Search

Zhen-Hua Li,1,&ast; Jie Wang,1,&ast; Xin Cheng,1,&ast; Yi-Cheng Mao,1 Kang-Di Zhang,1 Wen-Jie Yu,1 Ying-Qing Li,1 Kai Huang,1,2 Kun Ding,1 Xiao-Jing Yang,1 Cheng-Yang Hu,3 Xiu-Jun Zhang1,4 1Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, People’s Republic of China; 2Department of Hospital Infection Prevention and Control, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People’s Republic of China; 3Department of Humanistic Medicine, School of Humanistic Medicine, Anhui Medical University, Hefei, Anhui, People’s Republic of China; 4Center for Evidence-Based Practice, Anhui Medical University, Hefei, Anhui, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Cheng-Yang Hu; Xiu-Jun Zhang, Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, People’s Republic of China, Tel/Fax +86 551 65167031 ; +86 551 65169635, Email cy.hu@ahmu.edu.cn; zhangxiujun@ahmu.edu.cnBackground: There is growing evidence that the COVID-19 pandemic has had a dramatic impact on public mental health. However, less attention has been paid to left-behind experience college students (LBEs). This online study aimed to investigate the relationship between psychological capital (PsyCap) and anxiety among LBEs during COVID-19 pandemic, and further analyze the mediation role of self-esteem between them.Methods: A total of 9990 students were chosen using the stratified cluster sampling method. Three self-reported questionnaires were used to assess the PsyCap, self-esteem, and anxiety, respectively. All the statistical analyses were conducted using SPSS 23.0 and R, and to further investigate the mediation effect of self-esteem in the association of PsyCap with anxiety, AMOS 23.0 was used to build a structural equation model.Results: PsyCap, self-esteem, and anxiety were significantly correlated among LBEs during the COVID-19 pandemic. PsyCap affects anxiety directly (β = – 0.22, SE = 0.051, 95% CI: – 0.27, – 0.17, P < 0.05). In addition, self-esteem partially mediated the relationship between PsyCap and anxiety (mediating effect value = – 0.16, 95% CI: – 0.20, – 0.13, P < 0.05).Conclusion: During the pandemic of COVID-19, left-behind experience had a negative influence on the PsyCap and self-esteem of college students. In addition, for LBEs, self-esteem plays an important mediating role between PsyCap and anxiety. Therefore, from the perspective of PsyCap and self-esteem, schools should translate them into practical educational strategies to enhance the mental health and mitigate the anxiety levels of LBEs.Keywords: left-behind experience, COVID-19, psychology, mental health

Wuwei xiaoduyin (WWXDY) is a prescription for Chronic osteomyelitis (COM) in traditional Chinese medicine (TCM). However, its specific mechanism remains unclear. The objective of this study was to investigate the mechanism of WWXDY in COM treatment. To clarify the potential role of TAZ in the treatment of COM by WWXDY via regulatory CD4+ T cells differentiation. The expressions of TAZ, RORγt and Foxp3 were determined by Quantitative Real-time PCR and Western blot. Besides, levels of IL-21, IL-17 and IL-10 in peripheral blood were detected by using ELISA. Molecular dynamics simulations and docking were further utilized to explore the binding mechanism. COM resulted in abnormal cell differentiation and an imbalance of Treg/Th17. In comparison with the control group, the percentage of Treg cells, Foxp3 expression and secretion of IL-17 and −21 cytokines decreased (P < 0.001), while the proportion of Th17 cells, the levels of TAZ and RORγt and concentration of IL-10 in PBMCs increased in the COM group (P < 0.001). Furthermore, the above abnormal differentiation and function of Treg/Th17 cells in COM were suppressed after treatment with WWXDY in vivo and in vitro. In addition, TEAD1 inhibited the therapeutic effect of WWXDY in terms of Treg/Th17 cells with COM. it was found that the main active ingredients were cichoric acid and isocarlinoside. WWXDY regulates immunoregulatory properties of Treg/Th17 cells in COM mainly by mediating TAZ expression. By inhibiting the chronic inflammation in COM, WWXDY is potentially used to inhibit the progression of COM into bone tumors.

Lithium dendrite growth is an important issue in the design of lithium metal batteries (LMBs), and most relevant experimental studies lack theoretical guidance. We employ density functional theory to study the adsorption and diffusion of lithium atoms, which are two dominating factors for dendrite growth, by calculating the binding energy and potential map. Perfect, dislocation defective and heteroatom defective surfaces are considered. For a perfect surface, dendrite growth on the (110) face compared to the (200) face is dominated more by the adsorption mechanism. For dislocation defects, an extra potential barrier is found on the section of the dislocation, which might lead to uncontrolled dendrite growth. For heteroatom defects, the influence is correlated with the face direction due to the correlation between the chemical bond and cell parameters; it seems that Si, P and B are unfavourable, while F, Cl and alkali metal atoms are favourable for dendrite-free LMBs.

To explore the efficacy and safety of the Chinese medicine prescription Wuweixiaoduyin in inhibition of chronic osteomyelitis via regulatory T cells signaling. The effective components of Wuweixiaoduyin and osteomyelitis related genes were screened. Target proteins were cross-validated using the Venny database. GO and KEGG pathway analyses were performed for target proteins as well as pharmacological network was constructed. The bone properties were analyzed by HE staining and the concentration of immune factors were measured by ELISA. Real-time PCR and western blot were used to analyze mRNA and protein expression level. FACS assay was used to analyze the rate of cells. 117 genes overlapped between 785 target genes of active compounds of WWXDY and 912 Osteomyelitis related genes. Inflammation-related genes, including IL-6, TNFa, IL-1b and IL-2 showed high connection degree in drug-compounds-disease-targets network. GO function and KEGG pathway analyses revealed that 117 intersection genes mainly enriched in virus infection related pathways, immune related pathways and Chemokine signaling pathway. Besides, the development of chronic osteomyelitis was suppressed in rat models after treatment of Wuweixiaoduyin granule and meanwhile the concentration of IL-2 and CD4+CD25+Foxp3 Treg rates together with the levels of p-STAT5, CTLA-4 and Foxp3 were also downregulated. Further studies also showed that IL-2 and Wuweixiaoduyin drug-containing serum showed an opposite effect on regulating IL-2, IL-10, TGF-β1 Foxp3, CTLA4 and STAT5. In addition, STAT5 phosphorylation inhibitor could also suppress the expression of Foxp3 and CTLA-4. Wuweixiaoduyin could treat chronic osteomyelitis via suppressing the main regulating factors of Tregs and further interfere its immunodepression. Our results bring new solution for chronic osteomyelitis.

Container-based virtualization has gradually become a main solution in today's cloud computing environments. Detecting and analyzing anomaly in containers present a major challenge for cloud vendors and users. This paper proposes an online container anomaly detection system by monitoring and analyzing multidimensional resource metrics of the containers based on the optimized isolation forest algorithm. To improve the detection accuracy, it assigns each resource metric a weight and changes the random feature selection in the isolation forest algorithm to the weighted feature selection according to the resource bias of the container. In addition, it can identify abnormal resource metrics and automatically adjust the monitoring period to reduce the monitoring delay and system overhead. Moreover, it can locate the cause of the anomalies via analyzing and exploring the container log. The experimental results demonstrate the performance and efficiency of the system on detecting the typical anomalies in containers in both simulated and real cloud environments.

In animal husbandry, feed efficiency is a crucial economic trait. In this study, the general linear model was used to perform association analysis for various genotypes and feed conversion ratio (FCR)-related traits. Reverse transcription-quantitative PCR (RT-qPCR) was used to detect the expression of SHISA3 and RFC3 mRNA levels in 10 tissues from 6 sheep. The results showed that SNPs in the NC_040257.1:c.625 T > C and NC_040261.1:g.9905 T > C were analyzed whether they were associated to feed efficiency parameters in Hu sheep (body weight, feed intake, average daily growth, and feed conversion ratio). NC_040257.1:c.625 T > C was shown to be significantly associated with body weight at 80, 100, and 120 days as well as feed conversion ratio (P < 0.05), whereas NC_040261.1:g.9905 T > C was found to be significantly associated with average daily weight gain from 80-140 days (ADG80-140) and FCR (P < 0.05). In Hu sheep, the CC genotypes of SHISA3 and RFC3 were the most common genotypes related to feed efficiency traits. Furthermore, the feed conversion ratio of the combined genotypes TTSHISA3-CCRFC3, TTSHISA3-CTRFC3, TTSHISA3-TTRFC3, CTSHISA3-CCRFC3 and CTSHISA3-CTRFC3 was significantly better than the FCR of CCSHISA3-TTRFC3. RT-qPCR results showed that the expression levels of SHISA3 were lower in the lung than in spleen, kidney, muscle and lymph (P < 0.05), and RFC3 was the lung had a highly significant higher expression level than the heart, liver, spleen, and muscle (P < 0.01). In conclusion, SHISA3 and RFC3 polymorphisms can be used as genetic markers for improving feed conversion efficiency in Hu sheep.

The growing interest in language-conditioned robot manipulation aims to develop robots capable of understanding and executing complex tasks, with the objective of enabling robots to interpret language commands and manipulate objects accordingly. While language-conditioned approaches demonstrate impressive capabilities for addressing tasks in familiar environments, they encounter limitations in adapting to unfamiliar environment settings. In this study, we propose a general-purpose, language-conditioned approach that combines base skill priors and imitation learning under unstructured data to enhance the algorithm's generalization in adapting to unfamiliar environments. We assess our model's performance in both simulated and real-world environments using a zero-shot setting. In the simulated environment, the proposed approach surpasses previously reported scores for CALVIN benchmark, especially in the challenging Zero-Shot Multi-Environment setting. The average completed task length, indicating the average number of tasks the agent can continuously complete, improves more than 2.5 times compared to the state-of-the-art method HULC. In addition, we conduct a zero-shot evaluation of our policy in a real-world setting, following training exclusively in simulated environments without additional specific adaptations. In this evaluation, we set up ten tasks and achieved an average 30% improvement in our approach compared to the current state-of-the-art approach, demonstrating a high generalization capability in both simulated environments and the real world. For further details, including access to our code and videos, please refer to https://demoviewsite.wixsite.com/spil

Supplementary Material 1

Additional file 2: Fig S1. In vivo and in vitro experimental schemes in this study.

Supplementary Material 2

Additional file 3: Figure S3. (A) The three potential transcriptional factors of PDIA4 (ATF6, XBP1 and HIF1A) are all significantly upregulated in GBMs compared with normal human tissues. ***P < 0.001. (B) The expressions of all the three potential transcriptional factors (ATF6, XBP1 and HIF1A) are positive correlated with the PDIA4 expression in GBMs. (C) The GSEA analysis indicates the enrichment of hypoxia in hig-PDIA4 GBMs. (D) Public ChIP dataset revealed there is a significant binding site of HIF1α on PDIA4 promoter in T47D cells but not in PC-3 cells. (E) Western blot data unveiled that PDIA4 protein expressions are not upregulated when we cultured the U87 and LN229 cells with 0% O2.

Additional file 1: Figure S1. (A-C) Kaplan-Meier survival analysis of three public GBM datasets (including two cohorts from CGGA datasets, and one cohort from GEO repository) validated the robust prognostic role of PDIA4 in GBM patients. (D) Protein expressions of PDIA4 in human astrocyte and five GBM cell lines. (E) Validation of PDIA4 protein expression levels in lentivirus transfected U87 and LN229 cells.

Additional file 6. RNA-seq analysis of theimmunomodulation activities by LPPC/MP complex with different antibodies. (A) Volcano plot for gene expression and the FC values of genes. (B) Pie chart demonstrating the proportionof mouse RNA-seq reads assigned to annotated genomic functions.

Additional file 2: Figure S2. (A) Metascape enrichment analysis of DEGs between low- and high-PDIA4 GBM subgroups in the TCGA-GBM bulk RNA-seq dataset. (B) Mass spectrogram of FMDVYQR peptide sequence identified in PDIA4 protein substrates. (C) Intracellular VEGFA protein expressions are upregulated in PDIA4 overexpression U87 cells and downregulated in PDIA4-knockdown LN229 cells.

Additional file 3. Western Blot original gels.

Additional file 1: Supplementary Fig. 1. Notch3 expression was significantly positively correlated with macrophages infiltration. a. Representative correlation results analyzed using CIBERSORT-ABS. b. Survival curves of patients with colorectal carcinoma from the TCGA database stratified according to expression levels of Notch1,2,4. Supplementary Fig. 2. Notch3 expression was positively correlated with the degree of macrophage infiltration in colorectal carcinoma tissue. a. Immunohistochemical staining of HCT116 with or without Notch3 knockdown derived tumor tissues using Notch3 antibody. b. IHC score standard of Notch3 in colon cancer. c. Notch3 and CD68 staining of the colon cancer tissue continuous section from patient #2. Supplementary Fig. 3. Notch3 expression was positively correlated with the macrophage recruitment-related cytokines expression. a. The relation between Notch3 and macrophage recruitment-related genes analyzed using LinkedOmics database ( http://www.linkedomics.org/login.php ). b. The relationship between Notch3 and macrophage recruitment-related genes analyzed using GEPIA2 database ( http://gepia2.cancer-pku.cn/#index ). Supplementary Fig. 4. Interference Notch3 attenuated the colon tumor growth and decreased macrophage infiltration in vivo. a. Notch3 staining of NCT and Notch3-shRNA in mice tumor tissues. b. Gating strategy for flow cytometry. c. Flow cytometry analysis of blood from MC38 tumors carrying mice. d. The quantification of the results in b.

The white-lipped deer (Cervus albirostris) is a rare and endangered species found in the Qinghai-Tibet Plateau in China. To understand the space occupancy, activity rhythm, and sexual segregation of the white-lipped deer, 24,096 effective photos and 827 effective videos were captured using infrared cameras from February 2020 to January 2022. The ecology and behavior of the white-lipped deer in Jiacha Gorge were studied in more detail using site occupancy models, relative abundance index, and other technologies and methods. The results show that The occupancy predicted by the model exceeds or approaches 0.5. The occupancy increases with greater altitude and with larger EVI values, while the detection rate increases with altitude only during spring and decreases with EVI values only in summer. The daily activity peaks for white-lipped deer were observed from 7:00 to 11:00 and 17:00 to 22:00, with annual activity peaks occurring from April to June and from September to November. From July to the following January, white-lipped deer mostly move in mixed-sex groups, while during the remainder of the year, they predominantly associate with individuals of the same sex. Climate, vegetation coverage, food resources, and human disturbance collectively influenced the behavior and habitat utilization of white-lipped deer. The foundational research conducted on white-lipped deer over the past two years is expected to enhance the basic understanding of white-lipped deer in the Qinghai-Tibet Plateau and contribute to future protection and management decisions.

Additional file 3. The activities of LPPC/MP complexes. The splenocytes from different treatments were pulsed with BSA antigens, and the cytokines secretion were estimated at different times by ELISA, such as IFN-γ (A) and IL-4 (B). Each data indicated the mean ± SD from three independent experiments (N=6).

Halftoning aims to reproduce a continuous-tone image with pixels whose intensities are constrained to two discrete levels. This technique has been deployed on every printer, and the majority of them adopt fast methods (e.g., ordered dithering, error diffusion) that fail to render structural details, which determine halftone's quality. Other prior methods of pursuing visual pleasure by searching for the optimal halftone solution, on the contrary, suffer from their high computational cost. In this paper, we propose a fast and structure-aware halftoning method via a data-driven approach. Specifically, we formulate halftoning as a reinforcement learning problem, in which each binary pixel's value is regarded as an action chosen by a virtual agent with a shared fully convolutional neural network (CNN) policy. In the offline phase, an effective gradient estimator is utilized to train the agents in producing high-quality halftones in one action step. Then, halftones can be generated online by one fast CNN inference. Besides, we propose a novel anisotropy suppressing loss function, which brings the desirable blue-noise property. Finally, we find that optimizing SSIM could result in holes in flat areas, which can be avoided by weighting the metric with the contone's contrast map. Experiments show that our framework can effectively train a light-weight CNN, which is 15x faster than previous structure-aware methods, to generate blue-noise halftones with satisfactory visual quality. We also present a prototype of deep multitoning to demonstrate the extensibility of our method., Comment: Submitted to IEEE TIP

Generative model-based deep clustering frameworks excel in classifying complex data, but are limited in handling dynamic and complex features because they require prior knowledge of the number of clusters. In this paper, we propose a nonparametric deep clustering framework that employs an infinite mixture of Gaussians as a prior. Our framework utilizes a memoized online variational inference method that enables the "birth" and "merge" moves of clusters, allowing our framework to cluster data in a "dynamic-adaptive" manner, without requiring prior knowledge of the number of features. We name the framework as DIVA, a Dirichlet Process-based Incremental deep clustering framework via Variational Auto-Encoder. Our framework, which outperforms state-of-the-art baselines, exhibits superior performance in classifying complex data with dynamically changing features, particularly in the case of incremental features. We released our source code implementation at: https://github.com/Ghiara/diva, Comment: update supplementary materials

Additional file 1.

Additional file 5. Flow chart of theprocess for RNA-seq analysis. The flow chart described how RNA data wereprocessed, the criteria for every stage, and the number of genes. The number ofupregulation genes was shown in red, while that of downregulation genes wasshown in blue.

Additional file 1: Supplementary Figure 1. Scatter plot from genetically predicted sedentary TV watching on risk of VTE. Supplementary Figure 2. Scatter plot from genetically predicted sedentary computer use on risk of VTE. Supplementary Figure 3. Scatter plot from genetically predicted sedentary driving on risk of VTE. Supplementary Figure 4. Leave-one-out plot from genetically predicted sedentary TV watching on risk of VTE. Supplementary Figure 5. Leave-one-out plot from genetically predicted sedentary computer use on risk of VTE. Supplementary Figure 6. Leave-one-out plot from genetically predicted sedentary driving on risk of VTE. Supplementary Figure 7. Funnel plot from genetically predicted sedentary TV watching on risk of VTE. Supplementary Figure 8. Funnel plot from genetically predicted sedentary computer use on risk of VTE. Supplementary Figure 9. Funnel plot from genetically predicted sedentary driving on risk of VTE. Supplementary Figure 10. Forest plot from genetically predicted sedentary TV watching on risk of VTE. Supplementary Figure 11. Forest plot from genetically predicted sedentary computer use on risk of VTE. Supplementary Figure 12. Forest plot from genetically predicted sedentary driving on risk of VTE. Supplementary Figure 13. Forest plot of the meta-analysis for genetically predicted sedentary TV watching on risk of VTE in FinnGen and UK Biobank populations. Supplementary Table 1. Summary information on the excluded SNPs for LSB in the present MR study. Supplementary Table 2. Summary information on the SNPs used as genetic instruments for LSB in the present MR study. Supplementary Table 3. MR-PRESSO results. Supplementary Table 4. F-statistics of LSB and physical activity. Supplementary Table 5. MR estimates of the causal relationship between black hair color, physical activity and the risk of VTE. Supplementary Table 6. MRSamePopTest in the FinnGen and UK Biobank population.

Additional file 1. Construction of LPPC/MP andLPPC/MP/Ab complexes.The picture illustrated the formulation of LPPC complexes with different immunofunctionalproteins and their specific aims.

Additional file 2. The effects of LPPC/Abcomplexes on the cell cycle. The cell cycle profiles ofnaive (A) or activated (B) splenocytes under LPPC/Ab complexestreatments were performed by PI staining. A significant difference compared tothe LPPC/CD3 group was indicated by * (P

Simultaneous localization and mapping (SLAM) is critical to the implementation of autonomous driving. Most LiDAR-inertial SLAM algorithms assume a static environment, leading to unreliable localization in dynamic environments. Furthermore, accurate tracking of moving objects is of great significance for the control and planning of autonomous vehicle operation. This study proposes LIMOT, a tightly-coupled multi-object tracking and LiDAR-inertial SLAM system capable of accurately estimating the poses of both ego-vehicle and objects. First, we use 3D bounding boxes generated by an object detector to represent all movable objects and perform LiDAR odometry using inertial measurement unit (IMU) pre-integration result. Based on the historical trajectories of tracked objects in a sliding window, we perform robust object association. We propose a trajectory-based dynamic feature filtering method, which filters out features belonging to moving objects by leveraging tracking results. Factor graph-based optimization is then conducted to optimize the bias of the IMU and the poses of both the ego-vehicle and surrounding objects in a sliding window. Experiments conducted on KITTI datasets show that our method achieves better pose and tracking accuracy than our previous work DL-SLOT and other SLAM and multi-object tracking baseline methods., Comment: 8 pages, 4 figures. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

Deep reinforcement learning (RL) has been endowed with high expectations in tackling challenging manipulation tasks in an autonomous and self-directed fashion. Despite the significant strides made in the development of reinforcement learning, the practical deployment of this paradigm is hindered by at least two barriers, namely, the engineering of a reward function and ensuring the safety guaranty of learning-based controllers. In this paper, we address these challenging limitations by proposing a framework that merges a reinforcement learning \lstinline[columns=fixed]{planner} that is trained using sparse rewards with a model predictive controller (MPC) \lstinline[columns=fixed]{actor}, thereby offering a safe policy. On the one hand, the RL \lstinline[columns=fixed]{planner} learns from sparse rewards by selecting intermediate goals that are easy to achieve in the short term and promising to lead to target goals in the long term. On the other hand, the MPC \lstinline[columns=fixed]{actor} takes the suggested intermediate goals from the RL \lstinline[columns=fixed]{planner} as the input and predicts how the robot's action will enable it to reach that goal while avoiding any obstacles over a short period of time. We evaluated our method on four challenging manipulation tasks with dynamic obstacles and the results demonstrate that, by leveraging the complementary strengths of these two components, the agent can solve manipulation tasks in complex, dynamic environments safely with a $100\%$ success rate. Videos are available at \url{https://videoviewsite.wixsite.com/mpc-hgg}.

Additional file 7. RNA-seq analysis of the immunomodulation activitiesby LPPC/MP complex with different antibodies. The RNA expression levels of immunecells under different treatments were determined by t-tests and ANOVA,and the results were shownas boxplots. The description of group names was the same as in Fig. 9.

Sea surface temperature (SST) is uniquely important to the Earth's atmosphere since its dynamics are a major force in shaping local and global climate and profoundly affect our ecosystems. Accurate forecasting of SST brings significant economic and social implications, for example, better preparation for extreme weather such as severe droughts or tropical cyclones months ahead. However, such a task faces unique challenges due to the intrinsic complexity and uncertainty of ocean systems. Recently, deep learning techniques, such as graphical neural networks (GNN), have been applied to address this task. Even though these methods have some success, they frequently have serious drawbacks when it comes to investigating dynamic spatiotemporal dependencies between signals. To solve this problem, this paper proposes a novel static and dynamic learnable personalized graph convolution network (SD-LPGC). Specifically, two graph learning layers are first constructed to respectively model the stable long-term and short-term evolutionary patterns hidden in the multivariate SST signals. Then, a learnable personalized convolution layer is designed to fuse this information. Our experiments on real SST datasets demonstrate the state-of-the-art performances of the proposed approach on the forecasting task.

Additional file 4. The lung photos of mice under different treatments. (A)The representative photos of the lungs from differenttreatments of Fig. 7B were selected. (B) The representative photos ofthe lungs from different treatment groups of Fig. 8B were selected.

A series of experiments is performed to determine the damage behaviour and energy evolution of red-bed sandstones subjected to drying–wetting (D–W) cycles. The experimental results reveal that accompanied by the strain increases, the input energy density gradually increases, the elastic energy density increases slowly first, then increases linearly, and reaches the maximum value at the peak strength, then gradually decreases. The dissipated energy density continuously increases and then maintains a steady-state level before it finally increases rapidly. Furthermore, with the increase in the number of D–W cycles, all three energy densities of specimens present a linear downward trend. According to the damage variable defined by the energy principle, the damage evolution models of the uniaxial compression strength (UCS) and peak strain of the D–W specimen are established, which can well characterise the evolution of the UCS and peak strain of rocks after different numbers of D–W cycles.

In tribological applications, the degradation of alloy nitride coatings is an issue of increasing concern. The drawbacks of monolayer hard coatings can be overcome using a multilayer coating system. In this study, single-layer TiAlNbN and multilayer TiAlNbN/AlCrN coatings with AlCrN layer addition into TiAlNbN were prepared by cathodic arc evaporation (CAE). The multilayer TiAlNbN/AlCrN showed B1 NaCl structure, and the columnar structure continued from the bottom interlayer of CrN to the top multilayers without interruption. After AlCrN addition, the TiAlNbN/AlCrN coating consisted of TiAlNbN and AlCrN multilayers with a periodic thickness of 13.2 nm. The layer thicknesses of the TiAlNbN and AlCrN were 7 nm and 6.2 nm, respectively. The template growth of the TiAlNbN and AlCrN sublayers stabilized the cubic phases. The introduction of bottom CrN and the TiAlNbN/CrN transition layers possessed com-position-gradient that improved the adhesion strength of the coatings. The hardness of the deposited TiAlNbN was 30.2 ± 1.3 GPa. The TiAlNbN/AlCrN had higher hardness of 31.7 ± 3.5 GPa and improved tribological performance (wear rate = 8.2 ± 0.6 × 10−7 mm3/Nm) than those of TiAlNbN, which were because the multilayer architecture with AlCrN addition effectively resisted abrasion wear.

The water network plays an important role in maintaining the stability of regional water resource and ecological environment. It is also affecting the harmonious development between environment and economy. Guangxi is one of the provinces with relatively rich water resources in China, while the ecological water network exists deficiencies and faces challenges. The current situation and defects of ecological water network in Guangxi province will be discussed. By studying the experience of the establishing and the preserve of ecological water network in various regions at home and abroad, some suggestions and targeted measures will be mentioned for a better ecological water network in Guangxi.

Background Carpal tunnel syndrome (CTS), 1 of the most common peripheral neuropathies of the upper extremity, has been studied for decades regarding its epidemiology and associated medical conditions. We conducted a large-scale, age- and gender-matched study from an Asian population database to investigate the relationship between the incidence and the demographic characteristics. Methods A retrospective cohort study using data of National Health Insurance Research Database was conducted. One million enrollees in Taiwan was used to identify 9442 patients with CTS and 37,768 randomly selected controls, in a control-case ratio of 4:1. Diagnoses of CTS were ascertained from January 1, 2003, to December 31, 2012. Sociodemographic and medical characteristics were evaluated to assess the correlation with CTS. Results Annual incidence of CTS was approximately 0.4% during the 10-year-period in Taiwan, with higher incidence rate in female sex and middle age of group (50-59 years). Among the medical conditions, previous wrist injuries, obesity, gout, and rheumatoid arthritis were associated with CTS most significantly. Conclusions Carpal tunnel syndrome has presented a relatively constant incidence in Taiwan. Female gender with middle age seemed to have the highest incident rate during a 10-year period from 2003 to 2012. Among the risk factors of CTS, previous wrist injuries, obesity, gout, and rheumatoid arthritis were demonstrated to be the most significantly correlated comorbidities.

To systematically study the soil and water conservation functions of different straw mulching application rates on sloping farmland in karst area of Southwest China, the observation of runoff plots...

Assembly torque monitoring is an important aspect of assembly process monitoring. Currently, in manual assembly lines, torque monitoring sensors are usually installed on assembly tools or assembly jigs. This approach is restricted by the working environment and assembly space. To this end, operators can use wearable devices containing sensors without being restricted by the tool and working spaces, with the added advantage of portability. To use wearable electromyography equipment to monitor the assembly torque, this paper proposes an assembly torque monitoring method using surface electromyography (sEMG) and inertial signals. Two torque regression models, one based on a heterogeneous-kernel-based temporal convolutional network (Het-TCN) and the other based on a two-stream convolutional neural network (CNN), are proposed and compared with CNN, long short-term memory (LSTM), and temporal convolutional network (TCN) models. The experimental results show that, compared with using sEMG signals alone, performing an assembly torque data regression using a combination of sEMG and inertial signals can significantly reduce the regression error. The proposed Het-TCN model has the best regression performance, with an average error of 3.31 N m an RMSE of 9.18 %, and a coefficient of determination R2 of 0.72. Thus, the proposed Het-TCN along with the application of both sEMG and inertial signals can help effectively perform assembly torque data regression, which can be used for assembly torque or operation monitoring.

An improved image segmentation model was established to achieve accurate detection of target contours under high noise, low resolution, and uneven illumination environments. The new model is based on the variational level set algorithm, which improves the C–V (Chan and Vese) model and GAC (Geodesic Active Contour) model, fuses the contour and area models to segment the image information, that is, the edge information and region information of the image are fused into the same "energy" functional. According to the geometric characteristics of the curve, GAC model can effectively avoid re parameterization and light insensitivity in the evolution process, and CV model can effectively distinguish the fuzzy boundary of the image by maximizing the gray difference between the target and the background, it has strong anti-noise performance. By solving the steady-state solution of the partial differential equation, the optimal solution of the energy model is solved. New method can improve the calculation accuracy, topological structure adaptability, anti-noise ability, and reduce the light sensitivity effectively. Experiment shows that the new model has good robustness, high real-time performance, and it can effectively improve detection accuracy.

BackgroundDepression is common among patients with head and neck cancer, thereby affecting their survival rate. However, whether close monitoring of depression affects the survival outcomes of these patients is unknown. Therefore, this study aimed to determine whether depression treatment continuity after the diagnosis of cancer affects the survival of these patients.MethodsA total of 55,069 patients diagnosed with head and neck cancer in the Cancer Registration System database in Taiwan were enrolled. This cohort was followed from January 1, 2007 to December 31, 2017. Furthermore, the patients were divided into four groups, namely, “no depression,” “pre-cancer only,” “post-cancer only,” and “both before and after cancer,” on the basis of the diagnosis of depression and the duration of the follow-up period in the psychiatric clinic. Further, the Cox proportional hazard model was applied to estimate the hazard of death for the four groups.ResultsA total of 6,345 (11.52%) patients were diagnosed with depression in this cohort. The “pre-cancer only” group had a lower overall survival (HR = 1.18; 95% CI = 1.11–1.25) compared with the “no depression” group. Moreover, the “post-cancer only” group had better overall survival (HR = 0.88; 95% CI = 0.83–0.94) compared with the “no depression” group, especially in advanced-stage patients. Patients who were diagnosed with depression before cancer and had continuous depression treatments after the cancer diagnosis had better overall survival (HR = 0.78; 95% CI = 0.71–0.86) compared with patients who had treatment interruptions.ConclusionPatients with pre-cancer depression had poorer survival outcomes, especially those who did not receive psychiatric clinic visits after their cancer diagnosis. Nonetheless, in patients with advanced-stage cancer, depression treatment may improve overall survival.

Peripheral nerve injuries are commonly occurring traumas of the extremities; functional recovery is hindered by slow nerve regeneration (