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The heat transfer model for steel solidification in Al2O3 crucial and permanent mold by finite element method was developed and validated by temperature measurement. The multi-gradient operation was novelly designed, and the tailored cooling rate in range of 0.1–10 °C/s was obtained at the target location. The simulation aided experiment with the large-sized samples was carried out, and the local cooling rate was verified by secondary dendrite arm spacing. The size of austenite grain decreases slightly as cooling rate increases from 0.15 °C/s to 0.31 °C/s, and then increases dramatically in the range of 0.31–0.48 °C/s, finally decreases with cooling rate increasing further to 9.76 °C/s. The relationship between austenite grain size and cooling rate was logarithmically regressed in the range of 0.48–9.76 °C/s, in which the kinetic equations on basis of cooling experiment and continuously cast slab can also work. However, the grain size decrease in 0.15–0.31 °C/s and then increase in 0.31–0.48 °C/s cannot be described. Based on the mechanism of peritectic solidification, the austenite grain growth is mainly controlled by diffusion at a low cooling rate smaller than 0.31 °C/s, and the final grain size is less than 1.0 mm. At a medium cooling rate between 0.48 and 3.60 °C/s, austenite grain growth is accelerated by the energy stored during massive type peritectic transformation previously, and the grain size is between 1.7 and 2.9 mm. At high cooling rate larger than 9.76 °C/s, austenite grains grow to about 0.9 mm in columnar shape. The time for grain growth is not adequate, although addition energy storage by massive transformation can also occur. The critical cooling rate for the onset of massive type peritectic transformation in the large-sized sample is between 0.31 and 0.48 °C/s. The growth velocity in the isothermal experiment is much smaller than that in continuous cooling process, confirming that the austenite grain evolution is significantly affected by previous peritectic solidification.

The glycocalyx is a layer of villus-like structure covering the luminal surface of vascular endothelial cells. Damage to the glycocalyx has been proven linked to the development of many diseases. However, the factors that promote damage to the glycocalyx are not fully elaborated. This review summarizes factors leading to the reduction of the glycocalyx in detail, including inflammatory factors, ischemia-reperfusion, oxidative stress, lipids, glucose, high sodium, female sex hormones and others. Additionally, the mechanisms underlying its degradation are discussed. To better prevent and treat related diseases induced by glycocalyx degradation, it is a meaningful measure to avoid these factors.

The surface strengthening treatment of 304 stainless steel was carried out by using ultrasonic nanocrystal surface modification （UNSM） technology， and the effect of UNSM on the microstructure and mechanical performance of stainless steel was studied. The microstructure evolution and plastic deformation mechanism before and after UNSM treatment were analyzed by transmission electron microscopy （TEM）， electron backscattered diffraction （EBSD） and other characterization methods. The effects of UNSM on surface roughness， microhardness and residual stress of materials were studied by using white light interferometry and microhardness testing. The results show that after UNSM treatment， 304 stainless steel undergoes severe plastic deformation on the surface， resulting in an increase in dislocation density and significant grain refinement， and nanocrystals are generated on the near-surface region， forming a hardened layer about 300 μm deep. The deformation induces austenite-to-martensite transformation and introduces the residual compressive stress of about 900 MPa on the surface. The microhardness of the material increases from 238HV to 511HV， and the surface integrity is significantly improved.

Machine learning (ML) provides a new surrogate method for investigating groundwater flow dynamics in unsaturated soils. Traditional pure data-driven methods (e.g. deep neural network, DNN) can provide rapid predictions, but they do require sufficient on-site data for accurate training, and lack interpretability to the physical processes within the data. In this paper, we provide a physics and equality-constrained artificial neural network (PECANN), to derive unsaturated infiltration solutions with a small amount of initial and boundary data. PECANN takes the physics-informed neural network (PINN) as a foundation, encodes the unsaturated infiltration physical laws (i.e. Richards equation, RE) into the loss function, and uses the augmented Lagrangian method to constrain the learning process of the solutions of RE by adding stronger penalty for the initial and boundary conditions. Four unsaturated infiltration cases are designed to test the training performance of PECANN, i.e. one-dimensional (1D) steady-state unsaturated infiltration, 1D transient-state infiltration, two-dimensional (2D) transient-state infiltration, and 1D coupled unsaturated infiltration and deformation. The predicted results of PECANN are compared with the finite difference solutions or analytical solutions. The results indicate that PECANN can accurately capture the variations of pressure head during the unsaturated infiltration, and present higher precision and robustness than DNN and PINN. It is also revealed that PECANN can achieve the same accuracy as the finite difference method with fewer initial and boundary training data. Additionally, we investigate the effect of the hyperparameters of PECANN on solving RE problem. PECANN provides an effective tool for simulating unsaturated infiltration.

Summary: While the benefits of physical activity on mental health are well-known, systematic reviews and meta-analyses on its impact on mental illness in adults with COVID-19 are scarce. This study of 25 randomized controlled trials shows that physical activity significantly reduces anxiety (standardized mean difference [SMD] = −0.915; 95% confidence interval [CI] = −1.182 to −0.648; I2 = 82.0%; p 60 min for depression, yield the best outcomes. These results highlight the specific effectiveness of physical activity in alleviating anxiety and depression in COVID-19 patients.

Lipid metabolism disorders lead to lipotoxicity. The hyperlipidemia-induced early stage of renal injury mainly manifests as podocyte damage. CD36 mediates fatty acid uptake and the subsequent accumulation of toxic lipid metabolites, resulting in podocyte lipotoxicity.

Exploring deep learning and its influencing factors is receiving increasing attention. This study examines influencing factors (i.e. self-efficacy, learning engagement, and teacher-student interaction) of high school students' English deep learning in blending courses. Research hypotheses are proposed, and a structural equation model (SEM) of influencing factors of deep learning is built. A sample size of 225 participants was recruited on a voluntary and anonymous basis from a high school in Southwestern China for this study. We find: (1) self-efficacy, learning engagement and teacher-student interaction all predict and have positive impacts on English deep learning; (2) self-efficacy has a positive impact on learning engagement and teacher-student interaction; (3) teacher-student interaction has a positive impact on learning engagement. The findings underscore the importance of self-efficacy, learning engagement, and teacher-student interaction for EFL high school learners to achieve deep learning in a blending context. Drawn from these findings, pedagogical implications for promoting these learners' deep learning are provided.

Semi-macrosegregation in continuously cast blooms and its associated carbide banding defects in hot-rolled bars were investigated to explore the characteristics, evolution, and control methods in high-carbon chromium bearing steel. It was found that the semi-macrosegregation exists only in the central equiaxed crystal zone of the blooms, and C, Cr solute elements inside show typical spot-like positive segregation. Carbide banding appears as white bright bands along the rolling direction, composed of high number density M3C carbide particles, with a significant effect on the mechanical properties of the rolled products. The hereditary evolution from semi-macrosegregation to carbide banding was established by means of banded segregation. Morphologically, normal semi-macrosegregation and carbide-typed semi-macrosegregation are formed based on whether Cr-rich primary carbides are generated. These two types of semi-macrosegregation evolved into two kinds of carbide banding respectively, that is, dark bands and bright bands defined according to the ability to reflect light under OM. To alleviate the carbide banding defect in rolling products of high-carbon chromium bearing steel, the morphology and area ratio of equiaxed crystals in continuous cast blooms should be modified. It is observed that the equiaxed crystal ratio in the bloom can be decreased from 62.5 % to 28 % by increasing liquid steel superheat and inhibiting superheat dissipation in the mold through casting practices. Additionally, the morphology of equiaxed crystals is related to the as-cast solidification structure, and when the equiaxed crystal ratio is large, the equiaxed crystals turn out to be coarser ones with only cellular primary dendrite; when the columnar crystals are longer, however, the equiaxed crystals appear as a dendrite structure with fine secondary dendrites. As a result, semi-macrosegregation was improved obviously with the fine dendrite structure splitting the local residual liquid phase, leading to the decrease of the maximum width of carbide banding from 268.41 μm to 73.72 μm, and the increase of mechanical properties in the rolled bar of high-carbon chromium bearing steel.

Pine wilt disease (PWD) is one of the most destructive diseases for pine trees, causing a significant effect on ecological resources. The identification of PWD-infected trees is an effective approach for disease control. However, the effects of complex environments and the multi-scale features of PWD trees hinder detection performance. To address these issues, this study proposes a detection model based on PWD-YOLOv8 by utilizing aerial images. In particular, the coordinate attention (CA) and convolutional block attention module (CBAM) mechanisms are combined with YOLOv8 to enhance feature extraction. The bidirectional feature pyramid network (BiFPN) structure is used to strengthen feature fusion and recognition capability for small-scale diseased trees. Meanwhile, the lightweight FasterBlock structure and efficient multi-scale attention (EMA) mechanism are employed to optimize the C2f module. In addition, the Inner-SIoU loss function is introduced to seamlessly improve model accuracy and reduce missing rates. The experiment showed that the proposed PWD-YOLOv8n algorithm outperformed conventional target-detection models on the validation set (mAP@0.5 = 94.3%, precision = 87.9%, recall = 87.0%, missing rate = 6.6%; model size = 4.8 MB). Therefore, the proposed PWD-YOLOv8n model demonstrates significant superiority in diseased-tree detection. It not only enhances detection efficiency and accuracy but also provides important technical support for forest disease control and prevention.

Federated learning (FL) can guarantee privacy by allowing local users only upload their training models to central server (CS). However, the existence of Byzantine or inactive users may cause model corruption or inactively participation in FL. In this paper, a game theory based detection and incentive method is designed for Byzantine and inactive users. Specifically, a differential aggregate gradient descent (DAGD) algorithm is adopted to improve the stability and fasten the convergence. Then the loss function is modified by considering Byzantine and inactive users. For Byzantine users, a random Euclidean distance (RED) voting method is designed to identify Byzantine users, and after identification, Byzantine users are motivated by the game theory. For inactive users, when inactive users are detected by contribution, Nash equilibrium with a mixed strategy is used to solve the problem of inactive users’ participation in FL. Extensive experimental results show that Byzantine users and inactive users can be detected and motivated by the algorithm. Meanwhile, compared with other methods, the accuracy of the optimized model is improved with reduced training time.

With the deepening of the coupling degree between power network and natural gas network, the traditional independent optimal scheduling of transmission and distribution integrated electricity–gas systems cannot make full use of the flexible control ability of various resources and the complementary support capabilities between different energy systems. Therefore, this paper puts forward a cooperative optimization scheduling model of transmission–distribution​ integrated electricity–gas systems (TD-IEGS). The coordinated operation of multi-energy coupling devices including gas-fired units, combined heat and power (CHP) units and electric boilers (EB) are considered in this paper to enhance system operation flexibility and economy. The second order cone relaxation (SOCR) method is utilized to tackle the non-linear power and gas flow constraints, and the proposed mixed-integer non-linear programming co-optimization scheduling model is transformed into a mixed integer second order cone programming model (MISOCP). Case studies demonstrate that compared with the independent operation mode, the proposed co-optimization scheduling model of TD-IEGS can reduce total operation cost by about 6.7% under 50% wind power penetration level. Moreover, the co-optimization of TD-IEGS can promote wind power utilization especially in a high share of wind energy.

ABSTRACT: Objectives: Carbapenem-resistant Acinetobacter baumannii (CRAB) is a prevalent pathogen contributing to hospital infections. Pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST) and core-genome MLST (cgMLST) are frequently used methods to illuminate the nosocomial transmission of CRAB. In this study, we compared the discriminatory power of the three typing methods. Methods: Antimicrobial susceptibility tests were performed by the broth microdilution and Vitek2 methods. PFGE, MLST and cgMLST were conducted to determine the clonality and phylogenetic relationship of the strains. Whole-genome sequence data were acquired by an Illumina HiSeq 2000, and cgMLST was analysed by the Ridom SeqSphere+ v.7.2.3 software. Results: A total of 149 carbapenem-resistant A. baumannii isolates had 15 different PFGE profiles (A-O type), and 73 of the isolates had related subtypes (A1 and A2), accounting for the majority of type A isolates. The maximum-likelihood phylogenetic analysis based on the cgMLST genes grouped the same PFGE clonal pattern A into nine different clusters. ST_Pasteur grouped all the strains into ST2, whereas ST_Oxford grouped the PFGE clonal pattern A isolates into six STs. In addition, the gdhB allele in the ST_Oxford scheme had two copies in five strains, which complicated the ST_Oxford typing. Conclusions: cgMLST was more discriminant than PFGE and MLST. CgMLST is the most suitable and comprehensive method for genotyping A. baumannii in surveillance and epidemiological research.

Expansion-break connecting rods are high-end products for automotive precision transmission. They need to have high strength, high toughness, and brittle cleavage fracture characteristics during cracking processing. Continuous casting production of nonquenched and tempered steel for high-carbon, sulfur-containing, free-cutting, and expanding connecting rods is the current trend for efficient production. Based on the typical bloom continuous casting process and analysis of the as-cast structure and composition uniformity, the common unqualified fracture morphology due to as-cast hereditary factors were studied. Taking the typical German C70S6 steel as an example, a 250 mm × 280 mm section-curved continuous caster was adopted to study the as-cast macrostructure and dendrite morphology of the bloom casting with popular mold electromagnetic stirring. Moreover, the chemical distribution at different crystal regions was studied. Results show that the common center shrinkage defects of high-carbon steel continuous casting blooms are under control, which are beneficial to improve the qualified rate of internal flaw detection for their subsequent hot-rolled bars. However, it is found that there are obvious negative segregation white bands of carbon and sulfur and the deflection of columnar crystals in the solidification front of the initial solidified shell. Both the image analysis of the metallographic sample and solidification simulation by a phase-field method show that this columnar crystal has countercurrent growth characteristics. In addition, its deflection angle is the result of the primary dendrite tip growing in the opposite direction to the swirling fluid flow. In the center of the narrow surface, the measured primary dendrite deflection angle of the columnar crystal region is between −7° and 27°. EDS was used to further detect the distribution of the main alloying elements Si, Mn, and Mo in the different crystal regions of the bloom casting, revealing the segregation characteristics of the as-cast product and differences of each solute element. Finally, the heredity of this as-cast structure and composition segregation on the structure of subsequent hot-rolled bars and connecting rods was discussed. Moreover, the influence of the fracture inconsistency of its expansion and fracture processing were explored. It is pointed out that the as-cast quality control from the very beginning of casting has special significance in meeting the requirement of both processing and service properties of these high-grade high strength low alloy steels.

Hypervirulence and carbapenem resistance have emerged as two distinct evolutionary directions for Klebsiella pneumoniae, which pose a great threat in clinical settings. Multiple virulence factors contribute to hypervirulence, and the mechanisms of carbapenem resistance are complicated. However, more and more K. pneumoniae strains have been identified in recent years integrating both phenotypes, resulting in devastating clinical outcomes. Hypervirulent and carbapenem-resistant K. pneumoniae (CR-hvKP) emerged in the early 2010s and thereafter have become increasingly prevalent. CR-hvKP are primarily prevalent in Asia, especially China, but are reported all over the world. Mechanisms for the emergence of CR-hvKP can be summarised by three patterns: (i) carbapenem-resistant K. pneumoniae (CRKP) acquiring a hypervirulent phenotype; (ii) hypervirulent K. pneumoniae (hvKP) acquiring a carbapenem-resistant phenotype; and (iii) K. pneumoniae acquiring both a carbapenem resistance and hypervirulence hybrid plasmid. With their global dissemination, continued surveillance of the emergence of CR-hvKP should be more highly prioritised.

Federated learning has become increasingly important for modern machine learning, especially for data privacy sensitive scenarios. Existing federated learning mainly adopts a central server-based network topology, however, the training process of which is susceptible to the central node. To address this problem, this article proposed a decentralized federated learning method based on node selection and knowledge distillation. Specifically, the central node in this method is variable, and it is selected by the indicator interaction between nodes. Meanwhile, the knowledge distillation mechanism is added to make the student model as close as possible to the teacher’s network and ensure the model’s accuracy. The experiments were conducted on the public MNIST, CIFAR-10, and FEMNIST datasets for both the Independent Identically Distribution (IID) setting and the non-IID setting. Numerical results show that the proposed method can achieve an improved accuracy as compared to the centralized federated learning method, and the computing time is reduced greatly with less accuracy loss as compared to the blockchain decentralized federated learning. Therefore, the proposed method guarantees the model effect while meeting the individual model requirements of each node and reducing the running time.

The pine wilt disease (PWD) is one of the most dangerous and destructive diseases to coniferous forests. The rapid spread trend and strong destruction directly threaten the security of forests. The complex spread pattern and the hard labor process of diagnosis call for an effective way to detect the infected areas. In this paper, an airborne edge-computing and lightweight deep learning based system are designed for PWD detection by using imagery sensors. Unmanned aerial vehicle (UAV) is firstly utilized to realize a large-scale coverage of forests, which can substantially reduce the hard labor. Except for infected trees, a large number of irrelevant images are also acquired by the UAV, which will overload the burden of process and transmission. Then a lightweight improved YOLOv4-Tiny based method (named as YOLOv4-Tiny-3Layers) is proposed to filter these uninterested images by leveraging the computation capability of edge computing, which can realize a fast coarse-grained detection with a low missing rate. Finally, all the remaining images are transmitted to the ground workstation for the final fine-grained detection. Experimental results show that the proposed system can implement a fast detection with superior performance as compared to other methods, which helps to detect the infected pine trees in a quick manner.

Abstract Since the outbreak of COVID-19, many COVID-19 research studies have proposed different models for predicting the trend of COVID-19. Among them, the prediction model based on mathematical epidemiology (SIR) is the most widely used, but most of these models are adapted in special situations based on various assumptions. In this study, a general adapted time-window based SIR prediction model is proposed, which is characterized by introducing a time window mechanism for dynamic data analysis and using machine learning method predicts the basic reproduction number and the exponential growth rate of the epidemic. We analyzed COVID-19 data from February to July 2020 in seven countries–––China, South Korea, Italy, Spain, Brazil, Germany and France, and the numerical results showed that the framework can effectively measure the real-time changes of the parameters during the epidemic, and error rate of predicting the number of COVID-19 infections in a single day is within 5%.

ABSTRACT Cefiderocol is a novel siderophore cephalosporin exhibiting potent antimicrobial activities. Although cefiderocol has not been approved in China, resistance is emerging. A multicenter study was performed to evaluate the cefiderocol resistance in carbapenem-resistant Klebsiella pneumoniae (CRKP) strains from bloodstream infections in patients with hematologic malignancies in China. Clinical data analysis and whole-genome sequencing were conducted for collected cefiderocol-resistant CRKP strains. CRISPR-Cas9 system was employed to construct site-specific mutagenesis for gene cirA. Plasmid curing and cloning were performed to assess the effect of β-lactamases on cefiderocol resistance. Total 86 CRKP strains were collected. The MICs of cefiderocol ranged from 0.06 to >256 mg/L. Among four cefiderocol-nonsusceptible strains (4/86, 4.7%), two cefiderocol-resistant strains AR8538 (MIC = 32 mg/L) and AR8416 (MIC > 256 mg/L) were isolated from two patients with acute lymphocytic leukemia (frequency of resistance, 2/86, 2.3%). Metallo- and serine-β-lactamase inhibitors addition would decrease the MIC of cefiderocol from 32 to 1 mg/L in AR8538, which harbors blaSHV-12, blaDHA-1, and two copies of blaNDM-1 in different plasmids. Avibactam did not impact cefiderocol susceptibility of AR8416, which produces NDM-5. However, we found a deficient CirA in AR8416. Using the same K serotype strain D3, we proved CirA deficiency or carrying NDM individually reduced cefiderocol susceptibility, but their simultaneously existence rendered a high-level cefiderocol resistance. In summary, the resistance of CRKP against cefiderocol is mediated by multiple factors, including the deficiency of CirA, metallo- or serine-β-lactamases, while a high-level cefiderocol resistance could be rendered by the combined effect of NDM expression and CirA deficiency. IMPORTANCE Cefiderocol-resistant CRKP strains are emerging in bloodstream infections in Chinese patients with hematologic malignancies, although cefiderocol has not been approved for clinical use in China. Our study proved that the resistance of CRKP against cefiderocol is mediated by multiple factors, including the deficiency of CirA, metallo- or serine-β-lactamases, while a high-level cefiderocol resistance could be rendered by the combined effect of NDM expression and CirA deficiency. As NDM production is one of the most critical mechanisms resulting in carbapenem resistance, it would pose great challenges on the clinical efficacy of cefiderocol in future.

Pine wilt disease (PWD) has become increasingly serious recently and causes great damage to the world’s pine forest resources. The use of unmanned aerial vehicle (UAV)-based remote sensing helps to identify pine nematode trees in time and has become a feasible and effective approach to precisely monitor PWD infection. However, a rapid and high-accuracy detection approach has not been well established in a complex terrain environment. To this end, a deep learning-based pine nematode tree identification method is proposed by fusing visible and multispectral imagery. A UAV equipped with a multispectral camera and a visible camera was used to obtain imagery, where multispectral imagery includes six bands, i.e., red, green, blue, near-infrared, red edge and red edge 750 nm. Two vegetation indexes, NDVI (Normalized Difference Vegetation Index) and NDRE (Normalized Difference Red Edge Index) are extracted as a typical feature according to the reflectance of infected trees in different spectral bands. The YOLOv5 (You Only Look Once v5)-based detection algorithm is adopted and optimized from different aspects to realize the identification of infected pine trees with high detection speed and accuracy. e.g., GhostNet is adopted to reduce the number of model parameters and improve the detection speed; a module combining a CBAM (Convolutional Block Attention Module) and a CA (Coordinate Attention) mechanism is designed to improve the feature extraction for small-scale pine nematode trees; Transformer module and BiFPN (Bidirectional Feature Pyramid Network) structure are applied to improve the feature fusion capability. The experiments show that the mAP@0.5 of the improved YOLOv5 model is 98.7%, the precision is 98.1%, the recall is 97.3%, the average detection speed of single imagery is 0.067 s, and the model size is 46.69 MB. All these metrics outperform other comparison methods. Therefore, the proposed method can achieve a fast and accurate detection of pine nematode trees, providing effective technical support for the control of a pine nematode epidemic.

In this paper, a space-time absolute nodal coordinate formulation cable (SAC) element forming technique based on the Lagrange family of shape functions is proposed. Two distinct SAC elements, each with a distinct spatial shape function, have been generated by this method. Moreover, the external forces such as the bending moment and the air resistance formula have been accounted for. The Lagrange multiplier method, along with the concepts of replacement constraint and supplementary constraint, has been employed to provide a solution for the dynamics of constrained mechanical systems. Additionally, a constraint conversion strategy has been suggested. The solver has been constructed through Hamilton’s law of varying action. The space-time finite element method is used to solve dynamic problems, employing the Newton algorithm and quasi-Newton algorithm. The accuracy and efficiency of the solution has been verified by three simulations and one experiment. The circle-bending static simulation and the double-ended velocity impact dynamic simulation demonstrate the accuracy of the two elements. The correlation between statics and dynamics has been studied for different discretization methods and different solvers’ calculation accuracy and efficiency. Different modeling methods, time steps, order and the application of the quasi-Newton method all have a bearing on the efficiency of the solution. Finally, a comparison with an experiment in the free-pendulum simulation reveals the capability of this model to simulate dynamic problems with air resistance.

Objective Secondary infection, especially bloodstream infection, is an important cause of death in critically ill patients with COVID-19. We aimed to describe secondary bloodstream infection (SBI) in critically ill adults with COVID-19 in the intensive care unit (ICU) and to explore risk factors related to SBI. Methods We reviewed all SBI cases among critically ill patients with COVID-19 from 12 February 2020 to 24 March 2020 in the COVID-19 ICU of Jingmen First People's Hospital. We compared risk factors associated with bloodstream infection in this study. All SBIs were confirmed by blood culture. Results We identified five cases of SBI among the 32 patients: three with Enterococcus faecium , one mixed septicemia ( E. faecium and Candida albicans ), and one C. parapsilosis . There were no significant differences between the SBI group and non-SBI group. Significant risk factors for SBI were extracorporeal membrane oxygenation, central venous catheter, indwelling urethral catheter, and nasogastric tube. Conclusions Our findings confirmed that the incidence of secondary infection, particularly SBI, and mortality are high among critically ill patients with COVID-19. We showed that long-term hospitalization and invasive procedures such as tracheotomy, central venous catheter, indwelling urethral catheter, and nasogastric tube are risk factors for SBI and other complications.

Carbapenem-resistant Klebsiella pneumoniae (CRKP) is highly prevalent and poses a significant threat to public health. In critically ill patients, gut colonization is considered to be the reservoir of recurrent CRKP infection. Therefore, eliminating CRKP carriage in the intestine is critical for preventing subsequent CRKP infection. In the present study, Lactobacillus plantarum LP1812, a probiotic that can inhibit CRKP in vitro, was used as a candidate probiotic to investigate its efficacy for CRKP anticolonization. Compared with the control, mice fed with 1×10 8 CFU L. plantarum LP1812 exhibited significant CRKP clearance from 1×10 4 CFU/mg to less than 10 CFU/mg in mice feces. Furthermore, 16S RNA gene sequencing revealed that L. plantarum LP1812 modulated mice microbiota by increasing the relative abundance of the genus Halomanas, Blautia, and Holdemania. Further KEGG pathway enrichment analysis revealed that fatty acid-utilizing bacteria, such as acetate-producing Bacteroidetes and Blautia flourished in mice fed with L. plantarum LP1812. Moreover, we found that the concentration of acetic acid was higher in L. plantarum LP1812, which inhibited the growth of K. pneumoniae strains in vitro. Meanwhile, mice intragastrically administered with acetic acid exhibited significantly increased CRKP elimination in vivo. In conclusion, L. plantarum LP1812 is a potential candidate for intestinal CRKP anticolonization by regulating the intestinal microbiota and inhibiting CRKP via increased acetic acid in the intestinal lumen.

Typical engineering cable structures, such as high-voltage wire and wire rope, usually bring a damping effect which cannot be ignored due to the technological problems of manufacturing. For such problems, especially the damping of cable structures undergoing large displacement and severe deformation, few studies have been reported in the past. In this work, the fractional derivative viscosity model is introduced into the cables described by the absolute nodal coordinate formulation. The computer implementation algorithm of the proposed cable damping model is given based on the three-parameter fractional derivative model. Two numerical examples demonstrate the effectiveness and convergence property of the proposed cable damping model. An experiment is proposed in which a wire is tensioned and released. Configurations are captured by the high-speed camera and compared with the results obtained from the numerical simulation. The agreement of the simulation and experimental results validates the proposed cable damping in application.

The non-Typhi Salmonella (NTS) infection is critical to children’s health, and the ceftriaxone is the important empirical treatment choice. With the increase resistance rate of ceftriaxone in Salmonella, the molecular epidemiology and resistance mechanism of ceftriaxone-resistant Salmonella needs to be studied. From July 2019 to July 2020, a total of 205 NTS isolates were collected, 195 of which (95.1%) were cultured from stool, but 10 isolates were isolated from an extraintestinal site. Serogroup B accounted for the vast majority (137/205) among the isolates. Fifty-three isolates were resistant to ceftriaxone, and 50 were isolated from children younger than 4years of age. The resistance rates for ceftriaxone, ciprofloxacin, and levofloxacin were significantly higher in younger children than the older children. The resistance genes in the ceftriaxone-susceptible isolates were detected by PCR, and ceftriaxone-resistant Salmonella were selected for further whole-genome sequencing. Whole-genome analysis showed that serotype Typhimurium and its monophasic variant was the most prevalent in ceftriaxone-resistant isolates (37/53), which comprised ST34 (33/53), ST19 (2/53), and ST99 (2/53), and they were close related in the phylogenetic tree. However, the other isolates were diverse, which included one Enteritidis (ST11), one Indiana (ST17), one Derby (ST40), four Kentucky (ST198), two Goldcoast (ST2529, ST358), one Muenster (ST321), one Virchow (ST359), one Rissen (ST469), one Kedougou (ST1543), two Uganda (ST684), and one Kottbus (ST8839). Moreover, CTX-M-55 ESBLs production (33/53) was found to be mainly responsible for ceftriaxone resistance, followed by blaCTX-M-65 (12/53), blaCTX-M-14 (4/53), blaCTX-M-9 (2/53), blaCTX-M-64 (1/53), blaCTX-M-130 (1/53), and blaCMY-2 (1/53). ISEcp1, IS903B, IS Kpn26, IS1F, and IS26 were connected to antimicrobial resistance genes transfer. In conclusion, the dissemination of ESBL-producing Salmonella isolates resulted in an increased prevalence of ceftriaxone resistance in young children. The high rate of multidrug resistance should be given additional attention.

Klebsiella pneumoniae can cause both hospital- and community-acquired clinical infections. Last-line antibiotics against carbapenem-resistant K. pneumoniae (CRKP), such as ceftazidime/avibactam (CZA) and tigecycline (TGC), remain limited as treatment choices. This study aimed to investigate the mechanisms by which CRKP acquires CZA and TGC resistance in vivo under β-lactam antibiotic and TGC exposure. Three CRKP strains (XDX16, XDX31 and XDX51) were consecutively isolated from an inpatient with a urinary tract infection in two months. PFGE and MLST showed that these strains were closely related and belonged to sequence type (ST) 4496, which is a novel ST closely related to ST11. Compared to XDX16 and XDX31, XDX51 developed CZA and TGC resistance. Sequencing showed that double copies of blaKPC-2 were located on a 108 kb IncFII plasmid, increasing blaKPC-2 expression in XDX51. In addition, ramR was interrupted by Insertion sequence (IS) Kpn14 in XDX51, with this strain exhibiting upregulation of ramA, acrA and acrB expression compared with XDX16 and XDX31. Furthermore, LPS analysis suggested that the O-antigen in XDX51 was defective due to ISKpn26 insertion in the rhamnosyl transferase gene wbbL, which slightly reduced TGC susceptibility. In brief, CZA resistance was caused mainly by blaKPC-2 duplication, and TGC resistance was caused by ramR inactivation with additional LPS changes due to IS element insertion in wbbL. Notably, CRKP developed TGC and CZA resistance within one month under TGC and β-lactam treatment without exposure to CZA. The CRKP clone ST4496 has the ability to evolve CZA and TGC resistance rapidly, posing a potential threat to inpatients during antibiotic treatment.

Carbapenem-resistant Klebsiella pneumoniae (CRKP) is an urgent public health problem worldwide, and its rapid evolution in the clinical environment has been a major concern. A total of 99 CRKP isolates spreading in the intensive care unit (ICU) setting were included and subjected to whole-genome sequencing, and their sequence types (STs), serotype loci, and virulence determinants were screened based on genome data. The phylogenetic structure was reconstructed based on the core genome multilocus sequence typing method. Regions of recombination were assessed. Biofilm formation, serum resistance assays, and a Galleria mellonella infection model were used to evaluate strain virulence. A novel ST, designated ST4496, emerged in the ICU and spread for 6 months before its disappearance. ST4496 was closely related to ST11, with only a single-allele variant, and ST11 is the most dominant clinical clone in China. Recombination events occurred at capsule biosynthesis loci and divided the strains of ST11 and its derivative ST4496 into three clusters, including ST11-KL47, ST11-KL64, and ST4496-KL47. The phylogenetic structure indicated that ST11-KL47 was probably the origin of ST11-related strain evolution and presented more diversity in terms of both sequence similarity and phenotypes. ST4496-KL47 cluster strains presented less virulence than ST11-KL64, which was probably one of the factors preventing the former from spreading widely. In conclusion, ST4496-KL47 was probably derived from ST11-KL47 via intraspecies shifting but was less competitive than ST11-KL64, which also evolved from ST11-KL47 and developed increased virulence via capsule biosynthesis locus recombination. ST11-KL64 has the potential to be the predominant CRKP clone in China.

Hypervirulent Klebsiella pneumoniae strains are typically associated with severe infections and susceptible to most antimicrobial agents. In 2017, a carbapenem-resistant hypervirulent K. pneumoniae (CR-hvKP) strain was isolated from the sputum of a chronic obstructive pulmonary disease (COPD) patient in Zhejiang, China. The goal of the present study was to characterize the molecular features of the CR-hvKP isolate ZJ27003 and its blaKPC-2-harboring plasmid p27003_KPC. Antimicrobial susceptibility was evaluated using the broth microdilution and agar dilution methods. String tests, serum-killing and mouse survival assays were performed to assess virulence, and plasmid conjugation was performed by filter mating. The complete genome sequence of ZJ27003 was acquired using a hybrid assembly of Illumina and Nanopore platform data. The sequence type (ST) of this CR-hvKP isolate was identified as ST23, which exhibits hypervirulence with high serum resistance and murine infection model. The strain is also resistant to carbapenems (imipenem, meropenem and ertapenem), aztreonam and cephalosporins. Additionally, the CR-hvKP isolate carries a 36,708-bp blaKPC-2-harboring plasmid, named p27003_KPC, belonging to the P1 incompatibility (Inc) group. The backbone of p27003_KPC is similar to that of a blaGES-5-harboring Pseudomonas aeruginosa plasmid, in which the blaGES-5 and its surrounding regions were replaced by a blaKPC-2-containing translocatable unit derived from Enterobacteriaceae. The results of a conjugation assay revealed that p27003_KPC can be transferred from K. pneumoniae to P. aeruginosa PAO1 and make the recipient resistant against carbapenem. The identification of a carbapenem-resistant hypervirulent K. pneumoniae isolate carrying and disseminating the blaKPC-2 gene highlights a severe threat to public health.

Hypervirulent Klebsiella pneumoniae (hvKP) has raised grave concerns in recent years and can cause severe infections with diverse anatomic locations including liver abscess, meningitis, and endophthalmitis. However, there is limited data about neck abscess caused by hvKP. A K. pneumoniae strain Kp_whw was isolated from neck abscess. We characterized the genetic background, virulence determinates of the strain by genomic analysis and dertermined the virulence level by serum resistance assay. Kp_whw belonged to sequence type (ST) 1049 K locus (KL) 5. Kp_whw showed hypermucoviscosity phenotype and was resistant to ampicillin but susceptible to the majority of the other antimicrobial agents. A pLVPK-like virulence plasmid and a chromosomal ICEKp5-like mobile genetic element were carried by Kp_whw, resulting in the risk of dissemination of hypervirulence. The strain exhibited relative higher level of core genome allelic diversity than accessory genome profile, in comparison to hvKP of K1/K2 serotype. Kp_whw was finally demonstrated as virulent as the ST23 K1 serotype hvKP strain NTUH-K2044 in vitro. In conclusion, this work elaborates the genetic background of a clinical hvKP strain with an uncommon ST, reinforcing our understanding of virulence mechanisms of hvKP.

The relationship between the popular hot charging associated surface crack sensitivity and the charging temperature was studied from the view of phase transformation. The austenite reversion with various charging temperatures was investigated through the thermal simulation experiments. And a two-dimensional representative volume element model was constructed to analyze the crack sensitivity related to microstructures. Compared to cold charging reversion, with the residual austenite in starting microstructure, the kinetics of hot charging reversion is slightly accelerated and the reversion behavior is changed. As the charging temperature increases, the austenite nucleation-growth from pearlite and ferrite grain boundaries are suppressed, while the austenitization through the growth of residual austenite is enhanced. The change of transformation behavior facilitates the formation of ferrite film during reversion through the morphological influence of austenitization modes. With the increasing of charging temperature, the film-like morphology of the evolved ferrite intensifies, especially in the two-phase temperature range. Consequently, the calculated crack sensitivity index rises sharply from 0.0006 to 0.029 when the charging temperature increases from Ar1 to Ar3 temperature, which is agreeable with the statistical production data. Additionally, it was observed that the incomplete γ → α → γ transformation cannot bring an effective austenite grain refining for the present steel.

Abstract An automatic pump is developed using low water‐head hydropower. The energy conversion efficiency η of the gas‐water energy conversion equipment is the focus. In this equipment, low‐head water normally drains to the vertical downcomer. When water particles separate via gravity, a vacuum is generated, and air is mixed into the water spontaneously. High‐pressure gas is ultimately produced at the end of the pipe. To discuss the effects of the air intake pipe diameter, river drop and water flow rate on η, a full‐scale experiment is conducted, and an analytical solution based on the separation of water particles is derived. The air intake pipe diameter has almost no effect on η, but η changes dramatically as the water flow rate varies. Meanwhile, η initially increases and then decreases as the river drop increases. These findings enable the development of a method for low water‐head hydropower utilization.

Abstract Background Hypervirulent Klebsiella pneumoniae (hvKP) is emerging around the Asian-Pacific region and it is the major cause of the community-acquired pyogenic liver abscesses. Multidrug-resistant hypervirulent Klebsiella pneumoniae (MDR-hvKP) isolates were reported in France, China and Taiwan. However, the international-ally agreed definition for hvKP and the virulence level of hvKP are not clear. Results In this study, 56 hvKP isolates were collected from March 2008 to June 2012 and investigated by string test, capsule serotyping, multilocus sequence typing (MLST), virulence gene detection and serum resistance assay. Among the 56 K. pneumoniae isolates, 64.3% had the hypermucoviscosity phenotype, meanwhile, 64.3% were the K1 serotype and 19.6% were the K2 serotype. Within the K1 serotype, 94.4% were ST23, and within the K2 serotype, ST65, ST86 and ST375 accounted for the same percentage 27.3%. The serum resistance showed statistically normal distribution. According to the 50% lethal dose of Galleria. mellonella infection model, hvKP isolates were divided into high virulence level group and moderate virulence level group. The ability of each method evaluating the virulence level of hvKP was assessed using the area under the receiver operating characteristic curve. Conclusions K1 ST23 K. pneumoniae was the most prevalent clone of the hvKP. However, K1 ST23 K. pneumoniae was the dominant clone in the moderate virulence level group. MLST was a relatively reliable evaluation method to discriminate the virulence level of hvKP in our study.

In this paper, we propose an efficient 2-D direction-of-arrival (DOA) estimation method for co-prime parallel arrays. By using the second-order statistics of the received signals with different time lags, a conjugate augmented spatial-temporal virtual array is constructed to extend the array aperture and enhance the degrees-of-freedom (DOFs). Vectorizing the cross covariance matrix of the virtual array, the 2-D DOA estimation can be cast as a 1-D sparsity-based recovery problem. A dictionary learning technique is then proposed to compensate the off-grid bias caused by discretization. Simulation results show the effectiveness of the proposed method as compared with the state-of-the-art methods.

AlN precipitates are frequently adopted to pin the austenite grain boundaries for the high-temperature carburization of special gear steels. For these steels, the grain coarsening criterion in the carburizing process is required when encountering the composition optimization for the crack-sensitive steels. In this work, the quantitative influence of the Al and N content on the grain size after carburization is studied through pseudocarburizing experiments based on 20Cr steel. According to the grain structure feature and the kinetic theory, the abnormal grain growth is demonstrated as the mode of austenite grain coarsening in carburization. The AlN precipitate, which provides the dominant pinning force, is ripened in this process and the particle size can be estimated by the Lifshitz−Slyosov−Wagner theory. Both the mass fraction and the pinning strength of AlN precipitate show significant influence on the grain growth behavior with the critical values indicating the grain coarsening. These criteria correspond to the conditions of abnormal grain growth when bearing the Zener pinning, which has been analyzed by the multiple phase-field simulation. Accordingly, the models to predict the austenite grain coarsening in carburization were constructed. The prediction is validated by the additional experiments, resulting in accuracies of 92% and 75% for the two models, respectively. Finally, one of the models is applied to optimize the Al and N contents of commercial steel.

Create-Rank-Compete (CRC) is a teaching method designed to promote learner-to-learner, learner-to-material, and learner-to-instructor engagement through asynchronous and synchronous online interactions. The CRC method is rooted in the constructivism theory of learning; by design, it is a Bruner's spiral that supports metacognitive skill development through problem posing and peer assessment activities. The method is implementable in both seated and remote courses. Periodically during a course, students are asked to create multiple choice questions based on the covered material; then they perform pairwise comparisons of the de-identified peers' creations; from the ranked list of the questions, the instructor is able to track the class progress and use this student-generated content to compose quiz materials for testing and discussion. This paper details the CRC method and reports on its first implementation, which took place during the outbreak of the COVID-19 pandemic, in the semester when a large public university in the northeastern United States switched from live to online teaching. Students engaged with the CRC activities two times more than required, and reported high enjoyment and knowledge acquisition value delivered by the method.

Based on the Ø195 mm round bloom continuous casting of oil pipe steel, a two dimensional thermal-mechanical coupled model has been developed to investigate the deformation behavior of round bloom during soft reduction (SR) in the reduction force mode. Good agreement was achieved in surface temperature, shell thickness and contact zone width from modeling and measurement. Under the same reduction force, the reduction amount of round bloom at the front unit is much larger than back unit. Moreover, due to its higher temperature and lower center solid fraction, the deformation penetration before solidification is much stronger than that after solidification. Considering the limitation of the round bloom ovality, the maximum allowable force in reduction unit is calculated. According to the simulation results, a multi-unit soft reduction plan was proposed and carried out on the Ø195 mm round bloom. After the reduction process of No.1 to No.3 withdrawal units, the shrinkage porosity in the center of the round bloom was almost vanished, while the number and size of spot segregation were significantly reduced. Moreover, the oil pipe produced by the round bloom with SR got a better resistance to sulfide stress corrosion (SSC). It indicates that SR is an effective technology for the round bloom to control the shrinkage porosity and spot segregation in the continuous casting.

Objective This study aimed to examine the mechanism of diaphragmatic dysfunction in sepsis due to severe acute pancreatitis (SAP) with intra-abdominal hypertension (IAH) in a rat model. Methods The rats were assigned at random to four groups: (1) control (n = 5), (2) SAP (n = 5), (3) SAP+IAH (n = 5), and (4) SAP+IAH+SS-31 (n = 5). Length and force output of the diaphragm were analysed in vivo . Histopathological examinations were performed by haematoxylin–eosin. Oxidative stress levels related to protease in diaphragmatic mitochondria were detected with a colorimetric technique. Results In the septic rat model due to SAP complicated by IAH, myofibres were increased. Muscle contractile function was significantly lower in the SAP+IAH group compared with the SAP and control groups. Glutathione peroxidase and superoxide dismutase levels were significantly lower and malondialdehyde levels were higher in the SAP and SAP+IAH groups compared with the control group. Notably, SS-31 could reverse atrophy of myofibres in SAP+IAH rats, as well as contractile dysfunction and mitochondrial dysfunction in the diaphragm. Conclusions Diaphragmatic structure and biomechanics are altered in septic rats due to SAP and IAH. This finding is mainly due to an increase in release of mitochondrial reactive oxygen species.

A three-dimensional numerical model combining electromagnetic field, fluid flow, heat transfer, and solidification has been established to study the effect of nozzle injection mode and mold electromagnetic stirring (M-EMS) on the internal quality of a continuously cast bloom. The model is validated by measured data of the magnetic flux density along the stirrer center line. According to the simulation and experimental results, M-EMS can introduce a horizontal swirling flow ahead of the solidification front, promoting the superheat dissipation of molten steel and columnar to equiaxed transition (CET). As the stirring current increases from 0 to 800 A, the superheat at the mold exit in the bloom center decreases by 1.9 K for the single-port nozzle case and 3.8 K for the five-port nozzle case. The resulting increase in the equiaxed crystal ratio is about 5.65% and 4.06%, respectively. In comparison, the injection mode shows a more significant influence on the heat transfer and solidification structure in the bloom under the present casting conditions. The superheat at the mold exit in the bloom center decreases by 5.1−7.7 K as the injection mode changes from a single-port nozzle to a five-port nozzle, and the increase in the equiaxed crystal ratio ranges between 14.8% and 17%. It is found that the flow velocity of the molten steel in front of the solidification interface for the five-port nozzle is higher than that for the single-port nozzle regardless of the M-EMS power. The washing effect here reinforces both the heat exchange through the solidification interface and the dendrite re-melting or fragmenting, stimulating the formation of an equiaxed crystal at the bloom center. In addition, it is observed that both the central shrinkage and carbon segregation have decreased with the five-port nozzle plus M-EMS. This suggests that the combined application of a five-port nozzle and M-EMS can effectively improve the internal quality of large bloom castings.

In this paper, we investigate the problem of two-dimensional (2D) direction-of-arrival (DOA) estimation for generalized co-prime planar arrays. The classic multiple signal classification (MUSIC)-based methods can provide a superior estimation performance, but suffer from a tremendous computational burden caused by the 2D spectral search. To this end, we reduce the 2D problem into a one-dimensional (1D) one and propose a reduced dimension partial spectral search estimation method, which can compress the search region into a small 1D sector. Moreover, the proposed method can utilize the full information of the entire array without degrees-of-freedom loss. Furthermore, an iterative approach is also proposed to reduce complexity and improve performance. Simulation results show that the proposed methods can provide improved performance with substantially reduced complexity, as compared to other state-of-the-art methods.