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[Objective] This study was aimed to explore the impact of different land use patterns on regional ecosystem carbon storage. [Methods] In this paper, using the SD-PLUS coupled model and the coupled shared socio-economic path and representative concentration path (SSP-RCP) scenario proposed by the Coupled Model Intercomparison Project Phase 6 (CMIP6), the land use changes in Shaanxi province in 2030 were projected, and then the different future scenarios simulated by the InVEST model were used to predict the Shaanxi Province’s carbon storage and its spatial distribution under different future scenarios simulated by the InVEST model. [Results] (1) The SD model constructed was tested historically, and its error was less than 5%, and the Kappa index of land use in 2020 simulated by the PLUS model was 0.86, and the accuracy and reliability of the model generally met the requirements. (2) Under the three scenarios, the area of future construction land increased, and the scenarios with the lowest to highest growth rates were: SSP126, SSP245, SSP585. Under all scenarios, the area of forest land increased, and the area of watersheds remained stable; the area of grassland had a small increase under the SSP126 scenario, and decreased in other scenarios; and the area of arable land decreased in all three scenarios. (3) Carbon stock in Shaanxi Province decreased under all three scenarios, with the decrease in carbon stock in the Guanzhong plain being the main reason for the decrease in carbon stock in Shaanxi province. [Conclusion] The area of ecological land occupied by the expansion of construction land is the smallest under the SSP126 scenario, which takes into account both socio-economic development and the need for ecological protection, and can provide a reference model for the future protection of land resources and high-quality development in Shaanxi province.

Background: The purpose of this study is to investigate the genotype and allele distribution of MTHFR rs1801133 in the Chinese population, and to analyze the relationship between gene polymorphism of MTHFR rs1801133 and risk of childhood leukemia. Methods: Blood samples and clinical data of childhood leukemia cases (n=1132) and age-matched healthy controls (n=1053) were collected. Genotypes and allele distribution of MTHFR rs1801133 were detected by PCR-RFLP. Logistic regression model was generated to analyze the relation between MTHFR rs1801133 and susceptibility to childhood leukemia and the chemotherapy response. Results: Age, sex, BMI and family history of tumor were comparable between childhood leukemia cases and healthy controls. Genotypes and allele distribution of MTHFR rs1801133 were remarkably correlated to the risk of childhood leukemia. Genotype risk of MTHFR rs1801133 was parallel to the susceptibility to childhood leukemia. Specifically, compared with people carrying AA allele of MTHFR rs1801133, higher risk of childhood leukemia may occur in people carrying AG+GG allele of MTHFR rs1801133 with a younger age (

In order to further improve the stability and accuracy of the pouring trajectory of the heavy-duty casting robot during the pouring operation, a new hybrid four-degree-of-freedom heavy-duty casting robot is taken as the research object, and a trajectory planning method based on the synthesis of the fifth-order polynomial and the sinusoidal acceleration motion law is proposed. The degree-of-freedom of the actuator is calculated by the topological structure theory of the robot mechanism, and the position of the parallel mechanism is solved by the closed-loop vector method, the kinematic position equation of the hybrid mechanism is derived according to the equivalent method and the geometric method. The trajectory planning of the robot is carried out by combining the fifth-order polynomial and the sinusoidal acceleration motion law. The Adams software is used to simulate the trajectory motion of the robot end, and the parameters obtained by the theoretical solution are verified. The results show that the trajectory based on the combination of the fifth-order polynomial and the sine acceleration motion law is smoother and more natural than the fifth-order polynomial, and the maximum speed of the robot end is reduced by 14%, avoiding the vibration due to excessive speed fluctuations.

Abstract Before a wide range of enhanced oil recovery (EOR) techniques were implemented for an oilfield, the EOR potential and economic evaluation of the techniques should be evaluated in advance for each reservoir to determine which EOR technique was proper. In an oilfield developed with fluvial delta reservoirs, the complicated distribution of scattered small reservoirs in vertical and horizontal directions brought trouble for evaluation work. A rapid and reliable evaluation model for EOR techniques applicability was necessary to deal with the evaluation simulation for many small reservoirs of an oilfield. Combining fraction theory model with auxiliary equations, which describe the effect of formation heterogeneity and mechanism of different EOR technique on fractional flow rate, an evaluation analysis method for EOR techniques applicability of gas flooding, foam flooding and surfactant flooding was proposed. In the gas flooding model, the minimum miscible pressure of impure gas was introduced, and the relative permeability was modified by the minimum miscible factor. In the foam flooding model, changes in the mobility ratio and chemical adsorption were considered and a reduction factor of mobility ratio was introduced. In the surfactant flooding model, calculation formulas of viscosity and interfacial tension as well as the relative permeability were introduced. Finally, the model was simulated for a low permeability reservoir, and the simulation results were compared with that from Eclipse software. The similar results, little calculation time and feasibility of predicting optimal injection parameter had shown the reliability of the rapid evaluation model.

Background: For patients with advanced non‐small cell lung cancer (NSCLC) who have received frontline immunochemotherapy, subsequent treatment options are limited. As the first dual programmed cell death‐1 (PD‐1)/cytotoxic T lymphocyte‐associated antigen‐4 bispecific antibody approved globally, cadonilimab demonstrated potential antitumor activity in advanced NSCLC patients resistant to anti‐PD‐1/PD‐L1 antibodies. Methods: We retrospectively collected efficacy and safety data from advanced NSCLC patients treated with cadonilimab‐based regimens in later therapy lines. Results: A total of 41 advanced NSCLC patients refractory to anti‐PD‐1/PD‐L1 therapy were enrolled. More than half of the patients received cadonilimab‐based regimen as a fourth or later line of treatment. At the data cutoff date, treatment efficacy could be evaluated in 23 patients. One patient (4.3%) achieved partial response, eight patients (34.8%) experienced stable disease, and 14 patients (60.9%) progressed. The objective response rate and disease control rate were 4.3% and 39.1%, respectively. The median progression‐free survival for all evaluated patients was 108.0 days. Due to the short follow‐up period, the median overall survival has not yet been reached. Treatment‐related adverse events (TRAEs) and immune‐related AEs occurred in 63.4% and 22% patients, respectively. The most common TRAEs included gamma‐glutamyl transferase elevation (17.1%), coughing (14.6%), and fatigue (12.2%). Five patients (12.2%) experienced grade ≥3 TRAEs. Conclusions: In this heavily pretreated cohort of advanced NSCLC patients, cadonilimab‐based regimens showed moderate antitumor efficacy with a generally tolerable and manageable safety profile. However, more evidence is needed to support the administration of cadonilimab in NSCLC patients refractory to previous anti‐PD‐1/PD‐L1 therapy. [ABSTRACT FROM AUTHOR]

The surface quality of aluminium alloy castings is crucial to quality control. Aiming to address the challenges of limited samples and extensive computation in deep learning‐based surface defect detection for aluminium alloy castings, this paper proposes a surface defect detection method based on data enhancement and the Casting Real‐Time DEtection TRansformer. First, to tackle the issue of small sample sizes and uneven distribution in surface defect data sets of aluminium alloy castings, ECA‐MetaAconC Deep Convolution Generative Adversarial Networks is proposed for generating defects with fewer samples and employ the image augmentation (IMGAUG) library for sample enhancement. Second, building upon the Real‐Time DEtection TRansformer (RT‐DETR), a lightweight partial‐rep convolution is designed to decrease the network's parameter count. Simultaneously, the Deformable attention module and the DRBC3 module are introduced to enhance the neck network, thereby improving the model's capability to capture information and enhancing its detection performance. Compared to RT‐DETR, this method reduces the number of model parameters by 38.7%, increases mAP by 1.5%, and achieves a frame rate that is 1.58 times higher than the original model. The experimental results demonstrate that this method can effectively and accurately detect surface defects in aluminium alloy castings, satisfying industrial requirements. [ABSTRACT FROM AUTHOR]

The saline aquifer CCS is a crucial site for carbon storage. Safety monitoring is a key technology for saline aquifer CCS. Current CO2 leakage detection methods include microseismic, electromagnetic, and well-logging techniques. However, these methods face challenges, such as difficulties in determining CO2 migration fronts and predicting potential leakage events; as a result, the formulation of test timing and methods for these safety monitoring techniques are somewhat arbitrary. This study establishes a gas–water two-phase seepage model and solves it using a semi-analytical method to obtain the injection pressure and the derivative curve characteristics of the injection well. The pressure derivative curve can reflect the physical properties of the reservoir through which CO2 flows underground, and it can also be used to determine whether CO2 leakage has occurred, as well as the timing and amount of leakage, based on boundary responses. This study conducted sensitivity analyses on eight parameters to determine the impact of each parameter on the bottom-hole pressure and its derivatives, thereby obtaining the influence of its parameters on different flow stages. The research indicates that, when a steady-state flow characteristic appears at the outer boundary, CO2 leakage will occur. Additionally, the leakage location can be determined by calculating the distance from the injection well. This can guide the placement and measurement of safety monitoring methods for saline aquifer CCS. The method proposed in this paper can effectively monitor the timing, location, and amount of leakage, providing a technical safeguard for promoting CCS technology. [ABSTRACT FROM AUTHOR]

Aiming at the problems of single movement dimension of traditional vibrating screen, low screening efficiency, short life of key parts, etc. Using the randomness of chaotic vibration and the characteristics of reciprocating non-periodic motion, chaotic vibration is applied to the vibrating screen to improve the screening efficiency. A new type of chaotic vibrating screen with one redundant degree of freedom is developed, the dynamic model of the new chaotic vibrating screen is established, the vibration differential equation of the vibrating screen is obtained by the Lagrange method, and its dynamic characteristic diagram is obtained through simulink simulation analysis. Chaotic identification is performed on the time-frequency diagram, phase diagram, Poincare map and Lyapunov exponent diagram obtained from the simulation results. The simulation shows that the Poincre map of the chaotic vibrating screen is scattered and the maximum Lyapunov exponent is positive. The motion output of the new chaotic vibrating screen is chaos Vibration, the research results of the thesis can provide a theoretical basis for the design and application of chaotic vibrating screens.

Aiming at the problems of screen blinding, low screening efficiency and unstable screening performance of traditional vibrating screen in agricultural field, a three degree of freedom adjustable vibrating screen was designed, including leveling device, two degree of freedom excitation system, single degree of freedom excitation system, controller and level monitor.The two degree of freedom excitation system provides reciprocating movement along the x-axis and rotation around the y-axis for the screen disk, while the single degree of freedom excitation system provides reciprocating movement along the y-axis for the screen disk, and the two are connected in series to form a three degree of freedom excitation device.The kinematics simulation of the vibrating screen was carried out by using ADAMS software to verify that the vibrating screen can vibrate with 1～3 degrees of freedom; Based on the discrete element method, the screening process of rice particles on the adjustable three degree of freedom vibrating screen plate was simulated and analyzed, and the experiment was carried out on the prototype.The results show that the screening efficiency of three degree of freedom vibration is 8.8% and 33.4% higher than that of two degree of freedom and single degree of freedom vibration respectively, which solves the problems of less degree of freedom, low screening efficiency and unstable screening performance of traditional vibrating screen.

In the process of applying cold-stretching process to normal pressure vessel, the vessel will undergo two stages of elastic and plastic deformations. If the plastic deformation occurs, the minor change of deformation in the vessel is sensitive to the pressure. Therefore, the reasonable control of the deformation in the vessel is one of the key steps in the cold-stretching process. The resistance strain gauges（RSG） were pasted in the main parts of the vessel to determine the relationship between the elastic deformation of the corresponding position and the cold-stretching pressure applied gradually. In addition, the verification of the reliability of the finite element（FE） analysis was carried out based on strain measuring results. In the plastic deformation stage, the FE was used to analyze the overall deformation law of cylinder, head and around the nozzle of the vessel under the cold-stretching pressure, meanwhile the position where the maximum deformation occurred in each part of the vessel was obtained. The results show that the local maximum deformation of the vessel is 8.24%, which appears inside of the nozzle root, and meets the requirement of local maximum deformation of no more than 10% in the current standards.

Aiming at the problem that the vibration frequency of conventional vibration exciter is small and can not realize the resonance of high stiffness components, Based on the superharmonic vibration characteristics of nonlinear vibration system, designed a nonlinear ultraharmonic vibrator exciter composed of 3 linear springs and 3 nonlinear springs. Established the dynamic model of the nonlinear ultraharmonic vibrator exciter, solved the nonlinear vibration amplitude-frequency characteristic equation by using the multi-scale method, and analyzed the theoretical feasibility of the vibration exciter to achieve third ultraharmonic resonance. Analyzed effects of excitation force amplitude, nonlinear stiffness coefficient and nonlinear damping coefficient on nonlinear vibration amplitude-frequency response. Carried out dynamic simulation of nonlinear ultraharmonic vibrator exciter by using ADAMS, and carried out the vibration experiment of the nonlinear ultraharmonic vibrator exciter. The results show that under the adjustment of the nonlinear spring, the exciter can achieve third ultraharmonic resonance, which verifies the rationality of the design of the nonlinear super-resonant exciter.

Point cloud registration is a crucial technique in photogrammetry, remote sensing, etc. A generalized 3D point cloud registration framework has been developed to estimate the optimal rigid transformation between two point clouds using 3D key point correspondences. However, challenges arise due to the uncertainty in 3D key point detection techniques and the similarity of local surface features. These factors often lead to feature descriptors establishing correspondences containing significant outliers. Current point cloud registration algorithms are typically hindered by these outliers, affecting both their efficiency and accuracy. In this paper, we propose a fast and robust point cloud registration method based on a compatibility graph and accelerated guided sampling. By constructing a compatible graph with correspondences, a minimum subset sampling method combining compatible edge sampling and compatible vertex sampling is proposed to reduce the influence of outliers on the estimation of the registration parameters. Additionally, an accelerated guided sampling strategy based on preference scores is presented, which effectively utilizes model parameters generated during the iterative process to guide the sampling toward inliers, thereby enhancing computational efficiency and the probability of estimating optimal parameters. Experiments are carried out on both synthetic and real-world data. The experimental results demonstrate that our proposed algorithm achieves a significant balance between registration accuracy and efficiency compared to state-of-the-art registration algorithms such as RANSIC and GROR. Even with up to 2000 initial correspondences and an outlier ratio of 99%, our algorithm achieves a minimum rotation error of 0.737° and a minimum translation error of 0.0201 m, completing the registration process within 1 s. [ABSTRACT FROM AUTHOR]

Surface defect inspection methods have proven effective in addressing casting quality control tasks. However, traditional inspection methods often struggle to achieve high-precision detection of surface defects in castings with similar characteristics and minor scales. The study introduces DES-YOLO, a novel real-time method for detecting castings' surface defects. In the DES-YOLO model, we incorporate the DSC-Darknet backbone network and global attention mechanism (GAM) module to enhance the identification of defect target features. These additions are essential for overcoming the challenge posed by the high similarity among defect characteristics, such as shrinkage holes and slag holes, which can result in decreased detection accuracy. An enhanced pyramid pooling module is also introduced to improve feature representation for small defective parts through multi-layer pooling. We integrate Slim-Neck and SIoU bounding box regression loss functions for real-time detection in actual production scenarios. These functions reduce memory overhead and enable real-time detection of surface defects in castings. Experimental findings demonstrate that the DES-YOLO model achieves a mean average precision (mAP) of 92.6% on the CSD-DET dataset and a single-image inference speed of 3.9 milliseconds. The proposed method proves capable of swiftly and accurately accomplishing real-time detection of surface defects in castings. [ABSTRACT FROM AUTHOR]

The accurate extraction of agricultural parcels from remote sensing images is crucial for advanced agricultural management and monitoring systems. Existing methods primarily emphasize regional accuracy over boundary quality, often resulting in fragmented outputs due to uniform crop types, diverse agricultural practices, and environmental variations. To address these issues, this paper proposes DSTBA-Net, an end-to-end encoder–decoder architecture. Initially, we introduce a Dual-Stream Feature Extraction (DSFE) mechanism within the encoder, which consists of Residual Blocks and Boundary Feature Guidance (BFG) to separately process image and boundary data. The extracted features are then fused in the Global Feature Fusion Module (GFFM), utilizing Transformer technology to further integrate global and detailed information. In the decoder, we employ Feature Compensation Recovery (FCR) to restore critical information lost during the encoding process. Additionally, the network is optimized using a boundary-aware weighted loss strategy. DSTBA-Net aims to achieve high precision in agricultural parcel segmentation and accurate boundary extraction. To evaluate the model's effectiveness, we conducted experiments on agricultural parcel extraction in Denmark (Europe) and Shandong (Asia). Both quantitative and qualitative analyses show that DSTBA-Net outperforms comparative methods, offering significant advantages in agricultural parcel extraction. [ABSTRACT FROM AUTHOR]

Castings' surface-defect detection is a crucial machine vision-based automation technology. This paper proposes a fusion-enhanced attention mechanism and efficient self-architecture lightweight YOLO (SLGA-YOLO) to overcome the existing target detection algorithms' poor computational efficiency and low defect-detection accuracy. We used the SlimNeck module to improve the neck module and reduce redundant information interference. The integration of simplified attention module (SimAM) and Large Separable Kernel Attention (LSKA) fusion strengthens the attention mechanism, improving the detection performance, while significantly reducing computational complexity and memory usage. To enhance the generalization ability of the model's feature extraction, we replaced part of the basic convolutional blocks with the self-designed GhostConvML (GCML) module, based on the addition of p2 detection. We also constructed the Alpha-EIoU loss function to accelerate model convergence. The experimental results demonstrate that the enhanced algorithm increases the average detection accuracy (mAP@0.5) by 3% and the average detection accuracy (mAP@0.5:0.95) by 1.6% in the castings' surface defects dataset. [ABSTRACT FROM AUTHOR]