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Abstract During the coronavirus disease 2019 (COVID-19) pandemic, the exploration of microecology has been essential for elucidating the intricacies of infection mechanisms and the recovery of afflicted individuals. To decipher the interplay of microorganisms between the intestinal and respiratory tracts, we collected sputum and throat swabs and feces from COVID-19 patients and explored the mutual migration among intestinal and respiratory microorganisms. Using next-generation sequencing (NGS) technology, we investigated intestinal and respiratory microorganism intermigration in two patients with severe COVID-19 during their hospitalization. Notably, we observed an expedited recovery of microecological equilibrium in one patient harboring Mycobacterium avium. Comparative analyses between 32 healthy controls and 110 COVID-19 patients with different disease severities revealed alterations in predominant microorganisms inhabiting the respiratory and intestinal tracts of COVID-19 patients. Among the alterations, intestinal Bacteroides vulgatus (BV) was identified as a noteworthy microorganism that exhibited marked enrichment in patients with severe COVID-19. BV, when highly abundant, may inhibit the transitional growth of Escherichia coli/Enterococcus, indirectly prevent the overgrowth of salivary streptococci, and maintain lung/intestinal microecology stability. In summary, this study elucidates the bidirectional microbial intermigration between the intestinal and respiratory tracts in COVID-19 patients. These findings are expected to provide new ideas for the treatment and management of COVID-19, underscoring the essential role of microecology in infectious diseases. Nevertheless, a systematic study of the roles of BV in recovery from infection is required to gain a deeper understanding of the mechanisms of microbial migration.

Background/Objective: The aims of this study were to examine the effect of SARS-CoV-2 infection on cardiorespiratory fitness (CRF) and time-trial performance in vaccinated well-trained young kayak athletes. Methods: This is a longitudinal observational study. Sixteen (7 male, 9 female) vaccinated kayakers underwent body composition assessment, maximal graded exercise test, and 1000-m time-trial tests 21.9 ± 1.7 days before and 66.0 ± 2.2 days after the SARS-CoV-2 infection. The perception of training load was quantified with Borg's CR-10 scale before and after the infection return to sport period. Results: There were significant decreases in peak oxygen uptake (−9.7 %; effect size [ES] = 1.38), peak oxygen pulse (−5.7 %; ES = 0.96), and peak heart rate (−1.9 %; ES = 0.61). Peak minute ventilation, and minute ventilation/carbon dioxide production slope were unchanged after infection compared to the pre-infection values. In the entire 1000-m, the impaired tendencies were found in completion time, mean power, and mean speed (−2.4 to 1.2 %; small ESs = -0.40 to 0.47) as well as significant changes in stroke rate and stroke length (−4.5 to 3.7 %; ESs = -0.60 to 0.73). Conclusion: SARS-CoV-2 infection decreased CRF and time-trial performance even two months after return to regular training in vaccinated athletes.

Abstract Background This study assessed the global trends and burden of severe chest injury, including rib fractures, lung contusions, and heart injuries from 1990 to 2019. Herein, we predicted the burden patterns and temporal trends of severe chest injuries to provide epidemiological evidence globally and in China. Methods In our analysis, the age-standardized incidence rate (ASIR), prevalence rate (ASPR), and years lived with disability rate (ASYR) of severe chest injury were analyzed by gender, age, sociodemographic index, and geographical region between 1990 and 2019 using data from the Global Burden of Disease study 2019. Trends were depicted by calculating the estimated annual percentage changes (EAPCs). The impact of age, period, and cohort factors was assessed using an Age-Period-Cohort model. Autoregressive integrated moving average (ARIMA) model was employed to predict severe chest injury trends from 2020 to 2050. Results In 2019, the global number of severe chest injury cases reached 7.95 million, with the highest incidence rate observed in Central Europe (209.61). Afghanistan had the highest ASIRs at 277.52, while North Korea had the lowest ASIRs at 41.02. From 1990 to 2019, the Syrian Arab Republic saw significant increases in ASIR, ASPR, and ASYR, with EAPCs of 10.4%, 9.31%, and 10.3%, respectively. Burundi experienced a decrease in ASIR with an EAPC of − 6.85% (95% confidence interval [CI] − 11.11, − 2.37), while Liberia’s ASPR and ASYR declined with EAPCs of − 3.22% (95% CI − 4.73, − 1.69) and − 5.67% (95% CI − 8.00, − 3.28), respectively. Falls and road injuries remained the most common causes. The relative risk of severe chest injury by age, period, and cohort demonstrated a complex effect globally and in China. The ARIMA model forecasted a steady increase in global numbers from 2020 to 2050, while in China, it forecasted an increase in incidence, a decrease in ASIR and ASYR, and an increase in ASPR. Conclusions This study provides a groundbreaking analysis of global severe chest injury, shedding light on its measures and impact. These findings highlight the need for timely, specialized care and addressing regional disparities to mitigate the severe chest injury burden.

Staphylococcal enterotoxins (SEs) serve as the primary cause of staphylococcal food poisoning and other foodborne intoxications. Among them, staphylococcal enterotoxin C (SEC) has the highest prevalence in dairy products, leading to multiple outbreaks all around the world. Thus, it is of great significance to develop a highly sensitive, highly specific and easy to operate chemiluminescent sandwich enzyme immunoassay (CLEIA) for detecting staphylococcal enterotoxin C (SEC1). We selected two pairs of anti-SEC1 monoclonal antibodies (mAbs) (SEC1-G8 and SEC1-C4), and a chemiluminescent sandwich enzyme immunoassay (CLEIA) was constructed. This approach can detect SEC1 within a concentration spectrum of 3.2–4000 pg/mL, with the detection limit being 2.1 pg/mL. At three concentrations (3.2, 20, and 400 pg/mL), both the intra- and inter-assay coefficient variations were coming in at 6.31 % and 11.2 % respectively. No cross-reaction was noticed in the SEA, SEB, and SED tests. SEC1 was successfully detected by employing the CLEIA method in spiked matrices and commercial samples, and the average recovery rate ranges from 81.6 % to 108.1 %. Therefore, the highly sensitive, SEC1- specific, and easy-to-operate CLEIA could be a useful tool in the near future for quantifying SEC1 in public health and food safety.

Dimensional data directly reflects the growth rate of individual fish, an important economic trait of interest to fish researchers. Efficiently obtaining large-scale fish dimension data would be valuable for both selective breeding and production. To address this, our study proposes a custom dimension measurement method for fish using the YOLOv5-keypoint framework with multi-attention mechanisms. We optimized the YOLOv5 framework, incorporated the SimAM attention mechanism to achieve more accurate and faster fish detection, and added customizable landmarks to the network structure, enabling flexible configuration of the number and location of feature points in the training dataset. This method is applicable to various aquacultural species and other objects. We tested the effectiveness of the method using the economically important grass carp (Ctenopharyngodon idella). The proposed method outperforms pure YOLOv5, Faster R-CNN, and SSD in terms of precision and recall rates, achieving an impressive average precision of 0.9781. Notably, field trials confirmed the method's exceptional measurement accuracy, exceeding 97% compatibility with manual measurements, while demonstrating a real-time speed of 38 frames per second on the NVIDIA RTX A4000. This enables efficient and accurate large-scale surface dimension measurements of economic fish. To facilitate massive measurements in agricultural research, we have implemented this method as an online platform, called Mode-recognition Ruler (MrRuler, http://bioinfo.ihb.ac.cn/mrruler). The platform identifies objects in a single image at an average speed of 0.486 ​± ​0.005 ​s, based on a dataset of 10,000 images. MrRuler includes two preset carp models and allows users to upload training datasets for custom models of their targets of interest.

In this paper, we consider the estimators of distribution function and hazard rate for censored survival time. First, some properties and inequalities are established for linearly extended negative quadrant-dependent sequence as auxiliary results. Then by applying the properties and inequalities, we investigate the strong consistency and strong representation for the Kaplan–Meier estimator and hazard rate estimator with censored linearly extended negative quadrant-dependent data. Under some mild conditions, we derive that the rates of strong consistency are near [Formula: see text] and also obtain the strong representations with the remainder of order [Formula: see text]. The results established here extend and generalize the corresponding ones in recent literature.

As an effective computer-aided diagnostic tool, deep learning has been successfully applied to the classification of breast histopathological images. However, the performance of the deep model is data-driven, and it is difficult to obtain satisfied results when the number of histopathological images is small and labelling histopathological images is difficult. Moreover, in traditional deep learning methods, the representation of features is monotonous, which leads to the limitation of the classification performance of the model. This study proposes an auto-encoder reconstructed semi-supervised domain adaptation for a breast histopathological image classification algorithm. First, the model was pre-trained and transferred to extract high-level features of the sample images. Then, the encoding and decoding parts of the auto-encoder were used to reconstruct the feature representation learning and the sample feature reconstruction learning, respectively. This ensured that the useful information for the classification was purified and retained. At the same time, the domain discriminator was used to confuse the source and target domain features to enhance the learning ability of the model. Finally, the distribution difference of features at different depths of the auto-encoder was measured to minimize the discrepancy of feature distribution between domains, so as to complete the classification of histopathological images. Compared to the results of the comparative and ablation algorithms from the BreakHis to SNL datasets, the proposed method achieved the best results in terms of F1 score (93.40%), accuracy (95.24%), sensitivity (94.66%), and specificity (95.56%). The experimental results demonstrate that the proposed method achieves a remarkable classification performance.

Purpose As a global health concern, the diagnosis of obstructive sleep apnea hypopnea syndrome (OSAHS), characterized by partial reductions and complete pauses in ventilation, has garnered significant scientific and public attention. With the advancement of digital technology, the utilization of three-dimensional (3D) optical devices demonstrates unparalleled potential in diagnosing OSAHS. This study aimed to review the current literature to assess the accuracy of 3D optical devices in identifying the prevalence and severity of OSAHS. Methods A systematic literature search was conducted in the Web of Science, Scopus, PubMed/MEDLINE, and Cochrane Library databases for English studies published up to April 2024. Peer-reviewed researches assessing the diagnostic utility of 3D optical devices for OSAHS were included. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) guideline was employed to appraise the risk of bias. Results The search yielded 3216 results, with 10 articles meeting the inclusion criteria for this study. Selected studies utilized structured light scanners, stereophotogrammetry, and red, green, blue-depth (RGB-D) cameras. Stereophotogrammetry-based 3D optical devices exhibited promising potential in OSAHS prediction. Conclusions The utilization of 3D optical devices holds considerable promise for OSAHS diagnosis, offering potential improvements in accuracy, cost reduction, and time efficiency. However, further clinical data are essential to assist clinicians in the early detection of OSAHS using 3D optical devices.

GL-V9, a derivative of wogonin, has shown potent antitumor effects in various cancers, yet its impact on chronic myeloid leukemia (CML) remains unexplored. In this study, we found that GL-V9 significantly decreased the viability of CML cells. Annexin V/PI staining demonstrated that GL-V9 induced apoptosis in a concentration-dependent manner. The JC-1 assay indicated a significant reduction in mitochondrial membrane potential (ΔΨm) in cells treated with GL-V9. Additionally, GL-V9 altered reactive oxygen species (ROS) levels in CML cells. Through transcriptomic sequencing and Western blot analysis, we further revealed that GL-V9 activated the MAPK pathway. These results suggest that GL-V9 is a promising therapeutic candidate for CML.

Based on the elastic theory of porous media, embedded discrete fracture model and finite volume method, and considering the micro-seepage mechanism of shale gas, a fully coupled seepage-geomechanical model suitable for fractured shale gas reservoirs is established, the optimization method of refracturing timing is proposed, and the influencing factors of refracturing timing are analyzed based on the data from shale gas well in Fuling of Sichuan Basin. The results show that due to the depletion of formation pressure, the percentage of the maximum horizontal principal stress reversal area in the total area increases and then decreases with time. The closer the area is to the hydraulic fracture, the shorter the time for the peak of the stress reversal area percentage curve to appear, and the shorter the time for the final zero return (to the initial state). The optimum time of refracturing is affected by matrix permeability, initial stress difference and natural fracture approach angle. The larger the matrix permeability and initial stress difference is, the shorter the time for stress reversal area percentage curve to reach peak and return to the initial state, and the earlier the time to take refracturing measures. The larger the natural fracture approach angle is, the more difficult it is for stress reversal to occur near the fracture, and the earlier the optimum refracturing time is. The more likely the stress reversal occurs at the far end of the artificial fracture, the later the optimal time of refracturing is. Reservoirs with low matrix permeability have a rapid decrease in single well productivity. To ensure economic efficiency, measures such as shut-in or gas injection can be taken to restore the stress, and refracturing can be implemented in advance.

Electromagnetic launch (EML) systems with energy storage units in transient operating states are gradually being applied in modern ships, satellite launches, etc., power switching devices with higher voltage and switching frequency, Additionally, innovative topologies are being developed to enhance the electromagnetic performance of the EML systems. This inevitably leads to significant EMI issues. Therefore, this paper proposes a transient conducted EMI source modeling method for EML systems based on a multi-port equivalent circuit cascade model. Initially, a multi-port transient conducted EMI source model for supercapacitors is developed, taking into account the time-varying load characteristics of supercapacitors during charging and transient high-current discharge characteristics during discharging. Subsequently, a multi-port transient conducted EMI source model of the dual three-phase linear motor has been developed utilizing experimental measurement data. Leveraging the port-to-port cascade characteristics of various devices in the EML system, a dual three-phase dc-ac inverter multi-port conducted EMI model with high-frequency parasitic effects has been developed. A system-level modeling method based on the multi-port equivalent circuit cascade transient conducted EMI source modeling method is developed by cascading the multi-port equivalent circuit models of each functional component for the EML system. To evaluate the accuracy of this system-level modeling method, an experimental setup is constructed to assess transient conducted EM disturbances in a low-power EML system. The time-domain simulation results of the transient operating state are compared and analyzed with the actual operating conditions from the voltage, current, and energy perspectives, further validating the accuracy and efficacy of the EML system conducted EMI source modeling method based on a cascade of multi-port equivalent circuit models, as well as the transient conducted EM disturbances time-domain and frequency-domain characteristics.

This paper discusses the applicability conditions of the Physical Optics (PO) approximation and investigates its predictive power for far-field diffraction patterns of Reconfigurable Intelligent Surfaces (RISs) based on binary metasurfaces (BMSs). We compare the PO model with the approximation of socalled Reflection Locality (RL). Although these two approximations are conceptually different, in the case of BMSs, RL turns out to be a prerequisite of the applicability of the PO. If RL holds for such RISs, PO adequately predicts the diffraction pattern only in the case of large periods, which restricts the applicability of the PO to rather small deflection angles. Recently, it was shown that the RL approximation and the popular approximation of so-called angular stability for periodically non-uniform reflecting metasurfaces are equivalent. Therefore, we conclude that BMSs with angular stability can be successfully designed using the PO approximation if the required deflection angles are restricted. In the absence of angular stability, the accuracy of PO is very poor. This finding highlights the importance of considering both the angular stability and the electromagnetic dimensions in RISs designs.

In the field of remote sensing, change detection is a crucial study area. Deep learning has made significant strides in the study of remote sensing image change detection during the past few years. Deep learning techniques still have some drawbacks. The global context cannot be modeled by convolutional neural networks due to the receptive field's restrictions. When extracting visual characteristics, the neural network does not concentrate more on the change region, which results in poor distinction between change and no-change regions. To address these problems, we propose networks with large receptive fields (LRFs) and difference image enhancement. First, we design the LRF strategy. It employs a long kernel shape in one spatial dimension for obtaining a long range of relations. Keeping a narrow kernel size in the other spatial dimension can extract local context information while avoiding interference from irrelevant regions. To focus on the changing features, we design the image difference enhancement (IDE) method, which decreases the distance between invariant features and enlarges the distance between changing features. In addition, we design the cross-channel interaction (CNI) strategy, which models the relationship between feature map channels and extracts feature representations through local CNI. On the CDD, WHU-CD, and LEVIR-CD public datasets, we conducted comprehensive experiments. According to the experimental results, our proposed LRDE-Net performs better than other state-of-the-art change detection techniques, and the change regions are more precisely identified. It can better cope with seasonal changes, light intensity, and other pseudochange disturbances.

Abstract Background/Objective With the development of society, pulmonary fungal diseases, represented by pulmonary aspergillosis and pulmonary cryptococcosis, have become increasingly common. However, there is a lack of clear understanding regarding coinfection by these two types of fungi in immunocompetent individuals. Methods A retrospective study from 2014 to 2022 and a systematic literature review of original articles published in English were performed. Patients with pulmonary cryptococcosis complicated with pulmonary aspergillosis including 5 in the retrospective study and 6 in the systematic literature review. Result The diagnosis of concurrent pulmonary cryptococcosis and pulmonary aspergillosis in patients was confirmed through repeated biopsies or surgical resection. Pulmonary cryptococcosis is often diagnosed initially (6/11, 55%), while the diagnosis of pulmonary aspergillosis is established when the lesions become fixed or enlarged during treatment. Transbronchial lung biopsy (3/11, 27%), thoracoscopic lung biopsy (2/11, 18%), and percutaneous aspiration biopsy of the lung (1/11, 9%) were the main methods to confirm concurrent infection. Most patients were treated with voriconazole, resulting in a cure for the coinfection (6/11, 55%). Conclusion Pulmonary cryptococcosis complicated with pulmonary Aspergillus is an easily neglected mixed fungal infection. During the treatment of lesion enlargement in clinical cryptococcus, we need to watch out for Aspergillus infection.

The encapsulation of particular quality functions and predicates within temporal logic formulas markedly enhances the representation of detailed temporal characteristics within a system. During our preliminary investigations, we innovatively combined quality constraint functions and predicates with Possibility Linear Temporal Logic (PoLTL), yielding the conception of Fuzzy Linear Temporal Logic with Quality Constraints (QFLTL). This amalgamation results in a significant elevation of QFLTL’s expressivity relative to PoLTL, ensuring the preservation of informational integrity whilst achieving a synchronized, yet selectively inclined, and exact consolidation of path reachability specifics alongside property satisfaction evaluations. This treatise represents a significant contribution to the field by integrating quality constraint functions and predicates into Possibility Computation Tree Temporal Logic (PoCTL), thus giving rise to Fuzzy Computation Tree Temporal Logic with Quality Constraints (QFCTL). We provide a comprehensive definition of QFCTL’s syntax, conduct an in-depth analysis of its logical characteristics, outline a precise model checking algorithm for QFCTL, and perform a meticulous complexity assessment of said algorithm. It is illustrated by examples that PoCTL is a proper subset of QFCTL, and QFCTL has stronger expressive power than PoCTL and can characterize more refined temporal properties of the system. An in-depth exploration of the logical characteristics of QFCTL was carried out, showing its unique logical characteristics that are distinct from other temporal logic systems under the influence of quality constraints. In particular, the introduction of characteristic predicates effectively classifies the satisfaction of temporal formulas, making the logical framework of QFCTL more complete compared to the existing probabilistic temporal logic. Moreover, by enriching QFCTL with a quantitative characteristic predicate operator, we innovate, culminating in the development of an enhanced Fuzzy Computation Tree Temporal Logic with Quality Constraints (QFCTL*). The logical characteristics of QFCTL* are explored in detail. It is shown that with the support of quantitative feature predicates, QFCTL* can divide the satisfaction of temporal formulas more delicately than QFCTL. The decision theorems for the semantics of QFCTL* formulas containing quantitative feature predicates are given, and the decidability of QFCTL* is strictly proved. Through the bounded-depth search of GPKS, a model-checking algorithm of QFCTL* on GPKS is presented. The correctness of the algorithm is proved, and the complexity of the algorithm is analyzed. In order to prove the practical applications and strong expressive capabilities of QFCTL and QFCTL*, we present a model-checking example as empirical evidence for the effectiveness of the proposed model-checking algorithms. Through this example, we verify that, compared with the existing PoCTL, QFCTL and QFCTL* can avoid the loss of system path reachability information or system property satisfaction information, ensure the synchronization of the two types of information, and fuse these two types of information according to weight preferences. QFCTL and QFCTL* can also synthesize temporal formulas that characterize the subproperties of the system according to weight preferences. These application examples also verify that the QFCTL and QFCTL* model-checking algorithms proposed in this article are automatic and effective.

As an extension of quantitative temporal logic, uncertain temporal logic essentially describes the temporal behavior of uncertain and incomplete systems, thus better solving search and decision-making problems in such systems. Fuzzy linear temporal logic (FLTL) is a focal point in uncertain temporal logic research. However, there are evident shortcomings in the current research outcomes. First, in previous FLTL studies, the practice of obtaining path reachability and formula satisfaction values independently and subsequently selecting the smaller of the two as the satisfaction value metric led to information loss. Furthermore, this simplistic information fusion approach fails to reflect the varying importance of these two types of information to the requirements. Second, computing path reachability and temporal logic formula satisfaction values separately may result in a mismatch between the two pieces of information with respect to the same path segment. Thus, the primary challenge lies in accurately integrating the satisfaction values of temporal logic formulas with the path reachability of the segments that yields these satisfaction values, utilizing various reasonable information synthesis methods, to ensure synchronization between path reachability and formula satisfaction values without incurring information loss. Additionally, it is crucial to reflect the different preference requirements for these two types of information. Moreover, the temporal logic formula characterizes system properties, with its sub-formulas delineating distinct sub-properties. Consequently, considering the varying importance preferences of sub-formulas is also significant. To address these deficiencies, we introduced quality constraint operators into FLTL, resulting in quality-constrained fuzzy linear temporal logic (QFLTL). This incorporation enables the synchronization and comprehensive fusion of path-reachability information and formula satisfaction values within the final semantic metric, thereby resolving the issues related to information synchronization and loss. Furthermore, it can accommodate the differing preference requirements between the two types of information and sub-properties during the information synthesis process. We defined the syntax and semantics of QFLTL and examined its expressive power and properties. Notably, we investigated the decidability of logical decision problems in QFLTL, encompassing validity, satisfiability, and model-checking issues. We proposed corresponding solution algorithms and analyzed their complexities.

A self-designed full-diameter core experimental facility was used to evaluate the flow heterogeneity of bedding fractures at four radial directions under different closure pressures and injection rates, using full-diameter cores retaining original natural bedding fractures. The distribution morphology of bedding surface affects the conductivity of bedding fractures, and the flow capacity of bedding fractures in four radial directions varies greatly with the closure pressure and injection rate. The rougher the fracture surface, the greater the flow capacity varies with the closure pressure. For unsupported bedding fractures, the mean percentage error (MPE) of the conductivity in four radial directions increase gradually with the increase of the closure pressure. This phenomenon is especially prominent in deep rock samples. It is indicated that the flow heterogeneity of bedding fractures tends to increase with the closure pressure. When proppant is placed in the fracture, at a low closure pressure, due to the combined effects of self-support of rough fracture surface, proppant instability and uneven proppant placement, the flow heterogeneity is greater than that when proppant is not placed at the same closure pressure; however, with the increase of the closure pressure, the proppant becomes compact and stable, and the flow heterogeneity is mitigated gradually.

Abstract Background Hitherto, the bulk of diagnostic criteria regards Aspergillus-specific immunoglobulin E as a key item, and regard IgG as an auxiliary method in diagnose. Nevertheless, there is no conclusive study in summarize the performance of IgG and IgE diagnosing ABPA. Methods We conducted a systematic review to identify studies report results of IgE and IgG detection in diagnosing ABPA. QUADAS-2 tool was used to evaluate included studies, and we applied the HSROC model to calculate the pooled sensitivity and specificity. Deeks’ funnel was derived to evaluated the public bias of included studies, and Cochrane Q test and I 2 statistic were used to test the heterogeneity. Results Eleven studies were included in this study (1127 subjects and 215 for IgE and IgG). Deeks’s test for IgE and IgG were 0.10 and 0.19. The pooled sensitivity and specificity for IgE were 0.83 (95%CI: 0.77, 0.90) and 0.89 (0.83, 0.94), and for IgG were 0.93 (0.87, 0.97) and 0.73 (0.62,0.82), with P value

Objective: to (1) systematically review the chronic effect of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on maximal fat oxidation (MFO) in overweight and obese adults, and (2) explore MFO influencing factors and its dose-response relationships with HIIT and MICT. Methods: Studies using a between-group design involving overweight and obese adults and assessing the effect of HIIT and MICT on MFO were included. A meta-analysis on MFO indices was conducted, and the observed heterogeneities were explored through subgroup, regression, and sensitivity analyses. Results: Thirteen studies of moderate to high quality with a total of 519 overweight and obese subjects were included in this meta-analysis (HIIT, n = 136; MICT, n = 235; Control, n = 148). HIIT displayed a statistically significant favorable effect on MFO compared to no-training (MD = 0.07; 95%CI [0.03 to 0.11]; I2 = 0%). Likewise, MICT displayed a statistically significant favorable effect on MFO compared to no-training (MD = 0.10; 95%CI [0.06 to 0.15]; I2 = 95%). Subgroup and regression analyses revealed that exercise intensity (Fatmax vs. non-Fatmax; %VO2peak), exercise mode, BMI, and VO2peak all significantly moderated MICT on MFO. When analyzing studies that have directly compared HIIT and MCIT in obese people, it seems there is no difference in the MFO change (MD = 0.01; 95%CI [-0.02 to 0.04]; I2 = 64%). No publication bias was found in any of the above meta-analyses (Egger's test p > 0.05 for all). Conclusion: Both HIIT and MICT are effective in improving MFO in overweight and obese adults, and they have similar effects. MCIT with an intensity of 65–70% VO2peak, performed 3 times per week for 60 min per session, will optimize MFO increases in overweight and obese adults. Given the lack of studies examining the effect of HIIT on MFO in overweight and obese adults and the great diversity in the training protocols in the existing studies, we were unable to make sound recommendations for training.

Purpose: This study aimed to examine the short-term effects of SARS-CoV-2 infection and return to sport (RTS) on neuromuscular performance, body composition, and mental health in well-trained young kayakers. Methods: 17 vaccinated kayakers (8 male, 9 female) underwent body composition assessment, peak power output bench press (BP), and 40-s maximum repetition BP tests 23.9 ± 1.6 days before and 22.5 ± 1.6 days after a SARS-CoV-2 infection. A linear transducer was used to examine the BP performance. The perception of training load and mental health were quantified with Borg's CR-10 scale and the Hooper questionnaire before and after infection. The difference and relationship of variables were used Wilcoxon test, Student t-test, Pearson's, and Spearman's r correlation coefficients. Results: There was a significant increase in body mass, fat-free mass, and skeletal muscle mass, but no significant changes in body fat, fat mass, and all BP performance after infection (p

Abstract Background Periodontitis is the most common oral disease and is closely related to immune infiltration in the periodontal microenvironment and its poor prognosis is related to the complex immune response. The progression of periodontitis is closely related to necroptosis, but there is still no systematic study of long non-coding RNA (lncRNA) associated with necroptosis for diagnosis and treatment of periodontitis. Material and methods Transcriptome data and clinical data of periodontitis and healthy populations were obtained from the Gene Expression Omnibus (GEO) database, and necroptosis-related genes were obtained from previously published literature. FactoMineR package in R was used to perform principal component analysis (PCA) for obtaining the necroptosis-related lncRNAs. The core necroptosis-related lncRNAs were screened by the Linear Models for Microarray Data (limma) package in R, PCA principal component analysis and lasso algorithm. These lncRNAs were then used to construct a classifier for periodontitis with logistic regression. The receiver operating characteristic (ROC) curve was used to evaluate the sensitivity and specificity of the model. The CIBERSORT method and ssGSEA algorithm were used to estimate the immune infiltration and immune pathway activation of periodontitis. Spearman’s correlation analysis was used to further verify the correlation between core genes and periodontitis immune microenvironment. The expression level of core genes in human periodontal ligament cells (hPDLCs) was detected by RT-qPCR. Results A total of 10 core necroptosis-related lncRNAs (10-lncRNAs) were identified, including EPB41L4A-AS1, FAM30A, LINC01004, MALAT1, MIAT, OSER1-DT, PCOLCE-AS1, RNF144A-AS1, CARMN, and LINC00582. The classifier for periodontitis was successfully constructed. The Area Under the Curve (AUC) was 0.952, which suggested that the model had good predictive performance. The correlation analysis of 10-lncRNAs and periodontitis immune microenvironment showed that 10-lncRNAs had an impact on the immune infiltration of periodontitis. Notably, the RT-qPCR results showed that the expression level of the 10-lncRNAs obtained was consistent with the chip analysis results. Conclusions The 10-lncRNAs identified from the GEO dataset had a significant impact on the immune infiltration of periodontitis and the classifier based on 10-lncRNAs had good detection efficiency for periodontitis, which provided a new target for diagnosis and treatment of periodontitis.

The occurrence of corona discharge in ultra-high-voltage direct current transmission lines results in the generation of space charge, which significantly affects the nearby electromagnetic environment. To investigate the micro-physical mechanisms of discharge and provide better guidance for the calculation of the ground ion current density and total electric field, a method based on the theory of the transport of diluted species is proposed. This method enables the visualization and analysis of the movement process of space charge in air medium, as well as the calculation of the total electric field below the transmission lines. To validate the effectiveness of this algorithm, experimental tests of the total electric field are conducted on actual transmission lines. The experimental results demonstrate that the algorithm not only highlights the evident differences in the transient microscopic processes between positive and negative corona discharges but also accurately calculates the total electric field below the transmission lines. In addition, considering the weather conditions in the Chongqing region, relevant recommendations are provided under the influence of wind speed, aiming to offer protection guidelines for individuals engaged in activities near transmission lines.

In this paper, the event-triggered-based cluster-delay consensus control problem is investigated for leader-following nonlinear multi-agent systems (MASs). In control design, both state triggering in the agents’ network and constant time-delay in the leaders’ communication network are considered. Under the framework of Lyapunov function stability theory, the Lipschitz condition is used to overcome the influence caused by time-delay. In order to further effectively utilize data transmission resources, and reduce the communication load of the topology network between each agent, an event-triggered mechanism is established. Subsequently, a robust cluster consensus control strategy is proposed based on event-triggered mechanism, which can ensure all signals of the controlled system are bounded, and the tracking errors converge to zero. In addition, it can also effectively avoid the Zeno behavior. Finally, the effectiveness of the presented control method and theory is verified by a simulation example.

This systematic review investigated the job characteristics of National Collegiate Athletic Association (NCAA) strength and conditioning coaches (SCCs). Three databases were searched (Web of Science, EBSCO, and PubMed) until 12th January 2023. Eligible studies had to meet four criteria: (a) written in English, (b) published in a peer–reviewed journal, as a report on an official website, or a master/doctoral dissertation, (c) reported the demographic and job information of NCAA SCCs, and (d) complete data for at least one common question across two studies were available. Fifteen studies (n = 2,455 SCCs) were included. All studies adopted similar survey designs and questions, providing a basis for comparison. The results of this systematic review reveal that from 1989–2022, the age, race, and gender characteristics of SCCs were similar, lacking diversity, but academic degrees, majors, certifications, job titles, and salaries differed. This study provides valuable information for those looking to work in the NCAA as SCCs or those with existing roles to develop into more senior positions. Furthermore, This study will support employers in creating more informed job descriptors and employment strategies. Finally, based on our findings we propose a consolidated survey based on prior research to enable continuous and longitudinal investigations of SCCs working in NCAA sports.

It has become a consensus that large-scale hydraulic fracturing is adopted to achieve the stimulation of unconventional oil and gas reservoir. The complex fracture network formed by fracturing is closely related to the effect of reservoir stimulation, which has extremely complicated evolution process. Therefore, it is necessary to study the evolution law of fracture network in large-scale hydraulic fracturing of unconventional reservoirs. In this article, the geological engineering parameters of horizontal well H in shale gas reservoir in southern Sichuan are taken as an example, a three-dimensional fracture network expansion model is established based on the boundary element method and finite volume method, and the simulation of the complex fracture network in a whole well section is carried out to analyze the evolution law of reservoir fracture network under different geological and engineering parameters. The results show that the horizontal stress field distribution has a significant effect on fracture geometric form. Hydraulic fractures in reservoirs with larger horizontal stress difference have stronger directivity, while the horizontal wellbore tends to obtain better reservoir stimulation results when it is parallel to the minimum horizontal principal stress setting. The conjugated natural fracture developed in the reservoir inhibits the hydraulic expansion fractures in both directions. Although it increases the complexity of the fractures, it is not necessarily conducive to improving the reservoir stimulation effectiveness. The lower the strength of natural fracture is, the more complex the fracture geometric form becomes, and the smaller the stimulated reservoir volume is. Correspondingly, the higher the strength of natural fracture is, the simpler the fracture geometric form becomes, and the larger the stimulated reservoir volume is. Suitable fracturing construction displacement can not only contribute to form a more complex fracture distribution, but also help to obtain a larger stimulated reservoir volume. The optimal construction displacement ranges from 10 to 14 m3/min. Low viscosity fracturing fluids are suitable for the formation of long-narrow fractures and able to connect with the remote reservoir and form complex fracture networks. Lower viscosity fluids can be used to achieve better reservoir stimulation effectiveness when sand-carrying capacity is met.

BackgroundThe burden of cryptococcosis in mainland China is enormous. However, the in vitro characterization and molecular epidemiology in Guangdong, a key region with a high incidence of fungal infection in China, are not clear.MethodsFrom January 1, 2010, to March 31, 2019, clinical strains of Cryptococcus were collected from six medical centres in Guangdong. The clinical information and characteristics of the strains were analysed. Furthermore, molecular types were determined.ResultsA total of 84 strains were collected, mostly from male and young or middle-aged adult patients. Pulmonary and cerebral infections (82.1%) were most common. All strains were Cryptococcus neoformans, grew well at 37°C and had capsules around their cells. One melanin- and urea- and one melanin+ and urea- variants were found. Although most strains exhibited a low minimum inhibitory concentration (MIC) value for voriconazole (mean: 0.04 μg/mL) and posaconazole (mean: 0.12 μg/mL), the results for these isolates showed a high degree of variation in the MIC values of fluconazole and 5-fluorocytosine, and resistance was observed for 4 out of 6 drugs. A significant proportion of these strains had MIC values near the ECV values, particularly in the case of amphotericin B. The proportion of strains near the clinical breakpoints was as follows: fluconazole: 3.66%; voriconazole: 3.66%; itraconazole: 6.10%; posaconazole: 13.41%; amphotericin B: 84.15%; 5-fluorocytosine: 2.44%. These strains were highly homogeneous and were dominated by the Grubii variant (95.2%), VNI (94.0%), α mating (100%), and ST5 (89.3%) genotypes. Other rare types, including ST4, 31, 278, 7, 57 and 106, were also found.ConclusionPhenotypically variant and non-wild-type strains were found in Guangdong, and a significant proportion of these strains had MIC values near the ECV values towards the 6 antifungal drugs, and resistance was observed for 4 out of 6 drugs. The molecular type was highly homogeneous but compositionally diverse, with rare types found. Enhanced surveillance of the aetiology and evolution and continuous monitoring of antifungal susceptibility are needed to provide references for decision-making in the health sector and optimization of disease prevention and control.

Background: Evidence is limited regarding the relationship among physical activity, anxiety, and oral health in Chinese university students. This cross-sectional investigation aimed to assess the potential relationship between physical activity, anxiety, and oral health conditions among university students in China. Methods: An online questionnaire measuring physical activity, anxiety status, and oral health condition was completed by 1604 university students. The International Physical Activity Questionnaire Short Form (IPAQ-SF) and Generalized Anxiety Disorder-7 (GAD-7) were selected to evaluate physical activity and anxiety, respectively. Oral health condition was assessed through several self-reported variables, including self-reported toothache, gingival bleeding, frequency of tooth brushing, and use of dental floss. Multivariate logistic regression was performed to analyze the underlying relationship between outcome variables. The control variables included age, height, weight, gender, whether only one-child, education level, parental education level, smoking status, drinking habits, and length of sleep. Path analysis was conducted to disentangle the association between physical activity, anxiety, and oral health conditions. Results: Among 1604 university students, 666 (41.5 %) were males and 938 (58.5 %) were females, with an average of 21.9 ± 2.8 years. Only 833 (51.9 %) reported sufficient physical activity, while 684 (42.6 %) of the subjects displayed varying degrees of anxiety. Self-reported gingival bleeding was associated with insufficient physical activity (OR = 1.25; 95%CI: 1.02–1.55), anxiety (OR = 0.45; 95%CI: 0.27–0.74), frequency of tooth brushing (OR = 0.75; 95%CI: 0.60–0.95) and use of dental floss (OR = 0.75; 95%CI: 0.59–0.96), while toothache was not directly influenced by the physical activity and anxiety among university students. Anxiety markedly mediated the relationship between physical activity and oral health conditions. Conclusions: Anxiety was considered a factor associated with the level of physical activity, tooth brushing habits, and self-reported gingival bleeding among university students. Further investigations are required to elucidate whether oral health conditions could be enhanced through the improvement of anxiety and physical activity.

In this paper, an adaptive fuzzy fault-tolerant control (FTC) scheme is proposed for active seat suspension systems. The addressed system contains electromagnetic actuator faults. In addition, the constraints of the displacements of the car seat, active suspension, and wheel, their vertical vibration speeds and current intensity are included. In the control design, since the systems have dynamic characteristics of complexities and spring non-linearities, the fuzzy logic systems are utilized to approximate the unknown nonlinear dynamics. By the aid of Barrier Lyapunov functions and based on the adaptive backstepping recursive design algorithm, a novel adaptive fuzzy FTC scheme is formulated. When the electromagnetic actuator fails, the developed control scheme can guarantee that all the vertical vibration states are stable. Eventually, the effectiveness of the presented control method is offered to illustrate by a random road surface.

Ovarian growth is a critical phase of oogenesis that involves several events such as steroidogenesis, lipid deposition, and vitellogenesis. Although many studies have been conducted on fish ovarian growth and development, the molecular mechanisms that contribute to steroidogenesis and lipid deposition in common carp, the world's third largest freshwater aquaculture fish, remain elusive. In this study, transcriptome analyses were performed on ovaries from Yellow River carp at three different developmental stages: primary growth stage (PG), pre-vitellogenesis stage (PV), and mid-vitellogenesis stage (MV). A total of 22,511 genes were detected, and of these 122, 253, and 278 were differentially expressed genes (DEGs) when comparing PG to PV, PV to MV, and PG to MV stages, respectively. Gene ontology (GO) and KEGG enrichment analysis showed that the DEGs were mainly involved in steroidogenesis (e.g., fshr, cyp19a1a, hsd3b and foxl2b), lipid deposition (e.g., lpl, slc27a6, fabp4, acsl1a, agpat3, plpp3 and dgat1b), and vitellogenesis (e.g., lrp13, plb1, dgkaa and pik3r1). We also identified many signalling pathways involved in ovarian growth, including steroid hormone biosynthesis, the phospholipase D signalling pathway, glycerophospholipid metabolism, the Notch signalling pathway, the TGF-βsignalling pathway, and the Wnt signalling pathway. qPCR results of 9 representative genes related to steroidogenesis and lipid deposition verified the reliability of the generated RNA-seq data. Finally, a potential model for the formation of lipid droplets and yolks in the ovaries of common carp was proposed. Overall, the data from this study will contribute to further research on the molecular regulatory mechanisms of ovarian growth and development in common carp and other fish species.

It is key of “network fracturing” stimulation to correctly recognize the rock failure pattern during hydraulic fracturing treatment. In this paper, basic characteristics of the Carboniferous volcanic reservoirs in J230 area of Xinjiang oilfield are overviewed. Triaxial in-situ stresses of the formation are interpreted by conventional well-logging data, and the natural fissure characteristics are interpreted by imaging well logging information, and intersection of geometry relationship between hydraulic fracture and cross natural cracks is described on approaching angle. Current experimental achievements of hydraulic fracture penetration cross or extension along natural fissure are summarized, mechanics criterion under the different action manner are established for opening and shear failure of natural fractures. Taking Carboniferous volcanic reservoir of J230 area as an example, a hydraulic fracture propagation model is obtained by calculation results under the action of hydraulic-natural cracks synergy. It is shown that the approaching angle in the formation is mainly 50°–60°, shear sliding failure will be firstly induced along natural-hydraulic fracture interface and then natural fissure will open because of going net pressure. With further increase of the net fluid pressure, hydraulic fracture propagated along the natural fissure because of tangential failure and gradually turns to the direction of maximum horizontal principal stress, which is conducive to the formation of network fractures in stimulated reservoir treatment.

Abstract Owing to the renaissance of deep convolutional neural networks (CNN), salient object detection based on fully convolutional neural networks (FCNs) has attracted widespread attention. However, the scale variation of prominent objects, complex background features and fuzzy edges have historically been a great challenge to us. All these are closely associated with the utilization of multi‐level and multi‐scale features. At the same time, deep learning methods meet the challenges of computation and memory consumption in practice. To address these problems, the authors propose a different salient object detection method based on residuals learning and dense fusion learning framework. The proposed network is named Residual Dense Collaborative Network (RDCNet). First of all, the authors design a multi‐layer residual learning (MRL) module to extract salient object features in more detail, getting the utmost out of the object's multi‐scale and multi‐level information. Then, on the basis of the vigoroso stage‐wise convolution feature, the authors put forward the dilated convolution module (DCM) to acquire a rough global saliency map. Finally, the final accurate saliency detection map is obtained through dense cooperation learning (DCL), and the remaining learning is also used to improve gradually, so as to achieve high compactness and high‐efficiency results. Experimental results show that this method is the most advanced method for five widely used datasets (DUTS‐TE, HKU‐IS, PASCAL‐S, ECSSD, DUT‐OMRON) without any pre‐processing and post‐processing. Especially on the ECSSD dataset, the F‐measure of RDCNet achieves 95.2%.

A previously unknown Nocardia species was isolated from the lung tissue and bronchoalveolar lavage fluid (BALF) of a 58-year-old woman with bronchiectasis and recurrent pneumonia. This Nocardia (GZ2020T), which grew readily in Columbia blood agar and could induce pneumonia in a mouse model, represents a novel Nocardia species, and its closest known relatives are Nocardia anaemiae NBRC 100462T, Nocardia pseudovaccinii NBRC 100343T and Nocardia vinacea NBRC 16497T. However, unlike all previously known species, GZ2020T is the first genus of Nocardia spp. that is not susceptible to multiple drugs but does show susceptibility to linezolid and moxifloxacin, and thus, GZ2020T potentially represents a substantial health threat to patients with bronchiectasis and immunocompromised individuals. Although the original pathogen source and method of spreading remain uncertain, a mode of transmission from the environment to humans could exist. Vigilance with respect to its spread in the population and the transmission of antibiotic resistance genes in the environment should be maintained.

Under complex conditions, the vertical, lateral and longitudinal dynamics of vehicles have obvious coupling and interaction. This paper aims to provide a suitable driver cab and a vehicle model for the study of vehicle coupling dynamic performance. In modeling the cab and body kinetic equation, two shock absorbers are considered in the front axle suspension system. In addition, the vertical, roll and pitch motion of the diver cab, vehicle body, the vertical and roll behavior of three wheel axles, the pitch angles of the left and right balancing pole on rear suspension, and roll angle the of each tire are considered. Finally, based on the above coupled motion characteristics, a diver cab and a vehicle model for three-axles heavy-duty vehicle with 26 degrees of freedom (DOF) are proposed.

In recent years, since the unique advantages in automotive structures, the vehicle active suspension systems have received widespread attentions. A good active suspension system can reduce the vibration and improve the overall performance of the vehicle. Therefore, the design of the controller for the active suspension system to perform autonomous adjustment plays a vital role in vehicle comfort and safety. For the active suspension of the seven-DOF sport utility vehicle (SUV) model, this paper takes the vehicle body acceleration, tire dynamic load and suspension dynamic travel as the indicators to evaluate the performance, and the proportional-integral-derivative (PID) controller is designed to improve the performance of the vehicle active suspension system. Based on the software of MATLAB/Simulink and Carsim, a closed-loop co-simulation model diagram is established, which includes a PID controller module. Meanwhile, the random road input model and the whole vehicle model are constructed in Carsim. Finally, at the speeds of 70, 90, and 120 km/h, the active suspension system under the designed PID controller is simulated and compared with the passive suspension system. The simulation results show that the active suspension system based on PID controller can effectively improve the overall performance of the vehicle, and then the comfort and safety of the vehicle can be further enhanced.

Abstract U-Net has become baseline standard in the medical image segmentation tasks, but it has limitations in explicitly modeling long-term dependencies. Transformer has the ability to capture long-term relevance through its internal self-attention. However, Transformer is committed to modeling the correlation of all elements, but its awareness of local foreground information is not significant. Since medical images are often presented as regional blocks, local information is equally important. In this paper, we propose the GPA-TUNet by considering local and global information synthetically. Specifically, we propose a new attention mechanism to highlight local foreground information, called group parallel axial attention (GPA). Furthermore, we effectively combine GPA with Transformer in encoder part of model. It can not only highlight the foreground information of samples, but also reduce the negative influence of background information on the segmentation results. Meanwhile, we introduced the sMLP block to improve the global modeling capability of network. Sparse connectivity and weight sharing are well achieved by applying it. Extensive experiments on public datasets confirm the excellent performance of our proposed GPA-TUNet. In particular, on Synapse and ACDC datasets, mean DSC(%) reached 80.37% and 90.37% respectively, mean HD95(mm) reached 20.55 and 1.23 respectively.

The aim of this study was to determine the optimal velocity loss (VL) threshold that maximises the post activation potentiation (PAP) stimulus for achieving larger and more consistent performance gains in track and field athletes. Twenty-two athletes from athletics participated in four back squat PAP tests with four different VL threshold (5%, 10%, 15% and 20% VL) at an intensity of 85%1RM. Countermovement jump (CMJ) height, power, and momentum were assessed before, and 10 s, 4, 8, 12, 16 minutes after the PAP condition. Repetitions of the squat in all the PAP conditions were also recorded. Only the 5% VL condition produced significant improvements in height (ES = 0.73, P = 0.038), peak power output (ES = 0.73, P = 0.038) and momentum (ES = 0.72, P = 0.041) of CMJ, and these changes appeared 8 minutes after the condition. The total number of repetitions during the 5% VL condition was significantly lower than that observed in the 15% (P = 0.003) and 20% VL (P < 0.001) trials. The results from this study indicate that 5%VL during the 2 sets preconditioning squat at 85%1RM was optimal for eliciting PAP in a CMJ exercise, and resulted in significant increases at the 8-min recovery period. The same squat condition also had the least number of repetitions. However, considering the efficiency in practice, athletes can also choose the rest time of 4-min, which can also achieve similar results.

Artificial Intelligence (AI) is driving advancements across various fields by simulating and enhancing human intelligence. In Natural Language Processing (NLP), transformer models like the Kerformer, a linear transformer based on a kernel approach, have garnered success. However, traditional attention mechanisms in these models have quadratic calculation costs linked to input sequence lengths, hampering efficiency in tasks with extended orders. To tackle this, Kerformer introduces a nonlinear reweighting mechanism, transforming maximum attention into feature-based dot product attention. By exploiting the non-negativity and non-linear weighting traits of softmax computation, separate non-negativity operations for Query(Q) and Key(K) computations are performed. The inclusion of the SE Block further enhances model performance. Kerformer significantly reduces attention matrix time complexity from O(N2) to O(N), with N representing sequence length. This transformation results in remarkable efficiency and scalability gains, especially for prolonged tasks. Experimental results demonstrate Kerformer's superiority in terms of time and memory consumption, yielding higher average accuracy (83.39%) in NLP and vision tasks. In tasks with long sequences, Kerformer achieves an average accuracy of 58.94% and exhibits superior efficiency and convergence speed in visual tasks. This model thus offers a promising solution to the limitations posed by conventional attention mechanisms in handling lengthy tasks.

This study investigated the grouped and individualized load-velocity profile (GLVP vs. ILVP) in Bulgarian split squat using Smith machine and free weight. Seventy five recreational male lifters completed two incremental loading tests of Bulgarian split squat. Mean velocity was measured by a linear-position transducer (GymAware). Linear regression equation was applied to construct the GLVP and ILVP. The agreement of predicted %1RM and measured %1RM was assessed by a combination of intraclass correlation coefficient (ICC), coefficient of variation (CV), standard error of measurement (SEM) and Bland-Altman analysis. Acceptable validity was defined as ICC > 0.75, CV ≤ 10% and p ≥ 0.05 (a paired Wilcoxon signed-rank test). A very high level of inverse load-velocity relationships were demonstrated in Bulgarian split squat (r = − 0.92) with free weights and a Smith machine. ILVP (ICC ≥ 0.98, CV ≤ 8.73%, p ≥ 0.56) was valid enough to predict the %1RM, but GLVP of both limbs revealed large CVs in free weights (CV: 15.4%,15.63%) and a Smith machine (CV: 11.24%, 12.25%). Cross-validation between the actual %1RM and predicted %1RM using free weights and a Smith machine ILVP was not acceptable (p ≤ 0.03, CV ≥ 14.07%). A very high level of inverse relationship were observed between %1RM and MV in Bulgarian split squat using free weights and a Smith machine, indicating individualized load velocity properties, and the ILVP showed high between-devices variability in both scenarios. Using velocity as a measure of loading intensity in Bulgarian split squat needs to consider the individualized load velocity properties, and difference between free weights and a Smith machine.

This paper makes a survey about the recent development of optimal control based on adaptive dynamic programming (ADP). First of all, based on DP algorithm and reinforcement learning (RL) algorithm, the origin and development of the optimization idea and its application in the control field are introduced. The second part introduces achievements in the optimal control direction, then we classify and summarize the research results of optimization method, constraint problem, structure design in control algorithm and practical engineering process based on optimal control. Finally, the possible future research topics are discussed. Through a comprehensive and complete investigation of its application in many existing fields, this survey fully demonstrates that the optimal control algorithms via ADP with critic-actor neural network (NN) structure, which also have a broad application prospect, and some developed optimal control design algorithms have been applied to practical engineering fields.

Global oil and gas consumption continues to rise and new strategies are required to meet the growing demand. Carbonate gas reservoirs are an important natural gas resource that are often accompanied by water intrusion during the development process. The efficient development of such reservoirs has therefore been extensively studied and met with difficulty. This paper summarizes the basic geological and water invasion characteristics of water-bearing carbonate gas reservoirs and correlates the two. A method for identifying water invasion types by production dynamics is introduced. The variation curve of the production water to gas ratio is shown to correspond with the reservoir geological characteristics. Typical development methods and the advantages/disadvantages of different water control techniques are summarized. The findings are used to propose a full-cycle water control plan for water-bearing carbonate gas reservoirs, and the development strategies of “early preparation, early discovery, and early treatment” and “re-analyze, re-assess, and re-adjust” are implemented to organically combine water control, drainage, and water blocking methods. The results provide a reference for formulating efficient and scientific development plans of water-bearing carbonate gas reservoirs.

Abstract Background Grass carp are an important farmed fish in China that are infected by many pathogens, especially grass carp reovirus (GCRV). Notably, grass carp showed age-dependent susceptibility to GCRV; that is, grass carp not older than one year were sensitive to GCRV, while those over three years old were resistant to this virus. However, the underlying mechanism remains unclear. Herein, whole genome-wide DNA methylation and gene expression variations between susceptible five-month-old (FMO) and resistant three-year-old (TYO) grass carp were investigated aiming to uncover potential epigenetic mechanisms. Results Colorimetric quantification revealed that the global methylation level in TYO fish was higher than that in FMO fish. Whole-genome bisulfite sequencing (WGBS) of the two groups revealed 6214 differentially methylated regions (DMRs) and 4052 differentially methylated genes (DMGs), with most DMRs and DMGs showing hypermethylation patterns in TYO fish. Correlation analysis revealed that DNA hypomethylation in promoter regions and DNA hypermethylation in gene body regions were associated with gene expression. Enrichment analysis revealed that promoter hypo-DMGs in TYO fish were significantly enriched in typical immune response pathways, whereas gene body hyper-DMGs in TYO fish were significantly enriched in terms related to RNA transcription, biosynthesis, and energy production. RNA-seq analysis of the corresponding samples indicated that most of the genes in the above terms were upregulated in TYO fish. Moreover, gene function analysis revealed that the two genes involved in energy metabolism displayed antiviral effects. Conclusions Collectively, these results revealed genome-wide variations in DNA methylation between grass carp of different ages. DNA methylation and gene expression variations in genes involved in immune response, biosynthesis, and energy production may contribute to age-dependent susceptibility to GCRV in grass carp. Our results provide important information for disease-resistant breeding programs for grass carp and may also benefit research on age-dependent diseases in humans.

The first fractured shale gas well of China was constructed in 2010. After 10 years of development, China has become the second country that possesses the core technology of shale gas development around the world, realized the shale gas fracturing techniques from zero to one and from lagging to partially leading, and constructed the fracturing theory and technology system suitable for middle–shallow marine shale gas exploitation. In order to provide beneficial guidance for the efficient exploitation of shale gas in China in the future, this paper comprehensively reviews development history and status of domestic fundamental theories, optimized design methods, fluid systems, tools and technologies of shale gas fracturing and summarizes the research results in fundamental theories and optimized design methods, such as fracturing sweet-spot cognition, fracture network propagation simulation and control, rock hydration and flowback control, and SRV (stimulated reservoir volume) evaluation and characterization. The development and application of slick-water fracturing fluid system and new fracturing fluid with little or no water is discussed. The development and independent research & development level of multi-stage fracturing tools are evaluated, including drillable composite plug, soluble plug, large-diameter plug and casing cementing sleeve. The implementation situations of field technologies and processes are illustrated, including the early conventional multi-stage multi-cluster fracturing and the current “dense cluster” fracturing and temporary plugging fracturing. Based on this, the current challenges to domestic shale gas fracturing technologies are analyzed systematically, and the development direction of related technologies is forecast. In conclusion, it is necessary for China to continuously research the fracturing theories, technologies and methods suitable for domestic deep and ultra-deep marine shale gas, terrestrial shale gas and transitional shale gas to facilitate the future efficient development of shale gas in China.

Image-based identification and quantification of different types of spermatogenic cells is of great importance, not only for reproductive studies but also for genetic breeding. Here, we have developed antibodies against spermatogenesis-related proteins in zebrafish (Danio rerio), including Ddx4, Piwil1, Sycp3, and Pcna, and a high-throughput method for immunofluorescence analysis of zebrafish testicular sections. By immunofluorescence analysis of zebrafish testes, our results demonstrate that the expression of Ddx4 decreases progressively during spermatogenesis, Piwil1 is strongly expressed in type A spermatogonia and moderately expressed in type B spermatogonia, and Sycp3 has distinct expression patterns in different subtypes of spermatocytes. Additionally, we observed polar expression of Sycp3 and Pcna in primary spermatocytes at the leptotene stage. By a triple staining of Ddx4, Sycp3, and Pcna, different types/subtypes of spermatogenic cells were easily characterized. We further demonstrated the practicality of our antibodies in other fish species, including Chinese rare minnow (Gobiocypris rarus), common carp (Cyprinus carpio), blunt snout bream (Megalobrama amblycephala), rice field eel (Monopterus albus) and grass carp (Ctenopharyngodon idella). Finally, we proposed an integrated criterion for identifying different types/subtypes of spermatogenic cells in zebrafish and other fishes using this high-throughput immunofluorescence approach based on these antibodies. Therefore, our study provides a simple, practical, and efficient tool for the study of spermatogenesis in fish species.

In tight gas reservoirs, the major flow channels are composed of micro/nanopores in which the rarefaction effect is prominent and the traditional Darcy law is not appropriate for gas flow. By combining the Maxwell first-order slip boundary condition and Navier–Stokes equations, a three-dimensional (3D) analysis of compressible gas slip flow in a microtube was presented, and the flux rate and pressure variation in the flow direction were discussed. Subsequently, by superimposing the Knudsen diffusion, a gas flux formula applicable to a larger Knudsen number was further proposed and satisfactorily verified by two groups of published experimental data in microtubes or microchannels in the membrane. The results indicate that slip flow and Knudsen diffusion make an important contribution to the total gas flow in the microtube, and their weight increases with an increase in the Knudsen number. By substituting the gas flux formula into Darcy’s law for compressible gas, a new apparent permeability model for tight gas reservoirs was proposed, in which the slippage effect and Knudsen diffusion were synthetically considered. The results indicate that the apparent permeability of tight reservoirs strongly depends on the reservoir pressure and pore-throat radius, and an underestimation value may be predicted by the previously published models. This study provides a case study for evaluating these apparent permeability models, which remains a challenging task in the laboratory.

Abstract Crushing ratio and fracture conductivity are two key indicators for proppant evaluation. The most common way to evaluate these two indicators is physical testing, but physical testing is costly and time‐consuming, and the results are unstable. Therefore, a method for calculating proppant‐crushing ratio and fracture conductivity is proposed to replace repetitive physical experiments. However, in past attempts, only mathematical models using the same particle size have been established, while the particle‐size distribution in actual proppant arrangement is within a certain numerical range. Therefore, in order to establish a mathematical model more consistent with the actual situation of proppant arrangement, firstly, the Monte Carlo method was used to simulate proppant particles arranged with different particle sizes, and then a mathematical model was established describing the force of proppant particles. Secondly, according to the sparse, ill‐conditioned, and asymmetric characteristics of the coefficient matrix, an improved singular value decomposition method is proposed to improve the accuracy and efficiency of calculation. Finally, the crushing ratio and fracture conductivity of proppant were calculated through the new model in this paper. It was found that the results calculated by the new model in this paper are closer to actual test results.

Field production data indicate that the shale gas production rate decreases sharply after a few years of the first fracking. Feasible enhanced gas recovery (EGR) approaches are very necessary to be investigated. In this study, we compared re-fracturing with a huff-n-puff gas injection scheme in a shale gas reservoir for EGR. A fully compositional simulation approach coupled with a dual porosity and dual permeability model is used. The gas production performances by using different fracturing fluids (i.e., slickwater and supercritical CO2) are evaluated. The effects of huff-n-puff parameters and matrix permeability on the gas production rate and carbon sequestration are investigated. The results show that using a re-fracturing approach yields a better recovery performance than the huff-n-puff gas injection method. Re-fracturing using supercritical CO2 performs better than using slickwater because the former can create complex three-dimensional fracture networks. Huff-n-puff CO2 injection can enhance the gas recovery effectively in ultra-tight formations. In a relatively high permeable formation, viscous flow instead of adsorption-desorption isotherms becomes the primary mass transfer mechanisms, resulting in a lower gas recovery. Both the re-fracturing treatment and huff-n-puff CO2 injection are profitable from a long-term cash flowback perspective.

IntroductionSARS-CoV-2 has ravaged the world and undergone multiple mutations during the course of the COVID-19 pandemic. On 7 April 2022, an epidemic caused by SARS-CoV-2 Omicron (BA.2) variant broke out in Guangzhou, China, one of the largest transportation and logistical hubs of the country.MethodsTo fast curtained the Omicron epidemic, based on the routine surveillance on the risk population of SARS-CoV-2 infection, we identify key places of the epidemic and implement enhanced control measures against Omicron.ResultsTransmission characteristics of the Omicron variant were analyzed for 273 confirmed cases, and key places involved in this epidemic were fully presented. The median incubation time and the generation time were 3 days, and the reproduction number Rt was sharply increased with a peak of 4.20 within 2 days. We tried an all-out effort to tackle the epidemic in key places, and the proportion of confirmed cases increased from 61.17% at Stage 2 to 88.89% at Stage 4. Through delimited risk area management, 99 cases were found, and the cases were isolated in advance for 2.61 ± 2.76 days in a lockdown zone, 0.44 ± 1.08 days in a controlled zone, and 0.27 ± 0.62 days in a precautionary zone. People assigned with yellow code accounted for 30.32% (84/277) of confirmed COVID-19 cases, and 83.33% of them were detected positive over 3 days since code assignment. For the districts outside the epicenter, the implementation duration of NPIs was much shorter compared with the Delta epidemic last year.ConclusionBy blocking out transmission risks and adjusting measures to local epidemic conditions through the all-out effort to tackle the epidemic in key places, by delimiting risk area management, and by conducting health code management of the at-risk population, the Omicron epidemic could be contained quickly.