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PurposeAs an advanced calculation methodology, reliability-based multidisciplinary design optimization (RBMDO) has been widely acknowledged for the design problems of modern complex engineering systems, not only because of the accurate evaluation of the impact of uncertain factors but also the relatively good balance between economy and safety of performance. However, with the increasing complexity of engineering technology, the proposed RBMDO method gradually cannot effectively solve the higher nonlinear coupled multidisciplinary uncertainty design optimization problems, which limits the engineering application of RBMDO. Many valuable works have been done in the RBMDO field in recent decades to tackle the above challenges. This study is to review these studies systematically, highlight the research opportunities and challenges, and attempt to guide future research efforts.Design/methodology/approachThis study presents a comprehensive review of the RBMDO theory, mainly including the reliability analysis methods of different uncertainties and the decoupling strategies of RBMDO.FindingsFirst, the multidisciplinary design optimization (MDO) preliminaries are given. The basic MDO concepts and the corresponding mathematical formulas are illustrated. Then, the procedures of three RBMDO methods with different reliability analysis strategies are introduced in detail. These RBMDO methods were proposed for the design optimization problems under different uncertainty types. Furtherly, an optimization problem for a certain operating condition of a turbine runner blade is introduced to illustrate the engineering application of the above method. Finally, three aspects of future challenges for RBMDO, namely, time-varying uncertainty analysis; high-precision surrogate models, and verification, validation and accreditation (VVA) for the model, are discussed followed by the conclusion.Originality/valueThe scope of this study is to introduce the RBMDO theory systematically. Three commonly used RBMDO-SORA methods are reviewed comprehensively, including the methods' general procedures and mathematical models.

In mechanical engineering, most mechanical structural systems are composed of many parts, so their structures are complex. When a mechanical structure fails, it is generally caused by various failure modes. When designers want to improve the quality of mechanical products in the design of mechanical products, reliability analysis can play an important role. It is indispensable in the design and manufacture of mechanical products, engineering use, repair and maintenance. Research on time-varying reliability of mechanical structures is of great significance in improving the quality of mechanical products and bringing more economic benefits to engineering. It has received extensive attention in both academic fields and practical engineering applications. This paper takes the time-varying reliability analysis of mechanical structures based on performance degradation as the research topic, focusing on the reliability analysis methods and techniques of mechanical structures such as Gamma degradation process, material P-S-N curve, mixed Copula function, and nested Copula function. The main research content is divided into three parts. (1) The Gamma degradation process and the P-S-N material probabilistic fatigue life curve are used when establishing the strength degradation random model of the mechanical system. It provides the theoretical basis of strength degradation level for time-varying reliability analysis of mechanical structure based on performance degradation. (2) Combine the mixed Copula function and the nested Copula function to establish a comprehensive failure correlation analysis model of the mechanical system. It provides a theoretical basis for failure correlation for time-varying reliability analysis of mechanical structures based on performance degradation. (3) The time-varying reliability analysis of the one-stage gear transmission system in the engineering example is carried out. Researched and analyzed the time-varying reliability of the large and small gears in the one-stage gear transmission system and the mechanical structure of the system itself under the correlation of strength degradation and failure.

There are uncertain factors affecting structural performance in actual engineering. The uncertainty-based design and optimization (UBDO) is an effective strategy to deal with these uncertain factors and improve the reliability of structural systems. In UBDO, some non-probabilistic uncertainties are difficult to be described with a certain distribution information. In this situation, the interval uncertainty analysis (IUA) can be utilized to perform the reliability evaluation in UBDO. Generally, if IUA was performed directly in UBDO, the efficiency of UBDO with IUA (UBDO-IUA) cannot satisfy the requirements of actual engineering. To tackle this problem, in this study, an UBDO-IUA strategy based on the Taylor expansion is proposed. The particle swarm global optimization algorithm is also introduced in the given method as the optimization solver to further improve the computational efficiency. Two examples are introduced to show the utilization of the given method.

Viral infectious diseases are a devastating and continuing threat to human and animal health. Receptor binding is the key step for viral entry into host cells. Therefore, recognizing viral receptors is fundamental for understanding the potential tissue tropism or host range of these pathogens. The rapid advancement of single-cell RNA sequencing (scRNA-seq) technology has paved the way for studying the expression of viral receptors in different tissues of animal species at single-cell resolution, resulting in huge scRNA-seq datasets. However, effectively integrating or sharing these datasets among the research community is challenging, especially for laboratory scientists. In this study, we manually curated up-to-date datasets generated in animal scRNA-seq studies, analyzed them using a unified processing pipeline, and comprehensively annotated 107 viral receptors in 142 viruses and obtained accurate expression signatures in 2 100 962 cells from 47 animal species. Thus, the VThunter database provides a user-friendly interface for the research community to explore the expression signatures of viral receptors. VThunter offers an informative and convenient resource for scientists to better understand the interactions between viral receptors and animal viruses and to assess viral pathogenesis and transmission in species. Database URL: https://db.cngb.org/VThunter/.

Generally, the traditional uncertainty-based multidisciplinary design optimization (UBMDO) methods are based on the probability distribution information of random design variables and parameters. However, the probability distribution information needs to be obtained based on a large number of sample points. In many engineering structure design problems, for some uncertainties, it is difficult to obtain enough experimental samples to construct their accurate probability distribution, only the variation interval of them can be known. In this situation, mixed uncertainties exist in the engineering systems. Furthermore, with the increase in the complexity of engineering systems, these mixed uncertainties will even produce cumulative effects along with the internal coupling of the systems themselves. To tackle these challenges, the random and interval variables (RIV) are considered and a strategy of UBMDO with RIV (UBMDO-RIV) is proposed in this study. In the given method, the evaluation of uncertainty constraints is performed in the worst case scenario due to interval uncertainties. Meanwhile, the classic decoupling strategy for UBMDO, the framework of sequential design and uncertainty evaluation (SDUE), is introduced into UBMDO-RIV to reduce the computational burden. The engineering case study is utilized to illustrate the application of the proposed strategy.

Sooty moulds are a widespread group of saprophytic ascomycetes that obtain nutrients from honeydew excreted by sap-feeding insects and coat plant tissue with mycelia. Research on sooty moulds has focused on fungal morphology and phylogeny-based taxonomy, but little research has been conducted on the community structure. In this study, the PacBio sequencing platform was used to systematically analyse the fungal and bacterial diversity of the sooty mould community on camphor trees at two sampling sites. Six dominant sooty mould genera were identified, of which three genera of Dothideomycetes were enriched only in diseased samples, while three genera of Eurotiomycetes were present in both healthy and diseased samples. Bacterial diversity and co-occurrence network analysis indicated that the sooty moulds had an effect on the leaf surface bacterial communities but not on the endophyte communities. There was a close correlation between the six dominant pathogenic groups and bacteria in the soot layer. Transcriptomic data from Cinnamomum camphora samples showed that the sooty moulds that did not penetrate plant cells not only affected plant photosynthesis but also induced plant defence responses. This study systematically studied the microbial community of sooty moulds, indicating the close relationship between sooty moulds and the bacterial communities.

In this paper, the mathematical model and algorithm based on knowledge forgetting curve are studied. Through the analysis of the current mathematical modeling and application of “knowledge forgetting curve”, the artificial intelligence method of fuzzy mathematics knowledge and differential modeling is adopted. This paper puts forward the mathematical model and algorithm design of the new “knowledge forgetting curve”, which aims to improve the intelligence of the software and bring a new learning experience for the teaching evaluation of the education system in colleges and universities. The fuzzy logic theory is applied to the teaching evaluation system of higher learning pedagogy, according to pedagogy and other related theories, combined with the current teaching evaluation indicators of colleges and universities, the teaching evaluation indicators of higher learning education are set according to certain requirements. The sample wood data is divided into two parts by using the fuzzy logic principle, and the training model is obtained by training the sample data in the evaluation system, and the training model is used to intelligently evaluate and analyze the prediction data.

Zinc oxide nanoparticles (ZnO-NPs) are metal-based nanomaterials, but their long-term effects on plant growth and the soil environment in the field remain unclear with most previous studies using short-term laboratory and glasshouse studies. In this study, we used a field experiment to examine the long-term effects of ZnO-NPs in a soil-wheat (Triticum aestivum) system. It was found that although ZnO-NPs had no significant effect on either yield or the concentration of other nutrients within the grain, the application of ZnO-NPs significantly increased Zn concentrations. Indeed, for grain, the application of ZnO-NPs to both the soil and foliage (SFZnO) (average of 33.1 mg/kg) significantly increased grain Zn concentrations compared to the the control treatment (21.7 mg/kg). Using in situ analyses, nutrients were found to accumulate primarily in the crease tissue and the aleurone layer of the grain, regardless of treatment. Specifically, the concentration of Zn in the aleurone layer for the SFZnO treatment was 2-3 times higher than that in the control, being300 mg/kg, whilst the Zn concentration in the crease tissue was ca. 600 mg/kg in the SFZnO treatment, being two times higher than for the control. Although the application of ZnO-NPs increased the total Zn within the grain, it did not accumulate within the grain as ZnO-NPs with this being important for food safety, but rather mainly as Zn-phytate, with the remainder of the Zn complexed with either cysteine or phosphate. Finally, we also observed that ZnO-NPs caused fewer changes to the soil bacterial community structure and that it had no nano-specific toxicity.

In order to improve the financial support efficiency of new generation high-tech industry in China, from the perspective of the subject (enterprise) in which financial resources were invested, this paper selected 192 listed companies in quantum communication and artificial intelligence concept plates in Chinese stock market as samples. Based on the original data of 2015-2019, the influencing factors of financial support efficiency of new generation high-tech listed companies were then empirically analyzed by using DEA-BCC model and Tobit model. The results showed that the ownership concentration, executive compensation and regional digital inclusive finance level were main factors affecting the financial support efficiency of new generation high-tech listed companies, followed by the technological innovation capability and regional economic development level. However, the influence of growth and comprehensive leverage were limited, and the influence of profitability and capital structure were not obvious. Accordingly, the main countermeasures to improve the financial support efficiency of new generation high-tech industry were proposed, which included giving full play to the advantages and potential of digital inclusive finance, actively guiding enterprises to innovate management, improve quality and efficiency, etc.

The composition and structure of gut microbiota plays an important role in obesity induced by a high-fat diet (HFD) and related metabolic syndrome (MetS). Previous studies have shown that galacto-oligosaccharides (GOSs) have an effective anti-obesity effect. In this study, we aimed to investigate the effect of enzymatically synthesized α-galacto-oligosaccharides (ES-α-GOSs) on MetS and gut microbiota dysbiosis in HFD-fed mice, and to further investigate whether the attenuation of MetS is associated with the modulation of gut microbiota. Our results indicated that ES-α-GOS could notably ameliorate obesity-related MetS, including hyperlipidemia, insulin resistance and mild inflammation. The subsequent analysis of gut microbiota further showed that ES-α-GOS supplements can significantly modulate the overall composition of the gut microbiota and reverse the gut microbiota disorder caused by HFD feeding. Moreover, Spearman correlation analysis showed that 40 key bacteria reversed by ES-α-GOS were highly associated with metabolic parameters. These results suggested that ES-α-GOSs could serve as a potential candidate for preventing obesity-induced MetS in association with the modulation of gut microbiota.

MicroRNAs (miRNAs) play a vital role in many biological processes, including cell growth, differentiation, apoptosis, development, differentiation, and carcinogenesis. Since miRNAs might play a part in cancer initiation and progression, they comprise an original class of promising diagnostic and prognostic molecular markers. In order to systematically understand the regulation of miRNA expression in cancers, the current study analyzed the miRNA expression profile in NCI-60 human cancer cell lines. Over 300 miRNAs exhibited unique expression profiles in cell lines derived from the same lineage. This study identified 9 lineage-specific miRNA expression patterns. Moreover, results indicated that miR-720 and miR-887 are expressed at relatively high levels in breast cancer cell lines compared to other types of cancer. Ultimately, matching NCI-60 drug response data to miR-720 and miR-887 expression profiles revealed that several FDA-approved drugs were inversely related to miR-720 and miR-887. Furthermore, the anti-cancer effect of perifosine was significantly enhanced by inhibiting miR-720 and decreased by miR-720 precursor treatment in breast cancer cell lines. 5-Fu treatment was enhanced by inhibiting miR-887 and decreased by miR-887 precursor treatment. The current results offer insight into the relationship between miRNA expression and their lineage types, and the approach used here represents a potential cancer therapy with the help of miRNAs.

Soil specimens were initially prepared by freezing with a thermal gradient (Fnonuni) and then thawing under uniform temperature (Tuni), then the strain behaviors of which using digital processing technique (DPT)–aided unconfined compression on contacted specimens were investigated. Although the specimen treated under Fnonuni - Tuni exbihted a strength over 1.8 times higher and a specimen scale–based (S–) lateral strain over 0.3 times smaller than that treated under freeze–thaw with uniform temperatures Funi - Tuni, it exhibited a relatively greater local scale–based (L–) strain level under identical S–axial strain, and dominated the deformation process of the specimen assembly. The characteristic of L–strain relationship between top and bottom specimens under Fnonuni - Tuni and specimens under Funi - Tuni approached identical when S–axial strain exceeded a threshold corresponding to the peak strength. Further, an asymmetric L–strain gradient at two sides of the fractured surface in specimens was observed, and it was more evident in specimens treated under Fnonuni - Tuni. These test data and observations obtained have been validated by detailed comparisons with previous studies, and contribute to build a constitutive model considering nonlocal variable and thus improve the settlement prediction precision of the thawed soils.

Civets are small mammals belonging to the family Viverridae. The masked palm civets (Paguma larvata) served as an intermediate host in the bat-to-human transmission of severe acute respiratory syndrome coronavirus (SARS-CoV) in 20031. Because of their unique role in the SARS outbreak, civets were suspected as a potential intermediate host of SARS-CoV-2, the etiological pathogen of the COVID-19 pandemic. Besides their susceptibility to coronaviruses, civets can also be infected by other viruses, such as canine distemper viruses2, parvoviruses3, influenza viruses4, etc. Regarding the ecological and economical role of civets, it is vital to evaluate the potential threats from different pathogens to these animals. Receptor binding is a necessary step for virus entry into host cells. Understanding the distribution of receptors of various viruses provides hints to their potential tissue tropisms. Herein, we characterized the cell atlas of five important organs (the frontal lobe, lung, liver, spleen and kidney) of masked palm civets (Paguma larvata) and described the expression profiles of receptor associated genes of 132 viruses from 25 families, including 16 viruses from 10 families reported before that can attack civets and 116 viruses with little infection record.

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) issued a significant and urgent threat to global health. The exact animal origin of SARS-CoV-2 remains obscure and understanding its host range is vital for preventing interspecies transmission. Previously, we have assessed the target cell profiles of SARS-CoV-2 in pets, livestock, poultry and wild animals. Herein, we expand this investigation to a wider range of animal species and viruses to provide a comprehensive source for large-scale screening of potential virus hosts. Single cell atlas for several mammalian species (alpaca, hamster, hedgehog, chinchilla etc.), as well as comparative atlas for lung, brain and peripheral blood mononuclear cells (PBMC) for various lineages of animals were constructed, from which we systemically analyzed the virus entry factors for 113 viruses over 20 species from mammalians, birds, reptiles, amphibians and invertebrates. Conserved cellular connectomes and regulomes were also identified, revealing the fundamental cell-cell and gene-gene cross-talks between these species. Overall, our study could help identify the potential host range and tissue tropism of SARS-CoV-2 and a diverse set of viruses and reveal the host-virus co-evolution footprints.

Ciboria carunculoides is the dominant causal agent of mulberry sclerotial disease, and it is a necrotrophic fungal pathogen with a narrow host range that causes devastating diseases in mulberry fruit. However, little is known about the interaction between C. carunculoides and mulberry. Here, our transcriptome sequencing results showed that the transcription of genes in the secondary metabolism and defense-related hormone pathways were significantly altered in infected mulberry fruit. Due to the antimicrobial properties of proanthocyanidins (PAs), the activation of PA biosynthetic pathways contributes to defense against pathogens. Salicylic acid (SA) and jasmonic acid (JA) are major plant defense hormones. However, SA signaling and JA signaling are antagonistic to each other. Our results showed that SA signaling was activated, while JA signaling was inhibited, in mulberry fruit infected with C. carunculoides. Yet SA mediated responses are double-edged sword against necrotrophic pathogens, as SA not only activates systemic acquired resistance (SAR) but also suppresses JA signaling. We also show here that the small secreted protein CcSSP1 of C. carunculoides activates SA signaling by targeting pathogenesis-related protein 1 (PR1). These findings reveal that the infection strategy of C. carunculoides functions by regulating SA signaling to inhibit host defense responses.

The calculation and suppression measures of single-core cable sheath voltage is limited to the power frequency. However, the influence of harmonics and inrush current on the sheath layer overvoltage is not considered. Therefore, this paper proposes an analysis method and suppression measures for single-core cable sheath overvoltage considering harmonics and inrush current. First, the calculation of equivalent electrical parameters of the cable is proposed based on the internal modeling of single-core cable. Secondly, the equivalent circuit of the cable with the sheath single-ended grounding is proposed, and the voltage calculation formula of the sheath to the ground is derived. The analysis method of the harmonic and inrush current induction in the sheath and the transmission law of the cable core current-sheath layer voltage are further summarized. Accordingly, a method of suppressing the sheath layer harmonic overvoltage and inrush overvoltage is proposed. Finally, a 35kV single-core cable power model is built in PSCAD/EMTDC for simulation verification. The results show the effectiveness of the proposed analysis method and overvoltage suppression measures.