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Pathogens detected by metagenomic next-generation sequencing (mNGS) and the laboratory blood culture flask method were compared to understand the advantages and clinical significance of mNGS assays in the etiological diagnosis of peritoneal dialysis-associated peritonitis (PDAP). The study involved a total of 37 patients from the hospital’s peritoneal dialysis centre, six of whom were patients with non-peritoneal dialysis-associated peritonitis. Peritoneal dialysis samples were collected from the 37 patients, who were divided into two groups. One group’s samples were cultured using conventional blood culture flasks, and the other samples underwent pathogen testing using mNGS. The results showed that the positive rate of mNGS was 96.77%, while that of the blood culture flask method was 70.97% (p < 0.05). A total of 29 pathogens were detected by mNGS, namely 24 bacteria, one fungus, and four viruses. A total of 10 pathogens were detected using the bacterial blood culture method, namely nine bacteria and one fungus. The final judgment of the PDAP’s causative pathogenic microorganism was made by combining the clinical condition, response to therapy, and the whole-genome sequencing findings. For mNGS, the sensitivity was 96.77%, the specificity was 83.33%, the positive predictive value was 96.77%, and the negative predictive value was 83.33%. For the blood culture flask method, the sensitivity was 70.97%, the specificity was 100%, the positive predictive value was 100%, and the negative predictive value was 0%. In conclusion, mNGS had a shorter detection time for diagnosing peritoneal dialysis-related peritonitis pathogens, with a higher positive rate than traditional bacterial cultures, providing significant advantages in diagnosing rare pathogens.

This article used Mn-Mo-Cr-B low-carbon bainitic steel as the experimental material. The continuous cooling transformation curve of the steel during continuous cooling was determined using a Gleeble-1500D thermal simulation test machine, and a corresponding phase transformation model for bainitic steel during continuous cooling was established. The influence of different cooling rates and final cooling temperatures on the microstructure and mechanical properties of the steel was investigated. Employing metallography, SEM, and EBSD techniques, the microstructure, crystallographic orientation, and grain boundary angle distribution of the low-carbon bainitic steel were explored, and their relationship with the steel's strength and toughness was studied. The research findings reveal that varying cooling rates and final cooling temperatures impact the phase transformation process and microstructure of the steel, consequently affecting its mechanical properties indirectly. With increasing cooling rate, the diffusion and fineness of martensite increase, and the quantity of lath bainite grows while the laths become finer. Elevated final cooling temperatures lead to larger martensitic-austenitic (MA) islands and reduced lath bainite quantity, causing the laths to become wider. Through analysis of the substructure of bainitic steel, it was determined that the bainite organization in the tested steel comprises primary austenite grains, lath packet, and lath block in succession. Lath packets are composed of lath blocks with different orientations, where lath size predominantly controls strength. Finer lath size corresponds to higher strength, and the influence of substructure on toughness is comparatively minor.

The enhanced recovery after surgery (ERAS) program is less implemented in gastric cancer patients. The purpose of this survey is to investigate the implementation status of ERAS in perioperative period in gastric cancer.

In order to conform to the development of the times and effectively promote the reform of vocal music education in colleges and universities, this paper proposes an innovative path of diversified vocal music education reform in colleges and universities under the modern advanced educational concepts that are steadily gaining utilisation and popular acceptance in China and the West. In this paper, the passive collective behaviour of biology is introduced in the teacher stage in the basic TLBO algorithm, and then the feedback stage is added after the student stage to increase the effectiveness of students’ learning methods, maintain the diversity of students and make available a system the deployment of which would swiftly bring students with poor grades to the attention of teachers; to this end, the algorithm is made to perform a local fine search, and the optimisation accuracy of the algorithm and its global search ability are improved. Finally, based on the numerical simulation of the standard test set and compared with the existing optimised TLOB algorithm, it is concluded that 92% of the solutions in the ETLBO are dominated or not dominated by the solutions in the non-dominated solution set of the optimised TLBO, while only 2% of the solutions in the non-dominated solution set of the optimised ETLBO are dominated by the non-dominated solutions of the TLBO. Centralised solutions dominate or do not dominate each other. It is concluded that the optimised TLBO algorithm has the best solution ability and also has practical application significance.

This paper introduces the BOPPPS teaching model integrated with flipped classrooms into the intercultural communication classroom by decomposing the BOPPPS teaching module and analyzing the differences with traditional teaching methods by combining social network analysis methods. The basic teaching model framework was built, and an effective blended teaching model was created by utilizing the third-order nonlinear expression of social networks introduced into the online platform. A 10-week teaching model experiment was conducted for two classes to explore English major students in a university. The overall average score of the experimental class improved by 23.6 points to 86.02, and the score improvement was significantly higher than that of the control class, proving that the hybrid teaching model is an effective way to cultivate talents for universities.

ABSTRACTThe GaoFen-14 (GF-14) satellite is China’s most recent high-resolution earth observation satellite system. It is equipped with a two linear-array stereo camera and is intend for topographic mapping at 1:10,000-scale without ground control points (GCPs). The technical parameters of payloads will change once the satellite enters orbit. As a result, strict on-orbit geometric calibration is necessary. This study performs the on-orbit geometric calibration of the GF-14 stereo camera using ground calibration data. The exterior orientation errors are corrected by a comprehensive bias matrix, internal orientation errors are described by a fifth order polynomial. The results of Yinchuan calibration field show that the planar accuracy is better than 286 m (RMS) before calibration, and improved to 2.11 m (front camera) and 1.51 m (back camera) by external orientation, and further improved to 1.46 m (front camera) and 0.99 m (back camera) after internal calibration. The front intersection accuracy reaches 0.67 m in plane (RMS) and 1.10 m in elevation (RMS), respectively. Checking by multiple global check points (CKPs), the planar and elevation RMS reaches 2.38 m (5.09 m in CE90) and 2.08 m (3.43 m in LE90), respectively.

Summary: Honeycomb is a distributed smart building system that is robust, flexible, and portable. Here, we present a protocol that uses semi-physical simulation to construct a Honeycomb prototype. We describe steps for software and hardware preparation, as well as the implementation of a video-based occupancy detection algorithm. Besides, we provide examples and scenarios of distributed applications, including node failure and recovery. We further provide guidance on data visualization and analysis to facilitate the design of distributed applications for smart buildings.For complete details on the use and execution of this protocol, please refer to Xing et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

ObjectiveTo investigate the late detection of HIV/AIDS cases in the elderly in Jilin Province and analyze its influencing factors， to provide theoretical basis for improving their life quality.MethodsThe first CD4 values of HIV/AIDS patients aged 50 years and above living in Jilin Province were used to estimate late detection， and the influencing factors of late detection in elderly cases were analyzed.ResultsThe average CD4 cell count of newly reported HIV/AIDS cases aged 50 and above in Jilin Province from 1996 to 2021 was （230.55±191.97）， the low value group accounted for the largest proportion （50.8%）， and the late detection rate was 59.3% （1397/2325）. The late detection cases were mainly from sexual transmission （46.8% for same-sex and 48.2% for heterosexual contact）. From the perspective of sample sources， most of the late detection patients were diagnosed while testing for other illnesses， followed by testing and consulting. In terms of contact history， the late detection of cases of men who have sex with men was higher. The binary logistic regression analysis showed that gender， marriage， sample source and report year were the factors affecting the late detection of AIDS. The late detection rate of males was higher， and cases of married couples were more likely to be late detection. With the increase of report year， the late detection rate decreased， and testing and counseling could effectively reduce the late detection rate of AIDS.ConclusionThe CD4 cell count in the first detection of HIV/AIDS in the elderly in Jilin Province is low， and the late detection rate of male cases is high. In recent years， the expansion of voluntary counseling and testing in Jilin Province has effectively reduced the late detection rate of HIV/AIDS. At the same time， sex education should be strengthened for the elderly， healthy marital relationships should be advocated and more attention should be paid to the mental health of the elderly.

Cancer is one of the deadliest diseases in the world.Using machine learning to process microarray data plays an important role in assisting the early diagnosis of cancer,but the numbers of genetic features are much more than samples,leading to an imbalance in the sample,and the efficiency and accuracy of classification are affected,so it is important to select the feature of gene array data.Most of the existing feature selection algorithms are single condition feature selection,which seldom consider feature extraction.Most of them use the long-existing neural network and have low classification accuracy.So,a two-stage deep feature selection(TSDFS) algorithm is proposed.The first stage aggregates three feature selection algorithms for comprehensive feature selection,and feature subsets are obtained.In the second stage,unsupervised neural network is used to obtain the best representation of feature subset and improve the final classification accuracy.This paper analyzes the effectiveness of TSDFS by comparing the classification effect before and after feature selection and different feature selection algorithms.Experimental results show that TSDFS algorithm can reduce the number of features while maintaining or improving the accuracy of classification.

ObjectiveTo investigate the social support status and influencing factors of schizophrenics in remission in Northeast Sichuan， and to provide ideas for improving their social support.MethodsFrom May to September 2020， a total of 533 patients who met the diagnosis criteria of the International Classification of Diseases， tenth edition （ICD-10） for schizophrenics in remission at the mental health institutions in Guangyuan， Bazhong and Dazhou cities were selected for the survey， and patients were assessed by self-made demographic and clinical data inventory and Social Support Rating Scale （SSRS）. Then the social support status of schizophrenic in remission and influencing factors were analyzed， meantime， the impact of the second round reimbursement policy of medical insurance benefits on their social support was addressed particularly.Results①The SSRS total score， objective support， subjective support， and utilization of support scores of schizophrenics in remission were lower than those of the national norm （t=5.065~30.382， P5 000 yuan （F=15.892）， patient's economic income （t=4.083）， and outpatient or online follow-up （F=3.954）， with statistically significant differences （P

Buildings are responsible for approximately 40% of the world’s energy consumption and 36% of the total carbon dioxide emissions. Building occupancy is essential, enabling occupant-centric control for zero emissions and decarbonization. Although existing machine learning and deep learning methods for building occupancy prediction have made notable progress, their analyses remain limited when applied to complex real-world scenarios. Moreover, there is a high expectation for Transformer algorithms to predict building occupancy accurately. Therefore, this paper presents an occupancy prediction Transformer network (OPTnet). We fused and fed multi-sensor data (building occupancy, indoor environmental conditions, HVAC operations) into a Transformer model to forecast the future occupancy presence in multiple zones. We performed experimental analyses and compared it to different occupancy prediction methods (e.g., decision tree, long short-term memory networks, multi-layer perceptron) and diverse time horizons (1, 2, 3, 5, 10, 20, 30 min). Performance metrics (e.g., accuracy and mean squared error) were employed to evaluate the effectiveness of the prediction algorithms. Our OPTnet method achieved superior performance on our experimental two-week data compared to existing methods. The improved performance indicates its potential to enhance HVAC control systems and energy optimization strategies.

Text sentiment analysis is a hot field in natural language processing.In recent years,Chinese text sentiment analysis methods have been widely investigated.Most of the recurrent neural network and convolutional neural network models based on word vectors have insufficient ability to extract and retain text features.In this paper,a Chinese sentiment polarity analysis model combining bi-directional GRU (BGRU) and multi-scale CNN is proposed.First,BGRU is utilized to extract text serialization features filtered with attention mechanism.Then the convolution neural network with distinct convolution kernels is applied to attention mechanism to adjust the dynamic weights.The text is acquired by the Softmax emotional polarity.Experiments indicates that our model outperforms the state-of-the-art methods on Chinese datasets.The accuracy of sentiment classification is 92.94% on the online_shopping_10_cats dataset of ChineseNLPcorpus,and 92.75% on the hotel review dataset compiled by Tan Songbo of Chinese Academy of Sciences,which is significantly improved compared with the current mainstream methods.

Functional maturation of liver sinusoidal endothelial cells (LSECs) plays an important role in intrahepatic T‐cell activation and control of viral infections. Natural killer (NK) cells have been reported to prompt the maturation of antigen‐presenting cells (APCs), especially for dendritic cells (DCs), but the interaction between NK cells and LSECs is elusive. Here, we investigated whether and how NK cells are involved in regulating LSEC maturation and if this has a role in controlling hepatitis B virus (HBV) infection in a mouse model. A chronic HBV replication mouse model was established by hydrodynamic injection (HI) of 6 µg adeno‐associated virus plasmid (pAAV)/HBV 1.2. The nucleotide‐binding oligomerization domain‐containing protein 1 (NOD1) ligand diaminopemelic acid (DAP) was imported into liver by HI at day 14 after plasmid injection. We found that HI of DAP recruited conventional NK cells (cNK) into the liver and promoted tumor necrosis factor alpha (TNF‐α) and interferon‐gamma (IFN‐γ) production of NK cells in a chemokine (C‐X‐C motif) receptor 3 (CXCR3)‐dependent manner. Importantly, the maturation of LSECs and the anti‐HBV effects of DAP were impaired in CXCR3−/− mice; this possibly was associated with the decreased number of intrahepatic cNK cells. Consistently, depleting cNK cells but not liver‐resident NK cells also impaired the maturation and antigen‐presenting function of LSECs, which reduced intrahepatic HBV‐specific T‐cell responses and thus inhibited HBV clearance both in wild‐type and in Rag1−/− mice. Moreover, TNF‐α or IFN‐γ stimulation as well as coculture with intrahepatic NK cells partly promoted LSEC phenotypic and functional maturation in vitro. Conclusion: NOD1‐triggered NK cell activation may lead to the enhancement of intrahepatic T‐cell responses by promoting maturation of LSECs through soluble cytokines and cell–cell contact, thereby controlling HBV replication and expression.

Chikungunya virus (CHIKV) is an emerging mosquito-transmitted alphavirus that leads to acute fever and chronic debilitating polyarthralgia. To date, the mechanism underlying chronic recurrent arthralgia is unknown. In the present study, newborn wild-type C57BL/6 mice were infected with CHIKV, and the virological and pathological features of CHIKV infection were analyzed over a period of 50 days. Acute viral infection was readily established by footpad inoculation of CHIKV at doses ranging from 10 plaque forming unit (PFU) to 106 PFU, during which inoculation dose-dependent viral RNA and skeletal muscle damage were detected in the foot tissues. However, persistent CHIKV was observed only when the mice were infected with a high dose of 106 PFU of CHIKV, in which low copy numbers (103−104) of viral positive strand RNA were continuously detectable in the feet from 29 to 50 dpi, along with a low level and progressive reduction in virus-specific CD8+ T cell responses. In contrast, viral negative strand RNA was detected at 50 dpi but not at 29 dpi and was accompanied by significant local skeletal muscle damage at 50 dpi when mild synovial hyperplasia appeared in the foot joints, although the damage was briefly repaired at 29 dpi. These results demonstrated that a high viral inoculation dose leads to viral persistence and progression to chronic tissue damage after recovery from acute infection. Taken together, these results provide a useful tool for elucidating the pathogenesis of persistent CHIKV infection and viral relapse-associated chronic arthritis. Author summary CHIKV infection has caused several outbreaks and affected millions of people in epidemic areas since the virus was originally isolated in 1952. CHIKV is transmitted by mosquitoes, resulting in acute diseases typically characterized by severe and debilitating arthritis, myalgia and fever, followed by persistent or recurrent joint and muscle pain that may last for months to years. The persistence of CHIKV in patients has been validated by clinical evidence, but it remains unclear how chronic and recurrent tissue injury are correlated with persistent viral infection. In this study, we established acute and chronic CHIKV infections in mice with different viral inoculation doses and identified the correlation of infection dose with outcomes resulting from CHIKV infection. We found that a high inoculation dose not only resulted in persistent viral infection but also led to a typical acute-recovery-relapse model of myositis and joint injury in mice. We also found that CHIKV RNA replication was interrupted after the acute phase, which might be related to the low antiviral T cell responses and relapse of histopathological injuries. Our study highlights the key factors involved in the clinical outcomes after CHIKV infection and provides new insights into the interaction between viral persistence and recurrent arthritis.

Distributed energy systems (DES), as an integrated energy system with coupled distributed energy resources, have great potential in reducing carbon dioxide emissions and improving energy efficiencies. Considering the background of urbanization and the energy revolution in China, the study investigates the renewable-based DESs supply modes and their application in China. A new method is proposed to classify DESs supply modes into three categories considering the renewable resource in domination, and their application domains are discussed. A comprehensive model is given for economic and environmental evaluation. Typical case studies show that the renewable-based DES systems can supply the energy in a cost-effective and environment-friendly way. Among them, the biomass waste dominated supply mode can not only achieve “zero” carbon emissions but also “zero” energy consumption, even though not yet economically attractive under the present policy and market conditions. Thus, recommendations are given to promote the further deployment of renewable-based DESs, regarding their supply modes, policy requirements, and issues to be addressed.

The catenary of full-compensated simple chain suspension widely used at present china railway was taken as the research object,and a dynamic simulation model of pantograph-catenary was established using the finite element method. The pantograph and catenary model were established as three dimensional flexible multibody systems,while the droppers were simulated as non-linear spring model. The coupling of pantograph-catenary system was found by the contact of pantograph and catenary. The form-finding analysis of catenary was carried out before the transient dynamic analysis of catenary. Results shows that fluctuating range of contact force between the pantograph and catenary increase gradually. In the same span,the largest force fluctuations appear in number1 and 7 droppers,tension and compression states appear in one cycle,It is more prone to damage than the rest of droppers which only bear tension force.

Osteoarthritis (OA) is the most common type of arthritis with no effective therapy. Subchondral bone and overlying articular cartilage are closely associated and function as “osteo-chondral unit” in the joint. Abnormal mechanical load leads to activated osteoclast activity and increased bone resorption in the subchondral bone, which is implicated in the onset of OA pathogenesis. Thus, inhibiting subchondral bone osteoclast activation could prevent OA onset. Betaine, isolated from the Lycii Radicis Cortex (LRC), has been demonstrated to exert anti-inflammatory, antifibrotic and antiangiogenic properties. Here, we evaluated the effects of betaine on anterior cruciate ligament transection (ACLT)-induced OA mice. We observed that betaine decreased the number of matrix metalloproteinase 13 (MMP-13)-positive and collagen X (Col X)-positive cells, prevented articular cartilage proteoglycan loss and lowered the OARSI score. Betaine decreased the thickness of calcified cartilage and increased the expression level of lubricin. Moreover, betaine normalized uncoupled subchondral bone remodeling as defined by lowered trabecular pattern factor (Tb.pf) and increased subchondral bone plate thickness (SBP). Additionally, aberrant angiogenesis in subchondral bone was blunted by betaine treatment. Mechanistically, we demonstrated that betaine suppressed osteoclastogenesis in vitro by inhibiting reactive oxygen species (ROS) production and subsequent mitogen-activated protein kinase (MAPK) signaling. These data demonstrated that betaine attenuated OA progression by inhibiting hyperactivated osteoclastogenesis and maintaining microarchitecture in subchondral bone.

To evaluate the performance and energy savings of different ventilative cooling systems, three mixed forms of ventilative cooling were described and the most promising rule-based heuristic control criteria were used as applicable control strategies based on various control parameters. Parametric analyses including the ventilative cooling set-points and control frequencies have been conducted. EnergyPlus was used to perform the aforementioned analyses based on a typical office building. Case studies verified that the use of different control parameters led to different indoor air environment and energy performance in a certain climatic zone. Then, the percentages outside the range indexes (POR) of the three mixed forms of ventilative cooling with various control parameters in five representative climatic zones in China were calculated, the results demonstrated that the ventilative cooling performance was mainly related to the ventilative cooling form in HSCW, HSWW, and temperate climatic zones. While in cold and severe cold climatic zones, it was mainly affected by selection of control parameters and its corresponding set-points. It can provide guidance for the selection of ventilative cooling scheme capable of maintaining indoor environment level with a low energy consumption in different climatic zones of China.