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In order to achieve multi-objective optimization for a permanent magnet water pump motor in heavy commercial vehicles, we propose a strategy based on response-surface methodology and the improved sparrow algorithm (CGE-SSA). Firstly, the output capacity of the pump during actual operation was tested with an experimental bench to determine the design parameters of the motor, and then its modeling was completed using Ansys Maxwell 2022r2 software. Secondly, the response-surface model was established by taking the parameters of permanent magnet width, rib width, and slot width as optimization parameters and the output torque (Ta), torque ripple (Tr), and back electromotive force (EMF) amplitude as optimization objectives. Meanwhile, three methods—namely, circular sinusoidal chaotic mapping, improved golden sinusoidal strategy, and adaptive weight coefficients—were used to improve the convergence speed and accuracy of the sparrow search algorithm (SSA). Finally, the multi-objective optimization of the permanent magnet synchronous motor was completed using the improved sparrow algorithm. A comparative analysis of the motor's output before and after optimization showed that the torque pulsation and reverse electromotive force of the motor were significantly improved after optimization. [ABSTRACT FROM AUTHOR]

Hemerocallis citrina Borani (H. citrina) has garnered significant attention due to its abundant nutritional quality. Datong, located in Shanxi Province, is recognized as one of the four major production regions for high-quality H. citrina. While Datong boasts multiple production areas, the nutritional composition of daylilies varies across regions due to environmental factors and planting patterns, which remain unclear. This study focuses on the total polyphenol and flavonoid contents (TPCs and TFCs) and protein content of H. citrina from three areas in Datong: Sanshilipu (DTSSLP), Dangliuzhuang (DTDLZ), and Jijiazhuang (DTJJZ). Additionally, a widely targeted metabolomics analysis was used to analyze the metabolite composition of H. citrina from these three areas. The results showed that H. citrina in DTSSLP had the highest contents of protein and amino acids, as well as TPCs and TFCs. A total of 798 differential metabolites were identified in H. citrina across the areas, with DTSSLP showing the highest levels of different classifications of metabolites, indicating its enhanced health benefits and physiological activities. Nine metabolic pathways were related with the different characteristics among DTSSLP, DTDLZ, and DTJJZ. This study provides theoretical support for distinguish H. citrina from different producing regions and elucidates the mechanisms underlying its metabolic pathways. [ABSTRACT FROM AUTHOR]

Immunotherapy research focuses on reshaping the tumor microenvironment (TME) to enhance its antitumor immune responses, with an emphasis on understanding the impact of RNA methylation in triple-negative breast cancer (TNBC) TME regulation. This study explored the influence of various RNA methyltransferases on TME cells in TNBC and their correlation with prognosis and immunotherapy response. Using non-negative matrix factorization on single-cell RNA-sequencing data, distinct TME cell clusters were identified based on the expression of 30 RNA methyltransferases. Various analyses, including pseudotime, cell communication, transcription factor regulatory network, and gene enrichment, were conducted on these clusters. The roles of RNA methyltransferase-mediated TME clusters in prognosis and immunotherapy response were determined using TNBC bulk RNA-Seq data, and the findings were validated through immunofluorescence analysis of a tissue microarray comprising 87 samples. Spatial transcriptomic analysis further revealed the distribution of TME cell clusters. Different methyltransferase-mediated cell clusters exhibited unique metabolic, immune, transcriptional, and intercellular communication patterns. Survival analysis indicated prognostic significance in specific TME cell clusters, and immunofluorescence analysis confirmed the prognostic value of m6A_WTAP + CD8T + cells. In conclusion, our study illustrated the involvement of these cell subgroups in tumor growth and antitumor immunity modulation, providing insights into the enhancement of TNBC immunotherapy. [ABSTRACT FROM AUTHOR]

Summary: The cases of fake Moutai‐flavour liquor have occurred frequently, seriously disrupting market economic order, therefore it is of great significance to realise the Moutai‐flavour liquor identification. Herein, an approach based on GC–MS technology coupled with chemometrics was established to achieve products identification and origins traceability. The normalised metabolite data were analysed by PCA, OPLS‐DA and volcano plot to screen differential metabolites. The heatmap visualisation and boxplot were used to explore the correlation between chemical markers and liquor samples. PLS‐DA model realised the accurate classification of Moutai‐flavour liquor samples using the screened chemical markers. All Moutai‐flavour liquor samples of the prediction set were accurately differentiated with 100% accuracy during the external verification. This study indicated that an approach based on GC–MS coupled with chemometrics has great potential for products identification and source tracing, thus providing technical support for combating crime of fake Moutai‐flavour liquor. [ABSTRACT FROM AUTHOR]

UV radiation presents a substantial challenge to the stability of perovskite solar cells (PSCs), limiting their applications in harsh environments such as outer space. Herein, UV‐resistant molecule octinoxate (OCT) is introduced to mitigate the adverse effects of UV irradiation. OCT additive demonstrates the capability to modulate the crystallization process, resulting in perovskite films with larger grains and enhanced crystallinity. Moreover, OCT doping also facilitates charge extraction in PSCs. The PSCs with OCT doping exhibit an enhanced efficiency, increasing from 22.46% to 24.64%, along with improved stability with a T85 of 1000 h under continuous light exposure. Functioning as a sunscreen material, OCT mitigates UV‐induced degradation by absorbing irradiation and hindering I2 escape. Even after continuous exposure to 18.7 kWh m−2 UV illumination, the OCT‐doped PSCs maintain over 92% of their initial efficiency, meeting the 15 kWh m−2 UV exposure requirement specified in the IEC:61215 PV robustness testing standard. This study offers a straightforward approach to enhance the durability of PSCs under UV radiation, opening avenues for their application in extreme environments. [ABSTRACT FROM AUTHOR]

We construct a lot of optimal or near-optimal [ n , k , d ] 9 Hermitian self-orthogonal codes for k ≤ 3 using norm codes and matrix combinatorial construction method. As an application, we construct nine families of entanglement-assisted quantum error-correcting codes. Some of these codes can achieve q-ary linear EA-Griesmer bound with better parameters than those in the literature. [ABSTRACT FROM AUTHOR]

Smart warehousing has been widely used due to its efficient storage and applications. However, the efficiency of transporting high-demand goods is still limited, because the existing methods lack path optimization strategies applicable to multiple scenarios and are unable to adapt conflict strategies to different warehouses. For solving these problems, this paper considers a multi-robot path planning method from three aspects: conflict-free scheduling, order picking and collision avoidance, which is adaptive to the picking needs of different warehouses by hierarchical agglomerative clustering algorithm, improved Reservation Table, and Dynamic Weighted Table. Firstly, the traditional A* algorithm is improved to better fit the actual warehouse operation mode. Secondly, the reservation table method is applied to solve the head-on collision problem of robots, and this paper improves the efficiency of the reservation table by changing the form of the reservation table. And the dynamic weighted table is added to solve the multi-robot problem about intersection conflict. Then, the HAC algorithm is applied to analyse the goods demand degree in current orders based on historical order data and rearrange the goods order in descending order, so that goods with a high-demand degree can be discharged from the warehouse in the first batch. Moreover, a complete outbound process is presented, which integrates HAC algorithm, improved reservation table and dynamic weighting table. Finally, the simulation is done to verify the validity of the proposed algorithm, which shows that the overall transit time of high-demand goods is reduced by 21.84% on average compared to the "A* + reservation table" algorithm, and the effectiveness of the solution is fully verified. [ABSTRACT FROM AUTHOR]

In this paper, a bio-inspired sliding mode control (bio-SMC) and minimal learning parameter (MLP) are proposed to achieve the cooperative formation control of underactuated unmanned surface vehicles (USVs) with external environmental disturbances and model uncertainties. Firstly, the desired trajectory of the follower USV is generated by the leader USV's position information based on the leader–follower framework, and the problem of cooperative formation control is transformed into a trajectory tracking error stabilization problem. Besides, the USV position errors are stabilized by a backstepping approach, then the virtual longitudinal and virtual lateral velocities can be designed. To alleviate the system oscillation and reduce the computational complexity of the controller, a sliding mode control with a bio-inspired model is designed to avoid the problem of differential explosion caused by repeated derivation. A radial basis function neural network (RBFNN) is adopted for estimating and compensating for the environmental disturbances and model uncertainties, where the MLP algorithm is utilized to substitute for online weight learning in a single-parameter form. Finally, the proposed method is proved to be uniformly and ultimately bounded through the Lyapunov stability theory, and the validity of the method is also verified by simulation experiments. [ABSTRACT FROM AUTHOR]

Owing to their distinctive novel properties, topological metals hold significant promise for application in spintronics, quantum computing, and superconductivity. Using first-principle calculations, we have elucidated the unfolding band structure of 3d transition metal (3d-TM)-doped CrTe2. Notably, our investigation has revealed band crossings in Cu-doped CrTe2, forming a nodal ring near the Fermi level. Through analyzing Wannier charge centers, we have established the topological nontriviality of CrTe2 upon Cu doping. This study demonstrates a fresh platform for exploring their inherent topological properties and introduces a novel perspective on tectonic topological metals. [ABSTRACT FROM AUTHOR]

Background: Liver transplantation (LT) is the treatment of choice for end-stage liver disease and certain malignancies such as hepatocellular carcinoma (HCC). Data on the surgical management of de novo or recurrent tumors that develop in the transplanted allograft are limited. This study aimed to investigate the perioperative and long-term outcomes for patients undergoing hepatic resection for de novo or recurrent tumors after liver transplantation. Methods: The study enrolled adult and pediatric patients from 12 centers across North America who underwent hepatic resection for the treatment of a solid tumor after LT. Perioperative outcomes were assessed as well as recurrence free survival (RFS) and overall survival (OS) for those undergoing resection for HCC. Results: Between 2003 and 2023, 54 patients underwent hepatic resection of solid tumors after LT. For 50 patients (92.6 %), resection of malignant lesions was performed. The most common lesion was HCC (n = 35, 64.8 %), followed by cholangiocarcinoma (n = 6, 11.1 %) and colorectal liver metastases (n = 6, 11.1 %). The majority of the 35 patients underwent resection of HCC did not receive any preoperative therapy (82.9 %) or adjuvant therapy (71.4 %), with resection their only treatment method for HCC. During a median follow-up period of 50.7 months, the median RFS was 21.5 months, and the median OS was 49.6 months. Conclusion: Hepatic resection following OLT is safe and associated with morbidity and mortality rates that are comparable to those reported for patients undergoing resection in native livers. Hepatic resection as the primary and often only treatment modality for HCC following LT is associated with acceptable RFS and OS and should be considered in well selected patients. [ABSTRACT FROM AUTHOR]

Bulletproof glass exhibits excellent impact resistance and protective capabilities against bullets, explosive fragments, high-speed projectiles, and various other aggressive threats, making it extensively utilized in the field of safety and security. To investigate the dynamic mechanical properties and constitutive relation of the inorganic glass layers in bulletproof glass under impact loading, we firstly employed an electronic universal testing machine and a split Hopkinson pressure bar (SHPB) test setup to obtain the tensile and compressive mechanical properties of the material at different strain rates. Results reveal a noticeable strain rate effect that the material's strength increases with the strain rate. Secondly, drawing on the experience of geotechnical triaxial compression tests, we designed a high-strength confinement sleeve suitable for assessing the mechanical properties of glass particles under conditions of complete damage. Results show a significantly lower strength compared to that of the intact state of inorganic glass. Finally, by integrating test data, an JH2 constitutive model for inorganic glass with damage was established. By using the non-linear finite element software LS-DYNA, the SHPB test process was simulated. The effectiveness of the constitutive model was verified by comparing test and simulated results. [ABSTRACT FROM AUTHOR]

To achieve the efficient resource utilization of municipal sludge and promote the sustainability of pavement materials, this study employed liquefaction technology to process municipal sludge. The resulting liquefied-sludge-derived heavy oil was blended with 50# asphalt to prepare a bio-asphalt that can replace petroleum asphalt. Firstly, orthogonal experiments were conducted to analyze the effects of the solid–liquid ratio (dried sludge:anhydrous ethanol), liquefaction temperature, and reaction time on the yield of the sludge-derived heavy oil. Then, the basic characteristics of the sludge-derived heavy oil were studied using an elemental analyzer, gel permeation chromatography, thermal analysis, gas chromatography–mass spectrometry, and Fourier transform infrared spectroscopy, and the differences between the sludge-derived heavy oil and petroleum asphalt were compared. Finally, to determine the appropriate content range of sludge-derived heavy oil in bio-asphalt, a comprehensive evaluation of the three major indicators, aging resistance, storage stability, low-temperature performance, and high-temperature performance was carried out for the prepared bio-asphalts. The results indicated that the optimal preparation process for liquefied sludge oil involves a liquefaction temperature of 275 °C, a solid–liquid ratio of 1:15, and a reaction time of 1 h, resulting in an oil production rate of 22.36%. The sludge-derived heavy oil demonstrated good thermal stability, with its primary components being aliphatic compounds (carboxylic acids, ketones, aldehydes, alcohols, alkanes, esters, etc.), with esters being the most abundant. Furthermore, the sludge-derived heavy oil was highly compatible with 50# asphalt, but no chemical reaction occurred between them. When the sludge-derived heavy oil content ranged from 5% to 20%, bio-asphalt showed favorable aging resistance and storage stability. As the content of the sludge-derived heavy oil increased, its low-temperature performance improved, but there was a slight decrease in high-temperature performance. Additionally, correlation analysis highlighted that the influence of sludge-derived heavy oil content on the high-temperature performance of bio-asphalt was notably greater than on other properties. Therefore, the recommended dosage of sludge-derived heavy oil should be between 5% and 10%. [ABSTRACT FROM AUTHOR]

Simple Summary: This study initially analyzed surveillance videos to identify and extract key moments of Andrias davidianus' parental care behavior and established a dataset for this behavior. Based on this, this study optimized the existing YOLOv8 object detection model specifically for this task and proposed the ML-YOLOv8 model, which shows outstanding performance in recognizing and analyzing A. davidianus' parental care behavior. Following testing and verification, the ML-YOLOv8 model demonstrated excellent performance in efficiently and accurately detecting A. davidianus' parental care behavior. The findings of this study not only provide evidence for optimizing breeding technology and conservation management of A. davidianus in their natural habitat but also offer new technical means and research ideas for studying amphibian behavioral ecology. Optimizing the breeding techniques and increasing the hatching rate of Andrias davidianus offspring necessitates a thorough understanding of its parental care behaviors. However, A. davidianus' nocturnal and cave-dwelling tendencies pose significant challenges for direct observation. To address this problem, this study constructed a dataset for the parental care behavior of A. davidianus, applied the target detection method to this behavior for the first time, and proposed a detection model for A. davidianus' parental care behavior based on the YOLOv8s algorithm. Firstly, a multi-scale feature fusion convolution (MSConv) is proposed and combined with a C2f module, which significantly enhances the feature extraction capability of the model. Secondly, the large separable kernel attention is introduced into the spatial pyramid pooling fast (SPPF) layer to effectively reduce the interference factors in the complex environment. Thirdly, to address the problem of low quality of captured images, Wise-IoU (WIoU) is used to replace CIoU in the original YOLOv8 to optimize the loss function and improve the model's robustness. The experimental results show that the model achieves 85.7% in the mAP50-95, surpassing the YOLOv8s model by 2.1%. Compared with other mainstream models, the overall performance of our model is much better and can effectively detect the parental care behavior of A. davidianus. Our research method not only offers a reference for the behavior recognition of A. davidianus and other amphibians but also provides a new strategy for the smart breeding of A. davidianus. [ABSTRACT FROM AUTHOR]

Background: Breast cancer patients exhibit various response patterns to neoadjuvant chemotherapy (NAC). However, it is uncertain whether diverse tumor response patterns to NAC in breast cancer patients can predict survival outcomes. We aimed to develop and validate radiomic signatures indicative of tumor shrinkage and therapeutic response for improved survival analysis. Methods: This retrospective, multicohort study included three datasets. The development dataset, consisting of preoperative and early NAC DCE-MRI data from 255 patients, was used to create an imaging signature-based multitask model for predicting tumor shrinkage patterns and pathological complete response (pCR). Patients were categorized as pCR, nonpCR with concentric shrinkage (CS), or nonpCR with non-CS, with prediction performance measured by the area under the curve (AUC). The prognostic validation dataset (n = 174) was used to assess the prognostic value of the imaging signatures for overall survival (OS) and recurrence-free survival (RFS) using a multivariate Cox model. The gene expression data (genomic validation dataset, n = 112) were analyzed to determine the biological basis of the response patterns. Results: The multitask learning model, utilizing 17 radiomic signatures, achieved AUCs of 0.886 for predicting tumor shrinkage and 0.760 for predicting pCR. Patients who achieved pCR had the best survival outcomes, while nonpCR patients with a CS pattern had better survival than non-CS patients did, with significant differences in OS and RFS (p = 0.00012 and p = 0.00063, respectively). Gene expression analysis highlighted the involvement of the IL-17 and estrogen signaling pathways in response variability. Conclusions: Radiomic signatures effectively predict NAC response patterns in breast cancer patients and are associated with specific survival outcomes. The CS pattern in nonpCR patients indicates better survival. [ABSTRACT FROM AUTHOR]

The CO2 miscible flooding is an effective technology for development of low permeability reservoirs due to high oil displacement efficiency. However, CO2 miscible flooding for tertiary recovery technology typically occur after water flooding. Water hindered the contact and mass transfer of CO2 and oil, produce water resistance effect. Water can block CO2 and contact and mass transfer of crude oil (ie water blocking effect). The impact of this effect on the miscibility pressure and oil displacement effect is still unclear. In this study, homogeneous artificial cores with the same permeability as the reservoir were designed according to the miscible mechanism. Subsequently, the minimum miscibility pressure(MMP) between CO2 and crude oil at different water saturation was measured by the coreflood test. Based on the MMP, CO2 miscible flooding experiments were conducted by natural cores at different water saturation. The results showed that when the water saturation was 30%, 45%, and 60%, respectively, the corresponding MMP between CO2 and crude oil was 18.56, 19.48, and 21.76 MPa. The higher the water saturation, the longer the gas breakthrough time. But the oil recovery factor did not rise with the increase of water saturation. When the water saturation was 45%, the oil recovery factor in the miscible flooding experiment was the highest. In addition, the higher the water saturation, the weaker the CO2 extraction of various components in the crude oil. And the light components below C5 were most affected by water saturation. The mechanisms underlying these results are discussed. This study contributes to the development of CO2 miscible flooding reservoir plan. [ABSTRACT FROM AUTHOR]

Objective: Air pollutants have been reported to have a potential relationship with amyotrophic lateral sclerosis (ALS). The causality and underlying mechanism remained unknown despite several existing observational studies. We aimed to investigate the potential causality between air pollutants (PM2.5, NOX, and NO2) and the risk of ALS and elucidate the underlying mechanisms associated with this relationship. Methods: The data utilized in our study were obtained from publicly available genome‐wide association study data sets, in which single nucleotide polymorphisms (SNPs) were employed as the instrumental variantswith three principles. Two‐sample Mendelian randomization and transcriptome‐wide association (TWAS) analyses were conducted to evaluate the effects of air pollutants on ALS and identify genes associated with both pollutants and ALS, followed by regulatory network prediction. Results: We observed that exposure to a high level of PM2.5 (OR: 2.40 [95% CI: 1.26–4.57], p = 7.46E‐3) and NOx (OR: 2.35 [95% CI: 1.32–4.17], p = 3.65E‐3) genetically increased the incidence of ALS in MR analysis, while the effects of NO2 showed a similar trend but without sufficient significance. In the TWAS analysis, TMEM175 and USP35 turned out to be the genes shared between PM2.5 and ALS in the same direction. Conclusion: Higher exposure to PM2.5 and NOX might causally increase the risk of ALS. Avoiding exposure to air pollutants and air cleaning might be necessary for ALS prevention. [ABSTRACT FROM AUTHOR]

Background: Image‐to‐patient registration aligns preoperative images to intra‐operative anatomical structures and it is a critical step in image‐guided surgery (IGS). The accuracy and speed of this step significantly influence the performance of IGS systems. Rigid registration based on paired points has been widely used in IGS, but studies have shown its limitations in terms of cost, accuracy, and registration time. Therefore, rigid registration of point clouds representing the human anatomical surfaces has become an alternative way for image‐to‐patient registration in the IGS systems. Purpose: We propose a novel correspondence‐based rigid point cloud registration method that can achieve global registration without the need for pose initialization. The proposed method is less sensitive to outliers compared to the widely used RANSAC‐based registration methods and it achieves high accuracy at a high speed, which is particularly suitable for the image‐to‐patient registration in IGS. Methods: We use the rotation axis and angle to represent the rigid spatial transformation between two coordinate systems. Given a set of correspondences between two point clouds in two coordinate systems, we first construct a 3D correspondence cloud (CC) from the inlier correspondences and prove that the CC distributes on a plane, whose normal is the rotation axis between the two point clouds. Thus, the rotation axis can be estimated by fitting the CP. Then, we further show that when projecting the normals of a pair of corresponding points onto the CP, the angle between the projected normal pairs is equal to the rotation angle. Therefore, the rotation angle can be estimated from the angle histogram. Besides, this two‐stage estimation also produces a high‐quality correspondence subset with high inlier rate. With the estimated rotation axis, rotation angle, and the correspondence subset, the spatial transformation can be computed directly, or be estimated using RANSAC in a fast and robust way within only 100 iterations. Results: To validate the performance of the proposed registration method, we conducted experiments on the CT‐Skull dataset. We first conducted a simulation experiment by controlling the initial inlier rate of the correspondence set, and the results showed that the proposed method can effectively obtain a correspondence subset with much higher inlier rate. We then compared our method with traditional approaches such as ICP, Go‐ICP, and RANSAC, as well as recently proposed methods like TEASER, SC2‐PCR, and MAC. Our method outperformed all traditional methods in terms of registration accuracy and speed. While achieving a registration accuracy comparable to the recently proposed methods, our method demonstrated superior speed, being almost three times faster than TEASER. Conclusions: Experiments on the CT‐Skull dataset demonstrate that the proposed method can effectively obtain a high‐quality correspondence subset with high inlier rate, and a tiny RANSAC with 100 iterations is sufficient to estimate the optimal transformation for point cloud registration. Our method achieves higher registration accuracy and faster speed than existing widely used methods, demonstrating great potential for the image‐to‐patient registration, where a rigid spatial transformation is needed to align preoperative images to intra‐operative patient anatomy. [ABSTRACT FROM AUTHOR]

Mitochondrial dynamics has emerged as an important target for neuronal protection after cerebral ischaemia/reperfusion. Therefore, the aim of this study was to investigate the mechanism by which ARMC10 regulation of mitochondrial dynamics affects mitochondrial function involved in ischaemic stroke (IS). Mitochondrial morphology was detected by laser scanning confocal microscopy (LSCM), and mitochondrial ultrastructural alterations were detected by electron microscopy. The expression of mitochondrial dynamics‐related genes Drp1, Mfn1, Mfn2, Fis1, OPA1 and ARMC10 and downstream target genes c‐Myc, CyclinD1 and AXIN2 was detected by RT‐qPCR. Western blot was used to detect the protein expression of β‐catenin, GSK‐3β, p‐GSK‐3β, Bcl‐2 and Bax. DCFH‐DA fluorescent probe was to detect the effect of ARMC10 on mitochondrial ROS level, Annexin V‐FITC fluorescent probe was to detect the effect of ARMC10 on apoptosis, and ATP assay kit was to detect the effect of ARMC10 on ATP production. Mitochondrial dynamics was dysregulated in clinical IS samples and in the OGD/R cell model, and the relative expression of ARMC10 gene was significantly decreased in IS group (p < 0.05). Knockdown and overexpression of ARMC10 could affect mitochondrial dynamics, mitochondrial function and neuronal apoptosis. Agonist and inhibitor affected mitochondrial function and neuronal apoptosis by targeting Wnt/β‐Catenin signal pathway. In the OGD/R model, ARMC10 affected mitochondrial function and neuronal apoptosis through the mechanism that regulates Wnt/β‐catenin signalling pathway. ARMC10 regulates mitochondrial dynamics and protects mitochondrial function by activating Wnt/β‐catenin signalling pathway, to exert neuroprotective effects. [ABSTRACT FROM AUTHOR]

Recently, graphene has drawn considerable attention in the field of electronics, owing to its favorable conductivity and high carrier mobility. Crucial to the industrialization of graphene is its high-quality microfabrication via chemical vapor deposition. However, many problems remain in its preparation, such as the not fully understood cracking mechanism of the carbon source, the mechanism of its substrate oxidation, and insufficient defect repair theory. To help close this capability gap, this study leverages density functional theory to explore the role of O in graphene growth. The effects of Cu substrate oxidation on carbon source cracking, nucleation barriers, crystal nucleus growth, and defect repairs are discussed. OCu was found to reduce energy change during dehydrogenation, rendering the process easier. Moreover, the adsorbed O in graphene or its Cu substrate can promote defect repair and edge growth. [ABSTRACT FROM AUTHOR]

Isolation technology, especially for base isolation, is increasingly being applied in earthquake-prone areas. To satisfy some special demands (such as prevention from seawater erosion of an isolation layer, story-adding retrofit of existing buildings, avoidance of collision between base-isolated tall buildings, and so on), the isolation layer sometimes has to be set in the middle of a building to constitute inter-story isolated buildings. This special structural form inevitably encounters strong wind loads during service life, and its wind-resistant performance deserves to be investigated. This study conducts the wind-induced vibration analysis of inter-story isolated tall buildings with friction pendulum bearing (FPB). The nonlinear time domain analysis model and statistical linearization method to compute the wind-induced response of FPB inter-story isolated tall buildings are addressed based on an enhanced simplified model. Considering the independence of the upper and lower structures, two structural design schemes for inter-story isolated tall buildings are provided. Their dynamic characteristics are analyzed, and wind-induced responses are compared. Finally, the accuracy of the statistical linearization method is verified. This study provides an important theoretical basis for the structural design and wind resistance of inter-story isolated tall buildings. [ABSTRACT FROM AUTHOR]

The joint made of cast steel is frequently utilized within a treelike column structure to ensure a smooth transition. It is of great significance in ensuring the overall structural safety, but currently, the mechanical property and bearing capacity of this type of joint cannot be fully understood. This study investigates the load characteristics of three-forked cast steel joints through concrete experiments, finite element analysis, and regression method formula derivation, filling the gap in mechanical properties and calculation formulas of forked cast steel joints. Initially, a comprehensive model of the cast-steel joint, sourced from a practical engineering, underwent vertical load testing. Detailed scrutiny of stress distribution and vertical displacement of the tested joint was conducted based on the experimental outcomes. Subsequently, a finite element model of the tested joint was constructed using SolidWorks and subjected to analysis via ANSYS. The numerical findings were juxtaposed with experimental data and extrapolated to encompass other parametric scenarios. Ultimately, a regression analysis method was employed to derive a calculation formula for the load-carrying capacity of branch-bearing cast-steel joints. The regression analysis method can accurately obtain the load-bearing capacity calculation formula for tree-shaped joint models and can be extended to determine corresponding branch and main pipe dimensions, as well as the deviation angle between branches and the main pipe, under known load conditions. This improves design efficiency and accuracy. Comparative analysis reveals a substantial concurrence among experimental, finite element analysis, and formula-based predictive outcomes. The maximum error between experimental results and those obtained from finite element analysis is 9.02%. The maximum error between the results calculated using the load-bearing capacity formula derived from regression methods and those from finite element analysis is only 1.9%. [ABSTRACT FROM AUTHOR]

This study describes the application of a magnetic abrasive finishing process (MAF) to the inner wall of the Co-Cr alloy cardiovascular tube to obtain a fine surface roughness and improve the surface quality. The high-performance spherical iron-based diamond magnetic abrasive powder (MAP) used in the experiments was prepared via combining plasma molten metal powder with sprayed abrasive powder. The experiments were carried out on a MAF machining machine for slender tubes, with permanent slotted magnets as the magnetic field-generating device. The processing mechanism of the MAF on the inner wall of the tube was analyzed, and the magnitude and distribution of the magnetic flux in the processed area were simulated by software. The material removal model for MAF processing of the inner wall of the tube was constructed from mechanical properties of magnetic abrasives and the workpiece and five applied process parameters: finishing time, tube rotational speed, magnetic feed rate, size of MAPs, and filling quantity of MAPs. Single-factor experiments were designed and carried out using surface roughness Ra and quality differences before and after MAF processing as evaluation indicators. The results were used to analyze the relationship between five process parameters and surface roughness Ra and material removal MR. Scanning electron microscopy was used to observe the effect of the MAF process on the surface quality. It shows that the MAF process can effectively remove the defective layer from the workpiece and improve its surface smoothness and quality. The surface roughness Ra of 0.46–0.49 μm before finishing was decreased to 0.093 μm with optimal process parameters. [ABSTRACT FROM AUTHOR]

This article explores the use of artificial intelligence (AI) in the US military strategy. It categorizes academic studies on AI's impact into four groups and discusses the US's goals of leveraging emerging technologies, enhancing military capabilities, and building an integrated combat force. The article also highlights the US's focus on technological innovation, joint military operations, and an integrated intelligence system. It mentions the US's implementation of large-scale intelligence research projects and the development of AI strategies and approaches. The article concludes by suggesting that China should closely monitor and respond to the developments in the US military strategy. [Extracted from the article]

In this study, a new method of ultrasonic vibration processing of high-speed EDM ultra-fine copper tube electrode is proposed, and the deformation process of copper tube during processing is simulated by finite element analysis, and a prediction model of wall thickness change of ultrasonically processed copper tube electrode is established, and the predicted values are in good agreement with the experimental measurement data. The surface quality of copper tube electrode after ultrasonic processing was improved, and the roughness was reduced from Ra1.28 to Ra0.43 µm, which is important for the automated production of high-quality ultra-fine copper tube electrode. [ABSTRACT FROM AUTHOR]

While the monolayer sheet is well-established as a Mott-insulator with a finite energy gap, the insulating nature of bulk 1T-TaS2 crystals remains ambiguous due to their varying dimensionalities and alterable interlayer coupling. In this study, we present a unique approach to unlock the intertwined two-dimensional Mott-insulator and three-dimensional band-insulator states in bulk 1T-TaS2 crystals by structuring a laddering stack along the out-of-plane direction. Through modulating the interlayer coupling, the insulating nature can be switched between band-insulator and Mott-insulator mechanisms. Our findings demonstrate the duality of insulating nature in 1T-TaS2 crystals. By manipulating the translational degree of freedom in layered crystals, our discovery presents a promising strategy for exploring fascinating physics, independent of their dimensionality, thereby offering a "three-dimensional" control for the era of slidetronics. While monolayer of 1T-TaS2 is considered to be a Mott insulator, the nature of the bulk insulating state is debated. Here the authors introduce a ladder-type structures with fractional misalignment of adjacent layers, showing that it becomes a Mott insulator due to decoupling between the layers. [ABSTRACT FROM AUTHOR]

In the face of the serious threat to human health and the economic burden caused by bacterial antibiotic resistance, 2D phosphorus nanomaterials have been widely used as antibacterial agents. Violet phosphorus nanosheets (VPNSs) are an exciting bandgap-adjustable 2D nanomaterial due to their good physicochemical properties, yet the study of VPNS-based antibiotics is still in its infancy. Here, a composite of gold nanorods (AuNRs) loaded onto VPNS platforms (VPNS/AuNR) is constructed to maximize the potential of VPNSs for antimicrobial applications. The loading with AuNRs not only enhances the photothermal performance via a localized surface plasmon resonance (LSPR) effect, but also enhances the light absorption capacity due to the narrowing of the band gap of the VPNSs, thus increasing the ROS generation capacity. The results demonstrate that VPNS/AuNR exhibits outstanding antibacterial properties and good biocompatibility. Attractively, VPNS/AuNR is then extensively tested for treating skin wound infections, suggesting promising in vivo antibacterial and wound-healing features. Our findings may open a novel direction to develop a versatile VPNS-based treatment platform, which can significantly boost the progress of VPNS exploration. [ABSTRACT FROM AUTHOR]

Suppressing the formation of amorphous surface carbon and contaminants during the preparation of graphene by chemical vapor deposition remains an ongoing issue. Herein, we analyzed how substrate characteristics affect graphene quality by simulating margin extension, the nucleation process, and defect pegging configurations on mono-crystalline oriented metal substrates with the aim of enhancing graphene cleanliness. Defect formation energy and nucleation potential, which are indirect substrate–graphene interaction features, were found to appropriately evaluate graphene quality. The crystallographic orientation of the metal substrate was discovered to be critical for producing superclean graphene. A low graphene defect density and high nucleation rate on the Cu (100) facet guarantee growth of high-quality graphene, especially in terms of suppressing the formation of amorphous carbon. In addition, rapid kink growth and self-healing on the Cu (100) facet facilitate rapid graphene synthesis, which is also promoted by rapid kink splicing and margin self-repair on this facet. This study provides theoretical insight useful for the synthesis of superclean graphene. [ABSTRACT FROM AUTHOR]

Estimating rigid transformation using noisy correspondences is critical to feature-based point cloud registration. Recently, a series of studies have attempted to combine traditional robust model fitting with deep learning. Among them, DHVR proposed a hough voting-based method, achieving new state-of-the-art performance. However, we find voting on rotation and translation simultaneously hinders achieving better performance. Therefore, we proposed a new hough voting-based method, which decouples rotation and translation space. Specifically, we first utilize hough voting and a neural network to estimate rotation. Then based on good initialization on rotation, we can easily obtain accurate rigid transformation. Extensive experiments on 3DMatch and 3DLoMatch datasets show that our method achieves comparable performances over the state-of-the-art methods. We further demonstrate the generalization of our method by experimenting on KITTI dataset. [ABSTRACT FROM AUTHOR]

The problem of bearing current is common in wind power generation system, which leads to the attenuation of generator life and great economic losses. Bearing voltage of a 5.5 MW wind‐turbine permanent magnet synchronous generator is studied. The bearing voltage equivalent circuit is modelled by studying the internal system structure of the generator, and an extraction method of cable parameters, generator winding parameters and stray capacitance parameters based on experiments is proposed to simulate the system. A system test platform is built to test the common mode voltage, common mode current and bearing voltage, and the test results are compared with the simulation results in time domain and frequency domain. The result indicate that the common mode equivalent model can accurately simulate the actual bearing voltage. Finally, rotor flange insulation is adopted to suppress bearing voltage. The relationship between the design of rotor flange insulation with suppressing effect is discussed. Finally, an optimisation design method is presented for the proposed suppression scheme. [ABSTRACT FROM AUTHOR]

The modelling and analysis of high‐frequency bearing voltage are of great significance to the assessment and mitigation of the electrical erosion risk in wind power systems. However, the dual‐winding permanent magnet synchronous generator (DW‐PMSG), as one of the mainstream models in wind power industry, has not been specifically analysed for its bearing voltage modelling method in the existing research. The high frequency common mode equivalent circuit model of DW‐PMSG is established, and the effect of parasitic parameters between two sets of winding on bearing voltage is analysed. A model parameters extraction method based on differential evolution algorithm is proposed, and the range of parameters is estimated by finite element simulation and test results, which improves the search efficiency and solution accuracy. The accuracy of the proposed model is verified by the comparison of simulation and experimental results. On this basis, it is possible to conduct more in‐depth research on the bearing voltage and bearing currents of DW‐PMSG, and provide theoretical basis and simulation means for the design of suppression schemes. [ABSTRACT FROM AUTHOR]

Extreme disasters have become increasingly common in recent years and pose significant dangers to the integrated energy system's secure and dependable energy supply. As a vital part of an integrated energy system, the energy storage system can help with emergency rescue and recovery during major disasters. In addition, it can improve energy utilization rates and regulate fluctuations in renewable energy under normal conditions. In this study, the sizing scheme of multi-energy storage equipment in the electric–thermal–hydrogen integrated energy system is optimized; economic optimization in the regular operating scenario and resilience enhancement in extreme disaster scenarios are also considered. A refined model of multi-energy storage is constructed, and a two-layer capacity configuration optimization model is proposed. This model is further enhanced by the integration of a Markov two-state fault transmission model, which simulates equipment defects and improves system resilience. The optimization process is solved using the tabu chaotic quantum particle swarm optimization (TCQPSO) algorithm to provide reliable and accurate optimization results. The results indicate that addressing severe disaster situations in a capacity configuration fully leverages the reserve energy function of energy storage and enhances system resilience while maintaining economic efficiency; furthermore, adjusting the load loss penalty coefficients offers a more targeted approach to the balancing of the system economy and resilience. Thus, new algorithmic choices and planning strategies for future research on enhancing the resilience of integrated energy systems under extreme disaster scenarios are provided. [ABSTRACT FROM AUTHOR]

Cross-chain transaction technologies have greatly promoted the scalability of cryptocurrencies, which then facilitates the development of Metaverse applications. However, existing solutions rely heavily on centralized middleware (notary) or smart contracts. These schemes lack privacy considerations, and users' cross-chain transactions are easy to master by other parties. Some signature-based payment schemes have good privacy but do not support multi-party cross-chain protocols or rely heavily on some time assumptions. The uncertainty of user behavior makes it difficult to design a secure multi-party cross-chain protocol. To solve these problems, we investigate how to design a secure multi-party cross-chain transaction protocol with offline tolerance. We propose a new signature algorithm called the pre-adaptor signature scheme, an extension of the adaptor signature scheme. The pre-adaptor signature scheme combines the multi-signature and adaptor signature schemes, which can realize the secret transmission channel between multiple parties. To provide offline tolerance, we encode our protocol into the P2SH script. Our protocol provides better privacy due to no dependence on smart contracts. The performance evaluation was conducted with ten participants. For each participant of our cross-chain protocol, the initialization and execution process can be performed in 3 milliseconds and with 6 k bytes of communication overhead at most. The cost increases linearly with the increase in the number of participants. [ABSTRACT FROM AUTHOR]

Brain tumor segmentation is an important direction in medical image processing, and its main goal is to accurately mark the tumor part in brain MRI. This study proposes a brand new end-to-end model for brain tumor segmentation, which is a multi-scale deep residual convolutional neural network called mResU-Net. The semantic gap between the encoder and decoder is bridged by using skip connections in the U-Net structure. The residual structure is used to alleviate the vanishing gradient problem during training and ensure sufficient information in deep networks. On this basis, multi-scale convolution kernels are used to improve the segmentation accuracy of targets of different sizes. At the same time, we also integrate channel attention modules into the network to improve its accuracy. The proposed model has an average dice score of 0.9289, 0.9277, and 0.8965 for tumor core (TC), whole tumor (WT), and enhanced tumor (ET) on the BraTS 2021 dataset, respectively. Comparing the segmentation results of this method with existing techniques shows that mResU-Net can significantly improve the segmentation performance of brain tumor subregions. [ABSTRACT FROM AUTHOR]

Recommending APIs is a practical and essential feature of IDEs. Improving the accuracy of API recommendations is an effective way to improve coding efficiency. With the success of deep learning in software engineering, the state-of-the-art (SOTA) performance of API recommendation is also achieved by deep-learning-based approaches. However, existing SOTAs either only consider the API sequences in the code snippets or rely on complex operations for extracting hand-crafted features, all of which have potential risks in under-encoding the input code snippets and further resulting in sub-optimal recommendation performance. To this end, this article proposes to utilize the code understanding ability of existing general code Pre-Training Models to fully encode the input code snippet to improve the accuracy of APIRecommendation, namely, PTM-APIRec. To ensure that the code semantics of the input are fully understood and the API recommended actually exists, we use separate vocabularies for the input code snippet and the APIs to be predicted. The experimental results on the JDK and Android datasets show that PTM-APIRec surpasses existing approaches. Besides, an effective way to improve the performance of PTM-APIRec is to enhance the pre-trained model with more pre-training data (which is easier to obtain than API recommendation datasets). [ABSTRACT FROM AUTHOR]

Nodal-line semimetals, ZrSiX (X = S, Se, Te), provide an ideal platform to investigate the tunable Fermi surfaces by replacing chalcogens. Here, we study the magnetoresistance at various magnetic fields and temperatures in ZrSiSe and find the obedience of Kohler's law and sigmoidal-shaped field dependence, which are different to the behavior reported in ZrSiS. This difference is caused by compensated carriers and the non-negligible contribution from the trivial band in ZrSiSe. Furthermore, an anisotropic Berry-phase effect is observed and can be attributed to the enhanced spin–orbit coupling and the effect of a trivial band induced by Se replacement. Our findings provide further understanding for the topological states in nodal-line semimetal ZrSiX families and reveal the potential applications on magnetic sensors by manipulating the topological states. [ABSTRACT FROM AUTHOR]

Peroxidase-like based on double transition metals have higher catalytic activity and are considered to have great potential for application in the field of pollutant degradation. First, in this paper, a novel Fe0-doped three-dimensional porous Fe0@FeMn-NC-like peroxidase was synthesized by a simple one-step thermal reduction method. The doping of manganese was able to reduce part of the iron in Fe-Mn binary oxides to Fe0 at high temperatures. In addition, Fe0@FeMn-NC has excellent peroxidase-like mimetic activity, and thus, it was used for the rapid degradation of p-chlorophenol (4-CP). During the degradation process, Fe0 was able to rapidly replenish the constantly depleted Fe2+ in the reaction system and brought in a large number of additional electrons. The ineffective decomposition of H2O2 due to the use of H2O2 as an electron donor in the reduction reactions from Fe3+ to Fe2+ and from Mn3+ to Mn2+ was avoided. Finally, based on the experimental results of LC-MS and combined with theoretical calculations, the degradation process of 4-CP was rationally analyzed, in which the intermediates were mainly p-chloro-catechol, p-chloro resorcinol, and p-benzoquinone. Fe0@FeMn-NC nano-enzymes have excellent catalytic activity as well as structural stability and perform well in the treatment of simulated wastewater containing a variety of phenolic pollutants as well as real chemical wastewater. It provides some insights and methods for the application of peroxidase-like enzymes in the degradation of organic pollutants. [ABSTRACT FROM AUTHOR]

We investigate the magnetic and electronic properties of Co films on Fe3O4(001) achieved through epitaxial growth using magnetron sputtering. X-ray magnetic circularly dichroism measurements characterize the atomic magnetism. Compared to Co films on the MgO substrate, Co on Fe3O4 exhibits a 96% enhancement in orbital magnetic moment (from 0.25 to 0.49 µB/atom) and an increase in spin magnetic moment (from 1.37 to 1.53 µB/atom), resulting in an increased mratio(ml/ms) from 0.18 to 0.32. This enhancement of the orbital moment emerges as a consequence of the interface interaction between Co and Fe3O4. Density functional theory calculations attribute this heightened orbital magnetic moment to the robust electronic exchange interactions. Our findings not only offer insights into the modulation of magnetic and electronic characteristics in Co-based magnetic heterostructures but also provide valuable implications for the potential application of magnetic oxide/ferromagnetic heterostructures in future spintronic devices. [ABSTRACT FROM AUTHOR]

Utilizing the Open Integrated Forecasting System, the responses of Ural blocking (UB) to different stratospheric warming scenarios are investigated. Numerical results show that stratospheric warming with moderate strength in minor patterns prolongs the UB duration and enhances its intensity, while strong stratospheric warming in minor patterns tends to shorten its duration and weaken its intensity, even leading to the collapse of the UB events. Further diagnosis reveals that the planetary wave activity flux propagates downward from the stratosphere to the troposphere after stratospheric warming. Moreover, the convergence of planetary wave activity flux is a key factor for UB enhancement and maintenance. In addition, the weakened meridional temperature gradients, decelerated zonal westerly winds, and a reduced meridional potential vorticity gradient (PVy) result in UB enhancement in response to stratospheric warming with moderate strength. As stratospheric warming strengthens, planetary wave activity flux diverges, westerly winds in the tropospheric mid‐latitudes accelerate and the PVy in the Ural sector enlarges, which further weakens UB. Regarding the stratospheric perturbations in major patterns, they have similar influences on UB events, that is, UB enhances with moderate stratospheric warming and weakens with strong warming. However, the strengthened warming would trigger UB re‐enhancement, which is closely associated with anomalous activities of tropospheric synoptic‐scale waves induced by stratospheric perturbations. These results reveal UB events respond differently to stratospheric warming with various intensities and patterns in the short term, which makes a contribution to understanding stratosphere‐troposphere coupling. Plain Language Summary: Tropospheric Ural blocking (UB) is an important factor in modulating the weather and climate in East Asia, while stratospheric warming in the Arctic has great influences on UB in winter. Therefore, the influence of stratospheric warming on UB events is investigated with a complicated atmospheric model. We find that the anomalous energy from stratospheric warming propagates downward to the troposphere within 15 days, which in turn affects the UB events. Moderate stratospheric warmings can decelerate the mid‐latitude westerly winds, leading to enhanced UB. As the stratospheric warming strengthens, the UB weakens or even collapses due to the accelerated mid‐latitude westerly winds. These findings reveal the impact of stratospheric warming on UB events in the short term and contribute to a better understanding of the relationship between the stratosphere and the troposphere. Key Points: Stratospheric warming has notable effects on Ural blocking (UB) events within 15 daysThe moderate stratospheric warmings both in minor and major patterns enhance UB eventsStrengthened warming in major patterns would trigger UB re‐enhancement [ABSTRACT FROM AUTHOR]

Background: To create a dual-acting vaccine that can fight against tuberculosis, we combined antigenic arabino-mannan analogues with the Ag85B protein. To start the process, we studied the impact of modifying different parts of the Ag85B protein on its ability to be recognized by antibodies. Results: Through our research, we discovered that three modified versions of the protein, rAg85B-K30R, rAg85B-K282R, and rAg85B-K30R/K282R, retained their antibody reactivity in healthy individuals and those with tuberculosis. To further test the specificity of the sugar AraMan for AraMan antibodies, we used Human Serum Albumin glycosylated with AraMan-IME and Ara3Man-IME. Our findings showed that this specific sugar was fully and specifically modified. Bio-panning experiments revealed that patients with active tuberculosis exhibited a higher antibody response to Ara3Man, a sugar found in lipoarabinomannan (LAM), which is a major component of the mycobacterial cell wall. Bio-panning with anti-LAM plates could eliminate this increased response, suggesting that the enhanced Ara3Man response was primarily driven by antibodies targeting LAM. These findings highlight the importance of Ara3Man as an immunodominant epitope in LAM and support its role in eliciting protective immunity against tuberculosis. Further studies evaluated the effects of glycosylation on the antibody affinity of recombinant Ag85B and its variants. The results indicated that rAg85B-K30R/K282R, when conjugated with Ara3Man-IME, demonstrated enhanced antibody recognition compared to unconjugated or non-glycosylated versions. Conclusions: Coupling Ara3Man to rAg85B-K30R/K282R could lead to the development of effective dual-acting vaccines against tuberculosis, stimulating protective antibodies against both AraMan and Ag85B, two key tuberculosis antigens. [ABSTRACT FROM AUTHOR]

Multi-agent cooperation and confrontation technology have achieved rapid development in recent years. Most extant multi-agent reinforcement learning algorithms simplify the problem by using shared weights or local observation, and are only suitable for scenarios with less than ten agents. Given this, large-scale scene research needs to explore new directions. This paper presents a large-scale multi-agent evolutionary reinforcement jointed method. The multi-agent learning task is separated into numerous stages based on the agent's scale, and the self-attention mechanism is utilized to handle changing numbers of agents in each step. Simultaneously, to avoid the agents' poor adaptability in previous stages, the best individuals in the population are chosen at each stage of training via evolutionary techniques. Two typical unmanned aerial vehicle cluster missions, multi-domain joint sea crossing and landing missions, were created to validate the performance of the suggested technique, and the operational rules and reward functions were also given. Experiments have shown that the model trained using the suggested method has good performance and stability and can provide a multi-agent collaborative decision-making model suitable for large-scale environments. [ABSTRACT FROM AUTHOR]

Ultrasonic flowmeter is one of the most widely used devices in flow measurement. Traditional bulk piezoelectric ceramic transducers restrict their application to small pipe diameters. In this paper, we propose an ultrasonic gas flowmeter based on a PZT piezoelectric micromachined ultrasonic transducer (PMUT) array. Two PMUT arrays with a resonant frequency of 125 kHz are used as the sensitive elements of the ultrasonic gas flowmeter to realize alternate transmission and reception of ultrasonic signals. The sensor contains 5 × 5 circular elements with a size of 3.7 × 3.7 mm2. An FPGA with a resolution of ns is used to process the received signal, and a flow system with overlapping acoustic paths and flow paths is designed. Compared with traditional measurement methods, the sensitivity is greatly improved. The flow system achieves high-precision measurement of gas flow in a 20 mm pipe diameter. The flow measurement range is 0.5–7 m/s and the relative error of correction is within 4%. [ABSTRACT FROM AUTHOR]