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Metal rubber, which has the advantages of low density, strong environmental adaptability, and excellent design flexibility, is widely applied in manufacturing industries such as the aerospace, shipping, and automotive industries. Based on the research object of flexible porous metal rubber (FPMR) structures made of high-temperature elastic alloys, this study established a constitutive model for the quasi-static mechanical properties of FPMR structure under ultra-wide temperature range conditions. Firstly, the forming mechanism and the influencing factors of the static stiffness properties of the FPMR micro-structure were analyzed. Then, the theoretical model of the FPMR micro-element spring was established by applying the cylindrical spiral compression spring stiffness theory, and the theoretical model was corrected based on the large deformation theory and numerical analysis methods. A comparative analysis was carried out through the corrected theoretical model and the test results of different test samples. And the results show that the corrected theoretical model can comprehensively reflect the nonlinear quasi-static stiffness characteristics of the FPMR structure in an ultra-wide temperature range. More importantly, by comparison with the prediction models proposed by other scholars, it is proved that the model proposed in this paper has higher prediction accuracy and the goodness of fit R2 is closer to 1, which provides a theoretical basis for the application of metal rubber in flexible support structures under ultra-high temperature environments.

Rosuvastatin (RVS) is an excellent drug with anti-inflammatory and lipid-lowering properties in the academic and medical fields. However, this drug faces a series of challenges when used to treat atherosclerosis caused by hyperhomocysteinemia (HHcy), including high oral dosage, poor targeting, and long-term toxic side effects. In this study, we applied nanotechnology to construct a biomimetic nano-delivery system, macrophage membrane (Møm)-coated RVS-loaded Prussian blue (PB) nanoparticles (MPR NPs), for improving the bioavailability and targeting capacity of RVS, specifically to the plaque lesions associated with HHcy-induced atherosclerosis. In vitro assays demonstrated that MPR NPs effectively inhibited the Toll-like receptor 4 (TLR4)/hypoxia-inducible factor-1α (HIF-1α)/nucleotide-binding and oligomerization domain (NOD)-like receptor thermal protein domain associated protein 3 (NLRP3) signaling pathways, reducing pyroptosis and inflammatory response in macrophages. Additionally, MPR NPs reversed the abnormal distribution of adenosine triphosphate (ATP)-binding cassette transporter A1 (ABCA1)/ATP binding cassette transporter G1 (ABCA1)/ATP binding cassette transporter G1 (ABCG1) caused by HIF-1α, promoting cholesterol efflux and reducing lipid deposition. In vivo studies using apolipoprotein E knockout (ApoE−/−) mice confirmed the strong efficacy of MPR NPs in treating atherosclerosis with favorable biosecurity, and the mechanism behind this efficacy is believed to involve the regulation of serum metabolism and the remodeling of gut microbes. These findings suggest that the synthesis of MPR NPs provides a promising nanosystem for the targeted therapy of HHcy-induced atherosclerosis.

Under hypersonic flight conditions, the optical window external surface of a near-space remote sensing system generates a large thermal load due to aerodynamic friction, resulting in serious additional contact thermal stresses and deformation of the flat window. Consequently, the imaging performance of the optical remote sensing system (ORSS) is reduced. To overcome this issue, a flexible support combination structure (FSCS) for an optical window suitable for ultra-high temperature conditions was developed in this study, which ensures the optical imaging quality requirements of the system. Based on the external thermal environment characteristics of a hypersonic aircraft, an aerothermal simulation model of the aircraft with a window component was established. More importantly, the FSCS was optimized and a thermal–structural model of the window component was established, and the opto-mechanical-thermal analysis method was proposed for the ORSS. Finally, the thermal-optical properties of the deformed window were evaluated. The results show that the optimized window component satisfies the optical imaging design requirements, which guides engineers in ultra-high temperature thermal analysis and optical imaging.

Coal/oil co-processing is an efficient utilization process of coal and heavy oil by coupling direct coal liquefaction with heavy oil hydrogenation conversion. It is an important way for compensating the shortage of oil, balancing the energy structure, and ensuring the national energy security in China. Coal tar, FCC (fluid catalytic cracking) slurry and DCC (deep catalytic cracking) slurry were chosen as oil samples and a sub-bituminous coal was chosen as the coal sample to investigate their co-processing characteristics. The results show that the coal conversion in the co-processing of FCC and coal is the highest, followed by that of DCC and coal, and that of coal tar and coal is the lowest. Further analyses found that the difference of the coal conversion and product composition in coal/oil co-processing is mainly caused by the difference of the aromatic hydrocarbon types and content in the oil samples. The hydrogen donor capacity of the polycyclic aromatic hydrocarbons (PAHs) of the oil samples is the main route to stabilize and protect the free radicals generated in the co-processing technology. The PAHs is favored to combine with the active hydrogen atoms in the reaction system and generated hydrogenated aromatic hydrocarbons, for which has the ability to stabilize the free radicals. It could be deduced from the analysis of the content of the PAHs with 1−5 rings, the FCC with the highest content of 4 ring PAHs has a higher co-processing ability than of the DCC with the highest content of 3 ring PAHs. The aromatic hydrocarbons in coal tar mainly come from the broken bonds of the aromatic structure of the coal, which has good solubility with the coal sample. However, the content of the higher-ring-number PAHs in coal tar is low, and the hydrogen donor capacity is weak, which leads to relatively low coal conversion rate and liquid oil yield when coal tar is co-processed with coal. When FCC and coal tar are mixed as the oil sample for co-processing, the aromatic hydrocarbons in coal tar can ensure the good dispersion of coal, and the higher-ring-number PAHs in FCC slurry can guarantee the hydrogen donor capacity. The synergy of the FCC and coal tar promotes the coal conversion in the coal/oil co-processing.

The detection of the impurity rate in machine-picked seed cotton is crucial for precision agriculture. This study proposes a novel Cotton-YOLO-Seg cotton-impurity instance segmentation algorithm based on the you only look once version 8 small segmentation model (Yolov8s-Seg). The algorithm achieves precise pixel-level segmentation of cotton and impurities in seed cotton images and establishes a detection model for the impurity rate, enabling accurate detection of the impurity rate in machine-picked cotton. The proposed algorithm removes the Pyramid 4 (P4) feature layer and incorporates Multi-Scale Convolutional Block Attention (MSCBCA) that integrates the Convolutional Block Attention Module (CBAM) and Multi-Scale Convolutional Attention (MSCA) into the Faster Implementation of Cross Stage Partial Bottleneck with 2 Convolutions (C2f) module of the feature extraction network, forming a novel C2f_MSCBCA module. The SlimNeck structure is introduced in the feature fusion network by replacing the P4 feature layer with the small-target detection layer Pyramid 2 (P2). Additionally, transfer learning is employed using the Common Objects in Context (COCO) instance segmentation dataset. The analysis of 100 groups of cotton image samples shows that the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE) for impurity rate detection are 0.29%, 0.33%, and 3.70%, respectively, which are reduced by 52.46%, 48.44%, and 53.75% compared to the Yolov8s-seg model. The Precision (P), Recall (R), and mean Average Precision at an intersection over union of 0.5 (mAP@0.5) are 85.4%, 78.4%, and 80.8%, respectively, which are improved by 4.2%, 6.2%, and 6.4% compared to Yolov8s-seg model, significantly enhancing the segmentation performance of minor impurities. The Cotton-YOLO-Seg model demonstrates practical significance for precisely detecting the impurity rate in machine-picked seed cotton.

Introduction: The wear failure of spindle will lead to a decrease in cotton harvesting rate of the cotton picker during field operation and serious wastage.Method: Three types of spindle samples at different installation positions and working areas were obtained through field experiments to explore the wear failure law of spindle hook teeth of cotton picker during field operation. Hardness of hook tooth coating and substrate of spindles were tested, surface and cross-section microstructure of the spindle hook teeth were characterized, and wear area and width of the spindle hook teeth were extracted.Results: Results showed that the hardness of the hook tooth coating is evidently higher than that of the substrate; the average coating hardness of the No. 3 spindle hook teeth reaches the maximum at 1033.6 HV0.1; defects, such as microcracks and micropores, exist in the coating of the three types of spindle hook teeth; and the thickness of the coating is between 70 and 130 μm. The wear area of spindle hook tooth changes exponentially and the wear width changes linearly with the increase of field operation area at the same installation position. The wear area and width of the spindle hook teeth gradually increase with the decrease of the installation height and the wear change of the hook teeth is negatively correlated with the installation height in the same field operation area.Discussion: The wear failure of spindle hook tooth is mainly caused by abrasive, fatigue, and oxidation wear. The results of this study can provide a reference for improving the wear resistance of spindle hook teeth.

Ticks and tick-borne diseases have negative impacts on the health of wild animals including endangered and vulnerable species. The giant panda (Ailuropoda melanoleuca), a vulnerable and iconic flagship species, is threatened by tick infestation as well. Not only can ticks cause anemia and immunosuppression in the giant panda, but also bacterial and viral diseases. However, previous studies regarding tick infestation on giant pandas were limited in scope as case reports from sick or dead animals. In this study, an investigation focusing on the tick infestation of a reintroduced giant panda at the Daxiangling Reintroduction Base in Sichuan, China was conducted. Ticks were routinely collected and identified from the ears of the giant panda from March to September in 2021. A linear model was used to test the correlation between tick abundance and climate factors. All ticks were identified as Ixodes ovatus. Tick abundance was significantly different among months. Results from the linear model showed temperature positively correlated to tick abundance, while air pressure had a negative correlation with tick abundance. To the best of our knowledge, this study is the first reported investigation of tick species and abundance on a healthy giant panda living in the natural environment, and provides important information for the conservation of giant pandas and other species sharing the same habitat.

This paper takes the frame as the research object and explores the vibration characteristics of the frame to address the vibration problem of a 1-MSD straw-crushing and residual film recycling machine in the field operation process, and an accurate identification of the modal parameters of the frame is carried out to solve the resonance problem of the machine, which can achieve cost reduction and increase income to a certain extent. The first six natural frequencies of the frame are extracted by finite element modal identification and modal tests, respectively. The rationality of the modal test results is verified using the comprehensive modal and frequency response confidences. The maximum frequency error of modal frequency results of the two methods is only 6.61%, which provides a theoretical basis for the optimal design of the frame. In order to further analyze the resonance problem of the machine, the external excitation frequency of the machine during normal operation in the field is solved and compared with the first six natural frequencies of the frame. The results show that the first natural frequency of the frame (18.89 Hz) is close to the external excitation generated by the stripping roller (16.67 Hz). The first natural frequency and the volume of the frame are set as the optimization objectives, and the optimal optimization scheme is obtained by using the Optistruct solver, sensitivity method, and grey correlation method. The results indicate the first-order natural frequency of the optimized frame is 21.89 Hz, an increase of 15.882%, which is much higher than the excitation frequency of 16.67 Hz, and resonance can be avoided. The corresponding frame volume is 9.975 × 107 mm3, and the volume reduction is 3.46%; the optimized frame has good dynamic performance, which avoids the resonance of the machine and conforms to the lightweight design criteria of agricultural machinery structures. The research results can provide some theoretical reference for this kind of machine in solving the resonance problem and carrying out related vibration characteristics research.

Target geolocation in long-range oblique photography (LOROP) is a challenging study due to the fact that measurement errors become more evident with increasing shooting distance, significantly affecting the calculation results. This paper introduces a novel high-accuracy target geolocation method based on multi-view observations. Unlike the usual target geolocation methods, which heavily depend on the accuracy of GNSS (Global Navigation Satellite System) and INS (Inertial Navigation System), the proposed method overcomes these limitations and demonstrates an enhanced effectiveness by utilizing multiple aerial images captured at different locations without any additional supplementary information. In order to achieve this goal, camera optimization is performed to minimize the errors measured by GNSS and INS sensors. We first use feature matching between the images to acquire the matched keypoints, which determines the pixel coordinates of the landmarks in different images. A map-building process is then performed to obtain the spatial positions of these landmarks. With the initial guesses of landmarks, bundle adjustment is used to optimize the camera parameters and the spatial positions of the landmarks. After the camera optimization, a geolocation method based on line-of-sight (LOS) is used to calculate the target geolocation based on the optimized camera parameters. The proposed method is validated through simulation and an experiment utilizing unmanned aerial vehicle (UAV) images, demonstrating its efficiency, robustness, and ability to achieve high-accuracy target geolocation.

Understanding cottonseeds’ basic physical parameters and compressive mechanical properties is necessary in seed cotton packing and cottonseed processing. In this study, the basic physical parameters of three cottonseed varieties (Huiyuan 720, Xinluzao 61, and Xinluzao 74) under different moisture contents (6%, 9%, 12%, and 15%) were measured. These parameters include 1000-grain weight, triaxial dimension, and sphericity. The effects of different moisture, varieties, and compression orientation (horizontal and vertical) on the compressive mechanical properties of the cottonseed were studied, and the variance analysis of the experimental data showed that the triaxial dimension, 1000-grain weight, arithmetic mean diameter, and geometric mean diameter of cottonseeds of the same variety increased with an increase in moisture content. Extremely significant differences (p < 0.01) were found in the physical parameters among different varieties. The main factors affecting crushing force and apparent elastic modulus are moisture content, variety, and compression orientation. For deformation, the main factors are moisture content, compression orientation, and variety. Moreover, compression orientation, moisture content, and variety are the main factors affecting failure energy. The results obtained that the crushing force and apparent elastic modulus decreased, deformation increased, and failure energy decreased first and then increased with the increase in moisture content under the same cottonseed variety. The results also provided the basic physical parameters for the design parameter optimization of seed cotton harvesting and processing machinery.

Atherosclerosis is chronic inflammatory disease tightly related with defective efferocytosis of apoptotic cells (ACs) in the plaques. The strategy of efferocytosis reactivation using Atorvastatin (AT) and Metformin (Met) has attracted increasing attention for atherosclerosis treatment. Although these drug-based therapies could stimulate the phagocytic clearance of ACs, the rapid drug clearance and poor bioavailability limited their efficacy. In this study, by co-loading AT and Met into poly(lactic-co-glycolic) acid nanoparticles (PLGA NPs), we developed a biomimetic nanocomplexes for targeted atherosclerosis treatment. Macrophages membrane-coated nanocomplexes efficiently avoided the clearance of NPs from immune system and achieved targeting ability to the atherosclerotic plaques. Moreover, modified hyaluronic acid (HA) delivered NPs into the dysfunctional efferocytic cells of plaques, and achieved the plaques-macrophages-targeted therapy. In vitro results indicated that the biomimetic nanocomplexes reactivated efferocytosis by facilitating macrophages polarization from M1 to M2 phenotype through enhancing ERK5/MerTK pathway and inhibiting cellular senescence through inhibiting p53-p16/pRB pathway. In vivo study indicated that this biomimetic nanocomplexes accumulated in the atherosclerotic plaques, resulting in reduction of necrotic core area and protection against plaque rupture by reactivating efferocytosis. These findings indicated that reactivation of efferocytosis by AT and Met co-delivered nanocomplexes provided a novel promising strategy for targeted atherosclerosis treatment.

Machine-harvested seed cotton was taken as the research object to further clarify its creep performance, minimize its power consumption during the loading process, and obtain a better loading method. The uniaxial compression creep test was carried out using the Instron universal material test bench to apply cyclic loading treatment. The test factors included cyclic loading times, cyclic stress peak, and cyclic loading frequency. The energy consumption curve of the machine-harvested seed cotton during cyclic loading was obtained through OriginPro 2019b software, and its energy change law was analyzed. Creep strain was divided into two parts, namely, initial creep strain and creep strain increment, to elucidate the creep mechanism. The Burgers model was chosen to describe the creep strain increment. Results show that machine-harvested seed cotton exhibits energy consumption hysteresis during cyclic loading. The compression energy rapidly decreases with increasing cyclic loading times and then stabilizes. Meanwhile, the compression energy increases with increasing cyclic stress peak and cyclic loading frequency. The creep strain mechanism is also the same, which first rapidly increases and then levels off. Cyclic loading times, cyclic stress peak, and cyclic loading frequency have different effects on creep strain increment, instantaneous elastic modulus, hysteresis elastic modulus, viscosity coefficient, delay time, and relative deformation index. Finally, disregarding power consumption and interaction, extending the cyclic loading time, and increasing the cyclic stress peak while simultaneously minimizing the cyclic loading frequency can reduce the relative deformation index in the creeping stage. Accordingly, the deformation retention ability in the creep is improved, but the compression energy in the cyclic loading increases. The results can provide theoretical and data support for studying the theoretical basis of the rheological properties of machine-harvested seed cotton, the design of seed cotton baling devices, and the study of bale (mold) forming quality.

This study investigated the impact of compression molding parameters on the post-molding characteristics of machine-harvested seed cotton and aimed to determine the optimal compression molding parameters. The closed compression test of seed cotton and force analysis on a single cottonseed clarified the boundary conditions for cottonseed crushing and the relationship between crushing rate and compressive force. A seed cotton compression test bench facilitated single-factor and four-factor, three-level quadratic regression orthogonal experiments, varying the moisture content, initial density, compression force, and holding time. Variance analysis revealed each factor’s influence on the dimensional stability coefficient. Utilizing Design Expert 13.0.5, the optimal compression molding parameter ranges were identified: 6–11.7% moisture content, 47.87–74.84 kg/m3 initial density, 3–5.32 kN compression force, and 50–239.75 s holding time. Software predictions within this range indicated an optimal cottonseed crushing rate and dimensional stability coefficient of 2.853% and 3.274, respectively. Further verification experiments yielded a cottonseed crushing rate and dimensional stability coefficient of 2.888% and 3.282, respectively, with a maximum error of 3.85%, validating the model and optimized parameters. Therefore, strictly controlling seed cotton compression molding parameters was shown to reduce the cottonseed crushing rate and dimensional stability coefficient. These findings offer crucial theoretical insights for developing seed cotton compression processes and selecting parameters for cotton harvesting and packing devices.

Over the past decade, Unmanned Aerial Vehicles (UAVs) have emerged as essential tools for landslide studies, particularly in on-site investigations. This paper reviews UAV applications in landslide studies, with a focus on static geological characteristics, monitoring temporal and spatial dynamics, and responses post-events. We discuss the functions and limitations of various types of UAVs and sensors (RGB cameras, multi-spectral cameras, thermal IR cameras, SAR, LiDAR), outlining their roles and data processing methods in landslide applications. This review focuses on the UAVs’ roles in landslide geology surveys, emphasizing landslide mapping, modeling and characterization. For change monitoring, it provides an overview of the temporal and spatial evolution through UAV-based monitoring, shedding light on dynamic landslide processes. Moreover, this paper underscores UAVs’ crucial role in emergent response scenarios, detailing strategies and automated detection using machine learning algorithms. The discussion on challenges and opportunities highlights the need for ongoing UAV technology advancements, addressing regulatory hurdles, hover time limitations, 3D reconstruction accuracy and potential integration with technologies like UAV swarms.

In this study, the influence of different ionic composition in aqueous solution on the minerals surface wettability was studied. The differences effect of monovalent ion and divalent ions onto the wettability alteration were studied. The anions were Cl- and SO42-. The SO42- could make the minerals surface more hydrophilic. Besides, the influence of NaCl, MgCl2, CaCl2, Na2SO4, K2SO4 and MgSO4 on the mineral wettability alteration were studied. The results indicated that divalent ions showed significant impact on the minerals wettability alteration, compared with monovalent ion. The reasons were due to the fact that divalent ions showed higher ions adsorption than monovalent ion, and divalent ions have higher effect on compressing the electric double layer. The static contact angle and dynamic contact angle were measured. Different heavy oils were studied, including heavy oil with 100 ppm, heavy oil, heavy oil without resins, heavy oil without asphaltenes. The results showed that the asphaltenes would make it difficult for the heavy oils to liberate from minerals, thus decreasing the oil drops contact angle. Then the resins would decrease the heavy oil contact angles. CaCl2/MgCl2 and K2SO4 have synergistic effect on the change of the minerals surface wettability. Atomic force microscope (AFM) measurement indicated that the ions would effectively decrease the interaction force on the surface of heavy oil-minerals, which was beneficial to the heavy oil liberation. The roughness measurement indicated that the different ions would effectively increase the minerals surface wettability.

Malware classification is a critical task in cybersecurity, as it offers insights into the threats that malware poses to the victim device and helps in the design of countermeasures. For real-time malware classification, due to the high network throughputs of modern networks, there is a challenge of achieving high classification accuracy while maintaining low inference latency. We first introduce two self-attention transformer-based classifiers, SeqConvAttn and ImgConvAttn, to replace the currently predominant Convolutional Neural Network (CNN) classifiers. We then devise a file-size-aware two-stage framework to combine the two proposed models, thereby controlling the tradeoff between accuracy and latency for real-time classification. To assess our proposed designs, we conduct experiments on three malware datasets: the Microsoft Malware Classification Challenge (BIG 2015) and two selected subsets from the BODMAS PE malware dataset, BODMAS-11 and BODMAS-49. We show that our transformer-based designs can achieve better classification accuracy than traditional CNN-based designs. Furthermore, we show that the proposed two-stage framework reduces the average model inference latency while maintaining superior accuracy, thereby fulfilling the requirements of real-time classification.

Cardiovascular disease (CVD) caused by atherosclerosis has become a main threaten for human health. As an independent risk factor, hyperhomocysteinemia (HHcy) played an important role in the pathogenesis of atherosclerosis by regulating DNA methylation modification and autophagy of macrophages. In this study, we constructed a new kind of macro-liposome nanoparticle by hybridizing liposome with macrophages membranes (Møm) to encapsulate hydroxysafflower yellow A (HSYA). Assertion of Hyaluronic acid (HA) on the macro-liposome NPs was adopted to endow nanodrug targeting ability. In vitro results showed that the prepared macro-liposome nanoparticles can significantly inhibit Atg13 DNA methylation, while enhance autophagy of macrophages to promote cholesterol efflux, as well. In vivo studies have shown that the HA modification made the macro-liposome NPs an ideal decoy for targeting plaques. Thus, the macro-liposome NPs with prolonged blood circulation time, and improved targeting ability can achieve optimal HSYA accumulation at the region of atherosclerotic plaques to obtain high efficacy. According to our point, the nano-drug delivery system with high immune escape capability provided a feasible therapeutic strategy for efficient atherosclerosis therapy.

ObjectiveCblC deficiency, the most common cobalamin metabolic abnormality, is caused by pathogenic variants in the MMACHC gene. The renal complications of this disease have been described only in a small number of cases. This study aimed to better delineate renal phenotype and genetic characteristics in Chinese children with cblC defect.MethodsChildren with cblC deficiency who manifested as kidney damage were enrolled. Clinical, renal pathological, and genetic data were reviewed in detail.ResultsSeven cases were enrolled. Ages at disease onset ranged from 9 months to 5 years. All patients presented with hematuria and proteinuria, and 2/7 cases presented with nephrotic syndrome. Renal dysfunction was observed in 4/7 cases. Renal biopsy was performed in 5/7 cases, and all of them had renal thrombotic microangiopathy. Macrocytic anemia was detected in all seven patients. Six out of seven cases had hypertension, and 2/7 cases presented with pulmonary hypertension. Two of them had a mild intellectual disability, and one suffered from epilepsy. Increased urine methylmalonic acid and plasma homocysteine were detected in seven cases, while two patients had normal levels of urine methylmalonic acid at the initial evaluation. After diagnosis, all seven cases were treated with hydroxocobalamin IM. Six cases were followed-up for 3–8 years. After treatments, anemia was the first to be recovered, followed by proteinuria. Renal function recovered after 1 year in two cases, whereas patient 2 progressed to stage 2 chronic kidney disease 13 years after onset. While a case presented with end-stage kidney disease because of late diagnosis, one case died 3 months after disease onset due to giving up treatment. Three MMACHC pathogenic variants c.80A > G (8/14), c.609G > A (4/14), and c.658_660delAAG (2/14) were detected in all seven children.ConclusionMMACHC variant c.80A > G may be associated with prominent renal complications in Chinese cblC patients. Macrocytic anemia and hyperhomocysteinemia are useful clues for patients with hematuria and proteinuria caused by cblC defect. The most frequent renal pathological manifestation is thrombotic microangiopathy. Early diagnosis and treatment resulted in improving renal and hematological signs.

Abstract Background Low temperature freezing stress has adverse effects on wheat seedling growth and final yield. The traditional method to evaluate the wheat injury caused by the freezing stress is by visual observations, which is time-consuming and laborious. Therefore, a more efficient and accurate method for freezing damage identification is urgently needed. Results A high-throughput phenotyping system was developed in this paper, namely, RGB freezing injury system, to effectively and efficiently quantify the wheat freezing injury in the field environments. The system is able to automatically collect, processing, and analyze the wheat images collected using a mobile phenotype cabin in the field conditions. A data management system was also developed to store and manage the original images and the calculated phenotypic data in the system. In this experiment, a total of 128 wheat varieties were planted, three nitrogen concentrations were applied and two biological and technical replicates were performed. And wheat canopy images were collected at the seedling pulling stage and three image features were extracted for each wheat samples, including ExG, ExR and ExV. We compared different test parameters and found that the coverage had a greater impact on freezing injury. Therefore, we preliminarily divided four grades of freezing injury according to the test results to evaluate the freezing injury of different varieties of wheat at the seedling stage. Conclusions The automatic phenotypic analysis method of freezing injury provides an alternative solution for high-throughput freezing damage analysis of field crops and it can be used to quantify freezing stress and has guiding significance for accelerating the selection of wheat excellent frost resistance genotypes.

Salt stress is one of the major environmental stress factors that affect and limit wheat production worldwide. Therefore, properly evaluating wheat genotypes during the germination stage could be one of the effective ways to improve yield. Currently, phenotypic identification platforms are widely used in the seed breeding process, which can improve the speed of detection compared with traditional methods. We developed the Wheat Seed Vigour Assessment System (WSVAS), which enables rapid and accurate detection of wheat seed germination using the lightweight convolutional neural network YOLOv4. The WSVAS system can automatically acquire, process and analyse image data of wheat varieties to evaluate the response of wheat seeds to salt stress under controlled environments. The WSVAS image acquisition system was set up to continuously acquire images of seeds of four wheat varieties under three types of salt stress. In this paper, we verified the accuracy of WSVAS by comparing manual scoring. The cumulative germination curves of wheat seeds of four genotypes under three salt stresses were also investigated. In this study, we compared three models, VGG16 + Faster R-CNN, ResNet50 + Faster R-CNN and YOLOv4. We found that YOLOv4 was the best model for wheat seed germination target detection, and the results showed that the model achieved an average detection accuracy (mAP) of 97.59%, a recall rate (Recall) of 97.35% and the detection speed was up to 6.82 FPS. This proved that the model could effectively detect the number of germinating seeds in wheat. In addition, the germination rate and germination index of the two indicators were highly correlated with germination vigour, indicating significant differences in salt tolerance amongst wheat varieties. WSVAS can quantify plant stress caused by salt stress and provides a powerful tool for salt-tolerant wheat breeding.

IntroductionToxoplasma gondii, a globally zoonotic protozoan parasite, infects most warm-blooded animals including the giant panda, and poses a serious threat to the giant panda conservation. However, the seroprevalence and the risk factors for toxoplasmosis in giant pandas are unknown. Here we aimed to determine the seroprevalence of T. gondii in the captive population of giant pandas and analyze the factors associated with the increased risk of infection.MethodsA total of 203 serum samples were collected from 157 (95 females and 62 males) captive giant pandas from 2007 to 2022, antibodies against T. gondii were screened using commercial ELISA and MAT kits.ResultsThe results showed 56 (35.67%) giant pandas were seropositive, age and transfer history between institutions were identifified as risk factors for T. gondii infection. It is suggested that age-related seroprevalence was the main factor, and housing multiple species in the same environment may increase the chance of cross-infection of T. gondii.DiscussionThis study can provide research data for developing policies for the prevention and control of T. gondii and protecting the health of captive giant pandas and other wildlife.

For traditional imaging systems, high imaging quality and system miniaturization are often contradictory. In order to meet the requirements of high imaging quality and system miniaturization, this paper proposes a method to correct the aberration of coherent imaging optical systems. The method is based on the idea of phase recovery and the imaging principle of a coherent imaging system to recover the aberrations at the exit pupil of the system. According to the recovered aberrations, conjugate filters are constructed to correct the image quality in the frequency domain. The imaging quality of the system is improved without changing the original optical path, and the simplicity of the system is guaranteed. To solve the pupil frequency domain aberration more accurately, this paper adopts the dual competition and parallel recombination strategy based on the genetic algorithm and introduces the disaster model. The improved genetic algorithm can effectively restrain the appearance of the “precocity” phenomenon. Finally, the paraxial imaging optical path is simulated and verified by experiments. The results show that, after aberration correction, the image sharpness is improved and the edge information is richer, which verifies the feasibility of the coherent imaging system image quality enhancement method proposed in this paper.

Volatile organic compounds (VOCs), particularly monoaromatic hydrocarbon compounds (MACHs), pose a potential risk to the atmospheric environment and human health. Therefore, the progressive development of efficient detection methodologies is a pertinent need, which is still a challenge at present. In this study, we present a rapid and sensitive method to detect trace amounts of MACHs using a bifunctional SERS composite substrate. We prepared an Au/SiO2 enhanced layer and a porous Cu(OH)2 adsorption layer via microfluidic-assisted gas-liquid interface self-assembly. The composite substrate effectively monitored changes in benzaldehyde using time-varying SERS spectra, and track-specifically identified various VOCs such as benzene, xylene, styrene, and nitrobenzene. In general, the substrate exhibited a rapid response time of 20 s to gaseous benzaldehyde, with a minimum detection concentration of less than 500 ppt. Further experimental assessments revealed an optimum Cu(OH)2 thickness of the surrounding adsorption layer of 150 nm, which can achieve an efficient SERS response to MACHs. Furthermore, the recoverable and reusable property of the composite substrate highlights its practicality. This study presents a straightforward and efficient approach for detecting trace gaseous VOCs using SERS, with significant implications in the designing of SERS substrates for detecting other VOCs.

Background/objective: Thoracic injuries commonly occur after blunt or penetrating trauma, leading to a blowing wound. For thoracic damage control in emergency, we evaluated a novel chest wound treatment device manufactured using expandable material with a one-way valve, and compared it with closed thoracic drainage for first-line treatment of traumatic pneumothorax in a canine model. Methods: Twenty beagle dogs (10 males and 10 females) were randomly and equally divided into two groups. After arteriovenous catheterization, an open pneumothorax model was established in the beagle dog using a minimally invasive procedure. The experimental group was treated using our test device, while the control group was treated by closed thoracic drainage. Animal survival, oxygen saturation (SO2), oxygen pressure (PO2), and changes in chest radiograph with reference to open pneumothorax before and after intervention were recorded at 30, 60, and 120 min. Results: After a 24-h experimental period, all animals survived. The control group recovered more quickly than the experimental group at 30 min post-trauma. However, the indices were close to normal 120 min after the test device was inserted. During the puncture, chest-wall hemorrhage was stopped by using the device, whereas the control group experienced continual errhysis. The lung had almost re-expanded at the end of the experiment in both groups. The effect of pulmonary re-expansion in the control group was better than that in the experimental group at 120 min. Conclusion: The novel expandable one-way valve device is a safe and useful tool for the treatment of open chest trauma in emergency based on our animal experiment.

Aim: In this study, we examined the effects of branched silicon tube (BST) and temporary closed circle (TCC) in a Beagle dog model of multiple transection of small intestine and discontinuities suspected intestinal necrosis with hemorrhagic shock. Materials and Methods: Ten male Beagle dogs were randomly divided into two groups. Hemorrhagic shock was induced by bleeding. Intestine was severed. Suspected intestinal necrotic model by ligating the mesenteric vessels was established, with a small tertiary mesenteric vessel reserved. Fracted intestines were ligated (IL group, n = 5) or reconnected with BST (IR group, n = 5). The abdominal cavity was temporarily closed with TCC. Definitive surgery was conducted after 24 h. Results: There was no statistical difference between two groups in the weight of dogs, their blood loss, fluid resuscitation, operation time of early emergency treatment (EET). After definitive surgery, all dogs in IR group and 3 dogs in IL groups were alive. 18 (90%) suspicious necrotic intestinal segments in IL group became necrotic, but 20 (80%) segments in IR group didn't develop obvious changes (p

Volatile organic compounds (VOCs) in indoor environments have typical features of multiple components, high concentration, and long duration. The development of gas sensors with high sensitivity to multiple VOCs is of great significance to protect human health. Herein, we proposed a sensitive ZnO/WO3 composite chemi-resistive sensor facilely fabricated via a sacrificial template approach. Based on the transferable properties of self-assembled monolayer colloidal crystal (MCC) templates, two-dimensional honeycomb-like ordered porous ZnO/WO3 sensing matrixes were constructed in situ on commercial ceramic tube substrates with curved and rough surfaces. The nanocomposite thin films are about 250 nm in thickness with large-scale structural consistency and integrity, which facilitates characteristic responses with highly sensitivity and reliability. Furthermore, the nanocomposite sensor shows simultaneous responses to multiple VOCs that commonly exist in daily life with an obvious suppression sensing for traditional flammable gases. Particularly, a detection limit of 0.1 ppm with a second-level response/recovery time can be achieved, which is beneficial for real-time air quality assessments. We proposed a heterojunction-induced sensing enhancement mechanism for the ZnO/WO3 nanocomposite film in which the formation of abundant heterojunctions between ZnO and WO3 NPs significantly increases the thickness of the electron depletion layer in the bulk film and improves the formation of active oxygen species on the surface, which is conducive to enhanced responses for reducing VOC gases. This work not only provides a simple approach for the fabrication of high-performance gas sensors but also opens an achievable avenue for air quality assessment based on VOC concentration detection.

Due to the extreme environmental temperature variations, solutions that enable ultra-low thermal sensitivity in a mirror assembly are crucial for high-performance aerial optical imaging sensors (AOIS). Strategies such as the elimination of the coefficient of thermal expansion (CTE) mismatch and the employment of a flexure connection at the interface cannot be simply duplicated for the application involved, demanding specific design constraints. The contributions of support point number to the surface thermal sensitivity reduction and support stiffness improvement have been studied. A synthetic six-point support system that integrates equally spaced multiple ultra-low radial stiffness mirror flexure units and assembly external interface flexure units has been demonstrated on a 260 mm apertured annular mirror that involves significant CTE mismatch and demanding support stiffness constraint. The surface deformation RMS, due to the 35 °C temperature variation, is 16.7 nm.

Aerial cameras are one of the main devices for obtaining ground images in the air. Since the industrial community sets higher requirements of aerial cameras’ self-locating performance yearly using aerial cameras to locate ground targets has become a research hotspot in recent years. Based on the situation that no ground control point exists in target areas, the calculation principle of the aerial remote sensing image positioning algorithm has been analyzed by establishing different positioning models. Several error analysis models of the positioning algorithm based on the total differential method and the Monte Carlo method are established, and relevant factors that cause the positioning error are summarized. The last section proposes the optimization direction of aerial camera positioning algorithms in the future, which are verified by related simulation experiments. This paper provides a certain degree of guidelines in this area for researchers, who can quickly understand the current development and optimization direction of target geo-location algorithms of aerial remote sensing imagery.

Urban land-use affects surface air temperature; however, the impact of urban land-use on surface air temperature, particularly the extent to which it affects the duration of extreme heat waves, remains uncertain and the mechanisms of diurnal differences need to be further explored. This paper presents study of daytime/nighttime extreme heat waves duration in Beijing under different land-use changes by adopting an index of cumulative hours of extreme heat waves exceeding the certain thresholds. The urban day/night extreme heat waves cumulative hourly interpolation models were established based on high-resolution urban land-use and socioeconomic data and were assessed to have good performance. The annual average cumulative hours of extreme heat waves increased by 95% (daytime) and 116% (nighttime) in 2016–2020 compared to 2011–2015. The cumulative hours for each land-use type ranked as follows: urban land > cropland > water > grassland > woodland. We found that the cumulative hours of extreme heat waves increased significantly with the proportion of urban land and decreased significantly with the proportion of forested land and water. This research provided important information for alleviating extreme heat waves in cities and for rational land planning.

Renal hypodysplasia and cystic kidney diseases, the common non-glomerular causes of pediatric chronic kidney disease (CKD), are usually diagnosed by their clinical and imaging characteristics. The high degree of phenotypic heterogeneity, in both conditions, makes the correct final diagnosis dependent on genetic testing. It is not clear, however, whether the frequencies of damaged alleles vary among different ethnicities in children with non-glomerular CKD, and this will influence the strategy used for genetic testing. In this study, 69 unrelated children (40 boys, 29 girls) of predominantly Han Chinese ethnicity with stage 2–5 non-glomerular CKD caused by suspected renal hypodysplasia or cystic kidney diseases were enrolled and assessed by molecular analysis using proband-only targeted exome sequencing and array-comparative genomic hybridization. Targeted exome sequencing discovered genetic etiologies in 33 patients (47.8%) covering 10 distinct genetic disorders. The clinical diagnoses in 13/48 patients (27.1%) with suspected renal hypodysplasia were confirmed, and two patients were reclassified carrying mutations in nephronophthisis (NPHP) genes. The clinical diagnoses in 16/20 patients (80%) with suspected cystic kidney diseases were confirmed, and one patient was reclassified as carrying a deletion in the hepatocyte nuclear factor-1-beta gene (HNF1B). The diagnosis of one patient with unknown non-glomerular disease was elucidated. No copy number variations were identified in the 20 patients with negative targeted exome sequencing results. NPHP genes were the most common disease-causing genes in the patients with disease onsets above 6 years of age (14/45, 31.1%). The children with stage 2 and 3 CKD at onset were found to carry causative mutations in paired box gene 2 (PAX2) and HNF1B gene (11/24, 45.8%), whereas those with stage 4 and 5 CKD mostly carried causative mutations in NPHP genes (19/45, 42.2%). The causative genes were not suspected by the kidney imaging patterns at disease onset. Thus, our data show that in Chinese children with non-glomerular renal dysfunction caused by renal hypodysplasia and cystic kidney diseases, the common causative genes vary with age and CKD stage at disease onset. These findings have the potential to improve management and genetic counseling of these diseases in clinical practice.

As the popularity of Android smart phones has increased in recent years, so too has the number of malicious applications. Due to the potential for data theft that mobile phone users face, the detection of malware on Android devices has become an increasingly important issue for the field of cyber security. Traditional methods like signature-based routines are unable to protect users from the ever-increasing sophistication and rapid behavior changes in new types of Android malware. Therefore, a great deal of effort has been made recently to use machine learning models and methods to characterize and generalize the malicious behavior patterns of mobile apps for malware detection. In this paper, we propose a novel and highly reliable classifier for Android Malware detection based on a Factorization Machine architecture and the extraction of Android app features from manifest files and source code. Our results indicate that the numerical feature representation of an app typically results in a long and highly sparse vector and that the interactions among different features are critical to revealing malicious behavior patterns. After performing an extensive performance evaluation, our proposed method achieved a test result of 100.00% precision score on the DREBIN dataset and 99.22% precision score with only 1.10% false positive rate on the AMD dataset. These metrics match the performance of state-of-the-art machine-learning-based Android malware detection methods and several commercial antivirus engines with the benefit of training up to 50 times faster.

The spindle is a key core component of a cotton picker, and its operating parameters directly affect the quality of cotton harvesting. In this study, the spindle was selected as the research object. The kinematics and mechanics analysis of the cotton-picking process was conducted, the dynamic motion trajectory of the spindle was obtained, and the working parameters affecting the picking performance of the spindle were determined. A test bench for spindle picking performance was built; the spindle speed and feed speed were used as test factors; the seed cotton rejection rate, picking time, and picking force were used as evaluation indices for spindle picking performance; and a full-factor test was conducted. The range, variance, and regression analyses were conducted on the test results, and the results showed that spindle speed and feed speed had significant effects on seed cotton rejection rate, picking force, and picking time (p < 0.01). The primary and secondary order of factors affecting seed cotton rejection rate and picking time were spindle speed and feed speed, and the primary and secondary order of factors affecting picking force were feed and spindle speed. By comprehensively analyzing the influence of factors on the evaluation indices, the best combination was obtained as the spindle speed and feed speed of 4000 r/min and 1.8 m/s, respectively. The research results have theoretical research value and practical significance for revealing the picking law of spindles when rotating at a high speed and then realizing efficient cotton harvesting.

Surface-enhanced Raman scattering (SERS) provides an unprecedented opportunity for fingerprinting identification and trace-level detection in chemistry, biomedicine, materials, and so on. Although great efforts have been devoted to fabricating sensitive plasmonic nanomaterials, it is still challenging to batch-produce a SERS substrate with high sensitivity, good reproducibility, and perfect recyclability. Here, we describe a facile fabrication of three-dimensional (3D) hierarchical Au/CuS nanocomposites, in which high-density Au nanotips enable highly SERS-active sensing, and the well-defined microflower (MF) geometry produces perfect signal reproducibility (RSD < 5%) for large laser spot excitations (>50 μm2), which is particularly suitable for practical on-site detection with a handheld Raman spectrometer. In addition, a self-cleaning ability of this Au/CuS Schottky junction photocatalyst under sunlight irradiation allows complete removal of the adsorbed analytes, realizing perfect regeneration of the SERS substrates over many cycles. The mass-production, ultra-sensitive, high-reproducibility, and fast-recyclability features of hierarchical Au/CuS MFs greatly facilitate cost-effective and field SERS detection of trace analytes in practice.

As the core component of the cotton picker, the structural characteristics of the spindle directly affect not only its picking performance but also different components of the cotton picker. Therefore, in order to reveal the influence of different angle parameters of hook teeth on the performance of the spindle and the optimal hook tooth angle parameters, this study analyzes the working principle of the picking mechanism of the cotton picker and establishes the force balance equation for the process of picking cotton from the spindle. By analyzing the structural characteristics of the spindle, the best section shape of the spindle head is the equilateral triangle section. The spindle with different angle parameters was made by a metal 3D printer, and the testbed for the dynamic picking performance of the spindle was constructed. The single-factor test was carried out with tooth groove angle before the tooth angle and tooth inclination angle as experimental factors, and the rejection rate of seed cotton, picking time, and picking force as evaluation indexes. The results showed that the tooth groove angle and the tooth inclination angle were negatively correlated with the rejection rate of seed cotton (P < 0.01), and the tooth inclination angle was positively correlated with the picking time (p < 0.01). Further analysis shows that in order to reduce the ejection rate of seed cotton and reduce the picking time, the selection range of the tooth inclination angle should be 55~65°, and the large the tooth groove angle should be selected. Finally, the optimum hook angle parameters are determined as follows: tooth groove angle is 70° before the tooth angle is 89°, and the tooth inclination angle is 65°. The results are of practical significance to optimize the structure of picking hook tooth to improve the picking performance of the spindle and high efficiency of the cotton picker.

Abstract Background To characterize the phenotypic spectrum and assess the antialbuminuric response to angiotensin converting enzyme (ACE) inhibitor and/or angiotensin receptor blocker (ARB) therapy in a cohort of children with Dent disease. Methods The patients’ clinical findings, renal biopsy results, genetic and follow‐up data were analyzed retrospectively. Mutations in CLCN5 or OCRL were detected by next‐generation sequencing or Sanger sequencing. Results Of 31 Dent disease boys, 24 carried CLCN5 and 7 carried OCRL mutations. Low molecular weight proteinuria and albuminuria were detected in all cases. Nephrotic‐range proteinuria and severe albuminuria were identified in 52% and 62% of cases, respectively; by 7 years of age, 6 patients had hematuria and nephrotic‐range proteinuria, and 7 patients had hematuria and moderate to severe albuminuria. In addition to disease‐related renal features, patients with Dent‐1 disease also presented with congenital cataract (1/9) and developmental delay (2/7). Seventeen of 31 patients underwent renal biopsy. Glomerular changes included mild glomerular lesions, mesangial proliferative glomerulonephritis and focal segmental glomerular sclerosis. Thirteen of the 31 patients had follow‐up records and received ACE inhibitor and/or ARB treatment for more than 3 months. After a median 1.7 (range 0.3–8.5) years of treatment, a reduction in the urinary microalbumin‐to‐creatinine ratio was observed in 54% of children. Conclusions Hematuria with nephrotic‐range proteinuria or moderate to severe albuminuria was common in Dent disease patients. Extrarenal manifestations were observed in Dent‐1 patients, which extends the phenotypic spectrum. In addition, ACE inhibitors and ARBs are well tolerated, and they are partially effective in controlling albuminuria.

Spherical Janus micromotors (SJMs) have attracted much attention, and their high-speed motion is highly desired due to their various potential applications. However, the conventional template-deposition method often leads to an active Pt coating with a smooth surface, which is unbeneficial to speed enhancement in terms of catalytic reaction. Here, a facile surface roughening method is presented to fabricate the Pt-polystyrene (PS) SJMs with rough Pt surface (or Ptr-PS SJMs) by plasma-etching the PS colloidal monolayer and then depositing Pt. The Ptr-PS SJMs can exhibit directional motion pushed by the Pt in the various H2O2 solutions, and they show much higher motion speeds than the Pt-PS SJMs with smooth Pt surfaces at the same H2O2 concentration. The Pt-pushed motion is related to the locally asymmetric catalytic reaction of the Pt coating on PS. The speed is also associated with the surface roughness of the Pt coating. The Pt film with a rough surface causes enhanced motion speed due to the improvement of reaction catalytic activity. This work presents a new route to enhancing the motor motion speed, which is of significance in designing micromotors with high-speed motion.

High-precision, real-time, and long-range target geo-location is crucial to UAV reconnaissance and target strikes. Traditional geo-location methods are highly dependent on the accuracies of GPS/INS and the target elevation, which restricts the target geo-location accuracy for LRORS. Moreover, due to the limitations of laser range and the common, real time methods of improving the accuracy, such as laser range finders, DEM and geographic reference data are inappropriate for long-range UAVs. To address the above problems, a set of work patterns and a novel geo-location method are proposed in this paper. The proposed method is not restricted by conditions such as the accuracy of GPS/INS, target elevation, and range finding instrumentation. Specifically, three steps are given, to perform as follows: First, calculate the rough geo-location of the target using the traditional method. Then, according to the rough geo-location, reimage the target. Due to errors in GPS/INS and target elevation, there will be a re-projection error between the actual points of the target and the calculated projection ones. Third, a weighted filtering algorithm is proposed to obtain the optimized target geo-location by processing the reprojection error. Repeat the above process until the target geo-location estimation converges on the true value. The geo-location accuracy is improved by the work pattern and the optimization algorithm. The proposed method was verified by simulation and a flight experiment. The results showed that the proposed method can improve the geo-location accuracy by 38.8 times and 22.5 times compared with traditional methods and DEM methods, respectively. The results indicate that our method is efficient and robust, and can achieve high-precision target geo-location, with an easy implementation.

Seed cotton compression molding solves the inconvenience of seed cotton transportation and storage after mechanical harvesting. Stress relaxation is closely related to the performance of the compressed seed cotton. In this study, an electronic universal testing machine with a homemade compression device was used to study the stress relaxation characteristics of machine-harvested seed cotton. The stress relaxation model of machine-harvested seed cotton was established, the influence of test factors on the response indexes was analyzed and, finally, stress relaxation characteristics of machine-harvested seed cotton were simulated. Results show that machine-harvested seed cotton stress relaxation characteristics can be described by the five-element Maxwell model. The equilibrium elastic modulus is negatively correlated with moisture content and cross-section dimensions, and the equilibrium elastic modulus is positively correlated with trash content and compression density. The rapid decay time and the residual stress ratio are negatively correlated with moisture content and compression density, but the influence of trash content and cross-section dimensions are limited. The stress relaxation process of machine-harvested seed cotton was simulated using virtual prototype technology, and the maximum error between the experimental and simulated values was obtained as 4.96%. The feasibility of the virtual prototype technique for the viscoelastic simulation of biomaterials was demonstrated.

In order to enable the aerial photoelectric equipment to realize wide-area reconnaissance and target surveillance at the same time, a dual-band dynamic scan and stare imaging system is proposed in this paper. The imaging system performs scanning and pointing through a two-axis gimbal, compensating the image motion caused by the aircraft and gimbal angular velocity and the aircraft liner velocity using two two-axis fast steering mirrors (FSMs). The composition and working principle of the dynamic scan and stare imaging system, the detailed scheme of the two-axis FSM and the image motion compensation (IMC) algorithm are introduced. Both the structure and the mirror of the FSM adopt aluminum alloys, and the flexible support structure is designed based on four cross-axis flexural hinges. The Root-Mean-Square (RMS) error of the mirror reaches 15.8 nm and the total weight of the FSM assembly is 510 g. The IMC rate equations of the two-axis FSM are established based on the coordinate transformation method. The effectiveness of the FSM and IMC algorithm is verified by the dynamic imaging test in the laboratory and flight test.

From January 1995 to June 2018, 14 patients with congenital nephrotic syndrome (CNS) were diagnosed in the Department of Pediatrics, Peking University First Hospital. The clinical data were retrospectively studied. Eight patients underwent genetic testing; 7 of them had NPHS1 mutations (primary CNS), and 1 did not have a mutation. Of the 7 patients with NPHS1 mutations, 6 died, and 1 had proteinuria. Of the 14 patients, 8 had cytomegalovirus (CMV) infection, and anti-CMV therapy was administered to 7 of them. The other patient was hospitalized in critically ill condition and died before anti-CMV therapy administration. Of the 7 patients who were administered anti-CMV therapy, proteinuria disappeared in 2 patients; 2 patients died; 2 patients were lost to follow up; and 1 patient still had 3+ proteinuria. Three patients had both NPHS1 mutations and CMV infection. After anti-CMV therapy, proteinuria was resolved in 1 patient but relapsed to 3+ proteinuria due to a new infection. The other 2 patients died. Of 14 patients, only 1 patient underwent renal biopsy, with results showing mesangial proliferative glomerulonephritis pathology, negative CMV inclusion body, and CMV-DNA. In this study, genetic defect could play a primary role in CNS, and CMV could play a secondary role. Primary CNS with NPHS1 mutations has a poor prognosis. Primary CNS might be accompanied by CMV infection that responds poorly to antiviral treatment. Secondary CNS caused by CMV infection may be cured with antiviral therapy. However, genetic analysis is necessary to exclude genetic defects.

Abstract Background The aim of this study was to analyze the diverse phenotypes of children with PAX2‐related disorder so as to improve our understanding of this disease. Methods The clinical data of ten children with PAX2 mutations, detected by targeted region capture sequencing or whole‐exome sequencing, were retrospectively analyzed. Family members of index cases were verified by Sanger sequencing and family segregation analysis was performed. Results The age of first symptom of 10 unrelated children (six girls and four boys) was 6.4 (ranged from postnatal day to 14.8) years old. Proteinuria, abnormal renal function, and structure were found in all patients. Renal hypoplasia and renal cysts were found in 10 of 10 and five of 10 cases, respectively. Three patients progressed to chronic kidney disease stage 5 and the onset age of end‐stage renal disease was 9.8–16.4 years old. PAX2‐related ocular abnormalities were found in five of seven cases and three patients were observed to have more than one ocular findings involved. In addition to diverse renal and ocular findings, new phenotypes including congenital ventricular septal defect, skeletal deformity (fourth metatarsal microsomia), ovarian teratoma, and relatively rare extrarenal manifestations such as growth retardation, gout, and microcephaly were also found. Three novel mutations were reported for the first time. De novo mutations occurred in all patients who were carried out segregation analysis. Patients with the same mutation had different manifestations. PAX2‐related disorder showed remarkable clinical variability and phenotypic heterogeneity. Conclusion We firstly reported skeletal deformity (fourth metatarsal microsomia), ovarian teratoma, and congenital ventricular septal defect as new phenotypes of PAX2‐related disorder which enlarged the phenotypic spectrum. Gout was firstly reported as the onset symptom of PAX2‐related disorder. The diagnosis of PAX2‐related disorder should be considered without family history due to a much higher percentage of De novo mutations.

Genome-edited plants created by genome editing technology have been approved for commercialization. Due to molecular characteristics that differ from classic genetically modified organisms (GMOs), establishing regulation-compliant analytical methods for identification and quantification of genome-edited plants has always been regarded as a challenging task. An editing-site-specific PCR method was developed based on the unique edited sequence in CAO1-edited rice plants. Test results of seven primer/probe sets indicated that this method can identify specific CAO1-edited rice from other CAO1-edited rice and wild types of rice with high specificity and sensitivity. The use of LNA (locked nucleic acid) in a probe can efficiently increase the specificity of the editing-site-specific PCR method at increased annealing temperature which can eliminate non-specific amplification of the non-target. The genome-edited ingredient content in blinded samples at the level of 0.1% to 5.0% was accurately quantified by this method on the ddPCR platform with RSD of

Motion planning is one of the most important technologies for free-floating space robots (FFSRs) to increase operation safety and autonomy in orbit. As a nonholonomic system, a first-order differential relationship exists between the joint angle and the base attitude of the space robot, which makes it pretty challenging to implement the relevant motion planning. Meanwhile, the existing planning framework must solve inverse kinematics for goal configuration and has the limitation that the goal configuration and the initial configuration may not be in the same connected domain. Thus, faced with these questions, this paper investigates a novel motion planning algorithm based on rapidly-exploring random trees (RRTs) for an FFSR from an initial configuration to a goal end-effector (EE) pose. In a motion planning algorithm designed to deal with differential constraints and restrict base attitude disturbance, two control-based local planners are proposed, respectively, for random configuration guiding growth and goal EE pose-guiding growth of the tree. The former can ensure the effective exploration of the configuration space, and the latter can reduce the possibility of occurrence of singularity while ensuring the fast convergence of the algorithm and no violation of the attitude constraints. Compared with the existing works, it does not require the inverse kinematics to be solved while the planning task is completed and the attitude constraint is preserved. The simulation results verify the effectiveness of the algorithm.

In recent years, applications such as marine search and rescue, border patrol, etc. require electro-optical equipment to have both high resolution and precise geographic positioning abilities. The step and stare working based on a composite control system is a preferred solution. This paper proposed a step and stare system composed of two single-axis fast steering mirrors and a two-axis gimbal. The fast steering mirrors (FSMs) realize image motion compensation and the gimbal completes pointing control. The working principle and the working mode of the system are described first. According to the imaging optical path, the algorithm and control flow of the line of sight (LOS) and image motion compensation are developed. The proposed method is verified through ground imaging and flight tests. Under the condition of flight, the pointing accuracy of the target can be controlled within 15 m. The proposed algorithm can achieve effective motion compensation and get high-resolution images. This achieves high resolution and accurate LOS simultaneously.

To improve the accuracy of the geographic positioning of a single aerial remote sensing image, the height information of a building in the image must be considered. Oblique remote sensing images are essentially two-dimensional images and produce a large positioning error if a traditional positioning algorithm is used to locate the building directly. To address this problem, this study uses a convolutional neural network to automatically detect the location of buildings in remote sensing images. Moreover, it optimizes an automatic building recognition algorithm for oblique aerial remote sensing images based on You Only Look Once V4 (YOLO V4). This study also proposes a positioning algorithm for the building target, which uses the imaging angle to estimate the height of a building, and combines the spatial coordinate transformation matrix to calculate high-accuracy geo-location of target buildings. Simulation analysis shows that the traditional positioning algorithm inevitably leads to large errors in the positioning of building targets. When the target height is 50 m and the imaging angle is 70°, the positioning error is 114.89 m. Flight tests show that the algorithm established in this study can improve the positioning accuracy of building targets by approximately 20%–50% depending on the difference in target height.

It is important to clarify the distinct contributions of estrogen/estrogen receptor (ER) and androgen/androgen receptor (AR) signaling and their reciprocal effects on the regulation of hepatic lipid homeostasis. We studied the molecular mechanisms underlying the preventive effects of estradiol (E2), dihydrotestosterone (DHT), or E2+DHT on high-fat diet-induced nonalcoholic fatty liver disease (NAFLD) in an orchidectomized Sprague-Dawley (SD) rat model. E2 is shown to be associated with decreased fatty acid synthesis in hepatic zone 3-specific manner by increasing the phosphorylation of acetyl coenzyme-A carboxylase via an ERα-mediated pathway. DHT is shown to be associated with decreased lipid accumulation and cholesterol synthesis in a hepatic zone 1-specific manner by increasing expression of carnitine palmitotyltransferase1 and phosphorylation of 3-hydroxy-3-methyl-glutaryl-CoA reductase via an AR-mediated pathway. E2+DHT showed an additive positive effect and normalized all three impaired zones of the liver. Gene expression changes in human severe liver steatosis were similar to those of experimental rat NAFLD. Steroids reversed the histopathological NAFLD changes, likely by decreasing fatty acid and cholesterol synthesis and increasing β-oxidation. The diverse steroid effects (ER/AR) on NAFLD prevention in male rats indicate the potential applicability of ER/AR modulators for NAFLD treatment.