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Fault diagnosis plays an indispensable role in prognostics and health management of rotating machines. In recent years, intelligent fault diagnosis methods based on domain adaptation technology have attracted the attention of researchers. However, a more extensive application scenario of fault diagnosis − partial domain adaptation (PDA) − has not been well-resolved. In this article, for the first time, a novel stacked auto-encoder based partial adversarial domain adaptation (SPADA) model is proposed to solve the fault diagnosis problem in PDA situations. Two deep stack auto-encoders are first designed to extract representative features from the training data (source domain) and test data (target domain), respectively. Then, a weighted classifier based on Softmax is used to weight the features from the source and target domains. Meanwhile, another domain discriminator and label predictor using the Softmax classifier are adopted to simultaneously implement domain adaptation and fault diagnosis. Comprehensive analysis is performed on real data to test the performance of the SPADA model and detailed comparisons are provided; the extensive experimental results show that the diagnosis performance of SPADA outperforms the existing deep learning and domain adaptation methods in dealing with the PDA problem.

Remaining useful life (RUL) prediction for condition-based maintenance decision making plays a key role in prognostics and health management (PHM). Accurately predicting RUL of the rotating components of complex machines becomes a challenging task for PHM. For many existing methods, the current prediction error of RUL prediction may be accumulated into the future predictions, and thus can lead to a prediction error superposition problem. In this article, the formation mechanism of prediction error superposition is analyzed, and for the first time a deep adversarial long short-term memory (LSTM) prognostic framework is proposed to overcome the major issue related to prediction error superposition. In the proposed framework, a generative adversarial network (GAN) architecture combining the LSTM network and autoencoder (AE) is investigated for bearing RUL monitoring. In the proposed deep adversarial learning prediction framework, due to the potential involvement of long-term and complex tasks, the LSTM network (generator) is used to predict the degradation process of rolling bearings based on available historical data, and a simple but useful AE (discriminator) is used to determine and refine the accuracy of the prediction. Therefore, the AE plays the adversarial role of the LSTM network, and the prediction accuracy of the LSTM network can be significantly improved. For illustration purpose, two practical case studies, which use a series of bearing degradation data and the IEEE PHM 2012 PRONOSTIA datasets, respectively, are presented to show the prediction performance of the proposed method. Experimental results show that the proposed method works very well for vibration monitoring and performs better in comparison with the reference machine learning and deep learning approaches. Impact Statement —The damage of rolling bearing usually leads to a significant consequence to industrial production process. However, the existing remaining useful life (RUL) prediction methods for rolling bearing have a prediction error superposition problem that can affect the multistep prediction performance. The new adversarial learning prognostics model proposed in this article can overcome the problem. The proposed method uses LSTM network as a generator to predict RUL life for rolling bearing, and uses AE as a discriminator to estimate the prediction accuracy. The method can significantly improve the multistep prediction accuracy of RUL for rolling bearing, and provides reliable and scientific strategy in PHM of mechatronics equipment.

Fault diagnosis of rolling bearings is an essential process for improving the reliability and safety of the rotating machinery. It is always a major challenge to ensure fault diagnosis accuracy in particular under severe working conditions. In this article, a deep adversarial domain adaptation (DADA) model is proposed for rolling bearing fault diagnosis. This model constructs an adversarial adaptation network to solve the commonly encountered problem in numerous real applications: the source domain and the target domain are inconsistent in their distribution. First, a deep stack autoencoder (DSAE) is combined with representative feature learning for dimensionality reduction, and such a combination provides an unsupervised learning method to effectively acquire fault features. Meanwhile, domain adaptation and recognition classification are implemented using a Softmax classifier to augment classification accuracy. Second, the effects of the number of hidden layers in the stack autoencoder network, the number of neurons in each hidden layer, and the hyperparameters of the proposed fault diagnosis algorithm are analyzed. Third, comprehensive analysis is performed on real data to validate the performance of the proposed method; the experimental results demonstrate that the new method outperforms the existing machine learning and deep learning methods, in terms of classification accuracy and generalization ability.

African swine fever, a serious infectious disease, has been found in many countries around the world over the last nearly 100 years, and causes untold damage to the economy wherever it occurs. Diagnosis is currently performed by real-time PCR, which is highly sensitive but can only be carried out in a diagnostic laboratory environment with sophisticated equipment and expertise. A sensitive, rapid diagnostic method that can be implemented in agricultural settings is thus urgently needed for the detection and control of African swine fever virus (ASFV) infection. In this study, we developed an isothermal amplification technology to achieve molecular diagnosis of ASFV in clinical samples, using recombinase-aided amplification (RAA) assay combined with a portable instrument. This assay method avoids the limitations of traditional real-time PCR and offers detection times within 20 min, enabling detection of as few as 10 copies of ASFV DNA molecules per reaction without cross-reaction with other common swine viruses. We evaluated clinical performance using 200 clinical blood samples. The coincidence rate of the detection results between rt-RAA and RT-qPCR was 96.94% positive, 100% negative, and 97.50% total. We have also developed an rt-RAA system for the detection of ASFV targeting the EP402R gene, with detection of as few as 10 copies of DNA per reaction; this offers the possibility of DIVA (differentiating infected from vaccinated animals) diagnosis, because CD2V gene-deleted ASFV could soon be approved to be the leading candidate for live attenuated vaccine in China. The rt-RAA assay is a reliable, rapid, highly sensitive method, and it offers a reasonable alternative to RT-qPCR for point-of-care detection of ASFV. KEY POINTS: • The RT-RAA assay can detect as few as 10 copies of ASFV genome per reaction within 20 min. • The rt-RAA assay system targeting different genes can achieve differentiating infected from vaccinated diagnosis.

Introduction The relationship between patient expectations and clinical outcomes has recently been of increasing interest in the field of orthopaedics. The objective of this study was to evaluate the relationships between (1) patient pre-treatment expectations and post-treatment clinical outcomes, and (2) fulfillment of expectations and patient satisfaction, following distal radius fracture. Methods This was a prospective multicenter cohort study conducted across three hospitals. A total of 133 patients admitted to hospital between 2016 and 2018 with a distal radius fracture were recruited. Patients were administered the Trauma Expectation Factor (TEF) at baseline to measure expectations of pain and functioning at one-year post-injury. Patients were followed up at 6 and 12 months post-injury and outcomes were measured using the Trauma Outcome Measure (TOM), Shortened Disabilities of the Arm, Shoulder and Hand (QuickDASH) questionnaire, and Short-Form 12-item (SF-12) health survey. Fulfillment of expectations was measured as TEF score minus TOM score at each time point. Patient satisfaction was also measured using the Patient Satisfaction Questionnaire Short Form (PSQ-18). Multivariate regression models were created to evaluate the effect of expectations on outcomes. Results Patient expectations correlated moderately with outcomes at 6 and 12 months post-injury. In the multivariate analysis, patient expectations were predictive of better outcomes at 6 and 12 months. Injury severity, age, mechanism of injury, and whether the injury occurred on duty also contributed significantly to one or more regression models. Patient satisfaction correlated weakly with fulfillment of expectations at 6 months, but moderately with all outcome scores. At 12 months, satisfaction did not correlate significantly with expectations fulfillment but correlated moderately to highly with all outcome scores. Conclusion Patient expectations independently predicted outcomes at 6 and 12 months post-injury. Standardized assessment and management of patient expectations may be relevant to future clinical practice and research to best quantify and optimize patient outcomes.

The temperature-induced response of long-span steel bridges can be more significant than the structural responses associated with operational loads or structural damage. These responses depend on the spatio-temporal temperature variation in bridge members, including the effective temperature and temperature difference within members. Bridges are designed to withstand the extreme temperature variations predicted for a given site. Hence, numerous studies have employed statistical analysis techniques to provide critical information for the design and maintenance of bridges during life cycles. However, the correlation between the effective temperature and temperature difference is usually ignored, which can result in inaccurate assessment of the extreme temperatures in members. In this work, the joint probability distribution for the temperature variation in a long-span steel truss arch bridge is investigated based on field monitoring data. The extreme temperature variations are mapped on contours with relevant return periods; the results show that the probability distribution of the effective temperature can be described using the normal distribution; the weighted sum of two lognormal distributions can describe the distribution of temperature difference. Moreover, extreme values of the effective temperature and temperature difference do not occur concurrently. The effective temperature and temperature difference in the structural member directly exposed to solar radiation vary significantly, while the temperature of the shaded member can be assumed uniform, which is mainly affected by air temperature. The study leads to more accurate estimation of the temperature extremes in long-span steel truss arch bridges, which is of great importance for proper design and maintenance of bridges.

Community-acquired Pneumonia (CAP) is an infection of the lung parenchyma that is acquired outside of hospital, [1] involved approximately 150 million new cases annually, among children younger than 5 years old worldwide. We retrospectively evaluated the effect of Prednisolone in 89 children with CAP who were admitted to the 2nd hospital of Shandong University (China) and Infectious diseases of Andijon region (Uzbekistan). The mean age was 6.3 in China (Placebo) and 9.3 in Uzbekistan (control) years, 54% and 52% of them were boys respectively. All children had received broad spectrum antibiotics (cephalosporin) or Macrolides (Azithromycin) and Oxygen. In addition to these we added Prednisolone 1 mg/kg on day 2 of admission to control group. 24 (68.5% from all febrile) children were became afebrile within 24 hours after Predisolone use on day 3 of admission, and their clinical status developed in control group, when it was achieved on day 7 in Placebo group. Hospital days also shortened in control group (6 days) than placebo (8 days) (p value ≤ 0.01). In conclusion, steroid therapy helpful for reducing hospital stay and morbidity in children with community-acquired Pneumonia and no observed side effects.

Rotating machinery is important to industrial production. Any failure of rotating machinery, especially the failure of rolling bearings, can lead to equipment shutdown and even more serious incidents. Therefore, accurate residual life prediction plays a crucial role in guaranteeing machine operation safety and reliability and reducing maintenance cost. In order to increase the forecasting precision of the remaining useful life (RUL) of the rolling bearing, an advanced approach combining elastic net with long short-time memory network (LSTM) is proposed, and the new approach is referred to as E-LSTM. The E-LSTM algorithm consists of an elastic mesh and LSTM, taking temporal-spatial correlation into consideration to forecast the RUL through the LSTM. To solve the over-fitting problem of the LSTM neural network during the training process, the elastic net based regularization term is introduced to the LSTM structure. In this way, the change of the output can be well characterized to express the bearing degradation mode. Experimental results from the real-world data demonstrate that the proposed E-LSTM method can obtain higher stability and relevant values that are useful for the RUL forecasting of bearing. Furthermore, these results also indicate that E-LSTM can achieve better performance.

Ferroelectric Rashba semiconductors (FERSCs) have recently attracted intensive attention due to their giant bulk Rashba parameter, αR, which results in a locking between the spin degrees of freedom and the switchable electric polarization. However, the integration of FERSCs into microelectronic devices has provoked questions concerning whether the Rashba effect can persist when the material thickness is reduced to several nanometers. Here we find that αR can keep a large value of 2.12 eV A in the 5.0 nm thick GeTe film. The behavior of αR with thickness can be expressed by the scaling law and provides a 3D thickness limit of the bulk Rashba effect, dc = 2.1 ± 0.5 nm. Finally, we find that the thickness can modify the Berry curvature as well, which influences the polarization and consequently alters the αR. Our results give insight into understanding the factors influencing αR in FERSCs and pave a novel route for designing Rashba-type quantum materials.

The synchronization-inspired clustering algorithm (Sync) is a novel and outstanding clustering algorithm, which can accurately cluster datasets with any shape, density and distribution. However, the high-dimensional dataset with high dimensionality, high noise, and high redundancy brings some new challenges for the synchronization-inspired clustering algorithm, resulting in a significant increase in clustering time and a decrease in clustering accuracy. To address these challenges, an enhanced synchronization-inspired clustering algorithm, namely SyncHigh, is developed in this paper to quickly and accurately cluster the high-dimensional datasets. First, a PCA-based (Principal Component Analysis) dimension purification strategy is designed to find the principal components in all attributes. Second, a density-based data merge strategy is constructed to reduce the number of objects participating in the synchronization-inspired clustering algorithm, thereby speeding up clustering time. Third, the Kuramoto Model is enhanced to deal with mass differences between objects caused by the density-based data merge strategy. Finally, extensive experimental results on synthetic and real-world datasets show the effectiveness and efficiency of our SyncHigh algorithm.

Background Coronavirus disease 2019 (COVID-19) is a worldwide pandemic outbreak with a high mortality. Prognostic factors of critically ill patients with COVID-19 have not been fully elucidated yet. Methods In the present study, 59 patients with COVID-19 from the intensive care unit of the Caidian Branch of Tongji Hospital were enrolled. Epidemiological, demographic, clinical, laboratory, radiological, treatment data, and clinical outcomes were collected. Prognostic factors were statistically defined. Results Of the 59 patients studied (67.4±11.3 years), 38 patients were male, 51 had underlying diseases, and 41 patients died during admission. Compared with the survivors, the deceased patients were of older age, had more smoking history, severer fatigue, and diarrhea, a higher incidence of multiple organ injuries, more deteriorative lymphopenia and thrombocytopenia, remarkably impaired cellular immune response, and strengthened cytokine release. Age higher than 70 (OR=2.76, 95% CI=1.45-5.23), arrhythmia (OR=4.76, 95% CI=1.59-14.25), and a Sequential Organ Failure Assessment (SOFA) score above 4 (OR=5.16, 95% CI=1.29-20.55) were identified as risk factors for mortality of patients. Conclusion Critically ill COVID-19 patients aged higher than 70, arrhythmia, or a SOFA score above 4 have a high risk of mortality, and need prior medical intervention.

Among a variety of traditional Chinese medicines, Shuanghuanglian injection (SHLI), has the highest incidence of injection-induced immediate hypersensitivity reactions (IHRs). However, the precise mechanisms of SHLI-induced IHRs remain to be understood. In the present study, we characteriszed IHRs as induced by SHLI by recording changes in physiological and hemodynamic indicators following intravenous injections of SHLI in rats and dogs. The results indicate that SHLI induced the release of histamine, decreased mean arterial blood pressure (MAP), increased SC5b-9 in rats and dogs, increased C4d and Bb in dogs without any changes in IgE. n vitro incubation of SHLI with serum from dogs in the presence of an inhibitor of complement activation (EGTA/Mg2+) resulted in an increase in C4d. These results suggest that SHLI induces anaphylactoid reactions in rats and dogs. Furthermore, SHLI appears to activate the complement system through classical and alternative pathways in dogs in vivo. Additional experiments in mice demonstrated that SHLI induces locus coeruleus infiltration and results in significant increase in vascular permeability within the skin of mice. We established a reliable method for the evaluation of anaphylactoid reactions induced by complex compounds, using multiple physiological indicators, different experimental models in vivo and in vitro.

Background Intervertebral disc degeneration (IDD) is the most common diagnosis of patients with lower back pain. IDD is the underlying lesion of many spinal degenerative diseases; however, the role of cGAS/Sting/NLRP3 pathway and epigallocatechin gallate (EGCG) in the development of IDD remained unclear. Methods The expressions of cGAS, Sting and NLRP3 mRNA of intervertebral disc (IVD) samples from IDD patients and controls were detected by RT-PCR. The nucleus pulposus cells (NPCs) were induced by hydrogen peroxide (H2O2) and used as an in-vitro model. Both 5 μM and 25 μM EGCG treatment were used to detect the effect of EGCG on the in-vitro model. Cell viability was detected by the MTT method, and cell apoptosis and cell cycle would be detected by flow cytometry. Western blot was used in the detection of the expression of cGAS/Sting/NLRP3 as well as apoptosis-related protein level. ELISA was used in the detection of pro-inflammatory factors, including IL-1β, TNF-α, IL-6 and IL-10. Results The expressions of cGAS, Sting and NLRP3 mRNA were significantly increased in the IVD samples from IDD patients and NLRP3 was associated with cGAS and Sting. Advanced in-vitro study showed that H2O2 significantly increased the expression of cGAS, Sting and NLRP3 protein levels. Advanced experiments showed that EGCG treatment demonstrated significant protective effects in cell viability, apoptosis, cell cycle arrest and inflammatory status through down-regulation of cGAS/Sting/NLRP3 pathway. Conclusion It was shown that the cGAS, Sting and NLRP3 up-regulation was associated with the incidence of IDD. Our findings also suggest that EGCG treatment would provide anti-apoptosis, anti-inflammation and promote cell viability in H2O2 treatment-incubated NPCs through inhibiting cGAS/Sting/NLRP3 pathway.

Background Apoptosis has been repeatedly linked with diabetic kidney disease (DKD), which is a programmed cell death mediated by effector caspases-3, 6 and 7, targeting >600 substrates. However, the pathophysiologic correlations of this process remain obscure. As a putative tumor suppressor, gasdermin E (GSDME) was recently reported to be cleaved by caspase-3 to produce a GSDME-N fragment which targets the plasma membrane to switch apoptosis to secondary necrosis. However, it remains elusive whether GSDME is involved in the regulation of DKD. Methods To evaluate the therapeutic potential of caspase-3 inhibition in DKD, we administered caspase-3 inhibitor Z-DEVD-FMK to STZ-induced diabetic mice for eight weeks. Albuminuria, renal function, pathological changes, and indicators of secondary necrosis and fibrosis were evaluated. In vitro, human tubule epithelial cells (HK-2 cells) were subjected to high-glucose treatment. Secondary necrosis was determined by LDH release, GSDME cleavage, and morphological feature under confocal microscopy. Z-DEVD-FMK and GSDME inhibition by shRNA were administered to suppress the cleavage and expression of GSDME. Flow cytometry, cytotoxicity assay and immunoblot were used to assess cell death and fibrogenesis. Results Caspase-3 inhibition by Z-DEVD-FMK ameliorated albuminuria, renal function, and tubulointerstitial fibrosis in diabetic mice. The nephroprotection mediated by Z-DEVD-FMK was potentially associated with inhibition of GSDME. In vitro, molecular and morphological features of secondary necrosis were observed in glucose-stressed HK-2 cells, evidenced by active GSDME cleavage, ballooning of the cell membrane, and release of cellular contents. Here we showed that caspase-3 inhibition prevented GSDME activation and cell death in glucose-treated tubular cells. Specifically, knocking down GSDME directly inhibited secondary necrosis and fibrogenesis. Conclusion These data suggest GSDME-dependent secondary necrosis plays a crucial role in renal injury, and provides a new insight into the pathogenesis of DKD and a promising target for its treatment.

Hereditary Angioedema (HAE) is a rare genetic disease generally caused by deficiency or mutations in the C1-inhibitor gene, SERPING1, a member of the Serpin family. HAE results in acute attacks of edema, vasodilation, GI pain and hypotension. C1INH is a key inhibitor of enzymes controlling complement activation, fibrinolysis and the contact system. In HAE patients, contact system activation leads to uncontrolled production of bradykinin, the vasodilator responsible for the characteristic symptoms of HAE. In this study, we present the first physiological in vivo model to mimic acute HAE attacks. We evaluate hypotension, one of the many hallmark symptoms of acute HAE attacks using Serping1 deficient mice (serping1−/−) and implanted telemetry. Attacks were induced by IV injection of a silica nanoparticle (SiNP) suspension. Blood pressure was measured in real time, in conscious and untethered mice using implanted telemetry. SiNP injection induced a rapid, reversible decrease in blood pressure, in the presence of angiotensin converting enzyme (ACE) inhibition. We also demonstrate that an HAE therapeutic, ecallantide, can prevent HAE attacks in this model. The in vivo murine model described here can facilitate the understanding of acute HAE attacks, support drug development and ultimately contribute to improved patient care.

Background: Optimal adjustment of cardiac preload is essential for improving left ventricle stroke volume (LVSV) and tissue perfusion. Changes in LVSV caused by central venous pressure (CVP) are the most important concerns in the treatment of critically ill patients.Objectives: This study aimed to clarify the changes in LVSV after negative fluid balance in patients with elevated CVP, and to elucidate the relationship between the parameters of right ventricle (RV) filling state and LVSV changes.Methods: This prospective cohort study included patients with high central venous pressure (CVP) (≥8 mmHg) within 24 h of ICU admission in the Critical Medicine Department of Peking Union Medical College Hospital. Patients were classified into two groups based on the LVSV changes after negative fluid balance. The cutoff value was 10%. The hemodynamic and echo parameters of the two groups were recorded at baseline and after negative fluid balance.Results: A total of 71 patients included in this study. Forty in VI Group (LVOT VTI increased ≥10%) and 31 in VNI Group (LVOT VTI increased p < 0.001) and P(v-a)CO2 (p < 0.001) and lower ScVO2 (p < 0.001) relative to VNI Group, regarding the echo parameters at T0, the RVD/LVD ratio (p < 0.001), DIVC end−expiratory (p < 0.001), and ΔLVOT VTI (p < 0.001) were higher, while T0 LVOT VTI (p < 0.001) was lower, in VI Group patients. The multifactor logistic regression analysis suggested that a high CVP and RVD/LVD ratio ≥0.6 were significant associated with LVSV increase after negative fluid balance in critically patients. The AUC of CVP was 0.894. A CVP >10.5 mmHg provided a sensitivity of 87.5% and a specificity of 77.4%. The AUC of CVP combined with the RVD/LVD ratio ≥0.6 was 0.926, which provided a sensitivity of 92.6% and a specificity of 80.4%.Conclusion: High CVP and RVD/LVD ratio ≥0.6 were significant associated with RV stressed in critically patients. Negative fluid balance will not always lead to a decrease, even an increase, in LVSV in these patients.

Neutralizing antibodies to the SARS CoV-2 spike proteins have been issued Emergency Use Authorizations and are a likely mechanism of vaccines to prevent COVID-19. However, benefit of treatment with monoclonal antibodies has only been observed in clinical trials in outpatients with mild to moderate COVID-19 but not in patients who are hospitalized and/or have advanced disease. To address this observation, we evaluated the timing of anti SARS-CoV-2 antibody production in hospitalized patients with the use of a highly sensitive multiplexed bead-based immunoassay allowing for early detection of antibodies to SARS-CoV-2. We found significantly lower levels of antibodies to the SARS-CoV-2 spike protein in the first week after symptom onset in patients who expired as compared to patients who were discharged. We also developed a model to characterize the relationship between each patient’s individual antibody level trajectory and eventual COVID 19 outcome which can be adapted into a prediction model with more data., Author summary We evaluated antibodies to SARS-CoV-2 over time in patients that were hospitalized with COVID 19. Early detection of Anti-SARS-CoV-2 antibodies was associated with survival in patients hospitalized with COVID 19. Early antibody levels predicted outcome in our study. This result is consistent with the benefit of therapeutic antibodies early in the course of COVID 19 disease. With additional study, early antibody levels may be helpful in deciding on appropriate therapies.

Robust and reliable drivetrain is important for preventing electromechanical (e.g., wind turbine) downtime. In recent years, advanced machine learning (ML) techniques including deep learning have been introduced to improve fault diagnosis performance for electromechanical systems. However, electromechanical systems (e.g., wind turbine) operate in varying working conditions, meaning that the distribution of the test data (in the target domain) is different from the training data used for model training, and the diagnosis performance of an ML method may become downgraded for practical applications. This paper proposes a joint distribution optimal deep domain adaptation approach (called JDDA) based auto-encoder deep classifier for fault diagnosis of electromechanical drivetrains under the varying working conditions. First, the representative features are extracted by the deep auto-encoder. Then, the joint distribution adaptation is used to implement the domain adaptation, so the classifier trained with the source domain features can be used to classify the target domain data. Lastly, the classification performance of the proposed JDDA is tested using two test-rig datasets, compared with three traditional machine learning methods and two domain adaptation approaches. Experimental results show that the JDDA can achieve better performance compared with the reference machine learning, deep learning and domain adaptation approaches.

Angiopoietins (Angs) are a family of vascular growth factors that share multiple cellular functions related to cell survival, proliferation, and migration. Angs play physiological and pathological roles through the Tie tyrosine kinase receptors. The Ang-Tie signaling pathway participates in the developmental and tumor-induced angiogenesis and is also involved in many disease settings, such as vascular diseases, systemic inflammation, and cancers. Since Angs are widely expressed in the kidney, an enormous amount of research focuses on their roles in the kidney. In this review, we describe the biological functions of the Ang-Tie signaling pathway and summarize their roles in kidney development and maturation, acute and chronic kidney diseases, diabetic nephropathy, lupus nephropathy, hemolytic uremic syndrome, end-stage renal diseases, and renal cell carcinoma. Understanding the molecular mechanisms of Ang-Tie signaling may reveal potential therapeutic targets for preventing or alleviating kidney diseases.

Objective: To investigate the potential molecular mechanism of Xin Hui Tong Formula (XHTF) in the treatment of coronary heart disease (CHD) by using network pharmacology and bioinformatics. Methods: The targets network of CHD was constructed through Therapeutic Targets Database (TTD) and Drugbank database; The XHTF pharmacodynamic molecule-targets network and the XHTF pharmacodynamic molecule-CHD targets network were explored by the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP). And the multi-targets mechanism and molecular regulation network of XHTF in the treatment of CHD were explored from multiple perspectives by Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) database pathway enrichment analysis. Results: A total of 88 CHD targets were screened out through the Therapeutic Targets and the Drugbank database. 393 compounds and corresponding 205 drug targets of XHTF were retrieved from TCMSP. A total of 13 known targets directly related to the development of CHD were retrieved from the disease-related databases: TP53, MAPK14, NFKB1, HSPA5, PLG, PTGS2, ADRB1, NOS2, CYP3A4, GRIA2, CYP2A6, GRIA1, PTGS1. XHTF also contained 118 drug targets that directly interact with CHD targets. GO enrichment analysis showed that the biological processes of 13 direct targets proteins were found to be mainly enriched in response to drug, cellular response to biotic stimulus, long-chain fatty acid metabolic process, fatty acid metabolic process and regulation of blood pressure. KEGG pathway enrichment analysis found that XHTF participated in the CHD pathological process mainly through retrograde endocannabinoid signaling, regulation of lipolysis in adipocytes, cAMP signaling pathway, chemical carcinogenesis and other pathways. Conclusions: XHTF plays a role in the treatment of CHD through multiple targets and multiple pathways, and provides a scientific basis for the theory of “virtual standard” in the treatment of CHD. Keywords: Xin Hui Tong Formula (XHTF), Coronary heart disease, Network pharmacology, Network analysis, Bioinformatics

To explore the amplitude of low frequency fluctuation (ALFF) and functional connectivity (FC) disorders in non-neuropsychiatric systemic lupus erythematosus (non-NPSLE) patients by resting-state functional magnetic resonance imaging (rs-fMRI) and to study whether there are some clinical biomarkers that can be used to monitor the brain dysfunction. Based on the rs-fMRI data of 36 non-NPSLE patients and 30 normal controls, we first obtained the regions with abnormal ALFF signals in non-NPSLE patients. Then, by taking these areas as seed regions of interest (ROIs), we calculated the FC between ROIs and the whole brain to assess the network-level alterations. Finally, we correlated the altered values of ALFF and FC in non-NPSLE patients to some clinical data. Compared with the controls, non-NPSLE patients showed decreased ALFF in bilateral precuneus and increased ALFF in right cuneus and right calcarine fissure surrounding cortex (CAL). At network level, non-NPSLE patients exhibited higher FC between left precuneus and left middle occipital gyrus (MOG)/left superior occipital gyrus (SOG)/right middle frontal gyrus (MFG)/right dorsolateral superior frontal gyrus (SFGdor), and higher FC between right cuneus and bilateral precuneus/left posterior cingulate gyrus (PCG). The abnormal ALFF in right CAL and abnormal FC in right cuneus–left precuneus, right cuneus–right precuneus, and right cuneus–left PCG were correlated with the patients’ certain clinical data (p

Jun-Hong Zhou,1,&ast; Kang Yu,2,&ast; Hui Ding,1 Zhao-Hua Zhu,3,&ast; Li-Hua Han,1,&ast; Ting Zhang1 1Department of Obstetrics, Sunshine Union Hospital, Weifang, 261000, Shandong, People’s Republic of China; 2The Reproductive Medicine Center of Weifang People’s Hospital, Weifang, 261000, Shandong, People’s Republic of China; 3Department of Obstetrics, Traditional Chinese Medicine Hospital of Weifang, Weifang, 261000, Shandong, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Ting Zhang; Hui DingDepartment of Obstetrics, Sunshine Union Hospital, No. 9000 of Yingqian Street, Kuiwen District, Weifang, 261000, Shangdong, People’s Republic of ChinaTel +86 15169502878Email zhangting_nn@163.com; dinghui88con@163.comObjective: This study aimed to explore the impact of gestational diabetes mellitus (GDM) on the results of newborn hearing screening.Methods: A total of 666 pregnant women who gave birth in the Obstetric Department of Sunshine Ronghe Hospital from August 2017 to May 2018 were randomly selected, and 69 of these pregnant women had GDM and were assigned into group 1 (excluding other diseases). The average age of these patients was 31.07 years. A further 597 pregnant women had no GDM and were assigned into group 2 (excluding other diseases). The average age of these patients was 30.02 years. The results of newborn hearing screening results in group 1 and group 2 were compared.Results: Comparisons of abnormal hearing screening between 2 groups are significant different (P < 0.05). In the GDM group, the results of hearing screening of newborns delivered by vaginal delivery and cesarean delivery were compared, yielding a P-value of > 0.05, and the difference was not statistically significant. In the non-GDM group, the results of hearing screening of newborns delivered by vaginal delivery and cesarean delivery were compared, yielding a P-value of > 0.05, and the difference was not statistically significant.Conclusion: GDM increases the incidence of abnormal hearing in newborns.Keywords: diabetes, pregnancy, newborn, hearing screening, otoacoustic emission

Hoffa fracture is a rare type of distal femoral fracture occurs in the coronal plane of either femoral epicondyle. To date, screws in combination with lateral plate fixation is widely accepted to achieve stable fixation and good results. However, up to now there has not been a specially designed anatomical plate for lateral fixation of Hoffa fracture. In this report, we demonstrate a case of Hoffa fracture fixed with reverse application of "L" shaped contralateral proximal tibia plate and cannulated screws, resulting in good one-year results.

Nonmagnetic Rashba systems with broken inversion symmetry are expected to exhibit nonreciprocal charge transport, a new paradigm of unidirectional magnetoresistance in the absence of ferromagnetic layer. So far, most work on nonreciprocal transport has been solely limited to cryogenic temperatures, which is a major obstacle for exploiting the room-temperature two-terminal devices based on such a nonreciprocal response. Here, we report a nonreciprocal charge transport behavior up to room temperature in semiconductor α-GeTe with coexisting the surface and bulk Rashba states. The combination of the band structure measurements and theoretical calculations strongly suggest that the nonreciprocal response is ascribed to the giant bulk Rashba spin splitting rather than the surface Rashba states. Remarkably, we find that the magnitude of the nonreciprocal response shows an unexpected non-monotonical dependence on temperature. The extended theoretical model based on the second-order spin–orbit coupled magnetotransport enables us to establish the correlation between the nonlinear magnetoresistance and the spin textures in the Rashba system. Our findings offer significant fundamental insight into the physics underlying the nonreciprocity and may pave a route for future rectification devices., Most work on nonreciprocal transport is limited to cryogenic temperatures due to the low Rashba spin splitting energy. Here, the authors report a nonreciprocal charge transport behavior up to room temperature in semiconductor α-GeTe with coexisting the surface and bulk Rashba states.

In space environment, the charge will be collected on the surface of the spacecraft by the combination of the surrounding space plasma and photoelectric effect, forming a suspension potential different from the background plasma environment, that is, the surface charging phenomenon. The integrated monitoring system of plasma environment and surface charging includes 4 parts: omnidirectional electron spectrometer, omnidirectional ion spectrometer, surface potential probe and magnetometer. The main function is to detect the space plasma environment and the surface potential on the satellite, and to process, store and transmit the received signals. Ground testing and calibration have been done for all the four detectors, and the results agree well with the designed value.

A fast response high-voltage power supply for the electrostatic deflection system in a low-energy particle spectrometer is designed. The high-voltage power supply uses high-voltage optocouplers as the core amplifying devices, and the output stage is a two-arm push-pull amplifier composed of two high-voltage optocouplers. The experimental results show that the high-voltage power supply can output either positive or negative voltage from the same output port, and the output voltage range is from −3 kV to +3 kV, which can meet the demand of the electrostatic deflection system for the bipolar voltage supply. The adjustment speed of the output voltage is fast. The time of voltage rise or fall does not exceed 1.7 ms, which can speed up the scanning speed of the spectrometer and improve the time resolution. The output stage adopts a push-pull amplification structure, which can improve the temperature stability of the output voltage. The design satisfies the expected performance of the high-voltage power supply for the electrostatic deflection system.

This paper describes a sample-hold (SH) circuit for the front-ended pipelined 12-bit analog-to-digital converter (ADC). A differential OTA (operational transconductance amplifier) used in the sample-hold (SH) circuit is presented. The OTA is optimized for high-speed high-accuracy applications by using gain-boosted topology. By means of clamp circuit, the slewing rate of the OTA is greatly improved. The design uses the chartered 0.35-μm 2P4M CMOS process with a 3 V supply. The open-loop DC gain is over 110 dB and unity-gain bandwidth is 524.6 MHz. The slewing rate of the OTA is 1160 V/μs while the total load capacitance is 6pf. The SH circuit can settle within 10 ns to an accuracy of

This scheme makes the best use of structure of the cargo ship by integrating with air-breathing helicon plasma electrical propulsion. The normal operation of a manned space station requires regular replenishment of oxygen, fuel, food and instruments. Research on resupply spacecraft to supply oxygen and fuel to the space station will help reduce the replenishment needs of the station. A resupply spacecraft with air-breathing electrical propulsion as core technology will meet the replenishment needs of the space station during on-orbit operation at a low cost and bring high loading capacity and substantial economic benefits. The replenishment ship based on this scheme can collect 1000 kg working gas a year on 180 km orbit and reduce the cost of building and launching cargo ships. This paper carried out studies on mission process, resource consumption, orbit design and thrust Analysis. The ionization mode of air-breathing electrical propulsion is helicon discharge and the average power for orbit maintaining and air collecting is about 775 W.

BackgroundWhether tumour-infiltrating lymphocytes (TILs) play different roles in different molecular subtypes of breast cancer remains unknown. Additionally, their prognostic and predictive value in different molecular subtypes of breast cancer is still controversial. The aim of our meta-analysis was to assess the prognostic and predictive value of TILs in different molecular subtypes of breast cancer by summarizing all relevant studies performing multivariate analysis.MethodsPubMed, Embase, EBSCO, ScienceDirect, the Cochrane Database and Web of Science were comprehensively searched (until March 2020). Hazard ratios (HRs), odds ratios (ORs) and their 95% confidence intervals (CIs) were used as effect measures to perform our meta-analysis. A random effect model was used. Stata software, version 15 (2017) (StataCorp, College Station, TX, USA) was used to perform the statistical analysis.ResultsThirty-three studies including 18,170 eligible breast cancer patients were analysed. The meta-analysis showed that high TIL expression was significantly associated with increased pathological complete response (pCR) rates after neoadjuvant chemotherapy in patients with the HER2-enriched molecular subtype (OR = 1.137, 95% CI [1.061 ~ 1.218],p p < 0.001). However, high TIL expression was not significantly associated with high pCR rates after neoadjuvant chemotherapy in patients with the luminal molecular subtype of breast cancer (OR = 1.154, 95% CI [0.789 ~ 1.690],p = 0.460). We carried out a meta-analysis on the HRs of overall survival (OS) and disease-free survival (DFS) to assess the prognostic value of TILs in breast cancer with different molecular subtypes more deeply. Our meta-analysis confirmed that high TILs were associated with significantly improved DFS in patients with the HER2-enriched molecular subtype [HR = 0.940, 95% CI (0.903 ~ 0.979),p = 0.003] and TNBC molecular subtype [HR = 0.907, 95% CI (0.862 ~ 0.954),p p = 0.840]. Furthermore, the results confirmed that high TILs were significantly related to better OS in patients with the HER2-enriched molecular subtype [HR = 0.910, 95% CI (0.866 ~ 0.957),p p p = 0.012].ConclusionsOur meta-analysis confirms that high TILs are associated with favourable survival and predicts pCR in breast cancer patients with the TNBC and HER2-enriched molecular subtypes.

To improve the accuracy of partial demagnetization fault diagnosis for permanent magnet synchronous motor (PMSM), an improved fuzzy extreme learning machine (F-ELM) algorithm is constructed by integrating fuzzy theory into the extreme learning machine (ELM) in this paper. Firstly, a PMSM field-circuit coupling simulation system under vector control is established by employing finite element analysis method. Secondly, the feature samples affecting classification accuracy can be obtained using wavelet packet decomposition (WPD). Thirdly, by taking the imbalance of demagnetization feature into consideration, a new type of improved ELM, i.e., F-ELM, is proposed by associating input layer with a fuzzy membership. Finally, a comparison with the accuracy of back-propagation neural network (BPNN), support vector machine (SVM), and ELM is performed. The experimental results show that the proposed method outperforms the existing machine learning methods, and can effectively diagnose the partial demagnetization fault of PMSM.

This paper first analyzes the concept of computer network environment in China, and then expounds the shortcomings in the ecological teaching mode of college English under the computer network environment; finally, the paper analyzes the strategies of constructing the ecological teaching mode of college English under the computer network environment, including the detailed discussion and planning of diversified teaching methods, communication among subjects in the teaching process and the connection of classroom contents. Based on the current situation of ecological college English teaching in China, this paper makes full use of computer network environment to promote its application and development in ecological college English teaching mode.

In recent years, with the continuous development of life education and school physical education, both of them have been paid more and more attention, and life education has become a new proposition in the development of school physical education. Life education is not only a means of education, but also a people-oriented view of school physical education. There are many problems in the implementation of life education because of the difference between instrumental education and teachers' quality. Based on the concept of life education, this paper tries to analyze the current situation, existing problems and countermeasures of the implementation of life education in Chinese school physical education, so as to explore the value orientation of school physical education reform, which is a very meaningful research topic.

The stable operation of the remote sensing satellite receiving system is related to the success or failure of satellite data reception. Accurate fault diagnosis can promptly and effectively troubleshoot and reduce the loss of economic and social benefits. Aiming at the characteristics of fault diagnosis for remote sensing satellite receiving system, a fault diagnosis expert system based on fault tree is designed in this paper. The system builds a fault tree model and expert knowledge base for a remote sensing satellite receiving system, and uses a combination of forward reasoning based on a rule framework and quantitative fault tree analysis to locate the fault. The fault diagnosis expert system has been applied to practical engineering projects, which effectively improves the efficiency of fault diagnosis of remote sensing satellite receiving systems, and is conducive to preventing and controlling faults of remote sensing satellite receiving systems.

Orbit maneuver of non‐cooperative space targets is difficult to detect, and thus greatly affects the accuracy of real‐time target tracking. To solve this problem, a joint filter‐based algo...

Mars has become a hot spot in deep space exploration. New probe manner is required to investigate the planet more efficiently and flexibly. Mars aircraft is a new Mars exploration tool and the research in this field is of great significance. Quad-rotor aircraft is a key development direction of Mars aircraft research because of its simple structure, high reliability, the ability of hovering in the air and repeatable takeoff and landing. In this paper, the propulsion system, which is the most critical technology of the Mars quad-rotor UAV, is studied. When designing the propeller, the relationship between the blade inclination, rotation speed, radius and other factors on the blade lifting force is established, by using two-dimensional CFD simulation, and then the detailed structure of the propeller is designed. Based on design result, the carbon fiber propeller was manufactured and the lifting force measurement test and the load-bearing take-off test were carried out under the simulated Mars atmosphere environment. The results were consistent with the simulation analysis. This study can provide an important design basis for the development of Mars quad-rotor UAV.

As a new magnetic field measurement technology, magnetoresistive magnetometer has the absolute advantages in weight, power consumption and size, and plays an irreplaceable role in many fields. Because the data acquisition of the magnetoresistive magnetometer rely on ADC, So the paper presents the circuit design of a high-precision signal acquisition system based on sigma-delta ADC for magnetoresistive magnetometer. In this design, FPGA is adopted as the core controller of the system to control the read and write of six AD7710, it also completes receiving, caching, and sending ADC sampling data. The system self-test results show that the noise RMS value of the sampled data is 0.0019 mV when the sampling frequency is selected as 30 Hz, which is better than the typical output RMS noise value of the device.

Helicon wave ionization source could provide abundant and excellent plasma for space electric propulsion. Now it is widely recommended and required to test and verify the technology. This paper designed and analyzed the structure of the helicon wave electric propulsion system and completed mechanics calculation with finite element method (FEM) software to validate the rationality and reliability. At last, it gave final conclusion and prospect.

With the development of electric propulsion technology, the measurement of plasma parameters has been widely used in the field of aerospace. In the process of electric propulsion performance examination and test, the plasma parameters are indispensable to the analysis of electric propulsion performance. Plasma parameters such as electron temperature, plasma density, plasma flux density play important roles in plasma technology, which are the important basis to determine plasma state of electric propulsion. There has a variety of diagnosis method for Plasma electric propulsion. But the radio frequency, electric and magnetic fields often existed in electric propulsion environment. Therefore, It is necessary to use the Retarding potential analyzer (RPA) and Langmuir probe (ALP) together to test the plasma parameters. Experiment data can be mutually verified to effectively improve the accuracy and reliability of test data. The test data of xenon and nitrogen plume obtained in this experiment is of great significance for the in-depth study of helical wave propulsion.

This paper puts forward a kind of self-excited RF power control system, which is more suitable for helicon plasma electric propulsion system than traditional RF generator based on a servo motor. Simple structure makes it smaller and lighter. It has no moving parts, and so that can be easily transformed into aerospace products. This system achieves the goal of impedance matching by using phase lock loop to trace load frequency. A verification circuit is designed, and the results prove that the design is feasible.

In high-speed scenarios, channel model is of vital importance in Long term evolution (LTE) systems. By extensive measurements on Beijing-Tianjinrailway, this paper proposes a distance-dependent channel model. Both large-scale and small-scale channel characteristics are presented in detail. The large-scale path loss is modeled under the hierarchical network structure. Small-scale channel characteristics that include channel impulse response, power delay profile and Doppler spectrum are deduced and analyzed. In particular, a new stage-wise K-factor model is proposed. Combined with the cumulative distribution function of Root-mean squared (RMS) delay spread and the number of paths, they clearly illustrate the distancedependent variances of the channel. Finally, the integrated distance-dependent channel models are proposed to give a comprehensive description of broadband LTE channel in high-speed railway scenario.

Objective: We used a meta-analysis framework to examine the correlation between HIF-1α gene polymorphisms and the susceptibility to digestive cancers. Methods: Cochrane Library Database, EMBASE, MEDLINE, Pubmed, CINAHL, Chinese Biomedical Database and Web of Science were searched without language restrictions to identify relevant case-control studies reporting data on HIF-1α gene polymorphisms in digestive cancers. Data was extracted from the selected studies and meta-analysis was carried out using STATA 12.0 and Comprehensive Meta-analysis 2.0 softwares. Relative risk (RR) and its 95% confidence interval (95%CI) were calculated. A total of 8 eligible case-control studies were included. These 8 studies contained a combined total of 1,276 patients diagnosed with various digestive cancers and 3,392 healthy controls. Two functional HIF-1α polymorphisms (rs11549465 C>T and rs11549467 G>A) were examined in these 8 studies. Results: Our findings demonstrated that both rs11549465 C>T and rs11549467 G>A HIF-1α polymorphisms conferred significantly increased risk of digestive cancers. However, ethnicity-stratified analysis revealed that HIF-1α rs11549465 C>T and rs11549467 G>A polymorphisms were associated with an elevated risk of digestive cancer in Asians, but not in Caucasians. These two polymorphisms also conferred different degrees of susceptibility to various digestive cancer types. Conclusion: Our meta-analysis suggests that HIF-1α rs11549465 C>T and rs11549467 G>A polymorphisms influence the pathogenesis of digestive cancers in Asians.

Atomically flat MnSi films were fabricated on Si(1 1 1)-7 × 7 reconstructed surface by molecular beam epitaxy(MBE). Both scanning tunneling microscopy (STM) images and low energy electron diffraction (LEED) patterns demonstrate a well-defined ( 3 × 3 )R30o structure reconstruction. A thickness-driven metal–semiconductor transition in MnSi ultrathin films was observed with decreasing the thickness down to 6 ML (monolayers). The temperature dependence of the resistance and the negative magnetoconductivity suggest the MnSi ultrathin films with thickness lower than 6ML exhibit weak anti-localization (WAL) of two-dimensional (2D) electron systems. This finding that not only advances our understanding of the mechanism of thickness-driven metal–semiconductor transition, but also provides a new strategy to use ferromagnetic semiconductor as spin injector in spintronic devices.

Rechargeable sodium-ion batteries have drawn increasing attention as candidates for the post lithium-ion batteries in large-scale energy storage systems. Layered oxides are the most promising cathode materials and their pure phases (e.g., P2, O3) have been widely investigated. Here we report a series of cathode materials with O3/P2 hybrid phase for sodium-ion batteries, which possesses advantages of both P2 and O3 structures. The designed material, Na0.78Ni0.2Fe0.38Mn0.42O2, can deliver a capacity of 86 mAh g–1 with great rate capability and cycling performance. 66% capacity is still maintained when the current rate reaches as high as 10C, and the capacity retention is 90% after 1500 cycles. Moreover, in situ XRD was performed to examine the structure change during electrochemical testing in different voltage ranges, and the results demonstrate 4 V as the optimized upper voltage limit, with which smaller polarization, better structural stability, and better cycling performance are achieved. The results ob...

A dynamic particle swarm optimization with learning strategy (DPSO-LS) is proposed for key parameter estimation for permanent magnet synchronous machines (PMSMs), where the voltage-source inverter (VSI) nonlinearities are taken into account in the parameter estimation model and can be estimated simultaneously with other machine parameters. In the DPSO-LS algorithm, a novel movement modification equation with variable exploration vector is designed to effectively update particles, enabling swarms to cover large areas of search space with large probability and thus the global search ability is enhanced. Moreover, a Gaussian-distribution-based dynamic opposition-based learning strategy is developed to help the pBest jump out local optima. The proposed DPSO-LS can significantly enhance the estimator model accuracy and dynamic performance. Finally, the proposed algorithm is applied to multiple parameter estimation including the VSI nonlinearities of a PMSM. The performance of DPSO-LS is compared with several existing PSO algorithms, and the comparison results show that the proposed parameters estimation method has better performance in tracking the variation of machine parameters effectively and estimating the VSI nonlinearities under different operation conditions.

AIM: To investigate the effect of anti-vascular epithelial growth factor (VEGF) agents on the expression of fibrosis-related inflammatory mediators under normoxic and hypoxic conditions, and to further clarify the mechanism underlying fibrosis after anti-VEGF therapy. METHODS: Human retinal pigment epithelial (RPE) cells were incubated under normoxic and hypoxic conditions. For hypoxia treatment, CoCl2 at 200 μmol/L was added to the media. ARPE-19 cells were treated as following: 1) control group: no treatment; 2) bevacizumab group: bevacizumab at 0.25 mg/mL was added to the media; 3) hypoxia group: CoCl2 at 200 μmol/L was added to the media; 4) hypoxia+bevacizumab group: CoCl2 at 200 μmol/L and bevacizumab at 0.25 mg/mL were added to the media. The expression of interleukin (IL)-1β, IL-6, IL-8 and tumor necrosis factor (TNF)-α were evaluated using real-time polymerase chain reaction (RT-PCR) and enzyme-linked immunosorbent assay (ELISA) at 6, 12, 24 and 48h. RESULTS: Both mRNA and protein levels of IL-1β, IL-6 and IL-8 were statistically significantly higher in the bevacizumab group than in the control group at each time point, and TNF-α gene and protein expression was only significantly higher only at 24 and 48h (P

Based on collaborative innovation theory, the paper analyzes several more mature new energy vehicles in recent years and innovative technologies, and constructs a promoting strategic framework which is about five stages of Yutong new energy vehicles collaborative innovation. At the same time, through triple-helix theoretical analysis, the paper analyzes and summarizes the role of “Government - Industry - University - Research institution” in Yutong new energy vehicles innovation strategy and the roles that government, related enterprises, universities and research institutions play in collaborative innovation. Finally, the paper analyzes the stages of Yutong new energy vehicle development and the cooperation between Yutong business model innovation and technology innovation, thus studying on innovation strategy in the future and developing the international market.