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Abstract Microplastic pollution, an emerging environmental issue, poses significant threats to aquatic ecosystems and human health. In tackling microplastic pollution and advancing green hydrogen production, this study reveals a tandem catalytic microplastic degradation-hydrogen evolution reaction (MPD-HER) process using hierarchical porous carbon nitride-supported single-atom iron catalysts (FeSA-hCN). Through hydrothermal-assisted Fenton-like reactions, we accomplish near-total ultrahigh-molecular-weight-polyethylene degradation into C3-C20 organics with 64% selectivity of carboxylic acid under neutral pH, a leap beyond current capabilities in efficiency, selectivity, eco-friendliness, and stability over six cycles. The system demonstrates versatility by degrading various daily-use plastics across different aquatic settings. The mixture of FeSA-hCN and plastic degradation products further achieves a hydrogen evolution of 42 μmol h‒1 under illumination, outperforming most existing plastic photoreforming methods. This tandem MPD-HER process not only provides a scalable and economically feasible strategy to combat plastic pollution but also contributes to the hydrogen economy, with far-reaching implications for global sustainability initiatives.

Micro‐/nanomotors (MNMs) in water remediation have garnered significant attention over the past two decades. More recently, metal‐organic framework‐based micro‐/nanomotors (MOF‐MNMs) have been applied for environmental remediation; however, a comprehensive summary of research in this research area is yet to be reported. Herein, a review is presented to cover the recent advances in MOF‐MNMs and their various applications in wastewater remediation. The review presents a comprehensive introduction to MNMs, including different propulsion approaches, fabrication, and functionalization strategies, in addition to the unique features of MOF‐MNMs. The conception and various synthetic routes of MOF‐MNMs are extensively covered and the implementation of MOF‐MNMs in water‐related applications, including adsorption, degradation, sensing, and disinfection of different pollutants, is in depth discussed. Meanwhile, the propulsion and mechanism of action behind each MOF‐MNM are systematically studied. Finally, the review provides insights into the challenges and perspectives to build more effective MOF‐MNMs to cover versatile applications for wastewater treatment.

The COVID-19 outbreak has garnered significant global attention due to its impact on human health. Despite its relatively low fatality rate, the virus affects multiple organ systems, resulting in various symptoms such as palpitations, headaches, muscle pain, and hearing loss among COVID-19 patients and those recovering from the disease. These symptoms impose a substantial physical, psychological, and social burden on affected individuals. On February 15, 2020, the Chinese government advised incorporating antimalarial drugs into the guidelines issued by the National Health Commission of China for preventing, diagnosing, and treating COVID-19 pneumonia. We examine the adverse effects of Chloroquine (CQ) in treating COVID-19 complications to understand why it is no longer the primary treatment for the disease.

In the process of mariculture, a large number of toxic and harmful substances such as organic matter, ammonia, and nitrite are produced during the metabolism of cultured organisms and the decomposition of feed residuals. If such maricultural wastewater is discharged without purification treatment, it will aggravate the occurrence of eutrophication in the receiving sea area. Constructed wetlands (CW) have received widespread attention due to their low operating costs, simple maintenance, and management advantages. Using CW to treat maricultural wastewater has great prospects. Nitrogen removal is one of the main tasks of constructed wetlands. The characteristics of high salinity and low C/N of maricultural wastewater result in the unique treatment environment and operating mechanism of CW. The substrate can adsorb nitrogen in the constructed wetlands, and nitrogen-cycling microorganisms such as nitrifying bacteria and denitrifying bacteria can attach to the surface to form biofilms. The selection of suitable substrate materials, in addition to zeolite, cinder, sand, and other commonly used water purification materials, can strengthen water purification. Given the low C/N characteristics of maricultural wastewater, materials with slow-release carbon sources can be selected as the filling substrate of constructed marine wetlands. For example, biological carbon sources such as corncob and wood chips, and polymer materials such as PCL and PLC, have recently been used as substrates to fill constructed wetlands and release carbon sources. Meanwhile, substrates that can drive the autotrophic denitrification process of microorganisms such as sulfur autotrophic, hydrogen autotrophic, and iron autotrophic have also been used as a solution. Plants are an important component of constructed marine wetlands, supporting nitrogen removal in four aspects: Nitrogen absorption, oxygen transport, carbon source secretion, and root enrichment of microorganisms. The high salinity environment determines that the wetland plants should be salt-tolerant, and the screening of salt-tolerant plants is a key step in constructed marine wetlands. Currently, Spartina alterniflora, Suaeda salsa, Salicornia bigelovii, Kandelia candel, and similar plants are chosen as candidate plants for constructed marine wetlands. The selection of plants should also consider local conditions, choosing salt-tolerant plants suitable for growing in the local environment. The nitrogen cycle of microorganisms is the main path of biological nitrogen removal in CWs. Various nitrogen-metabolizing bacteria cooperate and restrict each other in CWs, including autotrophic and heterotrophic bacteria, as well as aerobic and anaerobic bacteria. In the process of nitrogen removal in constructed wetlands, dissolved oxygen (DO) is an important environmental factor affecting the distribution and functioning of nitrogen-removing microorganisms. The relatively high DO in the upper layer of the constructed wetland favors the growth and reproduction of aerobic microorganisms, promoting the traditional nitrification process dominated by AOA, AOB, and NOB. The relatively low DO in the bottom layer is more conducive to the growth and colonization of anoxic and anaerobic microorganisms, favoring anaerobic denitrification, Anammox, and DNRA. The occurrence of Comammox can be driven under low nutrient and low oxygen conditions. These bacteria with nitrogen metabolism functions are distributed in different areas, cooperating and restricting each other, forming a complex nitrogen cycle network. Clarifying the basic path of the nitrogen cycle in seawater constructed wetlands is the fundamental basis for regulating the operating parameters of constructed wetlands. The low C/N of mariculture wastewater is not favorable for denitrification by microorganisms. Carbon sources can be supplemented with additional liquid carbon sources, solid carbon sources, and plant litter. DO is the key control index of constructed marine wetlands. The dissolved oxygen content in constructed wetlands is significantly correlated with the community composition of denitrification microorganisms. Therefore, oxygen supply regulation modes, such as continuous aeration, intermittent aeration, and tidal flow, may be effective measures for mariculture wastewater constructed wetlands to improve the overall nitrogen removal performance of wetlands. Accurate regulation of the oxygen supply mode and oxygen supply in constructed wetlands and optimization of dissolved oxygen distribution in different times and spaces within the system are the development trends of nitrogen removal technology in constructed wetlands in the future. The hydraulic operation conditions of CW play an important role in its nitrogen removal effect. Too high or too low indices will affect the efficiency of nitrogen removal in wetlands. Therefore, the optimal control values of hydraulic retention time (HRT), hydraulic loading rate (HLR), and other hydraulic parameters of constructed wetlands also need to be studied. The hydraulic conditions of constructed wetlands also have a significant impact on plant growth, affecting the purification efficiency of plants. In this paper, recent research progress and perspectives on constructed wetlands for the purification of maricultural wastewater and its biological nitrogen removal process were reviewed from four aspects: Selection of substrate, screening of salt-tolerant plants, nitrogen cycling microorganisms, and operation regulation. It is expected to provide a theoretical basis and support for regulating the actual operation of maricultural wastewater constructed wetlands and improving the technical level of maricultural wastewater treatment.

Pulmonary invasive fungal infection in immunocompromised hosts is difficult to diagnose, and current tools for diagnosis or monitoring of response to antifungal treatments have inherent limitations. Droplet digital PCR (ddPCR) has emerged as a promising tool for pulmonary pathogen detection with high sensitivity. This study presents a novel ddPCR panel for rapid and sensitive identification of pulmonary fungal pathogens. First, a ddPCR method for detecting three fungal genera, including Pneumocystis, Aspergillus, and Cryptococcus, was established and evaluated. Then, the clinical validation performance of ddPCR was compared with that of qPCR using 170 specimens, and the 6 specimens with inconsistent results were further verified by metagenomics next-generation sequencing, which yielded results consistent with the ddPCR findings. Finally, the area under the ROC curve (AUC) was used to evaluate the efficiency of ddPCR. While the qPCR identified 16 (9.41%) cases of Aspergillus and 6 (3.53%) cases of Pneumocystis, ddPCR detected 20 (11.76%) Aspergillus cases and 8 (4.71%) Pneumocystis cases. The AUC for Aspergillus, Cryptococcus, and Pneumocystis was 0.974, 0.998, and 0.975, respectively. These findings demonstrated that the ddPCR assay is a highly sensitive method for identifying pathogens responsible for invasive fungal pulmonary infections, and is a promising tool for early diagnosis.

Summarizing the causation of an aviation accident is beneficial for improving aviation safety. Currently, accident analysis mainly focuses on causal analysis, while giving less consideration to the correlation between accident causal factors and other accident factors. To clarify accident causal factors and potential patterns affecting aviation safety and to optimize data mining methods for accident causal factors, this work proposes an aviation accident causation correlation analysis model based on a knowledge graph. Firstly, the accident causal factors are identified, and a knowledge graph is constructed. Subsequently, by utilizing multi-dimensional topological analysis metrics, an aviation accident causation correlation analysis model is established, using the relationships within accident causal factors as a foundation, to determine potential patterns among accident causal factors, flight phases, accident types, and consequences and to analyze the key accident causal factors influencing accident occurrences across different flight phases. Finally, preventive measures and recommendations are provided based on the analysis conclusions. Through a case study using 437 global aviation accidents from 2018 to 2022 as samples and employing the knowledge graph-based aviation accident causation correlation analysis model, the causation relationships among accident causal factors can be expressed more clearly, the potential risks of various accident causal factors can be identified, experiences can be gained from historical accident data, and underlying patterns can be unearthed. This work can provide auxiliary decision making and be an effective reference for the prevention of aviation accidents, playing a positive role in enhancing the level of aviation safety management.

CO2 is one of the primary greenhouse gases impacting global climate change, making it crucial to understand the spatiotemporal variations of CO2. Currently, commonly used satellites serve as the primary means of CO2 observation, but they often suffer from striping issues and fail to achieve complete coverage. This paper proposes a method for constructing a comprehensive high-spatiotemporal-resolution XCO2 dataset based on multiple auxiliary data sources and satellite observations, utilizing multiple simple deep neural network (DNN) models. Global validation results against ground-based TCCON data demonstrate the excellent accuracy of the constructed XCO2 dataset (R is 0.94, RMSE is 0.98 ppm). Using this method, we analyze the spatiotemporal variations of CO2 in China and its surroundings (region: 0°–60° N, 70°–140° E) from 2019 to 2020. The gapless and fine-scale CO2 generation method enhances people’s understanding of CO2 spatiotemporal variations, supporting carbon-related research.

Background: Glioma is the most frequent type of malignancy that may damage the brain with high morbidity and mortality rates and patients' prognoses are still dismal. Ferroptosis, a newly uncovered mode of programmed cell death, may be triggered to destroy glioma cells. Nevertheless, the significance of ferroptosis-related genes (FRGs) in predicting prognosis in glioma individuals is still a mystery. Methods: The CGGA (The Chinese Glioma Atlas), GEO (Gene Expression Omnibus), and TCGA (The Cancer Genome Atlas) databases were all searched to obtain the glioma expression dataset. First, TCGA was searched to identify differentially expressed genes (DEGs). This was followed by a machine learning algorithm-based screening of the glioma's most relevant genes. Additionally, these genes were subjected to Gene Ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) functional enrichment analyses. The chosen biological markers were then submitted to single-cell, immune function, and gene set enrichment analysis (GSEA). In addition, we performed functional enrichment and Mfuzz expression profile clustering on the most promising biological markers to delve deeper into their regulatory mechanisms and assess their clinical diagnostic capacities. Results: We identified 4444 DEGs via differential analysis and 564 FRGs from the FerrDb database. The two were subjected to intersection analysis, which led to the discovery of 143 overlapping genes. After that, glioma biological markers were identified in fourteen genes by the use of machine learning methods. In terms of its use for clinical diagnosis, SMG9 stands out as the most significant among these biomarkers. Conclusion: In light of these findings, the identification of SMG9 as a new biological marker has the potential to provide information on the mechanism of action and the effect of the immune milieu in glioma. The promise of SMG9 in glioma prognosis prediction warrants more study.

Groundwater with high concentrations of iron and manganese is harmful to the human body and modern industries. Conventional methods of treating iron and manganese have the disadvantage of high costs and complex control processes. A dielectric barrier discharge (DBD) water treatment system was built to remove iron and manganese from groundwater in this paper. Single-factor experiments were used to analyze the effect of discharge power, initial iron and manganese concentrations, gas flow rate, liquid flow rate, initial pH, flocculant and capture agent process parameters on iron and manganese removal rates. It was found that Fe2+ removal rates can reach 97.31% and Mn2+ removal rates can reach 81.42% when the initial concentrations of Fe2+ and Mn2+ are 6 and 3 mg/L, respectively. The use of 10 mg/L NaHCO3 or 5 mg/L Ca(OH)2 increased the removal rate of Fe2+ to 99% but had no effect on the removal rate of Mn2+. It was found that the optimum treatment time for Mn2+ was different for different process parameters, mainly in the range of 9–15 min, which needs to be noted in future production applications. This work shows that DBD can effectively remove iron and manganese ions from groundwater and analyzes the removal mechanism. HIGHLIGHTS The removal of iron and manganese from groundwater was investigated.; The effect of individual factors on the removal of iron and manganese was analyzed.; DBD removed up to 97.31% of Fe2+.; DBD removed up to 81.42% of Mn2+.;

In the food domain, text mining techniques are extensively employed to derive valuable insights from large volumes of text data, facilitating applications such as aiding food recalls, offering personalized recipes, and reinforcing food safety regulation. To provide researchers and practitioners with a comprehensive understanding of the latest technology and application scenarios of text mining in the food domain, the pertinent literature is reviewed and analyzed. Initially, the fundamental concepts, principles, and primary tasks of text mining, encompassing text categorization, sentiment analysis, and entity recognition, are elucidated. Subsequently, an analysis of diverse types of data sources within the food domain and the characteristics of text data mining is conducted, spanning social media, reviews, recipe websites, and food safety reports. Furthermore, the applications of text mining in the food domain are scrutinized from the perspective of various scenarios, including leveraging consumer food reviews and feedback to enhance product quality, providing personalized recipe recommendations based on user preferences and dietary requirements, and employing text mining for food safety and fraud monitoring. Lastly, the opportunities and challenges associated with the adoption of text mining techniques in the food domain are summarized and evaluated. In conclusion, text mining holds considerable potential for application in the food domain, thereby propelling the advancement of the food industry and upholding food safety standards.

The three-degrees-of-freedom (3-DOF) parallel robot is commonly employed as a shipborne stabilized platform for real-time compensation of ship disturbances. Pose accuracy is one of its most critical performance indicators. Currently, neural networks have been applied to the kinematic calibration of stabilized platforms to compensate for pose errors and enhance motion accuracy. However, collecting a large amount of measured configuration data for robots entails high costs and time, which restricts the widespread use of neural networks. In this study, a “transfer network” is established by combining fine-tuning with a Back Propagation (BP) neural network. This network takes the motion transmission characteristics inherent in the ideal kinematic model as prior knowledge and transfers them to a network trained based on the actual poses. Compared with the conventional BP neural network trained by actual poses alone, the transfer network shows significant performance advantages, effectively solving the problems of low prediction accuracy and weak generalization ability in the case of small-sample measured data. Considering this, the impact pattern of the sample number of the actual pose on the effectiveness of transfer learning is revealed through the construction of multiple transfer network models under varying sample numbers of the actual pose, providing valuable marine engineering guidance. Finally, simulated sea-service experiments were conducted on the 3-UPS/S shipborne stabilized platform to validate the correctness and superiority of the proposed method.

Objectives: The aim of this study is to understand the feelings and experiences of the main caregivers of temporary ostomy patien ts with Crohn's disease (CD). And explore the caregivers' inner feelings, to provide reference and basis for constructing the health education content of the main caregivers of CD patients with a temporary stoma. Methods: A qualitative descriptive approach was used to conduct an unstructured interview among 11 primary caregivers of CD patients with temporary enterostomy from the gastroenterology department of The Second Hospital of Nanjing. Participants were selected using a purposive sampling technique. Data were collected between July 2021 and September 2021. The interviews were audio recorded and then transcribed for a qualitative thematic analysis. Results: Five themes and accompanying subthemes were identified: (1) negative psychological experience (2) perceived caregiver burden (3) future uncertainty (4) disease benefit (5) insufficien support system. Conclusions: Study findings suggest that caregivers of CD temporary enterostomy patients have problems such as negative psychology, heavy caregiver burden, uncertain future, lack of support system, etc., but they also have positive experience of feeling of benefit from the disease, and are eager to obtain more disease information from more channels.Therefore, medical staff should improve their professionalism and health education capabilities, carry out diversified and targeted health education activities to reduce the burden of care, stimulate positive caregiver responses and help caregivers respond to and deal with caregiving problems in a timely and accurate manner.

In light of the significance of regulatory authorities and the rising demand for information disclosure, a vast amount of information on food safety news reports is readily accessible on the Internet. The extraction of such information for precise classification and provision of appropriate safety alerts based on their respective categories has emerged as a challenging problem for academic research. Given that most food safety-related events in news reports comprise lengthy text, the pre-trained language models currently employed for text analysis are generally limited in their capability to handle long documents. This paper proposes a long-text classification model utilising hierarchical Transformers. We categorise information in long documents into two distinct types: (1) multiple text chunks meeting the length constraint and (2) essential sentences within long documents, such as headings, paragraph start and end sentences, etc. Initially, our proposed model utilises the text chunks as input to the BERT model. Then, it concatenates the output of the BERT model with the important sentences from the document and use them as input to the Transformer model for feature transformation. Finally, we utilise a classifier for food safety news classification. We conducted several comparative experiments with various commonly used text classification models on a dataset constructed from publicly available information on food regulatory websites. Our proposed method outperforms existing methods, establishing itself as the leading approach in terms of performance.

An effective approach for the large-scale fabrication of conducting polyaniline (PANI) using in situ anodic electrochemical polymerization on nickel foam which had been coated in aryl diazonium salt (ADS)-modified graphene (ADS-G). In the present work, ADS-G was used as a high surface-area support material for the electrochemical polymerization of PANI. The electrochemical performances of the ADS-G/PANI composites exhibited better suitability as supercapacitor electrode materials than those of the PANI. The ADS-G/PANI composites achieved a specific capacitance of 528 F g−1, which was higher than that of PANI (266 F g−1) due to excellent electrode–electrolyte interaction and the synergistic effect of electrical conductivity between ADS-G and PANI in the composites. These findings suggest that the ADS-G/PANI composites are a suitable composite for potential supercapacitor applications.

Aviation safety has been an eternal theme, and safety assessment is taken as the important method to assess the aircraft safety, but it is difficult to assess the safety of a heavy equipment airdrop from a transport aircraft due to mission complexity and strong coupling. This study uses an improved STPA-BN methodology to assess the safety of transport aircraft heavy equipment airdrop. To this purpose, qualitative safety analysis is performed by STPA, and then quantitative safety assessment is performed by BN. In contrast to the-state-of-the-art, the distinguishing feature of the proposed design lies in the introduction of DS evidence theory, which makes the probability of nodes in BN a priori. More precisely, best-worst multi-criteria decision-making method (BWM) is skillfully incorporated into the DS evidence theory so as to tackle the conflict issue that exists in most existing designs. Importance analysis is utilized to determine the importance of the different risk nodes. A case of transport aircraft heavy equipment airdrop mission is used to test the effectiveness of the proposed method.

Interfacial charge separation is an essential issue to restrict catalytic activity of photocatalysts. In this work, we report a promising and easy-to-handle strategy to modulate the activity of a C60-based photocatalyst (C60@Pt) for visible-light-driven hydrogen evolution reaction (HER) with the coupling of magnetic substance that had weak ferromagnetism (Fe3O4 microbeads as an instance). It is found that Fe3O4 microbeads played a pivotal role in boosting photocatalytic activity and apparent quantum efficiency of C60@Pt for visible-light-driven HER, as the weak local magnetic field it induced around C60@Pt contributed to facilitating the separation of photo electrons from electron-donor in reaction system.

Abstract Background The mutation of insulin-like growth factor 2 (IGF2 mutation) that a single-nucleotide substitution (G→A) in the third intron of IGF2 abrogates the interaction with zinc finger BED-type containing 6 (ZBED6) and leads to increased muscle mass in pigs. IGF2 mutation knock-in (IGF2 KI) and ZBED6 knockout (ZBED6 KO) lead to changes in IGF2 expression and increase muscle mass in mice and pigs. Long noncoding RNAs (lncRNAs) may participate in numerous biological processes, including skeletal muscle development. However, the role of the ZBED6-lncRNA axis in skeletal muscle development is poorly characterized. Results In this study, we assembled transcriptomes using RNA-seq data published in previous studies by our group and identified 11,408 known lncRNAs and 2269 potential lncRNAs in seven tissues, heart, longissimus dorsi, gastrocnemius muscle, liver, spleen, lung and kidney, of ZBED6 KO (lean mass model) and WT Bama pigs. ZBED6 affected the expression of 1570 lncRNAs (differentially expressed lncRNAs [DE-lncRNAs]; log2-fold change ≥ 1, nominal p-value ≤ 0.05) in the seven examined tissues. The expressed lncRNAs (FPKM > 0.1) exhibited tissue-specific patterns in WT pigs. Specifically, 3410 lncRNAs were expressed exclusively in only one tissue. Potential functions of lncRNAs were indirectly predicted by searching their target cis- and trans-regulated protein-coding genes. LncRNAs with tissue-specific expression influence numerous genes related to tissue functions. Weighted gene coexpression network analysis (WGCNA) of 1570 DE-lncRNAs between WT and ZBED6 KO pigs was used to define the following six lncRNA modules specific to different tissues: skeletal muscle, heart, lung, spleen, kidney and liver modules. Furthermore, by conjoint analysis of longissimus dorsi data (tissue-specific expression, muscle module and DE-lncRNAs) and ChIP-PCR revealed NONSUSG002145.1 (adjusted p-values = 0.044), which is coexpressed with the IGF2 gene and binding with ZBED6, may play important roles in ZBED6 KO pig skeletal muscle development. Conclusions These findings indicate that the identified lncRNAs may play essential roles in tissue function and regulate the mechanism of ZBED6 action in skeletal muscle development in pigs. To our knowledge, this is the first study describing lncRNAs in ZBED6 KO pigs. These results may open new research directions leading to a better understanding of the global functions of ZBED6 and of lncRNA functions in skeletal muscle development in pigs.

ZBED6, a key transcription factor, plays an important role in skeletal muscle and organ growth. ZBED6 knockout (ZBED6−/−) leads to the upregulation of IGF2 in pig and mice muscle, thereby increasing muscle mass. However, the effects and mechanism of Zbed6 single-allele knockout (Zbed6+/−) on mice muscle remain unknown. Here, we reported that Zbed6+/− promotes muscle growth by a new potential target gene rather than Igf2 in mice muscle. Zbed6+/− mice showed markedly higher muscle mass (25%) and a markedly higher muscle weight ratio (18%) than wild-type (WT) mice, coinciding with a larger muscle fiber area (28%). Despite a significant increase in muscle growth, Zbed6+/− mice showed similar Igf2 expression with WT mice, indicating that a ZBED6–Igf2-independent regulatory pathway exists in Zbed6+/− mice muscle. RNA-seq of muscle between the Zbed6+/− and WT mice revealed two terms related to muscle growth. Overlapping the DEGs and C2C12 Chip-seq data of ZBED6 screened out a potential ZBED6 target gene Barx2, which may regulate muscle growth in Zbed6+/− mice. These results may open new research directions leading to a better understanding of the integral functions of ZBED6 and provide evidence of Zbed6+/− promoting muscle growth by regulating Barx2 in mice.

Thanks to its simplicity, versatility, and secondary reactivity, dopamine self-polymerized coatings (pDA) have been widely used in surface modification of biomaterials, but the limitation in secondary molecular grafting and the high roughness restrain their application in some special scenarios. Therefore, some other catecholamine coatings analog to pDA have attracted more and more attention, including the smoother poly-norepinephrine coating (pNE), and the poly-levodopa coating (pLD) containing additional carboxyl groups. However, the lack of a systematic comparison of the properties, especially the biological properties of the above three catecholamine coatings, makes it difficult to give a guiding opinion on the application scenarios of different coatings. Herein, we systematically studied the physical, chemical, and biological properties of the three catecholamine coatings, and explored the feasibility of their application for the modification of biomaterials, especially cardiovascular materials. Among them, the pDA coating was the roughest, with the largest amount of amino and phenolic hydroxyl groups for molecule grafting, and induced the strongest platelet adhesion and activation. The pLD coating was the thinnest and most hydrophilic but triggered the strongest inflammatory response. The pNE coating was the smoothest, with the best hemocompatibility and histocompatibility, and with the strongest cell selectivity of promoting the proliferation of endothelial cells while inhibiting the proliferation of smooth muscle cells. To sum up, the pNE coating may be a better choice for the surface modification of cardiovascular materials, especially those for vascular stents and grafts, but it is still not widely recognized.

Safety is the eternal theme of aviation activities. With the rapid development of military technology and equipment construction, the new equipment requires safer and more reliable technology and management guarantees. The aim of this paper is to evaluate the safety level of equipment in a single-stage mission. The mission safety is defined as the capacity of equipment to avoid unacceptable accidents during mission execution. A safety analysis framework is constructed according to the logic of mission-function-safety structure. The mission profile ensures the success of the mission by specifying the functional requirements and the safety structure realizes the functional requirements by adjusting the structure and scheduling resources. On this basis, the functional dependency network analysis (FDNA) method is improved to study the interaction failures between the components in the specific state. A numerical simulation method for mission safety is proposed to analyze the evolution relationship between components and behaviors, which could obtain the mission safety level under different failure modes. A case verifies the application process. The results revealed that the mission safety assessment needs to be evaluated with the consideration of safety structure and mission profile. The scale of system failures conforms to Weibull distribution in different attack modes. It is shown that the escalating risks will cause serious consequences.

Transcription factor zinc-finger BED domain-containing protein 6 (ZBED6) is unique to placental mammals and regulates insulin-like growth factor 2 (IGF2) expression, which lead to muscle growth. However, the effect of ZBED6 on the growth of spleen is still elusive. In this study, we explored the regulation of ZBED6 on spleen growth, and the results showed ZBED6 knockout (ZBED6 KO) pigs had heavier spleens than wild-type (WT) pigs. To analyze the mechanism of increased spleen weight in ZBED6 KO pigs, long noncoding RNAs (lncRNAs) and mRNAs in the spleen samples (WT:ZBED6 KO pigs = 3:3) were analyzed to identify differentially expressed lncRNAs (DE-lncRNAs) and genes (DEGs) based on the RNA sequencing (RNA-seq) method. Then, 142 DEGs and 82 DE-lncRNAs were obtained. The qRT-PCR results were consistent with those of the RNA-seq, indicating that the data were reliable. The heavier spleen weight of ZBED6 KO pigs coincided with the significantly upregulated IGF2 mRNA. Functional enrichment analysis of DEGs showed enrichment mainly in myofibril assembly and sarcomere. In addition, 252 cis- and 109 trans-acting target genes of 82 DE-lncRNAs were predicted. By conjoint analysis of lncRNA and mRNA revealed that IGF2, DE-lnRNAs (XLOC_113021, XLOC_078852, NONSUSG004057.1, NONSUSG014354.1, and NONSUSG009750.1), and their target gene ACTN2 may be the key candidate genes in promoting spleen growth in ZBED6 KO pigs. This study provides new directions to understand the global functions of ZBED6 and lncRNAs in spleen growth in pigs.

Due to the complexity of scientific experiments, existing methods for capturing the provenance information from the scientific workflows (SWFs) face high programming overhead and code errors. In addition, the coarse-grained nature of the SWF provenance implies the loss of internal details of the workflow processes, which can lead to incomplete or inaccurate data dependencies and dependency differentiation problems. The diversity in scientific fields also reveals the limited versatility of the SWF provenance models. In this context, we propose a content-rich and fine-grained SWF provenance model (CF-PROV). This model provides normative transformations and documentation declarations for the multi-field SWFs, reducing the programming overhead and increasing the versatility. Our method of dividing the workflow provenance into data provenance and process provenance and our formal description of data deduction at the field level enrich the provenance information and transform the coarse-grained workflow provenance into a fine-grained provenance. Finally, the experiments on the model compression ratio and model generation time in multiple scientific fields demonstrate the versatility and rationality of the CF-PROV.

Aiming at the problem that the geometric accuracy design index of machine tools is difficult to be determined reasonably in the geometric precision design process of CNC machine tools, this paper presents a mapping model between geometric tolerance of the workpiece and end pose error (positional and orientational error of the tool relative to the workpiece) of the machine tool considering structure distortion of cutting process system. Only considering the factors of the machine tool geometric errors, this paper first establishes the relationship between the geometric tolerance requirements of the workpiece and relative pose error at the end of machine tools, and completes the estimation of the machine tools end pose error. Then this paper analyzes the elastic deformations of the cutting process system caused by the cutting force. These elastic deformations produce machining errors. Based on the above analysis, the estimated variation range of the end pose error can be adjusted by the emulation of the geometric tolerance of the workpiece and used as the geometric accuracy design index of machine tools. This paper takes the international standard small size contour processing test piece as an example to explain the application process of the proposed model.

Background: Risk stratification of COVID-19 patients upon hospital admission is key for their successful treatment and efficient utilization of hospital resources. We sought to evaluate the risk factors on admission (including comorbidities, vital signs, and initial laboratory assessment) associated with ventilation need and in-hospital mortality in COVID-19. Methods: We established a retrospective cohort of COVID-19 patients from Mass General Brigham hospitals. Demographic, clinical, and admission laboratory data were obtained from electronic medical records of patients admitted to the hospital with laboratory-confirmed COVID-19 before May 19, 2020. Multivariable logistic regression analyses were used to construct and validate the Ventilation in COVID Estimator (VICE) and Death in COVID Estimator (DICE) risk scores. Findings: The entire cohort included 1042 patients (median age, 64 years; 56.8% male). The derivation and validation cohorts for the risk scores included 578 and 464 patients, respectively. We found four factors to be independently predictive for mechanical ventilation requirement (diabetes mellitus, SpO2:FiO2 ratio, C-reactive protein, and lactate dehydrogenase), and 10 factors to be predictors of in-hospital mortality (age, male sex, coronary artery disease, diabetes mellitus, chronic statin use, SpO2:FiO2 ratio, body mass index, neutrophil to lymphocyte ratio, platelet count, and procalcitonin). Using these factors, we constructed the VICE and DICE risk scores, which performed with C-statistics of 0.84 and 0.91, respectively. Importantly, the chronic use of a statin was associated with protection against death due to COVID-19. The VICE and DICE score calculators have been placed on an interactive website freely available to healthcare providers and researchers (https://covid-calculator.com/). Interpretation: The risk scores developed in this study may help clinicians more appropriately determine which COVID-19 patients will need to be managed with greater intensity. Funding: COVID-19 Fast Grant (fastgrants.org).

In recent years, as the heavy equipment airdrop work continues to deepen, Chinese heavy equipment airdrop business has shown a vigorous development trend, and mission training is getting closer and closer to actual combat. From the perspective of task-oriented analysis of safety risks, this paper selects the reloading airdrop mission as the entry point, and conducts research on the safety risk analysis and evaluation methods of reloading airdrop missions. At the same time, it discusses the task-oriented system safety analysis and evaluation methods, in order to carry out other tasks. The task of system security research has laid the foundation[1].

In the present study, using Aspergillus niger and Penicillium tricolor, the influence of the selected parameters, including sucrose concentration, inoculation size of spores, pulp density, and pre-culture time, on the bioleaching efficiency (biomass, organic acids production, and vanadium extraction, respectively) of red mud were studied. The bioleaching kinetics under optimal conditions were also explored. Sucrose concentration showed a positive linear effect on bioleaching efficiency below 143.44 and 141.82 g/L using A. niger and P. tricolor, respectively. However, a higher concentration was unfavorable for vanadium extraction. The inoculation size of spores showed an insignificant effect on both biomass and vanadium extraction if it exceeded the lowest coded levels (0.5 × 107/mL). Red mud pulp density showed a negative effect on the bioleaching efficiency of A. niger but a positive effect on organic acids production and vanadium extraction of P. tricolor. A pre-culture was indispensable for A. niger but not for P. tricolor due to the fact of its isolation from the red mud examined in this study. The kinetics analysis showed that the leaching rate of vanadium followed a two-domain behavior: initially, a rapid leaching period of approximately 10−15 days and, subsequently, a slow leaching period. Considering the change of the particles’ appearance as well as in the elemental composition of the bioleached red mud, it is speculated that the rate of leaching agents through the silicon minerals was the rate-limiting step of dissolution kinetics under the fungal bioleaching process.

Herein active manganese dioxide was prepared by different methods using KMnO 4 and MnSO 4 ·H 2 O as inorganic precursors. The impact of preparation methods on morphology and adsorption performance of the synthesized products was investigated. The experimental results show that the reaction temperature and pressure had a great effect on the morphology and adsorption performance of active manganese dioxide. The shape of active manganese dioxide prepared at room temperature and pressure was short rod-like while active manganese dioxide synthesized by hydrothermal method was mesoporous fibers and had better adsorption performance. The adsorption behavior of 2,4-dinitrophenol on mesoporous manganese dioxide was well described by Langmuir and Freundlich isotherm equation ( R 2 >0.99) and pseudo-second-order kinetic equation ( R 2 >0.99), so the adsorption process maybe a chemical and monolayer adsorption. The pH of solution had significant effect on the adsorption performance of 2,4-dinitrophenol on mesoporous manganese dioxide. The adsorption capacity was 2.539 mg/g in the condition of pH = 7.

The aim was to study the bioleaching performance of chemoheterotrophic bacterium involved in leaching of major, rare earth, and radioactive elements from red mud (RM), and to explore the underlying mechanism. An acid-producing bacterium, identified as Acetobacter sp., was isolated from RM impoundment and used in the bioleaching experiments under one-step, two-step and spent medium process at up to 10% pulp density. The results showed that the leaching ratios of Al, Lu, Y, Sc, and Th were 55%, 53%, 61%, 52%, and 53% respectively under one-step process at 2% pulp density. Under both one- and two-step processes at 2% pulp density, the radioactivity of bioleached RM can meet the relevant regulation in China. The total amount of organic acids excreted by Acetobacter sp. increased with an increase of RM pulp density. After bioleaching, contents of hematite and gibbsite decreased but perovskite increased in RM. Micromorphology analysis indicated that the cells of Acetobacter sp. adhered to RM particles and formed large-size aggregates, and a new crystal of weddellite emerged. In view of the shorter lag phase and smaller biomass comparing to fungi even under direct contact with RM, bacterium Acetobacter sp. is supposed to apply to in situ heap or dump bioleaching of RM.