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In this paper, three new types of fuzzy covering-based rough set models are proposed. First, the membership-degree-based fuzzy covering rough set is defined in the fuzzy covering approximation space by separately comparing the membership degree of each object belonging to the approximated fuzzy set with those of the component fuzzy sets in the fuzzy covering for the same object. Second, the membership-function-based fuzzy covering rough set is obtained by globally comparing the membership function of the approximated fuzzy set with those of the component fuzzy sets in the fuzzy covering. Finally, the membership-function-based fuzzy covering rough set model is generalized to the fuzzy β-covering approximation space. The properties of these new rough set models are discussed. Furthermore, the relationship between these new rough sets and the relationship between the new rough set and Pawlak rough set are described.

The purpose is to improve the application of museum robots in museum scenes, enhance the service capabilities of robots in museums, break tourists’ boring concepts of museum environment, manual explanation, services, etc., and promote tourists’ exhibition experience. A method for sentiment analysis of humanoid robots in museums is proposed by studying the transformation of museums with the help of artificial intelligence (AI) technology, as well as the function and significance of museums in history education. First, the function of museums in history education and the role of AI in constructing intelligent museums are described. Second, on account of the multimodal sentiment analysis method of speech and emotion, a scenario model of the visitor museum is established. An uncertain reasoning method for robot service tasks based on Multi-entity Bayesian network (MEBN) is also proposed. Finally, the proposed model is validated by experiments. The results show that compared with the recognition rates of Arousal and Valence dimensions, the consistency correlation coefficient value of the Kalman filter is higher. The Consistency Correlation Coefficient (CCC) value of the Arousal dimension is 0.703, and the CCC value of the Valence dimension is 0.766. Besides, in different tour times, the proportion of services that tourists want to be provided with varies in different emotional states. From time [Formula: see text]1 to time [Formula: see text]2, the proportion of tourists who want to hear explanations of cultural relics dropped by 11.5%, while the proportion of tourists who want to be provided with tea service increased by 24%. This indicates that when the Kalman filter algorithm performs continuous emotion recognition of a multimodal fusion, the final emotion recognition accuracy is higher, and emotion analysis can help humanoid robots to be more intelligent and humanized. The proposed sentiment analysis based on the multimodal analysis and MEBN’s uncertainty reasoning method for robot service tasks not only broadens the practical application field of intelligent robots under human–computer interaction technology but also has important research significance for the innovative education development of museum history education.

Histone H3 lysine 27 methylation catalyzed by polycomb repressive complex 2 (PRC2) is conserved from fungi to humans and represses gene transcription. However, the mechanism for recognition of methylated H3K27 remains unclear, especially in fungi. Here, we found that the bromo-adjacent homology (BAH)-plant homeodomain (PHD) domain containing protein BAH–PHD protein 1 (BP1) is a reader of H3K27 methylation in the cereal fungal pathogen Fusarium graminearum. BP1 interacts with the core PRC2 component Suz12 and directly binds methylated H3K27. BP1 is distributed in a subset of genomic regions marked by H3K27me3 and co-represses gene transcription. The BP1 deletion mutant shows identical phenotypes on mycelial growth and virulence, as well as similar expression profiles of secondary metabolite genes to the strain lacking the H3K27 methyltransferase Kmt6. More importantly, BP1 can directly bind DNA through its PHD finger, which might increase nucleosome residence and subsequently reinforce transcriptional repression in H3K27me3-marked target regions. A phylogenetic analysis showed that BP1 orthologs are mainly conserved in fungi. Overall, our findings provide novel insights into the mechanism by which PRC2 mediates gene repression in fungi, which is distinct from the PRC1-PRC2 system in plants and mammals.

Background The blade unit of the tridimensional rotational flow sieve tray (TRST) makes the fluid form a rotational–perforated flow. The analysis of the flow properties of the unit is helpful to understand the hydrodynamic characteristics of TRST. Methods The gas–liquid concurrent flow field was studied using the multi-fluid VOF method. The rotational and perforated flows at each section were analyzed based on the section rotational flow ratios. Significant findings The section rotational flow ratio for the gas phase was between 0.6 and 0.85, and the transition section of the rotational and perforated flows of the liquid phase was z = 30 mm. The relationships between TRST and blade unit were clarified. The simulation performed for analyzing the mass transfer and structural optimization of the blade unit and TRST.

Diclofenac (DCF), one of the most current and widely used nonsteroidal anti-inflammatory drugs (NSAIDs), has been frequently detected in aquatic environments worldwide. However, the ecotoxicological effects of DCF on freshwater invertebrates remain largely unknown. In the present study, Corbicula fluminea were exposed to environmentally relevant concentrations of DCF (0, 2, 20 and 200 µg/L) for 28 days, and the potential adverse effects of DCF on siphoning behavior, antioxidant responses and apoptosis were investigated. Our results showed that the siphon efficiencies of clams were significantly suppressed by DCF exposure. DCF exerted neurotoxicity via reducing the activity of acetylcholinesterase (AChE) in gills and digestive gland of C. fluminea. Exposure to DCF induced antioxidant stress and led to increased malondialdehyde (MDA) levels in both tissues of C. fluminea. Transcriptional alterations of apoptosis-related genes indicated that DCF might induce apoptosis by triggering mitochondrial apoptotic pathway. Our findings will help enhance our awareness of the negative effects of DCF on freshwater bivalves and highlight the ecological risks of DCF in freshwater ecosystems.

An efficient catalytic asymmetric cascade cycloaddition reaction of arylalkynols with dioxopyrrolidines was developed. This reaction was achieved using Au(I) and (R)-BINOL-Ti(IV) bimetallic catalysts and exclusively delivered a series of chiral oxo-bridged bicyclic benzooxacine compounds in up to 86% yield with 96% ee as well as >33:1 dr. Meanwhile, three new σ bonds and three new stereogenic centers were formed in a one-pot process.

This study aims to construct a robust prognostic model for adult adrenocortical carcinoma (ACC) by large‐scale multiomics analysis and real‐world data. The RPPA data, gene expression profiles and clinical information of adult ACC patients were obtained from The Cancer Proteome Atlas (TCPA), Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Integrated prognosis‐related proteins (IPRPs) model was constructed. Immunohistochemistry was used to validate the prognostic value of the IPRPs model in Fudan University Shanghai Cancer Center (FUSCC) cohort. 76 ACC cases from TCGA and 22 ACC cases from GSE10927 in NCBI’s GEO database with full data for clinical information and gene expression were utilized to validate the effectiveness of the IPRPs model. Higher FASN (P = .039), FIBRONECTIN (P

In population-oriented ergonomics product design and musculoskeletal kinetics analysis, digital spine models of different shape, pose and material property are in great demand. The purpose of this study was to construct a parameterized finite element spine model with adjustable spine shape and material property. We used statistical shape model approach to learn inter-subject shape variations from 65 CT images of training subjects. Second order polynomial regression was used to model the age-dependent changes in vertebral material property derived from spatially aligned CT images. Finally, a parametric spine generator was developed to create finite element instances of different shapes and material properties. For quantitative analysis, the generalization ability to emulate spine shapes of different people was evaluated by fitting into 17 test CT images. The median fitting accuracy was 0.8 for Dice coefficient and 0.43 mm for average surface distance. The age-dependent bone density regression curve was also proved to well agree with large population statistics data. Finite element simulation was performed to compare how shape parameters influenced the biomechanics distribution of spine. The proposed parametric finite element whole spine model will assist the design process of new devices and biomechanical simulation towards a wide range of population. peerReviewed

Background End-stage renal disease (ESRD) is the final stage during the development of renal failure. Depression is the most common psychiatric disorder in patients with ESRD, which in turn aggravates the progression of renal failure, however, its underlying mechanism remains unclear. This study aimed to reveal the pathogenesis and to discover novel peripheral biomarkers for ESRD patients with depression through metabolomic analysis. Methods Ultra-high-performance liquid chromatography coupled with mass spectrometry (UPLC-MS) was used to explore changes of serum metabolites among healthy controls, ESRD patients with or without depression. The differential metabolites between groups were subjected to clustering analysis, pathway analysis, receiver operating characteristic (ROC) curve analysis. Results A total of 57 significant serum differential metabolites were identified between ESRD patients with or without depression, which were involved in 19 metabolic pathways, such as energy metabolism, glycerolipid metabolism, and glutamate-centered metabolism. Moreover, the area under the ROC curve of gentisic acid, uric acid, 5-hydroxytryptamine, 2-phosphoglyceric acid, leucyl-phenylalanine, propenyl carnitine, naloxone, pregnenolone, 6-thioxanthene 5'-monophosphate, hydroxyl ansoprazole, zileuton O-glucuronide, cabergoline, PA(34:2), PG(36:1), probucol and their combination was greater than 0.90. Conclusions Inflammation, oxidative stress and energy metabolism abnormalities, glycerolipid metabolism, and glutamate-centered metabolism are associated with the pathogenesis of ESRD with depression, which may be promising targets for therapy. Furthermore, the identified differential metabolites may serve as biomarkers for the diagnosis of ESRD patients with depression.

Bacteria and fungi are dominant members of environmental microbiomes. Various bacterial-fungal interactions (BFIs) and their mutual regulation are important factors for ecosystem functioning and health. Such interactions can be highly dynamic, and often require spatiotemporally resolved assessments to understand the interplay which ranges from antagonism to mutualism. Many of these interactions are still poorly understood, especially in terms of the underlying chemical and molecular interplay, which is crucial for inter-kingdom communication and interference. BFIs are highly relevant under agricultural settings; they can be determinative for crop health. Advancing our knowledge related to mechanisms underpinning the interactions between bacteria and fungi will provide an extended basis for biological control of pests and pathogens in agriculture. Moreover, it will facilitate a better understanding of complex microbial community networks that commonly occur in nature. This will allow us to determine factors that are crucial for community assembly under different environmental conditions and pave the way for constructing synthetic communities for various biotechnological applications. Here, we summarize the current advances in the field of BFIs with an emphasis on agriculture.

With the advancement of science and technology, digital technology and Internet of Things network technology have been developed rapidly, and multimedia technology has also been widely used. Multimedia formats such as digital TV and elevator posters are shaking up traditional media. At the same time, many media operation models and multimedia technologies are combined to plan operational strategies, determine operational goals, and change the traditional media structure to achieve commercial profits and society benefit. However, due to limitations in the existing operating model or unreasonable technical solutions, it is not easy to maximize the value of multimedia technology. The XML-based database has been submitted, and it will carry out the business requirements of the transaction network and the business platform of the transaction network. Integrated management mechanism is analyzed and applied. The framework design includes parallel quota processing module, update processing module, result processing module, and storage library and database connection management module. The department runs multiple parts of the system together and completes the database. The development of cloud database is based on cloud computing. It can effectively fill the shortcomings and gaps of traditional database storage and processing, and it can also provide high-reciprocity databases to provide storage and management services. It has high reliability. Cloud servers use fair weighted rounding algorithms to achieve load balancing and use the in-memory database Redis to realize terminal data caching. After a comprehensive test of the system, the system can perform all functions normally, and it has good performance and stable operation.

Sulfamethoxazole (SMX), a broad-spectrum antibiotic, has been widely used in the treatment and prevention of infection caused by bacteria in recent years. The present study was aimed to evaluate the response mechanisms to SMX stress in gills and digestive gland of Corbicula fluminea (O. F. Müller, 1774). To this end, clams were exposed to environmentally relevant concentrations of SMX (0, 1, 10 and 100 μg/L) for 7 and 28 days, and siphon behavior, tissue-specific enzymatic and transcriptional changes were assayed. Our results showed that exposure to SMX significantly suppressed filtration rate and acetylcholinesterase (AChE) activity, activated antioxidant defense system and elevated transcription of several genes related to cell apoptosis in gills and digestive gland of clams. In general, SMX at environmentally relevant concentrations exhibited a negative impact on siphon behavior and induced neurotoxicology, oxidative stress and cell apoptosis in C. fluminea. The current study will help broaden our understanding of the ecotoxicity of SMX on freshwater bivalves.

Ras GTPases act as molecular switches to control various cellular processes by coupling integrated signals in eukaryotes. Activities of Ras GTPases are triggered by Ras GTPase guanine nucleotide exchange factors (RasGEFs) in general, whereas the role of RasGEF in plant pathogenic fungi is largely unknown. In this study, we characterized the only RasGEF protein in Fusarium graminearum, FgCdc25, by combining genetic, cytological and phenotypic strategies. FgCdc25 directly interacted with RasGTPase FgRas2, but not FgRas1, to regulate growth and sexual reproduction. Mutation of the FgCDC25 gene resulted in decreased toxisome formation and deoxynivalenol (DON) production, which was largely depended on cAMP signalling. In addition, FgCdc25 indirectly interacted with FgSte11 in FgSte11-Ste7-Gpmk1 cascade, and the ΔFgcdc25 strain totally abolished the formation of infection structures and was nonpathogenic in planta, which was partially recovered by addition of exogenous cAMP. In contrast, FgCdc25 directly interplayed with FgBck1 in FgBck1-MKK1-Mgv1 cascade to negatively control cell wall integrity. Collectively, these results suggest that FgCdc25 modulates cAMP and MAPK signalling pathways and further regulates fungal development, DON production and plant infection in F. graminearum.

Clear cell renal cell carcinoma (ccRCC) is the most common and highly malignant pathological type of kidney cancer. We sought to establish a metabolic signature to improve post‐operative risk stratification and identify novel targets in the prediction models for ccRCC patients. A total of 58 metabolic differential expressed genes (MDEGs) were identified with significant prognostic value. LASSO regression analysis constructed 20‐mRNA signatures models, metabolic prediction models (MPMs), in ccRCC patients from two cohorts. Risk score of MPMs significantly predicts prognosis for ccRCC patients in TCGA (P

A cocatalyst-controlled divergent cascade cycloaddition reaction was developed for the synthesis of two different complex oxygen-containing heterocyclic compounds from arylalkynols and dioxopyrrolidienes in the presence of Au(I) catalyst. Using two different cocatalysts, Ni(OTf)2 and (rac)-phosphoric acid, two completely different products, spiroketals and oxa-bridged eight-membered cyclic ethers, were precisely constructed with high yields and good stereoselectivities, respectively. These methods feature simple and high efficiency, good chemoselectivity and mild conditions in one-pot.

The interval data from different surveyed persons for one linguistic word can reflect the intra- and inter-uncertainties of the word. This study shows how to construct shadowed set models for linguistic words based on the surveyed interval data. Firstly, corresponding to the popularly used fuzzy sets for linguistic words, four kinds of shadowed sets are introduced according to their shapes and named as the normal, the left-shoulder, the right-shoulder, and the non-cored shadowed sets. A data-driven approach that utilizes different statistics to determine the shapes and parameters of the shadowed set models is then proposed. The proposed data-driven approach includes two methods; the first is the tolerance limit method depending on the mean and standard deviation of the remaining interval data after pre-processing, whilst the other is the percentile method relying on the percentiles of the remaining interval data. Additionally, to evaluate the modelling performance, three novel indices are presented to measure the uncertainty-capture capability and accuracy of the constructed shadowed set models. Finally, the proposed approach is applied to two real-world problems . One is the modelling of 32 words in a codebook, and the other is the modelling of the thermal feeling words. The proposed methods are compared with other interval data driven methods, e.g. the enhanced interval approach and the fuzzy statistic method. Our results show that the proposed percentile method performs better in both applications. The proposed approach can also be applied to some other linguistic word modelling applications when it is reasonable to adopt shadowed sets as the words’ models.

The blade unit of a tridimensional rotational flow sieve tray (TRST) is the origin for the rotational–perforated flow. The flow field of that was investigated using the Multi-fluid VOF method. The water fractions, and the gas perforation velocity on the blade unit were investigated. The liquid phase distribution in the jet and mixed flow is more dispersed than that in film and jet flow. The gas–liquid two-phase velocity fluctuated with the radial distance. The rotational and perforated flows on the blade unit were analyzed separately by the local rotational flow ratio . The variation range of the ratio for the gas-phase was 0.6 – 0.85, and that for the liquid-phase is 0.2 – 0.8. Based on the Q criterion, the vortices were mainly concentrated near the sieve holes. The simulation provides an important theoretical basis for the mass transfer investigation and structural optimization of the blade unit.

In the context of multicultural information, to explore and analyze the use effect of voice interactive educational robot in the classroom of adolescent students, and the physical and mental impact of movie characters on adolescent students, and to lay the foundation for studying the positive development of adolescents, under the guidance of positive psychology theory, the relationship between positive psychology and adolescent mental health is analyzed, the application of adolescent educational robot is discussed, and the relationship between adolescent educational robot combined with movies characters and positive development of adolescent is analyzed. The questionnaire is used to collect data, including the questionnaire on the influence of movie characters on the positive development of adolescents, the questionnaire of pre- and postpopularization of artificial intelligence in primary and secondary schools, and the satisfaction questionnaire of voice interactive educational robot. The reliability and validity of the questionnaire are analyzed. The results show that students who watch more than 20 movies are 20% in grade one and that is only 10% in grade three. 79% of the students think that the movie characters have an impact on themselves. The distribution of the number of the grade two students exposed to the movie is relatively uniform, 40% of them watch 10-20 movies, and 82% of them think that the movie characters have an impact on themselves; the Cronbach coefficient of classroom satisfaction questionnaire is 0.929 > 0.9, the average value of the correlation of total correction items of the corresponding item is 0.612 > 0.5, the Kaiser–Meyer–Olkin measurement value is 0.812 > 0.6, and the Sig value is 0.000

Computer tomography (CT) has been routinely used for decades in clinical neuroimaging. Compared to Magnetic resonance imaging (MR), CT is more readily available and more cost-effective, but the soft tissue contrast is much lower. In brain CT images, the unclear soft-tissue boundaries and the high noise level hamper accurate segmentation of the gray and white matter, leaving obstacles for the subsequent geometrical quantification of brain structures. To address this challenge, this paper specifically acquires same-patient CT and MR image pairs and proposes a multi-task learning model for simultaneous tissue segmentation and modality transfer. We aim to use the modality transfer task to learn corresponding MR and CT features which assists the segmentation task to achieve more accurate results than single modality learning. Moreover, we add a Shannon entropy loss function to the training loss to further combat the high noise influence and reduce the fragmentation problem of the segmentation results. Experimental results proved that our multi-task framework achieves more accurate segmentation than the single segmentation task, and the Shannon entropy loss results in much fewer broken brain regions than the state-of-the-art (SOTA) U-net method. Our study provides a useful tool for clinical neural CT image analysis.

Reconstructing personalized models of the human body is a key step for digital twin modeling of sports motion. There have been many studies reconstructing the body surface models based on video sequences, but these algorithms lack the modeling of internal structures (bones, muscles, blood vessels, etc.). Some researchers map internal organ structures into the 3D point cloud scanning of the body surface, but such mapping does not guarantee realistic tissue deformation and is not developed for video processing. This paper focuses on the video-based reconstruction of a personalized full-anatomy digital model in sports motion. Our method creates a four-dimensional (4D) model of the moving process composed of the 3D models of each time moment. We first use a deep network to regress the body surface of each time point and then estimate the internal structures by registering a previously constructed deformable human anatomy atlas to the body surfaces. To mimic realistic internal structure deformation, we applied articulated linear transform to the bony structures to avoid bone shape distortion and applied smooth nonlinear transform to the soft tissue to mimic the motion deformation. We also developed an intersection removal method to prevent the possible intersection between bones and soft tissues during the deformation. Our method is tested with athletes' sports videos and automatically generates full-anatomy motion models which cannot be achieved by previous methods. Our method also surpasses the existing video-based body surface modeling method by providing additional internal structures. The 4D human motion model constructed by our method is useful in sports modeling, biomechanics simulation, wearable device design, etc.

A new type of composite tridimensional rotational flow sieve tray is proposed. The flow pattern and operation domain of the tray were defined and divided by the image shooting method, combined with the standard deviation of the pressure difference sequence. There are membrane–drip column and foam–embolic flow in the TRST area of the internal packing–type tray, while bubbly and milk froth-ribbon flow are present in the packing area of the external packing-type tray. This study focused on the influence of the tray structure parameters on the pressure drop. Under the experimental operating conditions, the dry pressure drop was within 160 Pa, while the wet pressure drop was within 900 Pa. Under the same structural parameters, the internal packing–type pressure drop of the tray was higher than that of the external packing-type tray. A mathematical model of the pressure drop between dry and wet trays was established.

Diclofenac (DCF), one of typical non-steroidal anti-inflammatory drugs (NSAIDs), has been frequently detected in various environmental media. Nevertheless，the potential endocrine disrupting effects of DCF on fish were poorly understood. In the present study, zebrafish embryos/larvae were used as a model to evaluate the adverse effects of DCF on development and thyroid system. The results demonstrated that DCF only significantly decreased the heart rate at 72 h post-fertilization (hpf), exhibiting limited influence on the embryonic development of zebrafish. Treatment with DCF significantly reduced whole-body thyroxine (T4) levels, and changed transcriptional levels of several genes related to the hypothalamic-pituitary-thyroid (HPT) axis. These findings provide important information regarding to the mechanisms of DCF-induced developmental toxicity and thyroid disruption in fish.