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Abstract. Objectives. This study aimed to evaluate the performance of prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT) in comparison to multiparametric magnetic resonance imaging (mpMRI) for detecting biochemical recurrence of prostate cancer (PCa). Materials and methods. We conducted a comprehensive search for articles published in PubMed, Web of Science, Embase, and the Cochrane Library, spanning the inception of the database until October 26, 2022, which included head-to-head comparisons of PSMA PET/CT and mpMRI for assessing the biochemical recurrence of PCa. Results. A total of 5 studies including 228 patients were analyzed. The overall positivity rates of PSMA PET/CT and mpMRI for detecting biochemical recurrence of PCa after final treatment were 0.68 (95% confidence interval [CI], 0.52–0.89) and 0.56 (95% CI, 0.36–0.88), respectively. The positivity rates of PSMA PET/CT and mpMRI for detecting local recurrence, lymph node metastasis, and bone metastases were 0.37 (95% CI, 0.30–0.47) and 0.38 (95% CI, 0.22–0.67), 0.44 (95% CI, 0.35–0.56) and 0.25 (95% CI, 0.17–0.35), and 0.19 (95% CI, 0.11–0.31) and 0.12 (95% CI, 0.05–0.25), respectively. Compared with mpMRI, PSMA PET/CT exhibited a higher positivity rate for detecting biochemical recurrence and lymph node metastases, and no significant difference in the positivity rate of local recurrence was observed between these 2 imaging modalities. Conclusions. Compared with mpMRI, PSMA PET/CT appears to have a higher positivity rate for detecting biochemical recurrence of PCa. Although both imaging methods showed similar positivity rates of detecting local recurrence, PSMA PET/CT outperformed PSMA PET/CT in detecting lymph node involvement and overall recurrence.

Abstract Purpose To verify the effect and mechanism of baicalein in the treatment of periodontitis through network pharmacology, molecular docking and in vitro experiments. Methods Firstly, multiple databases were used to predict targets of baicalein and periodontitis. And the screened key target genes of baicalein for treating periodontitis were subjected to GO and KEGG analysis; then these targets were analyzed by molecular docking techniques. In vitro experiments including CCK-8, RT-qPCR, ELISA and Immunofluorescence were conducted to validate the efficacy of baicalein in treating periodontitis. Results Seventeen key targets were screened from the databases, GO and KEGG analysis of these targets revealed that baicalein may exert therapeutic effects through regulating TNF, PI3K-Akt, HIF-1 and other signaling pathways. Molecular docking analysis showed that baicalein has good binding potential to several targets. In vitro cellular assays showed that baicalein inhibited the expression of TNF-α, MMP-9, IL-6 and MCP1 in P.g-LPS-induced macrophages at both the mRNA and protein level. And the immunofluorescence intensity of iNOS, a marker of M1 type macrophages, which mainly secretes inflammatory factors, was significantly reduced. Conclusion Baicalein has the characteristics and advantages of “multicomponent, multitarget, and multipathway” in the treatment of periodontitis. In vitro cellular assays further confirmed the inhibitory effect of baicalein on the secretion of inflammatory factors of macrophages in periodontitis models, providing a theoretical basis for further study of the material basis and molecular mechanism of baicalein in the treatment of periodontal diseases.

Abstract Background Early childhood caries (ECC) is a challenge for pediatric dentists all over the world, and dietary factor is an important factor affecting the occurrence of ECC. Currently, there is limited research on the impact of dietary nutrient intake from Chinese diets on ECC. The purpose of this study is to explore the correlation of dietary nutrients intake with ECC and caries activity (CA) among children aged 3–5 years, and to provide dietary guidance to slow down the occurrence and development of ECC. Methods A cross-sectional study was conducted in 2022. A total of 155 children were divided into three groups: caries-free group, ECC group and Severe early childhood caries (SECC) group according to the caries statues. And according to the caries activity test (CAT) value, they were also divided into three group: low CA group (L-CA), middle CA group (M-CA) and high CA group (H-CA). The 24-hour dietary intake information was collected by mobile phone application (APP). The intake of children’s daily dietary nutrients were calculated referring to “China Food Composition Tables”. Results In this study, 17, 39,and 99 children were diagnosed with caries-free, ECC, and SECC. There were 33, 36, and 86 children diagnosed with L-CA, M-CA, and H-CA. The risk of ECC was increased with the intake of cholesterol(OR = 1.005) and magnesium (OR = 1.026) and decreased with the intake of iron (OR = 0.770). The risk of SECC was increased with the intake of cholesterol (OR = 1.003). The risk of high CA was increased with the intake of cholesterol (OR = 1.002). The combined application of dietary total calories, carbohydrate, cholesterol, sodium, magnesium and selenium in the diagnosis of ECC had an area under ROC curve of 0.741. Conclusions The increased dietary cholesterol intake may be a common risk factor for ECC and high CA in children aged 3–5. The combined application of dietary intake of total calories, carbohydrate, cholesterol, sodium, magnesium and selenium has a higher predictive value for the occurrence of ECC.

IntroductionPath planning algorithms are challenging to implement with mobile robots in orchards due to kinematic constraints and unstructured environments with narrow and irregularly distributed obstacles.MethodsTo address these challenges and ensure operational safety, a local path planning method for orchard mowers is proposed in this study. This method accounts for the structural characteristics of the mowing operation route and utilizes a path-velocity decoupling method for local planning based on following the global reference operation route, which includes two innovations. First, a depth-first search method is used to quickly construct safe corridors and determine the detour direction, providing a convex space for the optimization algorithm. Second, we introduce piecewise jerk and curvature restriction into quadratic programming to ensure high-order continuity and curvature feasibility of the path, which reduce the difficulty of tracking control. We present a simulation and real-world evaluation of the proposed method.ResultsThe results of this approach implemented in an orchard environment show that in the detouring static obstacle scenario, compared with those of the dynamic lattice method and the improved hybrid A* algorithm, the average curvature of the trajectory of the proposed method is reduced by 2.45 and 3.11 cm–1, respectively; the square of the jerk is reduced by 124 and 436 m2/s6, respectively; and the average lateral errors are reduced by 0.55 cm and 4.97 cm, respectively, which significantly improves the path smoothness and facilitates tracking control. To avoid dynamic obstacles while traversing the operation route, the acceleration is varied in the range of -0.21 to 0.09 m/s2. In the orchard environment, using a search range of 40 m × 5 m and a resolution of 0.1 m, the proposed method has an average computation time of 9.6 ms. This is a significant improvement over the open space planning algorithm and reduces the average time by 12.4 ms compared to that of the dynamic lattice method, which is the same as that of the structured environment planning algorithm.DiscussionThe results show that the proposed method achieves a 129% improvement in algorithmic efficiency when applied to solve the path planning problem of mower operations in an orchard environment and confirm the clear advantages of the proposed method.

IntroductionStudying the behavioral responses and movement trajectories of insects under different stimuli is crucial for developing more effective biological control measures. Therefore, accurately obtaining the movement trajectories and behavioral parameters of insects in three-dimensional space is essential.MethodsThis study used the litchi pest Thalassodes immissaria as the research object. A special binocular vision observation system was designed for nighttime movement. A thermal infrared camera was used for video recording of T. immissaria in a lightless environment. Moreover, a multi-object tracking method based on the YOLOX-GMM and SORT-Pest algorithms was proposed for tracking T. immissaria in thermal infrared images. By obtaining the central coordinates of the two T. immissaria in the video, target matching and 3D trajectory reconstruction in the parallel binocular system were achieved.ResultsError analysis of the T. immissaria detection and tracking model, as well as the 3D reconstruction model, showed that the average accuracy of T. immissaria detection reached 89.6%, tracking accuracy was 96.9%, and the average error of the reconstructed 3D spatial coordinates was 15 mm.DiscussionThese results indicate that the method can accurately obtain the 3D trajectory and motion parameters of T. immissaria. Such data can greatly contribute to researchers' comprehensive understanding of insect behavioral patterns and habits, providing important support for more targeted control strategies.

Abstract The optimal design of groundwater circulation wells (GCWs) is challenging. The key to purifying groundwater using this technique is its proficiency and productivity. However, traditional numerical simulation methods are limited by long modeling times, random optimization schemes, and optimization results that are not comprehensive. To address these issues, this study introduced an innovative approach for the optimal design of a GCW using machine learning methods. The FloPy package was used to create and implement the MODFLOW and MODPATH models. Subsequently, the formulated models were employed to calculate the characteristic indicators of the effectiveness of the GCW operation, including the radius of influence (R) and the ratio of particle recovery (Pr). A detailed collection of 3000 datasets, including measures of operational efficiency and key elements in machine learning, was meticulously compiled into documents through model execution. The optimization models were trained and evaluated using multiple linear regression (MLR), artificial neural networks (ANN), and support vector machines (SVM). The models produced by the three approaches exhibited notable correlations between anticipated outcomes and datasets. For the optimal design of circulating well parameters, machine learning methods not only improve the optimization speed, but also expand the scope of parameter optimization. Consequently, these models were applied to optimize the configuration of the GCW at a site in Xi’an. The optimal scheme for R (Q = 293.17 m3/d, a = 6.09 m, L = 7.28 m) and optimal scheme for Pr (Q = 300 m3/d, a = 3.64 m, L = 1 m) were obtained. The combination of numerical simulations and machine learning is an effective tool for optimizing and predicting the GCW remediation effect.

Abstract For expanding the amplitude-frequency response range of the differential cross-phase multiply (DCM) algorithm in the φ-OTDR system, a temporal spline interpolation (TSI) method is proposed to pre-process Rayleigh backscattering (RBS) signals. Through the TSI method, the discrete temporal signals characterizing RBS traces are subjected to interpolation, facilitating a reduction in differential approximation errors. This, in turn, establishes a heightened level of precision in phase demodulation, especially relevant across extensive sensing distances. By comparing the recovered time-domain waveforms and the corresponding power spectral densities without and with the TSI, the above improvement effect has been experimentally validated by utilizing the TSI. The results show that, with the TSI, the amplitude-frequency response range of the DCM algorithm is enlarged by 2.78 times, and the new relationship among f pulse, f, and D under the root mean square error (RMSE) tolerance less than 0.1 can be expressed as 1.9(D+1)f ≤ f pulse. This contribution underscores a substantial advancement in the capabilities of the DCM algorithm, holding promise for refined performance in optical fiber sensing applications.

Abstract Thyroid nodules are a common occurrence, and although most are non-cancerous, some can be malignant. The American College of Radiology has developed the Thyroid Imaging Reporting and Data System (TI-RADS) to standardize the interpretation and reporting of thyroid ultrasound results. Within TI-RADS, a category 4 designation signifies a thyroid nodule with an intermediate level of suspicion for malignancy. Accurate classification of these nodules is crucial for proper management, as it can potentially reduce unnecessary surgeries and improve patient outcomes. This study utilized deep learning techniques to effectively classify TI-RADS category 4 thyroid nodules as either benign or malignant. A total of 500 patients were included in the study and randomly divided into a training group (350 patients) and a test group (150 patients). The YOLOv3 model was constructed and evaluated using various metrics, achieving an 84% accuracy in the classification of TI-RADS category 4 thyroid nodules. Based on the predictions of the model, along with clinical and ultrasound data, a nomogram was developed. The performance of the nomogram was superior in both the training and testing groups. Furthermore, the calibration curve demonstrated good agreement between predicted probabilities and actual outcomes. Decision curve analysis further confirmed that the nomogram provided greater net benefits. Ultimately, the YOLOv3 model and nomogram successfully improved the accuracy of distinguishing between benign and malignant TI-RADS category 4 thyroid nodules, which is crucial for proper management and improved patient outcomes.

Kaposi's sarcoma-associated herpesvirus (KSHV) establishes persistent infection in the host by encoding a vast network of proteins that aid immune evasion. One of these targeted innate immunity pathways is the cGAS-STING pathway, which inhibits the reactivation of KSHV from latency. Previously, we identified multiple cGAS/STING inhibitors encoded by KSHV, suggesting that the counteractions of this pathway by viral proteins are critical for maintaining a successful KSHV life cycle. However, the detailed mechanisms of how these viral proteins block innate immunity and facilitate KSHV lytic replication remain largely unknown. In this study, we report that ORF48, a previously identified negative regulator of the cGAS/STING pathway, is required for optimal KSHV lytic replication. We used both siRNA and deletion-based systems to evaluate the importance of intact ORF48 in the KSHV lytic cycle. In both systems, loss of ORF48 resulted in defects in lytic gene transcription, lytic protein expression, viral genome replication and infectious virion production. ORF48 genome deletion caused more robust and global repression of the KSHV transcriptome, possibly due to the disruption of RTA promoter activity. Mechanistically, overexpressed ORF48 was found to colocalize and interact with endogenous STING in HEK293 cells. Endogenous ORF48 and STING interactions were also detected in reactivated iSLK.219 cells. Compared with the control cell line, HUVEC cells stably expressing ORF48 exhibited repressed STING-dependent innate immune signaling upon ISD or diABZI treatment. However, the loss of ORF48 in our iSLK-based lytic system failed to induce IFNβ production, suggesting a redundant role of ORF48 on STING signaling during the KSHV lytic phase. Thus, ORF48 is required for optimal KSHV lytic replication through additional mechanisms that need to be further explored.

Ultrasound-guided radiofrequency ablation (RFA) emerges as a minimally invasive strategy for papillary thyroid microcarcinoma (PTMC), offering advantages over traditional surgical approaches. RFA employs high-frequency electric currents under precise ultrasound guidance to ablate cancerous tissue. Clinical trials consistently demonstrate RFA’s efficacy in tumor control and patient-reported outcomes. However, long-term studies are essential to validate its durability and monitor for potential complications. Collaborative efforts among various medical disciplines ensure procedural accuracy and comprehensive postoperative care. Technological innovations, such as enhanced ultrasound imaging and temperature control, promise to refine RFA’s precision and effectiveness. Nevertheless, challenges persist, including the need for standardized protocols and comparative studies with traditional treatments. Future research should focus on long-term outcomes, patient selection criteria, and optimization of procedural techniques to solidify RFA’s role in PTMC management. RFA presents a promising avenue for PTMC treatment, warranting further investigation and refinement in clinical practice.

BackgroundIt is reported that the Ixeris chinensis has high medicinal value, but there are few reports about its potential molecular mechanism. We used a network pharmacology approach to predict the active ingredients, targets of action and possible interventions in diseases of Ixeris chinensis.MethodsWe employed various databases and software to predict the active ingredients, target genes, protein interactions, signaling pathways, network diagrams, and molecular docking of Ixeris chinensis. Simultaneously, we searched multiple Chinese and English databases and conducted meta-analyses of five randomized controlled trials.ResultsThe analysis results revealed 12 effective components, including apigenin β-sitosterol, baicalin, baicalein, and luteolin; and selected 40 key targets, including AKT1, TNF, EGFR, ESR1, SRC, among others. GO analysis generated 225 biological processes, 39 cellular components, and 65 molecular functions; KEGG analysis revealed 103 signaling pathways. Molecular docking results indicated that the main active components of Ixeris chinensis can bind well with key targets. Five randomized controlled trials were included. Meta-analysis showed that Ixeris extract can effectively reduce animal blood lipid levels.ConclusionThis study revealed the main active ingredients and key targets of Ixeris chinensis, analyzed the signaling pathways of potential targets, conducted disease prediction, and performed molecular docking prediction, providing a basis for research on the pathways of Ixeris treatment for related diseases and subsequent new drug development.

Abstract Acceleration of tooth movement during orthodontic treatment is challenging, with osteoclast-mediated bone resorption on the compressive side being the rate-limiting step. Recent studies have demonstrated that mechanoreceptors on the surface of monocytes/macrophages, especially adhesion G protein-coupled receptors (aGPCRs), play important roles in force sensing. However, its role in the regulation of osteoclast differentiation remains unclear. Herein, through single-cell analysis, we revealed that CD97, a novel mechanosensitive aGPCR, was expressed in macrophages. Compression upregulated CD97 expression and inhibited osteoclast differentiation; while knockdown of CD97 partially rescued osteoclast differentiation. It suggests that CD97 may be an important mechanosensitive receptor during osteoclast differentiation. RNA sequencing analysis showed that the Rap1a/ERK signalling pathway mediates the effects of CD97 on osteoclast differentiation under compression. Consistently, we clarified that administration of the Rap1a inhibitor GGTI298 increased osteoclast activity, thereby accelerating tooth movement. In conclusion, our results indicate that CD97 suppresses osteoclast differentiation through the Rap1a/ERK signalling pathway under orthodontic compressive force.

Abstract Facing to a planar tracking problem, a multiple-interpretable improved Proximal Policy Optimization (PPO) algorithm with few-shot technique is proposed, namely F-GBQ-PPO. Compared with the normal PPO, the main improvements of F-GBQ-PPO are to increase the interpretability, and reduce the consumption for real interaction samples. Considering to increase incomprehensibility of a tracking policy, three levels of interpretabilities has been studied, including the perceptual, logical and mathematical interpretabilities. Detailly speaking, it is realized through introducing a guided policy based on Apollonius circle, a hybrid exploration policy based on biological motions, and the update of external parameters based on quantum genetic algorithm. Besides, to deal with the potential lack of real interaction samples in real applications, a few-shot technique is contained in the algorithm, which mainly generate fake samples through a multi-dimension Gaussian process. By mixing fake samples with real ones in a certain proportion, the demand for real samples can be reduced.

In the digital age, the rapid growth of web information has made it increasingly challenging for individuals and organizations to effectively explore and extract valuable insights from the vast amount of information available. This paper presents a novel approach to automated web text summarization that combines advanced natural language processing techniques with recent breakthroughs in deep learning. we propose a dual-faceted technique that leverages extensive pre-training on a broad dataset outside the domain, followed by a unique refined tuning process. We introduce a carefully curated dataset that captures the heterogeneous nature of web articles and propose an innovative pre-training and tuning approach that establishes a new state-of-the-art in news summarization. Through extensive experiments and rigorous comparisons against existing models, we demonstrate the superiority of our method, particularly highlighting the crucial role of the refined tuning process in achieving these results. Through rigorous experimentation against state-of-the-art models, we demonstrate the superior performance of our approach, highlighting the significance of their refined tuning process in achieving these results.

This paper explores the evidentiary significance of blockchain records and the procedural implications of integrating this technology into the U.S. judicial system, as several states have undertaken legislative measures to facilitate the admissibility of blockchain evidence. We employ a comprehensive methodological approach, including legislative analysis, comparative case law analysis, technical examination of blockchain mechanics, and stakeholder engagement. Our study suggests that blockchain evidence may be categorized as hearsay exceptions or non-hearsay, depending on the specific characteristics of the records. The paper proposes a specialized consensus mechanism for standardizing blockchain evidence authentication and outlines strategies to enhance the technology’s trustworthiness. It also highlights the importance of expert testimony in clarifying blockchain’s technical aspects for legal contexts. This study contributes to understanding blockchain’s integration into judicial systems, emphasizing the need for a comprehensive approach to its admissibility and reliability as evidence. It bridges the gap between technology and law, offering a blueprint for standardizing legal approaches to blockchain and urging ethical and transparent technology use.

In plant horticulture, furrow fertilizing is a common method to promote plant nutrient absorption and to effectively avoid fertilizer waste. Considering the high resistance caused by soil compaction in southern orchards, an energy-saving ditching device was proposed. A standard ditching blade with self-excited vibration device was designed, and operated in sandy clay with a tillage depth of 30cm. To conduct self-excited vibration ditching experiments, a simulation model of the interaction between soil and the ditching mechanism was established by coupling the ADAMS and EDEM software. To begin with, the ditching device model was first set up, taking into account its motion and morphological characteristics. Then, the MBD-DEM coupling method was employed to investigate the interaction mechanism and the effect of ditching between the soil particles and the ditching blade. Afterwards, the time-domain and frequency-domain characteristics of vibration signals during the ditching process were analyzed using the fast fourier transform (FFT) method, and the energy distribution characteristics were extracted using power spectral density (PSD). The experimental results revealed that the vibrations ditching device has reciprocating displacement in the Dx direction and torsional displacements in the θy and θz directions during operation, verifying the correctness of the coupling simulation and the effectiveness of vibrations ditching resistance reduction. Also, a load vibrations ditching bench test was conducted, and the results demonstrated that the self-excited vibrations ditching device, compared with common ditching device, achieved a reduction in ditching resistance of up to 12.3%. The reasonable parameters of spring stiffness, spring damping, and spring quality in self-excited vibrations ditching device can achieve a satisfied ditching performance with relatively low torque consumption at an appropriate speed.

To simulate the creep characteristics of corn straw particles under uniaxial compression, a 6-level 2D model was created using PFC 2D software according to the actual uniaxial creep test, the grain size, and shape of corn straw particles. Five groups of controlled tests were designed by the control variable method to study the influence of Maxwell body parameters Em, ηm; Kelvin body parameters Ek, ηk; and friction coefficient f on the creep curve of Burgers model. Results revealed that the creep characteristics of corn straw are affected by these 5 parameters. After multiple debugging by trial-and-error method, simulation parameters suitable for describing the creep characteristics of corn straw particles were obtained. The creep curves obtained by simulation under these parameters are consistent with those obtained by physical tests. It was shown that PFC software can not only study the creep characteristics of geotechnical materials, but also study the creep characteristics of agricultural fiber materials, which provides a reference for the subsequent rheological characteristics of biomass materials.

Abstract The Baijigou Coal Mine in Helan mountain mining area is alpine gully landform, and the double key stratums are cut by the gully. A two-dimensional physical similarity model under this condition was established in the laboratory. The strain field, deformation field and pressure field of the model are jointly and accurately monitored by BOTDA, DIC and pressure sensors. The rock behavior in shallow coal seam mining under bedrock gullies are studied. In the mining stage under the gully, the deformation of overburden is intense because overburden is thin, and the surface is easy to form a depression basin. In the mining stage far away from the gully, the deformed rock mass lacks horizontal support in the process of deflecting to the lower goaf, and the movement rock is in a multilateral block. The multilateral block rock periodically deflects and rotates, resulting in the periodic deformation and break of the inferior key stratum. At the mining stage of away from the gully, nine times of roof weighting occurred. And there are large and small periodic weighting phenomenon with the average roof pressure concentration coefficient is 1.37. The distance between the peak point of advance abutment pressure and the coal wall is 6–18 cm, and the influence distance decreases with the advancing of the working face. The inferior key stratum has a significant impact on the weighting process and the weighting strength. In the mining stage under the mountaintop, large downward inclined tension crack is prone to produce in the slope on the side of the stope line, and the roof weighting is the most severe. In the mining stage close to the gully, the overburden falls in layers from bottom to top, and the overburden at the slope toe is prone to slip. At the mining stage under the mountaintop and close to the gully, five times of roof weighting occurred. And the roof weighting concentration coefficient is 1.46 on average. The distance between the peak point of advance abutment pressure and the coal wall is always kept at 6–16 cm, and the influence distance is 33–41 cm. The study can provide a reference for mining design and ensures safe and efficient mining in this condition.

This paper presents exploratory work on the use of Testing with Concept Activation Vectors (TCAV) within a concept-based explanation framework to provide the explainability of millimeter-wave (MMW) radar target recognition. Given that the radar spectrum is difficult for non-domain experts to understand visually, defining concepts for radar remains a significant challenge. In response, drawing from the visual analytical experience of experts, some basic concepts based on brightness, striping, size, and shape are adopted in this paper. However, the simplicity of basic concept definitions sometimes leads to vague correlations with recognition targets and significant variability among individuals, limiting their adaptability to specific tasks. To address these issues, this study proposes a Basic Concept-Guided Deep Embedding Clustering (BCG-DEC) method that can effectively discover task-specific composite concepts. BCG-DEC methodically analyzes the deep semantic information of radar data through four distinct stages from the perspective of concept discovery, ensuring that the concepts discovered accurately conform to the task-specific property of MMW radar target recognition. The experimental results show that the proposed method not only expands the number of concepts but also effectively solves the problem of difficulty in annotating basic concepts. In the ROD2021 MMW radar explainability experiments, the concepts proved crucial for recognizing specific categories of radar targets.

Coastal protection structures are essential defenses against wave energy, safeguarding coastal communities. This study aims to refine coastal protection strategies by employing a semicircular breakwater (SBW) model. Through a combination of physical and computational models, the hydrodynamic properties of the SBW under regular wave conditions were thoroughly examined. The primary objectives included delineating the hydrodynamic characteristics of SBWs, developing a computational model to validate experimental findings. Hydrodynamic characteristics of the SBW model were scrutinized across various wave conditions. Experimental testing in a wave flume covered a range of relative water depths (d/h) from 0.667 to 1.667, wave steepness (Hi/L) spanning 0.02 to 0.06 and wave periods ranging from 0.8 to 2.5 s. Notably, analysis of an emerged SBW with d/h = 0.667 revealed superior wave reflection, while an alternative submerged SBW with d/h = 1.000 showed the highest energy loss. These findings are further corroborated by the validation of computational models against experimental outcomes for d/h = 0.667, 1.000, 1.333 and 1.667. Moreover, the investigation of forces revealed an inverse correlation between horizontal forces and wave height, while vertical forces showed nuanced variations, including a slightly decreasing average vertical force with greater relative wave period (B/L) for different immersion scenarios.

The number of flowers is essential for evaluating the growth status of litchi trees and enables researchers to estimate flowering rates and conduct various phenotypic studies, particularly focusing on the information of individual panicles. However, manual counting remains the primary method for quantifying flowers, and there has been insufficient emphasis on the advancement of reliable deep learning methods for estimation and their integration into research. Furthermore, the current density map-based methods are susceptible to background interference. To tackle the challenges of accurately quantifying small and dense male litchi flowers, a framework counting the flowers in panicles is proposed. Firstly, an existing effective algorithm YOLACT++ is utilized to segment individual panicles from images. Secondly, a novel algorithm FlowerNet based on density map regression is proposed to accurately count flowers in each panicle. By employing a multitask learning approach, FlowerNet effectively captures both foreground and background information, thereby overcoming interference from non-target areas during pixel-level regression tasks. It achieves a mean absolute error of 47.71 and a root mean squared error of 61.78 on the flower dataset constructed. Additionally, a regression equation is established using a dataset of inflorescences to examine the application of the algorithm for flower counting. It captures the relationship between the predicted number of flowers by FlowerNet and the manually counted number, resulting in a determination coefficient (R2) of 0.81. The proposed algorithm shows promise for automated estimation of litchi flowering quantity and can serve as a valuable reference for litchi orchard management during flowering period.

The uneven spatial distribution of mineral resources necessitates the construction of mature global mineral governance system to ensure rational allocation of mineral resources. To this end, it is essential to analyze the structure of the global mineral governance system to provide a theoretical basis for the construction. The governance actor is the crucial element in driving the governance process, and country serves as the most central actor. Therefore, clarifying the roles and statuses of different countries in the governance system will be helpful to analyze the structure of the governance system. In the context of advancing globalization, a complex cooperative relationship has been presented between countries based on international organizations. Thus, we establish a national cooperation network based on the principle of the co-existence of countries in international organizations, to quantify these relationships between countries and identify the role and status of different countries, as well as the country communities in the cooperation network, by combining the characteristics of the countries in the network with the actual performance in the organizations. The research findings are as follow: (1) The UK, Germany, France, Sweden, and Canada play pivotal roles in promoting international cooperation as well as leading governance in the governance system. (2) Emerging economies are more actively engaged in these organizations and can promote international cooperation, but lack the capacity to assume leadership roles in governance. (3) The U.S. and China have a stronger ability to lead than to cooperate in the governance system. (4) Most African and South American countries, as well as some European nations, are marginalized in the governance system. (5) Countries with the same needs and similar economic and political conditions belong to the same community: The European countries and the U.S., consumer with a high level of economic and political development but low mineral resource endowment are in the first community. Canada, Australia, and certain African and South American countries, producers with high mineral resource endowments are in the second community. Most African and South American countries with lower levels of economic and political development are in the third group.

Summary: Prostate cancer (PCa) is one of the most common malignant diseases of urinary system and has poor prognosis after progression to castration-resistant prostate cancer (CRPC), and increased cytosine methylation heterogeneity is associated with the more aggressive phenotype of PCa cell line. Activation-induced cytidine deaminase (AID) is a multifunctional enzyme and contributes to antibody diversification. However, the dysregulation of AID participates in the progression of multiple diseases and related with certain oncogenes through demethylation. Nevertheless, the role of AID in PCa remains elusive. We observed a significant upregulation of AID expression in PCa samples, which exhibited a negative correlation with E-cadherin expression. Furthermore, AID expression is remarkably higher in CRPC cells than that in HSPC cells, and AID induced the demethylation of CXCL12, which is required to stabilize the Wnt signaling pathway executor β-catenin and EMT procedure. Our study suggests that AID drives CRPC metastasis by demethylation and can be a potential therapeutic target for CRPC.

Abstract Synthesis of capsular polysaccharide (CPS), an important virulence factor of pathogenic bacteria, is modulated by the CpsBCD phosphoregulatory system in Streptococcus. Serine/threonine kinases (STKs, e.g. Stk1) can also regulate CPS synthesis, but the underlying mechanisms are unclear. Here, we identify a protein (CcpS) that is phosphorylated by Stk1 and modulates the activity of phosphatase CpsB in Streptococcus suis, thus linking Stk1 to CPS synthesis. The crystal structure of CcpS shows an intrinsically disordered region at its N-terminus, including two threonine residues that are phosphorylated by Stk1. The activity of phosphatase CpsB is inhibited when bound to non-phosphorylated CcpS. Thus, CcpS modulates the activity of phosphatase CpsB thereby altering CpsD phosphorylation, which in turn modulates the expression of the Wzx-Wzy pathway and thus CPS production.

Existing data-driven object detection methods use the Constant False Alarm Rate (CFAR) principle to achieve more robust detection performance using supervised learning. This study systematically proposes a data-driven target detection framework based on the measured echo data from the ground early warning radar for low-altitude slow dim target detection. This framework addresses two key problems in this field: (1) aiming at the problem that current data-driven object detection methods fail to make full use of feature representation learning to exert its advantages, a representation learning method of echo temporal dependency is proposed, and two implementations, including unsupervised- and supervised-learning are given; (2) Low-altitude slow dim targets show extreme sparsity in the radar detection range, such unevenness of target-clutter sample scale causes the trained model to seriously tilt to the clutter samples, resulting in the decision deviation. Therefore, we further propose incorporating the data balancing policy of abnormal detection into the framework. Finally, ablation experiments are performed on the measured X-band echo data for each component in the proposed framework. Experimental results completely validate the effectiveness of our echo temporal representation learning and balancing policy. Additionally, under real sequential validation, our proposed method achieves comprehensive detection performance that is superior to multiple CFAR methods.

To regulate the energy flow in orchard ecosystems and maintain the environment, weeding has become a necessary measure for fruit farmers, and the use of automated mowers can help reduce labor costs and improve the economic efficiency of orchards. However, due to the complexity of the geographic and spatial environment of the orchard, in particular, the loose and undulating road surface, the interference of satellite signals by large trees, etc., which decreases the positioning accuracy and stability of the positioning system of the mower, and the high cost of the sensor also affect the popularization of intelligent mowers for these applications. To address the above problems, this paper constructs a positioning system through a low-cost global navigation satellite system (GNSS), inertial measurement unit (IMU), and odometry, and utilizes the Kalman filter algorithm based on the error state for a combined GNSS/IMU positioning so that the inertial navigation system can maintain a more accurate positioning when the GNSS signals are poor. Considering the side-slip and error accumulation problems of the odometry of the traction mower, the combined GNSS/IMU positioning information is used to optimize the odometry model and improve the navigation and positioning accuracy. To reduce the measurement error of the IMU and the problem of error accumulation, this paper utilizes the nonholonomic constraint (NHC) of a lawn mower to suppress the dispersion of IMU measurement errors and constructs periodic and nonperiodic zero-velocity updating (ZUPT) strategies in combination with the travel paths of lawn mower navigation operations in the region to update the IMU data to improve the positioning accuracy and stability of the positioning system. The experiments show that the average error of the constructed positioning system is controlled within 0.15 m, the maximum error is maintained at approximately 0.3 m, and the positioning system constructed by using low-cost sensors can achieve a positioning accuracy similar to that of the differential global navigation satellite system (DGNSS), which is beneficial for the promotion and application of intelligent mowers in orchards.

Modern supply chain systems face significant challenges, including lack of transparency, inefficient inventory management, and vulnerability to disruptions and security threats. Traditional optimization methods often struggle to adapt to the complex and dynamic nature of these systems. This paper presents a novel blockchain-based zero-trust supply chain security framework integrated with deep reinforcement learning (SAC-rainbow) to address these challenges. The SAC-rainbow framework leverages the Soft Actor–Critic (SAC) algorithm with prioritized experience replay for inventory optimization and a blockchain-based zero-trust mechanism for secure supply chain management. The SAC-rainbow algorithm learns adaptive policies under demand uncertainty, while the blockchain architecture ensures secure, transparent, and traceable record-keeping and automated execution of supply chain transactions. An experiment using real-world supply chain data demonstrated the superior performance of the proposed framework in terms of reward maximization, inventory stability, and security metrics. The SAC-rainbow framework offers a promising solution for addressing the challenges of modern supply chains by leveraging blockchain, deep reinforcement learning, and zero-trust security principles. This research paves the way for developing secure, transparent, and efficient supply chain management systems in the face of growing complexity and security risks.

A series of novel binuclear PNP ligands based on the cyclohexyldiamine scaffold were synthesized for this study. The experimental results showed that positioning the two PNP sites at the para-positions of the cyclohexyl framework led to a significant enhancement in the catalytic activity for selective tri/tetramerization of ethylene. The PNP/Cr(acac)3/MAO(methylaluminoxane) catalytic system exhibited relatively high catalytic activity (up to 3887.7 kg·g−1·h−1) in selective ethylene oligomerization with a total selectivity of 84.5% for 1-hexene and 1-octene at 40 °C and 50 bar. The relationship between the ligand structure and ethylene oligomerization performance was further explored using density functional theory calculations.

Angelicae pubescentis radix (APR) has been traditionally used for thousands of years in China to treat rheumatoid arthritis (RA), an autoimmune disorder. As the main active coumarin of APR, columbianadin (CBN) exhibits a significant anti-inflammatory effect in vitro. However, the anti-inflammatory activity and underlying mechanism of CBN in vivo remain unclear. This work aimed to elucidate the anti-inflammatory activity of CBN in vivo and its related signaling pathways in a D-Gal-induced liver injury mouse model. Analysis of biochemical indices (ALT and AST) and pro-inflammatory cytokines (IL-1β and IL-6) in serum indicated that CBN significantly ameliorated D-Gal-induced liver injury. CBN treatment also significantly increased the activities of antioxidant enzymes (SOD, CAT, GPx), and decreased the levels of pro-inflammatory cytokines (TNF-α, IL-1β and IL-6) in liver tissue. Liver histology revealed that CBN treatment reduced hepatic inflammation. Western blot analysis indicated that CBN down-regulates the expression of phosphorylated JAK2, STAT3, MAPK, and NF-κB in the related signaling pathways. These findings support the traditional use of APR as a remedy for the immune system, and indicate that the JAK2/STAT3 and JAK2/p38/NF-κB signaling pathways may be important mechanisms for the anti-inflammatory activity of CBN in vivo.

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by synovial inflammation and joint damage with complex pathological mechanisms. In recent years, many studies have shown that the dysregulation of intestinal mucosal immunity and the damage of the epithelial barrier are closely related to the occurrence of RA. Total glucosides of paeony (TGP) have been used clinically for the treatment of RA in China for decades, while the pharmacological mechanism is still uncertain. The purpose of this study was to investigate the regulatory effect and mechanism of TGP on intestinal immunity and epithelial barrier in RA model rats. The results showed that TGP alleviated immune hyperfunction by regulating the ratio of CD3+, CD4+ and CD8+ in different lymphocyte synthesis sites of the small intestine, including Peyer’s patches (PPs), intraepithelial lymphocytes (IELs), and lamina propria lymphocytes (LPLs). Specially, TGP first exhibited immunomodulatory effects on sites close to the intestinal lumen (IELs and LPLs), and then on PPs far away from the intestinal lumen as the administration time prolonged. Meanwhile, TGP restores the intestinal epithelial barrier by upregulating the ratio of villi height (V)/crypt depth (C) and expression of tight junction proteins (ZO-1, occludin). Finally, the integrated analysis of metabolomics-network pharmacology was also used to explore the possible regulation mechanism of TGP on the intestinal tract. Metabolomics analysis revealed that TGP reversed the intestinal metabolic profile disturbance in CIA rats, and identified 32 biomarkers and 163 corresponding targets; network pharmacology analysis identified 111 potential targets for TGP to treat RA. By intersecting the results of the two, three key targets such as ADA, PNP and TYR were determined. Pharmacological verification experiments showed that the levels of ADA and PNP in the small intestine of CIA rats were significantly increased, while TGP significantly decreased their ADA and PNP levels. In conclusion, purine metabolism may play an important role in the process of TGP improving RA-induced intestinal immune imbalance and impaired epithelial barrier.

Streptococcus equi subsp. zooepidemicus (SEZ) is an important zoonotic agent. Here, a virulence-attenuated strain M35246 derived from natural variation of wild-type SEZ ATCC35246 was found. M35246 showed a deletion of 25 contiguous genes as well as a loss-of-function mutation in covS. Subsequently, a 25-gene-deleted strain (ΔPI), a covS-mutant strain (McovS), and relevant complementary strains were constructed and investigated. M35246 and McovS were significantly less encapsulated and exhibited poorer anti-phagocytic capacity compared to wild-type SEZ. McovS was significantly more sensitive to β-lactams, aminoglycosides, macrolides, and lincosamides than wild-type SEZ. M35246, McovS, and ΔPI exhibited an increase in median lethal dose (LD50) in mice by 105, 105, and 5 times when compared to wild-type SEZ, respectively. Neither M35246 nor McovS were isolated from mice 48 h after being challenged with approximately 2 000 times the LD50 of wild-type SEZ. Transcriptome analysis showed that 668 significantly differentially expressed genes existed between McovS and wild-type SEZ. Numerous virulence factor-encoding genes and anabolic-related genes in McovS that were involved in anti-phagocytosis, capsule formation, pathogenicity, and antibiotic resistance were downregulated significantly relative to the wild-type strain. This study revealed that the CovS plays a vital role in the establishment of SEZ virulence.

Cervical cancer leads to 300,000 deaths annually and the mechanism of cervical carcinogenesis remains unclear. Zeste White 10-interacting kinetochore protein (ZWINT) is uniquely elevated in malignancies, promoting proliferation, migration, and colony formation of cancer cells. To investigate the role of ZWINT in proliferation, migration, invasion of cervical cancer, and evaluate the potential ability of ZWINT as a therapeutic target. First, ZWINT expression in cervical cancer was analyzed using the bioinformatic methods and assessed in several cervical cancer cell lines. The cell viability and colony formation assays were used to evaluate cell proliferation. Then, transwell assay was performed to investigate cell migration and invasion. Moreover, western blot was used to measure the expression level of ZWINT, matrix metalloproteinase 9 (MMP-9), N-cadherin, E-cadherin, p53 and p21 in CaSki and HeLa cells with ZWINT overexpression or knockdown. The bioinformatic analysis and western blot assay revealed the expression of ZWINT was significantly increased in cervical cancer. The cell viability and colony formation analysis illustrated that cell proliferation could be promoted by ZWINT overexpression and suppressed by ZWINT knockdown. Moreover, ZWINT promoted migration and invasion of CaSki and HeLa cells, through regulating the expression of MMP-9, N-cadherin, and E-cadherin. Furthermore, ZWINT attenuated the expression of p53 and p21 in cervical cancer cells. In summary, ZWINT functions in promoting cell proliferation, migration, and invasion of cervical cancer cells by suppressing p53/p21 signaling pathway, which indicated ZWINT is a potential therapeutic target for cervical cancer treatment.

Abstract Streptococcus suis serotype 2 (SS2) frequently colonizes the swine upper respiratory tract and can cause Streptococcal disease in swine with clinical manifestations of pneumonia, meningitis, and septicemia. Previously, we have shown that vimentin, a kind of intermediate filament protein, is involved in the penetration of SS2 through the tracheal epithelial barrier. The initiation of invasive disease is closely related to SS2-induced excessive local inflammation; however, the role of vimentin in airway epithelial inflammation remains unclear. Here, we show that vimentin deficient mice exhibit attenuated lung injury, diminished production of proinflammatory cytokines interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and the IL-8 homolog, keratinocyte-derived chemokine (KC), and substantially reduced neutrophils in the lungs following intranasal infection with SS2. We also found that swine tracheal epithelial cells (STEC) without vimentin show decreased transcription of IL-6, TNF-α, and IL-8. SS2 infection caused reassembly of vimentin in STEC, and pharmacological disruption of vimentin filaments prevented the transcription of those proinflammatory cytokines. Furthermore, deficiency of vimentin failed to increase the transcription of nucleotide oligomerization domain protein 2 (NOD2), which is known to interact with vimentin, and the phosphorylation of NF-κB protein p65. This study provides insights into how vimentin promotes excessive airway inflammation, thereby exacerbating airway injury and SS2-induced systemic infection.

As an emerging information technology, big data has been widely used in all aspects of life. As for the application of big data technology in dietary nutrition and health, it revolves mainly around the combination of nutrition, medicine and other relevant disciplines, during which big data technology is adopted to mine and analyze data for the provision of personalized information services tailored to personal physiological indicators. With the core collection of Web of Science and CNKI Chinese database as data sources, and VOSviewer is applied in this paper to analyze the annual volume of publication and the keywords of relevant literature on big data as well as dietary nutrition and health published over the past 10 years. Then, the application of big data technology in the field of dietary nutrition and health and the challenges arising from this field are summarized and analyzed. Finally, the future trend of big data research in the field of dietary nutrition and health is indicated, which would provide guidance for the in-depth research and application of big data technology in this field.

Long-time diversion irrigation has led to the continuous rise of the groundwater level in the Heifangtai platform,Gansu Province. So far, more than 200 loess landslides have occurred, causing more catastrophic threats to local people and property. The loess landslides on the Heifangtai Platform were charactered by rapid initiation,fast speed and wide accumulation area. A loess landslide occurred near Dangchuan village in the Heifangtai Platform on October 5, 2019. The characteristics and topographic data of the landslide were obtained by field investigation and UAV technology. We used the Massflow software to simulate the motion process of the landslide, and the deposits thickness and motion speed of the landslide are obtained. The result show that: (1) The “10·5 ” landslide has a volume of about 2.7×104 m3 and a maximum sliding distance of 355 m. It is a small kind of loess landslide; (2) The motion time is about 45 s, the maximum movement speed is 26 m/s, and the inversion result is consistent with the actual situation. The landslide movement process is divided into three stages: start acceleration→steady acceleration→deceleration accumulation; (3) It found that the average thickness and maximum accumlation thickness of the landslide in the main sliding direction were respectively 0.59 m and 1.35 m. The accumulation thickness shows a trend of increasing momently and then decreasing. The largest accumulation thickness is 0.82 m. The research results can provide related technical support for the risk prevention of the loess landslide occurred in the Heifangtai Platform.

Abstract The Earth’s outer core is mainly composed of Fe and Ni. The geodynamo of the Earth’s core are closely correlated with the transport properties of the fluid in the Earth’s core. We selected the typical FeNi fluid, and systemically calculated its diffusion coefficient and viscosity under Earth’s core condition by quantum molecular dynamics simulation. The diffusion coefficients are almost constant along the core adiabatic curve. The self-diffusion coefficients of Ni along the core adiabatic curve range from 2.47 × 10−9 to 3.37 × 10−9 m2s−1. The diffusion coefficient increases with temperature increase, while viscosity decrease with temperature increase. The calculations on the transport properties suggest that the Ni impurities have a negligible effect on the diffusion coefficient and viscosity of Earth’s core.

Beryllium is an ablator material used in inertial-confinement fusion and hypervelocity impact studies. The thermoelastic properties, structural factors, and optical properties of beryllium are important in these studies. In this paper, the static structural factors, ion–ion dynamic structural factors, adiabatic velocity, and optical properties of beryllium along the Hugoniot were calculated by ab initio simulations. The static structural factors show that beryllium atoms were randomly distributed. The dynamic structural factors extracted the dispersion relation for collective excitation via the scattering function. By collecting the peak position of the dynamic structural factors, the dispersion relation and adiabatic sound velocity were derived by definition. Using the calculated equation of state, the thermoelastic properties and adiabatic sound velocity have been derived. The two calculated methods for adiabatic sound velocity were verified to be equivalent.

The spiking neural network (SNN), as a promising brain-inspired computational model with binary spike information transmission mechanism, rich spatially-temporal dynamics, and event-driven characteristics, has received extensive attention. However, its intricately discontinuous spike mechanism brings difficulty to the optimization of the deep SNN. Since the surrogate gradient method can greatly mitigate the optimization difficulty and shows great potential in directly training deep SNNs, a variety of direct learning-based deep SNN works have been proposed and achieved satisfying progress in recent years. In this paper, we present a comprehensive survey of these direct learning-based deep SNN works, mainly categorized into accuracy improvement methods, efficiency improvement methods, and temporal dynamics utilization methods. In addition, we also divide these categorizations into finer granularities further to better organize and introduce them. Finally, the challenges and trends that may be faced in future research are prospected.

Due to the notable disparities in the physical and chemical characteristics between titanium and steel, the direct fusion of titanium/steel bimetallic sheets results in a considerable formation of fragile intermetallic compounds, making it difficult to achieve excellent metallurgical welded joints. In this study, a multi-principal powder of CoCrNiMn was designed and utilized as a filler material in the welding of the TA1/Q345 bimetallic sheet. It was expected that the in situ formation of Fex(CoCrNiMn)Tiy high-entropy alloys would be achieved using the filler powders, combined with the Ti and Fe elements from the melting of the TA1 and Q345 so as to restrain the generation of Fe-Ti IMCs and obtain the promising welded joints of the TA1/Q345 bimetallic sheet. An interesting finding is that high-entropy alloys were successfully obtained in the weld metal. The Fe-Ti intermetallic compounds at the welding interface were significantly reduced. The tensile strength was ~293 MPa, accounting for 60% of the strength of the base metal. Dimples were observed at the fracture of the welded joint.

Early childhood caries (ECC) is the most common chronic infectious oral disease in preschool children worldwide. It is closely related to the caries activity (CA) of children. However, the distribution characteristics of oral saliva microbiomes in children with different CA are largely underexplored. The aim of this study was to investigate the microbial community in saliva of preschool children with different CA and caries status, and to analyze the difference of microbial community in saliva of children with different CA and its correlation with ECC. Subjects were divided into 3 groups based on the Cariostat caries activity test: Group H, high CA (n=30); Group M, medium CA (n = 30); Group L, low CA (n=30). Questionnaire survey was used to explore the related influencing factors of CA. According to the caries status (on the basis of decayed mising filled teeth), these subjects were divided into caries-free group (dmft=0, n=19), caries-low group (0 < dmft ≤ 4, n=27) and caries-high group (dmft > 4, n=44). Microbial profiles of oral saliva were analyzed using 16S rRNA gene sequencing. There were significant differences in the microbial structure (P < 0.05). Scardovia and Selenomonas were the biomarkers of both H group and high caries group. The genus Abiotrophia and Lautropia were the biomarkers of both the L group and the low caries group, while the Lactobacillus and Arthrospira spp. were significantly enriched in the M group. The area under the ROC curve of the combined application of dmft score, age, frequency of sugary beverage intake, and the genus Scardovia, Selenomonas, and Campylobacter in screening children with high CA was 0.842. Moreover, function prediction using the MetaCyc database showed that there were significant differences in 11 metabolic pathways of salivary microbiota among different CA groups. Certain bacteria genera in saliva such as Scardovia and Selenomonas may be helpful in screening children with high CA.

GntR transcription factor of Streptococcus suis serotype 2 (SS2) is a potential substrate protein of STK, but the regulation mechanisms of GntR phosphorylation are still unclear. This study confirmed that STK phosphorylated GntR in vivo, and in vitro phosphorylation experiments showed that STK phosphorylated GntR at Ser-41. The phosphomimetic strain (GntR-S41E) had significantly reduced lethality in mice and reduced bacterial load in the blood, lung, liver, spleen, and brain of infected mice compared to wild-type (WT) SS2. Electrophoretic mobility shift assay (EMSA) and chromatin immunoprecipitation (ChIP) experiments demonstrated that the promoter of nox was bound by GntR. The phosphomimetic protein GntR-S41E cannot bind to the promoter of nox, and the nox transcription levels were significantly reduced in the GntR-S41E mutant compared to WT SS2. The virulence in mice and the ability to resist oxidative stress of the GntR-S41E strain were restored by complementing transcript levels of nox. NOX is an NADH oxidase that catalyzes the oxidation of NADH to NAD+ with the reduction of oxygen to water. We found that NADH is likely accumulated under oxidative stress in the GntR-S41E strain, and higher NADH levels resulted in increased amplified ROS killing. In total, we report GntR phosphorylation could inhibit the transcription of nox, which impaired the ability of SS2 to resist oxidative stress and virulence.

Testicular two-dimensional ultrasound is a testing modality that is often used to evaluate azoospermia and other related diseases. With the continuous development of deep learning in recent years, the combination of deep learning and testicular ultrasound appears unstoppable despite a lack of relevant standards. One of the major problems associated with the digitization of ultrasound images is the uneven quality of data however, and a standardized data source and acquisition process has not yet been developed. Such a standard could fill the current gap, and establish acquisition criteria for ultrasound images of testes during the male reproductive period, including grayscale ultrasound, shear wave elastography, and contrast-enhanced ultrasound. By following these guidelines the quality of testicular ultrasound images would be improved and standardized, which would lay a solid foundation for the standardization of testicular ultrasound images, and assist automated evaluation of testicular spermatogenic function of whole testis in azoospermic males.

Abstract To overcome the limitation of the virtual extensometer method in measuring the crack opening displacement (COD) in the process of complex multi-crack propagation of rock, the measurement error of Digital Image Correlation (DIC) local deformation is theoretically analyzed. An improved virtual extensometer method for measuring the COD is proposed, which considers the temporal and spatial characteristics of crack development in the process of complex crack propagation. The accuracy of the proposed method is verified by the strain localization band numerical simulation test and indoor single crack simulation test. Furthermore, the method is applied to the two-dimensional similarity simulation test of simulating complex multi-fractures in rock stratum. The COD obtained by the traditional and improved methods is compared with the measured COD. The results show that in the case of multiple complex cracks, to obtain the COD accurately, the relative distance between the virtual extensometer measuring point and the crack should be greater than half of the sum of the width of the crack strain localization zone and the subset size. With the development of the crack, the relative distance between the virtual extensometer measuring point and the crack should increase with the increase of the width of the crack strain localization zone. The error of the COD measured by the traditional method increases with fracture development, and the maximum is 21.20%. The maximum relative error between the COD measured by the improved method and the measured crack opening is 3.61%. The research results improve the accuracy of the virtual extensometer in measuring the COD under complex multi-crack conditions.

Abstract The three-dimensional target position is vital to automatic driving, which can efficiently detect the geometrical shape of obstacles and achieve automatic environment recognition for both indoor and outdoor scenarios. In this paper, we propose an RFID 3D localization prototype based on the polarization phase model. To eliminate the impacts of tag angle, we leverage the polarization effect to obtain polarized phases. After that, we use polarized phase decomposition to get pure phases, i.e., the phase corresponding to the line of sight path. Hence, we can calculate the raw phases using the HMFCW algorithm. Finally, we can estimate the target’s 3D position according to unwrapped phase information. In this way, we implement a low-cost, high-precision, easy-for-deployment 3D position solution using commercial UHF RFID hardware. The experiments show that the method can obtain effective positioning results in various environments and achieve positioning accuracy with an average error of about 9 cm.

Amid mounting concerns about climate change’s impact on coastal areas, this study investigates storm surge dynamics induced by Tropical Depression 29W (TD 29W) using the MIKE 21 model. Comprehending the complex mechanisms behind storm surges is crucial considering gaps in understanding their combined influences, including tide–surge interactions, varying typhoon parameters, and changing storm tracks. The impacts of climate change, including accelerating sea level rise and its correlation with storm surge magnitudes, require detailed investigations for effective disaster management in vulnerable coastal communities. Through precise calibration, matching simulations with tidal gauge stations, this research uncovers the intricate interplay between landfall timing, diverse storm tracks, wind intensities, and the amplifying impact of rising sea levels. Findings indicate surge residuals ranging from −0.03m to 0.01m during TD 29W’s landfall, with higher surge residuals during rising tide phases. Moreover, an increase in TD 29W’s maximum wind speed moderately influences positive surges while significantly amplifying negative surge heights by 68% to 92% with wind speed increments. An analysis of typhoon track variations emphasizes the vulnerability of the Pahang coast to changing storm dynamics, underlining the need for tailored resilience strategies. Projections suggest a significant surge height increase by the year 2100, emphasizing the urgency of adaptive measures for the region.

Aiming at the problem of excessive vertical vibration caused by seismic primary waves in jacket structures located in seismic zones in China, a new type of shear plate metal damper with upper and lower elliptical openings (SPA) is proposed in this paper. The seismic model test is carried out to compare the shear plate metal damper with three traditional opening forms, central elliptical opening, single row opening, and double row opening, and the hysteretic curve, skeleton curve, and cyclic hysteretic energy dissipation capacity are analyzed. The results show that the energy dissipation performance of the new shear plate metal damper with upper and lower elliptical openings proposed in this paper is better than that of the other three types of dampers.

In order to study the mountain deflection characteristics and the pressure law of the working face after the mining of a shallow coal seam under the valley terrain, a geometric size of 5.0 × 0.2 × 1.33 m is used in the physical similarity model. Brillouin optical time domain analysis (BOTDA) technology is applied to a similar physical model experiment to monitor the internal strain of the overlying rock. In this paper, the strain law of the horizontal optical fiber at different stages of the instability of the mountain structure is analyzed. Combined with the measurement of the strain field on the surface of the model via digital image correlation (DIC) technology, the optical fiber strain characteristics of the precursor of mountain instability are given. The optical fiber characterization method of working face pressure is proposed, and the working face pressures at different mining stages in gully terrain are characterized. Finally, the relationship between the deflection instability of the mountain and the strong ground pressure on the working face is discussed. The sudden increase in the strain peak point of the horizontally distributed optical fiber strain curve can be used to distinguish the strong ground pressure. At the same time, this conclusion is verified by comparing the measured underground ground pressure values. The research results can promote the application of optical fiber sensing technology in the field of mine engineering.

Offshore wind power industry presents to be one of the emerging industries with big strategic and pioneering significance in the world. In order to promote the high quality development of this industry in Shandong, the paper analyzed problems in the industry development and proposed corresponding strategies based on a thorough investigation. The results showed that offshore wind resources were abundant in Shandong with relatively solid foundation on the industry. But there were still acute problems including not detailed plan on the industry development, not strong enough support of science and technology on the industry, not systemic supporting industries, not enough grid capacity on the wind power, and lack of investors on manufacture. It was recommended to adhere to the principle of "develop innovative technologies and widen various channels based on overall layout to realize coordinated development through planning and piloting" to facilitate the industry development in a steady way.

Abstract In recent years, Klebsiella pneumoniae (KP) has caused disease outbreaks in different animals, resulting in serious economic losses and biosafety concerns. Considering the broad antibiotic resistance of KP, vaccines are the most effective tools against infection. However, there is still no KP vaccine available in the veterinary field. Our results indicate that the highly conserved outer membrane phosphoporin (PhoE) of KP is immunogenic in mice and elicits high titers of antibodies that were shown to be specific for PhoE by immunoblotting. Immunization with PhoE also induced robust cell-mediated immunity and elicited the secretion of high levels of IFN-γ and IL-4, suggesting the induction of mixed Th1 and Th2 responses. Sera from PhoE-immunized mice induced significantly higher complement-mediated lysis of KP cells than did sera from the PBS control mice. Finally, mice immunized with PhoE were significantly protected against KP challenge, with better survival and a reduced visceral bacterial load. Our data underscore the great potential of PhoE as a novel candidate antigen for a vaccine against KP infection.