed to evaluated the association between baseline neutrophil count (bNC), NC change rate (NCR), and death. Results bNC had a U‐shaped association with death. In the range of 0.1 to ≤1.49×109 /L (HR = 0.19, 95% CI = 0.05 to 0.66) and > 3.55×109 /L of bNC (HR = 2.82, 95% CI = 1.19 to 6.67), the trends on bNC with mortality were opposite. By recursive algorithm, the bNC at which the risk of the death was lower was range of >1.49 to ≤3.55×109 /L (HR=13.64, 95%CI=0.25 to 74.71). In addition, we find NCRs (NCR1 and NCR2) is not associated with COVID‐19‐related deaths. Conclusions Compared with NCR, bNC has the potential to be used for early risk stratification in patients with COVID‐19 infection. The relationship between bNC and mortality was U‐shaped. The safe range of bNC was 1.64 to 4.0 ×109 /L. Identifying the correlation may be helpful for early risk stratification and medical decision making. This article is protected by copyright. All rights reserved.

Objective Isoflavones and lignans are phytoestrogens present in plant-based foods, which have a potential preventive effect on breast carcinogenesis. The effects of phytoestrogens on breast cancer may differ according to the hormonal environment. This case-control study aimed to investigate the association between serum phytoestrogens and odds of breast cancer among Chinese pre- and postmenopausal women. Methods A total of 792 cases and 813 age-matched controls were included. Serum isoflavone (daidzein, genistein, glycitein, equol, and formononetin) and lignan (enterodiol and enterolactone) concentrations were measured using a liquid chromatography-tandem mass spectrometry method. Results Significant inverse associations were found between serum total soy isoflavone precursors, daidzein, genistein, formononetin, total lignans, enterodiol, enterolactone, and the odds of breast cancer in premenopausal but not postmenopausal women. For premenopausal women, the adjusted odds ratios (95% confidence intervals) for the highest versus the lowest serum concentration groups were 0.60 (0.41-0.87) for total soy isoflavones precursors, 0.64 (0.44-0.93) for daidzein, 0.62 (0.43-0.90) for genistein, 0.49 (0.35-0.68) for formononetin, 0.38 (0.25-0.57) for total lignans, 0.49 (0.33-0.73) for enterodiol, and 0.49 (0.33-0.74) for enterolactone. However, the interaction between serum phytoestrogens and menopausal status on odds of breast cancer was statistically significant only for daidzein. No significant association was found between serum equol or gycitein and the odds of breast cancer among either pre- or postmenopausal women. Conclusions Higher levels of certain serum isoflavones and lignans were associated with reduced odds of breast cancer in premenopausal women, but the interaction was statistically significant only for daidzein.

Background Little is known about the inter-relationship among fruit and vegetable intake, gut microbiota and metabolites, and type 2 diabetes (T2D) in human prospective cohort study. The aim of the present study was to investigate the prospective association of fruit and vegetable intake with human gut microbiota and to examine the relationship between fruit and vegetable-related gut microbiota and their related metabolites with type 2 diabetes (T2D) risk. Methods This study included 1879 middle-age elderly Chinese adults from Guangzhou Nutrition and Health Study (GNHS). Baseline dietary information was collected using a validated food frequency questionnaire (2008–2013). Fecal samples were collected at follow-up (2015–2019) and analyzed for 16S rRNA sequencing and targeted fecal metabolomics. Blood samples were collected and analyzed for glucose, insulin, and glycated hemoglobin. We used multivariable linear regression and logistic regression models to investigate the prospective associations of fruit and vegetable intake with gut microbiota and the association of the identified gut microbiota (fruit/vegetable-microbiota index) and their related fecal metabolites with T2D risk, respectively. Replications were performed in an independent cohort involving 6626 participants. Results In the GNHS, dietary fruit intake, but not vegetable, was prospectively associated with gut microbiota diversity and composition. The fruit-microbiota index (FMI, created from 31 identified microbial features) was positively associated with fruit intake (p p = 0.003) and the FMI-T2D association (OR 0.90, 95%CI 0.84–0.97) were both successfully replicated in the independent cohort. The FMI-positive associated metabolite sebacic acid was inversely associated with T2D risk (OR 0.67, 95%CI 0.51–0.86). The FMI-negative associated metabolites cholic acid (OR 1.35, 95%CI 1.13–1.62), 3-dehydrocholic acid (OR 1.30, 95%CI 1.09–1.54), oleylcarnitine (OR 1.77, 95%CI 1.45–2.20), linoleylcarnitine (OR 1.66, 95%CI 1.37–2.05), palmitoylcarnitine (OR 1.62, 95%CI 1.33–2.02), and 2-hydroglutaric acid (OR 1.47, 95%CI 1.25–1.72) were positively associated with T2D risk. Conclusions Higher fruit intake-associated gut microbiota and metabolic alteration were associated with a lower risk of T2D, supporting the public dietary recommendation of adopting high fruit intake for the T2D prevention.

Next location prediction has aroused great interests in the era of internet of things (IoT). With the ubiquitous deployment of sensor devices, e.g., GPS and Wi-Fi, IoT environment offers new opportunities for proactively analyzing human mobility patterns and predicting user’s future visit in low cost, no matter outdoor and indoor. In this paper, we consider the problem of next location prediction in IoT environment via a session-based manner. We suggest that user’s future intention in each session can be better inferred for more accurate prediction if patterns hidden inside both trajectory and signal strength sequences collected from IoT devices can be jointly modeled, which however existing state-of-the-art methods have rarely addressed. To this end, we propose a trajectory and sIgnal sequence (TSIS) model, where the trajectory transition regularities and signal temporal dynamics are jointly embedded in a neural network based model. Specifically, we employ gated recurrent unit (GRU) for capturing the temporal dynamics in the multivariate signal strength sequence. Moreover, we adapt gated graph neural networks (gated GNNs) on location transition graphs to explicitly model the transition patterns of trajectories. Finally, both the low-dimensional representations learned from trajectory and signal sequence are jointly optimized to construct a session embedding, which is further employed to predict the next location. Extensive experiments on two real-world Wi-Fi based mobility datasets demonstrate that TSIS is effective and robust for next location prediction compared with other competitive baselines.

Saturated fatty acids with different chain lengths have different biological activities, but little is known about very-long-chain saturated fatty acids (VLCSFAs). This study investigated the associations between the circulating VLCSFAs and cardiovascular health. This community-based cohort study included 2198 adults without carotid artery plaques (CAPs) at baseline. The percentage of baseline erythrocyte VLCSFA (arachidic acid (C20:0), behenic acid (C22:0), and lignoceric acid (C24:0)) was measured by gas chromatography. The presence of CAPs was determined at baseline and every 3 years thereafter by ultrasound examination. A meta-analysis was conducted to summarize the pooled associations between circulating VLCSFAs and the risk of cardiovascular diseases (CVDs). During a median of 7.2 years of follow-up, 573 women (35.1%) and 281 men (49.6%) were identified as CAP incident cases. VLCSFAs were inversely related with CAP risk in women (all p-trend &lt, 0.05) but not in men. Multivariate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of CAPs for the highest (vs. lowest) quartile were 0.80 (0.63&ndash, 1.01) for C20:0, 0.71 (0.56&ndash, 0.89) for C22:0, 0.75 (0.59&ndash, 0.94) for C24:0, and 0.69 (0.55&ndash, 0.87) for total VLCSFAs in women. The pooled HRs (95% CIs) of CVDs for the highest (vs. lowest) circulating VLCSFAs from seven studies including 8592 participants and 3172 CVD events were 0.67 (0.57&ndash, 0.79) for C20:0, 0.66 (0.48&ndash, 0.90) for C22:0, and 0.57 (0.42&ndash, 0.79) for C24:0, respectively. Our findings suggested that circulating VLCSFAs were inversely associated with cardiovascular health.

In vitro and in vivo studies suggested that flavonols, flavones, flavanones and flavan-3-ols have preventive effects on breast carcinogenesis. Epidemiological evidence about the associations between these flavonoid biomarkers and breast cancer risk is limited. This study aimed to investigate the association between serum concentration of these flavonoids and breast cancer risk among Chinese women. This hospital-based case–control study recruited 792 breast cancer cases and 813 age frequency-matched (5-year interval) controls who provided eligible blood samples in Guangdong Province, China. Ultra-high-performance liquid chromatography–tandem mass spectrometry was used to measure flavonoids. Unconditional logistic regression was used to estimate the odds ratio (OR) and 95% confidence internal (CI). Higher concentrations of serum flavonols, isorhamnetin, kaempferol, flavanones and naringenin were significantly associated with lower breast cancer risk, with adjusted ORs (95% CIs) for the highest versus the lowest group of 0.66 (0.49–0.89) for flavonols, 0.52 (0.38–0.70) for isorhamnetin, 0.60 (0.45–0.80) for kaempferol, 0.65 (0.49–0.87) for flavanones and 0.45 (0.34–0.60) for naringenin, respectively. Significant positive associations were observed between serum flavan-3-ols, epigallocatechin, epigallocatechin-3-gallate and breast cancer risk. No significant associations were observed for serum quercetin, flavones, apigenin, luteolin, hesperetin, catechin, epicatechin and epicatechin-3-gallate with overall breast cancer risk. This study suggested that serum flavonols and flavanones were inversely associated with breast cancer risk and serum flavan-3-ols were positively associated with breast cancer risk. Serum flavones were not associated with overall breast cancer risk. These findings warrant further confirmation in prospective studies.

BACKGROUND Lumbar disc herniation (LDH) places a serious burden on the daily lives and socioeconomics of people. Although the pathogenesis of LDH is complex, genetic factors such as single nucleotide polymorphisms (SNPs) may affect the risk of developing LDH. In the present study, we aimed to elucidate the effect of RAB40C SNPs on the risk of LDH in the Chinese Han population. METHODS We investigated 508 LDH cases and 508 healthy controls for this case-control study. Three tag SNPs in RAB40C were selected and genotyped using the Agena MassARRAY platform (Agena Bioscience, San Diego, CA, USA). After adjusting for age and gender, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using unconditional logistic regression. RESULTS In the allele model, we found rs62030917 and rs2269556 in RAB40C with a minor G allele significantly increased the risk of LDH (rs62030917: OR = 1.23, 95% CI = 1.00-1.50, p = 0.046; rs2269556: OR = 1.21, 95% CI = 1.02-1.45, p = 0.033). In genetic model analysis, rs2269556 was associated with an increased risk of LDH under both codominant (OR = 1.49, 95% CI = 1.03-2.15, p = 0.035) and log-additive models (OR = 1.21, 95% CI = 1.01-1.45, p = 0.035). rs62030917 of RAB40C was associated with an increased risk of LDH under codominant, recessive and log-additive models (p < 0.05) only among individuals younger than 49 years after stratification by age. CONCLUSIONS For the first time, our results suggest that rs62030917 and rs2269556 in the RAB40C gene influence genetic susceptibility to LDH.

BACKGROUND This study aimed to evaluate the biomechanical stress of the internal fixation screws and vertebral bodies after the full-segment, interval, key vertebral, and strategy pedicle screw fixations under 7 work conditions in a patient with adult degenerative scoliosis (ADS) using finite elements (FE) analysis. MATERIAL AND METHODS A patient with ADS underwent internal fixation by pedicle screws after posterior incision in combination with subtotal laminectomy decompression and bone graft fusion, and received thin-layer computed tomography (CT) spine scanning at T12-L5. The CT data were used to constitute three-dimensional FE full-segment, interval, key vertebral, and strategic pedicle screw models. The stress of each screw-rod system under different working conditions was evaluated. RESULTS Forward flexion, backward extension, lateral flexion, and rotation greatly increased the force of the pedicle screw systems. The maximum stress of the screw-rods was the lowest in the full-segment model under almost all the working conditions except for the upright situation. The maximum stress of the vertebral bodies was the minimum in the strategic model under all the 7 working conditions, followed by that in the key vertebra and full-segment models. CONCLUSIONS Collectively, the strategic and key vertebra pedicle screw schemes can decrease the biomechanical stress of screw-rod systems and vertebral bodies, which is close to the full-segment scheme. Our results may help explore the optimal surgical means for pedicle screw fixation for ADS patients, which can maximally reduce the risk of screws-related postoperative complications and simultaneously maintain a reasonable 3D orthopedic effect.

Background Changes in platelet count are common in COVID-19 patients. The platelet count reflects the thrombocyte turnover, acting as a sensitive indicator of illness severity that is of great clinical utility to monitor a quickly changing health condition of patients affected by aggressive viral infections. This study aims to investigate the significance of platelet count during the progression of the disease in COVID-19 patients. Methods A total of 532 COVID-19 patients were involved in the cohort study from the First People’s Hospital of Jiangxia District in Wuhan from January 7, 2020, to February 28, 2020. We collected the clinical characteristics and laboratory data of patients. Patients still hospitalized before February 29, 2020, died on admission, with malignant tumors, previous gastrointestinal surgery, missing baseline platelet count, or platelet count detected only once, were excluded. We used a generalized additive model and generalized additive mixed model to compare trends in platelet count over time among survivors and non-survivors, with an adjustment for potential confounders. Results During the follow-up, twenty-nine subjects died (mortality rate, 5.45%). The platelets among non-survivors decreased and among survivors increased gradually within 1 week after admission. In addition, the difference between the two groups showed an increasing trend during 1 week after admission. This difference increased by an average of 5.3 × 10^9/L daily. Conclusions In the early stage, platelet count can dynamically reflect the pathophysiological changes in COVID-19 patients. Early decrease in platelet count was associated with mortality in patients with COVID-19. Causality, however, cannot be deduced from our data.

Background: COVID-19 has caused a large number of deaths in a short period and lacks a specific treatment Early identification of poor prognosis patients may f

Background: Several descriptive studies have reported that higher neutrophil count (NC) may be correlated with poor prognosis in patients with confirmed COVID19

The objective of this paper was to evaluate the influence of initial flaws in the beam-column connections on the seismic performance of steel frame structures. The finite element models were constructed with different initial flaw lengths by ABAQUS. The initial flaw length was 0, 8, and 16 mm, respectively. The dynamic elastic-plastic time history analysis and the pushover analysis were conducted to obtain the probabilistic characteristics of seismic demand and seismic capacity. Seismic demands are quantified in terms of the maximum drift angle (RDA) and the displacement ductility ratio $$ \left( {\mu_{d} } \right) $$ . Moreover, the peak ground acceleration (PGA) was used for the pushover analysis. Formulas considering the influence of initial flaws on failure probability of a structure were derived for each length using different design basic acceleration of ground motion. The fragility curves were further constructed based on the data of seismic demand and capacity. The results show that the fragility of steel frame structures is similar across different seismic demand parameters. In addition, the analyses of fragility curves obviously indicate that the seismic fragility of steel frame structures increases as flaw length increases. Finally, the fragility of steel frame structures with initial flaws is consistent using different design basic acceleration of ground motion.

Aspect-based opinion mining is finding elaborate opinions towards a subject such as a product or an event. With explosive growth of opinionated texts on the Web, mining aspect-level opinions has become a promising means for online public opinion analysis. In particular, the boom of various types of online media provides diverse yet complementary information, bringing unprecedented opportunities for cross media aspect-opinion mining. Along this line, we propose CAMEL, a novel topic model for complementary aspect-based opinion mining across asymmetric collections. CAMEL gains information complementarity by modeling both common and specific aspects across collections, while keeping all the corresponding opinions for contrastive study. An auto-labeling scheme called AME is also proposed to help discriminate between aspect and opinion words without elaborative human labeling, which is further enhanced by adding word embedding-based similarity as a new feature. Moreover, CAMEL-DP, a nonparametric alternative to CAMEL is also proposed based on coupled Dirichlet Processes. Extensive experiments on real-world multi-collection reviews data demonstrate the superiority of our methods to competitive baselines. This is particularly true when the information shared by different collections becomes seriously fragmented. Finally, a case study on the public event “2014 Shanghai Stampede” demonstrates the practical value of CAMEL for real-world applications.

Bolt pre-tension is regularly used in the practical case of bearing-type connection. Due to confinement of lap plates, complicate triaxial stress field can be observed near bolt hole, which may affect bearing behavior of the whole connection. Currently, investigations on the related issues are limited. To fill this research gap, this paper presents a combined experimental and numerical study on high strength steel single-bolt connections with bolt pre-tension. Results reveal several meaningful recognitions on the bearing behavior of connection with bolt pre-tension. Firstly, the effect of bolt pre-tension on the final tearout failure mode is negligible. Secondly, distribution of triaxial stress field initiates with a circular pattern and gradually shrinks to a localized pattern between shear fracture lines at ultimate resistance of the connection. Thirdly, out-plane confinement will limit the piling-up of plate material in front of bolt, which will reduce the related bearing resistance. However, increasing bolt grade is still beneficial to the whole connection due to a trade-off between ultimate resistance of the connection and related bearing resistance. Comparison with current code is further conducted. It is found that current Eurocode3 has adequate design safety for connection with bolt pre-tension while extra safety is needed for current AISC 360-16.

High Strength Structural (HSS) steels, with nominal yield strength greater than 450 MPa exhibit phenomena including Lode angle dependence of yield, and accelerated cyclic softening at large strains that cannot be conveniently simulated by existing constitutive models that are developed primarily for conventional strength structural steels. This paper presents an experimental study consisting of 25 coupon scale tests (monotonic and cyclic) as well as 2 large scale cantilever column tests. According to experimental results, a classical combined isotropic and kinematic hardening constitutive model, the Armstrong and Frederick (A-F) model is identified by using the particle swarm optimization (PSO) algorithm. However, the yield plateau region and full-range softening behavior of HSSs under cyclic loading are difficult to be captured by the A-F model. A new constitutive model, termed the HSS-TD model with consideration of the yield plateau and three-stage strength softening, is formulated to simulate the response of HSS steels. The HSS-TD model shows significantly lower errors relative to the conventional A-F model, when assessed relative to test data. Moreover, the limitations of the HSS-TD model including influence of strain history and nonproportional loading are discussed.

Recently structural members fabricated of high strength constructional steels in civil and building engineering has been widely explored. However, their usage in earthquake zones is still restricted by seismic standards worldwide due to its poor ductility. In order to attain potential seismic application, this paper conducted five cyclic lateral loading experiments on H-shaped beam-columns fabricated of Q690D high strength structural steel. The tested members were cyclically bent about the weak axis. It was recognized that the low-fatigue fracture of edge fiber around bottom cross-section was the main failure mode. Besides, the hysteretic curves, cyclic backbones and energy dissipation characteristics were thoroughly discussed. The ultimate inter-storey drift was greater than the limitation of 1/50. All tested beam-columns exhibit favorable cyclic deformability and energy dissipated ability. To further study the influence of several factors, a series of FEA simulations were performed through verified numerical models. Ductile damage behaviors and advanced cyclic constitutive relationships were considered to improve the simulation performance. The influences of plate component slenderness and axial load ratio on seismic performance of steel beam-columns were thoroughly discussed. It is concluded that there exist interdependence characteristics between different influential factors on seismic performance.

Chaboche model has gained prominent utilization in numerical simulation on cyclic behaviors of metal structure. However, the calibration of its material parameter may produce considerable cost. A simplified calibration way is of great importance to ease its application. To this end, a re-evaluation on chaboche model material parameters and simulated elastic-plastic laws was conducted regarding various steel grades. Futhermore, the characterisitcs of isotropic softening was coupled with the present model hardening rule. The kinematic rule was correlated with cumulative plastic strain. The modified model was then calibrated and validated base upon the coupon test result on 41 batches of steels, whose yield stress ranges from 100 MPa to 890 MPa. The calibrated material parameter were then correlated with corresponding monotonic mechanical properties. Accordingly, a simplified calibration procedure, based upon which the material parameters of modifed Chaboche model can be fastly estimated by yield strength and yield ratio, was constructed. As for low yield point steels, mild steels and high strength steels, this calibration method can ease the calibration of modified Chaboche model considerably.

The relationship between von Mises equivalent stress σ ¯ and equivalent plastic strain e ¯ (PEEQ), termed as von Mises stress-strain, plays an important role in numerical simulations for ductile fracture of structural metallic materials with large plastic strain. The standard uniaxial tensile test on cylindrical specimens is the most straightforward method to derive the ( σ ¯ − e ¯ ) data. However, the distribution of the stress and strain along the necking section of the tensile specimen is no longer uniform in the post-necking process, which induces difficulty in acquiring the ( σ ¯ − e ¯ ) data. The existing correction methods to identify von Mises stress-strain in the post-necking regime need instantaneous geometry of the notched region and ignore influence of the initial geometry of the specimen, which induces these methods are inconvenient for application and inapplicable for circumferentially notched tensile specimens to determine ( σ ¯ − e ¯ ) of each individual material zone in a hybrid coupon (e.g. weldment). In the present study, influences of initial geometry of the specimen and plastic hardening property of material on necking process are investigated firstly. It is found that the shrinking behavior of the minimum cross-section of the specimen is determined by the geometric parameter of specimen and plastic hardening exponent of materials. Based on an extensive parametric study a modified power law function to characterize the von Mises stress-strain curve from tensile tests on circumferentially notched specimens without measuring instantaneous geometry of cross-section is proposed.

Background Evolocumab (AMG 145), a PCSK9 inhibitor, has been shown to decrease low-density lipoprotein cholesterol (LDL-C) levels. Doses of 140 mg administered every 2 weeks (Q2W) and 420 mg administered every 4 weeks (Q4W) are widely used, and both dosing schedules were effective in clinical trials. However, some researchers have speculated that 140 mg Q2W administration has equal or even greater efficacy. This meta-analysis was performed to assess the differences in efficacy and safety between the two doses. Methods We searched the PubMed, EMBASE, and Web of Science databases to identify relevant clinical trials published before January 2016. A total of 2403 patients from 8 randomized controlled trials were identified and included in the analysis. Results Evolocumab administered at 140 mg Q2W resulted in a greater percent change from baseline in LDL-C concentration (− 7.27; 95% confidence interval (CI), − 10.36 to − 4.18) and had greater efficacy in achieving the treatment goal of LDL-C ≤ 1.8 mmol/L with an relative risk (RR) of 1.09 (95% CI, 1.00 to 1.18) compared with 420 mg Q4W in patients who were concomitantly treated with statins. These findings were not significantly different between the 140 mg Q2W and 420 mg Q4W groups when evolocumab was administered as monotherapy. There was no difference in the rate of occurrence of the main treatment-related adverse events between the two doses. Conclusions Evolocumab administered at 140 mg Q2W was more effective than the 420 mg Q4W dosage at lowering lipid concentrations, especially in patients who concomitantly received stable statin therapy.

A new uniform shallow trenches termination (ST 2 ) with field plate for high-voltage VDMOS transistor is proposed in this Letter. In ST 2 structure, the electric field near the source is decreased and the depletion region is extended by the field plate, besides, many electric field peaks are introduced in shallow trenches under the field plate and the average electric field strength is increased, both improve the characteristic of the breakdown voltage (BV). Simulation results show the BV of ST 2 VDMOS is 706 V with a termination length L d = 132 μm, which reaches 97% of that of the parallel-plane junction, and the influence of the edge curvature effect is almost entirely eliminated. The ST 2 structure is compatible with conventional CMOS process with only one additional mask and its fabrication is low-cost.

Previous investigations have shown that changes in total prostate volume (TPV) are highly variable among aging men, and a considerable proportion of aging men have a stable or decreasing prostate size. Although there is an abundance of literature describing prostatic enlargement in association with benign prostatic hyperplasia, less is known about the appropriate age cut-off points for TPV growth rate. In this community-based cohort study, TPV was examined once a year in men who had consecutive health checkup, during a follow-up of 4 years. A total of 5058 men (age 18-92 years old) were included. We applied multiple regression analyses to estimate the correlation between TPV growth rate and age. Overall, 3232 (63.9%) men had prostate growth, and 1826 (36.1%) had a stable or decreased TPV during the study period. The TPV growth rate was correlated negatively with baseline TPV (r=-0.32, P

Fraud detection is usually regarded as finding a needle in haystack, which is a challenging task because fraudulences are buried in massive normal behaviors. Indeed, a fraudulent incident usually takes place in consecutive time steps to gain illegal benefits, which provides unique clues to probing frauds by considering a complete behavioral sequence, rather than detecting frauds from a snapshot of behaviors. Also, fraudulent behaviors may entail different parties, such that the interaction pattern between sources and targets can help distinguish frauds from normal behaviors. Therefore, in this paper, we model the attributed behavioral sequences generated from consecutive behaviors, in order to capture the sequential patterns, while those deviate from the pattern can be regarded as fraudulence. Considering the characteristics of behavioral sequence, we propose a novel model, HAInt-LSTM, by augmenting traditional LSTM with a modified forget gate where interval time between consecutive time steps are considered. Meanwhile, we employ a self-historical attention mechanism to allow for long-time dependencies, which can help identify repeated or cyclical appearances. In addition, we encode the source information as an interaction module to enhance the learning of behavioral sequences. To validate the effectiveness of the learned sequential behavior representations, we experiment on real-world telecommunication dataset under both supervised and unsupervised scenarios. Experimental results show that the learned representations can better identify fraudulent behaviors, and also show a clear cut with normal sequences in the lower dimensional embedding space through visualization. Last but not least, we visualize the weights of attention mechanism to provide rational interpretation of human behavioral periodicity.

Spinal cord injury (SCI) comprises nerve and motor function disorders that may be caused by a variety of damaging factors and is challenging to treat. The aim of the present study was to investigate the regenerative effects of neural stem cell (NSC) transplantation combined with intraperitoneal injection of erythropoietin (EPO) on cross-sectional SCI in rats. A model of SCI was induced in 40 adult Wistar rats via the complete transection of the 10th thoracic vertebra (T10). The rats were allocated at random into 4 groups: Control, NSC, EPO and NSC + EPO groups (n=10 per group). Morphological alterations associated with axonal regeneration were detected using neurofilament (NF)-200 immunohistochemistry and immunofluorescence staining after 8 weeks. Basso, Beattie and Bresnahan (BBB) scoring was used to evaluate the recovery of hindlimb function. A total of 5 rats died following surgery, including 2 control rats and 1 rat each in the EPO, NSC and NSC + EPO groups. NSCs labeled with bromodeoxyuridine were observed to have survived and migrated in the spinal cord tissue after 8 weeks. Significant histomorphological differences were observed in the NSC and NSC + EPO groups compared with the EPO and control groups. Furthermore, the rats of the NSC + EPO group exhibited significantly enhanced axonal regeneration in the SCI area compared with the NSC group rats. The rats of the NSC and NSC + EPO groups exhibited significantly improved BBB scores compared with the EPO and control group rats at 7 days after treatment (P

This paper presents an experimental and numerical investigation on the bearing behavior of multi-bolt high strength steel connections in single bolt line. Three grades of high strength steel with nominal yield stress of 550 MPa, 690 MPa and 890 MPa were used to fabricate thirty lap connections with two or three bolts. It is found that the deformation capability of high strength steel plate near bolt hole is sufficient to meet the deformation demand of compatibility in multi-bolt connection even with an intended bolt hole misalignment of 2 mm for M24 high strength bolt. The comparison with Eurocode3 and AISC 360-16 is conducted. When no partial or safety factors are considered, the original formulae of Eurocode3 already has sufficient safety while AISC 360-16 gives unsafe predictions. Numerical models were established and verified by test results. With the obtained results, the full-range distribution of internal load among different bolts can be divided into four stages. Features for each stage are summarized and the effect of bolt hole misalignment on the distribution pattern is evaluated. Numerical analysis results indicate that, behavior of an individual bolt in multi-bolt connection may be influenced by surrounding bolts. The formation of critical yielding band between different bolts may explain this influence. Based on the experimental and numerical analyses, this paper proposed a new ultimate bearing resistance model for multi-bolt connections. The proposed model is capable of describing the nonlinearity in the ultimate bearing resistance of multi-bolt connection and achieves improved predicting accuracy compared to classical models.

In order to evaluate the slip performance of hybrid connections between high strength steel and mild steel, 30 hybrid connection specimens between high strength steel (Q550, Q690 and Q890) and mild steel (Q235 and Q345) with shot-blasted surface are designed to measure slip factors. The test results are compared with the slip factors measured from the connections with the same grade of high strength steel. According to the test results, the slip factors of hybrid connections are lower than the slip factor of 0.5 for mild steel specified in existing design code. Furthermore, the influence of steel strength grade on slip factor is investigated based on friction mechanism. It can be concluded that with the increase of steel grade, the slip factor of hybrid connection tends to decrease due to the reduction of surface roughness and the reduced potential increase in contact surface by plastic deformation. The slip factor of 0.45 is recommended for hybrid connections between Q550 or Q690 and Q235 mild steel. The slip factor of 0.40 is recommended for hybrid connections between Q550 or Q690 and Q345 mild steel. For hybrid connections between Q890 and mild steel Q235 or Q345, slip factor of 0.40 is recommended.

With the tremendous development of Internet, many domain-specific new words appear in various media text streams such as forums, Sina Weibo, Wechat, etc. These new words are always a group of important words in specific domains and are significant for NLP tasks. Most existing models have time-consuming processing or cannot handle out of vocabulary (OOV) words on streaming and online scenes. In this paper, we propose an unsupervised method, D-TopWords with Gaussian LDA, to perform online detection of domain-specific new words effectively. Different from traditional new words detection models, our method is a joint statistical model based on a finite word dictionary without any handcraft features. By further introducing Gaussian LDA into our model, we solve properly the problem of OOV words from new text streams. Experimental results show that our work can successfully extract domain-specific new words and it has a better performance in online detection task than some state-of-the-art methods.

Online advertising has attracted lots of attention in both academic and industrial domains. Among many realworld advertising systems, click through rate (CTR) prediction plays a central role. With a large volume of user history log and given its various features, it is quite a challenge to fully extract the meaningful information inside that amount of data. What's more, for many machine learning models, in order to achieve the best performance of the CTR prediction, a lot of hyper-parameters need to be tuned, which often costs plenty of time. In this paper, we propose an ensemble model named ETCF, which cascades GBDT with gcForest to tackle the practical problems of CTR prediction and do not need much hyper-parameter tuning work to realize its best performance. Experimental results validate the effective prediction power of ETCF against classical baseline models, and the superiority of GBDT transformed features.

Background and aims Dyslipidemia contributes to the development and progression of renal disease. The objective of this study was to investigate whether an elevated non-HDL-cholesterol to HDL-cholesterol ratio (NonHDLc/HDLc) predicts new-onset chronic kidney disease (CKD). Methods and results We followed 1891 Chinese adults with normal or near-normal kidney function at baseline who participated in an annual health checkup program for the occurrence of new-onset CKD [defined as an estimated glomerular filtration rate (eGFR) of 2 (low eGFR) and/or proteinuria (defined as urinary protein ≥1 + on dipstick testing)] or low eGFR. Cox proportional hazards models were used to examine the independent relationship between the plasma NonHDLc/HDLc ratio and new-onset CKD. During a median follow-up period of 2.8 years, 3% ( n = 57) of participants developed new-onset CKD. Compared with patients in the lowest tertile, patients with NonHDLc/HDLc ratios in the highest tertile had a 1.45-fold higher risk of new-onset CKD (hazard ratio [HR], 2.45; 95% confidence interval [95% CI], 1.07 to 5.61; P = 0.035) after adjustment for potential confounders. There was a marginally significant association with low eGFR (tertile 3 versus tertile 1: HR, 2.94; 95% CI, 0.98 to 8.82; P = 0.054). Conclusions NonHDLc/HDLc ratio is an independent risk factor for the development of CKD. Assessment of NonHDLc/HDLc ratio may help identify high risk groups with chronic kidney disease.

A non-dipper pattern of high blood pressure is associated with increased risk of organ damage and cardiovascular disease in patients with hypertension. The aim of the study was to evaluate the left ventricular (LV) remodeling and function and arterial stiffness in a dipper/non-dipper pattern of high blood pressure in patients with hypertension. A total of 183 hypertensive patients with no history of adverse cardiovascular events were divided into two groups based on 24 hours ambulatory blood pressure monitoring (ABPM): 66 patients with a dipper pattern and 117 patients with non-dipper pattern. Detailed transthoracic echocardiogram was performed and analyzed with advance speckle tracking 3-orthogonal direction strain analysis to assess LV systolic function and tissue Doppler-derived E/E′ for LV diastolic function assessment. Cardio ankle vascular index (CAVI) was used to evaluate arterial stiffness. Compared with patients with dipper hypertension, those with non-dipper hypertension had increased LV mass index, higher prevalence of eccentric and concentric LV hypertrophy, more impaired LV diastolic and systolic function and peripheral arterial stiffness. Multivariable analysis revealed that a non-dipper pattern was independently associated with LV systolic dysfunction evaluated by speckle tracking-derived strain analysis. In conclusion, a non-dipper pattern of hypertension is an independent risk factor for LV systolic dysfunction. Treatment that could reverse this non-dipper pattern may reduce cardiac damage in these patients.

With the rapid development of online social media, the short text has become the prevalent format for information of Internet. Due to the severe data sparsity issue, accurately discovering knowledge behind these short texts remains a critical challenge. Since regular topic models, such as the Latent Dirichlet Allocation (LDA), can not perform well on short texts, many efforts have been put on building different types of probabilistic topic models for short texts. Inducing topics from dense word-word space instead of sparse document-word space becomes an emerging solution for avoiding data sparsity issue, and the representative one is the Word Network Topic Model (WNTM). However, the word-word space building procedure of WNTM often imports much irrelevant information. In light of this, we propose the Robust WNTM (RWNTM), which can filter out unrelated information during the sampling. The experimental results demonstrate that our method can learn more coherent topics and is more accurate in text classification, as compared with WNTM and other state-of-the-arts.

A stacked lateral double-diffused metal–oxide–semiconductor field-effect transistor (LDMOS) with enhanced depletion effect by surface substrate is proposed (ST-LDMOS), which is compatible with the traditional CMOS processes. The new stacked structure is characterized by double substrates and surface dielectric trenches (SDT). The drift region is separated by the P-buried layer to form two vertically parallel devices. The doping concentration of the drift region is increased benefiting from the enhanced auxiliary depletion effect of the double substrates, leading to a lower specific on-resistance (R on,sp). Multiple electric field peaks appear at the corners of the SDT, which improves the lateral electric field distribution and the breakdown voltage (BV). Compared to a conventional LDMOS (C-LDMOS), the BV in the ST-LDMOS increases from 259 V to 459 V, an improvement of 77.22%. The R on,sp decreases from 39.62 mΩcm2 to 23.24 mΩcm2 and the Baliga's figure of merit (FOM) of is 9.07 MW/cm2.

The hybrid electric vehicle (HEV) is becoming one of the main trends of the development of automobile technology. The structure and operation principle of HEV are introduced. The noise and vibration (NV) of engine, motor, generator, power split device, converter assembly and battery in HEV were analyzed. According to the NV characteristics in HEV, the measurements for NV control technology such as the excitation source control technology and route control technology were summarized, which provides a reference for further studying of the NV in HEV.

We investigate the relationship of SNPs in XRCC1, ERCC1 and ERCC2 to methotrexate intravenous adriamycin and intra-arterial cisplatin chemotherapy response and survival in bone cancer patients. 281 consecutive patients diagnosed with bone tumor between January 2003 to January 2005, and they were followed up until the end of January 2010. Polymorphisms in XRCC1Arg280His, XRCC1Arg399Gln, ERCC1 Asn118Asn, ERCC1 Gln504Lys, ERCC2 Asp312Asn and ERCC2 Lys751Gln were detected based upon Sequenom MassARRAY platform. All 281 patients were followed up until the end of January 2010. The median follow-up time was about 43.9 months. Our study showed a longer survival rate in XRCC1 399 Arg/Arg genotype than Gln/ Gln, and with a significant increased death risk (HR=0.46, 95%CI=0.31-0.96). For ERCC1 Asn118Asn, the variant genotype T/T was strongly significantly associated with a higher event free survival when compared with the wide-type C/C, with the adjusted OR (95% CI) of 0.33(0.15-0.97). ERCC2 751 A/A genotype showed increased the event free survival of osteosarcoma (HR=0.45; 95%CI=0.15-0.91), and T allele genotype of ERCC2 Lys751Gln was significantly associated with low risk of death from osteosarcoma (HR=0.53, 95%CI= 0.28-0.95). This study is the first time to report the ERCC1 and ERCC2 gene polymorphisms might well be useful as a surrogate marker of clinical outcome in bone cancer. Key words: DNA repaired gene, polymorphisms, osteosarcoma, chemotherapy, response.

Recent years have witnessed the unprecedented growth of online social media, which empower short texts as the prevalent format for information of Internet. Given the nature of sparsity, however, short text topic modeling remains a critical yet much-watched challenge in both academy and industry. Rich research efforts have been put on building different types of probabilistic topic models for short texts, among which the self aggregation methods without using auxiliary information become an emerging solution for providing informative cross-text word co-occurrences. However, models along this line are still rarely seen, and the representative one Self-Aggregation Topic Model (SATM) is prone to overfitting and computationally expensive. In light of this, in this paper, we propose a novel probabilistic model called Pseudo-document-based Topic Model (PTM) for short text topic modeling. PTM introduces the concept of pseudo document to implicitly aggregate short texts against data sparsity. By modeling the topic distributions of latent pseudo documents rather than short texts, PTM is expected to gain excellent performance in both accuracy and efficiency. A Sparsity-enhanced PTM (SPTM for short) is also proposed by applying Spike and Slab prior, with the purpose of eliminating undesired correlations between pseudo documents and latent topics. Extensive experiments on various real-world data sets with state-of-the-art baselines demonstrate the high quality of topics learned by PTM and its robustness with reduced training samples. It is also interesting to show that i) SPTM gains a clear edge over PTM when the number of pseudo documents is relatively small, and ii) the constraint that a short text belongs to only one pseudo document is critically important for the success of PTM. We finally take an in-depth semantic analysis to unveil directly the fabulous function of pseudo documents in finding cross-text word co-occurrences for topic modeling.

We investigated the effect of neural stem cells (NSC) and erythropoietin (EPO) on axon regeneration in adult rats with transected spinal cord injury, and provided an experimental basis for clinical treatment. Forty Wistar rats with T10-transected spinal cord injury were randomly divided into four groups of ten rats: a control group (group A), an NSC-transplant group (group B), an NSC-transplant and EPO group (group C), and an EPO group (group D). Biotinylated dextran amines (BDA) anterograde corticospinal cord neuronal tracing and Fluoro-Gold (FG) retrograde tracing were carried out at the 8th week after operation to observe the regeneration of nerve fibers. The Basso, Beattie, and Bresnahan (BBB) locomotor score was used to evaluate restoration. 1) BDA and FG immunofluorescence staining: in group C, a large number of regenerated axons were observed and some penetrated the injured area. In group B, only a small number of regenerated axons were observed and none penetrated the injured area. In group D, only sporadic regenerated nerve fibers were observed occasionally, while in group A, no axonal regeneration was observed. In group C, a small number of cones and axons emitted yellow fluorescence, and no FG-labeled cells were observed in the other groups. 2) The BBB scores for group C were higher than those for the other groups, and the differences were statistically significance (P < 0.05). NSC transplantation combined with EPO intraperitoneal injection may benefit axon regeneration in rats with transected spinal cord injury, and accelerate the functional recovery of the hindlimb locomotor.

Aspect-based opinion mining is to find elaborate opinions towards an underlying theme, perspective or viewpoint as to a subject such as a product or an event. Nowadays, with rapid growing of opinionated text on theWeb, mining aspect-level opinions has become a promising means for online public opinion analysis. In particular, the booming of various types of online media provide diverse yet complementary information, bringing unprecedented opportunities for public opinion analysis across different populations. Along this line, in this paper, we propose CAMEL, a novel topic model for complementary aspect-based opinion mining across asymmetric collections. CAMEL gains complementarity by modeling both common and specific aspects across different collections, and keeping all the corresponding opinions for contrastive study. To further boost CAMEL, we propose AME, an automatic labeling scheme for maximum entropy model, to help discriminate aspect and opinion words without heavy human labeling. Extensive experiments on synthetic multicollection data sets demonstrate the superiority of CAMEL to baseline methods, in leveraging cross-collection complementarity to find higher-quality aspects and more coherent opinions as well as aspect-opinion relationships. This is particularly true when the collections get seriously imbalanced. Experimental results also show that the AME model indeed outperforms manual labeling in suggesting true opinion words. Finally, case study on two public events further demonstrates the practical value of CAMEL for real-world public opinion analysis.

The electromechanical impedance (EMI) technique, which employs piezoelectric ceramic (PZT) patches as transducers, is emerging as an effective and powerful technique in structural health monitoring (SHM). This paper presents a novel method to extract the damage-sensitive feature (DSF) for EMI-based SHM. Firstly, the concept of effective drive point (EDP) impedance was introduced briefly. Secondly, a novel DSF was proposed as the ratio of the active parts of EDP admittances before and after damages. Finally, the effectiveness of the proposed DSF was experimentally verified. The results show that the novel method provides a sensitive feature for EMI-based SHM

The part-through circumferential crack is a typical crack form in pipe structure, which often lead to the structure failure. Firstly, the local flexibility equations of a pipe with a part-through circumferential crack are derived by using linearly elastic fracture mechanics. Secondly, an adaptive Simpson quadrature-revisted was used to numerically calculate the local flexibility coefficients. Finally, the model test were performed to validate the local flexibility for a part-through circumferentially cracked pipe. The results show that the natural frequencies of cracked pipe obtained by the model test agree well with the theoretical values from the proposed equations of the local flexibility. It is demonstrated the feasibility of the proposed method for vibtaion analysis and damage identification of a cracked pipe.

The charge islands SOI LDMOS with Back-side Etching technology structure is proposed. The new structure features the equally spaced charge islands of the upper LDMOS and a back-side etched structure of the lower LDMOS. A series of equidistant high concentration N+ regions are formed at the upper SOI LDMOS by the ion implanting method. The breakdown voltage of the device is improved due to dielectric field enhancement and the interaction of charges. The results show that the breakdown voltage is increased from 210V to 615V (192.8% enhanced), compared to the conventional LDMOS. The on-resistance of the as-studied stacked SOI LDMOS reduces from 48.2 Ω⋅mm2 to 37.23 Ω⋅mm2 comparing with conventional charge islands device, leading to a reduction ratio of 22.7%.