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Abstract As the core of ontology integration, the task of ontology mapping is to find the semantic relationship between ontologies. Nevertheless, most existing ontology mapping methods only rely ontext information to calculate entity similarity, thereby disregarding semantic nuances and necessitating substantial manual intervention. Therefore, this paper introduces an ontology mapping method. Based on the traditional ontology mapping method, the process employs a deep learning model to mine the semantic information of entity concepts, entity properties and ontology structure to obtain the embedding vector. We use the similarity mechanism to calculate the similarity between different embedding vectors, and combine the similarity values obtained from multiple strategy entities into a similarity matrix. The similarity matrix serves as input to the support vector machine (SVM), and the ontology mapping problem is finally transformed into a binary classification problem. However, since the number of mapped pairs is much larger than the number of non-mapped pairs, the number of positive samples in the data set is much smaller than the number of negative samples. Therefore, based on the traditional SVM, the paper adopts cost-sensitive strategy to deal with the class imbalance problem. In comparative evaluations against contemporary ontology mapping techniques, our method demonstrates a noteworthy 5.0% enhancement in recall and a 3.0% improvement in F1 score when tested on both public benchmark datasets and domain-specific datasets.

In particular, the secondary development of overlying strata fractures can easily lead to the upper goaf, resulting in gas and water gathered in the goaf entering the working face of the lower coal seam through the overlying strata fractures, threatening the safety of coal mine production. Security risks may arise. To further understand the caving and evolution law of overlying strata during repeated mining in extremely close distance coal seam down mining, 9# coal and 10# coal in the Nanyaotou Coal Industry were used as the engineering background. The caving characteristics and fracture evolution law of overlying strata during single and repeated mining were analyzed through similar material simulation tests. Based on fractal geometry theory, the relationship between the advancing distance of the working face and the fractal dimension of the overlying strata fracture is established to reflect the changing trend of fracture development. The calculation formula is derived from the tensile rate of rock strata to predict the development height of water-conducting fractures. The results show that the overlying strata failure structure is mainly a “hinged structure” and a “step structure,” which respectively promotes and inhibits the development of overlying strata fractures. Repeated mining causes mining-induced fractures in the lower coal seam to pass through the goaf of the upper coal seam and develop more vigorously in the upper coal seam, and the fractal dimension can effectively reflect the development of overlying strata fractures. The height of the water-conducting fracture zone increases in four stages: incubation, gradual increase, further gradual increase, and stability, eventually stopping development under the influence of the key layer (thick mudstone) bearing the load above. The development height of water-conducting fractures predicted by on-site water injection measurement is similar to that predicted by simulation experiments and theoretical calculations, verifying the feasibility of predicting the development height of water-conducting fractures through simulation tests and theoretical analysis. This study provides a reference for coal seam mining under similar conditions.

The western mining regions of China, known for shallow-buried and high-intensity mining activities, face significant ecological threats due to damage to loose strata and the surface. The evolution of fissures within the loose layer is a critical issue for surface ecological environment protection in coal mining areas. The study employed field measurements, mechanical experiments, numerical simulations, and theoretical analysis, using the ‘triaxial consolidation without drainage’ experiment to assess the physical and mechanical properties of various strata in the loose layer. Additionally, the PFC2D numerical simulation software was employed to construct a numerical model that elucidates the damage mechanisms and reveals the evolution of loose layer fissures and the development of ground cracks. The research findings indicate that during shallow-buried high-intensity mining loose layer fissures undergo a dynamic evolution process characterized by “vertical extension-continuous penetration-lateral expansion”. As the working face advances, these fissures eventually propagate to the surface, forming ground cracks. The strong force chains within the overlying rock (or soil) layers develop in the form of an “inverted catenary arch”. As the arch foot and the middle of the arch overlap, fissures propagate along these strong force chains to the surface, resulting in ground cracks. The study elucidates the surface damage patterns in shallow-buried, high-intensity mining, offering theoretical insights for harmonizing coal mining safety with ecological conservation in fragile regions.

The large-scale deployment and rapid development of the new generation mobile communication system underpin the widespread application of a massive and diverse range of Internet of things (IoT) devices.However, the distributed application of IoT devices results to significant disparities in private data and substantial heterogeneity in local processing models, which severely limits the aggregation capability of global intelligent model.Therefore, to tackle the challenges of data heterogeneity, model heterogeneity, and insufficient labeling faced by intelligent modulation recognition in cognitive IoT, an algorithm was proposed for heterogeneous federated bidirectional semi-supervised modulation recognition, which incorporated bidirectional knowledge distillation.In the proposed algorithm, a public pseudo dataset was generated by variational autoencoder in the cloud for supporting uplink global knowledge distillation, and adaptively sharing to the local devices for downlink heterogeneous knowledge distillation, while integrating a semi-supervised algorithm within the distillation process.The simulation results indicate that the proposed algorithm outperforms current federated learning algorithms in terms of effectiveness and applicability in the field of communication signal processing.

Coilia nasus is a precious migratory fish typical to the Yangtze River Basin of China. It is locally referred to as the "Three delicious fish of the Yangtze River, " with its fresh meat being particularly delicious and popular. In recent years, wild C. nasus numbers in the Yangtze River Basin have been decreasing due to environmental changes and illegal overfishing, among other reasons. To attenuate the availability of C. nasus, the Shanghai Fisheries Research Institute has successfully established an indoor artificial breeding and pond culture program in 2011. The research and development of C. nasus artificial breeding technologies have steadily progressed, though the artificial breeding yield of C. nasus remains relatively low. In addition, related research on the artificial cultivation of C. nasus is still in its infancy. Research on C. nasus in China and abroad mainly focuses on gonad development, breeding technology, muscle nutrient composition, and growth performance. No reports exist on the effects of brackish water culture conditions on the physiology of C. nasus. Given its economic importance, it would be of great value to evaluate the changes in the digestive, antioxidant, nonspecific immune capacity, and metabolic rates of C. nasus from brackish water (natural seawater in Hangzhou Bay, salinity 8.7~12.5) to freshwater aquaculture, to determine the breeding conditions of C. nasus, and to improve the artificial breeding yield and related technology. To investigate the differences in digestive capacity, antioxidant capacity, nonspecific immune capacity, and metabolic rates of C. nasus in brackish water and freshwater aquaculture conditions, the experiment adopted the pond interbreeding method. Two groups were established: A brackish aquaculture group and a freshwater aquaculture group (control group). Each group was housed in a single aquaculture pond with an area of 0.17 hm2. 500 C. nasus were stocked in each pond and moved to a Takifugu obscurus pond for a seven-month aquaculture experiment. At the end of the experiment, 12 C. nasus were randomly selected from each group and randomly divided into three replicates. Four C. nasus samples were selected from each replicate. The liver, intestine, stomach, and cecum of C. nasus were dissected on an ice plate and carefully removed to prepare a 10% homogenate. The activities of digestive enzymes, antioxidant enzymes, nonspecific immune enzymes, and metabolic enzymes and the total protein content were measured using a kit produced by the Nanjing Jiancheng Bioengineering Institute. The activities of digestive enzymes, antioxidant enzymes, nonspecific immunity enzymes, and metabolic enzymes in brackish water and freshwater aquaculture environments were compared and analyzed in a seven-month aquaculture experiment using the same batch of artificially bred C. nasus. The growth and survival rates of C. nasus cultured in brackish water (hereafter referred to as brackish water C. nasus) were significantly higher than that in the freshwater (hereafter referred to as freshwater C. nasus) (P < 0.05). The digestive ability of protein and starch in brackish water C. nasus was higher than that of freshwater C. nasus, while the digestive ability was weakened. Among them, the activity of amylase (AMS) in the four organs of brackish water C. nasus was higher than those in freshwater, but not significantly so (P > 0.05). The activities of protease in the liver and stomach were significantly higher than those in freshwater C. nasus (P < 0.05), and the activities of lipase (LPS) in the liver and cecum were significantly lower than those in freshwater C. nasus (P < 0.05). The order of AMS and protease activity of brackish water C. nasus was: cecum > intestine > stomach > liver, while the order of LPS activity was intestine > cecum > stomach > liver. The order of AMS, protease, and LPS activity of freshwater C. nasus was: cecum > intestine > stomach > liver. Brackish water had significant effects on antioxidant, nonspecific immunity, and metabolic abilities, and the activities of superoxide dismutase (SOD), glutathione peroxidase (GSH-PX), and malondialdehyde (MDA) in the liver of C. nasus were significantly increased, while the activity of catalase (CAT) was significantly decreased (P < 0.05). The activities of alkaline phosphatase (AKP) and acid phosphatase (ACP) in the liver of C. nasus in brackish water were significantly lower than those in freshwater (P < 0.05). Brackish water had no significant effect on the activity of aspartate aminotransferase (AST), but it significantly reduced the activity of alanine aminotransferase (ALT). In summary, brackish water aquaculture conditions promoted the growth of C. nasus; increased the survival rate; improved the ability of C. nasus to digest protein and starch; improved the immunity of fish; and reduced the influence of external stresses by decreasing the activities of AKP, ACP, and ALT enzymes and increasing the activities of SOD and GSH-PX enzymes. This study also found that C. nasus living in brackish water, as a result of maintaining the internal osmotic balance, significantly reduced ALT enzyme activity and reduced urea production and emission, thereby reducing the pollution of the direct environment. Therefore, brackish water is more suitable for the aquaculture of C. nasus, and it is recommended that brackish water (salinity of 8.7~12.5) be used for aquaculture of 1+ age C. nasus individuals in the future. The results of this study provide a scientific basis for the improvement of artificial breeding technology, improving the yield of C. nasus, and the development of special compound feed for C. nasus.

Background and Aims:. Restitution of the extrahepatic biliary luminal epithelium in cholangiopathies is poorly understood. Prominin-1 (Prom1) is a key component of epithelial ciliary body of stem/progenitor cells. Given that intrahepatic Prom1-expressing progenitor cells undergo cholangiocyte differentiation, we hypothesized that Prom1 may promote restitution of the extrahepatic bile duct (EHBD) epithelium following injury. Approach and Results:. Utilizing various murine biliary injury models, we identified Prom1-expressing cells in the peribiliary glands of the EHBD. These Prom1-expressing cells are progenitor cells which give rise to cholangiocytes as part of the normal maintenance of the EHBD epithelium. Following injury, these cells proliferate significantly more rapidly to re-populate the biliary luminal epithelium. Null mutation of Prom1 leads to significantly >10-fold dilated peribiliary glands following rhesus rotavirus–mediated biliary injury. Cultured organoids derived from Prom1 knockout mice are comprised of biliary progenitor cells with altered apical-basal cellular polarity, significantly fewer and shorter cilia, and decreased organoid proliferation dynamics consistent with impaired cell motility. Conclusions:. We, therefore, conclude that Prom1 is involved in biliary epithelial restitution following biliary injury in part through its role in supporting cell polarity.

The integrity of a point cloud frequently suffers from discontinuous material surfaces or coarse sensor resolutions. Existing methods focus on reconstructing the overall structure, but salient points or small irregular surfaces are difficult to be predicted. Toward this issue, we propose a new end-to-end neural network for point cloud completion. To avoid non-uniform point density, the regular voxel centers are selected as reference points. The encoder and decoder are designed with Patchify, transformers, and multilayer perceptrons. An implicit classifier is incorporated in the decoder to mark the valid voxels that are allowed for diffusion after removing vacant grids from completion. With newly designed loss function, the classifier is trained to learn the contours, which helps to identify the grids that are difficult to be judged for diffusion. The effectiveness of the proposed model is validated in the experiments on the indoor ShapeNet dataset, the outdoor KITTI dataset, and the airbone laser dataset by competing with state-of-the-art methods, which show that our method can predict more accurate point coordinates with rich details and uniform point distributions.

Five established clearing protocols were compared with a modified and simplified method to determine an optimal clearing reagent for three-dimensionally visualizing fluorophores in the murine liver, a challenging organ to clear. We report successful clearing of whole liver lobes by modification of an established protocol (UbasM) using only Ub-1, a urea-based amino sugar reagent, in a simpler protocol that requires only a 24-h processing time. With Ub-1 alone, we observed sufficiently preserved liver tissue structure in three dimensions along with excellent preservation of fluorophore emissions from endogenous protein reporters and lipophilic tracer dyes. This streamlined technique can be used for 3D cell lineage tracing and fluoroprobe-based reporter gene expression to compare various experimental conditions.

Image retrieval is becoming more and more important due to the rapid increase of the number of images on the web. To improve the efficiency of computing the similarity of images, hashing has moved into the focus of research. This paper proposes a Deep Attention-based Hash (DAH) retrieval model, which combines an attention module and a convolutional neural network to obtain hash codes with strong representability. Our DAH has the following features: The Hamming distance between the hash codes generated by similar images is small and the Hamming distance of hash codes of dissimilar images has a larger constant value. The quantitative loss from Euclidean distance to Hamming distance is minimized. DAH has a high image retrieval precision: We thoroughly compare it with ten state-of-the-art approaches on the CIFAR-10 dataset. The results show that the Mean Average Precision (MAP) of DAH reaches more than 92% in terms of 12, 24, 36 and 48 bit hash codes on CIFAR-10, which is better than what the state-of- art methods used for comparison can deliver.

This article mainly studies first-order coherence related to the robustness of the triplex MASs consensus models with partial complete graph structures; the performance index is studied through algebraic graph theory. The topologies of the novel triplex networks are generated by graph operations and the approach of graph spectra is applied to calculate the first-order network coherence. The coherence asymptotic behaviours of the three cases of the partial complete structures are analysed and compared. We find that under the condition that the number of nodes in partial complete substructures n tends to infinity, the coherence asymptotic behaviour of the two sorts of non-isomorphic three-layered networks will be increased by r−12(r+1), which is irrelevant to the peripheral vertices number p; when p tends to infinity, adding star copies to the original triplex topologies will reverse the original size relationship of the coherence under consideration of the triplex networks. Finally, the coherence of the three-layered networks with the same sorts of parameters, but non-isomorphic graphs, are simulated to verify the results.

Background/Aims MicroRNAs (miRNAs) play critical regulatory roles in the pathogenesis of pulmonary fibrosis. The aim of this study was to explore whether miRNA antagomirs could serve as potential therapeutic agents in interstitial lung diseases. Methods A mouse model of pulmonary fibrosis was established by intratracheal injection of bleomycin (BLM). Using microarray analysis, up-regulated miRNAs were identified during the development of pulmonary fibrosis. miR-155 was chosen as the candidate miRNA. Fifteen mice were then randomized into the following three groups: BLM + antagomiR-155 group, treated with BLM plus intravenously injected with antagomiR-155; BLM group, treated with intratracheal BLM plus phosphate-buffered saline (PBS); and a control group, treated with PBS only. Lung tissues were collected for histopathological analysis, hydroxyproline measurement, and Western blotting. Enzyme-linked immunosorbent assays were used for the measurement of cytokines associated with pulmonary fibrosis. Results Histological changes and hydroxyproline levels induced by BLM were significantly inhibited by antagomiR-155. The levels of interleukin 4 (IL-4) and transforming growth factor-β (TGF-β) expression were increased after BLM treatment. However, miR-155 silencing decreased the expression of IL-4, TGF-β, and interferon-γ. TGF-β-activated kinase 1/mitogen-activated protein kinase kinase kinase 7 (MAP3K7)-binding protein 2 (TAB2) of the mitogen-activated protein kinase (MAPK) signaling pathway, was activated by BLM and inhibited by in vivo silencing of miR-155 via antagomiR-155. Conclusions In vivo treatment with antagomiR-155 alleviated the pathological changes induced by BLM and may be a promising therapeutic strategy for pulmonary fibrosis.

Abstract Cholestatic liver injury is associated with intrahepatic biliary fibrosis, which can progress to cirrhosis. Resident hepatic progenitor cells (HPCs) expressing Prominin‐1 (Prom1 or CD133) become activated and participate in the expansion of cholangiocytes known as the ductular reaction. Previously, we demonstrated that in biliary atresia, Prom1(+) HPCs are present within developing fibrosis and that null mutation of Prom1 significantly abrogates fibrogenesis. Here, we hypothesized that these activated Prom1‐expressing HPCs promote fibrogenesis in cholestatic liver injury. Using Prom1CreERT2‐nLacZ/+;Rosa26Lsl‐GFP/+ mice, we traced the fate of Prom1‐expressing HPCs in the growth of the neonatal and adult livers and in biliary fibrosis induced by bile duct ligation (BDL). Prom1‐expressing cell lineage labeling with Green Fluorescent Protein (GFP) on postnatal day 1 exhibited an expanded population as well as bipotent differentiation potential toward both hepatocytes and cholangiocytes at postnatal day 35. However, in the adult liver, they lost hepatocyte differentiation potential. Upon cholestatic liver injury, adult Prom1‐expressing HPCs gave rise to both PROM1(+) and PROM1(‐) cholangiocytes contributing to ductular reaction without hepatocyte or myofibroblast differentiation. RNA‐sequencing analysis of GFP(+) Prom1‐expressing HPC lineage revealed a persistent cholangiocyte phenotype and evidence of Transforming Growth Factor‐β pathway activation. When Prom1‐expressing cells were ablated with induced Diphtheria toxin in Prom1CreERT‐nLacZ/+;Rosa26DTA/+ mice, we observed a decrease in ductular reactions and biliary fibrosis typically present in BDL as well as decreased expression of numerous fibrogenic gene markers. Our data indicate that Prom1‐expressing HPCs promote biliary fibrosis associated with activation of myofibroblasts in cholestatic liver injury.

Abstract In this paper, a diffusive and delayed virus dynamics model with Crowley-Martin incidence function and CTL immune response is investigated. By constructing the Lyapunov functionals, the threshold conditions on the global stability of the infection-free, immune-free and interior equilibria are established if the space is assumed to be homogeneous. We show that the infection-free equilibrium is globally asymptotically stable if the basic reproductive number R 0 ≤ 1 $R_{0}\leq1$ ; the immune-free equilibrium is globally asymptotically stable if the immune reproduction number and the basic reproduction number satisfy R 1 ≤ 1 < R 0 $R_{1}\leq1< R_{0}$ ; the interior equilibrium is globally asymptotically stable if R 1 > 1 $R_{1}>1$ .

Objective. Urumqi is one of the key areas of HIV/AIDS infection in Xinjiang and in China. The AIDS epidemic is spreading from high-risk groups to the general population, and the situation is still very serious. The goal of this study was to use four data mining algorithms to establish the identification model of HIV infection and compare their predictive performance. Method. The data from the sentinel monitoring data of the three groups of high-risk groups (injecting drug users (IDU), men who have sex with men (MSM), and female sex workers (FSW)) in Urumqi from 2009 to 2015 included demographic characteristics, sex behavior, and serological detection results. Then we used age, marital status, education level, and other variables as input variables and whether to infect HIV as output variables to establish four prediction models for the three datasets. We also used confusion matrix, accuracy, sensitivity, specificity, precision, recall, and the area under the receiver operating characteristic (ROC) curve (AUC) to evaluate classification performance and analyzed the importance of predictive variables. Results. The final experimental results show that random forests algorithm obtains the best results, the diagnostic accuracy for random forests on MSM dataset is 94.4821%, 97.5136% on FSW dataset, and 94.6375% on IDU dataset. The k-nearest neighbors algorithm came out second, with 91.5258% diagnostic accuracy on MSM dataset, 96.3083% diagnostic accuracy on FSW dataset, and 90.8287% diagnostic accuracy on IDU dataset, followed by support vector machine (94.0182%, 98.0369%, and 91.3571%). The decision tree algorithm was the poorest among the four algorithms, with 79.1761% diagnostic accuracy on MSM dataset, 87.0283% diagnostic accuracy on FSW dataset, and 74.3879% accuracy on IDU. Conclusions. Data mining technology, as a new method of assisting disease screening and diagnosis, can help medical personnel to screen and diagnose AIDS rapidly from a large number of information.

Background and Aims: Restitution of the extrahepatic biliary luminal epithelium in cholangiopathies is poorly understood. Prominin-1 (Prom1) is a key component of epithelial ciliary body of stem/progenitor cells. Given that intrahepatic Prom1-expressing progenitor cells undergo cholangiocyte differentiation, we hypothesized that Prom1 may promote restitution of the extrahepatic bile duct (EHBD) epithelium following injury. Approach and Results: Utilizing various murine biliary injury models, we identified Prom1-expressing cells in the peribiliary glands of the EHBD. These Prom1-expressing cells are progenitor cells which give rise to cholangiocytes as part of the normal maintenance of the EHBD epithelium. Following injury, these cells proliferate significantly more rapidly to repopulate the biliary luminal epithelium. Null mutation of Prom1 leads to significantly > 10-fold dilated peribiliary glands following rhesus rotavirus-mediated biliary injury. Cultured organoids derived from Prom1 knockout mice are comprised of biliary progenitor cells with altered apical-basal cellular polarity, significantly fewer and shorter cilia, and decreased organoid proliferation dynamics consistent with impaired cell motility. Conclusions: We, therefore, conclude that Prom1 is involved in biliary epithelial restitution following biliary injury in part through its role in supporting cell polarity. [ABSTRACT FROM AUTHOR]