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Background. Both low skeletal muscle mass and delirium are prevalent in older hospitalized patients, while their associations are unclear. This systematic review and meta-analysis aim to investigate the associations between low skeletal muscle mass and the incidence of delirium in hospitalized patients. Methods. The PubMed, Web of Science, and Embase were searched for relevant studies published before May 2022, and we conducted this systematic review and meta-analysis according to the PRISMA and MOOSE guidelines. The summary odds ratios (OR) and 95% confidence intervals (CI) were estimated, and subgroup analyses were also conducted according to the age and major surgeries. Results. Finally, nine studies with 3 828 patients were included. The pooled result showed no significant association between low skeletal muscle mass and the incidence of delirium (OR 1.69, 95% CI 0.85 to 2.52). However, sensitivity analysis suggested that one study caused a significant alteration of the summary result, and the meta-analysis of the remaining 8 studies showed that low skeletal muscle mass was significantly associated with an 88% increased incidence of delirium (OR 1.88, 95% CI 1.43 to 2.33). Furthermore, subgroup analyses indicated that low skeletal muscle mass was associated with a higher incidence of delirium in patients ≥75 years old or undergoing major surgeries instead of those

For space robots, it is difficult to track continuous time-varying manifolds on SE(3) by using traditional closed-loop control strategies, which are designed to track the position and the attitude separately. Therefore, the dynamics model should be rebuilt, and the corresponding control strategy should be redesigned. Firstly, the dynamics equations for a space robot in the joint space and workspace are established separately in the framework of Lie group SE(3) and screw theory based on the Lagrange principle. Secondly, based on the proposed feedback form, a PD (proportional derivative) control law of output force on the end-effector is designed, and a closed-loop continuous tracking control strategy is proposed using the force Jacobian matrix and the kinematic model. The simulation results show that the control scheme has good performance when the system state changes gently. Furthermore, a robust sliding mode tracking control scheme is designed. The simulation results show that the proposed robust control law has better accuracy than the PD control law because the system state changes wildly. Finally, a robust fuzzy sliding mode tracking control scheme is designed to deal with the chattering phenomenon. The simulation results show that the proposed robust fuzzy control law can eliminate the chattering well and decrease the joint control torque significantly. The robustness of the proposed robust fuzzy control law is also verified by numerical simulation.

The exploitation of intersatellite links (ISLs) makes the LEO satellite constellation based Internet service widely favored due to its advantages of low-latency and high-speed communications. However, considering the time-varying network topology, limited on-board resources, and high node failure probability, the design of link assignment has become one of the key challenges for the future megaconstellation. To solve this problem, we adopt the idea of modified finite state automaton (FSA) to model the LEO satellite network and use nondominated sorting genetic algorithm (NSGA-II) to optimize the minimum residual capacity and the maximum transmission delay. The simulation results show that our method is more invulnerable and flexible, which is fit for megaconstellations. This work can provide comprehensive guidance on intersatellite link assignment for future megaconstellations.

Beta-amyloid (Aβ) accumulation in the brains of Alzheimer’s disease (AD) patients leads to mitochondrial dysfunction and ferroptosis in neurons. Voltage-dependent anion channel 1 (VDAC1) is a major protein in the mitochondrial outer membrane. It has been reported that VDAC1 associated with mitochondrial dysfunction and ferroptosis. However, the mechanism by which VDAC1 regulates mitochondrial dysfunction and ferroptosis of neurons in AD remains unclear. This study is aimed at investigating the mechanism of action of VDAC1 in mitochondrial dysfunction and ferroptosis in neurons of the AD model. In this study, we determined cell viability after treatment with Aβ1-42 via the MTT assay. The SOD, MDA, ROS, and MMP production was measured via the SOD kit, MDA kit, DCFDA staining, and JC-1 staining. The memory abilities of mice were detected via the Morris water maze test. The expression of AMPK/mTOR, Wnt/β-catenin, and GPX4 regulated by VDAC1 was detected via western blotting. Our present study showed that PC12 cells had decreased cell viability, increased LDH release, and decreased GPX4 expression after Aβ1-42 treatment. Meanwhile, Aβ1-42 induced MMP and SOD downregulation and increased MDA and ROS generation in PC12 cells. In addition, the expression of VDAC1 is increased in the brain tissue of AD mice and Aβ1-42-treated PC12 cells. Further investigation of the role of VDAC1 in regulating AD found that all effects induced by Aβ1-42 were reversed by inhibition of VDAC1. Additionally, inhibition of VDAC1 activates the AMPK/mTOR and Wnt/β-catenin pathways. Taken together, these findings demonstrate that inhibition of VDAC1 alleviates mitochondrial dysfunction and ferroptosis in AD neurons by activating AMPK/mTOR and Wnt/β-catenin.

Cardiovascular diseases (CVDs) are a set of heart and blood vessel disorders that include coronary heart disease (CHD), rheumatic heart disease, and other conditions. Traditional Chinese Medicine (TCM) has definite effects on CVDs due to its multitarget and multicomponent properties, which are gradually gaining national attention. Tanshinones, the major active chemical compounds extracted from Salvia miltiorrhiza, exhibit beneficial improvement on multiple diseases, especially CVDs. At the level of biological activities, they play significant roles, including anti-inflammation, anti-oxidation, anti-apoptosis and anti-necroptosis, anti-hypertrophy, vasodilation, angiogenesis, combat against proliferation and migration of smooth muscle cells (SMCs), as well as anti-myocardial fibrosis and ventricular remodeling, which are all effective strategies in preventing and treating CVDs. Additionally, at the cellular level, Tanshinones produce marked effects on cardiomyocytes, macrophages, endothelia, SMCs, and fibroblasts in myocardia. In this review, we have summarized a brief overview of the chemical structures and pharmacological effects of Tanshinones as a CVD treatment to expound on different pharmacological properties in various cell types in myocardia.

Background. Myocardial fibrosis (MF) is an essential pathological factor for heart failure. Previous studies have shown that the combination of Carthamus tinctorius L. and Lepidium apetalum Willd. (C-L), two types of Chinese herbal medicine, can ameliorate MF after myocardial infarction (MI) in rats and inhibit the activation of myocardial fibroblasts. However, the mechanism of C-L in the treatment of MF remains unclear. Methods. A rat model of MF with left anterior descending coronary ligation-induced MI was first established. Then, the effects of C-L on cardiac function, MF, and endothelial-to-mesenchymal transition (EndMT) were evaluated by the left ventricular ejection fraction (LVEF), serum N-terminal pro-brain natriuretic peptide (NT-proBNP) levels, Masson’s trichrome staining, and immunohistochemical and immunofluorescence staining. Next, a hypoxia-induced cardiac microvascular endothelial cell (CMEC) model was established to observe the effects of C-L on EndMT. The supernatant of CMECs was collected and used to culture cardiac fibroblasts (CFs) and observe the effects of CMEC paracrine factors on CFs. Results. Animal experiments indicated that C-L improves the cardiac function of rats after MI, inhibits the progression of EndMT and MF, and downregulates TGFβ1, Snail, and CTGF expression. Cell experiments showed that drug-loaded serum containing C-L inhibits the EndMT of CMECs under hypoxic conditions. The culture supernatant of CMECs grown under hypoxic conditions significantly activated CFs. After treatment with C-L, the activating factor for CFs in hypoxic CMEC culture supernatant was substantially downregulated, and the effect of the culture supernatant on CF activation was also reduced. However, TGFβ1 agonists inhibited the effects of C-L on CMECs and CFs. Conclusion. Our data demonstrated that by regulating the TGFβ1/Snail pathway, C-L inhibits EndMT of CMECs and reduces the release of CF-activating factors in cells undergoing EndMT.

With the advent of the digital society, the amount of information we face will increase exponentially, which will challenge our level of educational knowledge, so we begin to pay attention to the effect of education and teaching in the context of digitalization. The purpose of this paper is to study the evaluation of students’ classroom learning effect based on the neural network algorithm and scientific objectivity. Assessment and other principles are to create an assessment system for students’ learning outcomes in the classroom. The system includes three first-level indicators, including first-level indicators and their weights. By selecting a university to test the system, the results show that the system can quantitatively evaluate the learning outcomes, and the corresponding scores and grades can be obtained through the formula. After adjusting the parameters of the hidden layer nodes, the BP elastic gradient algorithm is used to complete the evaluation model generation. The training error results show that the target curve and the output curve almost coincide, and the error curve is also between −0.2 and 0.5. Therefore, the learning outcome score obtained by the BP neural network based on the principal component factor data is basically consistent with the given learning outcome score.

Background. Colorectal cancer is one of the most common gastrointestinal malignancies globally. Necroptosis has been proved to play a role in the occurrence and development of the tumor, which makes it a new target for molecular therapy. However, the role of necroptosis in colorectal cancer remains unknown yet. Our study aims to build a prognostic signature of necroptosis-related lncRNAs (nrlncRNAs) to predict the outcomes of patients with colorectal cancer and facilitate in anticancer therapy. Method. We obtained RNA-seq and clinical data of colorectal adenocarcinoma from the TCGA database and got prognosis-related nrlncRNAs by univariate regression analysis. Then, we carried out the LASSO regression and multivariate regression analysis to build the prognostic signature, whose predictive ability was tested by the Kaplan-Meier as well as ROC curves and verified by the internal cohort. Moreover, we divided the cohort into 2 groups based on median of risk scores: high- and low-risk groups. By analyzing the difference in the tumor microenvironment, microsatellite instability, and tumor mutation burden between the two groups, we explored the potential chemotherapy and immunotherapy drugs. Results. We screened out 9 nrlncRNAs and built a prognostic signature based on them. With its good prognostic ability, the risk scores can act as an independent prognostic factor for patients with colorectal cancer. The overall survival rate of patients in high-risk group was significantly higher than the low-risk one. Furthermore, risk scores can also give us hints about the tumor microenvironment and facilitate in predicting the response to the CTLA-4 blocker treatment and other chemotherapeutic agents with potential efficacy such as cisplatin and staurosporine. Conclusions. In conclusion, our prognostic signature of necroptosis-related lncRNAs can facilitate in predicting the prognosis and response to the anticancer therapy of colorectal cancer patients.

Purpose. Traditional Chinese medicine (TCM) sometimes plays a crucial role in advanced cancer treatment. Despite the significant therapeutic efficacy in hepatocellular carcinoma (HCC) that Actinidia chinensis Planch root extract (acRoots) has proven, its complex composition and underlying mechanism have not been fully elucidated. Therefore, this study analyzed the multiple chemical compounds in acRoots and their targets via network pharmacology and bioinformatics analysis, with the overarching goal of revealing the potential mechanisms of the anti-HCC effect. Methods. The main ingredients contained in acRoots were initially screened from the traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the candidate bioactive ingredient targets were identified using DrugBank and the UniProt public databases. Second, the biological processes of the targets of active molecules filtered from the ingredients of acRoots were evaluated using gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Third, weighted gene coexpression network analysis (WGCNA) was performed to identify gene coexpression modules associated with HCC. The hub genes of acRoots in HCC were defined via contrasting the above module eigengenes with candidate target genes of acRoots. Furthermore, the target-pathway network was analyzed to explore the mechanism for anti-HCC effect of hub genes. Kaplan–Meier plotter database analysis was performed to validate the hub genes of acRoots correlation with prognostic values in HCC. In order to verify the results of the network pharmacological analysis, we performed a molecular docking approach on the active ingredients and key targets using the Discovery Studio software. The viability of SMMC-7721 and HL-7702 cells was determined by Cell counting kit-8 (CCK-8) after being treated with different concentrations of (+)-catechin (0, 50, 100, 150, 200, and 250 g/ml) for 24, 48, and 72 hours, respectively. Finally, qRT-PCR and Western blot involving human hepatocarcinoma cells were utilized to verify the impact of (+)-catechin on the hub genes associated with prognosis. Results. 6 out of 26 active ingredients extracted from TCMSP were deemed as the core ingredients of acRoots. 175 bioactive-ingredient targets of acRoots were obtained and a bioactive-ingredient targets network was established correspondingly. The biological processes (BP) of target genes mainly involved processes, such as toxic substance and wounding. The results of KEGG pathways indicated that the target genes were mainly enriched in pathways in cancer, AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, and other pathways. Also, the two hub genes (i.e., ESR1 and CAT) were closely associated with the prognosis of HCC patients. As a consequence, we predicated a series of signaling pathways, including estrogen signaling pathway and longevity regulation pathway, through which acRoots could facilitate the treatment for HCC. The molecular docking experiment ascertained that ESR1 and CAT had an effective binding force with (+)-catechin, one of the core ingredients of acRoots. Furthermore, (+)-catechin inhibited SMMC-7721 cell growth in a dose-dependent manner and a time-dependent manner. Finally, we suggest that the expression level of ESR1 and CAT is positively related to the (+)-catechin concentrations in in-vitro experiments. Conclusion. The bioactive ingredients of acRoots, including quercetin, (+)-catechin, beta-sitosterol, and aloe-emodin, have synergistic interactions in reinforcing the anticancer effect in HCC. Evidently, acRoots took effect by regulating multitargets and multipathways through its active ingredients. Further, (+)-catechin, the possible paramount anti-HCC active ingredient in acRoots, helped improve the prognosis of HCC patients by increasing the expression of ESR1 and CAT. Additionally, the findings yielded provide a conceptual guidance for the clinical treatment of HCC and the methods adopted are potentially applicable in the future comprehensive analysis of the underlying mechanisms of TCMs.

Saliency detection is a technique for automatically extracting regions of interest from the background and has been widely used in the computer vision field. This study proposes a simple and effective saliency detection method combining color contrast and hash fingerprint. In our solution, the input image is segmented into nonoverlapping superpixels, so as to perform the saliency detection at the region level to reduce computational complexity. A background optimization selection is used to construct an accurate background template. Based on this, a saliency map that highlights the whole salient region is obtained by estimating color contrast. Besides, another saliency map that enhances the salient region while restraining the background is also generated through hash fingerprint matching. Ultimately, the final saliency map can be obtained by fusing the two saliency maps. Comparing the performance with other methods, the proposed algorithm works better even in the presence of complex background or very large salient regions.

Protein elicitors play a key role in signaling or displaying plant defense mechanism and emerging as vital tools for biocontrol of insects. This study was aimed at the characterization of the novel protein elicitor isolated from entomopathogenic fungi Lecanicillium lecanii (V3) strain and its activity against whitefly, Bemisia tabaci, in cotton (Gossypium hirsutum L.). The sequence of purified elicitor protein showed 100% similarity with hypothetical protein LEL_00878 (Cordyceps confragosa RCEF 1005) (GenBank accession no. OAA81333.1). This novel protein elicitor has 253 amino acid residues and 762 bp with a molecular mass of 29 kDa. Their combatant protein was expressed in Escherichia coli using pET-28a (+) plasmid. Bioassay was revealed to quantify the impact of numerous concentrations of protein (i.e., 58.32, 41.22, and 35.41 μg/ml) on the fecundity rate of B tabaci on cotton plants. Bioassay results exhibited a significant effect ( P ≤ 0.001 ) of all the concentrations of protein on the fecundity rate of B. tabaci. In addition, the gene expression analysis found a significant upregulation of the major genes associated with salicylic acid (SA) and jasmonic acid (JA) defense pathways in elicitor protein-treated plants. Our results showed that the potential application of novel protein elicitor derived from Lecanicillium lecanii will be used as future biointensive controlling approaches against whitefly, Bemisia tabaci.

Pusa village is located in the karst mountain area of Nayong County, Guizhou Province, China. Laoyingyan mountain rock is gently dipping, the upper part consists of hard rock formations, and the lower part is made up of soft rock composed of 3 coal seams. On August 28, 2017, a massive landslide occurred in this area, resulting in 82,3000 m3 of debris, which resulted in significant casualties and brought up the malaise in society. In this paper, the geological conditions and long-term mining activities in the study area are analyzed by field investigation. The base friction tests and numerical models are used to simulate and analyze the failure and deformation process of Pusa collapse to accommodate the research on the deformation and failure mechanism of the slope and provide better prevention and treatment suggestions. The results show that the Pusa collapse can mainly be attributed to unique geological conditions, underground mining activities, and the topography of the slope. The intensified mining activities promoted the development of fractures and cracks in the slope, resulting in unstable upper slopes. The failure process of the Pusa collapse can be summarized into four-stage: the development of goaves roof deformation, the crest of the slope cracks, intensification of deformation, and occurrence of collapse. The upper slope with high strength rock developed crack-toppling failure. Meanwhile, the upper slope with low strength rock developed subside-crack-sliding failure, and those two failures together contributed to the mechanism of Pusa collapse. Slope deformation and failure mechanism can be summarized as subside-crack-toppling-shear sliding type.

Background. Modified Sanmiaosan is an effective cure in the treatment of ulcerative colitis, but its mechanisms of action remain unclear. This study revealed the pharmacological mechanisms of Modified Sanmiaosan acting on ulcerative colitis through a pharmacology approach. Materials and Methods. The active compounds and the targets of Modified Sanmiaosan were selected from the Traditional Chinese Medicine Systems Pharmacology database according to the absorption and metabolism. The UC-related therapeutic targets were collected from the PharmGKB database, the GeneCards database, the GADA database, and the OMIM database. The networks of “drug-component-target-disease” and “herbal-component-target” were constructed by the Cytoscape software. Protein–protein interaction network was generated by the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by the R software. Molecular docking technology was used to identify the affinity and activity between active compounds and targets. Results. The 80 effective ingredients of MSM were collected. A total of 5180 UC-related genes and the 153 key targets of MSM and UC-related were obtained. JUN, Akt1, and MAPK1 were identified as the “hub targets” involved in the effects of Modified Sanmiaosan on ulcerative colitis. Hub targets were mainly involved in inflammatory response and oxidative stress. As the results of GO analysis, biological processes such as DNA-binding transcription and RNA polymerization may participate in the treatment process; KEGG pathway analysis showed that hub targets were mainly involved in IL-17 signal pathway and TNF signal pathway of ulcerative colitis. The high affinity and activity of the active compounds and targets were verified through molecular docking. Conclusion. These findings demonstrate the active ingredients in Modified Sanmiaosan reduce inflammatory response by TNF and IL-17 signaling pathways to treat ulcerative colitis. Anti-inflammation and immune regulation may be the main mechanism of Modified Sanmiaosan in the treatment of ulcerative colitis. This study not only provide new insights into the development of a natural therapy for the prevention and treatment of ulcerative colitis but also proves a feasible method for discovering potential activated compounds from Chinese herbs.

The Target. The purpose of this study is to explore the reduction of sports injury risk and verify the effective methods and means of athlete’s muscle injury rehabilitation. Methods. In this study, 80 sanda athletes from a university were randomly selected as subjects, and the main parts of injury of all subjects were counted. After 12 weeks of muscle injury rehabilitation intervention, the pain, acute injury, and technical and tactical evaluation levels of subjects in the intervention group and the control group were compared. Results/Discussion. The overall performance of the 80 subjects’ basic exercise ability was at a moderate level, and there was no significant difference between male and female subjects (P >0.05). After 12 weeks of rehabilitation intervention, there was no significant difference in the scores of shoulder joint flexibility, supine straight leg raising, and trunk stable support between male and female subjects in the intervention group in more than 7 sports (P >0.05). In the control group, there were significant differences in the scores of shoulder flexibility and trunk stability of male and female subjects ( P < 0.05 ). Future research should further explore the effect of muscle injury rehabilitation on effectively reducing potential sports injuries and introduce advanced and effective medical rehabilitation methods.

As the most important strategic resource of enterprises, big data has become the basic background of business model innovation. From the perspective of psychological contract, this paper discusses the mechanism of psychological contract in customer value proposition driven business model innovation and puts forward four research hypotheses. This paper adopts the confirmatory factor analysis method of structural equation to verify these four hypotheses. It is concluded that there is a significant positive relationship between customer value proposition and psychological contract; there is a significant positive correlation between psychological contract and business model innovation; and psychological contract has intermediary effect between value proposition and business model innovation. Furthermore, value proposition has a significant positive correlation with business model innovation, which has not been verified.

This paper proposes an indoor localization algorithm based on AOA (Arrive of Angle) and orientation angle (OA) for passive UHF RFID (Ultra-High Frequency Radio Frequency Identification) tag array. By utilizing a uniform linear tag array (ULA), the AOA, which is defined as the angle of the reader relative to the tag array, can be estimated by the Multiple Signal Classification (MUSIC) algorithm. The relationship between AOA, OA of the tag array, and the direction angle (DA) between each reader antenna to the geometric center of the tag array is analyzed, and an OA retrieval method based on rotating the coordinate system is proposed to calculate DA. The tag array localization is finally acquired by the DA of each antenna. Simulation and experiment results show that the proposed algorithm can achieve decimeter-level localization accuracy. The proposed algorithm achieves a mean accuracy of 0.216 m, which is a significant improvement compared with the traditional AOA localization algorithm.

Erasure coding has been widely deployed in today’s data centers for it can significantly reduce extra storage costs while providing high storage reliability. However, erasure coding introduced more network traffic and computational overhead in the data update process. How to improve the efficiency and mitigate the system imbalance during the update process in erasure coding is still a challenging problem. Recently, most of the existing update schemes of erasure codes only focused on the single stripe update scenario and ignored the heterogeneity of the node and network status which cannot sufficiently deal with the problems of low update efficiency and load imbalance caused by the multistripe concurrent update. To solve this problem, this paper proposes a Load-Aware Multistripe concurrent Update (LAMU) scheme in erasure-coded storage systems. Notably, LAMU introduces the Software-Defined Network (SDN) mechanism to measure the node loads and network status in real time. It selects nonduplicated nodes with better performance such as CPU utilization, remaining memory, and I/O load as the computing nodes for multiple update stripes. Then, a multiattribute decision-making method is used to schedule the network traffic generated in the update process. This mechanism can improve the transmission efficiency of update traffic and make LAMU adapt to the multistripe concurrent update scenarios in heterogeneous network environments. Finally, we designed a prototype system of multistripe concurrent updates. The extensive experimental results show that LAMU could improve the update efficiency and provide better system load-balancing performance.

Recent years have witnessed the rapid development of microelectromechanical systems, and human motion tracking technology based on IMU (inertial measurement unit) has attracted much attention. However, the magnetic field varies with time and position, which makes it necessary to calibrate sensors before tracking. To address the poor adaptability of IMU to the environments and improve the accuracy of estimated traces, this paper presents an ENN-based (Elman neural network) method to track human arm motions, which consists of two steps. First, the data derived from IMUs are preprocessed for the rough Euler angles; then, an ENN is trained to estimate motions. We explore the initially estimated position to calibrate the acceleration measurements as the input of the ENN. Real-world experiments of arm motion tracking are carried out with the ground truth from an optical motion tracking system. The experimental results show that the mean tracking errors are around 35 mm, with a strong ability to eliminate the effect of extreme measurement and environment noises, avoiding calibrating the magnetometer. The implementation of the well-trained model to independent motions indicates that the robustness of the proposed method is excellent, and the errors reduce by 37.2% on the x -axis and perform similarly on the z -axis compared with 4 traditional methods. This method quite suits those situations where trajectory tracking of the standardized motions is required, such as the medical habilitation.

Objective. To analyze the role of PD-1/PD-L1 signaling pathway in regulating T cell activation and secretion of proinflammatory factors in atrial fibrillation. Methods. Forty-five patients with atrial fibrillation admitted to the cardiology department of our hospital from July 2019 to March 2021 were selected to be included in the atrial fibrillation group, and another 45 healthy volunteers were selected as the control group to compare the changes of T cell CD69 and human leukocyte antigen-DR (HLA-DR) expression in the peripheral blood of the two study groups; compare the changes of programmed death factor-1 on CD4+ and CD8+ lymphocytes in the peripheral blood of the two groups (PD-1) expression changes and PD-L1 and PD-L2 expression changes on peripheral blood myeloid dendritic cells (mDCs) cells; compare the changes of interleukin-2, interleukin-6, interleukin-10, and interleukin-17A (IL-2, IL-6, IL-10, and IL-17), tumor necrosis factor (TNF), and interferon gamma (IFN-γ) concentrations on peripheral blood inflammatory factors in the two groups; and isolate the two groups of peripheral blood mDCs cells; α interferon upregulated PD-L1 expression in the cells and analyzed the effect of PD-L1 expression on the ability of mDCs to stimulate T cells to secrete cytokines.Results. The positive expression rates of CD69 and HLA-DR on peripheral blood CD3+ T lymphocytes were significantly higher in patients in the atrial fibrillation group than in the control group, and the differences were statistically significant ( P < 0.01 ). The positive expression rate of PD-1 on CD4+ lymphocytes was significantly lower in patients in the atrial fibrillation group than in the control group ( P < 0.01 ). There was no statistically significant difference between the two groups in terms of PD-1 positive expression rate on CD8+ lymphocytes ( P > 0.05 ). The positive expression rate of PD-L1 on mDCs cells was significantly lower in patients in the atrial fibrillation group than in the control group ( P < 0.01 ), and there was no statistically significant difference between the two groups in the positive expression rate of PD-L2 on mDCs cells, PD-L1, and PD-L2 on CD4+ and CD8+ T cells ( P > 0.05 ). The concentrations of IL-2, IL-6, IL-10, and IFN-γ in peripheral blood were significantly higher in patients in the atrial fibrillation group than in the control group ( P < 0.05 ), and there was no statistically significant difference in the comparison of IL-17A and TNF concentrations in peripheral blood between the two groups ( P > 0.05 ). In the atrial fibrillation group, the ability of mDCs to stimulate T cells to secrete IL-2 and IFN-γ was significantly higher, and the ability to secrete IL-10 was significantly lower compared with the control group ( P < 0.05 ). After α interferon upregulated PD-L1 expression in cells, the ability of mDCs to stimulate T cells to secrete IL-2, IL-10, and IFN-γ cytokines was reversed in patients in the atrial fibrillation group, and the differences compared with the control group were not statistically significant ( P > 0.05 ). Conclusion. PD-1/PD-L1 signaling pathway may play an immunomodulatory role in the pathogenesis of atrial fibrillation by promoting increased secretion of inflammatory factors through regulating T cell activation.

Due to the rapid development of network communication technology and the significant increase in network terminal equipment, the application of new network architecture software-defined networking (SDN) combined with reinforcement learning in network traffic scheduling has become an important focus of research. Because of network traffic transmission variability and complexity, the traditional reinforcement-learning algorithms in SDN face problems such as slow convergence rates and unbalanced loads. The problems seriously affect network performance, resulting in network link congestion and the low efficiency of inter-stream bandwidth allocation. This paper proposes an automatic load-balancing architecture based on reinforcement learning (ALBRL) in SDN. In this architecture, we design a load-balancing optimization model in high-load traffic scenarios and adapt the improved Deep Deterministic Policy Gradient (DDPG) algorithm to find a near-optimal path between network hosts. The proposed ALBRL uses the sampling method of updating the experience pool with the SumTree structure to improve the random extraction strategy of the empirical-playback mechanism in DDPG. It extracts a more meaningful experience for network updating with greater probability, which can effectively improve the convergence rate. The experiment results show that the proposed ALBRL has a faster training speed than existing reinforcement-learning algorithms and significantly improves network throughput.

Objective. This study was aimed at developing a model for predicting postoperative biochemical recurrence of prostate cancer (PCa) using clinical data-CEUS-MRI radiomics and at verifying its clinical effectiveness. Methods. The clinical imaging data of 159 patients pathologically confirmed with PCa and who underwent radical prostatectomy in Xiangyang No. 1 People’s Hospital and Jiangsu Hospital of Chinese Medicine from March 2016 to December 2020 were retrospectively analyzed. According to the 2-5-year follow-up results, the patients were divided into the biochemical recurrence (BCR) group ( n = 59 ) and the control group ( n = 100 ). The training set and test set were established in the proportion of 7/3; 4 prediction models were established based on the clinical imaging data. In training set, the area under the curve (AUC) and decision curve analysis (DCA) by R was conducted to compare the efficiency of 4 prediction models, and then, external validation was performed using the test set. Finally, a nomogram tool for predicting BCR was developed. Results. Univariate regression analysis confirmed that the SmallAreaHighGrayLevelEmphasis, RunVariance, Contrast, tumor diameter, clinical T stage, lymph node metastasis, distant metastasis, Gleason score, preoperative PSA, treatment method, CEUS-peak intensity (PI), time to peak (TTP), arrival time (AT), and elastography grade were the influencing factors for predicting BCR. In the training set, the AUC of combinatorial model demonstrated the highest efficiency in predicting BCR [AUC: 0.914 (OR 0.0305, 95% CI: 0.854-0.974)] vs. the general clinical data model, the CEUS model, and the MRI radiomics model. The DCA confirmed the largest net benefits of the combinatorial model. The test set validation gave consistent results. The nomogram tool has been well applied clinically. Conclusion. The previous clinical and imaging data alone did not perform well for predicting BCR. Our combinatorial model firstly using clinical data-CEUS-MRI radiomics provided an opportunity for clinical screening of BCR and help improve its prognosis.

Currently, smart devices of Internet of Things generate massive amount of data for different applications. However, it will expose sensitive information to external users in the process of IoT data collection, transmission, and mining. In this paper, we propose a novel indexing and searching schema based on homocentric hypersphere and similarity-aware asymmetric LSH (H2SA-ALSH) for privacy-preserved data collection and mining over IoT environments. The H2SA-ALSH collects multidimensional data objects and indexes their features according to the Euclidean norm and cosine similarity. Additionally, we design a c - k -AMIP searching algorithm based on H2SA-ALSH. Our approach can boost the performance of the maximum inner production (MIP) queries and top- k queries for a given query vector using the proposed indexing schema. Experiments show that our algorithm is excellent in accuracy and efficiency compared with other ALSH-based algorithms using real-world datasets. At the same time, our indexing scheme can protect the user’s privacy via generating similarity-based indexing vectors without exposing raw data to external users.

Purpose. Hepatocellular carcinoma (HC) has emerged as one of the most prevalent malignancies on a global scale. Recently, immunotherapy has achieved favorable effectiveness in the management of multiple cancers. However, there are limited therapeutic options for advanced HC. As the liver is a special immune organ, we intend to uncover potential and effective immunotherapeutic modalities for HC. Our study was designed to develop specific immune-related miRNAs (IRMs) for outcome assessment and individualized strategies for the management of HC. Methods. The miRNA-seq and survival data of TCGA-LIHC dataset was enrolled into this program. We first collected IRMs from Immune-miR website. Differentially expression analysis was applied to screen aberrantly expressed IRMs. In order to set up an IRM-related index (IRMRI) in HC, we conducted the Cox relevant methods. Next, the statistical approaches (survival curve and ROC curve analyses) were utilized to detect the evaluation capacity of our IRMRI. Subsequently, we obtained the target genes of hub miRNAs from IRMRI through three miRNA-related predictive online tools (miRDB, miRTarBase, and TargetScan websites). Results. Five IRMs were determined to develop the IRMRI. It can effectively segregate all HC cases from two different risk subgroups. We identified a marked discrepancy in survival outcome between the two groups by survival analysis and confirmed the reliability of IRMRI in two testing sets. Moreover, we collected 10 hub target genes (ESR1, IGF1, PDGFRB, JUN, MYC, ZWINT, MAD2L1, TOP2A, KIF11, and CDCA8) which were strongly linked to HC progression and malignant behavior. Conclusion. We screened out five hub IRMs with clinical value and constructed a risk index model in HC, which can precisely assess the risk status and outcome of patients to a certain extent.

In recent years, there have been more and more studies on the use of construction and demolition waste (CDW) as subgrade filler. The physical performance indexes of a single material of floor slabs waste (FSW) are studied, which meet the requirements of subgrade specification. From the perspective of construction quality control, it is proposed that when FSW is used as subgrade filler, the compaction thickness and the maximum allowable particle size should be controlled according to different layers, and the gradation of subgrade filler is evaluated by using the nonuniformity coefficient (Cu) and curvature coefficient (Cc). The compaction test of FSW shows that the maximum dry density and optimum moisture content of different gradations do not change much. The crushing value under the freeze-thaw cycle is proposed to evaluate the frost resistance of FSW. The crushing value of FSW after water absorption and frost heaving changes a little. The CBR and resilience modulus tests were carried out on the FSW such that the results show that they have a good relationship and the relevant expressions under different compaction degrees are fitted. When performing on-site compaction testing, it is proposed that the upper roadbed adopts the sand replacement method according to the different layers of the FSW subgrade and the settlement discrepancy method should be adopted for other parts. Through laboratory tests and construction field detective, the quality control requirements, road performance indexes, and design indexes of FSW materials are put forward.

Aiming at the problems of low accuracy, poor stability, and effect of balance control in the current basketball skill balance control process, a basketball skill balance control method based on ant colony algorithm is proposed. The principle and characteristics of ant colony algorithm are analyzed, the mathematical model of ant colony algorithm is established, and the implementation steps of ant colony algorithm are given. According to the balance and stability control principle of basketball skills, this paper constructs the balance and stability control model of basketball skills. By establishing the knee-ankle-foot joint analysis model and using the ant colony algorithm, the basketball movement path is constructed. Through the fitness function, select the basketball motion path nodes and update the pheromone, obtain the relationship between the internal stress and displacement of the body under different force directions, and obtain the influence law of the effective knee joint stress with the varus and internal rotation, so as to achieve the balance and stability of the basketball skills sexual control analysis. The experimental results show that the proposed method has better stability and effect of basketball technique balance control and can effectively improve the accuracy of basketball technique balance control.

In this paper, we consider the three-dimensional Cauchy problem of the nonisentropic compressible Euler equations with relaxation. Following the method of Wu et al. (2021, Adv. Math. Phys. Art. ID 5512285, pp. 1–13), we show the existence and uniqueness of the global small H k k ⩾ 3 solution only under the condition of smallness of the H 3 norm of the initial data. Moreover, we use a pure energy method with a time-weighted argument to prove the optimal L p – L q 1 ⩽ p ⩽ 2 , 2 ⩽ q ⩽ ∞ -type decay rates of the solution and its higher-order derivatives.

The identification and analysis of the spatiotemporal dynamic traffic patterns in citywide road networks constitute a crucial process for complex traffic management and control. However, city-scale and synchronal traffic data pose challenges for such kind of quantification, especially during peak hours. Traditional studies rely on data from road-based detectors or multiple communication systems, which are limited in not only access but also coverage. To avoid these limitations, we introduce real-time, traffic condition digital maps as our input. The digital maps keep spatiotemporal urban traffic information in nature and are open to access. Their pixel colors represent traffic conditions on corresponding road segments. We propose a stacked convolutional autoencoder-based method to extract a low-dimension feature vector for each input. We compute and analyze the distances between vectors. The statistical results show different traffic patterns during given periods. With the actual data of Chongqing city, we compare the feature extraction performance between our proposed method and histogram. The result shows our proposed method can extract spatiotemporal features better. For the same data set, there is little difference in the number distribution of red pixels found in the statistics result of the histogram, while differences do exist in the results of our proposed method. We find the most fluctuated morning is on Friday; the most fluctuated evening is on Tuesday; and the most stable evening is on Wednesday. The distance captured by our method can represent the evolution of different traffic conditions during the morning and evening peak hours. Our proposed method provides managers with assistance to sense the dynamics of citywide traffic conditions in quantity.

We study the Cauchy problem of the three-dimensional full compressible Euler equations with damping and heat conduction. We prove the existence and uniqueness of the global small H N N ≥ 3 solution; in particular, we only require that the H 4 norms of the initial data be small when N ≥ 5 . Moreover, we use a pure energy method to show that the global solution converges to the constant equilibrium state with an optimal algebraic decay rate as time goes to infinity.

This work is concerned with the H ∞ control for Markov switching singularly perturbed systems with the stochastic communication protocol. To coordinate the data transmission and save the bandwidth usage, the stochastic communication protocol with a compensator is applied to schedule the information exchange. The goal of this work is to design a joint-Markov-process-based controller such that the resulting system is stochastically stable with prescribed performance. Based on the Lyapunov functional technique, a sufficient condition is derived to ensure the existence of the achieved controller. Finally, the effectiveness and correctness of the developed results are verified by the simulation example.

Stick-slip vibration reduces the drilling rate of penetration, causes early wear of bits, and threatens the safety of downhole tools. Therefore, it is necessary to study suppression methods of stick-slip vibration to achieve efficient and safe drilling. Field tests show that the use of downhole axial impactors is helpful to mitigate stick-slip vibration and improve rock-breaking efficiency. However, there are many deficiencies in the study of how axial impact load affects stick-slip vibration of a PDC bit. In this paper, based on the two-degrees-of-freedom spring-mass-damper model and similarity theory, a laboratory experiment device for suppressing stick-slip vibration of a PDC bit under axial impact load has been developed, and systematic experimental research has been carried out. The results show that the axial impact force can suppress the stick-slip vibration by reducing the amplitude of weight on bit and torque fluctuations and by increasing the main frequency of torque. The amplitude of impact force affects the choice of the optimal back-rake angle. The impact frequency is negatively correlated with the fluctuation amplitude of the rotary speed. When the impact frequency is greater than 100 Hz, the fluctuation amplitude of the rotary speed will not decrease.

The wide application of superhydrophobic materials is mainly hindered by the poor mechanical robustness and complicated preparation method. To overcome these problems, we tried to make a combination of hierarchical and self-similar structure by the means of a simple spraying method. By adding nanofiller (carbon nanotube) and microfiller (graphite powder and expanded graphite), the hierarchical structure was constructed. By further doping the fillers in the commercial asphalt uniformly, the self-similar structure was prepared. Based on the aforementioned work, the as-prepared sample could withstand the sandpaper abrasion for 12.00 m under 4.90 kPa. Moreover, this superhydrophobic coating demonstrated good conductivity, superior self-cleaning property, and excellent corrosion resistance. The integration of conductivity with the superhydrophobicity might open new avenues for ground grid applications.

With the rapid development of e-commerce, online retailing has become an important part of the market. In order to improve market competitiveness and increase market share, more and more retailers have opened both regular offline channel and online e-tail channel to sell products. Then how to price becomes an urgent problem for upstream manufacturers and dual-channel retailers when there is price competition between regular channel and e-tail channel, especially when consumers have peer-induced fairness concerns. However, linking consumers’ behavioral factors such as fairness concerns to pricing decisions of mixed retail and e-tail channels draws little attention in the literature on supply chain management. This paper incorporates “consumers’ peer-induced fairness concerns” (CPFC) into pricing decisions in a dyadic supply chain, where dual-channel retailer obtains products from manufacturers and then sells products to consumers through both regular channel and e-tail channel. We use game-theoretic models to analyze the equilibrium pricing strategies under the setting with “symmetry consumers’ peer-induced fairness concerns” (SCPFC) and with “asymmetry consumers’ peer-induced fairness concerns” (ACPFC), respectively. Detailed comparisons and numerical analysis are further conducted to examine the impacts of different types of CPFC on equilibrium pricing strategies and profits.

The successful development of tight oil reservoirs in the U.S. shows the bright future of unconventional reservoirs. Tight oil reservoirs will be the main target of exploration and development in the future, and CO2 huff-n-puff is one of the most important methods to enhance oil recovery factor of tight oil reservoirs in North America. To improve the performance of CO2 huff-n-puff, injection and production parameters need to be optimized through numerical simulation. The phase behavior and microscopic flow mechanism of CO2 huff-n-puff in porous media need to be further investigated. This paper presents a detailed review of phase behavior and microscopic flow mechanism in tight porous media by CO2 huff-n-puff. Phase behavior in tight porous media is different from that in a PVT cylinder since the capillary pressure in tight porous media reduces the bubble point pressure and increases the miscibility pressure and critical temperature. The condensate pressure in tight porous media and nonequilibrium phase behavior need to be further investigated. The microscopic flow mechanism during CO2 huff-n-puff in tight porous media is complicated, and the impact of molecular diffusion, gas-liquid interaction, and fluid-rock interaction on multiphase flow is significant especially in tight porous media. Nuclear magnetic resonance (NMR) and molecular simulation are efficient methods to describe the microscopic flow in tight oil reservoirs, while the NMR is not cost-effective and molecular simulation needs to be improved to better characterize and model the feature of porous media. The improved molecular simulation is still a feasible method to understand the microscopic flow mechanism of CO2 huff-n-puff in tight oil reservoirs in the near future. The microscopic flow model in micropore network based on digital core is worth to be established, and phase behavior needs to be further incorporated into the microscopic flow model of CO2 huff-n-puff in tight porous media.

Energy supply is an important system that affects the overall efficiency of urban transportation. To improve the system operational efficiency and reduce costs, we formulate and solve a collaborative multidepot petrol station replenishment problem with multicompartments and time window assignment by establishing a mixed-integer linear programming model. The hybrid heuristic algorithm composed of genetic algorithm and particle swarm optimization is used as a solution, and then the Shapley value method is applied to analyze the profit allocation of each petrol depot under different coalitions. The optimal membership sequence of the cooperation is determined according to the strict monotone path. To analyze and verify the effectiveness of the proposed method, a regional petrol supply network in Chongqing city in China is investigated. Through cooperation between petrol depots in the supply network, the utilization of customer clustering, time window coordination, and distribution truck sharing can significantly reduce the total operation costs and improve the efficiency of urban transportation energy supply. This approach can provide theoretical support for relevant government departments and enterprises to make optimal decisions. The implementation of the joint distribution of energy can promote the sustainable development of urban transportation.

Equipped with two power sources, the dual-driving powertrain system for pure electric vehicles has a driving mode different from traditional electric vehicles. Under the premise that the structural form of the transmission system remains unchanged, the following transmission schemes can be adopted for double drive electric vehicles according to the demand power: the main and auxiliary electric transmission scheme (two motors are driven separately with dual-motor coupling drive), the transmission scheme in which the two motors always maintain coupling drive, and the speed-regulating type electric transmission scheme (the main motor is always responsible for driving, and the auxiliary motor is responsible for speed regulation). Therefore, a significant difference exists in the design methods of the power transmission system of double drive electric vehicles and existing vehicles. As for such differences, this paper adopts intelligent algorithm to design the parameters of the transmission system and introduces the genetic algorithm into the optimization design of parameters to obtain the optimal vital parameters of the power transmission system based on computer simulation. The prototype car used in this paper is a self-owned brand car; MATLAB/Simulink platform is used to build the vehicle simulation model, which is used for the computer simulation analysis of the vehicle dynamic performance and economy. It can be seen from the analysis result that the system parameters obtained by using the global optimization method proposed in this study can improve the vehicle dynamic performance and economic performance to varying degrees, which proves the efficiency and feasibility of the optimization method.

Purpose. We assessed the clinical outcomes and toxicities following hypofractionation with helical tomographic intensity-modulated radiotherapy technology (tomotherapy) in patients with stage III non-small cell lung cancer (NSCLC) who were not candidates for surgery or concurrent chemoradiation. Methods. Forty-three patients with stage III NSCLC who were treated between 2011 and 2017 were enrolled. The prescription doses for gross target volume and clinical target volume were 70 Gy and 60 Gy (respectively) delivered in 15–25 fractions over 3–5 weeks. Results. The median overall survival (OS) time was 34.23 (range 11.33–99.33) months. The estimated 1-, 2-, and 3-year OS rates were 97.7%, 74.4%, and 55.9%, respectively; the corresponding progression-free survival (PFS) rates were 79.1%, 53.5%, and 36.1%, respectively. The local disease recurrence, regional disease recurrence, and distant metastasis rates at 3 years were 4.7%, 11.62%, and 55.81%, respectively. On multivariate analysis, dose regimen (p<0.05). Seven patients developed grade 1-2 acute radiation pneumonia (RP), 5 patients developed grade 1-2 late RP, while 3 patients developed grade 3 late RP. None of the patients developed grade 4-5 radiation lung injury. Conclusion. Tomotherapy may be an effective treatment option for patients with stage III NSCLC. It may be a viable alternative to surgery with lower incidence of side effects.

The injection-production ratio of ultralow-permeability reservoirs is generally higher in the early stage of development because of the water absorption characteristics of transition layers and mudstone formations. In this paper, the water absorption characteristics of mudstone are experimentally studied, and the empirical function of the water absorption process is established. A new mathematical model of the whole lithology is established by applying the research results of mudstone water absorption characteristics. Combining the material balance method and finite difference method, the space terms in the basic differential equation are replaced by the material balance equation, and the finite difference in the time term is obtained. Then, the analytical solutions of the average pressures of the reservoir oil well area, reservoir water well area, transition layers, and mudstone formations are solved. Based on the static parameters of the reservoir in the Chaoyang Gou Oilfield of the ultralow-permeability reservoir in China, the new pressure prediction model is verified by the ideal model of numerical simulation and production data of the oil field. The experimental results show that the saturation water absorption rate of mudstone is 1.54-2.55%, and the water absorption process of mudstone cannot be described by the seepage equation of sandstone. The verification results of the numerical simulation show that the pressure of the transition layers and mudstone at the end of the water well gradually increases, while the pressure at the end of the oil well basically remains unchanged, which is consistent with the assumptions of the model. The verification results of the oilfield production data show that the water well static pressure and oil well static pressure calculated by the new model are highly consistent with the actual values, which well explains the phenomenon of the low reservoir pressure level under the condition of a high injection production ratio in an ultralow-permeability reservoir.