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The advanced prostate biopsy robot system has broad application prospects in clinical practice, but due to the deformation and distortion between MR-TRUS (magnetic resonance transrectal ultrasound) images, it poses challenges in biopsy accuracy and safety. The study utilized an advanced prostate biopsy robot system based on MR-TRUS image flexible registration technology and conducted experiments on animal models. Retrospective analysis of the puncture accuracy of 12 animal experiments undergoing prostate puncture using MR-TRUS flexible registration technology from May 2022 to October 2023, and observation of intraoperative and 7-day postoperative complications. The study obtained MR-TRUS images and utilized image processing algorithms for registration to reduce image deformation and distortion. Then, precise positioning and operation are carried out through the robot system to execute the prostate biopsy program. The experimental results indicate that the advanced prostate biopsy robot system based on MR-TRUS image flexible registration technology has demonstrated good feasibility and safety in animal experiments. Image registration technology has successfully reduced image distortion and deformation, improving biopsy accuracy. The precise positioning and operation of robot systems play a crucial role in the biopsy process, reducing the occurrence of complications.

As a by-product of oil extraction, walnut meal was often used as feed or discarded, resulting in a waste of a large amount of high-quality protein resources. In this paper, for the high-value utilization of walnut meal resources, the highest content of glutelin was used as raw material to prepare walnut glutelin bacteriostatic peptide by solid-state fermentation with Bacillus subtilis and alkaline protease. The polypeptide content and the diameter of the inhibition zone of Staphylococcus aureus were used as the response values to optimize the optimal bacterial enzyme synergistic solid-state fermentation process parameters by single factor test. and response surface test. The thermal stability of the prepared glutelin bacteriostatic peptide was investigated. The results showed that the single factor test showed that the glutelin bacteriostatic peptide had a certain inhibitory effect on Escherichia coli and Staphylococcus aureus. The optimal fermentation process parameters under the response surface test were as follows: Inoculation amount 5%, solid-liquid ratio 1:1.5, fermentation temperature 43 ℃, fermentation time 3 d, and enzyme dosage 400 U/g. Under the optimal process conditions, the peptide content reached 26.35±1.29 mg/g, and the diameter of the inhibition zone against Staphylococcus aureus was 15.50±1.53 mm. Differential scanning calorimetry (DSC) analysis showed that glutelin antimicrobial peptides had higher thermal stability than glutelin. This study showed that the bacteriostatic peptide prepared by solid-state fermentation of walnut glutelin with enzyme has a good bacteriostatic effect and relatively stable structure.

Porcine circovirus type 2 (PCV2) has been recognized as a critical pathogen associated with numerous porcine circovirus-related diseases. Immunization is commonly regarded as the most efficient method to combat PCV2 infection. The virus's main antigen is the Cap protein, which is encoded by the ORF2 gene. In this investigation, we cloned the PCV2 Cap gene into the pYA3681 plasmid and subsequently electrotransferred it into the delayed lysis Salmonella strain χ11802, ultimately generating the χ11802 (pYA3681-Cap) vaccine candidate strain. We assessed the levels of sIgA and IgG specific to the Cap protein in mice, revealing that their mucosal and humoral immunity had been activated by χ11802 (pYA3681-Cap). The result was a substantial elevation in antibody levels, and a notable reduction in viral load in the immunized group compared to the unvaccinated group. Furthermore, the study revealed a significant decrease in the viral load in the lungs, liver, and spleen of mice inoculated with χ11802 (pYA3681-Cap), in comparison to both the empty carrier group and the phosphate buffered saline control group. This study further investigated the lytic effect of the delayed lysis vaccine vector. The χ11802 (pYA3681-EGFP) strain was undetectable 10 days post-challenge, indicating that the vaccine strain can effectively release the carried exogenous antigen and prevent the residual vaccine strain from spreading and causing pollution in the environment. A successful construction of the χ11802 (pYA3681-Cap) strain expressing the PCV2 Cap protein was executed in this study. To summarize, our study suggests that PCV2-Cap, when expressed in the delayed lysis Salmonella strain χ11802, could serve as a safe and economically efficient candidate PCV2 vaccine.

Drought has exerted significant impacts on terrestrial ecosystems and reduction in vegetation biomass through its unfavorable effects on vegetation growth status, and directly causing the degradation and death of vegetation. Therefore, investigating the response mechanisms of various vegetation types to drought is of great importance for vegetation resource conservation and sustainable development. In this study, based on the Vegetation Health Index (VHI) and Standardized Precipitation Evapotranspiration Index (SPEI), the dynamic changes and response relationships were revealed between vegetation and drought in Inner Mongolia (IM) during 1982–2020. Additionally, the fluctuation patterns of vegetation during drought events were identified. The results demonstrated that: (1) the probability of seasonal change point occurrence in VHI was 62.73 % in April 2018, with a confidence interval ranging from March 2014 to May 2019; (2) the identified optimal copula model was the Gaussian-copula for the duration and severity of drought events in IM; (3) the maximum and minimum percentages of degraded vegetation in IM occurred in January (74.32 %) and October (53.86 %); and (4) the cumulative lag-time of vegetation response to drought varied among different sub-regions, with response times ranging from 4 to 5 months. This finding provide a new perspective for elucidating the impact of drought variations on vegetation dynamics, which have positive implications for vegetation protection and ecological environment management.

Abstract The forming limit diagram plays an important role in predicting the forming limit of sheet metals. Previous studies have shown that, the method to construct the forming limit diagram based on instability theory of the original shear failure criterion is effective and simple. The original shear instability criterion can accurately predict the left area of the forming limit diagram but not the right area. In this study, in order to improve the accuracy of the original shear failure criterion, a modified shear failure criterion was proposed based on in-depth analysis of the original shear failure criterion. The detailed improvement strategies of the shear failure criterion and the complete calculation process are given. Based on the modified shear failure criterion and different constitutive equations, the theoretical forming limit of TRIP780 steel and 5754O aluminum alloy sheet metals are calculated. By comparing the theoretical and experimental results, it is shown that proposed modified shear failure criterion can predict the right area of forming limit more reasonably than the original shear failure criterion. The effect of the pre-strain and constitutive equation on the forming limits are also analyzed in depth. The modified shear failure criterion proposed in this study provides an alternative and reliable method to predict forming limit of sheet metals.

Abstract Papillary thyroid carcinoma (PTC) is the most common endocrine malignancy with a rapidly increasing incidence. The pathogenesis of PTC is unclear, but metabolic and lipidomic reprogramming may play a role in tumor growth. We applied ultra-performance liquid chromatography-tandem mass spectrometry to perform widely targeted metabolomics and lipidomics on plasma samples from 94 patients with PTC and 100 healthy controls. We identified 113 differential metabolites and 236 differential lipids, mainly involved in branched-chain amino acid metabolism, glutamate and glutamine metabolism, tricarboxylic acid cycle, and lipid metabolism. We also screened three potential metabolite biomarkers: sebacic acid, L-glutamine, and indole-3-carboxaldehyde. These biomarkers showed excellent diagnostic performance for PTC in both discovery and validation cohorts, with areas under the receiver operating characteristic curves of 0.994 and 0.925, respectively. Our findings reveal distinct metabolic and lipidomic features of PTC and provide novel targets for diagnosis and treatment.

The spatiotemporal continuity characteristics of drought are the basis for analyzing its spatial migration and evolution, which is significant for mitigation and early warning of drought. The aim of this paper is to identify meteorological and vegetation drought events in China from 1982 to 2022, reveal the dynamic changes of typical drought events, and elucidate the propagation characteristics of meteorological and vegetation drought. The results showed that (1) based on a three-dimensional spatiotemporal clustering algorithm, China experienced 138 meteorological drought events and 76 vegetation drought events; (2) the severity of the meteorological drought event No. M138 (2022.03–2022.11) reached 667.58 × 104 km2·month, and the severity of the vegetation drought event No. V68 (2019.06–2020.04) reached 572.89 × 104 km2·month; (3) a total of 40 meteorological-vegetation drought event pairs had been identified, which was divided into three main types: “single”, “simple”, and “complexity”; and (4) in the typical drought event pair No. P-34, the area difference was 16.45 × 104 km2, and the severity difference was 3.89 × 104 km2. The research results can provide a new perspective for identifying the dynamic changes and propagation characteristics of drought events from a three-dimensional perspective, which is of great significance for predicting vegetation drought and protecting the ecological environment.

Drought is a complex and recurrent natural disaster that can have devastating impacts on economies, societies, and ecosystems around the world. In light of climate change, the frequency, duration, and severity of drought events worldwide have increased, and extreme drought events have caused more severe and irreversible damage to terrestrial ecosystems. Therefore, estimating the resilience of different vegetation to drought events and vegetation’s response to damage is crucial to ensuring ecological security and guiding ecological restoration. Based on meteorological and remote-sensing datasets from 1982 to 2022, the spatial distribution characteristics and temporal variability of vegetation were identified in the Yellow River Basin (YRB), the dynamic changes and recurrence periods of typical drought events were clarified, and the driving effects of different drought types on vegetation were revealed. The results indicated that (1) during the research period, the standardized vegetation water-deficit index (SVWI) showed a downward trend in the YRB, with a 99.52% probability of abrupt seasonal changes in the SVWI occurring in January 2003; (2) the characteristic values of the grid trend Zs were −1.46 and 0.20 in winter and summer, respectively, indicating a significant downward trend in the winter SVWI; (3) the drought with the highest severity (6.48) occurred from September 1998 to February 1999, with a recurrence period of 8.54 years; and (4) the growth of vegetation was closely related to drought, and as the duration of drought increased, the sensitivity of vegetation to drought events gradually weakened. The research results provide a new perspective for identifying vegetation’s dynamic changes and responses to drought, which is of great significance in revealing the adaptability and potential influencing factors of vegetation in relation to climate.

Background and objective Lung large cell neuroendocrine carcinoma (LCNEC) is a rare and highly malignant lung tumor with a poor prognosis. Currently, most research on LCNEC is based on retrospective studies and lacks validation in the real world. The study aims to identify independent risk factors and establish and validate a predictive model for the prognosis of LCNEC. Methods Patient data were extracted from Surveillance, Epidemiology, and End Results (SEER) and our department's hospitalization records from 2010 to 2015 and 2016 to 2020, respectively. Kaplan-Meier analysis was used to evaluate overall survival (OS). OS is defined as the time from diagnosis to death or last follow-up for a patient. Univariate and multivariate Cox regression analyses were performed to identify significant prognostic factors and construct a Nomogram for predicting the prognosis of LCNEC. Results In total, 1892 LCNEC patients were included and divided into a training cohort (n=1288) and two validation cohorts (n=552, n=52). Univariate Cox regression analysis showed that age, gender, primary tumor site, laterality, T stage, N stage, M stage, surgery, and radiotherapy were factors that could affect the prognosis of LCNEC patients (P

Abstract Background Atherosclerosis (AS) is a common frequently-occurring disease in the clinic and a serious threat to human health. This research aimed to explore the value between GASL1 and AS. Methods The expression and values of GASL1 in AS patients were revealed by qRT-PCR and ROC curve. The HUVEC cells were induced by ox-LDL to construct in-vitro models. Cell viability was detected by MTT assay, and apoptosis was detected by flow cytometry. The inflammatory situation was reflected by the ELISA assay. Double luciferase reporter gene assay verified the regulatory relationship between GASL1 and miR-106a, miR-106a and LKB1. Results The levels of GASL1 was lower in AS group than those in control group. The value of GASL1 in predicting AS patients was also tested by the ROC curve. After HUVEC cells were induced by ox-LDL, the levels of GASL1 and LKB1 decreased significantly, while the level of miR-106a increased significantly. Upregulation of LKB1 reversed the effect of upregulation of GASL1 on viability, apoptosis, and inflammation of HUVEC cells induced by ox-LDL. Conclusion Overexpression of GASL1 might suppress ox-LDL-induced HUVEC cell viability, apoptosis, and inflammation by regulating miR-106a/LKB1 axis.

To promote the comprehensive utilization of solid waste in highway engineering, asphalt rubber hot mixture (ARHM-13) was prepared with steel slag and SBS/CR modified asphalt. The pavement performance of steel slag and basalt asphalt mixtures, including Marshall stability, moisture susceptibility, high temperature and low temperature performance, were evaluated in the laboratory. Combined with the project case of the trial pavement section in Beijing-Qinhuangdao Expressway, and the compactness, flatness, skid resistance and seepage resistance of the asphalt pavements were tested. And volatile organic compounds (VOCs) emissions and economic performance of asphalt mixtures were analyzed. The results showed that steel slag asphalt mixture reveals more excellent pavement performance than basalt asphalt mixture. The compactness, skid resistance and anti-seepage performance of asphalt mixture with steel slag are superior than basalt in contrast to the surface flatness. The VOCs emission concentrations of the steel slag asphalt mixture during mixing plant, spreading and rolling are higher than that of basalt asphalt mixture. Replacing basalt with steel slag can reduce by about 56.7% of aggregate cost and increase by 6.2% of asphalt cost. The total cost of raw materials for 1 km asphalt mixture with steel slag is reduced by about 10.5%. The research conclusion of this study provides the theoretical support for the promotion and utilization of steel slag and crumb rubber in road engineering.

The data-driven phenomenological models based on deformation measurements have been widely utilized to predict the slope failure time (SFT). The observational and model uncertainties could lead the predicted SFT calculated from the phenomenological models to deviate from the actual SFT. Currently, very limited study has been conducted on how to evaluate the effect of such uncertainties on SFT prediction. In this paper, a comprehensive slope failure database was compiled. A Bayesian machine learning (BML)-based method was developed to learn the model and observational uncertainties involved in SFT prediction, through which the probabilistic distribution of the SFT can be obtained. This method was illustrated in detail with an example. Verification studies show that the BML-based method is superior to the traditional inverse velocity method (INVM) and the maximum likelihood method for predicting SFT. The proposed method in this study provides an effective tool for SFT prediction.

Thiol–yne coupling is a reliable method to link two molecular units, but has not been extensively explored for the construction of macrocycles. Here, the authors use gaseous acetylene, the simplest alkyne unit, to synthesize a variety of macrocycles under photocatalytic conditions.

The continental shale oil resource in China exhibits significant potential and serves as a crucial strategic alternative to the country’s conventional oil and gas reserves. The efficacy of shale oil exploration and production is heavily contingent upon the heterogeneity of the pore structure within the reservoir. However, there remains a scarcity of research pertaining to the pore structure of continental shale and the factors that influence it. The objective of this study is to provide a quantitative characterization of the heterogeneity exhibited by the continental shale of the Funing Formation in the Gaoyou Sag. In this study, the research focus is directed toward the continental shale of the Funing Formation located in the Gaoyou Sag of the Subei Basin. This paper examines the correlation between the fractal dimension of nuclear magnetic resonance (NMR) and various factors including the total organic carbon (TOC), mineral composition, geochemical parameters, and physical properties, utilizing the principles of fractal dimension theory. The findings indicate that the primary pore types observed in the Funing Formation continental shale are inorganic matrix pores, which encompass dissolution pores, clay mineral intergranular pores, and a limited number of pyrite intergranular pores. By employing a relaxation time cutoff, the NMR fractal dimension can be categorized into two distinct dimensions: the bound-fluid-pore fractal dimension (0.5795~1.3813) and the movable-fluid-pore fractal dimension (2.9592~2.9793). The correlation between mineral composition and the fractal dimension indicates a negative relationship between the fractal dimensions of bound-fluid pores and movable-fluid pores and the content of quartz. The correlation between clay minerals and the fractal dimension indicates a significant negative relationship between the fractal dimensions of bound-fluid pores and movable-fluid pores with illite. There exists a negative correlation between the pore fractal dimension of bound fluid and the content of organic matter, whereas a positive correlation is observed between the pore fractal dimension of mobile fluid and the content of organic matter. The range of maturity of organic matter within the Funing Formation exhibits a relatively limited span, as indicated by the vitrinite reflectance (Ro) values falling between 0.8% and 0.9%. This narrow range of maturity does not exert a substantial influence on the two fractal dimensions. The NMR fractal dimension exhibits a negative correlation with permeability in relation to reservoir physical properties, while the bound-fluid-pore fractal dimension demonstrates a negative correlation with the total porosity. The findings suggest that the NMR fractal dimension can serve as a valuable indicator for evaluating the physical characteristics of reservoirs. The present study successfully examined the pore structure of continental shale through the utilization of nuclear magnetic resonance technology. This innovative technique provides a novel avenue for the assessment of continental shale reservoirs and the investigation of pore heterogeneity on a global scale.

Grinding robots are widely used in the automotive, mechanical processing, aerospace industries, among others, due to their strong adaptability, high safety and intelligence. The grinding process parameters are the main factors that affect the quality and efficiency of grinding robots. However, it is difficult to obtain the optimal combination of the grinding process parameters only by manual experience. This study proposes an artificial intelligence-based method for optimizing the process parameters of a grinding robot using neural networks and a genetic algorithm, with the aim to reduce the workpiece surface roughness and shorten the grinding time. Specifically, this is the first study utilizing a multi-objective optimization approach to optimize the process parameters of a grinding robot. Based on the experimental data of the grinding robot ROKAE XB7, the long short-term memory (LSTM) and multilayer perceptron (MLP) neural networks were trained to fit the quantitative relationships between the process parameters of the grinding robot, such as feed rate, spindle pressure and pneumatic motor pressure, and the result of grinding surface roughness and grinding time. After that, the non-dominated sorting genetic algorithm II (NSGA-II) was used to calculate the Pareto optimal process parameter combinations using the trained LSTM and MPL model as the objective function. Compared with the method based on manual experience, the process parameters optimized with this method achieved a reduction in surface roughness of at least 13.62% and a reduction in the whole grinding process time of 28%. The excellent grinding results obtained for grinding time and surface roughness validated the feasibility and efficiency of the proposed multi-objective method for the optimization of grinding robots’ process parameters in practical manufacturing applications.

This paper considers the active fault isolation problem for a class of uncertain multimode fault systems with a high-dimensional state-space model. It has been observed that the existing approaches in the literature based on a steady-state active fault isolation method are often accompanied by a large delay in making the correct isolation decision. To reduce such fault isolation latency significantly, this paper proposes a fast online active fault isolation method based on the construction of residual transient-state reachable set and transient-state separating hyperplane. The novelty and benefit of this strategy lies in the embedding of a new component called the set separation indicator, which is designed offline to distinguish the residual transient-state reachable sets of different system configurations at any given moment. Based on the results delivered by the set separation indicator, one can determine the specific moments at which the deterministic isolation is to be implemented during online diagnostics. Meanwhile, some alternative constant inputs can also be evaluated for isolation effects to determine better auxiliary excitation signals with smaller amplitudes and more differentiated separating hyperplanes. The validity of these results is verified by both a numerical comparison and an FPGA-in-loop experiment.

BackgroundThyroid carcinoma is one of the most common endocrine tumors, and papillary thyroid carcinoma (PTC) is the most common pathological type. Current studies have reported that PTC has a strong propensity for central lymph node metastases (CLNMs). Whether to prophylactically dissect the central lymph nodes in PTC remains controversial. This study aimed to explore the risk factors and develop a predictive model of CLNM in PTC.MethodsA total of 2,554 patients were enrolled in this study. The basic information, laboratory examination, characteristics of cervical ultrasound, genetic test, and pathological diagnosis were collected. The collected data were analyzed by univariate logistic analysis and multivariate logistic analysis. The risk factors were evaluated, and the predictive model was constructed of CLNM.ResultsThe multivariate logistic analysis showed that Age (p < 0.001), Gender (p < 0.001), Multifocality (p < 0.001), BRAF (p = 0.027), and Tumor size (p < 0.001) were associated with CLNM. The receiver operating characteristic curve (ROC curve) showed high efficiency with an area under the ROC (AUC) of 0.781 in the training group. The calibration curve and the calibration of the model were evaluated. The decision curve analysis (DCA) for the nomogram showed that the nomogram can provide benefits in this study.ConclusionThe predictive model of CLNM constructed and visualized based on the evaluated risk factors was confirmed to be a practical and convenient tool for clinicians to predict the CLNM in PTC.

The conventional theoretical forming limit diagram (FLD) based on the plane stress state has defects due to the neglect of the stress in the thickness direction of the sheet. It is urgent to study the FLD which considers the stress in the thickness direction. Through the finite element simulation, it is further confirmed that the stress in the thickness direction will be induced in the deformation process. At the same time, the effect of the induced stress in the thickness direction on FLD is not the same as that always applied stress in the thickness direction during the deformation process. Based on the Modified Maximum Force Criterion (MMFC) instability theory, C-H instability theory, Mises and Hill48 yield criterion, the effects of the two stresses on FLD are compared. The induced stress in the thickness direction also affects the sensitivity of the coefficient of normal anisotropy r, but does not significantly change the effect of the stress-strain index n on Forming Limit Curves (FLC). The theoretical calculations of the three materials TRIP780, AA5182, and 5754O are compared with the experimental data, which proves that the FLD which considers induced stress in the thickness direction is more accurate than the FLD of the plane stress.

Few researchers have studied the diagnostic value of inflammation-related hematological indexes of pediatric thyroid carcinoma exclusively. Whether thyroid-stimulating hormone (TSH) is an independent risk factor for pediatric thyroid cancer is still controversial. To assess the correlativity and predictive values of inflammation-related markers and thyroid function in pediatric thyroid cancer patients, we collected a total of 270 children with thyroid nodules for two consecutive years. Clinical data including age, gender, thyroid function, inflammation indexes, and clinical pathologic finding were collected and analyzed. The above-mentioned data were compared between the benign group and the malignant group, followed by the subgroups comparison. Binary logistic regression analysis was used to evaluate the correlation of markers and the pathological features of thyroid nodules. The neutrophil-to-lymphocyte ratio (NLR) showed a significant difference between thyroid cancer and thyroid nodules, while TSH did not. NLR > 1.49529 was the prognostic indicator of pediatric thyroid cancer. The logistic regression model further revealed that NLR > 1.49529 was an independent risk factor for thyroid cancer in pediatric patients. Furthermore, TSH was not correlated with the tumor characteristics in the thyroid cancer group. In conclusion, the findings in this study showed that NLR could be a predictor of thyroid cancer in pediatric patients and refuted the present view that TSH is a risk factor in pediatric thyroid cancer.

To lessen the spread of COVID-19 and other dangerous bacteria and viruses, contactless distribution of different items has gained widespread popularity. In order to complete delivery tasks at a catering facility, this paper explores the development of an autonomous mobile robot. The robot, in particular, plans its path and maintains smooth and flexible mobility using a Time Elastic Band (TEB) motion control method and an upgraded Dijkstra algorithm. On the open-source AI platform of iFLYTEK, a voice recognition module was trained to recognize voice signals of different tones and loudness, and an image recognition capability was attained using YOLOv4 and SIFT. The UCAR intelligent vehicle platform, made available by iFLYTEK, served as the foundation for the development of the mobile robot system. The robot took part in China’s 16th National University Student Intelligent Car Race, an experimental demonstration test of the developed mobile robotics. The results of the experiments and task tests demonstrated that the proposed robot architecture was workable. In addition, we designed and put together a mobile robot utilizing components from the Taobao website. Compared to UCAR, this robot is less expensive and has the flexibility to be used in a variety of real-world settings.

A new active fault tolerant control scheme based on active fault diagnosis is proposed to address the component/actuator faults for systems with state and input constraints. Firstly, the active fault diagnosis is composed of diagnostic observers, constant auxiliary signals, and separation hyperplanes, all of which are designed offline. In online applications, only a single diagnostic observer is activated to achieve fault detection and isolation. Compared with the traditional multi-observer parallel diagnosis methods, such a design is beneficial to improve the diagnostic efficiency. Secondly, the active fault tolerant control is composed of outer fault tolerant control, inner fault tolerant control and a linear-programming-based interpolation control algorithm. The inner fault tolerant control is determined offline and satisfies the prescribed optimal control performance requirement. The outer fault tolerant control is used to enlarge the feasible region, and it needs to be determined online together with the interpolation optimization. In online applications, the updated state estimates trigger the adjustment of the interpolation algorithm, which in turn enables control reconfiguration by implicitly optimizing the dynamic convex combination of outer fault tolerant control and inner fault tolerant control. This control scheme contributes to further reducing the computational effort of traditional constrained predictive fault tolerant control methods. In addition, each pair of inner fault tolerant control and diagnostic observer is designed integratedly to suppress the robust interaction influences between estimation error and control error. The soft constraint method is further integrated to handle some cases that lead to constraint violations. The effectiveness of these designs is finally validated by a case study of a wastewater treatment plant model.