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Vanadium (V) plays a crucial role in the formation of precipitates. In this study, different amounts of submicron-sized precipitates were introduced in high-carbon pearlitic CrMo wear-resistant cast steel by the addition of V. The result shows that the microstructure of high-carbon CrMo wear-resistant cast steel consists of lamellar pearlite and submicron-sized precipitates. With higher V content, the density of submicron-sized precipitates increases. The wear resistance of the steel also enhances with the addition of V, which is primarily attributed to the formation of submicron-sized precipitates resulting in the enhancement of initial mechanical properties and the creation of a harder work-hardening layer in worn surface. The wear mechanisms involve microploughing, microcutting, microfatigue, and microcracking in high-carbon pearlitic CrMo wear-resistant cast steel, but the introduction of submicron-sized precipitates leads to a substantial reduction in the depth of microploughing and microcutting.

Rare earth (RE) elements not only modify inclusions but also refine the steel's microstructure. This study investigates the evolution mechanism of cerium on inclusions and microstructure in low-alloy cast steel through experimental and thermodynamic analyses. After cerium is added to the steel, strip-like inclusions transform into spherical ones, accompanied by a reduction in size. The evolution path of inclusions follows MnS + MnS–Al2O3→Ce2O2S–Ce2S3–MnS + CeAlO3–Ce2S3–MnS with cerium addition. Notably, Ce2S3 and Ce2O2S exhibit an orientation relationship, with [1‾ 22]Ce2S3//[01 1‾ 1]Ce2O2S and (02 2‾)Ce2S3//(1‾ 011)Ce2O2S. Compared to Ce-free steel, the Ce-0.06 steel shows a reduced grain size and the absence of needle-shaped Widmanstätten structures, which may be mainly attributed to rare earth inclusions as heterogeneous nucleation of δ-Fe. This work can provide a theoretical basis for improving the overall mechanical properties of low-alloy cast steel by adding cerium.

Hot tearing is a serious destructive solidification defect of magnesium alloys and other casting metals. Quantitative and controllable measurements on the thermal and the mechanical behavior of an alloy during its solidification process are crucial for the understanding of hot tearing formation. We developed a new experimental method and setup to characterize hot tearing behavior via controlled cooling and active loading to force hot hearing formation on cooling at selected fractions of solid. The experimental setup was fully instrumented so that stress, strain, strain rate, and temperature can be measured in-situ while hot tearing was developing. An AZ91D magnesium alloy, which is prone to hot tearing, was used in this study. Results indicate that when hot hearing occurred, the local temperature, critical stress, and cumulative strain were directly affected by strain rate. Depending on the applied strain rate, hot tearing of the AZ91D magnesium alloy could occur in two solidification stages: one in the dendrite solidification stage (fS ∼ 0.81–0.82) and the other in the eutectic solidification stage (fS ∼ 0.99). AZ91D alloy exhibited distinct mechanical behaviors in these two ranges of fraction solid.

The rising prevalence of viral-induced diseases, particularly those caused by certain strains, poses a substantial risk to the genetic diversity of Solanaceae crops and the overall safety of horticultural produce. According to the “gene-for-gene” hypothesis, resistance proteins are capable of selectively identifying nontoxic effectors produced by pathogens, as they are under purview of the host’s immune defenses. The sensitivity and responsiveness of Solanaceae plants to viral attacks play a crucial role in shaping the outcomes of their interactions with viruses. Pathogenic organisms, devise an array of infection tactics aimed at circumventing or neutralizing the host’s immune defenses to facilitate effective invasion. The invasion often accomplishes by suppressing or disrupting the host’s defensive mechanisms or immune signals, which are integral to the infection strategies of such invading pathogens. This comprehensive review delves into the myriad approaches that pathogenic viruses employ to infiltrate and overcome the sophisticated immune system of tomatoes. Furthermore, the review explores the possibility of utilizing these viral strategies to bolster the resilience of horticultural crops, presenting a hopeful direction for forthcoming progress in plant health and agricultural stability.

Precipitation strengthening is a crucial method for enhancing the mechanical properties of steel. The bridgman directional solidification furnace, optical microscope (OM), scanning electron microscope (SEM), electron probe analyzer (EPMA) and transmission electron microscope (TEM) were used to investigate the effect of solidification cooling rate on the solidification microstructure, microsegregation, and nanoprecipitates in medium carbon CrMo cast steel. The results indicate that as the cooling rate increases, the solidification microstructure is significantly refined. The relationship between the cooling rate (CA) and primary dendrite arm spacing (PDAS, λ1) and secondary dendrite arm spacing (SDAS, λ2) are given by λ1 = 123.74 × C-0.4088A, λ2 = 66.63 × C-0.6532 A. Solute elements like Cr, Mo, and V exhibit noticeable positive segregation in the inter-dendritic. When the cooling rate does not exceed 0.47 °C/s, the solute concentrations in the inter-dendritic increase with higher cooling rate, leading to a decrease in the effective solute partition coefficient. This phenomenon is primarily attributed to the back diffusion of solute elements during solidification. Following heat treatment, precipitation of M6C, V(C,N), and M23C6 occurs within the inter-dendritic regions. If the solidification cooling rate does not exceed 0.47 °C/s, the density and volume fraction of nanoprecipitates increase with higher cooling rate. This trend primarily results from the reduction in critical nucleation radius and critical nucleation energy, facilitating easier nucleation of nanoprecipitates.

Abstract Background Ultrasound-guided thermal ablation (TA) has emerged as a robust therapeutic approach for treating solid tumors in multiple organs, including the thyroid. Yet, its efficacy and safety profile in the management of Graves’ Disease (GD) remains to be definitively established. Methods A retrospective study was conducted on 50 GD patients treated with TA between October 2017 and December 2021. Key metrics like thyroid volume, volume reduction rate (VRR), thyroid hormones, and basal metabolic rate (BMR) were evaluated using paired Wilcoxon tests. Results The intervention of ultrasound-guided TA yielded a statistically significant diminution in total thyroid volume across all postoperative follow-up intervals—1, 3, 6, and 12 months—relative to pre-intervention baselines (p

Abstract Background Sublobar resection for ground-glass opacity became a recommend surgery choice supported by the JCOG0804/JCOG0802/JCOG1211 results. Sublobar resection includes segmentectomy and wedge resection, wedge resection is suitable for non-invasive lesions, but in clinical practice, when pathologists are uncertain about the intraoperative frozen diagnosis of invasive lesions, difficulty in choosing the appropriate operation occurs. The purpose of this study was to analyze how to select invasive lesions with clinic-pathological characters. Methods A retrospective study was conducted on 134 cases of pulmonary nodules diagnosed with minimally invasive adenocarcinoma by intraoperative freezing examination. The patients were divided into two groups according to intraoperative frozen results: the minimally invasive adenocarcinoma group and the at least minimally invasive adenocarcinoma group. A variety of clinical features were collected. Chi-square tests and multiple regression logistic analysis were used to screen out independent risk factors related to pathological upstage, and then ROC curves were established. In addition, an independent validation set included 1164 cases was collected. Results Independent risk factors related to pathological upstage were CT value, maximum tumor diameter, and frozen result of AL-MIA. The AUC of diagnostic mode was 71.1% [95%CI: 60.8-81.3%]. The independent validation included 1164 patients, 417 (35.8%) patients had paraffin-based pathology of invasive adenocarcinoma. The AUC of diagnostic mode was 75.7% [95%CI: 72.9-78.4%]. Conclusions The intraoperative frozen diagnosis was AL-MIA, maximum tumor diameter larger than 15 mm and CT value is more than − 450Hu, highly suggesting that the lung GGO was invasive adenocarcinoma which represent a higher risk to recurrence. For these patients, sublobectomy would be insufficient, lobectomy or complementary treatment is encouraged.

Abstract Objectives The right lower sleeve lobectomy is a rarely performed major lung resection.This study aims to evaluate the safety and effectiveness of this procedure by comparing to right lower bilobectomy in non-small cell lung cancer patients. Methods We retrospectively reviewed a prospective database of non-small cell lung cancer patients who underwent right lower sleeve lobectomy (group S) or right lower bilobectomy (group B) from January 2014 to January 2020 in Shanghai Pulmonary Hospital. Propensity score matching method was applied to balance confounders between the two groups, resulting in 41 matched pairs.The analysis was performed to compare perioperative outcomes, long-term survival, and postoperative pulmonary volume between the two groups. Results No significant differences in the characteristics were observed between the two matched groups.Major postoperative complications developed in 31.7% of the patients in group B and 12.1% of the patients in group S (P = 0.032).Intervention rate for surgical residual cavity in group B is significantly higher than those patients in group S(21.9%vs7.3%,p = 0.037).The postoperative right lateral and overall lung volume in group S were both significantly larger than that in group B (P = 0.026,P = 0.001,respectively). Conclusions Compared to bi-lobectomy, a middle lobe sparing sleeve resection obtains a less prevalence of major complications, smaller postoperative residual air space and similar long-term survival for selected central right lower NSCLC patients.

Abstract Background In recent years, natural bone extracellular matrix (ECM)-inspired materials have found widespread application as scaffolds for bone tissue engineering. However, the challenge of creating scaffolds that mimic natural bone ECM’s mechanical strength and hierarchical nano-micro-macro structures remains. The purposes of this study were to introduce an innovative bone ECM-inspired scaffold that integrates a 3D-printed framework with hydroxyapatite (HAp) mineralized graphene oxide-collagen (GO-Col) microscaffolds and find its application in the repair of mandibular bone defects. Methods Initially, a 3D-printed polycaprolactone (PCL) scaffold was designed with cubic disks and square pores to mimic the macrostructure of bone ECM. Subsequently, we developed multi-layer mineralized GO-Col-HAp microscaffolds (MLM GCH) to simulate natural bone ECM's nano- and microstructural features. Systematic in vitro and in vivo experiments were introduced to evaluate the ECM-inspired structure of the scaffold and to explore its effect on cell proliferation and its ability to repair rat bone defects. Results The resultant MLM GCH/PCL composite scaffolds exhibited robust mechanical strength and ample assembly space. Moreover, the ECM-inspired MLM GCH microscaffolds displayed favorable attributes such as water absorption and retention and demonstrated promising cell adsorption, proliferation, and osteogenic differentiation in vitro. The MLM GCH/PCL composite scaffolds exhibited successful bone regeneration within mandibular bone defects in vivo. Conclusions This study presents a well-conceived strategy for fabricating ECM-inspired scaffolds by integrating 3D-printed PCL frameworks with multilayer mineralized porous microscaffolds, enhancing cell proliferation, osteogenic differentiation, and bone regeneration. This construction approach holds the potential for extension to various other biomaterial types. Graphical Abstract

Evolutionary neural architecture search (ENAS) aims to automate the architecture design of deep neural networks (DNNs). In recent years, various ENAS algorithms have been proposed, and their effectiveness has been demonstrated. In practice, most ENAS methods based on genetic algorithms (GAs) use fixed-length encoding strategies because the generated chromosomes can be directly processed by the standard genetic operators (especially the crossover operator). However, the performance of existing ENAS methods with fixed-length encoding strategies can also be improved because the optimal depth is regarded as a known priori. Although variable-length encoding strategies may alleviate this issue, the standard genetic operators are replaced by the developed operators. In this paper, we proposed a framework to bridge this gap and to improve the performance of existing ENAS methods based on GAs. First, the fixed-length chromosomes were transformed into variable-length chromosomes with the encoding rules of the original ENAS methods. Second, an encoder was proposed to encode variable-length chromosomes into fixed-length representations that can be efficiently processed by standard genetic operators. Third, a decoder cotrained with the encoder was adopted to decode those processed high-dimensional representations which cannot directly describe architectures into original chromosomal forms. Overall, the performances of existing ENAS methods with fixed-length encoding strategies and variable-length encoding strategies have both improved by the proposed framework, and the effectiveness of the framework was justified through experimental results. Moreover, ablation experiments were performed and the results showed that the proposed framework does not negatively affect the original ENAS methods.

While numerous hydrogel dressings are available for treating chronically infected wounds, their clinical application is impeded by intricate preparation processes, low mechanical strength, and frequent reliance on exogenous antimicrobial agents. The latter often leads to antibiotic misuse and compromises the bioactivity of cell growth-promoting substances. Therefore, the field of therapeutic treatment is faced with a pressing need to prepare high-mechanical-strength hydrogels through a facile procedure, achieving endogenous antibacterial characteristics and long-term healing abilities for chronically infected wounds. In this study, employing the Michael addition reaction principle, we conducted the conjugate addition of the natural antimicrobial poly amino acid, ε-polylysine (ε-PL), to gelatin methacrylate. This not only augmented the hydrogel’s mechanical strength but also preserved its antimicrobial efficacy. Subsequently, platelet-rich plasma (PRP), capable of releasing diverse growth factors, was introduced. Injectable and degradable hydrogels with high mechanical strength and water absorption were prepared through UV curing while retaining PRP bioactivity. The combination of PRP and ε-PL substantiated the enhanced antimicrobial properties and promotion of human umbilical vein endothelial cell growth, as validated through bacterial inhibition experiments, such as live-dead bacterial staining and cellular assays, including cell proliferation. Therefore, the as-developed PL-PRP hydrogel presents as a promising hydrogel dressing for the treatment of chronically infected wounds.

Multicentric reticulohistiocytosis (MRH) is a rare systemic disorder characterized by histiocytic hyperplasia that mainly involves the skin, mucous membranes, and joints. The typical clinical features include papules, nodules, and arthritis. MRH lesions are relatively extensive but small and scattered. Joint inflammation is characterized by diffuse symmetric polyarthritis as the first symptom, which can be severe and disabling due to destructive joint changes. MRH is easily misdiagnosed in clinical practice. Here, we report the case of an elderly male patient who presented with polyarticular pain in the hip and interphalangeal joints as the first manifestation, followed by the development of large, isolated, bulging skin nodules, which are atypical MRH lesions. This is rare in all MRH case reports, and we made the correct diagnosis by combining skin histopathology, immunohistochemistry, and other clinical examinations. We performed surgical treatment on the local skin lesions of this patient. This case suggests that clinicians should actively correlate the condition and accurately diagnose MRH when encountering atypical skin changes or other diseases as the first symptom and explore the mechanisms of MRH and other clinical manifestations.

Solar radiation prediction research is a key area of interest in the realm of solar energy utilization and has garnered significant attention in recent times. In order to realize accurate prediction of solar radiation and make solar radiation prediction better serve photovoltaic (PV) power generation, this study proposes a solar radiation prediction method based on sequence model, which integrates two kinds of neural networks, namely, temporal convolutional network (TCN) and neural basis expansion analysis (N-BEATS). First, the dataset is preprocessed using Pearson’s correlation coefficient, outlier detection, and normalized to obtain valid and relevant data; second, the features of TCN feature extraction and N-BEATS flexible extension are integrated to predict the solar radiation; then, the model’s hyperparameters are fine-tuned using the grid search algorithm to ensure precise predictions; and last, the correctness of the method is verified by comparing the error metrics and the running time. Empirical findings indicate that the TCN-N-BEATS sequence model has high prediction accuracy and short time overhead, and it has certain application value in solar radiation prediction, and the model could offer valuable insights for predicting solar radiation.

The information and communication technology (ICT) makes the smart city exchange information with the general public and deliver higher-quality services to citizens. The collection of waste is important in smart city service and smart technology has great potential for increasing garbage collection efficiency and quality all around the world. This is a waste of resources since garbage is emptied even half-full, city resources are misused, and vehicle gas is wasted. High costs and poor effectiveness are the two main problems with smart city garbage collection. This problem can be solved by recycling since it reduces the garbage that has to be disposed of and protects valuable storage space. Although the recycling rates are rising, estimates predict that people can generate more waste than ever before. A key focus of machine learning is developing algorithms that can acquire and utilize information in the learning process to make future predictions. Therefore, this paper’s automatic machine learning-based waste recycling framework (AMLWRF) has been proposed to classify and separate materials in a mixed recycling application for improved separation of complicated waste. The major goal of this research is to examine machine learning algorithms utilized in recycling systems. This paper suggests the ML and Internet of Things (IoT) for smart waste management to overcome this problem in the smart city. The IoT-powered devices may be installed in waste containers including recycling bins and it gives real-time data on garbage generating behavior. Image processing may be used to calculate a dump’s garbage index. They offer a clear picture of trash and recycling trends and suggestions on improving productivity. This research compiles the most recent advances in recycling-related machine learning.

Summary: Background: Mediastinal neoplasms are typical thoracic diseases with increasing incidence in the general global population and can lead to poor prognosis. In clinical practice, the mediastinum's complex anatomic structures and intertype confusion among different mediastinal neoplasm pathologies severely hinder accurate diagnosis. To solve these difficulties, we organised a multicentre national collaboration on the basis of privacy-secured federated learning and developed CAIMEN, an efficient chest CT-based artificial intelligence (AI) mediastinal neoplasm diagnosis system. Methods: In this multicentre cohort study, 7825 mediastinal neoplasm cases and 796 normal controls were collected from 24 centres in China to develop CAIMEN. We further enhanced CAIMEN with several novel algorithms in a multiview, knowledge-transferred, multilevel decision-making pattern. CAIMEN was tested by internal (929 cases at 15 centres), external (1216 cases at five centres and a real-world cohort of 11 162 cases), and human–AI (60 positive cases from four centres and radiologists from 15 institutions) test sets to evaluate its detection, segmentation, and classification performance. Findings: In the external test experiments, the area under the receiver operating characteristic curve for detecting mediastinal neoplasms of CAIMEN was 0·973 (95% CI 0·969–0·977). In the real-world cohort, CAIMEN detected 13 false-negative cases confirmed by radiologists. The dice score for segmenting mediastinal neoplasms of CAIMEN was 0·765 (0·738–0·792). The mediastinal neoplasm classification top-1 and top-3 accuracy of CAIMEN were 0·523 (0·497–0·554) and 0·799 (0·778–0·822), respectively. In the human–AI test experiments, CAIMEN outperformed clinicians with top-1 and top-3 accuracy of 0·500 (0·383–0·633) and 0·800 (0·700–0·900), respectively. Meanwhile, with assistance from the computer aided diagnosis software based on CAIMEN, the 46 clinicians improved their average top-1 accuracy by 19·1% (0·345–0·411) and top-3 accuracy by 13·0% (0·545–0·616). Interpretation: For mediastinal neoplasms, CAIMEN can produce high diagnostic accuracy and assist the diagnosis of human experts, showing its potential for clinical practice. Funding: National Key R&D Program of China, National Natural Science Foundation of China, and Beijing Natural Science Foundation.

In high-speed steel, carbides are essential phase constituents, which have a direct impact on engineering performance and qualities of high-speed steel. The formation, morphology, and distribution of carbides are dictated by alloying elements. In this paper, various types of carbides in high-speed steel are presented. The effects of different alloying elements such as C, W, Mo, Cr, and V on the formation of carbides in high-speed steel are discussed. Research progresses on carbide improvement by microalloying elements such as N, B, Mg, and rare earth (RE) elements are reviewed. It is reported that Cr promotes the precipitation of M2C, N enhances the formation of fibrous M2C, Mg effectively shatters the large-size carbide grid, Nb refines granular carbide MC, and rare earth elements encourage the formation of M6C, resulting in irregular M2C lamellae. The incorporation of microalloying elements improves the distribution and size of carbides and also refines the solidification structure of high-speed steel.

Abstract Background Drug–target interaction (DTI) prediction plays a crucial role in drug discovery. Although the advanced deep learning has shown promising results in predicting DTIs, it still needs improvements in two aspects: (1) encoding method, in which the existing encoding method, character encoding, overlooks chemical textual information of atoms with multiple characters and chemical functional groups; as well as (2) the architecture of deep model, which should focus on multiple chemical patterns in drug and target representations. Results In this paper, we propose a multi-granularity multi-scaled self-attention (SAN) model by alleviating the above problems. Specifically, in process of encoding, we investigate a segmentation method for drug and protein sequences and then label the segmented groups as the multi-granularity representations. Moreover, in order to enhance the various local patterns in these multi-granularity representations, a multi-scaled SAN is built and exploited to generate deep representations of drugs and targets. Finally, our proposed model predicts DTIs based on the fusion of these deep representations. Our proposed model is evaluated on two benchmark datasets, KIBA and Davis. The experimental results reveal that our proposed model yields better prediction accuracy than strong baseline models. Conclusion Our proposed multi-granularity encoding method and multi-scaled SAN model improve DTI prediction by encoding the chemical textual information of drugs and targets and extracting their various local patterns, respectively.

Consensus is lacking regarding whether high-intensity interval training (HIIT) effectively improves VO2max (VO2peak) in elite athletes (Athlete must be involved in regular competition at the national level). This meta-analysis compared the effects of HIIT and conventional training methods (continuous training, repeated-sprint training, high volume low-intensity training, high-intensity continuous running, sprint-interval training, moderate-intensity continuous training)on VO2max in elite athletes. Nine studies were included, comprising 176 elite athletes (80 female). Compared to that with conventional training, VO2max was significantly increased after HIIT (overall: 0.58 [0.30, 0.87], I2 = 0.49, P = 0.03; males: 0.41 [0.06, 0.76], I2 = 0%, P = 0.89). VO2max had positive training effects when the HIIT recovery period had an interval time ≥2 min (0.44 [0.03, 0.84], I2 = 0%, P = 0.99) and recovery phase intensity ≤40% (0.38 [0.05, 0.71], I2 = 0%, P = 0.96). Thus, HIIT shows superiority over conventional training methods in improving VO2max, promoting aerobic capacity, in elite athletes.

BackgroundSurvival outcomes of early-stage T1-2N0M0 small cell lung cancer (SCLC) patients differ widely, and the existing Veterans Administration Lung Study Group (VALSG) or TNM staging system is inefficient at predicting individual prognoses. In our study, we developed and validated nomograms for individually predicting overall survival (OS) and lung cancer-specific survival (LCSS) in this special subset of patients.MethodsData on patients diagnosed with T1-2N0M0 SCLC between 2000 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. All enrolled patients were split into a training cohort and a validation cohort according to the year of diagnosis. Using multivariable Cox regression, significant prognostic factors were identified and integrated to develop nomograms for 1-, 3-, and 5-year OS and LCSS prediction. The prognostic performance of our new model was measured by the concordance index (C-index) and calibration curve. We compared our latest model and the 8th AJCC staging system using decision curve analyses (DCA). Kaplan–Meier survival analyses were applied to test the application of the risk stratification system.ResultsA total of 1,147 patients diagnosed from 2000 to 2011 were assigned to the training cohort, and 498 cases that were diagnosed from 2012 to 2015 comprised the validation cohort. Age, surgery, lymph node removal (LNR), and chemotherapy were independent predictors of LCSS. The variables of sex, age, surgery, LNR, and chemotherapy were identified as independent predictors of OS. The above-mentioned prognostic factors were entered into the nomogram construction of OS and LCSS. The C-index of this model in the training cohort was 0.663, 0.702, 0.733, and 0.658, 0.702, 0.733 for predicting 1-, 3-, and 5-year OS and LCSS, respectively. Additionally, in the validation cohort, there were 0.706, 0.707, 0.718 and 0.712, 0.691, 0.692. The calibration curve showed accepted prediction accuracy between nomogram-predicted survival and actual observed survival, regardless of OS or LCSS. In addition, there were significant distinctions in the survival curves of OS and LCSS between different risk groups stratified by prognostic scores. Compared with the 8th AJCC staging system, our new model also improved net benefits.ConclusionsWe developed and validated novel nomograms for individual prediction of OS and LCSS, integrating the characteristics of patients and tumors. The model showed superior reliability and may help clinicians make treatment strategies and survival predictions for early-stage T1-2N0M0 SCLC patients.

Androgenic alopecia (AGA) is a common disease that negatively affects patients’ physical and mental health. AGA can be treated with drugs that improve the perifollicular microenvironment, such as 5α-reductase inhibitors (e.g., dutasteride [DUT]), androgen receptor blockers, and minoxidil. However, the efficacy of these treatments is limited. Therefore, this study aimed to show that nanoparticles are effective as stable carriers with high curative benefits and little adverse effects. The in vitro study showed that PLGA-DUT/siAR@DPCM NPs could deliver both DUT and siAR to dermal papilla cells. They could successfully suppress 5α-reductase and knock down androgen receptor, respectively, and thereby promote cell proliferation. In the in vivo study, PLGA-DUT/siAR@DPCM NPs showed a significant therapeutic effect in an AGA mouse model. They successfully penetrated the stratum corneum and showed a clear targeting effect on hair follicles and surrounding tissues. PLGA-DUT/siAR@DPCM NPs could enable the targeted delivery of DUT and siAR through percutaneous penetration, enhancing phagocytosis and decreasing adverse effects. Thus, they have great potential in the clinical treatment of AGA.

Rhizoctonia solani is a widely distributed plant pathogen that can damage many crops. Here, we identified a novel mycovirus tentatively named Rhizoctonia solani partitivirus 433 (RsPV433) from an R. solani (AG-3) strain which caused tobacco target spot disease on flue-cured tobacco. RsPV433 was consisted of two dsRNA segments with lengths of 2450 and 2273 bp, which encoded an RNA-dependent RNA polymerase and a coat protein, respectively. BLASTP results of RsPV433 showed that the closest relative of RsPV433 was Sarcosphaera coronaria partitivirus (QLC36830.1), with an identity of 60.85% on the RdRp amino sequence. Phylogenetic analysis indicated that RsPV433 belonged to the Betapartitivirus genus in the Partitiviridae family. The virus transmission experiment revealed that RsPV433 can be transmitted horizontally. We further tested the biological effect of RsPV433 on R. solani strains and found that the RsPV433-infected R. solani strain grew slower than the RsPV433-free strain on the PDA medium and RsPV433 seemed to have no obvious impact on the lesion inducing ability of R. solani.

Bacillus velezensis strain GUMT319 is a rhizobacteria biocontrol agent that can control tobacco black shank disease. We took GUMT319 as a biological fertilizer on Vitis vinifera L. The test group was treated with GUMT319 for one year and the control group had a water treatment. Yields of GUMT319-treated grape groups were significantly increased compared to the controls. The average length and width of single grape fruit, weight of 100 grape fruits, the sugar/acid ratio, and the content of vitamin C were all increased in the GUMT319-treated grape group. The pH of the soil was higher and the contents of alkaline hydrolyzable nitrogen and available potassium were significantly lower in the GUMT319-treated groups than the controls. The soil microbial community composition was evaluated by 16S rDNA high-throughput sequencing, and the Shannon index and Simpson index all showed that soil microbes were more abundant in the GUMT319-treated group. These results indicate that GUMT319 is not only a biocontrol agent, but also a plant growth-promoting rihizobacteria. It can increase the yield of grape by altering the physical and chemical properties and the microbial community composition of the soil.

Poleroviruses are positive-sense, single-stranded viruses. In this study, we describe the identification of a novel polerovirus isolated from soybean displaying curled leaves. The complete viral genome sequence was identified using high-throughput sequencing and confirmed using rapid amplification of cDNA ends (RACE), RT-PCR and Sanger sequencing. Its genome organization is typical of the members of genus Polerovirus, containing seven putative open reading frames (ORFs). The full genome is composed of single-stranded RNA of 5822 nucleotides in length, with the highest nucleotide sequence identity (79.07% with 63% coverage) for cowpea polerovirus 2 (CPPV2). Amino acid sequence identities of the protein products between the virus and its relatives are below the threshold determined by the International Committee of Taxonomy of Viruses (ICTV) for species demarcation, and this strongly supports this virus’ status as a novel species, for which the name soybean chlorotic leafroll virus (SbCLRV) is proposed. Recombination analysis identified a recombination event in the ORF5 of the 3’ portion in the genome. Phylogenetic analyses of the genome and encoded protein sequences revealed that the new virus is closely related to phasey bean mild yellows virus, CPPV2 and siratro latent polerovirus. Subsequently, we demonstrated the infectivity of SbCLRV in Nicotiana benthamiana via infectious cDNA clone generation and agroinoculation.

The analysis of severity causality for traffic crash is essential for enhancing the crash rescue responding speed, thereby reducing the casualties and property losses caused by roadway crashes. This study constructs a severity causation network to explore the relationship between risk factors and crash severity by combining information entropy and Bayesian network. The impacts of different risk factors on the severity indexes are quantitatively estimated and compared by utilizing entropy weight method, and the key factors for severity prediction are determined by considering both the weight and the accessibility. Then, the severity indexes, i.e., the number of injuries, fatalities, and the amount of property damage, are predicted with the selected key factors based on Bayesian parameter learning. The verification results confirm that compared with severity prediction utilizing all the risk factors, the prediction utilizing selected key factors do not lead to obviously precision loss. Moreover, it significantly enhances the feasibility of crash severity prediction. Due to the appropriate abbreviation of risk factors, the prediction efficiency and practical operability in crash rescue responding is improved. The findings can be utilized in analyzing the severity causation of traffic crashes, which is serviceable for managers to find effective measures to improve traffic safety as well as reduce the casualties and property losses caused by traffic crashes. By providing the severity causation network, this study facilitates the prediction of severity level, which can provide valuable reference information for a crash response.

A NbTiHfZr high-entropy alloy (HEA) with a main phase of body-centered cubic structure is fabricated. Some hexagonal closed-packed (hcp) precipitates are observed in this alloy. A thermal-mechanical process, i.e., cold-rolling followed by annealing, can manipulate the volume fraction of the hcp nano-precipitates that can enhance strength and ductility. The enhancement is tailorable as a function of the volume fraction of the hcp nano-precipitate. The results indicate that the strength-ductility property can be manipulated via adjusting post-deformation heat-treatment methods, which provide a new strategy by utilizing metastability at high-temperature to design high strength refractory HEAs (RHEAs) without lost in ductility.

To address the problem of poor efficacy in hybrid learning in higher education, this study conducted a mix-method explanatory case study with structural equation modelling to examine a new construct, "perceived pedagogical value" (PPV), and its relationship with the core constructs of the Unified Theory of Acceptance and Use of Technology (UTAUT) model. This study recruited 246 undergraduate students from a year 2 computer science course at an English Medium Instruction University in China to investigate their perceptions of using JazzQuiz for interactive hybrid learning using an online survey and semi-structured interviews. One of the key findings suggests that students who have a deeper understanding of technology's pedagogical value (i.e. higher PPV) are more likely to accept and use the technology with reduced efforts through five dimensions. Our contribution to the literature is threefold: (1) the new construct, PPV, extends our understanding of the UTAUT model for interactive hybrid learning; (2) the extended model highlights the role of student PPV in improving learning efficacy; (3) the five dimensions of how PPV influences technology acceptance, and student academic performance clarify the underlying mechanisms of effective interactive hybrid learning. Further studies are needed to test the new model in different contexts.

The effects of cryogenic temperature on the toughness of a Zr-based metallic glass are investigated. Based on three-dimensional fracture morphologies at different temperatures, the crack formation and propagation are analyzed. Through the calculation of the shear transformation zone volume, the shear modulus and bulk modulus of the metallic glass at different temperatures and the crack formation mechanism associated with the temperature is discussed. Once the crack commences propagation, the hyperelasticity model is used to elucidate the fractographic evolution of crack propagation.

BACKGROUND: Many clinicians do not encourage breastfeeding in hepatitis B virus (HBV) carriers, since HBV DNA can be detected in breast milk and breast lesions may increase exposure of infants to HBV. The aim of this study was to determine whether breastfeeding may add risk for perinatal HBV transmission. METHODOLOGY/PRINCIPAL FINDINGS: Totally 546 children (1-7-year-old) of 544 HBV-infected mothers were investigated, with 397 breastfed and 149 formula-fed; 137 were born to HBeAg-positive mothers. All children had been vaccinated against hepatitis B but only 53.3% received hepatitis B immune globulin (HBIG). The overall prevalence of HBsAg+, HBsAg-/anti-HBc+, and anti-HBs (≥10 mIU/ml) in children was 2.4%, 3.1%, and 71.6% respectively. The HBsAg prevalence in breast- and formula-fed children was 1.5% and 4.7% respectively (P = 0.063); the difference was likely due to the higher mothers' HBeAg-positive rate in formula-fed group (formula-fed 49.0% vs. breastfed 15.9%, P

The investigation of a columnar to equiaxed transition (CET) and grain refinement is of high commercial importance for the improvement of the solidification structure of metal castings. The crystal rain from the free surface is frequently generated to produce grain refinement and promote a CET in alloys under the application of electromagnetic fields. However, the mechanism underlying the CET influenced by the generated crystal rain is not clear because the employed metallic alloys are opaque. In the present paper, the crystal rain in a transparent NH4Cl–H2O solution is produced by blowing a cooled nitrogen gas on the free surface to observe in situ its impact on the occurrence of a CET. The results show that the crystal rain can significantly promote a CET even in a high temperature gradient and that a CET only can occur when the temperature gradient is almost close to zero in the reference experiment. Finally, the most likely mechanism is discussed and clarified.