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Clarifying the key sectors and influencing factors of carbon emissions from energy consumption is an important prerequisite for achieving the “carbon peaking and carbon neutrality” goals. This study calculated the carbon emissions of fuel combustion in 7 major departments and regional electricity trading of Sichuan Province from 2000 to 2021, and empirically analyzed the impact of energy structure effect, energy intensity effect, industrial structure effect, economic development level effect, and population size effect on the carbon emissions of energy consumption based on the LMDI model. The main research conclusions are as follows: (1) LMDI model has the advantages of no residual and high interpretation. By refining the multi-departments of energy consumption and different types of fuel, it is helpful to improve the accuracy of empirical analysis results. (2) The carbon emissions of energy consumption mainly come from the fuel combustion process. Specifically, the industry sector composed of steel, building materials, chemicals and machinery is the key emission sector, and transportation and residential life are also vital. Regional electricity trading can indirectly reduce the intensity of carbon emissions while ensuring the safety of energy supply. (3) From 2000 to 2021, the energy intensity effect and the economic development level effect were key factors in slowing down and promoting the carbon emission growth of energy consumption in Sichuan Province, respectively. The population scale effect mainly played a positive role in driving carbon emissions, but the impact is small and almost negligible. Before 2012, the energy structure effect and the industrial structure effect were mainly positive driving effects, and after 2012, they all turned into negative inhibitory effects. This was mainly due to the low-carbon transformation of energy structure and the optimization of industrial structure.

Heterotopic ossification refers to the pathological formation of extra-skeletal bone. It is a common complication of trauma or surgery that can cause disability and has no definitive cure. Furthermore, the mechanisms underlying chronic inflammation during ossification remain unclear. Therefore, this study aimed to elucidate the systemic immune microenvironment status of heterotopic ossification and identify biomarkers of therapeutic efficacy and recurrence. A combination of stereoarthrolysis with prophylactic radiotherapy and non-steroidal anti-inflammatory drugs was used to treat patients with heterotopic ossification. Changes were observed in peripheral blood lymphocyte levels after treatment. The number of IFNγ+CD8+T cells (3.753 % vs 12.90 %, P

Previous studies have reported inconsistent associations between platelet count (PLT) and cancer survival. However, whether there is linear causal effect merits in-depth investigations. We conducted a cohort study using the UK Biobank and a two-sample Mendelian randomization (MR) analysis. PLT levels were measured prior to cancer diagnosis. We adopted overall survival (OS) as the primary outcome. Cox models were utilized to estimate the effects of PLTs on survival outcomes at multiple lag times for cancer diagnosis. We employed 34 genetic variants as PLT proxies for MR analysis. Linear and non-linear effects were modeled. Prognostic effects of gene expression harboring the instrumental variants were also investigated. A total of 65 471 cancer patients were included. We identified a significant association between elevated PLTs (per 100 × 109/L) and inferior OS (HR: 1.07; 95% CI: 1.04–1.10; p

To mitigate the risk of gas pipelines in karst sinkhole-prone areas, this study employs the DEMATEL/ISM method to elucidate the hierarchical structure and causal relationships among various factors in the system, considering four categories of accident causes: human, material, environment and management. Additionally, the MICMAC method is utilized to analyze the dependence and driving force of risk factors. Utilizing the Visual Studio platform, the software for risk analysis of gas pipelines in karst sinkhole-prone areas is developed. This research introduces the D/I-MICMAC-VS integrated risk analysis method and provides an example analysis. The results demonstrate that: (1) The risk factors for gas pipelines in karst sinkhole-prone areas are distributed across six levels. The possibility of risk accidents can be reduced in the short term by rigorously managing surface-level direct factors, while middle-level indirect factors play an intermediary role in the system. Effective control of gas pipeline accidents can only be achieved by addressing deep-rooted factors fundamentally. (2) The spontaneous cluster serves as a key element for risk management and control of gas pipeline accidents, and prioritized intervention significantly aids in accident prevention. The independent cluster directly influences the system’s risk level through its own changes and development. The linkage cluster plays a pivotal role in transmitting and promoting the evolution and development of accidents. Effective risk management and control can be achieved by discerning the deep root factors that inducing changes in the dependency cluster.

Abstract AMP-activated protein kinase (AMPK) is a ubiquitous sensor of energy and nutritional status in eukaryotic cells. It plays a key role in regulating cellular energy homeostasis and multiple aspects of cell metabolism. During macrophage polarisation, AMPK not only guides the metabolic programming of macrophages, but also counter-regulates the inflammatory function of macrophages and promotes their polarisation toward the anti-inflammatory phenotype. AMPK is located at the intersection of macrophage metabolism and inflammation. The metabolic characteristics of macrophages are closely related to immune-related diseases, infectious diseases, cancer progression and immunotherapy. This review discusses the structure of AMPK and its role in the metabolism, function and polarisation of macrophages. In addition, it summarises the important role of the AMPK pathway and AMPK activators in the development of macrophage-related diseases.

The rigid pile composite foundation method is the most commonly used method for strengthening weak soil foundations. In this method, piles usually need to pass through weak soil layers, and the pile end falls on a bearing layer with good bearing capacity. Under existing technical conditions, the thicker the weak soil layer, the longer the pile body, and the more difficult it is to ensure the construction quality of the pile. In response to this issue, some scholars have adopted the rigid pile composite foundation method with a thick cushion layer for reinforcement treatment. This article uses PLAXIS 3D (V20.04.00.790) software to establish a finite element model of rigid pile composite foundation with a thick cushion layer and simulate the process of foundation reinforcement. The influence of parameters such as thickness, compression modulus, and shear strength index of the cushion layer on foundation settlement and pile–soil stress distribution is studied, and the reasonable range of these parameters is analyzed under the condition of considering reinforcement effect. Through comparative analysis, it can be concluded that for deep and weak soil areas, the thickness of the cushion layer can range from 0.5 to 2.6. The thickness and compressive modulus of the cushion layer have a significant impact on the settlement of the foundation, the pile–soil stress ratio, and the stress of the pile body, while the shear strength index of the cushion layer has a relatively small impact on these parameters. Reasonably selecting the geometric and mechanical parameters of the cushion layer can effectively reduce stress concentration at the pile top and better play the role of the soil between piles.

Water-based or waterborne polyurethane matting resins find extensive application in surface coating to diminish gloss, offering a pleasant tactile experience and a matte aesthetic. This review represents the inaugural effort to consolidate the recent advancements in waterborne polyurethane matting resins, encompassing both physical and chemical matting types. The exploration commences with an introduction to a range of innovative matting agents tailored for the formulation of physical matting waterborne polyurethane resins. Subsequently, a thorough analysis and discussion unfold, delving into the synthesis, characterization, and matting mechanisms of chemical matting waterborne polyurethane resins. This comprehensive discussion draws upon a decade of dedicated research work by our group, contributing fresh perspectives to the evolution of chemical matting techniques. In conclusion, the review not only addresses the current state but also outlines potential challenges and future trends. This forward-looking perspective is intended to offer guidance for the design and synthesis of innovative waterborne polyurethane matting resins.

BackgroundTo assess the relationship between glycemic variability, glucose fluctuation trajectory and the risk of in-hospital mortality in patients with acute myocardial infarction (AMI).MethodsThis retrospective cohort study included AMI patients from eICU Collaborative Research Database. In-hospital mortality of AMI patients was primary endpoint. Blood glucose levels at admission, glycemic variability, and glucose fluctuation trajectory were three main study variables. Blood glucose levels at admission were stratified into: normal, intermediate, and high. Glycemic variability was evaluated using the coefficient of variation (CV), divided into four groups based on quartiles: quartile 1: CV≤10; quartile 2: 1030. Univariate and multivariate Cox regression models to assess the relationship between blood glucose levels at admission, glycemic variability, glucose fluctuation trajectory, and in-hospital mortality in patients with AMI.Results2590 participants were eventually included in this study. There was a positive relationship between high blood glucose level at admission and in-hospital mortality [hazard ratio (HR) = 1.42, 95%confidence interval (CI): 1.06-1.89]. The fourth quartile (CV>30) of CV was associated with increased in-hospital mortality (HR = 2.06, 95% CI: 1.25-3.40). The findings indicated that only AMI individuals in the fourth quartile of glycemic variability, exhibited an elevated in-hospital mortality among those with normal blood glucose levels at admission (HR = 2.33, 95% CI: 1.11-4.87). Additionally, elevated blood glucose level was a risk factor for in-hospital mortality in AMI patients.ConclusionGlycemic variability was correlated with in-hospital mortality, particularly among AMI patients who had normal blood glucose levels at admission. Our study findings also suggest early intervention should be implemented to normalize high blood glucose levels at admission of AMI.

Edge–edge collaboration is the main collaboration mode for edge computing (EC) in time-sensitive networking (TSN). This distributed collaboration mode, in which the computing work is implemented collaboratively by the edge computing nodes (ECNs) without the involvement of cloud servers, poses challenges to collaboration management. However, most existing methods of ECN collaboration only focus on the scheduling of computing resources rather than management process design and rarely consider the transparency, security, and fair distribution guarantee mechanism of collaboration benefits. To address this issue, we propose a blockchain-based and decentralized management scheme for ECNs autonomous collaboration in TSN. First, we design an edge–edge collaboration management framework and its workflow based on blockchain for EC in TSN (TECChain), which combines blockchain with TSN technology and EC paradigm. To solve the consensus problem in TECChain, the proof of diligence (PoD) and delegated PoD (DPoD) consensus mechanisms are designed. Furthermore, by leveraging the high-precision synchronous clock foundation of TSN, we propose two time-slot-driven consensus algorithms, named sequential decision-making based on DPoD (S-DPoD) and Byzantine fault tolerance based on DPoD (BFT-DPoD) respectively. Theoretical analysis results show that the proposed algorithms perform better in terms of security, transactions per second (TPS), energy saving, etc., compared to other algorithms. Comparison experiments reveal that S-DPoD consumes fewer interactive messages and has higher Byzantine fault tolerance and success rate of consensus than BFT-DPoD, but BFT-DPoD has lower transaction verification latency and larger TPS.

In this study, in order to promote the development of far-reaching marine aquaculture equipment in an intelligent direction and solve the problems related to power supply, a tidal current energy harvesting device for a low-velocity sea area is proposed. For low-velocity waters in farming areas, the device can effectively harness tidal energy to provide a stable power supply to open sea cages. A mathematical model of the Savonius turbine blade is established, and the influence of the distance between the impeller center and the water surface on the energy capture efficiency of the turbine is analyzed through numerical simulation. Using ANSYS2021R1 software, the velocity field of the floating body is simulated, and the overall structure and anchoring system of the power generation device is designed. In order to verify the effectiveness of the power generation device, a test model is built and a physical model test is carried out. The variation in parameters related to the relative distance between the impeller and the water under different flow velocities is tested, and the test data are analyzed. The test results show that the floating body can increase the flow speed by 10%. Optimizing the blade number and order of the S-turbine can capture more than 20% of the energy. Under different flow velocities, the capture power of the impeller first increases and then decreases with increasing distance from the water. When the center of the impeller is one-quarter of the impeller diameter higher than the water surface, the output power of the impeller is at the maximum. This indicates that the proposed power generation device can effectively use tidal energy under different water depth conditions and provide a stable power supply for far-reaching marine aquaculture equipment.

China’s coal industry has long faced challenges due to imbalance between supply and demand divisions and the discrepancies between supply and demand prices. Research on optimizing coal transfer amid fluctuating coal prices is crucial for enhancing coal resource allocation, ensuring a balanced and stable supply of coal resources, and promoting the sustainable development of the coal industry. This paper focuses on optimizing coal transfer schemes within a comprehensive transportation system, considering fixed transportation routes and opening times of railroad transportation and waterway transportation, with road transportation serving as a supplementary network. A three-dimensional spatio-temporal network model is established to represent the spatial and temporal paths and transportation modes of coal logistics. The study uses the coal transportation network from Inner Mongolia and Shaanxi to East China as a case study, analyzing factors such as coal price fluctuation, transportation rates, and the ratio of self-produced to purchased coal at the production end via sensitivity analysis. The findings indicate that the proposed model can effectively guide transportation practices under the integrated production, transportation, and sales framework in the energy industry. Additionally, it shows that enterprises can achieve higher profits and maintain revenue and supply stability despite coal price fluctuations, aligning with the coal industry’s transformation and development in the current context.

With the rapid development of the economy, it is imperative to improve the quality of training for operational and managerial talents in the railway industry. To address issues such as efficiency, safety, and cost in railway industry practical training, it is crucial to establish a more comprehensive and efficient high-value virtual–real integration simulation experimental training resource. Therefore, this paper takes the actual work process as the core driving force, utilizes advanced information technology and intelligent devices, and is based on the comprehensive training platform for automatic control of physical trains combined with unmanned aerial vehicle (UAV) equipment. It achieves the integration of hardware and software construction to design and develop a comprehensive simulation training sand table system that incorporates functions such as training, demonstration, testing, and experiments. This system builds an integrated platform for training simulation functions, capable of simulating a railway centralized traffic control system, enabling railway dispatching simulation, driving simulation, and inspection simulation experiences. Additionally, it designs experimental processes at three levels: cognition, practical operation, and enhancement, tailored to the needs of talent development. The rail transportation training simulation sand table effectively reduces training costs and enhances the practical ability training quality of railway operation management personnel, meeting the requirements for talent development in the railway and related industries under new circumstances.

Water-based chloroprene latex is a solvent-free, environmentally friendly adhesive. Currently, its market demand is growing rapidly. However, there are problems such as a lack of heat resistance and poor mechanical properties, which limit its application. The introduction of vinyl-POSS (OVS) into the resin structure can effectively improve the thermal stability of chloroprene adhesives. In this paper, modified waterborne chloroprene latex was prepared by copolymerization of methyl methacrylate and OVS with chloroprene latex. The results showed that vinyl-POSS was successfully grafted onto the main chain of the waterborne chloroprene latex, and the modified waterborne chloroprene latex had good storage stability. With the increase in vinyl-POSS, the tensile strength of the chloroprene latex firstly increased and then decreased, the tensile property (peel strength of 20.2 kgf) was maintained well at a high temperature (100 °C), and the thermal stability of the chloroprene latex was improved. When the addition amount was 4%, the comprehensive mechanical properties were their best. This study provides a new idea for the construction of a new and efficient waterborne chloroprene latex system and provides more fields for the practical application of waterborne chloroprene latex. This newly developed vinyl-POSS modified chloroprene latex has great application potential for use in home furniture, bags, and seat cushions.

Accurate segmentation of the mandibular canal is essential in dental implant and maxillofacial surgery, which can help prevent nerve or vascular damage inside the mandibular canal. Achieving this is challenging because of the low contrast in CBCT scans and the small scales of mandibular canal areas. Several innovative methods have been proposed for mandibular canal segmentation with positive performance. However, most of these methods segment the mandibular canal based on sliding patches, which may adversely affect the morphological integrity of the tubular structure. In this study, we propose whole mandibular canal segmentation using transformed dental CBCT volume in the Frenet frame. Considering the connectivity of the mandibular canal, we propose to transform the CBCT volume to obtain a sub-volume containing the whole mandibular canal based on the Frenet frame to ensure complete 3D structural information. Moreover, to further improve the performance of mandibular canal segmentation, we use clDice to guarantee the integrity of the mandibular canal structure and segment the mandibular canal. Experimental results on our CBCT dataset show that integrating the proposed transformed volume in the Frenet frame into other state-of-the-art methods achieves a 0.5%∼12.1% improvement in Dice performance. Our proposed method can achieve impressive results with a Dice value of 0.865 (±0.035), and a clDice value of 0.971 (±0.020), suggesting that our method can segment the mandibular canal with superior performance.

Dental pulp pericytes are reported to have the capacity to generate odontoblasts and express multiple cytokines and chemokines that regulate the local immune microenvironment, thus participating in the repair of dental pulp injury in vivo. However, it has not yet been reported whether the transplantation of exogenous pericytes can effectively treat pulpitis, and the underlying molecular mechanism remains unknown. In this study, using a lineage-tracing mouse model, we showed that most dental pulp pericytes are derived from cranial neural crest. Then, we demonstrated that the ablation of pericytes could induce a pulpitis-like phenotype in uninfected dental pulp in mice, and we showed that the significant loss of pericytes occurs during pupal inflammation, implying that the transplantation of pericytes may help to restore dental pulp homeostasis during pulpitis. Subsequently, we successfully generated pericytes with immunomodulatory activity from human pluripotent stem cells through the intermediate stage of the cranial neural crest with a high level of efficiency. Most strikingly, for the first time we showed that, compared with the untreated pulpitis group, the transplantation of hPSC-derived pericytes could substantially inhibit vascular permeability (the extravascular deposition of fibrinogen, ** p < 0.01), alleviate pulpal inflammation (TCR+ cell infiltration, * p < 0.05), and promote the regeneration of dentin (** p < 0.01) in the mouse model of pulpitis. In addition, we discovered that the knockdown of latent transforming growth factor beta binding protein 1 (LTBP1) remarkably suppressed the immunoregulation ability of pericytes in vitro and compromised their in vivo regenerative potential in pulpitis. These results indicate that the transplantation of pericytes could efficiently rescue the aberrant phenotype of pulpal inflammation, which may be partially due to LTBP1-mediated T cell suppression.

A straightforward and convenient protocol was established for the synthesis of thiophosphates and 3-sulfenylated indoles via low-valent-tungsten-catalyzed aerobic oxidative cross-dehydrogenative coupling reactions. These reactions occur under mild conditions and simple operations with commercially available starting materials, processing the advantage of excellent atom and step economy, broad substrate scope, and good functional groups tolerance. Moreover, this transformation could be practiced on the gram scale, which exhibits great potential in the preparation of drug-derived or bioactive molecules.

Vinyl-capped cationic waterborne polyurethane (CWPU) was prepared using isophorone diisocyanate (IPDI), polycarbonate diol (PCDL), N-methyldiethanolamine (MDEA), and trimethylolpropane (TMP) as raw materials and hydroxyethyl methacrylate (HEMA) as a capping agent. Then, a crosslinked FPUA composite emulsion with polyurethane (PU) as the shell and fluorinated acrylate (PA) as the core was prepared by core-shell emulsion polymerization with CWPU as the seed emulsion, together with dodecafluoroheptyl methacrylate (DFMA), diacetone acrylamide (DAAM), and methyl methacrylate (MMA). The effects of the core-shell ratio of PA/PU on the surface properties, mechanical properties, and heat resistance of FPUA emulsions and films were investigated. The results showed that when w(PA) = 30~50%, the stability of FPUA emulsion was the highest, and the particles showed a core-shell structure with bright and dark intersections under TEM. When w(PA) = 30%, the tensile strength reached 23.35 ± 0.08 MPa. When w(PA) = 50%, the fluorine content on the surface of the coating film was 14.75% and the contact angle was as high as 98.5°, which showed good hydrophobicity; the surface flatness of the film was observed under AFM. It is found that the tensile strength of the film increases and then decreases with the increase in the core-shell ratio and the heat resistance of the FPUA film is gradually increased. The FPUA film has excellent properties such as good impact resistance, high flexibility, high adhesion, and corrosion resistance.

The incorporation of a naphthyl curing agent (NCA) can enhance the thermal stability of pressure-sensitive adhesives (PSAs). In this study, a PSA matrix was synthesized using a solution polymerization process and consisted of butyl acrylate, acrylic acid, and an ethyl acrylate within an acrylic copolymer. Benzoyl peroxide was used as an initiator during the synthesis. To facilitate the UV curing of the solvent-borne PSAs, glycidyl methacrylate was added to introduce unsaturated carbon double bonds. The resulting UV-curable acrylic PSA tapes exhibited longer holding times at high temperatures (150 °C) compared to uncross-linked PSA tapes, without leaving any residues on the substrate surface. The thermal stability of the PSA was further enhanced by adding more NCA and increasing the UV dosage. This may be attributed to the formation of cross-linking networks within the polymer matrix at higher doses. The researchers successfully balanced the adhesion performance and thermal stability by modifying the amount of NCA and UV radiation, despite the peel strength declining and the holding duration shortening. This research also investigated the effects of cross-linking density on gel content, molecular weight, glass transition temperature, and other properties of the PSAs.

Monitoring forest species diversity is essential for biodiversity conservation and ecological management. Currently, unmanned aerial vehicle (UAV) remote sensing technology has been increasingly used in biodiversity monitoring due to its flexibility and low cost. In this study, we compared two methods for estimating forest species diversity indices, namely the spectral angle mapper (SAM) classification approach based on the established species-spectral library, and the self-adaptive Fuzzy C-Means (FCM) clustering algorithm by selected biochemical and structural features. We conducted this study in two complex subtropical forest areas, Mazongling (MZL) and Gonggashan (GGS) National Nature Forest Reserves using UAV-borne hyperspectral and LiDAR data. The results showed that the classification method performed better with higher values of R2 than the clustering algorithm for predicting both species richness (0.62 > 0.46 for MZL and 0.55 > 0.46 for GGS) and Shannon-Wiener index (0.64 > 0.58 for MZL, 0.52 > 0.47 for GGS). However, the Simpson index estimated by the classification method correlated less with the field measurements than the clustering algorithm (R2 = 0.44 and 0.83 for MZL and R2 = 0.44 and 0.62 for GGS). Our study demonstrated that the classification method could provide more accurate monitoring of forest diversity indices but requires spectral information of all dominant tree species at individual canopy scale. By comparison, the clustering method might introduce uncertainties due to the amounts of biochemical and structural inputs derived from the hyperspectral and LiDAR data, but it could acquire forest diversity patterns rapidly without distinguishing the specific tree species. Our findings underlined the advantages of UAV remote sensing for monitoring the species diversity in complex forest ecosystems and discussed the applicability of classification and clustering methods for estimating different individual tree-based species diversity indices.

Grassland canopy height is a crucial trait for indicating functional diversity or monitoring species diversity. Compared with traditional field sampling, light detection and ranging (LiDAR) provides new technology for mapping the regional grassland canopy height in a time-saving and cost-effective way. However, the grassland canopy height based on unmanned aerial vehicle (UAV) LiDAR is usually underestimated with height information loss due to the complex structure of grassland and the relatively small size of individual plants. We developed canopy height correction methods based on scan angle to improve the accuracy of height estimation by compensating the loss of grassland height. Our method established the relationships between scan angle and two height loss indicators (height loss and height loss ratio) using the ground-measured canopy height of sample plots with 1×1m and LiDAR-derived heigh. We found that the height loss ratio considering the plant own height had a better performance (R2 = 0.71). We further compared the relationships between scan angle and height loss ratio according to holistic (25–65cm) and segmented (25–40cm, 40–50cm and 50–65cm) height ranges, and applied to correct the estimated grassland canopy height, respectively. Our results showed that the accuracy of grassland height estimation based on UAV LiDAR was significantly improved with R2 from 0.23 to 0.68 for holistic correction and from 0.23 to 0.82 for segmented correction. We highlight the importance of considering the effects of scan angle in LiDAR data preprocessing for estimating grassland canopy height with high accuracy, which also help for monitoring height-related grassland structural and functional parameters by remote sensing.

The Middle East holds a critical strategic position in global politics, economy, and military affairs, serving as a pivotal hub for the advancement of the Belt and Road Initiative (BRI) through both land and sea routes. Since the proposal of BRI, China's cooperation with Middle Eastern countries has steadily deepened. Consequently, examining the evolution of China's interaction with Middle Eastern nations over the past decade is of paramount significance for future development. This study utilizes the GDELT database to construct formulas for measuring event impact and bilateral relationship intensity. It analyzes the temporal development and spatial patterns of China's interaction with Middle Eastern countries while also examining the types of interactive relationships between China and individual countries in the Middle East under the principle of reciprocity. The findings indicate that the overall interaction between China and Middle Eastern countries remains stable. Cooperative relationships have transitioned from a "single cooperation" approach to a "dual cooperation" model involving Iran and Saudi Arabia. Moreover, the development trajectory has shifted from an imbalanced "north-high, south-low" pattern towards equilibrium, resulting in a general decline in conflict relations and a decrease in inter-country disparities. The prevalent type of interaction between countries is characterized by balance.

Aqueous polyurethane is an environmentally friendly, low-cost, high-performance resin with good abrasion resistance and strong adhesion. Cationic aqueous polyurethane is limited in cathodic electrophoretic coatings due to its complicated preparation process and its poor stability and single performance after emulsification and dispersion. The introduction of perfluoropolyether alcohol (PFPE-OH) and light curing technology can effectively improve the stability of aqueous polyurethane emulsions, and thus enhance the functionality of coating films. In this paper, a new UV-curable fluorinated polyurethane-based cathodic electrophoretic coating was prepared using cationic polyurethane as a precursor, introducing PFPE-OH capping, and grafting hydroxyethyl methacrylate (HEMA). The results showed that the presence of perfluoropolyether alcohol in the structure affected the variation of the moisture content of the paint film after flash evaporation. Based on the emulsion particle size and morphology tests, it can be assumed that the fluorinated cationic polyurethane emulsion is a core–shell structure with hydrophobic ends encapsulated in the polymer and hydrophilic ends on the outer surface. After abrasion testing and baking, the fluorine atoms of the coating were found to increase from 8.89% to 27.34%. The static contact angle of the coating to water was 104.6 ± 3°, and the water droplets rolled off without traces, indicating that the coating is hydrophobic. The coating has excellent thermal stability and tensile properties. The coating also passed the tests of impact resistance, flexibility, adhesion, and resistance to chemical corrosion in extreme environments. This study provides a new idea for the construction of a new and efficient cathodic electrophoretic coating system, and also provides more areas for the promotion of cationic polyurethane to practical applications.

To investigate the toughening effect and stress–strain relationship of steel fibre-reinforced steel slag micropowder ultra-high-performance concrete (UHPC), nine sets of specimens with coarse aggregate and steel fibre contents were prepared for axial compression and elastic modulus tests. This study examines the variations in compressive strength and peak strain of the steel slag micropowder UHPC specimens to determine the corresponding characteristics of the stress–strain relationship. The results indicate that the experimental groups mixed with 1%, 1.5%, and 2% steel fibre increased the peak strain by about 20.3%, 25.3%, and 26.2%, respectively, compared to the non-steel fibre specimens. It can be seen that the toughening effect of UHPC with steel fibre and slag micro powder is good. With a fixed steel fibre content, the compressive strength and peak strain of steel slag micropowder UHPC initially increase and then decrease as the coarse aggregate content increases. The maximum compressive strength is achieved when the steel fibre content is 1.5% and the coarse aggregate content is 20%. A constitutive equation suitable for steel fibre-reinforced steel slag micropowder UHPC was derived through curve fitting based on the experimentally obtained stress–strain curves. The calculated values from the equation show deviations within 10% of the measured values, indicating a good fit. Nonlinear analysis of the entire compression process of prismatic specimens using the finite element method confirms the rationality of the constitutive equation, as the simulated curve closely aligns with the experimental curve. This research findings provide a reference for the engineering application of steel slag micropowder UHPC.

The progressive expansion and contraction damage caused by heavy metal intrusion into rocks is one of causes to the collapse of rock slopes. Based on the shear strength test, point load test, disintegration resistance test, durability test, and weathering test, the mechanical properties of typical heavy metal contaminated mudstone and sandstone are studied. The spectral band characteristics and spatial frequency changes of mineral elements before and after the intrusion are identified by the spectral diffraction method and acoustic wave detection technology. The penetration effect of heavy metals after an intrusion is analyzed. According to the Weibul1 distribution law of microstructure, the discrete characteristics of intrusion failure of the microelement structure of rock under the single-porous medium, and the relationship between the intrusion performance, elongation performance and time of heavy metals are discussed. The results show that the mechanical strength decreases with the intrusion of heavy metals into rock, and the value reduces with the increasing content of intrusive elements. The differentiation degree of intrusion relationship is shown as the relationship of logarithmic function and power function. The spectral color band characteristics and spatial frequency changes reflect the expansion process of the fissure surface after the intrusion of heavy metal into rock effectively. The penetration effect of microstructure caused by the expansion results in the damage of the integrity of rock. The loss of microscopic mineral colloid particles, the expansion of macroscopic cracks, and the penetration failure are mainly affected by the intrusion and extension properties of the contaminated elements.

Abstract Face recognition has become very challenging in unconstrained conditions due to strong intra‐personal variations, such as large pose changes. Face normalisation can help to resolve these problems and effectively improve the face recognition performance in unconstrained conditions by converting non‐frontal faces to frontal ones. However, there are other complex facial variations in addition to pose, such as illumination and expression, which will also influence face recognition performance. The authors propose a well‐designed generative adversarial network‐based multi‐factor joint normalisation network (MFJNN) to normalise multiple factors simultaneously. First, a multi‐encoder generator and a feature fusion strategy are designed and implemented in the MFJNN to realise the joint normalisation of multiple factors in addition to pose. Second, a convolutional neural network‐based (CNN‐based) network is applied in the MFJNN, which allows the MFJNN to simultaneously realise image synthesis and facial representation learning. Moreover, an identity perceptive loss is introduced based on the CNN‐based network to produce reliable identity‐preserving features of the input face images. The experimental results demonstrate that the proposed method can synthesise multi‐factor normalisation results with identity preservation and effectively improve the face recognition performance.

Brassinosteriod (BR) plays important roles in regulation of plant growth, development and environmental responses. BR signaling regulates multiple biological processes through controlling the activity of BES1/BZR1 regulators. Apart from the roles in the promotion of plant growth, BR is also involved in regulation of the root foraging response under low nitrogen, however how BR signaling regulate this process remains unclear. Here we show that BES1 and LBD37 antagonistically regulate root foraging response under low nitrogen conditions. Both the transcriptional level and dephosphorylated level of BES1, is significant induced by low nitrogen, predominantly in root. Phenotypic analysis showed that BES1 gain-of-function mutant or BES1 overexpression transgenic plants exhibits progressive outgrowth of lateral root in response to low nitrogen and BES1 negatively regulates repressors of nitrate signaling pathway and positively regulates several key genes required for NO3- uptake and signaling. In contrast, BES1 knock-down mutant BES1-RNAi exhibited a dramatical reduction of lateral root elongation in response to low N. Furthermore, we identified a BES1 interacting protein, LBD37, which is a negative repressor of N availability signals. Our results showed that BES1 can inhibit LBD37 transcriptional repression on N-responsive genes. Our results thus demonstrated that BES1-LBD37 module acts critical nodes to integrate BR signaling and nitrogen signaling to modulate the root forging response at LN condition.

A phosphorylcholine polymer (poly(MPC–co–BMA–co–TSMA), PMBT) was prepared by free radical polymerization and coated on the surface of the polymethylpentene hollow fiber membrane (PMP–HFM). ATR–FTIR and SEM analyses showed that the PMBT polymer containing phosphorylcholine groups was uniformly coated on the surface of the PMP–HFM. Thermogravimetric analysis showed that the PMBT had the best stability when the molar percentage of MPC monomer in the polymer was 35%. The swelling test and static contact angle test indicated that the coating had excellent hydrophilic properties. The fluorescence test results showed that the coating could resist dissolution with 90% (v/v%) ethanol solution and 1% (w/v%) SDS solution. The PMBT coating was shown to be able to decrease platelet adherence to the surface of the hollow fiber membrane, and lower the risk of blood clotting; it had good blood compatibility in tests of whole blood contact and platelet adhesion. These results show that the PMBT polymer may be coated on the surface of the PMP–HFM, and is helpful for improving the blood compatibility of membrane oxygenation.

The global express market has expanded significantly in recent years. High-speed rail express freight transportation has been implemented between multiple cities in China, significantly improving transportation efficiency and effectively meeting demand. In this paper, an optimization model for HSR (high-speed railway) express transport plan is constructed using a space-time-state network, and an improved adaptive genetic algorithm is designed to solve the model. Reasonable transport schemes could be arranged for each cargo flow with the objective of maximizing operational revenue. The numerical experiment based on the Harbin–Dalian high-speed railway in China verifies the effectiveness and applicability of the proposed model. The results show that for HSR operators, appropriate transport strategies can be planned in terms of delivery priorities and transportation mode selection to make full use of the remaining capacity of HSR trains and increase operational revenue.

In this paper, the blade solidity of the tidal current turbine was investigated. Based on the blade element momentum theory, different design flow velocities were selected to design two blade types with different solidities. The geometric parameters of the blade were calculated using MATLAB programming, and the performance of two blades was compared in terms of the start-up flow rate, power generation and thrust by test experiment, which showed that the blade with higher solidity has better start-up performance and higher energy capture efficiency at low flow rates. The performance is better than that of the blade with low solidity, but due to the high solidity, the thrust is also high, which should be taken into account when installing the turbine.

Abstract A type of grafted acrylate copolymer resins, containing 3‐oxo‐N‐allyl‐1,2‐benzisothiazole‐2(3H)‐carboxamide monomer and heterocyclic monomers, was synthesized through the copolymeri‐ zation of methyl methacrylate (MMA) and butyl acrylate (BA) with functional monomers. The structures of the monomers and copolymers were validated by infrared (IR) and 1H nuclear magnetic resonance (NMR) spectroscopies. The inhibitory activities of the copolymers on algae, bacteria, and barnacle larvae were measured, and the antifouling potencies against marine macrofouling organisms were investigated. The results showed that the grafted resin had significant inhibitory effects on the growth of three marine algae (Isochrysis galbana, Nannochloropsisoculata, and Chlorella pyrenoidosa), and three bacteria (Vibrio coralliilyticus, Staphylococcus aureus,and Vibrio parahaemolyticus). The target copolymers also showed excellent inhibition of the survival of barnacle larvae. Additionally, the release rate of the antifoulant and the results of the marine field tests indicated that the grafted copolymers had outstanding antifouling potency against the attachment of marine macrofouling organisms.

Safety helmet wearing plays a major role in protecting the safety of workers in industry and construction, so a real-time helmet wearing detection technology is very necessary. This paper proposes an improved YOLOv4 algorithm to achieve real-time and efficient safety helmet wearing detection. The improved YOLOv4 algorithm adopts a lightweight network PP-LCNet as the backbone network and uses deepwise separable convolution to decrease the model parameters. Besides, the coordinate attention mechanism module is embedded in the three output feature layers of the backbone network to enhance the feature information, and an improved feature fusion structure is designed to fuse the target information. In terms of the loss function, we use a new SIoU loss function that fuses directional information to increase detection precision. The experimental findings demonstrate that the improved YOLOv4 algorithm achieves an accuracy of 92.98%, a model size of 41.88 M, and a detection speed of 43.23 pictures/s. Compared with the original YOLOv4, the accuracy increases by 0.52%, the model size decreases by about 83%, and the detection speed increases by 88%. Compared with other existing methods, it performs better in terms of precision and speed.

The continuous increase of carbon emissions is a serious challenge all over the world, and many countries are striving to solve this problem. Since 2020, a widespread lockdown in the country to prevent the spread of COVID-19 escalated, severely restricting the movement of people and unnecessary economic activities, which unexpectedly reduced carbon emissions. This paper aims to analyze the carbon emissions data of 30 provinces in the 2020 and provide references for reducing emissions with epidemic lockdown measures. Based on the method of time series visualization, we transform the time series data into complex networks to find out the hidden information in these data. We found that the lockdown would bring about a short-term decrease in carbon emissions, and most provinces have a short time point of impact, which is closely related to the level of economic development and industrial structure. The current results provide some insights into the evolution of carbon emissions under COVID-19 blockade measures and valuable insights into energy conservation and response to the energy crisis in the post-epidemic era.

With the steady increase in passenger volume of high-speed railways in China, some high-speed railway sections have faced a difficult situation. To provide more transport services, it is necessary to add as many trains as possible in a section to increase capacity. To solve this problem, a compressed multilayer space-time network model is constructed with the maximum number of trains that can be scheduled in the train timetable as the objective. The combination of the train stop plan and speed level is represented by the layer of network where the train is located, and constraints such as train selection, train safety, train overtake and cross-line trains are considered. A method based on timing-cycle iterative optimization is designed to decompose the original problem into multiple subproblems, and the solving order of the subproblems is determined by a heuristic greedy rule. Taking the Beijing-Jinan section of the Beijing-Shanghai high-speed railway as an example, the maximum number of trains was increased by 12.5% compared with the timetable before optimization. The saturated timetables provide detailed schedules, which helps decision-makers better adjust the timetable to run more trains.

Objective: To introduce the emergency management of nursing human resources and supplies of a large general hospital when facing the outbreak of coronavirus disease 2019(COVID-19). Method: The Nursing Department of the hospital fully executed its functional authority to establish a three-level echelon of sustainable support, allocate human recourses dynamically, organize pre-service training, supervise the key working steps, formulate positive incentive methods, and deploy medical supplies scientifically. Result: By taking these strategies, the hospital effectively improved the coping capacity of the nursing team and played a positive role in the prevention and treatment of COVID-19. Conclusion: The emergency management of nursing human resources and material resources for COVID-19 of the hospital is successful. But several deficiencies were identified as well, which indicated that the hospital needs to establish an efficient emergency management system, and pay attention to the practice of nursing emergency plans to enhance coping capacities in public health emergencies.

This article introduces safety management strategies of nasopharyngeal specimen collection from suspected cases of coronavirus disease 2019 in a tertiary designated hospital. The key points include establishing a special sampling room, strict sterilization of the entire environment, training of professional nurses, enhancement of personal protection, standardization of methods and processes for swab collection, and a timely and safety sample submission. More than 11,000 nasopharyngeal specimens were collected by eight nurses, with an average of 1,375 specimen swab collections each nurse, and no one was infected.

Abstract The important parameters to describe waves are their amplitude and length. In order to make it easier to improve wave amplitude and facilitate wave experiment, a simple push-type wave generating method using digital rotary valve control was proposed and different wave amplitudes were generated by the new method. After the mathematical model of the new method had been established, numerical analysis based on the linear wave theory was carried out by means of Matlab/Simulink software tools, and experiments were conducted on the push-type wave maker to ascertain the validity of the established model and the numerical simulation results. It shows that both experimental and theoretical results agree relatively well, and the plate motion frequency and amplitude of the push-type wave maker can be continuously adjusted and the various required regular waves can be obtained. Although the wave amplitude and length descends with the increasing of working frequency, the wave amplitude can be improved conveniently by setting the axial opening width of the valve and the oil supply pressure of system. The wave length remains unchanged with the axial opening width and the oil supply pressure change. The research indicates that different regular waves can be easily generated by the new method and the wave amplitude can be further improved in a certain plate motion frequency range.

Online magnetization current control is a critical concern of the variable-flux permanent magnet machine control. Increasing the magnetization speed benefits the machine system, which reduces manipulation losses and mechanical impact. Thus, this paper proposes an online trajectory prediction method that increases the DC-link voltage utilization, boosting the manipulation speed. The prediction method decouples the rotating voltage and the induction voltage in the machine model. The induction voltage is the source of di/dt, which influences the magnetization manipulation speed. The proposed method updates the maximum available induction voltage at every manipulation stage by excluding the rotating voltage from the DC-link voltage limitation. Based on the induction voltage, the magnetization current trajectory is predicted. The trajectory prediction is cooperated with a feed-forward current controller to increase the control dynamics. Verified by various experiments, the proposed method achieves fast manipulation speed with high control accuracy. Besides, the proposed method shows self-adaptive capabilities in variable-speed and variable-voltage conditions.

In edge computing, for dimensionality reduction and core data extraction, both edge computing node (ECN) and cloud server may implement a high-order singular value decomposition (HOSVD) algorithm before data are passed to local computing models. However, at present, many edge computing systems regard the two HOSVD procedures as two independent parts, which leads to repeated calculations in the cloud. In this paper, we propose an aggregative HOSVD method by reusing intermediate results of subtensor HOSVD in ECNs to reduce the HOSVD computing cost of the merged tensor in the cloud server. First, two equivalence lemmas of singular value decomposition (SVD) are proven. Second, the SVD left mergence algorithm (SVDLM), hierarchical-SVDLM (H-SVDLM) algorithm and aggregative HOSVD (AHOSVD) algorithm are proposed to obtain the HOSVD result of the merged tensor by efficiently merging the unfolded matrix SVD results of the subtensors. Finally, the efficiency and accuracy between the HOSVD and the AHOSVD are compared, and the experimental results validate that the proposed AHOSVD algorithm improves efficiency compared with the HOSVD algorithm in circumstances with comparable accuracy results with the HOSVD algorithm.

Variable flux memory machines (VFMM) use magnetization and demagnetization manipulations to adjust machine voltage, achieving wide-speed high-efficiency operation. The machine magnetization state manipulation is a critical concern in the VFMM control. Thus, this article proposes an on-line magnetization state estimation and closed-loop control using the magnetization manipulation signals. The magnetization state manipulation requires voltage injection to create the manipulation current. The current shows non-linear response at different magnetization state because the current changes the magnets state and the machine saturation level. The flux change rate, which is calculated by the injected voltage and the current response, is affected by the non-linearity and utilized in the proposed method for the magnetization state estimation. The proposed magnetization state estimation achieves self-sensing characteristic because the signals in the estimation already exist in the magnetization state manipulation. Based on the estimated and the target magnetization state, the closed-loop magnetization state control is achieved by the voltage injection regulation.

This study collects data on electric vehicle (EV) charging piles for various provinces in China and analyzes the development of the network of EV chargers from the perspective of a complex network. Features of the distribution of EV charging piles for the period from May 2016 to April 2019 and the spatio-temporal variations across provinces are thus analyzed. The study then transforms time-series data of the EV charging piles into a complex network by applying a visibility graph, uses several clustering methods to categorize different provinces, and predicts the future development of the network of EV charging piles in China. Additionally, the distribution of EV charging piles across time is analyzed for a combination of national policies and new-energy vehicles. The results of the study will guide provincial governments in creating policies that develop relevant industries progressively and promote the sustainable development of EVs and green-energy industry.

A pick-up zone links a hub of inter-city transportation (e.g., airplane and rail, etc.) with a connected roadway belonging to the city road network. Passengers depart through the pick-up zone and the interactions between passengers and vehicles lead to delays and queues of vehicles on the connected roadway. A better understanding of the unique traffic characteristics of the connected roadway can help to reveal the collecting or dispersing capacity of the hub. This paper treats passenger boarding in a pick-up zone as a service process in a queue system and uses a fundamental diagram model derived from M/M/1 threshold queueing theory with two service phases to investigate the supply–demand relationship of the system. A calibration method is proposed to determine the parameters of the model. Numerical experiments showed that the model can capture a unique capacity drop in the pick-up zone. Moreover, analyses on the impacts of designed parameters on the model features, such as capacity and degree of capacity drop, were performed, and the comparisons showed that the model used performs better than other classical methods with a 0.69 mean squared error and a 0.90 sum of squares due to error). The results will be important supports for hub capacity management.

Rail expresses play a vital role in intracity and intercity transportations. For accommodating multi-source passenger traffic with different travel demand, while optimizing the energy consumption, we propose a multi-cycle train timetable optimization model and a decomposition algorithm. A periodized spatial-temporal network that can support the integrated optimization of passenger service satisfaction and energy consumption considering multi-cycles is studied as the basis of the modeling. Based on this, an integrated optimization model taking the planning of the train spatial-temporal path, cycle length and active lines as variables is proposed. Then, for solving the issues caused by the complex relationships among the cycle length, line and train spatial-temporal path in large-scale cases, a hybrid heuristic Lagrangian decomposition method is investigated. Numerical experiments under different passenger flow demand scenarios are performed. The results show that the more fluctuating the passenger flow is, the more obvious the advantage of a multi-cycle timetable is. For the scenario with two passenger flow peaks, compared to a single-cycle timetable, the demand satisfaction ratio of the multi-cycle timetable is 4.44% higher and the train vacancy rate is 11.49% lower. A multi-cycle timetable also saves 3.24 h running time and 15,553.6 kwh energy consumption compared to a single-cycle timetable. Large-scale real cases show that this advantage still exists in practice.

In the Industry 4.0 era, with the continuous integration of industrial field systems and upper-layer facilities, interconnection between industrial wireless sensor networks (IWSNs) and industrial Internet networks is becoming increasingly pivotal. However, when deployed in real industrial scenarios, IWSNs are often connected to legacy control systems, through some wired industrial network protocols via gateways. Complex protocol translation is required in these gateways, and semantic interoperability is lacking between IWSNs and the industrial Internet. To fill this gap, our study focuses on realizing the interconnection and interoperability between an IWSN and the industrial Internet. The Open Platform Communications Unified Architecture (OPC UA) and joint publish/subscribe (pub/sub) communication between the two networks are used to achieve efficient transmission. Taking the Wireless Networks for Industrial Automation Process Automation (WIA-PA), a typical technology in IWSNs, as an example, we develop a communication architecture that adopts OPC UA as a communication bridge to integrate the WIA-PA network into the industrial Internet. A WIA-PA virtualization method for OPC UA pub/sub data sources is designed to solve the data mapping problem between WIA-PA and OPC UA. Then, the WIA-PA/OPC UA joint pub/sub transmission mechanism and the corresponding configuration mechanism are designed. Finally, a laboratory-level verification system is implemented to validate the proposed architecture, and the experimental results demonstrate its promising feasibility and capability.

Predicting short-term passenger flow accurately is of great significance for daily management and for a timely emergency response of rail transit networks. In this paper, we propose an attention-based Graph–Temporal Fused Neural Network (GTFNN) that can make online predictions of origin–destination (OD) flows in a large-scale urban transit network. In order to solve the key issue of the passenger hysteresis in online flow forecasting, the proposed GTFNN takes finished OD flow and a series of features, which are known or observable, as the input and performs multi-step prediction. The model is constructed from capturing both spatial and temporal characteristics. For learning spatial characteristics, a multi-layer graph neural network is proposed based on hidden relationships in the rail transit network. Then, we embedded the graph convolution into a Gated Recurrent Unit to learn spatial–temporal features. For learning temporal characteristics, a sequence-to-sequence structure embedded with the attention mechanism is proposed to enhance its ability to capture both local and global dependencies. Experiments based on real-world data collected from Chongqing’s rail transit system show that the metrics of GTFNN are better than other methods, e.g., the SMAPE (Symmetric Mean Absolute Percentage Error) score is about 14.16%, with a range from 5% to 20% higher compared to other methods.

The intercity railway is subject to variation and fluctuation in demand both in time and space over a day to a large extent. In that case, more advanced line planning techniques are practically needed to match the non-equilibrium passenger demand. We propose an integer linear programming model for adapting to the fluctuating demand and improving rail line profit, in which the multi-period planning approach and flexible train composition mode are taken into consideration. In particular, we also consider the limitations of the carriage and the dynamic transfer of resources during a finite period to ensure the better implementation of the line planning and subsequent operation plans. Our purpose is to improve on previous line planning models by integrating the multi-period strategic-level line planning decision with resource constraints. Since the problem is computationally intractable for realistic size instances, an improved round heuristic algorithm that is based on linear relaxation is proposed and we compare the round heuristic performance with the commercial solver Gurobi on artificial instances. The numerical experiments that are based on an intercity railway in China certify the effectiveness and applicability of the proposed model and algorithm. We evaluate the impact of different optimization parameters and reserved carriages and the computation results show that in comparison to the fixed composition mode, the proposed approach can improve the utilization efficiency of carriage resources and increase the line profit by 1.9% under the same carriage resource conditions.

Paprika is a widely consumed spice in the world and its authentication has gained interest considering the increase in adulteration cases in recent years. In this study, second-order fingerprints acquired by liquid chromatography with fluorescence detection (HPLC-FLD) were first used to detect and quantify adulteration levels of Chinese paprika samples. Six different adulteration cases, involving paprika production region, cultivar, or both, were investigated by pairs. Two strategies were employed to reduce the data matrices: (1) chromatographic fingerprints collected at specific wavelengths and (2) fusion of the mean data profiles in both spectral and time dimensions. Afterward, the fingerprint data with different data orders were analyzed using partial least squares (PLS) and n-way partial least squares (N-PLS) regression models, respectively. For most adulteration cases, N-PLS based on second-order fingerprints provided the overall best quantitation results with cross-validation and prediction errors lower than 2.27% and 20.28%, respectively, for external validation sets with 15–85% adulteration levels. To conclude, second-order HPLC-FLD fingerprints coupled with chemometrics can be a promising screening technique to assess paprika quality and authenticity in the control and prevention of food frauds.

Accurate and convenient assessment of a section’s capacity is an essential problem in the operation of high-speed railway companies. The concept of occupancy time is widely used in the field, but there is still a lack of quantitative analysis to support follow-up studies and application. In this research, the calculation method for one train, two trains and multiple trains is discussed. The occupancy time of the two trains was divided into three cases according to the relationship between them, and the calculation formulas are given. For the calculation of multiple trains, the circumstances were too intricate to be classified. To solve this problem, the concept of a continuous train group was proposed. The three properties of the continuous train group were analyzed and proved by mathematical derivation to provide theoretical support to transform a multi-train problem into many two-train problems. Finally, a combined occupancy method for capacity assessment was formed and applied to the Beijing–Shanghai high-speed railway. A series of numerical cases were designed to evaluate the performance compared with the UIC406 method. The results demonstrate that the combined occupancy method can better assess the capacity and is more convenient to implement.

Aiming at the breeding environment where the construction of marine pastures requires low wind and waves, a floating breakwater (FB) with a Savonius type (referred to as S type) runner with wave absorption and energy reduction function is studied for wave absorption and energy reduction in aquaculture sea areas. The wave-absorbing and energy-reducing performance of the floating breakwater is studied by the method of combining numerical simulation and experiment. Using Star-CCM+ numerical simulation software, based on linear wave theory and energy conservation law, using overlapping grid technology, calling DFBI model, second-order time discretization, a three-dimensional flow field model of the floating breakwater was established and numerically simulated. At the same time, a floating breakwater physical test system was developed for experimental verification, the transmission wave and the conversion power consumption of the S-shaped runner under different wave heights and different periods were measured, and the results Please carefully check the accuracy of names and affiliations. of numerical simulation and physical experiments were comprehensively evaluated. The research results show that the floating breakwater based on the S-shaped runner has the functions of reducing the wave height and reducing the wave energy, which have guiding significance for practical engineering.

SERINC5 incorporates into HIV-1 particles and inhibits the ability of Env glycoprotein to mediate virus-cell fusion. SERINC5-resistance maps to Env, with primary isolates generally showing greater resistance than laboratory-adapted strains. Here, we examined a relationship between the inhibition of HIV-1 infectivity and the rate of Env inactivation using a panel of SERINC5-resistant and -sensitive HIV-1 Envs. SERINC5 incorporation into pseudoviruses resulted in a faster inactivation of sensitive compared to resistant Env strains. A correlation between fold reduction in infectivity and the rate of inactivation was also observed for multiple Env mutants known to stabilize and destabilize the closed Env structure. Unexpectedly, most mutations disfavoring the closed Env conformation rendered HIV-1 less sensitive to SERINC5. In contrast, functional inactivation of SERINC5-containing viruses was significantly accelerated in the presence of a CD4-mimetic compound, suggesting that CD4 binding sensitizes Env to SERINC5. Using a small molecule inhibitor that selectively targets the closed Env structure, we found that, surprisingly, SERINC5 increases the potency of this compound against a laboratory-adapted Env which prefers a partially open conformation, indicating that SERINC5 may stabilize the closed trimeric Env structure. Our results reveal a complex effect of SERINC5 on Env conformational dynamics that promotes Env inactivation and is likely responsible for the observed restriction phenotype.

A novel recoverable visible-light photocatalyst, amorphous Fe2TiO5/C composite, was prepared via nonhydrolytic sol-gel method with carbon-containing precursors as in-situ carbon sources. It is demonstrated that the precursors, iron ethoxide and butyl titanate, react to form Fe-O-Ti bonds in gel through a ether elimination reaction and amorphous Fe2TiO5 at 300 °C, which finally crystallizes at 600 °C. The residual organic groups form uniform-doped C. Interestingly, the photocatalytic activity of amorphous Fe2TiO5/C is distinctly superior to those of its crystalline counterparts without C and P25 (43-fold increase and 12-fold increase, respectively), which is mainly attributed to the incorporation of C (8.17 wt%) and amorphous Fe2TiO5 with a hollow spherical structure and a high BET surface area of 195.5 m2/g. Importantly, the photocatalyst can be recovered with a recovery rate of 100% simply by an external magnetic field, making it have promising applications in the wastewater treatment field.