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Abstract Advancements in sequencing have enabled the assembly of numerous sheep genomes, significantly advancing our understanding of the link between genetic variation and phenotypic traits. However, the genome of East Friesian sheep (Ostfriesisches Milchschaf), a key high-yield milk breed, remains to be fully assembled. Here, we constructed a near-complete and gap-free East Friesian genome assembly using PacBio HiFi, ultra-long ONT and Hi-C sequencing. The resulting genome assembly spans approximately 2.96 Gb, with a contig N50 length of 104.1 Mb and only 164 unplaced sequences. Remarkably, our assembly has captured 41 telomeres and 24 centromeres. The assembled sequence is of high quality on completeness (BUSCO score: 97.1%) and correctness (QV: 69.1). In addition, a total of 24,580 protein-coding genes were predicted, of which 97.2% (23,891) carried at least one conserved functional domain. Collectively, this assembly provides not only a near T2T gap-free genome, but also provides a valuable genetic resource for comparative genome studies of sheep and will serve as an important tool for the sheep research community.

Abstract Inhibitors of α‐amylase have been developed to regulate postprandial blood glucose fluctuation. The enzyme inhibition arises from direct or indirect inhibitor‐enzyme interactions, depending on inhibitor structures. However, an ignored factor, substrate, may also influence or even decide the enzyme inhibition. In this work, it is innovatively found that the difference in substrate enzymolysis modes, i.e., structural composition and concentration of α‐1,4‐glucosidic bonds, triggers the diversity in inhibitor‐enzyme aggregating behaviors and α‐amylase inhibition. For competitive inhibition, there exists an equilibrium between α‐amylase‐substrate catalytic affinity and inhibitor‐α‐amylase binding affinity; therefore, a higher enzymolysis affinity and concentration of α‐1,4‐glucosidic structures interferes the balance, unfavoring inhibitor‐enzyme aggregate formation and thus weakening α‐amylase inhibition. For uncompetitive inhibition, the presence of macromolecular starch is necessary instead of micromolecular GalG2CNP, which not only binds with active site but with an assistant flexible loop (involving Gly304‐Gly309) near the site. Hence, the refined enzyme structure due to the molecular flexibility more likely favors the inhibitor binding with the non‐active loop, forming an inhibitor‐enzyme‐starch ternary aggregate. Conclusively, this study provides a novel insight into the evaluation of α‐amylase inhibition regarding the participating role of substrate in inhibitor‐enzyme aggregating interactions, emphasizing the selection of appropriate substrates in the development and screening of α‐amylase inhibitors.

The purpose of this study was to investigate the effects of BOC on glioblastoma cells and its underlying mechanisms. In vitro, BOC-knockdown was performed in glioma cell lines. CCK-8 and Transwell were used to assess the impact of BOC on the viability, invasion, and migration of gliobma cells. RNA-seq technology was employed to analyze the differential gene expression between BOC-knockdown glioma cells and the control group, and qRT-PCR was used to validate the expression of downstream differential genes. SMO-overexpression was performed to investigate the effects of SMO on glioma cells. A BOC-knockdown mouse subcutaneous tumor model was to verify the effects of BOC on mouse tumors. Tissue microarray technology was used to detect the expression of BOC and SMO in samples of normal human brain tissue and glioma tissue. In vitro, BOC-knockdown inhibited the viability, invasion, and migration of glioma cells, as well as downregulated the expression of downstream differential genes SMO, EGFR, HRAS, and MRAS. Conversely, SMO-overexpression upregulated the viability, invasion, and migration abilities of BOC-knockdown cells. In vivo, BOC-knockdown suppressed tumor growth in mice and downregulated the expression of downstream differential genes SMO, EGFR, HRAS, and MRAS. Tissue microarray results showed that both BOC and SMO were highly expressed in glioma tissues. BOC is aberrantly overexpressed in glioma patients and promotes glioma development. Mechanistically, BOC activates the Hedgehog (Hh) and RAS signaling pathways by upregulating the expression of SMO, EGFR, HRAS, and MRAS, thereby facilitating the Proliferation, invasion and migration of glioma cells.

ABSTRACT Enhancing the availability of representative isolates from hydrothermal vents (HTVs) is imperative for comprehending the microbial processes that propel the vent ecosystem. In recent years, Campylobacteria have emerged as the predominant and ubiquitous taxon across both shallow and deep-sea vent systems. Nevertheless, only a few isolates have been cultured, primarily originating from deep-sea HTVs. Presently, no cultivable isolates of Campylobacteria are accessible in shallow water vent systems (

Abstract Background Foot‐and‐mouth disease virus (FMDV) is an important pathogen of the MicroRNA virus family. Infection of livestock can cause physical weakness, weight loss, reduced milk production, and a significant reduction in productivity for an extended period. It also causes a high mortality rate in young animals, seriously affecting livestock production. The host range of FMDV is mainly limited to cloven‐hoofed animals such as cattle and sheep, while odd‐toed ungulates such as horses and donkeys have natural resistance to FMDV. The mechanism underlying this resistance in odd‐toed ungulates remains unclear. Objective This study aimed to analyze the differences between FMDV‐infected cattle and horses to provide valuable insights into the host‐FMDV interaction mechanisms, thereby contributing to the control of foot‐and‐mouth disease and promoting the development of the livestock industry. Methods We observed the distribution of integrins, which help FMDV enter host cells, in the nasopharyngeal tissues of cattle and horses using immunohistochemistry. Then, we employed high‐throughput RNA sequencing (RNA‐Seq) to study the changes in host gene expression in the nasopharyngeal epithelial tissues of cattle and horses after FMDV infection. We performed enrichment analysis of GO and KEGG pathways after FMDV infection and validated related genes through qPCR. Results The immunohistochemical results showed that both cattle and horses had four integrin receptors that could assist FMDV entry into host cells. The transcriptome analysis revealed that after FMDV infection, pro‐apoptotic genes such as caspase‐3 (CASP3) and cytochrome C (CYCS) were upregulated in cattle, while apoptosis‐inhibiting genes such as NAIP and BCL2A1 were downregulated. In contrast, the expression trend of related genes in horses was opposite to that in cattle. Additionally, autophagy‐related genes such as beclin 1, ATG101, ATG4B, ATG4A, ATG13, and BCL2A1 were downregulated in cattle after FMDV infection, indicating that cattle did not clear the virus through autophagy. However, key autophagy genes including ATG1, ATG3, ATG9, ATG12, and ATG16L1 were significantly upregulated in horses after viral infection. Conclusion Both water buffaloes and Mongolian horses express integrin receptors that allow FMDV entry into cells. Therefore, the resistance of Mongolian horses to FMDV may result from more changes in intracellular mechanisms, including processes such as autophagy and apoptosis. Significant differences were observed between water buffaloes and Mongolian horses in these processes, suggesting that these processes influence FMDV replication and synthesis.

Hadal zones account for the deepest 45% of the oceanic depth range and play an important role in ocean biogeochemical cycles. As the least-explored aquatic habitat on earth, hadal ecosystems contain a vast diversity of so far uncultured microorganisms that cannot be grown on conventional laboratory culture media. Therefore, it has been difficult to gain a true understanding of the detailed metabolic characteristics and ecological functions of those difficult-to-culture microorganisms in hadal environments. In this study, a novel anaerobic bacterial strain, MT110T, was isolated from a hadal sediment–water interface sample of the Mariana Trench at 10,890 m. The level of 16S rRNA gene sequence similarity and percentage of conserved proteins between strain MT110T and the closest relatives, Anaerovorax odorimutans DSM 5092T (94.9 and 46.6%) and Aminipila butyrica DSM 103574T (94.4 and 46.7%), indicated that strain MT110T exhibits sufficient molecular differences for genus-level delineation. Phylogenetic analyses based on both 16S rRNA gene and genome sequences showed that strain MT110T formed an independent monophyletic branch within the family Anaerovoracaceae. The combined evidence showed that strain MT110T represents a novel species of a novel genus, proposed as Anoxybacterium hadale gen. nov. sp. nov. (type strain MT110T = KCTC 15922T = MCCC 1K04061T), which represents a previously uncultured lineage of the class Clostridia. Physiologically, no tested organic matter could be used as sole carbon source by strain MT110T. Genomic analysis showed that MT110T had the potential capacity of utilizing various carbon sources, but the pathways of sulfur reduction were largely incomplete. Our experiments further revealed that cysteine is one of the essential nutrients for the survival of strain MT110T, and cannot be replaced by sulfite, leucine, or taurine. This result suggests that organic sulfur compounds might play an important role in metabolism and growth of the family Anaerovoracaceae and could be one of the key factors affecting the cultivation of the uncultured microbes. Our study brings a new perspective to the role of dissolved organic sulfur in hadal ecosystems and also provides valuable information for optimizing the conditions of isolating related microbial taxa from the hadal environment.

IntroductionThe advancement of high-throughput, high-quality, flexible, and cost-effective genotyping platforms is crucial for the progress of dairy breeding in Bactrian camels. This study focuses on developing and evaluating a 1K functional liquid single nucleotide polymorphism (SNP) array specifically designed for milk performance in Bactrian camels.MethodsWe utilized RNA sequencing data from 125 lactating camels to identify and select 1,002 loci associated with milk production traits for inclusion in the SNP array. The array’s performance was then assessed using 24 randomly selected camels. Additionally, the array was employed to genotype 398 individuals, which allowed for population validation to assess the polymorphism of SNP sites.ResultsThe SNP array demonstrated high overall SNP call rates (> 99%) and a remarkable 100% consistency in genotyping. Population validation results indicate that camels from six breeding areas in Northwest China share a similar genetic background regarding lactation functionality.DiscussionThis study highlights the potential of the SNP array to accelerate the breeding process of lactating Bactrian camels and provides a robust technical foundation for improving lactation performance.

Consensus has been widely used in distributed control, where distributed individuals need to share their states with their neighbors through communication links to achieve a common goal. However, the objectives of existing consensus-based control strategies for energy systems seldom address battery degradation cost, which is an important performance indicator to assess the performance and sustainability of battery energy storage (BES) systems. In this paper, we propose a consensus-based optimal control strategy for multi-microgrid systems, aiming at multiple control objectives including minimizing battery degradation cost. Distributed consensus is used to synchronize the ratio of BES output power to BES state-of-charge (SoC) among all microgrids while each microgrid is trying to reach its individual optimality. In order to reduce the pressure of commu-nication links and prevent excessive exposure of local information, this ratio is the only state variable shared between microgrids. Since our complex nonlinear problem might be difficult to solve by traditional methods, we design a compressive sensing-based gradient descent (CSGD) method to solve the control problem. Numerical simulation results show that our control strategy results in a 74.24 % reduction in battery degradation cost on average compared to the control method without considering battery degradation. In addition, the compressive sensing method causes an 89.12 % reduction in computation time cost compared to the traditional Monte Carlo (MC) method in solving the control problem.

Abstract The α‐amylase inhibition and binding behaviors of shikimic acid and its structural analogues were studied. Uncompetitive inhibition characteristic of shikimic acid was identified through several linear transformation equations of enzymatic data considering the good linearity. Interestingly, the change in concentrations of starch would not decrease the inhibitory effects of shikimic acid with various concentrations used in present study. The inhibitory effect reduced greatly after the ethyl esterification of shikimic acid. Gallic acid was distinguished from shikimic acid by a benzene ring and exhibited lower inhibition than shikimic acid. Shikimic acid affected the α‐amylase structure by binding to the non‐active site but did not quench the α‐amylase fluorescent intensity. However, gallic acid anchored with a subsite containing some fluorescent residues at the entrance of active pocket, quenching the fluorescence intensity of α‐amylase strongly. The difference in shikimic acid and gallic acid made the changes in their binding sites as well as the binding behavior. Conclusively, the carboxyl and hexatomic ring with one double‐bond played an important role in binding of shikimic acid with the non‐active sites of α‐amylase. Shikimic acid has potentials as a functional‐factor in α‐amylase inhibition for controlling the postprandial blood sugar level.

Lignocellulosic materials, made up of cellulose, hemicellulose, and lignin, constitute some of the most prevalent types of biopolymers in marine ecosystems. The degree to which marine microorganisms participate in the breakdown of lignin and their impact on the cycling of carbon in the oceans is not well understood. Strain LCG002, a novel Marivivens species isolated from Lu Chao Harbor’s intertidal seawater, is distinguished by its ability to metabolize lignin and various aromatic compounds, including benzoate, 3-hydroxybenzoate, 4-hydroxybenzoate and phenylacetate. It also demonstrates a broad range of carbon source utilization, including carbohydrates, amino acids and carboxylates. Furthermore, it can oxidize inorganic gases, such as hydrogen and carbon monoxide, providing alternative energy sources in diverse marine environments. Its diversity of nitrogen metabolism is supported by nitrate/nitrite, urea, ammonium, putrescine transporters, as well as assimilatory nitrate reductase. For sulfur assimilation, it employs various pathways to utilize organic and inorganic substrates, including the SOX system and DSMP utilization. Overall, LCG002’s metabolic versatility and genetic profile contribute to its ecological significance in marine environments, particularly in the degradation of lignocellulosic material and aromatic monomers.

Deep-sea environments, as relatively unexplored extremes within the Earth’s biosphere, exhibit notable distinctions from terrestrial habitats. To thrive in these extreme conditions, deep-sea actinomycetes have evolved unique biochemical metabolisms and physiological capabilities to ensure their survival in this niche. In this study, five actinomycetes strains were isolated and identified from the Mariana Trench via the culture-dependent method and 16S rRNA sequencing approach. The antimicrobial activity of Microbacterium sp. B1075 was found to be the most potent, and therefore, it was selected as the target strain. Molecular networking analysis via the Global Natural Products Social Molecular Networking (GNPS) platform identified 25 flavonoid compounds as flavonoid secondary metabolites. Among these, genistein was purified and identified as a bioactive compound with significant antibacterial activity. The complete synthesis pathway for genistein was proposed within strain B1075 based on whole-genome sequencing data, with the key gene being CHS (encoding chalcone synthase). The expression of the gene CHS was significantly regulated by high hydrostatic pressure, with a consequent impact on the production of flavonoid compounds in strain B1075, revealing the relationship between actinomycetes’ synthesis of flavonoid-like secondary metabolites and their adaptation to high-pressure environments at the molecular level. These results not only expand our understanding of deep-sea microorganisms but also hold promise for providing valuable insights into the development of novel pharmaceuticals in the field of biopharmaceuticals.

The existing post-processing methods of precipitation forecast tend to correct the 24 h precipitation averaged in the whole region, ignoring the regional differences of precipitation, and cannot meet the needs of refined forecasting. Based on the evaluation of CMA-MESO 3 km (China Meteorological Administration Mesoscale Model at 3km resolution) precipitation prediction during the flooding season of 2020 in Shanxi province, the frequency matching method was applied to correct the hourly precipitation forecast for specific periods and regions. The correction results were also analyzed in detail. The results showed that: (1) 24-hour precipitation forecast of CMA-MESO 3 km showed consistent false alarm, and the positive errors in the basin were prominent in Shanxi Province. (2) The forecast biases are inconsistent over different periods and altitudes. The precipitation frequency showed large wet biases during the daytime, especially in the area with lower altitude, but had dry bias in the region with higher altitude, for light precipitation at night. (3) After correction for different periods and regions, the mean errors decreased by 76.8% for 24-hour precipitation, the overestimates of heavy rain in the forecast were significantly reduced. (4) By reducing the over-predicted frequency and intensity, the problems of earlier peak of precipitation and false prediction of precipitation peak in the morning were also solved. The diurnal variation characteristics of precipitation was reproduced well. (5) The correction could improve the forecast of precipitation intensity, which could further effectively improve the forecast of terrain distribution characteristics of precipitation. However, the improvement of forecast of terrain distribution deviation of precipitation was limited.

While live commerce provides consumers with a new shopping experience, it also leads them to experience shopping failures and to develop a self-protection mechanism to prevent wrong purchases. To address this issue, merchants have attempted to explore new marketing methods for live commerce, giving rise to an offense and defense game between streamers and consumers. In this study, we sought to confirm the effectiveness of consumer protection mechanisms and the impact of streamers' information overload marketing strategy in live commerce. Accordingly, we constructed a hypothetical model based on protection motive theory and information overload theory. In addition, we analyzed the data from the simulated live streaming marketing on seven hundred people through partial least squares structural equation modeling. The results indicate that product utilitarian value uncertainty, consumers' experiential efficacy, and response costs, which are the main factors in the formation of consumer protection mechanisms, influence consumers' intention to stop their purchases. Streamers can circumvent consumer self-protection mechanisms through information overload marketing by reducing utilitarian value uncertainty and consumers' experiential efficacy and increasing consumers' response costs. However, consumers would be able to rebuild their self-protection mechanism through consumer resilience, which moderates the effects of information overload. This study's results provide important theoretical perspectives and new ideas for formulating marketing strategies for live commerce.

With the rapid advancement of information technology, telemedicine apps have gradually become an indispensable tool for providing patients with more convenient, efficient, and accessible healthcare services. However, the successful implementation of these apps largely depends on widespread acceptance among the public. To thoroughly investigate the factors influencing the public’s acceptance of these apps and the relationships between these factors, this study developed a theoretical model based on the Diffusion of Innovation theory and the Theory of Perceived Value. To validate this model, we conducted a survey of 387 residents in Beijing, China, and employed structural equation modeling to analyze the collected data. The research findings indicate that attributes of innovation diffusion, including relative advantage, compatibility, complexity, trialability, and observability, significantly and positively influence the public’s perceived value. Particularly noteworthy is that perceived value partially mediates the relationship between innovation attributes and public acceptance, emphasizing the crucial role of perceived value in the public decision-making process. This study employed a theory-driven approach to elucidate the acceptance of telemedicine apps and offers fresh insights into the existing literature. By integrating the research paradigms of innovation diffusion and customer perceived value, we provide a coherent explanation of how individual cognitive processes lead to acceptance behavior. In summary, this research enriches the existing theoretical studies on the acceptance of telemedicine apps and holds positive implications for healthcare practice.

The virtual synchronous generator (VSG) is an important concept and primary control method in modern power systems. The penetration of power-electronics-based distributed generators in the power grid provides uncertainty and reduces the inertia of the system, thus increasing the risk of instability when disturbance occurs. The VSG produces virtual inertia by introducing the dynamic characteristics of the synchronous generator, which provides inertia and becomes a grid-forming control method. The disadvantages of the VSG are that there are many parameters to be adjusted and its operation process is complicated. However, with the rapid development of artificial intelligence (AI) technology, the powerful adaptive learning capability of AI algorithms provides potential solutions to this issue. Two research hotspots are deep learning (DL) and reinforcement learning (RL). This paper presents a comprehensive review of these two techniques combined with VSG control in the energy internet (EI). Firstly, the basic principle and classification of the VSG are introduced. Next, the development of DL and RL algorithms is briefly reviewed. Then, recent research on VSG control based on DL and RL algorithms are summarized. Finally, some main challenges and study trends are discussed.

ABSTRACTA feature of the camel is its tolerance to osmotic stress. However, few studies of osmotic stress in vivo or comparative analyses between different tissues of the camel have been performed. Here, we report the roles of Krüppel-associated box domain containing zinc-finger repressor proteins (KRAB-ZFPs) in transcriptional networks under osmotic stress in camels by analyzing transcriptomes of four different tissues under various osmotic conditions. We found that 273 of 278 KRAB-ZFPs were expressed in our data set, being involved in all of the 65 identified networks and exhibiting their extensive functional diversity. We also found that 110 KRAB-ZFPs were hub genes involved in more than half of the networks. We demonstrated that the osmotic stress response is involved in network shifts and that KRAB-ZFPs mediate this process. Finally, we presented the diverse mechanisms of osmotic stress responses in different tissues. These results revealed the genetic architecture of systematic physiological response in vivo to osmotic stress in camels. Our work will lead to new directions for studying the mechanism of osmotic stress response in anti-arid mammals.

Lignocellulosic materials are composed of cellulose, hemicellulose and lignin and are one of the most abundant biopolymers in marine environments. The extent of the involvement of marine microorganisms in lignin degradation and their contribution to the oceanic carbon cycle remains elusive. In this study, a novel lignin-degrading bacterial strain, LCG003, was isolated from intertidal seawater in Lu Chao Harbor, East China Sea. Phylogenetically, strain LCG003 was affiliated with the genus Aliiglaciecola within the family Alteromonadaceae. Metabolically, strain LCG003 contains various extracellular (signal-fused) glycoside hydrolase genes and carbohydrate transporter genes and can grow with various carbohydrates as the sole carbon source, including glucose, fructose, sucrose, rhamnose, maltose, stachyose and cellulose. Moreover, strain LCG003 contains many genes of amino acid and oligopeptide transporters and extracellular peptidases and can grow with peptone as the sole carbon and nitrogen source, indicating a proteolytic lifestyle. Notably, strain LCG003 contains a gene of dyp-type peroxidase and strain-specific genes involved in the degradation of 4-hydroxy-benzoate and vanillate. We further confirmed that it can decolorize aniline blue and grow with lignin as the sole carbon source. Our results indicate that the Aliiglaciecola species can depolymerize and mineralize lignocellulosic materials and potentially play an important role in the marine carbon cycle.

Abstract The apolipoprotein E4 (APOE4) genotype is one of the strongest genetic risk factors for Alzheimer’s disease (AD), and is generally believed to cause widespread pathological alterations in various types of brain cells. Here, we developed a novel engineering method of creating the chimeric human cerebral organoids (chCOs) to assess the differential roles of APOE4 in neurons and astrocytes. First, the astrogenic factors NFIB and SOX9 were introduced into induced pluripotent stem cells (iPSCs) to accelerate the induction of astrocytes. Then the above induced iPSCs were mixed and cocultured with noninfected iPSCs under the standard culturing condition of cerebral organoids. As anticipated, the functional astrocytes were detected as early as 45 days, and it helped more neurons matured in chCOs in comparation of the control human cerebral organoids (hCOs). More interestingly, this method enabled us to generate chCOs containing neurons and astrocytes with different genotypes, namely APOE3 or APOE4. Then, it was found in chCOs that astrocytic APOE4 already significantly promoted lipid droplet formation and cholesterol accumulation in neurons while both astrocytic and neuronal APOE4 contributed to the maximum effect. Most notably, we observed that the co-occurrence of astrocytic and neuronal APOE4 were required to elevate neuronal phosphorylated tau levels in chCOs while Aβ levels were increased in chCOs with neuronal APOE4. Altogether, our results not only revealed the essence of both neuronal and astrocytic APOE4 for tau pathology, but also suggested chCOs as a valuable pathological model for AD research and drug discovery.

Recently, several reports showed that n-alkanes were abundant in the hadal zone, suggesting that n-alkanes could be an important source of nutrients for microorganisms in hadal ecosystems. To date, most of the published studies on the microbial capacity to degrade hydrocarbons were conducted only at atmospheric temperature and pressure (0.1 MPa), and little is known about whether and which microbes could utilize n-alkanes at in situ environmental conditions in the hadal zone, including low temperature and high hydrostatic pressure (especially >30 MPa). In this study, a piezotolerant bacterium, strain C2-1, was isolated from a Mariana Trench sediment at depth of 5,800 m. Strain C2-1 was able to grow at in situ temperature (4°C) and pressure (58 MPa) with n-alkanes as the sole carbon source. Phylogenetically, strain C2-1 and related strains (TMPB967, ST750PaO-4, IMCC1826, and TTBP476) should be classified into the genus Venatorbacter. Metagenomic analysis using ~5,000 publicly available datasets showed that Venatorbacter has a wide environmental distribution in seawater (38), marine sediments (3), hydrothermal vent plumes (2), Antarctic ice (1), groundwater (13), and marine sponge ecosystems (1). Most Venatorbacter species are non-obligate n-alkane degraders that could utilize, at a minimal, C16−C18n-alkanes, as well as other different types of carbon substrates, including carbohydrates, amino acids, peptides, and phospholipids. The type II secretion system, extracellular proteases, phospholipase, and endonuclease of Venatorbacter species were robustly expressed in the metatranscriptomes of deep-sea hydrothermal vents, suggesting their important contribution to secondary productivity by degrading extracellular macromolecules. The identification of denitrifying genes suggested a genus-specific ecological potential that allowed Venatorbacter species to be active in anoxic environments, e.g., the oxygen-minimal zone (OMZ) and the deeply buried marine sediments. Our results show that Venatorbacter species are responsible for the degradation of hydrocarbon and extracellular macromolecules, suggesting that they may play an important role in the biogeochemistry process in the Trench ecosystems.

Abstract Background The deep sea harbors the majority of the microbial biomass in the ocean and is a key site for organic matter (OM) remineralization and storage in the biosphere. Microbial metabolism in the deep ocean is greatly controlled by the generally depleted but periodically fluctuating supply of OM. Currently, little is known about metabolic potentials of dominant deep-sea microbes to cope with the variable OM inputs, especially for those living in the hadal trenches—the deepest part of the ocean. Results In this study, we report the first extensive examination of the metabolic potentials of hadal sediment Chloroflexi, a dominant phylum in hadal trenches and the global deep ocean. In total, 62 metagenome-assembled-genomes (MAGs) were reconstructed from nine metagenomic datasets derived from sediments of the Mariana Trench. These MAGs represent six novel species, four novel genera, one novel family, and one novel order within the classes Anaerolineae and Dehalococcoidia. Fragment recruitment showed that these MAGs are globally distributed in deep-sea waters and surface sediments, and transcriptomic analysis indicated their in situ activities. Metabolic reconstruction showed that hadal Chloroflexi mainly had a heterotrophic lifestyle, with the potential to degrade a wide range of organic carbon, sulfur, and halogenated compounds. Our results revealed for the first time that hadal Chloroflexi harbor pathways for the complete hydrolytic or oxidative degradation of various recalcitrant OM, including aromatic compounds (e.g., benzoate), polyaromatic hydrocarbons (e.g., fluorene), polychlorobiphenyl (e.g., 4-chlorobiphenyl), and organochlorine compounds (e.g., chloroalkanes, chlorocyclohexane). Moreover, these organisms showed the potential to synthesize energy storage compounds (e.g., trehalose) and had regulatory modules to respond to changes in nutrient conditions. These metabolic traits suggest that Chloroflexi may follow a “feast-or-famine” metabolic strategy, i.e., preferentially consume labile OM and store the energy intracellularly under OM-rich conditions, and utilize the stored energy or degrade recalcitrant OM for survival under OM-limited condition. Conclusion This study expands the current knowledge on metabolic strategies in deep-ocean Chlorolfexi and highlights their significance in deep-sea carbon, sulfur, and halogen cycles. The metabolic plasticity likely provides Chloroflexi with advantages for survival under variable and heterogenic OM inputs in the deep ocean. Video Abstract

Salt dietary intake is tightly coupled to human health, and excessive sodium can cause strokes and cardiovascular diseases. Research into the renal medulla of camels exhibiting high salt resistance may aid identification of the mechanisms governing resistance to high salinity. In this study, we used RNA sequencing (RNA‐seq) to show that in the renal medulla of camels under salt stress, 22 mRNAs, 2 long noncoding RNAs (lncRNAs), and 31 microRNAs (miRNAs) exhibited differential expression compared with the free salt‐intake diet group. Using fluorescence in situ hybridization and dual‐luciferase reporter assays, we demonstrated that the lncRNA LNC003834 can bind miRNA‐34a and thereby relieve suppression of the salt‐absorption‐inhibiting SLC14A1 mRNA from miRNA‐34a, suggesting that the above lncRNA‐miRNA‐mRNA act as competing endogenous RNAs (ceRNAs). We subsequently performed short hairpin RNA and small RNA interference and reactive oxygen species (ROS) detection assays to show that SLC6A1, PCBP2, and PEX5L can improve the antioxidation capacity of renal medulla cells of camel by decreasing ROS levels. Our data suggest that camels achieve sodium homeostasis through regulating the expression of salt‐reabsorption‐related genes in the renal medulla, and this involves ceRNAs (SLC14A1 mRNA, LNC003834, and miRNA‐34a) and antioxidant genes (SLC6A1, PCBP2, and PEX5L). These data may assist in the development of treatments for diseases induced by high salt diets.

Today, users of smart devices are from increasingly younger generations, and their use is very common among preschoolers. The problem of smart device addiction in preschool children has attracted widespread attention, due to which this study explores the influencing factors in children aged 2–5 years. Based on the protection–risk model, 236 Chinese parents were surveyed, and the data was analyzed using partial least squares structural equation modeling. The findings show that parental emotion regulation significantly and negatively influences children’s depression and social withdrawal symptoms, whereas it has a significant and positive influence on parental self-control as well as outdoor intention. Also, children’s depression and social withdrawal symptoms have a significant and positive influence on their smart device addiction, whereas parental self-control and outdoor intentions have no significant influence on it. Moreover, children’s social withdrawal and depression have a mediating effect between parental emotion regulation and children’s smart device addiction, but parental self-control and outdoor intention have no mediating effect between the two. This study identifies the factors influencing children’s smart device addiction from a new perspective, providing theoretical support to address this problem of addiction.

In this study, the entropy method and the Super-SBM model with unexpected output are used at first to calculate the digital economy development index and the level of green transformation in manufacturing. Then, a range of multi-dimensional empirical methods, including fixed effects models, threshold models, and mediation models, are applied to analyze the characteristics shown by the impact of digital economy development on the green transformation of manufacturing. The research results are obtained as follows. Firstly, the digital economy contributes significantly to promoting the green transformation of manufacturing after excluding the macro-system environmental effects, conducting such robustness tests as stepwise regression and introducing instrumental variables. Secondly, there is a nonlinear relationship between the development of the digital economy and the green transformation of manufacturing with an increasing marginal effect. Lastly, it is revealed through mechanism analysis that the digital economy promotes the green transformation of manufacturing by enhancing the capabilities of green technological innovation and rationalizing industrial upgrading, with the partial mediation effects reaching 21.2% and 21.8%, respectively. Despite the contribution of digital economy to the advanced upgrading of industries, there is no mediation effect exhibited. In addition to confirming the path of achieving the green transformation of manufacturing through the digital economy, these results also guide the government on how policies can be formulated and improved to grow the digital economy and promote the green transformation of manufacturing.

The increasing scale of the injection of renewable energy has brought about great uncertainty to the operation of power grid. In this situation, probabilistic power flow (PPF) calculation has been introduced to mitigate the low accuracy of traditional deterministic power flow calculation in describing the operation status and power flow distribution of power systems. Polynomial chaotic expansion (PCE) method has become popular in PPF analysis due to its high efficiency and accuracy, and sparse PCE has increased its capability of tackling the issue of dimension disaster. In this paper, we propose a principal component analysis-based compressive sensing (PCA-CS) algorithm solve the PPF problem. The l1-optimization of CS is used to tackle the dimension disaster of sparse PCE, and PCA is included to further increase the sparsity of expansion coefficient matrix. Theoretical and numerical simulation results show that the proposed method can effectively improve the efficiency of PPF calculation in the case of random inputs with higher dimensions.

Hydrothermal vent (HTV) systems are important habitats for understanding the biological processes of extremophiles on Earth and their relative contributions to material and energy cycles in the ocean. Current understanding on hydrothermal systems have been primarily focused on deep-sea HTVs, and little is known about the functions and metabolisms of microorganisms in shallow-water HTVs (SW-HTVs), which are distinguished from deep-sea HTVs by a depth limit of 200 m. In this study, we analyzed metagenomes of sulfur-rich sediment samples collected from a SW-HTV of Kueishan Island, located in a marginal sea of the western Pacific Ocean. Comparing with a previously published report of pelagic samples from the nearby sampling site, microbial communities in the SW-HTV sediments enriching with genes of both aerobic and anaerobic respiration inferred variable environments in the tested sediments. Abundant genes of energy metabolism encoding sulfur oxidation, H2 oxidation, and carbon fixation were detected from the sediment samples. Sixty-eight metagenome-assembled-genomes (MAGs) were reconstructed to further understand the metabolism and potential interactions between different microbial taxa in the SW-HTVs sediment. MAGs with the highest abundant were chemolithotrophic sulfur-oxidization bacteria, including Sulfurovum represented Campylobacteria involved sox multienzyme, sulfide oxidation genes and rTCA cycle, and Gammaproteobacteria involved dsr gene and CBB cycle. In addition, Desulfobacterota with the potential to participate in sulfur-disproportionating processes also had higher abundance than the sample’s overall mean value. The interaction of these bacterial groups allows the microbial communities to efficiently metabolize a large variety of sulfur compounds. In addition, the potential to use simple organic carbon, such as acetate, was found in chemolithotrophic Campylobacterial MAGs. Collectively, our results revealed the complexity of environmental conditions of the vent sediment and highlight the interactive relationships of the dominant microbial populations in driving sulfur cycles in the SW-HTV sediments off Kueishan Island.

The market size of live streaming on the Internet, in which the streamer earns profit by prompting users to give virtual gifts through emotional labor, is getting bigger and bigger. However, most users will only buy cheap virtual gifts in live streaming, therefore exploring how to promote users to buy expensive virtual gifts is a valuable topic in live commerce research. Based on social presence theory and information overload theory, this study used the PLS-SEM method to investigate the factors influencing live streaming users to shift from buying cheap virtual gifts to buying expensive virtual gifts, and analyzed the moderating role of information overload in these relationships. The results show that immediate interaction anxiety, verbal intimacy, and virtual physical intimacy positively influence users’ shift to purchasing expensive virtual gifts, and that perceived network size and perceived financial risk are negative factors in users’ shift to purchasing expensive virtual gifts. Information overload has a moderating role in the relationship between immediate interaction anxiety and switch intention, and it also plays a moderating role in the relationship between perceived network size and perceived financial risk on users’ switch intention.

With Facebook’s name changing to Meta, the metaverse concept has become popular again. There are many indications that the current fashionableness of the metaverse is not driven by technical factors, rather related to the public hype. To clarify the reasons for the increasing popularity of the concept, this study develops a model based on embodied social presence theory. We surveyed 292 metaverse users, and analyzed the obtained data using partial least squares structural equation modeling (PLS-SEM). The results show that the main technical factors influencing the metaverse popularity do not significantly predict users’ embodied presence and embodied co-presence, while users’ imagination positively predicts their embodied presence in the metaverse and positively influences users’ willingness to continuously participate through the multiple mediating effects of embodied presence and co-presence. The results of this study confirm, to some extent, that user imagination triggered by public opinion drives the popularity of the metaverse.

Bacillota are widely distributed in various environments, owing to their versatile metabolic capabilities and remarkable adaptation strategies. Recent studies reported that Bacillota species were highly enriched in cold seep sediments, but their metabolic capabilities, ecological functions, and adaption mechanisms in the cold seep habitats remained obscure. In this study, we conducted a systematic analysis of the complete genome of a novel Bacillota bacterium strain M8S5, which we isolated from cold seep sediments of the South China Sea at a depth of 1151 m. Phylogenetically, strain M8S5 was affiliated with the genus Abyssisolibacter within the phylum Bacillota. Metabolically, M8S5 is predicted to utilize various carbon and nitrogen sources, including chitin, cellulose, peptide/oligopeptide, amino acids, ethanolamine, and spermidine/putrescine. The pathways of histidine and proline biosynthesis were largely incomplete in strain M8S5, implying that its survival strictly depends on histidine- and proline-related organic matter enriched in the cold seep ecosystems. On the other hand, strain M8S5 contained the genes encoding a variety of extracellular peptidases, e.g., the S8, S11, and C25 families, suggesting its capabilities for extracellular protein degradation. Moreover, we identified a series of anaerobic respiratory genes, such as glycine reductase genes, in strain M8S5, which may allow it to survive in the anaerobic sediments of cold seep environments. Many genes associated with osmoprotectants (e.g., glycine betaine, proline, and trehalose), transporters, molecular chaperones, and reactive oxygen species-scavenging proteins as well as spore formation may contribute to its high-pressure and low-temperature adaptations. These findings regarding the versatile metabolic potentials and multiple adaptation strategies of strain M8S5 will expand our understanding of the Bacillota species in cold seep sediments and their potential roles in the biogeochemical cycling of deep marine ecosystems.

As the research of HCPS in EI is ongoing, an increasing number of problems should be addressed, such as the leading role or aid function definition of humans, the coordination of humans with cyber and physical equipment, the state awareness of information handling, etc. Therefore, an increasing number of advanced techniques should be considered and adopted, such as IOT, AI and big data, etc., the main target of which is to improve the timely, digitalized, informationized and intelligent characters of the related tasks. This paper first introduces the applications of CPS in every industry, especially in the power grid and EI (Energy Internet), the introduction of which can be classified as a framework design, support technologies and algorithms, system function, power ancillary service, Energy Internet realization, etc. Then, this paper summarizes the related technologies of Human-Cyber-Physical Systems, which mainly include the areas of system design, theoretical analysis, technique development and application forecasting, which emphasizes its applications in EI. For the development of HCPS, it uses the human-in-the-loop concept and digital transformation as the future research and development directions, the performance of which can be largely promoted through these means. With the aid of HCPS, the optimal system performance of EI can be achieved more robustly, which finally evolves into an integrated and comprehensive modern power grid.

Abstract Background The full biosphere structure and functional exploration of the microbial communities of the Challenger Deep of the Mariana Trench, the deepest known hadal zone on Earth, lag far behind that of other marine realms. Results We adopt a deep metagenomics approach to investigate the microbiome in the sediment of Challenger Deep, Mariana Trench. We construct 178 metagenome-assembled genomes (MAGs) representing 26 phyla, 16 of which are reported from hadal sediment for the first time. Based on the MAGs, we find the microbial community functions are marked by enrichment and prevalence of mixotrophy and facultative anaerobic metabolism. The microeukaryotic community is found to be dominated by six fungal groups that are characterized for the first time in hadal sediment to possess the assimilatory and dissimilatory nitrate/sulfate reduction, and hydrogen sulfide oxidation pathways. By metaviromic analysis, we reveal novel hadal Caudovirales clades, distinctive virus-host interactions, and specialized auxiliary metabolic genes for modulating hosts’ nitrogen/sulfur metabolism. The hadal microbiome is further investigated by large-scale cultivation that cataloged 1070 bacterial and 19 fungal isolates from the Challenger Deep sediment, many of which are found to be new species specialized in the hadal habitat. Conclusion Our hadal MAGs and isolates increase the diversity of the Challenger Deep sediment microbial genomes and isolates present in the public. The deep metagenomics approach fills the knowledge gaps in structure and diversity of the hadal microbiome, and provides novel insight into the ecology and metabolism of eukaryotic and viral components in the deepest biosphere on earth.

Abstract Energy internet (EI) can alleviate the arduous challenges brought about by the energy crisis and global warming and has aroused the concern of many scholars. In the research of EI control systems, the access of distributed energy causes the power system to exhibit complex nonlinearity, high uncertainty and strong coupling. Traditional control and optimization methods often have limited effectiveness in solving these problems. With the widespread application of distributed control technology and the maturity of artificial intelligence (AI) technology, the combination of distributed control and AI has become an effective method to break through current research bottlenecks. This study reviews the research progress of EI distributed control technologies based on AI in recent years. It can be found that AI‐based distributed control methods have many advantages in maintaining EI stability and achieving optimal energy management. This combination of AI and distributed control makes EI control systems more intelligent, safe and efficient, which will be an important direction for future research. The purpose of this study is to provide a reference as well as useful research ideas for the study of EI control systems.

Understanding the complete map of melatonin synthesis, the information transfer network among circadian genes in pineal gland, promises to resolve outstanding issues in endocrine systems and improve the clinical diagnosis and treatment level of insomnia, immune disease and hysterical depression. Currently, some landmark studies have revealed some genes that regulate circadian rhythm associated with melatonin synthesis. However, these studies don't give a complete map of melatonin synthesis, as transfer information among circadian genes in pineal gland is lost. New biotechnology, integrates dynamic sequential omics and multiplexed imaging method, has been used to visualize the complete process of melatonin synthesis. It is found that there are two extremely significant information transfer processes involved in melatonin synthesis. In the first stage, as the light intensity decreased, melatonin synthesis mechanism has started, which is embodied in circadian genes, Rel, Polr2A, Mafk, and Srbf1 become active. In the second stage, circadian genes Hif1a, Bach1, Clock, E2f6, and Per2 are regulated simultaneously by four genes, Rel, Polr2A, Mafk, and Srbf1 and contribute genetic information to Aanat. The expeditious growth in this technique offer reference for an overall understanding of gene-to-gene regulatory relationship among circadian genes in pineal gland. In the study, dynamic sequential omics and the analysis process well provide the current state and future perspectives to better diagnose and cure diseases associated with melatonin synthesis disorder.

The architecture of cloud–edge collaboration can improve the efficiency of Internet of Things (IoT) systems. Recent studies have pointed out that using IoT terminal devices as destinations for computing offloading can promote further optimized allocation of computational resources. However, in practice, this idea encounters the problem that participants might lack the motivation to take over computational tasks from others. Although the edge and the terminal are provided with symmetrical positions in collaborative offloading, their computational resources and capabilities are asymmetric. To mitigate this issue, this paper designs a distributed strategy for the trading of computational resources. The most prominent feature of our strategy is its multi-preference optimization objective that takes into account the overall satisfaction with task delay, energy cost, trading prices, and user reputation of participants. In addition, this paper proposes a system architecture based on the Blockchain-as-a-Service (BaaS) design to give full play to the good distributed technology features of blockchain, such as decentralization, traceability, immutability, and automation. Meanwhile, BaaS delivers decentralized identifier (DID) based distributed identity infrastructure for the distributed computational resource trading stakeholders as well. In the simulation evaluation, we compare our trading strategy based on a matching mechanism called multi-preference matching (MPM) to trading using the classical double auction (DA) matching mechanism. The results show that our computational resource trading strategy is able to offload and execut more tasks, achieving a better throughput compared to the DA-based strategy.

Shewanella species are widely distributed in various environments, especially deep-sea sediments, due to their remarkable ability to utilize multiple electron receptors and versatile metabolic capabilities. In this study, a novel facultatively anaerobic, psychrophilic, and piezotolerant bacterium, Shewanella sp. MTB7, was isolated from the Mariana Trench at a depth of 5900 m. Here, we report its complete genome sequence and adaptation strategies for survival in deep-sea environments. MTB7 contains what is currently the third-largest genome among all isolated Shewanella strains and shows higher coding density than neighboring strains. Metabolically, MTB7 is predicted to utilize various carbon and nitrogen sources. D-amino acid utilization and HGT-derived purine-degrading genes could contribute to its oligotrophic adaptation. For respiration, the cytochrome o ubiquinol oxidase genes cyoABCDE, typically expressed at high oxygen concentrations, are missing. Conversely, a series of anaerobic respiratory genes are employed, including fumarate reductase, polysulfide reductase, trimethylamine-N-oxide reductase, crotonobetaine reductase, and Mtr subunits. The glycine reductase genes and the triplication of dimethyl sulfoxide reductase genes absent in neighboring strains could also help MTB7 survive in low-oxygen environments. Many genes encoding cold-shock proteins, glycine betaine transporters and biosynthetic enzymes, and reactive oxygen species-scavenging proteins could contribute to its low-temperature adaptation. The genomic analysis of MTB7 will deepen our understanding of microbial adaptation strategies in deep-sea environments.

Knowledge sharing not only promotes communication among teachers to achieve self-professional growth but also facilitates knowledge innovation. Thus, knowledge sharing among preschool teachers deserves attention. This study explored the factors influencing preschool teachers’ knowledge-sharing behaviors. A questionnaire was administered to 297 preschool teachers using a Norm Activation Model from a thinking style perspective. Data analysis was performed using partial least square-structural equation modelling (PLS-SEM). The findings indicate that executive thinking style preschool teachers showed a significant positive influence of awareness of consequences; legislative thinking style preschool teachers showed a significant positive influence of awareness of consequences and ascription of responsibility; awareness of consequences had a significant positive influence on ascription of responsibility; awareness of consequences and ascription of responsibility had a significant positive influence on personal norms; and personal norms had a significant positive influence on knowledge-sharing behavior. Meanwhile, the influence of executive thinking style on ascription of responsibility, legislative thinking style on ascription of responsibility, and awareness of consequences on personal norms emerged as significantly different among preschool teachers in two different contexts: interpersonal sharing and Internet sharing. This study confirmed the factors influencing preschool teachers’ knowledge-sharing behaviors from a thinking style perspective and provides suggestions for improving preschool teachers’ knowledge-sharing behaviors.

Based on the cross-sectional data of 40 large-scale international airports in China in 2019, this paper introduced natural and social factors into the calculation of airport operating efficiency and constructed a BCC-SFA-BCC-Tobit 4-stage analysis framework. Combining with the connotation of the “green, smart, humane, and safe” airport high-quality development, the paper applied the Tobit model to quantitatively analyze the influencing factors of the operating efficiency of airports, and the research shows that (1) the overall operating efficiency of the study airports is 0.734; in terms of the region, the operating efficiency of airports located in southwest and northwest regions is greatly affected by natural factors, while the operating efficiency of airports located in North China is mostly affected by social factors. (2) Under the perspective of human-earth relationship, the impact of natural factors on the operating efficiency of airports is greater than that of social factors, wherein PM2.5 and relative humidity have negative impact, while the actual foreign capital utilization of the city and domestic and foreign tourists have positive impact. (3) The regression results of the Tobit model indicate that green, smart, and safe indicators can promote the high-quality development of airports, while the humane indicator restrains the high-quality development of airports.

The increase in the number of elderly patients with degenerative diseases has brought additional medical and financial pressures, which are adding to the burden on society. The development of sports rehabilitation robotics (SRR) is becoming increasingly sophisticated at the technical level of its application; however, few studies have analyzed how it works and how effective it is in aiding rehabilitation, and fewer individualized exercise rehabilitation programs have been developed for elderly patients. The purpose of this study was to analyze the working methods and the effects of different types of SRR and then to suggest the feasibility of applying SRR to enhance the physical abilities of elderly patients with degenerative diseases. The researcher’s team searched 633 English-language journal articles, which had been published over the past five years, and they selected 38 of them for a narrative literature review. Our summary found the following: (1) The current types of SRR are generally classified as end-effector robots, smart walkers, intelligent robotic rollators, and exoskeleton robots—exoskeleton robots were found to be the most widely used. (2) The current working methods include assistant tools as the main intermediaries—i.e., robots assist patients to participate; patients as the main intermediaries—i.e., patients dominate the assistant tools to participate; and sensors as the intermediaries—i.e., myoelectric-driven robots promote patient participation. (3) Better recovery was perceived for elderly patients when using SRR than is generally achieved through the traditional single-movement recovery methods, especially in strength, balance, endurance, and coordination. However, there was no significant improvement in their speed or agility after using SRR.

As the COVID-19 pandemic progressed, the resulting demand for telemedicine services increased. This research empirically examines the role of trust, privacy concerns, and perceived usefulness in customer confirmation, satisfaction, and continuing intention in telemedicine. A typology of trust was employed to classify trust into three dimensions and explore the mediating role of the three dimensions of trust in the relationship between satisfaction, perceived usefulness, and continued intention. We also examined the moderating role of personal privacy concerns in the relationship between trust and continued intention. For this study, we developed a structural equation model based on expectation confirmation theory and analyzed 465 questionnaires from Chinese online users. The expectancy confirmation theory (ECT) was reaffirmed by empirical evidence. The results showed that the relationship between perceived usefulness and satisfaction with continued intention is moderated by the three dimensions of trust. Privacy concerns can negatively moderate the relationship between structural assurance-based trust and continued intention. This study also identified potential threats to telehealth market growth alongside new insights.

The state of charge (SOC) for a lithium-ion battery is a key index closely related to battery performance and safety with respect to the power supply system of electric vehicles. The Kalman filter (KF) or extended KF (EKF) is normally employed to estimate SOC in association with the relatively simple and fast second-order resistor-capacitor (RC) equivalent circuit model for SOC estimations. To improve the stability of SOC estimation, a two-stage method is developed by combining the second-order RC equivalent circuit model and the eXogenous Kalman filter (XKF) to estimate the SOC of a lithium-ion battery. First, approximate SOC estimation values are observed with relatively poor accuracy by a stable observer without considering parameter uncertainty. Second, the poor accuracy SOC results are further fed into XKF to obtain relative stable and accurate SOC estimation values. Experiments demonstrate that the SOC estimation results of the present method are superior to those of the commonly used EKF method. It is expected that the present two-stage XKF method will be useful for the stable and accurate estimation of SOC in the power supply system of electric vehicles.

A revised version of the ISO9001:2015 quality management system is an indispensable element for a corporation to survive against the severe competition and maintain sustainable, competitive superiority, as well as a new outlook. With this in mind, the first purpose of this research was to seek customer satisfaction through the continuous improvement of the organization in the IoT industry. Furthermore, it aimed to lay a foundation for a preemptive response and formulate a management strategy regarding the continuity of the business. Simultaneously, we explored whether the scale items of the lower-ranking level resulting from the latent variables in the main provision of the revised edition are the variables that can sufficiently explain the latent variables. Furthermore, the statistical programs of the SPSS22.0 and the AMOS18.0 were utilized for analysis. The results demonstrated that corporations can achieve customer satisfaction through continuous improvements concerning the successful introduction and conversion of the new quality management system. It was confirmed that the core variables of the revised edition sufficiently explained the latent variables. Consequently, it is imperative to understand the latent risks from the internal and external environments surrounding the organization and formulate the short-term and long-term strategies of the organization on the part of a corporation.

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With the rapid development of industry 4.0 and the boom of large-scale product customization, the adoption of collaborative robots’ innovation becomes a hot topic in research. Previous studies have mainly focused on individuals, but few on enterprises, and in particular, there has been a lack of empirical research on the enterprise level. Based on the combined model of Technology-Organization-Environment Framework (TOE) and Diffusion of Innovations Theory (DOI), this study investigated 373 small and medium-sized enterprises (SMEs) in Guangdong Province, China, to explore the determinants of SMEs’ adoption of collaborative robot innovation in technology, organization, and environment. The result shows that the technical factors of relative advantage, compatibility, observability, and trialability have a significant positive correlation with the adoption of collaborative robots, while complexity has a significant negative correlation with the adoption. Among the organizational factors, top management support and organizational readiness have a significant positive correlation with the adoption of collaborative robots. Among the environmental factors, agent support is positively and significantly correlated with adoption. The findings will help practitioners develop appropriate strategies for the adoption of collaborative robot innovation.

During the COVID-19 pandemic, many countries have used digital contact tracing apps (DCTAs) to implement contact tracing. Although the use of DCTAs has contributed to the prevention and control of COVID-19, there are doubts in academia about their actual effectiveness. In this study, the role of DCTAs in the prevention of COVID-19 was analyzed in terms of both the responsibility and inconvenience to life in a large-scale DCTA overuse environment, based on the normative activation model. The findings suggest that the overuse of a DCTA activates people’s personal norms by triggering awareness of the consequences and ascription of responsibility, leading people to consistently cooperate with the government to prevent COVID-19. However, the inconvenience of living with DCTA overuse weakens the effect of the awareness of consequences and ascription of responsibility and the role of the ascription of responsibility in influencing personal norms. These effects may bear on people’s willingness to consistently cooperate with the government to prevent COVID-19. The results of this study confirm the effectiveness of DCTA in counteracting pandemics from a social responsibility perspective in a large-scale environment where DCTA is used, enriching the literature on DCTA research in the COVID-19 pandemic. The results of this study can also help governments develop and improve policies to prevent COVID-19, as well as improve the DCTAs’ operating patterns.

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Advanced LIGO and Advanced Virgo are monitoring the sky and collecting gravitational-wave strain data with sufficient sensitivity to detect signals routinely. In this paper we describe the data recorded by these instruments during their first and second observing runs. The main data products are gravitational-wave strain time series sampled at 16384 Hz. The datasets that include this strain measurement can be freely accessed through the Gravitational Wave Open Science Center at http://gw-openscience.org, together with data-quality information essential for the analysis of LIGO and Virgo data, documentation, tutorials, and supporting software.