Search

Glycosylation is an important post-modification reaction in plant secondary metabolism, and contributes to structural diversity of bioactive natural products. In plants, glycosylation is usually catalyzed by UDP-glycosyltransferases. Flavonoid 2′-O-glycosides are rare glycosides. However, no UGTs have been reported, thus far, to specifically catalyze 2′-O-glycosylation of flavonoids. In this work, UGT71AP2 was identified from the medicinal plant Scutellaria baicalensis as the first flavonoid 2′-O-glycosyltransferase. It could preferentially transfer a glycosyl moiety to 2′-hydroxy of at least nine flavonoids to yield six new compounds. Some of the 2′-O-glycosides showed noticeable inhibitory activities against cyclooxygenase 2. The crystal structure of UGT71AP2 (2.15 Å) was solved, and mechanisms of its regio-selectivity was interpreted by pKa calculations, molecular docking, MD simulation, MM/GBSA binding free energy, QM/MM, and hydrogen‒deuterium exchange mass spectrometry analysis. Through structure-guided rational design, we obtained the L138T/V179D/M180T mutant with remarkably enhanced regio-selectivity (the ratio of 7-O-glycosylation byproducts decreased from 48% to 4%) and catalytic efficiency of 2′-O-glycosylation (kcat/Km, 0.23 L/(s·μmol), 12-fold higher than the native). Moreover, UGT71AP2 also possesses moderate UDP-dependent de-glycosylation activity, and is a dual function glycosyltransferase. This work provides an efficient biocatalyst and sets a good example for protein engineering to optimize enzyme catalytic features through rational design.

Abstract Background Associations between metabolic status and metabolic changes with the risk of cardiovascular outcomes have been reported. However, the role of genetic susceptibility underlying these associations remains unexplored. We aimed to examine how metabolic status, metabolic transitions, and genetic susceptibility collectively impact cardiovascular outcomes and all-cause mortality across diverse body mass index (BMI) categories. Methods In our analysis of the UK Biobank, we included a total of 481,576 participants (mean age: 56.55; male: 45.9%) at baseline. Metabolically healthy (MH) status was defined by the presence of

Objective Focal cervical kyphotic deformity (FCK) without neurologic compression is not uncommon in patients with cervical spondylotic myelopathy (CSM) who underwent anterior cervical decompression and fusion (ACDF) surgery. It remains unclear whether FCK at non‐responsible levels needs to be treated simultaneously. This study aims to investigate whether FCK at non‐responsible levels is the prognostic factor for CSM and elucidate the surgical indication for FCK. Methods Patients with CSM who underwent ACDF between January 2016 and April 2021 were included. Patients were divided into two groups according to the presence of FCK and two classifications according to global cervical sagittal alignment. Clinical outcomes were compared using Japanese Orthopaedic Association (JOA) scores and recovery rate (RR) of neurologic function. Univariate and multivariate analysis based on RR assessed the relationship between various possible prognostic factors and clinical outcomes. The receiver operating characteristic curve (ROC) was used to determine the optimal cutoff value of the focal Cobb angle to predict poor clinical outcomes. Results A total of 94 patients were included, 41 with FCK and 53 without. Overall, the RR of neurologic function was significantly lower in the FCK than in the non‐FCK group. Further analysis showed that the RR difference between the two groups was only observed in hypo‐lordosis classification (kyphotic and sigmoid alignment), but not in the lordosis classification. Multivariate analysis showed that the preoperative focal Cobb angle in the FCK level (OR = 0.42; 95% CI = 0.18–0.97) was independently associated with clinical outcomes in the hypo‐lordosis classification. The optimal cutoff point of the preoperative focal kyphotic Cobb angle was calculated at 4.05°. Conclusion For CSM with hypo‐lordosis, FCK was a risk factor for poor postoperative outcomes. Surgeons may consider treating the FCK simultaneously if the focal kyphotic Cobb angle of FCK is greater than 4.05° and is accompanied by cervical global kyphotic or sigmoid deformity.

ObjectiveTo retrospectively analyze the characteristics of newly diagnosed marginal zone lymphoma (MZL) patients, evaluate the efficacy of different treatment regimens, and explore prognostic factors in the era of immunotherapy.MethodsWe reviewed the clinical data of newly diagnosed MZL patients treated at the Department of Hematology, The First Hospital of Jilin University, from October 2013 to October 2023. Survival differences between groups were analyzed using the log-rank test, and prognostic factors were identified.ResultsA total of 265 newly diagnosed MZL patients were included, with a median age of 59 years (range 22-90). The most common pathological type was mucosa-associated lymphoid tissue (MALT) lymphoma, accounting for 66.0% of cases. Among the 147 MZL patients included in the efficacy analysis, the median follow-up was 43.4 months. Both the median progression-free survival (PFS) and overall survival (OS) were not reached. The 5-year PFS and OS rates were 76.0% and 86.6%, respectively. Patients who achieved complete response (CR) after induction therapy had significantly better PFS (P=0.0045), OS (P

Background: From 1990 to 2019, low back pain (LBP) was the leading cause of years lived with disability (YLDs) in China. However, the change patterns of LBP and its risk factors in China remain unclear. Methods: Data from the Global Burden of Disease Study 2019 were used. We used the join-point regression model and age-period-cohort analysis to evaluate the time trends of attributable risk factors on the burden of LBP. Results: In 2019, the risk factors included in this analysis accounted for 4.36 million YLDs of LBP, representing 42.2% of all YLDs of LBP in China, with 2.86 million due to occupational ergonomic factors, 1.74 million due to smoking, and 0.46 million due to high body mass index (BMI). The age-standardized YLD rates of LBP showed downward trends during 1990–2019, while there was a faster decline between 1990 and 1994. The curves of local drifts, which reflected the average annual percentage change across age groups, showed an increasing trend with age for high BMI and smoking, and a downward trend for occupational ergonomic factors. The YLD rates for LBP increased dramatically with age for high BMI, while it reached a peak at 40–60 years old for occupational ergonomic factors, and 65–80 years old for smoking. The period and cohort rate ratios of LBP YLD decreased in the past 3 decades for occupational ergonomic factors and smoking, while increased for high BMI. Conclusions: Our results provided strong evidence that there were diverse changing patterns for different risk factors, highlighting the need for risk-specific strategies. The translational potential of this article: China has the largest senior population and the fastest aging population in the world. Given that LBP typically occurs in the senior population, there would be an increasing LBP burden on China's health system. This suggests that effective strategies for LBP prevention should be strictly implemented in China, particularly in the senior population, which is of crucial translational potential.

Abstract Background Inflammatory bowel disease (IBD), which includes Crohn’s disease (CD) and ulcerative colitis (UC), has been associated with several cancer risks in observational studies, but the observed associations have been inconsistent and may face the bias of confounding and reverse causality. The potential causal relationships between IBD and the risk of cancers remain largely unclear. Methods We performed genome-wide linkage disequilibrium score regression (LDSC), standard two-sample Mendelian randomization (MR), and colocalization analyses using summary genome-wide association study (GWAS) data across East Asian and European populations to evaluate the causal relationships between IBD and cancers. Sensitivity analyses for the MR approach were additionally performed to explore the stability of the results. Results There were no significant genetic correlations between IBD, CD, or UC and cancers (all P values > 0.05) in East Asian or European populations. According to the main MR analysis, no significant causal relationship was observed between IBD and cancers in the East Asian population. There were significant associations between CD and ovarian cancer (odds ratio [OR] = 0.898, 95% CI = 0.844–0.955) and between UC and nonmelanoma skin cancer (OR = 1.002, 95% CI = 1.000–1.004, P = 0.019) in the European population. The multivariable MR analysis did not find any of the above significant associations. There was no shared causal variant to prove the associations of IBD, CD, or UC with cancers in East Asian or European populations using colocalization analysis. Conclusions We did not provide robust genetic evidence of causal associations between IBD and cancer risk. Exposure to IBD might not independently contribute to the risk of cancers, and the increased risk of cancers observed in observational studies might be attributed to factors accompanying the diagnosis of IBD.

Monolayer and few-layer CoPS3 have been successfully synthesized via an Au-assisted exfoliation technique, with their transport properties subsequently investigated by conductive atomic force microscopy. Rectification effects can be observed in CoPS3 nanosheets due to the Schottky junction formation at the Au/CoPS3 interface, especially in configurations comprising two or more layer flakes. The distinct transport properties between monolayer and few-layer samples demonstrate that the charge transport behavior in the vertical direction is associated with the van der Waals gap. The calculated electron affinity for CoPS3 is about 4.84 eV, as revealed by the thermionic emission model. The results obtained contribute to the knowledge base concerning the transport characteristics of ultrathin MPX3, facilitating further exploration of the transport behavior of these materials and their potential applications in novel electronic devices.

Abstract Objectives To investigate and characterize epileptic seizures and electrophysiological features of familial cortical myoclonic tremor with epilepsy (FCMTE) type 1 patients in a large Chinese cohort. Methods We systematically evaluated 125 FCMTEtype 1 patients carrying the pentanucleotide (TTTCA) repeat expansion in the SAMD12 gene in China. Results Among the 28 probands, epileptic seizures (96.4%, 27/28) were the most common reason for an initial clinic visit. Ninety‐seven (77.6%, 97/125) patients had experienced seizures. The seizures onset age was 36.5 ± 9.0 years, which was 6.9 years later than cortical tremors. The seizures were largely rare (

To reduce the difficulty and enhance the enthusiasm of private-owned electric vehicles (EVs) to participate in frequency regulation ancillary service market (FRASM), a decision aid model (DAM) is proposed. This paper presents three options for EV participating in FRASM, i. e., the base mode (BM), unidirectional charging mode (UCM), and bidirectional charging/discharging mode (BCDM), based on a reasonable simplification of users' participating willingness. In BM, individual EVs will not be involved in FRASM, and DAM will assist users to set the optimal charging schemes based on travel plans under the time-of-use (TOU) price. UCM and BCDM are two modes in which EVs can take part in FRASM. DAM can assist EV users to create their quotation plan, which includes hourly upper and lower reserve capabilities and regulation market mileage prices. In UCM and BCDM, the difference is that only the charging rate can be adjusted in the UCM, and the EVs in BCDM can not only charge but also discharge if necessary. DAM can estimate the expected revenue of all three modes, and EV users can make the final decision based on their preferences. Simulation results indicate that all the three modes of DAM can reduce the cost, while BCDM can get the maximum expected revenue.

Abstract U-10 wt.% Zr (U-10Zr) metallic fuel is the leading candidate for next-generation sodium-cooled fast reactors. Porosity is one of the most important factors that impacts the performance of U-10Zr metallic fuel. The pores generated by the fission gas accumulation can lead to changes in thermal conductivity, fuel swelling, Fuel-Cladding Chemical Interaction (FCCI) and Fuel-Cladding Mechanical Interaction (FCMI). Therefore, it is crucial to accurately segment and analyze porosity to understand the U-10Zr fuel system to design future fast reactors. To address the above issues, we introduce a workflow to process and analyze multi-source Scanning Electron Microscope (SEM) image data. Moreover, an encoder-decoder-based, deep fully convolutional network is proposed to segment pores accurately by integrating the residual unit and the densely-connected units. Two SEM 250 × field of view image datasets with different formats are utilized to evaluate the new proposed model’s performance. Sufficient comparison results demonstrate that our method quantitatively outperforms two popular deep fully convolutional networks. Furthermore, we conducted experiments on the third SEM 2500 × field of view image dataset, and the transfer learning results show the potential capability to transfer the knowledge from low-magnification images to high-magnification images. Finally, we use a pre-trained network to predict the pores of SEM images in the whole cross-sectional image and obtain quantitative porosity analysis. Our findings will guide the SEM microscopy data collection efficiently, provide a mechanistic understanding of the U-10Zr fuel system and bridge the gap between advanced characterization to fuel system design.

The safety management of laboratories is of utmost importance in the construction and management of university laboratories. Abnormal behaviors such as smoking, incorrect wearing of personal protective equipment (PPE) like lab coats, hats, masks, and gloves pose significant safety hazards. In this paper, in order to improve the level of laboratory safety management and effectively provide an alert in the case of unsafe behaviors, video analysis technology is employed to achieve abnormal behavior recognition and monitoring through steps such as human key point detection, posture estimation, and behavior recognition. Firstly, the human pose estimation algorithm YOLO is used for human detection, followed by the extraction of human key points after segmentation. Finally, spatiotemporal graph convolution is used for feature detection and classification of abnormal behaviors. The experimental results show that the accuracy of abnormal behavior detection and recognition based on human key points reaches over 85%, which is of great significance for safety management and behavior warning in university laboratories, and thus, improves the efficiency and level of laboratory safety management.

The rapid development of remote sensing technology has provided new sources of data for marine rescue and has made it possible to find and track survivors. Due to the requirement of tracking multiple survivors at the same time, multi-object tracking (MOT) has become the key subtask of marine rescue. However, there exists a significant gap between fine-grained objects in realistic marine rescue remote sensing data and the fine-grained object tracking capability of existing MOT technologies, which mainly focuses on coarse-grained object scenarios and fails to track fine-grained instances. Such a gap limits the practical application of MOT in realistic marine rescue remote sensing data, especially when rescue forces are limited. Given the promising fine-grained classification performance of recent text-guided methods, we delve into leveraging labels and attributes to narrow the gap between MOT and fine-grained maritime rescue. We propose a text-guided multi-class multi-object tracking (TG-MCMOT) method. To handle the problem raised by fine-grained classes, we design a multi-modal encoder by aligning external textual information with visual inputs. We use decoding information at different levels, simultaneously predicting the category, location, and identity embedding features of objects. Meanwhile, to improve the performance of small object detection, we also develop a data augmentation pipeline to generate pseudo-near-infrared images based on RGB images. Extensive experiments demonstrate that our TG-MCMOT not only performs well on typical metrics in the maritime rescue task (SeaDronesSee dataset), but it also effectively tracks open-set categories on the BURST dataset. Specifically, on the SeaDronesSee dataset, the Higher Order Tracking Accuracy (HOTA) reached a score of 58.8, and on the BURST test dataset, the HOTA score for the unknown class improved by 16.07 points.

Trace minerals are essential for biological processes, including enzyme function, immune response, and hormone synthesis. The study assessed the effects of different dietary trace minerals on the gut health, microbiota composition, and immune function of cats. Eighteen adult British Shorthair cats were divided into three groups receiving inorganic trace minerals (ITM), a 50/50 mix of inorganic and organic trace minerals (ITM + OTM), or organic trace minerals (OTM) for 28 days. The OTM showed enhanced immune capacities, reduced intestinal barrier function, and lower inflammation condition. The OTM altered gut microbiota diversity, with a lower Simpson index and higher Shannon index (p < 0.05). Specifically, the abundance of Bacteroidota, Lachnospiraceae, and Prevotella in the OTM group were higher than the ITM group (p < 0.05). Metabolomic analysis identified 504 differential metabolites between the OTM and ITM groups (p < 0.05, VIP-pred-OPLS-DA > 1), affecting pathways related to steroid hormone biosynthesis and glycerophospholipid metabolism (p < 0.05, VIP-pred-OPLS-DA > 2). Additionally, there was a significant correlation between intestinal microbiota and differential metabolites. To conclude, dietary OTM can modulate the gut metabolite and microbiota composition, enhance immune and intestinal barrier function, and mitigate inflammation in cats, highlighting the benefit of using OTM in feline diet to promote the intestinal and overall health.

This study addresses the challenge of efficiently peeling pineapples, which have a distinct elliptical form, thick skin, and small eyes that are difficult to detect with conventional automated methods. This results in significant flesh waste. To improve the process, we developed an integrated system combining an enhanced BlendMask method, termed SAAF-BlendMask, and a Pose Correction Planning (PCP) method. SAAF-BlendMask improves the detection of small pineapple eyes, while PCP ensures accurate posture adjustment for precise path planning. The system uses 3D vision and deep learning technologies, achieving an average precision (AP) of 73.04% and a small object precision (APs) of 62.54% in eye detection, with a path planning success rate reaching 99%. The fully automated electromechanical system was tested on 110 real pineapples, demonstrating a reduction in flesh waste by 11.7% compared to traditional methods. This study highlights the potential of advanced machine vision and robotics in enhancing the efficiency and precision of food processing.

Abstract Objective Recent studies have found a high prevalence of hepatitis B virus (HBV) infection in patients with non‐Hodgkin's lymphoma (NHL), especially B‐cell non‐Hodgkin's lymphoma (B‐NHL). However, most studies did not classify it and analyze the correlation between HBV and its various subtypes. Methods The authors retrospectively analyzed 1424 patients with lymphoma. Differences in the prevalence of HBV infection in patients with different pathological types of lymphoma were analyzed. The clinical characteristics, progression‐free survival (PFS), and overall survival (OS) of HBV‐positive and negative B‐NHL subtypes were compared according to HBV infection. Results The HBV infection rate in NHL patients was 7.65%, which was higher than that in HL patients (2.59%, p

The trajectory of China's PPP market since 2014, characterized by rapid expansion and a high failure rate, now plunges into a state of limbo and uncertainty. Through a quantitative analysis of failed PPP projects in China from 2014 to 2020, this study investigates the impact of local government institutional quality, private capital business environment, local economic development, and local fiscal affordability on the development and implementation of PPP projects. The findings reveal that larger government size is associated with a higher likelihood of PPP project failure, while a favorable private capital business environment can mitigate the failure rate of local PPP projects. Furthermore, empirical results demonstrate a positive relationship between local fiscal affordability and the success rate of PPP projects. The analysis underscores the significant influence of the institutional environment on the effectiveness of PPP projects and provides policy recommendations for local governments to enhance the business environment and other key factors contributing to the resilience of PPP projects.

IntroductionEarly detection of leaf diseases is necessary to control the spread of plant diseases, and one of the important steps is the segmentation of leaf and disease images. The uneven light and leaf overlap in complex situations make segmentation of leaves and diseases quite difficult. Moreover, the significant differences in ratios of leaf and disease pixels results in a challenge in identifying diseases.MethodsTo solve the above issues, the residual attention mechanism combined with atrous spatial pyramid pooling and weight compression loss of UNet is proposed, which is named RAAWC-UNet. Firstly, weights compression loss is a method that introduces a modulation factor in front of the cross-entropy loss, aiming at solving the problem of the imbalance between foreground and background pixels. Secondly, the residual network and the convolutional block attention module are combined to form Res_CBAM. It can accurately localize pixels at the edge of the disease and alleviate the vanishing of gradient and semantic information from downsampling. Finally, in the last layer of downsampling, the atrous spatial pyramid pooling is used instead of two convolutions to solve the problem of insufficient spatial context information.ResultsThe experimental results show that the proposed RAAWC-UNet increases the intersection over union in leaf and disease segmentation by 1.91% and 5.61%, and the pixel accuracy of disease by 4.65% compared with UNet.DiscussionThe effectiveness of the proposed method was further verified by the better results in comparison with deep learning methods with similar network architectures.

Abstract Osteoporosis is a prevalent bone disorder characterized by low bone mineral density (BMD) and deteriorated bone microarchitecture, leading to an increased risk of fractures. Vitamin D (VD), an essential nutrient for skeletal health, plays a vital role in maintaining bone homeostasis. The biological effects of VD are primarily mediated through the vitamin D receptor (VDR), a nuclear receptor that regulates the transcription of target genes involved in calcium and phosphate metabolism, bone mineralization, and bone remodeling. In this review article, we conduct a thorough literature search of the PubMed and EMBASE databases, spanning from January 2000 to September 2023. Utilizing the keywords “vitamin D,” “vitamin D receptor,” “osteoporosis,” and “therapy,” we aim to provide an exhaustive overview of the role of the VD/VDR system in osteoporosis pathogenesis, highlighting the most recent findings in this field. We explore the molecular mechanisms underlying VDR’s effects on bone cells, including osteoblasts and osteoclasts, and discuss the impact of VDR polymorphisms on BMD and fracture risk. Additionally, we examine the interplay between VDR and other factors, such as hormonal regulation, genetic variants, and epigenetic modifications, that contribute to osteoporosis susceptibility. The therapeutic implications of targeting the VDR pathway for osteoporosis management are also discussed. By bringing together these diverse aspects, this review enhances our understanding of the VD/VDR system’s critical role in the pathogenesis of osteoporosis and highlights its significance as a potential therapeutic target.

A new species of freshwater mussel belonging to the genus Pseudocuneopsis, namely Pseudocuneopsis wuana sp. nov., is diagnosed and described from Guangxi Province, China. This paper provides a detailed shell morphological description, soft-body anatomical characteristics, and partial sequences of mitochondrial COI as DNA barcode data for the novel species. The new species can be distinguished from its congeners (Pseudocuneopsis sichuanensis, P. yangshuoensis, and P. capitata) by shell shape, beak position, and surface sculpture. Phylogenetic analyses based on the mitochondrial COI gene reveal that Pseudocuneopsis wuana sp. nov. forms a sister group with P. yangshuoensis and exhibits an interspecific genetic distance of 5.1%. Therefore, we provide robust morphological and molecular evidence to support the validity of this new species.

The production management of lactating sows is a crucial aspect of pig farm operations, as their health directly impacts the farm’s production efficiency. The feeding behavior of lactating sows can reflect their health and welfare status, and monitoring this behavior is essential for precise feeding and management. To address the issues of time-consuming and labor-intensive manual inspection of lactating sows’ feeding behavior and the reliance on breeders’ experience, we propose a method based on the improved YOLO (You Only Look Once) v5s algorithm and image segmentation for detecting the feeding behavior of lactating sows. Based on the YOLOv5s algorithm, the SE (Squeeze-and-Excitation) attention module was added to enhance the algorithm’s performance and reduce the probability of incorrect detection. Additionally, the loss function was replaced by WIoU (Weighted Intersection over Union) to accelerate the model’s convergence speed and improve detection accuracy. The improved YOLOv5s-C3SE-WIoU model is designed to recognize pre-feeding postures and feed trough conditions by detecting images of lactating sows. Compared to the original YOLOv5s, the improved model achieves an 8.9% increase in mAP@0.5 and a 4.7% increase in mAP@0.5 to 0.95. This improvement satisfies the requirements for excellent detection performance, making it suitable for deployment in large-scale pig farms. From the model detection results, the trough remnant image within the detection rectangle was extracted. This image was further processed using image processing techniques to achieve trough remnant image segmentation and infer the remnant amount. Based on the detection model and residue inference method, video data of lactating sows’ feeding behavior were processed to derive the relationship between feeding behavior, standing time, and residue amount. Using a standing duration of 2 s and a leftover-feed proportion threshold of 2% achieves the highest accuracy, enabling the identification of abnormal feeding behavior. We analyzed the pre-feeding postures and residual feed amounts of abnormal and normal groups of lactating sows. Our findings indicated that standing time was significantly lower and residual feed amount was higher in the abnormal groups compared to the normal groups. By combining standing time and residual feed amount information, accurate detection of the feeding status of lactating sows can be realized. This approach facilitates the accurate detection of abnormal feeding behaviors of lactating sows in large-scale pig farm environments.

Few-shot learning (FSL) is designed to equip models with the capability to quickly adapt to new, unseen domains in open-world scenarios. However, there is a notable discrepancy between the multitude of new concepts encountered in the open world and the limited scale of existing FSL studies, which focus predominantly on a small number of novel classes. This limitation hinders the practical implementation of FSL in real-world situations. To address this issue, we introduce a novel problem called Few-Shot Learning with Many Novel Classes (FSL-MNC), which expands the number of novel classes more than 500 times compared to traditional FSL settings. This new challenge presents two main difficulties: increased computational load during meta-training and reduced classification accuracy due to the larger number of classes during meta-testing. To tackle these problems, we introduce the Simple Hierarchy Pipeline (SHA-Pipeline). In response to the inefficiency of traditional Episode Meta-Learning (EML) protocols, we redesign a more efficient meta-training strategy to manage the increased number of novel classes. Moreover, to distinguish distinct semantic features across a broad array of novel classes, we effectively reconstruct and utilize class hierarchy information during meta-testing. Our experiments demonstrate that the SHA-Pipeline substantially outperforms both the ProtoNet baseline and current leading alternatives across various numbers of novel classes.

Bismuth sodium titanate (Bi0.5Na0.5TiO3, BNT) ceramics are expected to replace traditional lead-based materials because of their excellent ferroelectric and piezoelectric characteristics, and they are widely used in the industrial, military, and medical fields. However, BNT ceramics have a low breakdown field strength, which leads to unsatisfactory energy storage performance. In this work, 0.85Bi0.5Na0.5TiO3-0.15LaFeO3 ceramics are prepared by the traditional high-temperature solid-phase reaction method, and their energy storage performance is greatly enhanced by improving the process of buried sintering. The results show that the buried sintering method can inhibit the formation of oxygen vacancy, reduce the volatilization of Bi2O3, and greatly improve the breakdown field strength of the ceramics so that the energy storage performance can be significantly enhanced. The breakdown field strength increases from 210 kV/cm to 310 kV/cm, and the energy storage density increases from 1.759 J/cm3 to 4.923 J/cm3. In addition, the energy storage density and energy storage efficiency of these ceramics have good frequency stability and temperature stability. In this study, the excellent energy storage performance of the ceramics prepared by the buried sintering method provides an effective idea for the design of lead-free ferroelectric ceramics with high energy storage performance and greatly expands its application field.

Probiotics demonstrated effectiveness in modulating oral microbiota and improving oral health in humans and rodents. However, its effects and applications on the oral microbiota of cats remain underexplored. Twelve healthy cats were randomly assigned to a control group (CON) and a composite probiotic group (CPG) for a 42-day trial. The CPG diet included additional supplementation of Bifidobacterium animalis subsp. lactis HN019, Lactobacillus acidophilus NCFM, and Lactobacillus casei LC-11, each at approximately 1 × 1010 CFU/kg. On days 0 and 42, microbial samples were collected from the gingiva, tooth surfaces, and tongue of all cats for 16S rRNA gene sequencing. Bacteroidetes, Firmicutes, and Proteobacteria were the dominant phyla across all oral sites. The CPG treatment enriched seven genera, such as Moraxella, Actinomyces, and Frederiksenia in the gingiva. Meanwhile, Bergeyella and Streptococcus were enriched on the tooth surfaces, while Bergeyella, Flavobacterium, and Luteimonas were enriched on the tongue. Furthermore, the composite probiotic effectively suppressed eight genera, such as Bacteroides, Desulfovibrio, and Filifactor in the gingiva of CPG cats, as well as Helcococcus, Lentimicrobium, and Campylobacter on tooth surfaces, and Porphyromonas, Treponema, and Fusibacter on the tongue. These findings suggest that the composite probiotic used in this study modulates the feline oral microbiota by supporting beneficial or commensal bacteria and inhibiting oral pathogens, demonstrating potential to improve oral health in cats.

Separating overlapped nuclei is a significant challenge in histopathology image analysis. Recently published approaches have achieved promising overall performance on nuclei segmentation; however, their performance on separating overlapped nuclei is limited. To address this issue, we propose a novel multitask learning network with a bending loss regularizer to separate overlapped nuclei accurately. The newly proposed multitask learning architecture enhances generalization by learning shared representation from the following three tasks: instance segmentation, nuclei distance map prediction, and overlapped nuclei distance map prediction. The proposed bending loss defines high penalties to concave contour points with large curvatures, and small penalties are applied to convex contour points with small curvatures. Minimizing the bending loss avoids generating contours that encompass multiple nuclei. In addition, two new quantitative metrics, the Aggregated Jaccard Index of overlapped nuclei (AJIO) and the accuracy of overlapped nuclei (ACCO), have been designed to evaluate overlapped nuclei segmentation. We validate the proposed approach on the CoNSeP and MoNuSegv1 data sets using the following seven quantitative metrics: Aggregate Jaccard Index, Dice, Segmentation Quality, Recognition Quality, Panoptic Quality, AJIO, and ACCO. Extensive experiments demonstrate that the proposed Bend-Net outperforms eight state-of-the-art approaches.

The intestinal microbiome changes with age, influencing the host’s health and immune status. Saccharomyces cerevisiae (S. cerevisiae) positively affects intestinal function in humans and animals, but its effects on gut health and the microbiota profile in aged dogs have not been thoroughly investigated. Twenty aged Labrador Retrievers were divided into two groups: a control group (CON) and a S. cerevisiae group (SC). The experiment lasted for 42 days, with assessments of their intestinal barrier function, inflammatory factors, antioxidant markers, and fecal microbiome composition. The results showed that dietary S. cerevisiae reduced the levels of TNF-α, IL-6, and IL-1β in the serum (p < 0.05). In the SC group, plasma superoxide dismutase and glutathione peroxidase activities increased, while the level of malondialdehyde significantly decreased (p < 0.05). Additionally, dietary S. cerevisiae lowered the serum zonulin and lipopolysaccharide (LPS) levels (p < 0.05) and inhibited fecal ammonia production (p < 0.05). Furthermore, the microbiota profile showed that dietary S. cerevisiae decreased the abundance of Firmicutes but increased the Chao index, the abundance of Bacteroidetes, and the proportion of Bacteroidetes to Firmicutes (p < 0.05). To conclude, dietary S. cerevisiae can regulate the gut’s microbial structure and gut health, which may contribute to the overall health of companion animals as they age.

Observational studies revealed changes in Immunoglobulin G (IgG) N-glycosylation during the aging process. However, it lacks causal insights and remains unclear in which direction causal relationships exist. The two-sample bidirectional Mendelian randomization (MR) design was adopted to explore causal associations between IgG N-glycans and the senescence-associated secretory phenotype (SASP). Inverse variance weighted (IVW) and Wald ratio methods were used as the main analyses, supplemented by sensitivity analyses. Forward MR analyses revealed causal associations between the glycan peak (GP) and SASP, including GP6 (odds ratio [OR] = 0.428, 95% confidence interval [CI] = 0.189–0.969) and GP17 (OR = 0.709, 95%CI = 0.504–0.995) with growth/differentiation factor 15 (GDF15), GP19 with an advanced glycosylation end-product-specific receptor (RAGE) (OR = 2.142, 95% CI = 1.384–3.316), and GP15 with matrix metalloproteinase 2 (MMP2) (OR = 1.136, 95% CI =1.008–1.282). The reverse MR indicated that genetic liability to RAGE was associated with increased levels of GP17 (OR = 1.125, 95% CI = 1.003–1.261) and GP24 (OR = 1.222, 95% CI = 1.046–1.428), while pulmonary and activation-regulated chemokines (PARC) exhibited causal associations with GP10 (OR = 1.269, 95% CI = 1.048–1.537) and GP15 (OR = 1.297, 95% CI = 1.072–1.570). The findings provided suggested evidence on the bidirectional causality between IgG N-glycans and SASP, which might reveal potential regulatory mechanisms.

ObjectivesThe paper aims to solves the limitations of the Goldstein body force method in a hydrodynamic simulation of a ducted propeller. MethodsAn analysis of the reason for the distortion of the duct hydrodynamic simulation is carried out based on the wing theory, and a correction method based on the mass flow and body force distribution model is proposed. The RANS method is then used to study the simulation accuracy of two kinds of improved body force method. ResultsThe results show that the average relative error of the total thrust coefficient of the two improved body force methods under open water conditions is about 5%. The average relative error of the resultant forward force of the two improved volume force methods behind the underwater vehicle are 1.8% and 11.6% respectively. ConclusionsThe simulation accuracy of a ducted propeller based on the improved body force method in open water and behind an underwater vehicle is greatly improved compared with the traditional method. The proposed method can accurately simulate the hydrodynamic performance of a ducted propeller, laying the foundation for the efficient dynamic maneuverability simulation of underwater vehicles.

Abstract Background The protective effect of a higher ideal cardiovascular health (CVH) score on cardiovascular diseases (CVDs) and mortality is well recognized. However, little is known regarding the length of favorable CVH status associated with CVDs and mortality. This study aimed to examined whether the duration of better (ideal or intermediate) CVH is associated with risk of developing CVDs and mortality. Methods This prospective cohort study used data from 83,536 individuals from 2006 to 2020 who were enrolled in the Kailuan Study. The CVH scores of individuals were assessed at visits 1, 2, 3, and 4, respectively. The years spent in better CVH were estimated for each individual as the number of examination cycles (0–4) in which the participant was in that CVH score ≥ 8 multiplied by 2 (the mean year interval of each visit). The primary outcomes are CVD events and all-cause mortality. Results After a median follow-up period of 7.48 years, 5486 (7.07%) cases of incident CVD events and 7669 (9.18%) deaths occurred. Compared with participants in “ ≤ 4 years” group, those who maintained for > 4 years had less likely to develop adverse outcomes (CVD events: hazard ratio (HR): 0.60, 95% confidence interval (CI 0.56–0.63; all-cause mortality: HR: 0.77, 95% CI 0.74–0.81). The number of years spent in better CVH was nonlinearly correlated with CVD events or mortality (all Ps for nonlinear

CO2 blasting has been identified as a potent method for enhancing the permeability of coal seams and improving gas drainage efficiency. This study is focused on elucidating the deformation and fracture mechanisms of coal and rock during CO2 blasting and on identifying the precursor characteristics of these processes. To this end, a CO2 blasting-induced coal rock fracture pressure model and a gas pressure distribution model were developed. The research utilized a self-developed CO2 blasting test platform along with a non-contact full-strain field measurement analysis system. Briquette samples were subjected to CO2 blasting tests under controlled experimental conditions, which included an axial pressure of 1.0 MPa and variable gas pressures of 0.5, 1.0, and 1.5 MPa. This methodology enabled the capture of the principal strain field on the surface of the samples. The Gray Level Co-occurrence Matrix (GLCM) was employed to extract and analyze the grayscale and texture features of the strain cloud maps, facilitating a quantitative assessment of their evolution. The aim was to pinpoint the precursor characteristics associated with coal rock cracking and crack propagation. The results revealed that: (1) During the cracking and subsequent propagation of samples, the strain field's grayscale histogram underwent a transformation from a "broad and low" to a "narrow and high" configuration, with a consistent increase in peak frequency. Specifically, at 3 ms, a primary crack was observed in the sample, evidenced by a grayscale peak frequency of 0.0846. By 9 ms, as the crack propagated, the grayscale peak frequency escalated to 0.1626. (2) The texture feature parameters experienced their initial abrupt change at 3ms. Correlation with the gas pressure distribution model indicated that this was the crack initiation moment in the sample. (3) A secondary abrupt shift in the texture feature parameters occurred at 9ms, in conjunction with experimental phenomena, was identified as the crack propagation phase. Monitoring the grayscale and texture features of the principal strain field on the coal rock surface proved effective in recognizing the precursor characteristics of crack initiation and propagation. This research has the potential to reduce blasting costs in coal mines, optimize blasting effects, and provided theoretical guidance for enhancing gas extraction efficiency from deep and low permeability coal seams.

Marginal zone lymphoma (MZL) is the second most common subtype of inert B-cell non-Hodgkin’s lymphoma, accounting for 5–15% of non-Hodgkin’s lymphoma cases. Patients with MZL have a long survival period, with a median survival of >10 years, and patients treated with a combination of anti-CD20 monoclonal antibody can achieve an overall effective rate of 81%. However, 20% of patients with MZL show relapse or experience disease progression within 2 years, with a median survival of only 3–5 years. Currently, the treatment options for patients with relapsed/refractory (R/R) MZL are limited, underscoring the pressing need for novel therapeutic drugs. The advent of novel anti-CD20 monoclonal antibodies, small molecule kinase inhibitors, immunomodulators, and other therapeutic strategies has ushered in a new era in the treatment of R/R MZL. Our objective is to summarize the existing treatment strategies, including immunotherapy and the emergent targeted therapies, and to evaluate their effectiveness and safety in the management of R/R MZL. By doing so, we aim to provide a clear understanding of the therapeutic landscape for R/R MZL, and to guide future research directions toward improving the prognosis and quality of life for patients afflicted with this challenging disease.

ObjectiveThe development of diffuse large B-cell lymphoma (DLBCL) is closely related to the host infection status. China is a highly endemic area for hepatitis B virus (HBV) infection. It is not clear whether HBV infection has a consistent effect on the prognostic implications of patients with DLBCL in different treatment settings.Materials and methodsWe conducted a cohort study of 692 patients with DLBCL receiving three or more cycles of treatment with a CHOP or R-CHOP regimen from the First Hospital of Jilin University between July 2011 and July 2022. The patients were divided into two groups based on their hepatitis B surface antigen (HBsAg) status: HBsAg-positive (n = 84, 12.1%) and HBsAg-negative (n = 608, 87.9%) groups. Tumor specimens from 180 patients with primary DLBCL were collected for next-generation sequencing (NGS).ResultsThe HBsAg-positive group had more frequent abnormal liver function (P = 0.003), hypoalbuminemia (P < 0.001), incidence of > 2 extranodal organs (P = 0.011), and spleen involvement (P < 0.001) than the HBsAg-negative group. HBsAg-positive patients had lower complete response (CR) and overall response rates (ORR) rates (all the p values < 0.05), in either the CHOP group or R-CHOP group. Among patients receiving R-CHOP, the rates of disease progression within 12 and 24 months were higher in the HBsAg-positive group than in the HBsAg-negative group (P=0.018, P=0.029). However, no significant difference in disease progression was observed between HBsAg-positive and HBsAg-negative patients in the CHOP group(P > 0.05). HBsAg positivity (OS: HR [95% CI] = 2.511 [1.214-5.192], P = 0.013) was only associated with poorer OS in the CHOP group. Whereas in the R-CHOP group, HBsAg positivity was associated with both poorer OS and PFS (OS: HR [95% CI] = 1.672 [1.050-2.665], P = 0.030; PFS: HR [95% CI] = 1.536 [1.013-2.331], P = 0.043). Additionally, HBsAg-positive patients with DLBCL also had a higher prevalence of mutations in MYC, ATM, PTPN6, and epigenetically regulated genes.ConclusionThese findings suggest that HBsAg-positive DLBCL patients may represent a distinct subgroup with a poorer prognosis. The standard therapies may be insufficient and new therapeutic strategies should be developed based on a better understanding of the underlying mechanisms of chemoresistance.

The recent discovery of infinite-layer nickel oxide superconductors has highlighted the importance of first-principles simulations. We predict an infinite-layer bismuth oxide superconductor BaBiO2, which is isostructural to NdNiO2. In this work, electronic structure, lattice dynamics, and electron–phonon interaction are studied, with special attention paid to the influence of spin–orbit coupling (SOC) on the above-mentioned quantities. Our calculations show that the structure will be dynamically stable under pressure and induce superconductivity, whether SOC is considered or not. In addition, SOC will significantly enhance the electron–phonon coupling (EPC), resulting in an increase in EPC constant λ from 0.43 to 0.73. We further find that the Fermi surface nesting is partially responsible for its superconductivity. A strong SOC changes the Fermi surface and enhances the nesting, and the EPC becomes stronger. Our results propose a bismuth-based superconductor, demonstrating the importance of SOC for its superconductivity and providing clues for further experimental synthesis.

Information cascade prediction is a crucial task in social network analysis. However, previous research has only focused on the impact of social relationships on cascade information diffusion, while ignoring the differences caused by the characteristics of cascade information itself, which limits the performance of prediction results. We propose a novel cascade information diffusion prediction model (Topic-HGAT). Firstly, we extract features from different topic features to enhance the learned cascade information representation. To better implement this method, we use hypergraphs to better characterize cascade information and dynamically learn multiple diffusion sub-hypergraphs according to the time process; secondly, we introduce cross-attention mechanisms to learn each other's feature representations from the perspectives of both user representation and cascade representation, thereby achieving deep fusion of the two features. This solves the problem of poor feature fusion effect caused by simply calculating self-attention on learned user representation and cascade representation in previous studies; finally, we conduct comparative experiments on four real datasets, including Twitter and Douban. Experimental results show that the proposed Topic-HGAT model achieves the highest improvements of 2.91% and 1.59% on Hits@100 and MAP@100 indicators, respectively, compared to other 8 baseline models, verifying the rationality and effectiveness of the proposed Topic-HGAT model.

Abstract Background Observational studies demonstrated a bidirectional association between type 2 diabetes (T2D) and hypertension, whereas Mendelian randomization (MR) analyses supported the causality from T2D to hypertension but not causal from hypertension to T2D. We previously found that IgG N-glycosylation is associated with both T2D and hypertension, and thus IgG N-glycosylation might link the causality between them. Methods We carried out a genome-wide association study (GWAS) to identify IgG N-glycosylation-quantitative-trait loci (QTLs) integrating GWAS for T2D and hypertension and then performed bidirectional univariable and multivariable MR analyses to infer the causal association among them. The inverse-variance-weighted (IVW) analysis was performed as the primary analysis, followed by some sensitivity analyses to explore the stability of the results. Results Six putatively causal IgG N-glycans for T2D and four for hypertension were identified in the IVW method. Genetically predicted T2D increased the risk of hypertension (odds ratio [OR] = 1.177, 95% confidence interval (95% CI) = 1.037–1.338, P = 0.012) and vice versa (OR = 1.391, 95% CI = 1.081–1.790, P = 0.010). Multivariable MR showed that T2D remained at risk effect with hypertension ([OR] = 1.229, 95% CI = 1.140–1.325, P = 7.817 × 10–8) after conditioning on T2D-related IgG-glycans. Conversely, hypertension was associated with higher T2D risk (OR = 1.287, 95% CI = 1.107–1.497, P = 0.001) after adjusting for related IgG-glycans. No evidence of horizontal pleiotropy was observed, as MR‒Egger regression provided P values for intercept > 0.05. Conclusion Our study validated the mutual causality between T2D and hypertension from the perspective of IgG N-glycosylation, further validating the “common soil” hypothesis underlying the pathogenesis of T2D and hypertension.

Background: Immunoglobulin G (IgG) N-glycosylation is considered a potential biomarker for aging and various pathological conditions. However, whether these changes in IgG N-glycosylation are a consequence or a contributor to the aging process remains unclear. This study aims to investigate the causality between IgG N-glycosylation and aging using Mendelian randomization (MR) analysis. Methods: We utilized genetic variants associated with IgG N-glycosylation traits, the frailty index (FI), and leukocyte telomere length (LTL) from a previous genome-wide association study (GWAS) on individuals of European ancestry. Two-sample and multivariable MR analyses were conducted, employing the inverse-variance weighted (IVW) method. Sensitivity analyses were performed to assess potential confounding factors. Results: Using the IVW method, we found suggestive evidence of a causal association between GP14 and FI (β 0.026, 95% CI 0.003 to 0.050, p = 0.027) and LTL (β −0.020, 95% CI −0.037 to −0.002, p = 0.029) in the two-sample MR analysis. In the multivariable MR analysis, suggestive evidence was found for GP23 and FI (β −0.119, 95% CI −0.219 to −0.019, p = 0.019) and GP2 and LTL (β 0.140, 95% CI 0.020 to 0.260, p = 0.023). Conclusions: In conclusion, our results supported a potentially causal effect of lower GP23 levels on an advanced aging state. Additional verification is required to further substantiate the causal relationship between glycosylation and aging.

For the sake of deriving the signature frequencies of the composite malfunctions of broken and worn teeth of gearbox, the essay raised a method on account of local mean decomposition and Hilbert demodulation to diagnose gearbox composite fault. The local mean decomposition translates a complicated multi-component AM-FM signal into several PF elements with certain physical significance. Every PF component can be approximately regarded as a simplex component AM-FM signal. Using correlation coefficient method, the Hilbert envelope demodulation spectrum is analyzed by selecting the PF component which is strongly relevant to the incipient composite malfunction signal, and the malfunction signature frequency is identified from the demodulation spectrum. Through analyzing the emulation signal and the vibration signal of the actual gear box broken-wear complex fault, and compared with EMD, it is shown that the means can effectually discern the malfunction characteristic frequency in the composite fault signal.

Upper limb tremor is a prominent symptom of both Parkinson’s disease and essential tremor. Its kinematic parameters overlap substantially for these two pathological conditions, thus leading to high rate of misdiagnosis, especially for community doctors. Several groups have proposed various methods for improving differential diagnosis. These prior studies have attempted to identify better kinematic parameters, however they have mainly focused on single limb features including tremor intensity, tremor frequency, and tremor variability. In this paper, we propose a wearable system for multi-segment assessment of upper limb tremor and differential diagnosis of Parkinson’s disease versus essential tremor. The proposed system collected tremor data from both wrist and fingers simultaneously. From this data, we extracted multi-segment features in the form of phase relationships between limb segments. Using support vector machine classifiers, we then performed differential diagnosis from the extracted features. We evaluated the performance of the proposed system on 19 Parkinson’s disease patients and 12 essential tremor patients. Moreover, we also assessed the performance cost associated with reducing task load and sensor array size. The proposed system reached perfect accuracy in leave-one-out cross validation. Task reduction and sensor array reduction were associated with penalties of 2% and 9-10% respectively. The results demonstrated that the proposed system could be simplified for clinical applications, and successfully applied to the differential diagnosis of Parkinson’s disease versus essential tremor in real-world setting.

The finger tapping test is a widely-used and important examination in the Movement Disorder Society Clinical Diagnosis for Parkinson’s Disease. However, finger tapping motion could be affected by age, medication, and other conditions. As a result, Parkinson’s disease patients with mild sign and healthy people could be rated as similar scores on the Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale, making it difficult for community doctors to perform diagnosis. We therefore propose a three-dimensional finger tapping framework to recognize mild PD patients. Specifically, we first derive the three-dimensional finger-tapping motion using a self-designed three-dimensional finger-tapping measurement system. We then propose a three-dimensional finger-tapping segmentation algorithm to segment three-dimensional finger tapping motion. We next extract three-dimensional pattern features of motor coordination, imbalance impairment, and entropy. We finally adopted the support vector machine as the classifier to recognize PD patients. We evaluated the proposed framework on 49 PD patients and 29 healthy controls and reached an accuracy of 94.9% for the right hand and 89.4% for the left hand. Moreover, the proposed framework reached an accuracy of 95.0% for the right hand and 97.8% for the left hand on 17 mild PD patients and 28 healthy controls who were both rated as 0 or 1 on the Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale. The results demonstrated that the proposed framework was less sensitive to traditional features and performed well in recognizing mild PD patients by involving three-dimensional patter features.

Introduction: Triterpenoids and saponins have a broad range of pharmacological activities. Unlike most legumes which contain mainly oleanane-type scaffold, Astragalus membranaceus contains not only oleanane-type but also cycloartane-type saponins, for which the biosynthetic pathways are unknown. Objectives: This work aims to study the function and catalytic mechanism of oxidosqualene cyclases (OSCs), one of the most important enzymes in triterpenoid biosynthesis, in A. membranaceus. Methods: Two OSC genes, AmOSC2 and AmOSC3, were cloned from A. membranaceus. Their functions were studied by heterologous expression in tobacco and yeast, together with in vivo transient expression and virus-induced gene silencing. Site-directed mutagenesis and molecular docking were used to explain the catalytic mechanism for the conserved motif. Results: AmOSC2 is a β-amyrin synthase which showed higher expression levels in underground parts. It is associated with the production of β-amyrin and soyasaponins (oleanane-type) in vivo. AmOSC3 is a cycloartenol synthase expressed in both aerial and underground parts. It is related to the synthesis of astragalosides (cycloartane-type) in the roots, and to the synthesis of cycloartenol as a plant sterol precursor. From AmOSC2/3, conserved triad motifs VFM/VFN were discovered for β-amyrin/cycloartenol synthases, respectively. The motif is a critical determinant of yield as proved by 10 variants from different OSCs, where the variant containing the conserved motif increased the yield by up to 12.8-fold. Molecular docking and mutagenesis revealed that Val, Phe and Met residues acted together to stabilize the substrate, and the cation-π interactions from Phe played the major role. Conclusion: The study provides insights into the biogenic origin of oleanane-type and cycloartane-type triterpenoids in Astragalus membranaceus. The conserved motif offers new opportunities for OSC engineering.

As the essential equipment in ultra-high voltage direct current transmission systems, converter transformers provide an important role in the stable operation of the power grid. During the long-term operation of converter transformers, the aging and decomposition of the oil-paper insulation cause a great quantity of metal and non-metal solid particles in the transformer oil, which is one of the important reasons for the equipment failure. The solid particles are affected by various forces in transformer oil, among which the Coulomb force dominates their motion characteristics. The charging process of solid particles contacting the electrode is very important. There are many discussions on the charge carried by metal particles after colliding with the electrode, but less research on the Coulomb force of non-metallic particles in the oil. A simulation model is established to calculate the Coulomb force of metal and non-metal particles in the oil, and the moving process of spherical solid particles of different diameters under different voltages is observed. The research shows that for spherical solid particles with the same material, the Coulomb force increases non-linearly with the increase of particle size. For particles with different materials of the same particle size, the Coulomb force experienced by metal particles is relatively large. Therefore, the charge carried by non-metal particles after colliding with the electrode cannot be calculated by the charge calculation method of metal particles. The research is helpful to analyze the force and movement process of particles in oil and provides support for transformer fault diagnosis and insulation structure design.

Abstract Although oscillating switching impulse (OSI) voltage is recommended for the transformer field test, the lack of corresponding fault diagnosis technologies limits its application in the field. In this study, the inductive OSI test technology and diagnostic methods are investigated. The front time and the oscillation frequency of the OSI are altered by changing the additional inductance, whereas the tail time is affected by both the front and tail resistance. The OSI voltage withstand test is carried out on a 110 kV three‐phase double‐winding transformer on site. Furthermore, transfer function (TF) analysis is used for the diagnosis of transformer insulation with high sensitivity during the OSI test. The fault winding is distinguished by comparing the change in the voltage TF and current TF at different voltage levels. The partial discharge (PD) detection method has the highest sensitivity, which realizes the early diagnosis of insulation faults. The insulation status of the windings is ascertained based on the number and amplitude of PDs. The test results prove that the inductive OSI voltage withstand test is easy to perform on site and can successfully diagnose the insulation faults of the transformer in more detail compared with other routine insulation tests.

Solid–liquid mixing has been a common industrial process operation. The measurement of solid–liquid mixing quality can help improve the efficiency of related industrial processes, but there is still a lack of an intuitive, accurate, and simple measurement method. As an important indicator to evaluate the solid–liquid mixing quality, the degree of solid suspension and the uniformity of solid distribution are directly related to mass transfer and reaction efficiency. Therefore, it is necessary to study the solid suspension and distribution in a solid–liquid system. In this work, the solid suspension and distribution of a solid–liquid system composed of glass beads–water stirred by the impeller are studied experimentally via digital image processing combined with statistical analysis. Specifically, images of solid–liquid mixing are first obtained using a camera and digitally processed. The area ratio of the solid in the image is proposed to reflect the degree of solid suspension, and the modified L2-star discrepancy (MD) is then used to quantify the uniformity of the solid distribution. Then, the solid–liquid mixing quality can be characterized by combining the area ratio and solid distribution. The feasibility of this method was proved by qualitative analysis of the solid–liquid mixing state and comparison with known studies. In addition, the effects of various stirring factors on the solid distribution were studied and discussed by using the proposed method. The results show that the method proposed in this paper can measure the quality of the solid–liquid mixing state more directly and is effective and accurate. Furthermore, it was used to find the best experimental parameters in this work. This method is also simpler and cheaper than many other methods. It is of great significance to improve the efficiency of chemical and metallurgical and other industrial processes.

In this paper, an improved APF-GFARRT* (artificial potential field-guided fuzzy adaptive rapidly exploring random trees) algorithm based on APF (artificial potential field) guided sampling and fuzzy adaptive expansion is proposed to solve the problems of weak orientation and low search success rate when randomly expanding nodes using the RRT (rapidly exploring random trees) algorithm for disinfecting robots in the dense environment of disinfection operation. Considering the inherent randomness of tree growth in the RRT* algorithm, a combination of APF with RRT* is introduced to enhance the purposefulness of the sampling process. In addition, in the context of RRT* facing dense and restricted environments such as narrow passages, adaptive step-size adjustment is implemented using fuzzy control. It accelerates the algorithm’s convergence and improves search efficiency in a specific area. The proposed algorithm is validated and analyzed in a specialized environment designed in MATLAB, and comparisons are made with existing path planning algorithms, including RRT, RRT*, and APF-RRT*. Experimental results show the excellent exploration speed of the improved algorithm, reducing the average initial path search time by about 46.52% compared to the other three algorithms. In addition, the improved algorithm exhibits faster convergence, significantly reducing the average iteration count and the average final path cost by about 10.01%. The algorithm’s enhanced adaptability in unique environments is particularly noteworthy, increasing the chances of successfully finding paths and generating more rational and smoother paths than other algorithms. Experimental results validate the proposed algorithm as a practical and feasible solution for similar problems.

Prostate specific antigen (PSA), as a biomarker, plays important roles in early diagnosis of male prostate diseases, especially prostate cancer. In this study, a novel electrochemical probe polymer of poly(ferriporphyrin-co-acrylamide) was synthesized, by further combined with reduced graphene oxide and gold nanoparticles, and oriented immobilization of PSA antibody, a label-free electrochemical immunosensor was obtained, and then successfully applied in the determination of PSA in 10 % non-antigen serum system. The prepared biosensor expressed high selectivity toward PSA, with a LOD of 0.001 ng mL−1, a linear range of 0.01–110 ng mL−1, and a sensitivity of 15.78 µA mL ng−1. What’s more, it showed good stability, well repeatability and high selectivity in the real PSA sample detection. This work provided certain references for the design of the new electrochemical probes and the detection of tumor markers.

In order to study the group cooperative control method of multiple intelligent networked vehicles, the multiple intelligent networked vehicles can move in the form of a fleet. Based on the leader–follower method, the paper optimizes the control effect of the leader–follower method by solving the error transmission phenomenon in the leader–follower method. In this paper, the modeling of the multiple intelligent connected vehicle adopts the vehicle dynamics model and the Magic Formula/Swift Magic tire model, and adopts the model predictive control (MPC) dynamics trajectory tracking controller for control. Through the CarSim–Simulink multi-vehicle dynamics co-simulation platform established in this paper, the group cooperative control experiments of multiple intelligent networked vehicles under different working conditions were carried out for simulation verification. The analysis results show that the maximum average error of the proposed method decreases from 8.802 to 0.094 in the case of straight line and 0.669 to 0.379 in the case of curve tracking, which proves that the method can effectively reduce the transmission of errors.

We conduct an asteroseismological analysis on the non-Blazhko ab-type RR Lyrae star EPIC 248846335, employing the Radial Stellar Pulsations module of the Modules for Experiments in Stellar Astrophysics based on the set of stellar parameters. The atmospheric parameters T _eff = 6933 ± 70 K, log g = 3.35 ± 0.50, and [Fe/H] = −1.18 ± 0.14 are estimated from low-resolution spectra of LAMOST DR9. The luminosity L = ${49.70}_{-1.80}^{+2.99}$ L _⊙ and mass M = 0.56 ± 0.07 M _⊙ are calculated, respectively, using the distance provided by Gaia and the metallicity estimated from the low-resolution spectra. The Fourier parameters of the light curves observed by K2 and radial velocity (RV) curves determined from the medium-resolution spectra of LAMOST DR10 are also calculated in this work. The period of the fundamental mode of the star and the residuals r of the Fourier parameters between the models and observations serve to select an optimal model, whose stellar parameters are T _eff = 6700 ± 220 K, log g = 2.70, [Fe/H] = −1.20 ± 0.2, M = 0.59 ± 0.05 M _⊙ , and L = 56.0 ± 4.2 L _⊙ . The projection factors are constrained as 1.20 ± 0.02 and 1.59 ± 0.13 by the blue- and red-arm observed velocities with their corresponding RV curves derived from the best-fit model, respectively. The precise determination of stellar parameters in ab-type RR Lyrae stars is crucial for understanding the physical processes that occur during pulsation and for providing a deeper understanding of their period–luminosity relationship.

Stellar flares are critical phenomena on stellar surfaces, which are closely tied to stellar magnetism. While extensively studied in main-sequence (MS) stars, their occurrence in evolved compact stars, specifically hot subdwarfs and white dwarfs (WDs), remains scarcely explored. Based on Cycles 1–5 of TESS photometry, we conducted a pioneering survey of flare events in ∼12,000 compact stars, corresponding to ∼38,000 light curves with a 2 minute cadence. Through dedicated techniques for detrending light curves, identifying preliminary flare candidates, and validating them via machine learning, we established a catalog of 1016 flares from 193 compact stars, including 182 from 58 sdB/sdO stars and 834 from 135 WDs, respectively. However, all flaring compact stars showed signs of contamination from nearby objects or companion stars, preventing sole attribution of the detected flares. For WDs, it is highly probable that the flares originated from their cool MS companions. In contrast, the higher luminosities of sdB/sdO stars diminish companion contributions, suggesting that detected flares originated from sdB/sdO stars themselves or through close magnetic interactions with companions. Focusing on a refined sample of 23 flares from 13 sdB/sdO stars, we found their flare frequency distributions were slightly divergent from those of cool MS stars; instead, they resemble those of hot B/A-type MS stars having radiative envelopes. This similarity implies that the flares on sdB/sdO stars, if these flares did originate from them, may share underlying mechanisms with hot MS stars, which warrants further investigation.

Abstract The presence of lightning impulses (LIs) on the DC waveform can seriously influence the insulation performance of a GIL system. The waveshape can be a superposition of the DC and impulse waveform. In this study, the behaviour of partial discharge (PD) on an epoxy surface is investigated under DC and LI superimposed voltage in SF6. The lightning impulses with different polarities are superimposed on the epoxy surface under both positive and negative DC voltages, respectively. Positive lightning impulses are superimposed on a negative DC voltage with a 90% of the partial discharge inception voltage (PDIV) magnitude. The number and amplitude of the PDs are used to evaluate the insulation performance. The experimental results show that the LI with a different polarity applied to DC can excite the PDs on the epoxy surface. The excitation effect of positive LI superimposed on negative DC is more significant. According to the impulse amplitude and PD characteristics, the influence of superimposed LI on PD excitation can be divided into three stages. As the superimposed LI increases, the amplitude of the excited PD increases gradually, while the PD number first increases and then decreases. This study is expected to provide reference for manufacture and protection of power equipment.