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In this paper, as-received Zn powder and as-prepared Zn@(ZnWO4/ZnO) core–shell powder were used as feedstocks for plasma spraying to prepare Zn-based composite coatings and nano-ZnO was co-deposited by chemical vapor deposition induced by plasma spraying. The composition and morphology were controllable within certain range by plasma spraying power. The photocatalytic activities of the coatings were analyzed by the degradation efficiency of methyl orange (MO) solution. It was found the photocatalytic activity can be improved with ZnWO4 decoration. The Zn/ZnO/ZnWO4 coating which presented tremella-like surface morphology was testified to have the best photocatalytic activity under UV light irradiation among all coatings. On the other hand, the chemical surface modification with 1H,1H,1H,2H-perfluorodecyltriethoxysilane (FAS-17) was implemented to produce superhydrophobic coatings. Among all modified coatings, the ZnWO4-containing coating with tremella-like surface structure presented the best superhydrophobicity. By the cyclic wetting and tape adhesion experiments, the tremella-like structure was proved to make a great improvement on the robustness of the Zn-based superhydrophobic coatings. The superhydrophobic and photocatalytic properties provide the possibility for the application of the coating in the fields of antifouling, antibacterial, and photocatalytic degradation of organics. [ABSTRACT FROM AUTHOR]

The conventional repairing of CFRP (continuous fiber-reinforced polymer composites) includes complicated steps of patching, splicing, repairing, and post-curing. Intensive labor work needs to be conducted, and poor surface quality and weak interfacial adhesion are usually observed. This work mainly introduces an in situ online repairing method using AM (additive manufacturing) facilitated composite fabrication. With the advances of the robotic-assisted AM process, the surface roughness and accuracy during the repairing process can be evaluated online upon layer-by-layer process. In order to fulfill the efficient and on-site requirements for repairing damage in structural components, this study explores the method including in situ repairing, laser point clouds online collection, and repairing path planning based on multi-axial additive manufacturing of composites. A repair algorithm is proposed incorporating point clouds collection, measurement evaluation, and path planning. Furthermore, relevant mechanical measurements have been conducted, so as to assess the interface degree of recovery. A rapid online evaluation and surface conformal repairing method have been proposed to overcome the technical bottleneck of in situ automatic repairing of damaged composites. It expands the application of multi-axial robot-assisted CFRP AM. [ABSTRACT FROM AUTHOR]

Nanjing Yunjin, a traditional Chinese silk weaving craft, is celebrated globally for its unique local characteristics and exquisite workmanship, forming an integral part of the world's intangible cultural heritage. However, with the advancement of information technology, the experiential knowledge of the Nanjing Yunjin production process is predominantly stored in text format. As a highly specialized and vertical domain, this information is not readily convert into usable data. Previous studies on a knowledge graph-based Nanjing Yunjin Question-Answering System have partially addressed this issue. However, knowledge graphs need to be constantly updated and rely on predefined entities and relationship types. Faced with ambiguous or complex natural language problems, knowledge graph information retrieval faces some challenges. Therefore, this study proposes a Nanjing Yunjin Question-Answering System that integrates Knowledge Graphs and Retrieval Augmented Generation techniques. In this system, the ROBERTA model is first utilized to vectorize Nanjing Yunjin textual information, delving deep into textual semantics to unveil its profound cultural connotations. Additionally, the FAISS vector database is employed for efficient storage and retrieval of Nanjing Yunjin information, achieving a deep semantic match between questions and answers. Ultimately, related retrieval results are fed into the Large Language Model for enhanced generation, aiming for more accurate text generation outcomes and improving the interpretability and logic of the Question-Answering System. This research merges technologies like text embedding, vectorized retrieval, and natural language generation, aiming to overcome the limitations of knowledge graphs-based Question-Answering System in terms of graph updating, dependency on predefined types, and semantic understanding. System implementation and testing have shown that the Nanjing Yunjin Intelligent Question-Answering System, constructed on the basis of Knowledge Graphs and Retrieval Augmented Generation, possesses a broader knowledge base that considers context, resolving issues of polysemy, vague language, and sentence ambiguity, and efficiently and accurately generates answers to natural language queries. This significantly facilitates the retrieval and utilization of Yunjin knowledge, providing a paradigm for constructing Question-Answering System for other intangible cultural heritages, and holds substantial theoretical and practical significance for the deep exploration and discovery of the knowledge structure of human intangible heritage, promoting cultural inheritance and protection. [ABSTRACT FROM AUTHOR]

Purpose: Pancreatic cancer (PC) is one of the most deadly human malignancies. Curcumin is a natural polyphenolic compound with wide-ranging pharmacological effects. Growing evidence suggests that curcumin has anticancer activity against PC, but the mechanism remains incompletely elucidated. This study aimed to investigate the effects and mechanisms of curcumin on the invasion and migration of PC cells. Methods: Effect of curcumin on tissue factor pathway inhibitor (TFPI)-2 mRNA expression in PC cells was initially identified using qRT-PCR. Cytotoxicity of curcumin was assessed with MTT assays and IC50 was calculated. Involvement of ERK and JNK pathways, as well as protein expression of TFPI-2 and epithelial–mesenchymal transition (EMT)-related markers, were detected using immunoblotting. Invasion and migration of PC cells were examined using Transwell assays. TFPI-2 expression was manipulated by transfection with siRNA and shRNA. Rescue assays were used to validate the effect of curcumin on cell invasion and migration via TFPI-2. Results: Curcumin increased the expression of TFPI-2 mRNA and protein in PC cells and attenuated cell invasion and migration. Curcumin also inhibited ERK and JNK pathways and EMT in PC cells. Knockdown of TFPI-2 partially reversed the inhibition of ERK and JNK pathways and EMT by curcumin. Mechanistically, curcumin upregulated TFPI-2, thereby inhibiting the ERK and JNK pathways, leading to the inhibition of EMT in PC cells. Conclusion: Collectively, curcumin inhibits ERK- and JNK-mediated EMT through upregulating TFPI-2, which in turn suppresses the migration and invasion of PC cells. These findings provide new insights into the antitumor mechanism of curcumin. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is one of the leading cause of cancer-associated death in the world. However, due to the complexity of HCC, it is urgent for us to find a reliable and accurate biomarker for HCC gene therapy.TopBP1-interacting checkpoint and replication regulator (TICRR), known as Treslin in vertebrate and sld3 in yeast, is involved in the tumorigenesis, progression, matastasis, diagnosis, and predicting prognosis of HCC. Disappointingly, the mechanism of TICRR expression in HCC is still not described in detail and requires further analysis. In this study, TCGA (www.tcga-data.nci.nih.gov/tcga/) datasets and GEO (www.ncbi.nlm.nih.gov/geo) datasets were used to analyze the expression of TICRR in HCC, the relevance of TICRR mRNA expression and clinicopathological characteristics in patients with HCC, and the relationship between TICRR expression and immune infiltration level in Patients with HCC. Based on MethSurv database, the impact of TICRR in patients with HCC was investigated. In addition, GO/KEGG enrichment analysis of TICRR co-expression was performed using the R package. TICRR was found drastically highly expressed in a variety of cancer types including HCC.ROC curve analysis showed that TICRR had higher accuracy in predicting HCC compared with AFP. The expression level of TICRR was marked positively correlated with tumor stage and prognosis in Patients with HCC.GO/KEGG enrichment analysis showed that TICRR was associated with cell division and cell cycle as well as p53 signaling pathway. In addition, patients with high TICRR methylation of cg05841809, cg09403165, and cg03312532 CpG sites were significantly correlated with poor prognosis of HCC. This study demonstrated that increased TICRR expression in HCC might play an important role in the tumorigenesis, progression, diagnosis, and predicting prognosis of HCC. Therefore, TICRR might be used as a promising diagnostic and prognostic biomarker for HCC gene therapy. [ABSTRACT FROM AUTHOR]

The powerful parallel computing capability of GPU and the development of matrix processing unit in recent years provide more possibilities to improve the performance of convolutional neural network (CNN) on GPU. For the Winograd convolution algorithm, which is the most widely used in CNN and has the best performance, there are already some tuning results, but they all ignore the utilization of the matrix operation unit and fail to make full use of the computing resources of GPU. This paper introduces a single precision accelerated solution on GPU for CNN. According to the indicators of architecture, the optimal data layout, grid division and block division methods are derived. In order to adapt to a variety of padding in practical application, an efficient dynamic scheme for filling is designed, and by the use of matrix cores, a pipeline algorithm with operator fusion is implemented. The deep learning accelerated library MIOpen in AMD is used as the baseline. Taking several convolutional layers of ResNet50 as the experimental input, the evaluation shows that our approach outperforms MIOpen with the speedup of 1.41x on MI210, and reaches 74% of the peak value of single precision calculations. Applying this method to the training and inference of ResNet50, the speedup of 1.68x is obtained. [ABSTRACT FROM AUTHOR]

Nanjing Yunjin, one of China's traditional silk weaving techniques, is renowned for its unique local characteristics and exquisite craftsmanship, and was included in the Representative List of the Intangible Cultural Heritage of Humanity by UNESCO in 2009. However, with rapid development in weaving technology, ever-changing market demands, and shifting public aesthetics, Nanjing Yunjin, as an intangible cultural heritage, faces the challenge of survival and inheritance. Addressing this issue requires efficient storage, management, and utilization of Yunjin knowledge to enhance public understanding and recognition of Yunjin culture. In this study, we have constructed an intelligent question-answering system for Nanjing Yunjin digital resources based on knowledge graph, utilizing the Neo4j graph database for efficient organization, storage, and protection of Nanjing Yunjin knowledge, thereby revealing its profound cultural connotations. Furthermore, we adopted deep learning algorithms for natural language parsing. Specifically, we adopted BERT-based intent recognition technology to categorize user queries by intent, and we employed the BERT + BiGRU + CRF model for entity recognition. By comparing with BERT + BILSTM + CRF, BERT + CRF and BILSTM + CRF models, our model demonstrated superior performance in terms of precision, recall, and F1 score, substantiating the superiority and effectiveness of this model. Finally, based on the parsed results of the question, we constructed knowledge graph query statements, executed by the Cypher language, and the processed query results were fed back to the users in natural language. Through system implementation and testing, multiple indices including system response time, stability, load condition, accuracy, and scalability were evaluated. The experimental results indicated that the Nanjing Yunjin intelligent question-answering system, built on the knowledge graph, is able to efficiently and accurately generate answers to user's natural language queries, greatly facilitating the retrieval and utilization of Yunjin knowledge. This not only reinforces the transmission, promotion, and application of Yunjin culture but also provides a paradigm for constructing other intangible cultural heritage question-answering systems based on knowledge graphs. This has substantial theoretical and practical significance for deeply exploring and uncovering the knowledge structure of human intangible heritage, promoting cultural inheritance and protection. [ABSTRACT FROM AUTHOR]

Nanjing Yunjin, one of China's traditional silk weaving techniques, is renowned for its unique local characteristics and exquisite craftsmanship, and was included in the Representative List of the Intangible Cultural Heritage of Humanity by UNESCO in 2009. However, with rapid development in weaving technology, ever-changing market demands, and shifting public aesthetics, Nanjing Yunjin, as an intangible cultural heritage, faces the challenge of survival and inheritance. Addressing this issue requires efficient storage, management, and utilization of Yunjin knowledge to enhance public understanding and recognition of Yunjin culture. In this study, we have constructed an intelligent question-answering system for Nanjing Yunjin digital resources based on knowledge graph, utilizing the Neo4j graph database for efficient organization, storage, and protection of Nanjing Yunjin knowledge, thereby revealing its profound cultural connotations. Furthermore, we adopted deep learning algorithms for natural language parsing. Specifically, we adopted BERT-based intent recognition technology to categorize user queries by intent, and we employed the BERT + BiGRU + CRF model for entity recognition. By comparing with BERT + BILSTM + CRF, BERT + CRF and BILSTM + CRF models, our model demonstrated superior performance in terms of precision, recall, and F1 score, substantiating the superiority and effectiveness of this model. Finally, based on the parsed results of the question, we constructed knowledge graph query statements, executed by the Cypher language, and the processed query results were fed back to the users in natural language. Through system implementation and testing, multiple indices including system response time, stability, load condition, accuracy, and scalability were evaluated. The experimental results indicated that the Nanjing Yunjin intelligent question-answering system, built on the knowledge graph, is able to efficiently and accurately generate answers to user's natural language queries, greatly facilitating the retrieval and utilization of Yunjin knowledge. This not only reinforces the transmission, promotion, and application of Yunjin culture but also provides a paradigm for constructing other intangible cultural heritage question-answering systems based on knowledge graphs. This has substantial theoretical and practical significance for deeply exploring and uncovering the knowledge structure of human intangible heritage, promoting cultural inheritance and protection. [ABSTRACT FROM AUTHOR]

In the extracorporeal shock wave lithotripsy for infants, we used a medical polymer gel pad to assist ultrasonic positioning, so that the ultrasonic probe could be far away from the shock wave energy field. Although not affecting the ultrasonic positioning and monitoring effect, we discussed the protective effect of this method on the ultrasonic probe. A retrospective analysis was made on 21 infants (0–3 years old) who received ESWL in our hospital from June 2021 to February 2023. After the stones were accurately located by B-ultrasound before surgery, a 4 * 5 * 10 cm medical polymer gel pad was placed between the skin and the ultrasonic probe to keep the ultrasonic probe away from the shock wave energy field. The B-ultrasonic wave source locked the target stone through the gel pad, and the lithotripter Dornier Compact Delta II was used for lithotripsy. The extracorporeal shock wave lithotripsy was completed under the whole process of B-ultrasonic monitoring. All patients completed the surgery under ultrasound monitoring, and there were no abnormalities in the ultrasound probe during the surgery. The average stone size was 0.60 ± 0.21 cm, the surgical time was 39.8 ± 13.8 min, and the total energy of lithotripsy was 7.41 ± 4.35 J. There were no obvious complications in all patients after the surgery. After 2 weeks of ultrasound examination, the success rate of lithotripsy in 21 patients reached 85.7%. We believe that the use of the gel pad increases the distance between the ultrasonic probe and the skin, leaving the probe away from the shock wave energy field, avoiding the damage of the shock wave source to the ultrasonic probe, and does not affect the monitoring effect of ultrasound on stones and the success rate of lithotripsy, which is worthy of further promotion in the field of children's urinary stones. [ABSTRACT FROM AUTHOR]

The Dahua Lou loom, pivotal to Nanjing Yunjin weaving, constitutes an integral part of global intangible cultural heritage. Its intricate weaving technique remains unmatched by modern machinery, marking it as a vital cultural artefact warranting protection. However, current virtual interactive systems grapple with adequately demonstrating its craftsmanship due to limitations like system iteration, multi-system integration, and data interoperability. To address these challenges, this study proposes a method that synergizes knowledge ontology, virtual reality technology, and data-driven design.Knowledge ontology enables enhanced management, reuse, and wide-ranging dissemination of domain knowledge, improving system interoperability. This methodology is utilized in constructing the loom model, animation demonstration, and in integrating it into the virtual interactive system. This multifaceted application of knowledge ontology significantly bolsters the system's efficiency and optimizes its development, maintenance, and integration processes.This research provides crucial advancements in domain knowledge modeling, 3D visualization, and virtual reality interactive systems, playing a significant role in preserving cultural heritage. Despite certain limitations, it offers an immersive, intuitive, and enriched design experience. The study concludes with a critique of the developed system, discussions on the encountered challenges, and future research directions include improving and expanding the knowledge ontology based on the opinions and practical experiences of domain experts, enhancing system compatibility, and conducting broader evaluations. [ABSTRACT FROM AUTHOR]

This paper investigates the interplay between the algebraic properties of the rings, the combinatorial properties of their corresponding zero-divisor graphs, and the associated Hermitian matrix of such graphs. For a finite ring R, its zero-divisor graph may contain both directed edges and undirected edges; such graphs are called mixed graphs. The Hermitian matrices of mixed graphs are natural generalizations of the adjacency matrices of undirected graphs. In this paper, we completely determine the structure and the Hermitian eigenvalues of the zero-divisor graph Γ (D × R) by using the structure and the Hermitian eigenvalues of the zero-divisor graph Γ (R) . As applications, we investigate Γ (D × R) for some special R and extend some known results on this topic. [ABSTRACT FROM AUTHOR]

The translocation of a polymer through a pore that is much smaller than its size is a fundamental and actively researched topic in polymer physics. An understanding of the principles governing polymer translocation provides important guidance for various practical applications, such as the separation and purification of polymers, nanopore-based single-molecule deoxyribonucleic acid/ribonucleic acid(DNA/RNA) sequencing, transmembrane transport of DNA or RNA, and infection of bacterial cells by bacteriophages. The past several decades have seen great progresses on the study of polymer translocation. Here we present an overview of theoretical, experimental, and simulational stduies on polymer translocation, focusing on the roles played by several important factors, including initial polymer conformations, external fields, polymer topology and architectures, and confinement degree. We highlight the physical mechanisms of different types of polymer translocations, and the main controversies about the basic rules of translocation dynamics. We compare and contrast the behaviors of force-induced versus flow-induced translocations and the effects of unknotted versus knotted polymers. Finally, we mention several opportunities and challenges in the study of polymer translocation. [ABSTRACT FROM AUTHOR]

Nanjing Yunjin, a highly representative Chinese silk weaving handicraft, was included in the Representative List of Intangible Cultural Heritage of Humanity in 2009. However, due to modern silk weaving technology advancements, aesthetic style evolution, and inadequate public recognition of Yunjin culture, the art faces a decline in market recognition and practitioners, posing a risk to its preservation. Addressing this issue necessitates product innovation, efficient knowledge storage, management, and utilization, and enhancing public cultural identity for Yunjin. Following the government's "productive conservation" concept for intangible cultural heritage (ICH) projects in the handicraft category, this study uses Yunjin video resources as the primary data source. It constructs a domain knowledge graph (DKG) using an ontological approach to effectively and systematically preserve Yunjin knowledge. Furthermore, the study leverages Neo4j network topology to reveal intricate and diverse relationships within Yunjin knowledge, uncovering rich cultural connotations. Lastly, Cypher is employed for semantic queries, graph visualization, and domain expert evaluation. Evaluation results indicate that the constructed Yunjin DKG meets quality standards, supporting the development of products that align with market aesthetics while preserving Yunjin's intrinsic cultural values. This approach fosters a complementary relationship between economic benefits and ICH. Additionally, the Yunjin DKG application presents a technical path for knowledge interconnection, integration, and discovery within ICH projects in the handicraft category. [ABSTRACT FROM AUTHOR]

Compacted graphite iron has been used more and more in industry because of its excellent mechanical properties, especially in the automobile industry to manufacture high performance and light weight diesel engine. However, the excellent mechanical properties of compacted graphite iron cause the tool life greatly shortened. In this research, the influence of tool structure on tool life is studied by simulation and experiment. Firstly, turning simulations for tools with different rake angles, clearance angles, and cutting edge radius were performed by the software Deform. Then orthogonal simulation was used to optimize the tool parameters. In addition, according to the tool parameters obtained in the simulation, a batch of tools with rake angles of 13°, 15°, and 19° were prepared, and their performances in turning compacted graphite cast iron were studied. The experiment results show that the life of the tool with 19° rake angle was 11.73% and 16.94% higher than that of the tool with 13° rake angle and 15° rake angle, respectively. And it has the minimum cutting force and lower wear value of the flank face. Our research is especially aimed at compacted graphite iron, which might have some function in improving the processing efficiency of compacted graphite iron. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks are booming with the development of computer technology, network communication technology, and sensor technology. However, the question of how to use fewer nodes to achieve maximum coverage still exists. In this paper, a two-layer Surrogate-Assisted Phasmatodea Population Evolution (SAPPE) is proposed for 3D coverage of wireless sensors by combining the characteristics of meta-heuristic algorithms and surrogate models. In this algorithm, Radial Basis Function Networks are used to construct the surrogate model, and the two surrogate models are global surrogate-assisted and local surrogate-assisted, respectively. The global-surrogate model is used to smooth the fitness function, and the local surrogate-assisted model is used to find the optimal value accurately. They use the same archive DataBase (DB) to store particle positions and true fitness values. However, the number of particles involved in the creation of the surrogate-assisted model is different. Seven benchmark functions are used to test and analyze the algorithm, and the results show that the algorithm has good performance. Also, the algorithm verified the significance of the algorithm using Wilcoxon rank test. The result shows that the proposed algorithm is effective compared with PPE, PSO, PPSO, FMO, and BA. This paper compares the number of nodes and coverage radius using different algorithms to ensure maximum coverage. The result shows that the SAPPE algorithm has better performance in terms of 3D coverage. [ABSTRACT FROM AUTHOR]

A photo-controlled approach is developed to regulate the interpenetrating polymer network (IPN) topology by varying the connecting structure between the first and second networks. The approach is based on multifunctional inimer (Vinyl-oNB-Br) possessing three moieties, i.e., an acrylate-based double bond for incorporation within a polymer network, a Br group for grafting polymerization to get connect-IPN (c-IPN), and an o-nitrobenzyl spacer for photocleaving to convert the c-IPN to disconnected-IPN (d-IPN) with UV light irradiation. Such design allows for finely controlling the connection degree between two networks. A systematic study on the mechanical property of a series of samples with different connection degrees thus can be conducted. The results reveal that decreasing the connecting degree between two networks of IPN made a negligible contribution to materials' mechanical properties. [ABSTRACT FROM AUTHOR]

Fast Fourier transform (FFT) is a well-known algorithm that calculates the discrete Fourier transform (DFT) of discrete data and is an essential tool in scientific and engineering computation. Due to the large amounts of data, parallelly executing FFT in graphics processing unit (GPU) can effectively optimize the performance. Following this approach, FFTW and some other FFT packages were designed, but the fixed computation pattern makes it hard to utilize the computing power of GPU. Additionally, the memory access pattern is not optimized to alleviate the bottleneck of data exchange. Motivated by these challenges, we propose an efficient GPU-accelerated multidimensional FFT library to achieve better performance in this paper. We present a detailed and clear implementation strategy and optimize FFT by having as few memory transfers as possible. The data will be reshuffled on the CPU, and the access mode is also optimized to coordinate with the GPU memory access pattern. Several optimizations are also demonstrated to enhance the performance of our approach for varying FFT sizes, and the evaluation shows that our approach consistently outperforms rocFFT with a speedup of about 25% to 250% on average in AMD Instinct MI100 GPU. [ABSTRACT FROM AUTHOR]

This paper introduces an efficient and flexible 3D FFT framework for state-of-the-art multi-GPU distributed-memory systems. In contrast to the traditional pure MPI implementation, the multi-GPU distributed-memory systems can be exploited by employing a hybrid multi-GPU programming model that combines MPI with OpenMP to achieve effective communication. An asynchronous strategy that creates multiple streams and threads to reduce blocking time is adopted to accelerate intra-node communication. Furthermore, we combine our scheme with the GPU-Aware MPI implementation to perform GPU-GPU data transfers without CPU involvement. We also optimize the local FFT and transpose by creating fast parallel kernels to accelerate the total transform. Results show that our framework outperforms the state-of-the-art distributed 3D FFT library, being up to achieve 2× faster in a single node and 1.65× faster using two nodes. [ABSTRACT FROM AUTHOR]

Generalized matrix multiplication (GEMM) is one of the most widely utilized algorithms in many fields such as deep learning, astrophysics, signal processing, and advanced physical analysis. It plays an extremely important role in deep learning, especially for convolutional neural networks, because many of the calculations involved are converted into matrix multiplications in order to speed up the computation process leveraging the parallel processing power of GPUs. However, the sizes of the converted matrices are generally too small to fully occupy the GPU. In this paper, we focus on the impact of GEMM on deep learning and propose a framework for calculating a batch of GEMMs in one kernel function so as to increase GPU occupancy. A suite of tiling strategies is designed for a batch of matrices with small dimensions and variable sizes. The tiling strategy is determined by considering Kernel Occupancy for each GEMM to fit different matrix sizes and GPU architectures. Then the GoogLeNet is implemented using MIOpen as a representative case and the batched GEMM framework is integrated into it. The experimental results show that compared with MAGMA, the elapsed time of the GoogLeNet optimized with our framework obtains 2.60 × and 2.79 × speedup on AMD Radeon Instinct MI50 and MI100 GPU, respectively. [ABSTRACT FROM AUTHOR]

Enterotoxigenic Escherichia coli (ETEC) in humans and animals colonizes the intestine and thereafter secrets heat-stable enterotoxin (ST) with or without heat-labile enterotoxin (LT), which triggers massive fluid and electrolyte secretion into the gut lumen. The crosstalk between the cyclic nucleotide-dependent protein kinase/cystic fibrosis transmembrane conductance regulator (cAMP or cGMP/CFTR) pathway involved in ETEC-induced diarrhea channels, and the canonical Wnt/β-catenin signaling pathway leads to changes in intestinal stem cell (ISC) fates, which are strongly associated with developmental disorders caused by diarrhea. We review how alterations in enterotoxin-activated ion channel pathways and the canonical Wnt/β-catenin signaling pathway can explain inhibited intestinal epithelial activity, characterize alterations in the crosstalk of cyclic nucleotides, and predict harmful effects on ISCs in targeted therapy. Besides, we discuss current deficits in the understanding of enterotoxin-intestinal epithelial cell activity relationships that should be considered when interpreting sequelae of diarrhea. [ABSTRACT FROM AUTHOR]

RNase2 is the member of the RNaseA family most abundant in macrophages. Here, we knocked out RNase2 in THP-1 cells and analysed the response to Respiratory Syncytial Virus (RSV). RSV induced RNase2 expression, which significantly enhanced cell survival. Next, by cP-RNAseq sequencing, which amplifies the cyclic-phosphate endonuclease products, we analysed the ncRNA population. Among the ncRNAs accumulated in WT vs KO cells, we found mostly tRNA-derived fragments (tRFs) and second miRNAs. Differential sequence coverage identified tRFs from only few parental tRNAs, revealing a predominant cleavage at anticodon and d-loops at U/C (B1) and A (B2) sites. Selective tRNA cleavage was confirmed in vitro using the recombinant protein. Likewise, only few miRNAs were significantly more abundant in WT vs RNase2-KO cells. Complementarily, by screening of a tRF & tiRNA array, we identified an enriched population associated to RNase2 expression and RSV exposure. The results confirm the protein antiviral action and provide the first evidence of its cleavage selectivity on ncRNAs. [ABSTRACT FROM AUTHOR]

A new 2D coordination polymer, namely{[Cd2(BDC)2(bmb)2]·H2O}n (1) (H2BDC = 1,4-benzenedicarboxylic acid and bmb = 1,4-bis(2-methyl-1H-imidazol-1-yl)butane), has been prepared and full characterized. Coordination polymer 1 has 2D layer, which was further extended into 3D supramolecular motif through the π–π packing interactions. Coordination polymer 1 illustrated effectively photocatalytic performance to the disintegration of dyes Rhodamine B (Rh B), methyl orange (MO) and methylene blue (MB). Coordination polymer 1 can remove the dye MB with 90.37% after 100 min under simulated UV light and its catalytic feature conforms to the first order kinetics model. In addition, the possible mechanism of the catalytic degradation toward MB was suggested through the trapping experiments and LC–MS methods. [ABSTRACT FROM AUTHOR]

To improve the wear resistance of 6061 aluminum alloys, we reported the fabrication of Fe–Al coatings by laser surface alloying with mixed Fe and Al powders. The alloyed coatings mainly consisted of Fe4Al13, FeAl, Fe3Al and α-Al phases. Due to its high specific gravity, the Fe-rich melt segregated at the bottom of the molten pool during the laser process, and special microstructures characterized by a bright white stripe at the interfacial zone were formed. Additionally, the nonuniform exothermic reactions occurring along the width of the interfacial zone resulted in the formation of a rough sawtooth interface. The typical microstructures from the top layer to the interfacial zone of the alloyed coatings were investigated to explore the formation and solidification processes of the molten pool. Additionally, the microhardness of the coatings markedly improved with increasing Fe concentration in the mixed powders, reaching 720 HV0.2. Moreover, a 92.3% reduction in the volume loss of the 70Fe–30Al coating compared with that of the substrate significantly enhanced the wear resistance. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to evaluate the value of machine learning models (ML) based on MRI radiomics in diagnosing early parotid gland injury in primary Sjögren’s syndrome (pSS).A total of 164 patients (114 in the training cohort and 50 in the testing cohort) with pSS (n=82) or healthy controls (HC) (n=82) were enrolled. Itksnap software was used to perform two-dimensional segmentation of the bilateral parotid glands on T1-weighted (T1WI) and fat-suppressed T2-weighted imaging (fs-T2WI) images. A total of 1548 texture features of the parotid glands were extracted using radiomics software. A radiomics score (Radscore) was constructed and calculated. A t-test was used to compare the Radscore between the two groups. Finally, five machine learning models were trained and tested to identify early pSS parotid injury, and the performance of the machine learning models was evaluated by calculating the acceptance operating curve (ROC) and other parameters.The Radscores between the pSS and HC groups showed significant statistical differences (p<0.001). Among the five machine learning models, the Extra Trees Classifier (ETC) model performed high predictive efficacy in identifying early pSS parotid injury, with an AUC of 0.87 in the testing set.MRI radiomics–based machine learning models can effectively diagnose early parotid gland injury in primary Sjögren’s syndrome.Methods: This study aimed to evaluate the value of machine learning models (ML) based on MRI radiomics in diagnosing early parotid gland injury in primary Sjögren’s syndrome (pSS).A total of 164 patients (114 in the training cohort and 50 in the testing cohort) with pSS (n=82) or healthy controls (HC) (n=82) were enrolled. Itksnap software was used to perform two-dimensional segmentation of the bilateral parotid glands on T1-weighted (T1WI) and fat-suppressed T2-weighted imaging (fs-T2WI) images. A total of 1548 texture features of the parotid glands were extracted using radiomics software. A radiomics score (Radscore) was constructed and calculated. A t-test was used to compare the Radscore between the two groups. Finally, five machine learning models were trained and tested to identify early pSS parotid injury, and the performance of the machine learning models was evaluated by calculating the acceptance operating curve (ROC) and other parameters.The Radscores between the pSS and HC groups showed significant statistical differences (p<0.001). Among the five machine learning models, the Extra Trees Classifier (ETC) model performed high predictive efficacy in identifying early pSS parotid injury, with an AUC of 0.87 in the testing set.MRI radiomics–based machine learning models can effectively diagnose early parotid gland injury in primary Sjögren’s syndrome.Results: This study aimed to evaluate the value of machine learning models (ML) based on MRI radiomics in diagnosing early parotid gland injury in primary Sjögren’s syndrome (pSS).A total of 164 patients (114 in the training cohort and 50 in the testing cohort) with pSS (n=82) or healthy controls (HC) (n=82) were enrolled. Itksnap software was used to perform two-dimensional segmentation of the bilateral parotid glands on T1-weighted (T1WI) and fat-suppressed T2-weighted imaging (fs-T2WI) images. A total of 1548 texture features of the parotid glands were extracted using radiomics software. A radiomics score (Radscore) was constructed and calculated. A t-test was used to compare the Radscore between the two groups. Finally, five machine learning models were trained and tested to identify early pSS parotid injury, and the performance of the machine learning models was evaluated by calculating the acceptance operating curve (ROC) and other parameters.The Radscores between the pSS and HC groups showed significant statistical differences (p<0.001). Among the five machine learning models, the Extra Trees Classifier (ETC) model performed high predictive efficacy in identifying early pSS parotid injury, with an AUC of 0.87 in the testing set.MRI radiomics–based machine learning models can effectively diagnose early parotid gland injury in primary Sjögren’s syndrome.Conclusion: This study aimed to evaluate the value of machine learning models (ML) based on MRI radiomics in diagnosing early parotid gland injury in primary Sjögren’s syndrome (pSS).A total of 164 patients (114 in the training cohort and 50 in the testing cohort) with pSS (n=82) or healthy controls (HC) (n=82) were enrolled. Itksnap software was used to perform two-dimensional segmentation of the bilateral parotid glands on T1-weighted (T1WI) and fat-suppressed T2-weighted imaging (fs-T2WI) images. A total of 1548 texture features of the parotid glands were extracted using radiomics software. A radiomics score (Radscore) was constructed and calculated. A t-test was used to compare the Radscore between the two groups. Finally, five machine learning models were trained and tested to identify early pSS parotid injury, and the performance of the machine learning models was evaluated by calculating the acceptance operating curve (ROC) and other parameters.The Radscores between the pSS and HC groups showed significant statistical differences (p<0.001). Among the five machine learning models, the Extra Trees Classifier (ETC) model performed high predictive efficacy in identifying early pSS parotid injury, with an AUC of 0.87 in the testing set.MRI radiomics–based machine learning models can effectively diagnose early parotid gland injury in primary Sjögren’s syndrome. [ABSTRACT FROM AUTHOR]

Gland macrophages are primed for gland development and functions through interactions within their niche. However, the phenotype, ontogeny, and function of steady-state salivary gland (SG) macrophages remain unclear. We herein identified CD11c+ and CD11c− subsets among CD64+ macrophages in steady-state murine SGs. CD11c− macrophages were predominant in the SGs of embryonic and newborn mice and decreased with advancing age. CD11c+ macrophages were rarely detected in the embryonic period, but rapidly expanded after birth. CD11c+, but not CD11c−, macrophage numbers decreased in mice treated with a CCR2 antagonist, suggesting that CD11c+ macrophages accumulate from bone marrow-derived progenitors in a CCR2-dependent manner, whereas CD11c− macrophages were derived from embryonic progenitors in SGs. CD11c+ and CD11c− macrophages strongly expressed colony-stimulating factor (CSF)-1 receptor, the injection of an anti-CSF-1 receptor blocking antibody markedly reduced both subsets, and SGs strongly expressed CSF-1, indicating the dependency of SG resident macrophage development on CSF-1. The phagocytic activity of SG macrophages was extremely weak; however, the gene expression profile of SG macrophages indicated that SG macrophages regulate gland development and functions in SGs. These results suggest that SG CD11c+ and CD11c− macrophages are developed and instructed to perform SG-specific functions in steady-state SGs. [ABSTRACT FROM AUTHOR]

Flash floods cause great harm to people's lives and property safety. Rainfall is one of the main causes of flash floods in small watersheds. The uncertainty of rainfall events results in inconsistency between the traditional single rainfall pattern and the actual rainfall process, which poses a great challenge for the early warning and forecasting of flash floods. To carry out the effective flash flood early warning and forecasting, this paper proposes a novel rainfall pattern by coupling total rainfall and peak rainfall intensity based on copula functions, i.e., the rainfall pattern of risk probability combination (RPRPC). On this basis, the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) hydrological model is used to simulate the rainfall-runoff process, the trial algorithm is used to calculate the critical rainfall (CR), and the optimistic-general-pessimistic (O–G-P) early warning mode considering the decision maker's risk preference is proposed. The small watershed of Xinxian in Henan province, China, is taken as a case study for calculation. The results show that the RPRPC is feasible and closer to the actual rainfall process than the traditional rainfall pattern, Frank copula function is the best for determining the joint distribution function of total rainfall and peak rainfall intensity, and the HEC-HMS model can be applied to small watersheds in hilly areas. Additionally, both RPRPC and antecedent soil moisture condition (ASMC) have influence on CR, and the variation of RPRPC will change the influence of ASMC on CR. Finally, the effectiveness of O–G-P early warning mode is verified. [ABSTRACT FROM AUTHOR]

High performance LINPACK (HPL) benchmark is used to evaluate the maximum floating-point performance of a computer cluster. Since the performance of the graphics processing unit (GPU) has been improved rapidly, many researchers start to optimize HPL benchmark through GPU to maximize system utilization. Nevertheless, it is difficult to determine the optimal combination of parameters in this process due to the complexity of the input. Therefore, running HPL on a heterogeneous system is time-consuming and is not flexible under different hardware components. So we propose a simulation model of HPL in this paper. The model is no longer limited by hardware components and able to simulate the execute process of HPL across different computing node in heterogeneous GPU-enhanced clusters at any scale. It can also assist researchers in evaluating the floating-point performance quickly and provide a reference for the hardware investment. [ABSTRACT FROM AUTHOR]

The "solid-liquid" behavior of vitrimers have not been systematically investigated. Herein, a series of "solid-liquid" vitrimers bearing varying contents of dynamic boronic ester bonds were synthesized via thiol-ene click reactions. These vitrimers allow for flexibile modulation of their network structures and thus show a range of intriguing properties including high stretchability, flexible transition from elasticity to plasticity, strong strain rate dependence, and solid-liquid performance. The dynamic association rate of boronic ester bonds within these vitrimers could be apparently accelerated via increasing the content of boronic ester, which could be used to shape-program the flat vitrimer films into various complex 3D structures just with external force. Materials with such versatile dynamic behavior may open up a range of new applications. [ABSTRACT FROM AUTHOR]

The dynamics of entanglement measured by concurrence and quantum correlation described by quantum discord under Ornstein-Uhlenbeck noise are investigated in several different cases. Our study mainly found that for both anti-ferromagnetic and ferromagnetic cases, the value of concurrence could be increased significantly by the cooperative effect of XZX+YZY and XZY-YZX three-site interactions. For anti-ferromagnetic case, XZY-YZX interaction has a positive effect on increasing the value of concurrence, nonetheless, for the ferromagnetic case, the XZX+YZY interaction plays a major role in enlarging and sustaining the value of concurrence. Whereas XZY-YZX interaction has a negative effect on concurrence for small J. The Non-Markovian case is much more effective than short-time limit or Markov limit case to preserve both concurrence and quantum discord. For small dissipation, the short-time limit is better than the Markov limit to prolong the lifetime of concurrence and quantum discord. For large dissipation, the Markov limit case is a preferable approximation. The entanglement sudden death time could be prolonged in the ferromagnetic case more than in the anti-ferromagnetic case. [ABSTRACT FROM AUTHOR]

The relationship between a balanced time perspective and life satisfaction has been demonstrated in previous studies, yet the potential mechanisms underlying this relationship remain unclear. The current study tested whether a latent factor "temporal negative affect" underlay anxiety and depression and whether this latent factor mediated the relationship between balanced time perspective and life satisfaction. To assess life satisfaction, time perspectives, anxiety and depression, a total of 995 university students aged from 17 to 25 years were recruited. Structural equation modelling analysis demonstrated that the latent factor "temporal negative affect" consisted of anxiety and depression and played a mediating role in the relationship between balanced time perspective and life satisfaction. These findings can deepen our understanding of how time perspectives potentially influence life satisfaction, offering new directions towards enhancing well-being in health and disease. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the clinical efficacy and long-term outcomes associated with the treatment of hepatic vein (HV)-type Budd–Chiari syndrome (BCS) via accessory HV (AHV) recanalization. Methods: In total, 26 HV-type BCS patients underwent AHV recanalization between July 2014 and December 2019 at our hospital, while 73 HV-type BCS patients without compensatory AHV underwent main HV (MHV) recanalization and served as controls in the present study. Short- and long-term clinical outcomes were compared. Results: AHV and MHV recanalization approaches were both associated with 100% technical success rates, with one recanalization procedure being performed per patient. Respective clinical success rates for the AHV and MHV recanalization approaches were 96.2% and 94.5% (P = 0.744). Re-obstruction rates were comparable between these two approaches at 20% and 34.8%, respectively (P = 0.17). Primary cumulative 1-, 2-, and 5-year patency rates in the AHV group were 96.0%, 91.6%, and 76.3%, respectively, whereas in the MHV group, these three respective rates were 87.0%, 78.6%, and 58.6% (P = 0.048). Secondary cumulative 1-, 2-, and 5-year patency rates in the AHV group were 96.0%, 96.0%, and 96.0%, respectively, whereas in the MHV group, they were 97.1%, 97.1%, and 81.8%, respectively (P = 0.289). Cumulative 1-, 2-, and 5-year survival rates for AHV group patients were 96.0%, 96.0%, and 96.0%, respectively, while for the MHV group, these respective rates were 98.6%, 95.2%, and 89.7% (P = 0.462). Conclusion: HV-type BCS can be safely and effectively treated via AHV recanalization, which may achieve longer patency relative to MHV recanalization. [ABSTRACT FROM AUTHOR]

The incidence of disease arising from food-borne pathogens is increasing continuously and has become a global public health problem. Rapid and accurate identification of food-borne pathogens is essential for adopting disease intervention strategies and controlling the spread of epidemics. Surface-enhanced Raman spectroscopy (SERS) has attracted increasing interest due to the attractive features including simplicity, rapid measurement, and high sensitivity. It can be used for rapid in situ sensing of single and multicomponent samples within the nanostructure-based confined space by providing molecular fingerprint information and has been demonstrated to be an effective detection strategy for pathogens. This article aims to review the application of SERS to the rapid sensing of food-borne pathogens in food matrices. The mechanisms and advantages of SERS, and detection strategies are briefly discussed. The latest progress on the use of SERS for rapid detection of food-borne bacteria and viruses is considered, including both the labeled and label-free detection strategies. In closing, according to the current situation regarding detection of food-borne pathogens, the review highlights the challenges faced by SERS and the prospects for new applications in food safety. [ABSTRACT FROM AUTHOR]

Voltage-gated sodium channels are currently recognized as one of the targets of analgesics. Magnolol (Mag), an active component isolated from Magnolia officinalis, has been reported to exhibit analgesic effects. The objective of this study was to investigate whether the analgesic effect of Mag was associated with blocking Na+ channels. Inflammatory pain was induced by the injection of carrageenan into the hind paw of mice. Mag was administered orally. Mechanical hyperanalgesia was evaluated by using von Frey filaments. Na+ currents and neuronal excitability in acutely isolated mouse dorsal root ganglion (DRG) neurons were recorded with the whole-cell patch clamp technique. Results showed that Mag (10 ~ 40 mg/kg) dose-dependently inhibited the paw edema and reduced mechanical pain in the inflammatory animal model. Injection of carrageenan significantly increased the amplitudes of TTX-sensitive and TTX-resistant Na+ currents. Compared with the carrageenan group, Mag inhibited the upregulation of two types of Na+ currents induced by carrageenan in a dose-dependent manner. Mag 40 mg/kg shifted the inactivation curves of two types of Na+ currents to hyperpolarization and returned to normal animal level without changing their activation curves. Mag 40 mg/kg significantly reduced the percentage of cells firing multiple spikes and inhibited the neuronal hyperexcitability induced by carrageenan. Our data suggest that the analgesic effect of Mag may be associated with a decreased neuronal excitability by blocking Na+ current. [ABSTRACT FROM AUTHOR]

The human RNase3 is a member of the RNaseA superfamily involved in host immunity. RNase3 is expressed by leukocytes and shows broad-spectrum antimicrobial activity. Together with a direct antimicrobial action, RNase3 exhibits immunomodulatory properties. Here, we have analysed the transcriptome of macrophages exposed to the wild-type protein and a catalytic-defective mutant (RNase3-H15A). The analysis of differently expressed genes (DEGs) in treated THP1-derived macrophages highlighted a common pro-inflammatory "core-response" independent of the protein ribonucleolytic activity. Network analysis identified the epidermal growth factor receptor (EGFR) as the main central regulatory protein. Expression of selected DEGs and MAPK phosphorylation were inhibited by an anti-EGFR antibody. Structural analysis suggested that RNase3 activates the EGFR pathway by direct interaction with the receptor. Besides, we identified a subset of DEGs related to the protein ribonucleolytic activity, characteristic of virus infection response. Transcriptome analysis revealed an early pro-inflammatory response, not associated to the protein catalytic activity, followed by a late activation in a ribonucleolytic-dependent manner. Next, we demonstrated that overexpression of macrophage endogenous RNase3 protects the cells against infection by Mycobacterium aurum and the human respiratory syncytial virus. Comparison of cell infection profiles in the presence of Erlotinib, an EGFR inhibitor, revealed that the receptor activation is required for the antibacterial but not for the antiviral protein action. Moreover, the DEGs related and unrelated to the protein catalytic activity are associated to the immune response to bacterial and viral infection, respectively. We conclude that RNase3 modulates the macrophage defence against infection in both catalytic-dependent and independent manners. [ABSTRACT FROM AUTHOR]

Objective: We describe an unusual case of corticosteroid-responsive autoimmune meningoencephalomyelitis with linear perivascular gadolinium enhancement but in the absence of anti- glial fibrillary acidic protein (GFAP) antibodies (ABs) in the cerebral spinal fluid (CSF).Methods: The patient's clinical symptoms, brain magnetic resonance imaging (MRI) features, serum and CSF analysis and treatment were reviewed.Results: A 47-year-old female experienced a subacute course with bilateral lower limbs weakness, unsteady walking, and dysuria. Brain MRI revealed typical radial perivascular gadolinium enhancement extending from the lateral ventricles to the white matter; MRI spine revealed lesions distributed in the entire spinal cord. Immunohistochemical staining of a brain biopsy revealed CD3+ T cells and CD20+ B cells cuffing around brain vessels, accompanied by CD68+ macrophages. CSF was negative for anti-GFAP ABs while serum was positive for anti-GFAP ABs (1:100). The patient responded well to corticosteroid.Conclusions: There are no uniform diagnostic criteria for autoimmune GFAP astrocytopathy. Our case suggested the importance of typical MRI findings in the diagnosis of this rare disease. Early treatments are very important to alleviate symptoms. [ABSTRACT FROM AUTHOR]

Methane generation has a significant impact on climate change. Aquatic plants have been widely studied for their role in methane emissions. Most research has focused on the contribution of the plant itself whereas the potential involvement of the phyllosphere microbiota associated with aquatic plants in methanogenesis remains largely unexplored. This study investigated the phyllosphere microbiota on both the top and bottom sides of lotus (Nelumbo nucifera), a commonly found aquatic plant in Asia, sampled from two urban ponds, using sequencing for both the 16S rRNA gene and the methanogenesis functional marker gene. Methanogenesis potential was assessed through laboratory-based 13C labeling experiments. Results show that methanogenic archaea were successfully detected on the floating lotus leaves but not on the standing leaves. Among the methanogens detected, Methanobacterium was identified as the predominant group, with significantly higher relative abundance on the bottom sides of floating leaves compared to the surrounding pond water. This study demonstrates the metabolic activity of the phyllosphere methanogens of floating lotus. The microbiota associated with the bottom sides of floating leaves exhibited the ability to produce methane and incorporate 13C carbon into methane during incubation. Overall, this study provides the first compelling genetic and functional evidence for the existence of epiphytic methanogens on the phyllosphere of aquatic plants. Hence, the phyllosphere of floating-leaved macrophytes represents a previously unrecognized habitat for methanogens and a potential microbial source of methane at the water–atmosphere interface. [ABSTRACT FROM AUTHOR]

Objective: Rate-limiting enzyme 3b-hydroxysteroid dehydrogenase type 1 (3βHSD1) encoded by HSD3B1 catalyzes the transition of dehydroepiandrosterone (DHEA) to dihydrotestosterone (DHT). The HSD3B1 (1245C) variant renders 3bHSD1 of resistant to ubiquitination and degradation, leading to a large amount of protein accumulation in the cell. Multiple clinical studies have shown that this mutation was correlated with resistance to androgen-deprivation therapy in prostate cancer. However, the results were not consistent depending on different treatment strategy and in some researches, the number of observed cases was relatively small.Methods: To determine the effects of HSD3B1 (1245C) variant on resistance to androgen-deprivation therapy in prostate cancer, we performed a meta-analysis of the available literature. Electronic database searches identified appropriately designed studies that detected HSD3B1 in prostate cancer. We conducted a systematic search of studies in the following databases: PubMed, and EMBASE published until August 10, 2020 using the following search terms: (HSD3B1 AND ((((prostate cancer) OR prostatic neoplasm) OR prostatic carcinoma) OR prostatic cancer).Results: Eight researches were included in this research. The result validated that the HSD3B1 (1245C) variant allele was associated with a shorter PFS (HR, 1.97; 95% CI, 1.39-2.79; P = 0.0001) (homozygous wild-type group) in men with prostate cancer when treated with ADT, however, a higher PFS (HR, 0.68; 95% CI, 0.48-0.96; P = 0.03) when treated with ADT and CYP17A1 inhibitor.Conclusion: The HSD3B1 (1245C) variant is a predictor of ADT plus CYP17A1 inhibitor response in prostate cancer. [ABSTRACT FROM AUTHOR]

Nb-modified Mo–V–Nb tri-component oxides were synthesized for catalytic oxidative dehydrogenation of Cα–OH lignin model compounds. Nb–O octahedron as the nucleation center refined the Mo–V–Nb oxide particles with TiO2 as the support and changed the selective oxidation performance of the catalyst to a certain extent. However, the conversion of Cα–OH lignin model compounds was significantly reduced under the catalysis of Mo–V–Nb–O with too much Nb content. The experimental results showed that the effect of Nb in the three-component oxides not only reduced the crystal size of the catalyst, but also more importantly adjusted the valence state of vanadium. The valence state of vanadium in vanadyl octahedron formed based on Nb nucleation center was adjusted. The ratio between tetravalent vanadium and pentavalent vanadium was directly proportional to the conversion rate. The catalytic mechanism was that there were oxygen vacancies at the catalytic active sites of V4+, which provided a basis for the generation of reactive oxygen species in the oxidative dehydrogenation reaction. [ABSTRACT FROM AUTHOR]

Aiming at the problem of object recognition caused by small object scale, multi-interaction (occlusion), and strong hiding characteristics in the scene analysis task, an object-region-enhanced network based on deep learning was proposed. The network integrated two core modules designed for the task: object area enhancement strategy and black-hole-filling strategy. The former directly corresponded the object region with high semantic confidence to the local region of the specific category channel of the convolutional feature image. Weighted features were used to improve contextual relationships, and difficult object regions were identified. The latter avoided the mistake of identifying some difficult areas as additional background classes by masking additional background classes. The results showed that the modular design scheme improved the overall parsing performance of the model by replacing the modules, and the two strategies were applied to other existing scenario parsing networks. A unified framework is proposed for handling scene resolution tasks. Benefiting from the modular design approach, the proposed algorithm improves overall performance by replacing convolution or detection modules. Object enhancement and black hole filling are applied to other systems to improve the system's ability to parse objects. Object area enhancement methods are used to recall objects that are not recognized in a standard split network. Black hole fill techniques can be used to resolve pixels that are incorrectly categorized into additional background classes that do not exist. Therefore, a variety of contextual semantic fusion strategies have certain reference value in the theoretical level of computer vision. More critically, this method has certain reference significance for the design and development of robust and practical application systems. [ABSTRACT FROM AUTHOR]

Pennisetum sinese Roxb (P. sinese) is an efficient and economic energy crop for its high productivity, and has been well studied in its application in phytoremediation and fodder production. However, little is known about how P. sinese plantation and fermented manures of P. sinese-feed livestock affect the composition of soil bacterial and fungal communities. In this study, 16S rRNA/ITS1 gene-based Illumina Miseq sequencing was employed to compare the bacterial and fungal community structure among soils that had been subjected to uncultivated control (CK), 2-year P. sinese plantation (P), and P. sinese plantation combined with the use of organic manures (P-OM) in a "P. sinese—breeding industry" ecological agriculture farm. The results found microbial communities were altered by P. sinese plantation and fertilization. The P. sinese plantation resulted in increased Actinobacteria and Planctomycetes abundance. Comparatively, significant increased abundance of Chloroflexi, Firmicutes, Nitrospirae, and Euryarchaeota, and genes related with nitrogen and carbon metabolic pathways based on PICRUSt prediction was observed in P-OM soil. Fungal compositions suggested a markedly increased abundance of Ascomycota in P soil. Potential organic matter decomposers Candida, Thermoascus, and Aspergillus were enriched in P soil, indicating the enhanced role of fungi in litter decomposition. Redundancy analysis suggested that soil properties (NH4+-N, total nitrogen, organic matter content, and soil water content) significantly correlated with the changes of microbial compositions (P < 0.05). These results highlight the divergence of microbial communities occurs during P. sinese-based plantation, implying functional diversification of soil ecosystem in P. sinese fields. [ABSTRACT FROM AUTHOR]

Heteroepitaxial oxide-based nanocomposite films possessing a variety of functional properties have attracted tremendous research interest. Here, self-assembled vertically aligned nanocomposite (Pr0.5Ba0.5MnO3)1-x:(CeO2)x (x = 0.2 and 0.5) films have been successfully grown on single-crystalline (001) (La,Sr)(Al,Ta)O3 substrates by the pulsed laser deposition technique. Self-assembling behavior of the nanocomposite films and atomic-scale interface structure between Pr0.5Ba0.5MnO3 matrix and CeO2 nanopillars have been investigated by advanced electron microscopy techniques. Two different orientation relationships, (001)[100]Pr0.5Ba0.5MnO3//(001)[1-10]CeO2 and (001)[100]Pr0.5Ba0.5MnO3//(110)[1-10]CeO2, form between Pr0.5Ba0.5MnO3 and CeO2 in the (Pr0.5Ba0.5MnO3)0.8:(CeO2)0.2 film along the film growth direction, which is essentially different from vertically aligned nanocomposite (Pr0.5Ba0.5MnO3)0.5:(CeO2)0.5 films having only (001)[100]Pr0.5Ba0.5MnO3//(001)[1-10]CeO2 orientation relationship. Both coherent and semi-coherent Pr0.5Ba0.5MnO3/CeO2 interface appear in the films. In contrast to semi-coherent interface with regular distribution of interfacial dislocations, interface reconstruction occurs at the coherent Pr0.5Ba0.5MnO3/CeO2 interface. Our findings indicate that epitaxial strain imposed by the concentration of CeO2 in the nanocomposite films affects the self-assembling behavior of the vertically aligned nanocomposite (Pr0.5Ba0.5MnO3)1-x:(CeO2)x films. [ABSTRACT FROM AUTHOR]

The aim of single-image super-resolution is to recover a high-resolution image based on a low-resolution image. Deep convolutional neural networks have largely enhanced the reconstruction performance of image super-resolution. Since the input image is always bicubic-interpolated, the main weakness of deep convolutional neural networks is that they are time-consuming. Moreover, fast convolutional neural networks can perform real-time image super-resolution but are unable to achieve reliable performance. To address those drawbacks, we propose a real-time image super-resolution method with good reconstruction performance. We replace the default upsampling method (bicubic interpolation) with a pixel shuffling layer. Local and global residual connections are taken to guarantee better performance. As shown in Fig. 1, our proposed method is not only fast but also accurate. [ABSTRACT FROM AUTHOR]

Key message: A major radish QTL (Fwr1) for fusarium wilt resistance was fine-mapped. Sequence and expression analyses suggest that a gene encoding a serine/arginine-rich protein kinase is a candidate gene for Fwr1. Fusarium wilt resistance locus 1 (Fwr1) is a major quantitative trait locus (QTL) mediating the resistance of radish inbred line 'B2' to Fusarium oxysporum, which is responsible for fusarium wilt. We previously detected Fwr1 on radish linkage group 3 (i.e., chromosome 5). In this study, a high-resolution genetic map of the Fwr1 locus was constructed by analyzing 354 recombinant F2 plants derived from a cross between 'B2' and '835', the latter of which is susceptible to fusarium wilt. The Fwr1 QTL was fine-mapped to a 139.8-kb region between markers FM82 and FM87 in the middle part of chromosome 5. Fifteen candidate genes were predicted in this region based on a sequence comparison with the 'WK10039' radish reference genome. Additionally, we examined the time-course expression patterns of these predicted genes following an infection by the fusarium wilt pathogen. The ORF4 expression level was significantly higher in the resistant 'B2' plants than in the susceptible '835' plants. The ORF4 sequence was predicted to encode a serine/arginine-rich protein kinase and includes SNPs that result in nonsynonymous mutations, which may have important functional consequences. This study reveals a novel gene responsible for fusarium wilt resistance in radish. Further analyses of this gene may elucidate the molecular mechanisms underlying the fusarium wilt resistance of plants. [ABSTRACT FROM AUTHOR]

In this paper, a novel size-dependent functionally graded (FG) cylindrical shell model is developed based on the nonlocal strain gradient theory in conjunction with the Gurtin-Murdoch surface elasticity theory. The new model containing a nonlocal parameter, a material length scale parameter, and several surface elastic constants can capture three typical types of size effects simultaneously, which are the nonlocal stress effect, the strain gradient effect, and the surface energy effects. With the help of Hamilton's principle and first-order shear deformation theory, the non-classical governing equations and related boundary conditions are derived. By using the proposed model, the free vibration problem of FG cylindrical nanoshells with material properties varying continuously through the thickness according to a power-law distribution is analytically solved, and the closed-form solutions for natural frequencies under various boundary conditions are obtained. After verifying the reliability of the proposed model and analytical method by comparing the degenerated results with those available in the literature, the influences of nonlocal parameter, material length scale parameter, power-law index, radius-to-thickness ratio, length-to-radius ratio, and surface effects on the vibration characteristic of functionally graded cylindrical nanoshells are examined in detail. [ABSTRACT FROM AUTHOR]

The metal-organic frameworks MIL-101 and sulfo-MIL-101 were used to modify graphite paste electrodes (GPEs) to obtain sensors for determination of dopamine (DA). Taking advantage of the catalytic activity of metal-organic frameworks (MOFs) and of the electrical conductivity of graphite, the modified GPEs show enhanced voltammetric responses, and the GPE modified with the sulfo-MOF displays superior sensitivity when operated at a working potential of −0.4 to 0.8 V (vs. Ag/AgCl). The sensor works in the 0.07 to100 μM DA concentration range and has a 43 nM detection limit. It is concluded that the sulfo group provides open sites for efficient electrostatic and hydrogen bonding interactions, which facilitates electron transfer. [ABSTRACT FROM AUTHOR]

Editor's Note: this Article has been retracted; the Retraction Note is available at https://doi.org/10.1038/s41598-023-32251-x [ABSTRACT FROM AUTHOR]

Traditional data-driven deep learning models often struggle with high training costs, error accumulation, and poor generalizability in complex physical processes. Physics-informed deep learning (PiDL) addresses these challenges by incorporating physical principles into the model. Most PiDL approaches regularize training by embedding governing equations into the loss function, yet this depends heavily on extensive hyperparameter tuning to weigh each loss term. To this end, we propose to leverage physics prior knowledge by "baking" the discretized governing equations into the neural network architecture via the connection between the partial differential equations (PDE) operators and network structures, resulting in a PDE-preserved neural network (PPNN). This method, embedding discretized PDEs through convolutional residual networks in a multi-resolution setting, largely improves the generalizability and long-term prediction accuracy, outperforming conventional black-box models. The effectiveness and merit of the proposed methods have been demonstrated across various spatiotemporal dynamical systems governed by spatiotemporal PDEs, including reaction-diffusion, Burgers', and Navier-Stokes equations. Most physics-informed deep learning models alleviate the poor generalizability of pure data-driven models by minimizing residuals of the governing equations. In this work the authors propose to leverage physics priors, by embedding the discretized governing equations into the neural network architecture, which improves the generalizability and long-term prediction accuracy. [ABSTRACT FROM AUTHOR]

As a precision goniometer, photoelectric encoder plays an important role in rotational inertial navigation system (RINS). The encoder is used to measure the rotate angle of rotating mechanism for attitude calculation and feedback of motor control. However, the experiment shows that there are position-related errors in the encoder output, so calibration is necessary in high precision applications. This paper presents a calibration method designed by the characteristics of encoder errors and the structure of a tri-axis RINS. In RINS, the gyro sensitive axis can be coincided with the motor axis by gimbals rotation, and then the gyro and the photoelectric encoder measure the same angle, so the error can be calculated as the difference between the encoder output and the integral of gyro output. The error will be analyzed through Fourier method, then the error will be fitted by least squares method and a harmonic model will be established. The verification experiments demonstrate that the angle measurement error is reduced from ± 40″ to ± 2″, and the attitude output error drops 75″. The calibration method is proved to be experimentally effective. [ABSTRACT FROM AUTHOR]

A ternary coupling material of phosphomolybdic acid cluster bridging carbon dots and polyaniline (CDs-PMo12-PANI) nanofibers is designed to improve electrochemical performance of PANI. The proton-rich PMo12 bonds with PANI via electrostatic interaction to promote the proton-doping level of PANI. The reversible multi-electron redox reactivity of PMo12 contributes to improving pseudo-capacitance of PANI. PMo12 cluster bonds with carbon dots via chemisorption interaction to achieve the immobilization of hydrosoluble PMo12. PMo12 cluster keeps a bridge connection between polyaniline chain and carbon dots. The good electric conductivity of carbon dots and the distinct bonding interface of CDs-PMo12-PANI contribute to improving rate capability and cycling stability of PANI. CDs-PMo12-PANI achieves high specific capacitance of 479 F g−1 at 1 A g−1, reasonable rate capacitance retention of 69.3% when increasing current density from 0.5 to 10 A g−1 and reasonable cycling capacitance retention of 68.1% after 1000 cycles at 5 A g−1. CDs-PMo12-PANI shows higher electrochemical performance of capacitance, rate capability and cycling stability than PANI, PMo12-PANI and CDs-PANI. All-solid-state flexible supercapacitor based on CDs-PMo12-PANI electrode exhibits high specific capacitance of 118.6 F g−1 and specific energy of 37.1 W h kg−1 at 1 A g−1. A single unit of high-performance supercapacitor can directly drive various electronic devices, indicating effective electrochemical energy storage of CDs-PMo12-PANI. [ABSTRACT FROM AUTHOR]

To reveal the internal discipline and accurately identify the inflection point, the Poisson-Nernst-Planck equations combined with the Navier-Stokes equation are employed and a method based on the horizontal angle of the tangent line and the distance from a pointcut to the origin is presented. Utilizing a micromachining technique and a photopolymerization reaction, a polyacrylamide gel plug is integrated into a microchannel to form a micro-nanofluidic chip. With the chip, FITC concentration experiments are developed with the initial concentration of 10 nM. Experimental testing confirms the results and demonstrates that the concentration is increased at first and then decreased with the increasing of the electric potential. That variation trend should be attributed to a balance between the repulsive force and the electrophoresis effect. The research results also demonstrate that upon increasing the voltage, the horizontal angle first decreases and then increases corresponding with the reverse trend of the distance. For a given micro-nanochannel, the peak ion concentration can be obtained through decreasing the horizontal angle and increasing the distance. The results will help determine peak voltage. [ABSTRACT FROM AUTHOR]