“Reporting or Interpreting?”—A Discoursal Study of Broadcasts on NBA Games in China

From the perspective of empirical discourse analysis, this paper identifies the site broadcasters’ roles and cognitive blending process in NBA (National Basketball Association) broadcasts in China. The authors find that NBA broadcasters chiefly interpret the information they have obtained from sports sites and interviews with the coaches and players, employing various interpreting strategies, such as commentary, amplification, supplementation and restructure. Cognitively, the language that NBA broadcasters applied reveals their cognitive blending process of interpreting techniques, strategies, sports knowledge and attitudes towards the games, of who take up different roles to fulfill different communicating purposes, all of which project various cognitions on NBA games. Despite the fact that one role might make certain linguistic behaviors prevail over the others, especially their interpreting role, NBA site broadcasters coordinate it with other roles properly through which they present different levels of translational and constructional schematicity, thus yielding a coherent and constructional working mode of NBA broadcasting practice in China

Integrin αvβ3-targeted radionuclide therapy combined with immune checkpoint blockade immunotherapy synergistically enhances anti-tumor efficacy.

RATIONALE(#br)Radiotherapy combined with immunotherapy has revealed promising outcomes in both preclinical studies and ongoing clinical trials. Targeted radionuclide therapy (TRT) is a branch of radiotherapy concerned with the use of radioisotopes, radiolabeled molecules or nanoparticles that deliver particulate radiation to cancer cells. TRT is a promising approach in cases of metastatic disease where conventional treatments are no longer effective. The increasing use of TRT raises the question of how to best integrate TRT with immunotherapy. In this study, we proposed a novel therapeutic regimen that combined programmed death ligand 1 (PD-L1)-based immunotherapy with peptide-based TRT (177Lu as the radionuclide) in the murine colon cancer model.(#br)METHODS(#br)To explore the most appropriate timing of immunotherapy after radionuclide therapy, the anti-PD-L1 antibody (αPD-L1 mAb) was delivered in a concurrent or sequential manner when 177Lu TRT was given.(#br)RESULTS(#br)The results demonstrated that TRT led to an acute increase in PD-L1 expression on T cells, and TRT in combination with αPD-L1 mAb stimulated the infiltration of CD8+ T cells, which improved local tumor control, overall survival and protection against tumor rechallenge. Moreover, our data revealed that the time window for this combination therapy may be critical to outcome.(#br)CONCLUSIONS(#br)This therapeutic combination may be a promising approach to treating metastatic tumors in which TRT can be used. Clinical translation of the result would suggest that concurrent rather than sequential blockade of the PD-1/PD-L1 axis combined with TRT improves overall survival and long-term tumor control

Yi Qi Qing Re Gao Attenuates Podocyte Injury and Inhibits Vascular Endothelial Growth Factor Overexpression in Puromycin Aminonucleoside Rat Model

Proteinuria is the hallmark of chronic kidney disease. Podocyte damage underlies the formation of proteinuria, and vascular endothelial growth factor (VEGF) functions as an autocrine/paracrine regulator. Yi Qi Qing Re Gao (YQQRG) has been used to treat proteinuria for more than two decades. The objective of this study was to investigate the protective effect and possible mechanisms of YQQRG on puromycin aminonucleoside (PAN) rat model. Eighty male Sprague-Dawley rats were randomized into sham group, PAN group, PAN + YQQRG group, and PAN + fosinopril group. Treatments were started 7 days before induction of nephrosis (a single intravenous injection of 40 mg/kg PAN) until day 15. 24 h urinary samples were collected on days 5, 9, and 14. The animals were sacrificed on days 3, 10, and 15, respectively. Blood samples and renal tissues were obtained for detection of biochemical and molecular biological parameters. YQQRG significantly reduced proteinuria, elevated serum albumin, and alleviated renal pathological lesions. YQQRG inhibited VEGF-A, nephrin, podocin, and CD2AP mRNA expression and elevated nephrin, podocin, and CD2AP protein levels starting on day 3. In conclusion, YQQRG attenuates podocyte injury in the rat PAN model through downregulation of VEGF-A and restoration of nephrin, podocin, and CD2AP protein expression

A Low-Cost Relative Positioning Method for UAV/UGV Coordinated Heterogeneous System Based on Visual-Lidar Fusion

Unmanned Ground Vehicles (UGVs) and Unmanned Aerial Vehicles (UAVs) are commonly used for various purposes, and their cooperative systems have been developed to enhance their capabilities. However, tracking and interacting with dynamic UAVs poses several challenges, including limitations of traditional radar and visual systems, and the need for the real-time monitoring of UAV positions. To address these challenges, a low-cost method that uses LiDAR (Light Detection and Ranging) and RGB-D cameras to detect and track UAVs in real time has been proposed. This method relies on a learning model and a linear Kalman filter, and has demonstrated satisfactory estimation accuracy using only CPU (Central Processing Unit)- in GPS (Global Positioning System)-denied environments without any prior information

Simulation Research on Cotton Stalk Cutting and Crushing Based on ANSYS/LS-DYNA and Field Experiments

In order to solve the problem of high straw content in recovered residual film and the low rate of qualified straw crushing in combination with a front-mounted cotton-straw-crushing device, the cutting and crushing mechanisms of cotton stalks were studied based on ANSYS/LS-DYNA. The height h and dip angle α of the fixed blade were determined to be 30 mm and 75° through a finite element analysis. On the basis of the device design, explicit dynamic models of the cutting and crushing of a single cotton stalk were established based on ANSYS/LS-DYNA. The results of the dynamic analysis revealed the cutting mechanism of the cotton stalk, and the influences of the cutting edge angle γ and front baffle height h1 on cotton stalk cutting were studied by using single-factor simulation tests. An edge angle of γ = 45° and a height of h1 = 265 mm were determined. Meanwhile, the mechanism of cotton straw crushing was revealed, and the motion states of the straw were studied at different times. The results of the simulation experiments on the influence of the cutter shaft’s rotational speed showed that with an increase in the cutter shaft’s speed, the rate of qualified crushing and the removal rate were both increased. At the design speed of n = 1800 RPM, the rate of qualified crushing was 84.6%, and the removal rate was 95.1%. Then, field experiments were carried out. The test results were as follows: the stubble height was 8.0 cm, the rate of qualified straw crushing was 91.8%, the clearance rate of film-surface impurities was 92.3%, and the film content was 3.6%, which met the working quality requirements (not less than 85%) of NYT 500-2015: “Operating quality for straw-smashing machines”

Research and Experiment on the Removal Mechanism of Light Impurities of the Residual Mulch Film Recovery Machine

Aiming at the problem of high impurity rate in the recycled residual film, combined with the existing installation (4JMLE-210 agricultural residual film recycling machine), the removal mechanism of light impurities on the film surface was analyzed. The statics and kinematics analysis of light impurity particles in different spatial positions were carried out to determine the conditions for the movement of impurity particles. By analyzing critical conditions, such as ideal collision and throwing capacity, the structural dimensions of the straight pipe section and its outlet section were determined. Using Origin 2018 software, the movement track of the impurity particles left from the upper and lower limit positions and the ideal curve of the throwing arc were plotted, and the trapezoidal section was determined at the outlet of the throwing arc section. Finally, trial-produce prototype, and a field test was carried out on the performance of the machine by selecting the impurity rate in the recovered residual film as the test index. The results showed that when the forward speed of the machine and the rotating speed of the cutter roll were in the range of 5.4–5.8 km/h and 1440–1460 r·min−1, the light impurity rate and working efficiency could keep a good balance. The light impurity rate in the recovered residual film was between 10.9% and 31.4%, and the average light impurity rate was around 18.7%, which met the design and application requirements

The Cross-media Publishing Data Model of Map

Aiming at the problem of repeated map production and differences of visual expression effect appeared when the same spatial data are published across different media, the concept of cross-media publishing of map is proposed. Through analyzing the existing map data models and deeply mining the potential advantages of PDF page content objects such as mark content object, logic structure object, optional content object and so on in PDF structure, the point is around the feature object code, the feature object structure and the feature layered structure launched the design of the cross-media publishing data model of map. The model breached the past limit that the map data which satisfies the printing request and geographic spatial data only can be described on different stages or with different models. It creates the conditions for storage and management of the cross-media publishing data of map. After the experimental tests the results show that the model is feasible and effective

Statistical Texture Learning Method for Monitoring Abandoned Suburban Cropland Based on High-Resolution Remote Sensing and Deep Learning

Cropland abandonment is crucial in agricultural management and has a profound impact on crop yield and food security. In recent years, many cropland abandonment identification methods based on remote sensing observation data have been proposed, but most of these methods are based on coarse-resolution images and use traditional machine learning methods for simple identification. To this end, we perform abandonment recognition on high-resolution remote sensing images. According to the texture features of the abandoned land, we combine the method of statistical texture learning and propose a new deep learning framework called pyramid scene parsing network-statistical texture learning (PSPNet-STL). The model integrates high-level semantic feature extraction and deep mining of low-level texture features to identify cropland abandonment. First, we labeled the abandoned cropland area and built the high-resolution abandoned cropland (HRAC) dataset, a high-resolution cropland abandonment dataset. Second, we improved PSPNet by fusing statistical texture learning modules to learn multiple texture information on low-level feature maps and combined high-level semantic features for cropland abandonment recognition. Experiments are performed on the HRAC dataset. Compared with other methods, the proposed model has the best performance on this dataset, both in terms of accuracy and visualization, proving that deep mining of low-level statistical texture features is beneficial for crop abandonment recognition