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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.

Abstract The elevated level of hydrogen sulfide (H2S) in colon cancer hinders complete cure with a single therapy. However, excessive H2S also offers a treatment target. A multifunctional cascade bioreactor based on the H2S-responsive mesoporous Cu2Cl(OH)3-loaded hypoxic prodrug tirapazamine (TPZ), in which the outer layer was coated with hyaluronic acid (HA) to form TPZ@Cu2Cl(OH)3-HA (TCuH) nanoparticles (NPs), demonstrated a synergistic antitumor effect through combining the H2S-driven cuproptosis and mild photothermal therapy. The HA coating endowed the NPs with targeting delivery to enhance drug accumulation in the tumor tissue. The presence of both the high level of H2S and the near-infrared II (NIR II) irradiation achieved the in situ generation of photothermic agent copper sulfide (Cu9S8) from the TCuH, followed with the release of TPZ. The depletion of H2S stimulated consumption of oxygen, resulting in hypoxic state and mitochondrial reprogramming. The hypoxic state activated prodrug TPZ to activated TPZ (TPZ-ed) for chemotherapy in turn. Furthermore, the exacerbated hypoxia inhibited the synthesis of adenosine triphosphate, decreasing expression of heat shock proteins and subsequently improving the photothermal therapy. The enriched Cu2+ induced not only cuproptosis by promoting lipoacylated dihydrolipoamide S-acetyltransferase (DLAT) heteromerization but also performed chemodynamic therapy though catalyzing H2O2 to produce highly toxic hydroxyl radicals ·OH. Therefore, the nanoparticles TCuH offer a versatile platform to exert copper-related synergistic antitumor therapy.

Tumor metabolic reprogramming requires high levels of adenosine triphosphate (ATP) to maintain treatment resistance, which poses major challenges to chemotherapy and photothermal therapy. Especially, high levels of ATP promote copper ion efflux for limiting the curative effect of cuproptosis. Here, an H2S-responsive mesoporous Cu2Cl(OH)3-loading chemotherapeutic cisplatin (CDDP) was synthesized, and the final nanoparticle, CDDP@Cu2Cl(OH)3-CDs (CDCuCDs), was encapsulated by electrostatic action with carbon dots (CDs). CDCuCDs reacted with overproduction H2S in colon tumor to produce photothermic copper sulfide for photothermal therapy. CDDP was released by lysis to achieve chemotherapeutic effects. Importantly, CDDP elevated H2O2 levels in cells through a cascade reaction and continuously transforms H2O2 into highly cytotoxic •OH through chemodynamic therapy between H2O2 and Cu+, which enables nanoparticles to generate •OH and improve the chemotherapeutic efficacy. Highly toxic •OH disrupts mitochondrial homeostasis, prohibiting it from performing normal energy-supplying functions. Down-regulated ATP inhibits heat shock protein expression, which promotes the therapeutic effect of mild photothermal therapy and reduces the efflux of intracellular copper ions, thus improving the therapeutic effect of cuproptosis. Our research provides a potential therapeutic strategy using overproduction H2S responses in tumors, allowing tumor microenvironment-activated •OH nanogenerators to promote tumor energy remodeling for cancer treatment.

The real-time monitoring of corn yield by a combine harvester is a critical data source for constructing the yield histogram, which significantly benefits precision management and decision-making in modern precision agriculture. While widely used, the current photoelectric sensor-based yield monitoring method has limitations. It detects the corn height on each scraper and calculates the yield through a geometric formula. However, it neglects the noticeable difference in the corn stacking patterns affected by factors such as feeding volume, terrain, and driving speed. This oversight often results in low accuracy and poor stability in the prediction of corn yield, highlighting the need for a more advanced approach. To resolve this, we employ EDEM discrete element simulation to demonstrate the large difference of corn stacking patterns on the scraper of the elevator corresponding to feeding volume. Then, we develop a real-time monitoring system on our self-developed double elevator testing rig for carrying out a composite dataset for training three machine learning algorithm-based models, namely Deep Neural Networks (DNN), Gradient Boosting Machine (GBM), and Random Forest (RF). Importantly, these models have undergone rigorous validation under various feeding volumes, ensuring their robustness and reliability. The auxiliary elevator speed is meticulously set at 150r/min, 225r/min, and 450r/min, providing a comprehensive performance assessment. The results denote that the DNN model performs best and is stable, with a coefficient of determination (R2) of 0.998, root mean square error (RMSE) of 0.526, and mean absolute error (MAE) of 0.425. The paper also performs field experiments to test the proposed three prediction models and the system. The results also denote the DNN-based prediction model’s best performance for the lowest relative error of 2.29% and the highest average accuracy of 97.85%. Consequently, the proposed real-time corn yield monitoring system achieves high accuracy and reliability for the combine harvester applications.

Background With the increasing application of guided endodontics to treat complex root canal treatment, the entire process of root canal treatment has become more precise, reducing damage to tooth structure and improving success rates. However, due to the limitations of the operating space, the use of guided endodontic templates in posterior root canal treatment is less common. This study aims to compare the accuracy and reliability of selective laser melting (SLM) and traditional stereolithography etching (SLA) guided endodontic templates for posterior root canals, providing better treatment strategies for posterior root canal treatment. Methods The teeth were randomly assigned to either SLM or SLA group. Preoperative cone-beam computed tomography (CBCT) and a three-dimensional (3D) scanner were used to establish the 3D root canal system and the accurate occlusal models of the teeth. The virtual access to the canal access was designed using Mimics 19.0 and 3-Matic 11.0. The endodontic access was performed based on either SLM or SLA templates. The accuracy of endodontic preparation was measured in three-dimensions by calculating deviations from planned accesses. The template height and tooth substance loss rates in each group were measured. Results SLM-guided templates have a low average deviation at the entry point and apical portion of the bur of total posterior teeth (including premolars and molars) and individual molars (P < 0.05). Moreover, there was a significant difference in angular deviations and height of template in total posterior teeth and individual molars (P < 0.05). The mean substance loss rate of the SLA group was slightly greater than that of the SLM group, but the difference was not statistically (P > 0.05). Conclusions SLM-guided endodontics provides a more predictable and precise location of root canal orifice for the treatment of posterior teeth.

Objective·To detect the serum levels of high mobility group box 1 (HMGB1) and soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) in patients with multiple injuries at different time points, and to analyze their correlation with disease severity, complications and prognosis.Methods·Ninety-two patients with multiple injuries admitted to the Department of Emergency Medicine of the Suzhou Ninth People′s Hospital from December 2020 to December 2022 were selected. According to the injury severity scores of the patients at admission, the patients were divided into light injury group (n=24), grave injury group (n=58) and severe injury group (n=10). According to whether there was multiple organ dysfunction syndrome (MODS) after admission, the patients were divided into MODS group (n=20) and non-MODS group (n=72). According to the outcome within 28 d after trauma, the patients were divided into death group (n=13) and survival group (n=79). Inflammatory factor indicators in venous blood of patients after admission were detected. Enzyme linked immunosorbent assay (ELISA) was used to detect the serum HMGB1 and sTREM-1 levels at 24 h, 72 h and 7 d after trauma, and the differences of serum HMGB1 and sTREM-1 levels among different groups were analyzed. Multiple Logistic regression was used to analyze the influencing factors of adverse outcomes in patients with multiple injuries. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of HMGB1 and sTREM-1 for adverse outcomes.Results·The levels of HMGB1 and sTREM-1 in the grave injury and severe injury groups were significantly higher than those in the light injury group (P

Abstract In two-dimensional chiral metal-halide perovskites, chiral organic spacers endow structural and optical chirality to the metal-halide sublattice, enabling exquisite control of light, charge, and electron spin. The chiroptical properties of metal-halide perovskites have been measured by transmissive circular dichroism spectroscopy, which necessitates thin-film samples. Here, by developing a reflection-based approach, we characterize the intrinsic, circular polarization-dependent complex refractive index for a prototypical two-dimensional chiral lead-bromide perovskite and report large circular dichroism for single crystals. Comparison with ab initio theory reveals the large circular dichroism arises from the inorganic sublattice rather than the chiral ligand and is an excitonic phenomenon driven by electron-hole exchange interactions, which breaks the degeneracy of transitions between Rashba-Dresselhaus-split bands, resulting in a Cotton effect. Our study suggests that previous data for spin-coated films largely underestimate the optical chirality and provides quantitative insights into the intrinsic optical properties of chiral perovskites for chiroptical and spintronic applications.

Abstract The active-cooling elastomer concept, originating from vascular thermoregulation for soft biological tissue, is expected to develop an effective heat dissipation method for human skin, flexible electronics, and soft robots due to the desired interface mechanical compliance. However, its low thermal conduction and poor adaptation limit its cooling effects. Inspired by the bone structure, this work reports a simple yet versatile method of fabricating arbitrary-geometry liquid metal skeleton-based elastomer with bicontinuous Gyroid-shaped phases, exhibiting high thermal conductivity (up to 27.1 W/mK) and stretchability (strain limit >600%). Enlightened by the vasodilation principle for blood flow regulation, we also establish a hydraulic-driven conformal morphing strategy for better thermoregulation by modulating the hydraulic pressure of channels to adapt the complicated shape with large surface roughness (even a concave body). The liquid metal active-cooling elastomer, integrated with the flexible thermoelectric device, is demonstrated with various applications in the soft gripper, thermal-energy harvesting, and head thermoregulation.

Background: To evaluate the predictive value of sICAM-1 and sP-Selectins in the risk of death in a prospective cohort of adult acute respiratory distress syndrome (ARDS). Methods: Adult ARDS patients were included. Plasma sICAM-1, sP-Selectins, and inflammatory cytokines (TNF-α, IL-1b, IL-6, IL-8, and IL-17A) were detected in ARDS subjects. The correlation between different factors and the potential of sICAM-1 and sP-Selectins as endothelial markers to predict the risk of deathfrom ARDS was analyzed. Results: Plasma sICAM-1 and sP-Selectins were higher in ARDS patients and higher in non-survivors of ARDS. sICAM-1 was significantly correlated with TNF-α, IL-6 and IL-8, and sP-Selectins was also significantly correlated with IL-6 and IL-8. Above the critical values of 245.5 ng/mL (sICAM-1) and 482.5 ng/mL (sP-Selectins), the death of the ARDS population increased. High plasma sICAM-1 and sP-Selectins at ICU admission were independent predictors of death of ARDS patients. Conclusion: sICAM-1 and sP-Selectins can predict the risk of death in critically ill patients with ARDS.

Aiming at the lack of speed variators with large transmission ratio for the chain cold drawing production line, on the basis of the ZSY500-50 three-stage reducer, the technical contradiction existing in the technical system is analyzed using the TRIZ theory, and the invention principles that are conducive to solving the technical contradiction are found in the contradiction matrix table. Under the inspiration of the invention principles, the 50/100 second-speed gear transmission with reasonable and compact structure is designed by adding sliding gears, improving the sliding mechanism and optimizing the shafting layout. The strength calculation of the core components and the mechanical simulation using the Ansys Workbench software show that the core components of the two-speed variator all meet the strength requirements.

In this study, a novel Ho(iii) coordination complex with the chemical composition of [Ho6(acac)4L4(CH3O)6]·xCH3OH (1) has been prepared via using a polydentate Schiff base ligand N′-(2,3-dihydroxybenzylidene) picolinohydrazide (H2L) and a β-diketone (Hacac = acetylacetone) co-ligand, and then successfully loaded with drug omeprazole. Hyaluronic acid, a natural polysaccharide with good biocompatibility, was used as raw material to prepare drug carriers that can be injected into hydrogels based on chemical synthesis method. The internal microstructure of the hydrogel was observed by scanning electron microscope, which showed a good three-dimensional connected porous structure. After the synthesis of the hydrogel, the value of their application in the treatment of pancreatitis was evaluated and the related mechanisms were explored at the same time.

This paper summarized the nursing of a patient with type 2 diabetes mellitus complicated with invasive pulmonary aspergillosis resulting in the formation of a cavity in the upper lobe of the right lung causing hemoptysis. Nurses had closely observe the changes in the patient's condition and carried out comprehensive interventions including hemoptysis care, dietary care, disinfection and isolation, cough and sputum production and oxygen therapy care, Traditional Chinese Medicine nursing, psychological care and health education. Efforts were made to reduce the risk of hemoptysis, control the blood glucose, improve immunity and quality of life of the patient. (本文总结1例2型糖尿病合并侵袭性肺曲霉菌病导致右肺上叶空洞形成致大咯血患者的护理的经验。患入院后密切观察病情变化, 给予咯血护理、饮食护理、消毒隔离、咳嗽咳痰及氧疗护理、中医护理、心理护理以及健康宣教, 降低患者咯血风险, 积极控制血糖, 增强机体抵抗力, 提高生活质量。)

In optimization problems, the principle of symmetry provides important guidance. This article introduces an enhanced NSGA-II algorithm, termed NDE-NSGA-II, designed for addressing multi-objective optimization problems. The approach employs Tent mapping for population initialization, thereby augmenting its search capability. During the offspring generation process, a hybrid local search strategy is implemented to augment the population’s exploration capabilities. It is crucial to highlight that in elite selection, norm selection and average distance elimination strategies are adopted to strengthen the selection mechanism of the population. This not only enhances diversity but also ensures convergence, thereby improving overall performance. The effectiveness of the proposed NDE-NSGA-II is comprehensively evaluated across various benchmark functions with distinct true Pareto frontier shapes. The results consistently demonstrate that the NDE-NSGA-II method presented in this paper surpasses the performance metrics of the other five methods. Lastly, the algorithm is integrated with the DSSAT model to optimize maize irrigation and fertilization scheduling, confirming the effectiveness of the improved algorithm.

The accurate recognition of maize growth stages is crucial for effective farmland management strategies. In order to overcome the difficulty of quickly obtaining precise information about maize growth stage in complex farmland scenarios, this study proposes a Maize Hybrid Vision Transformer (MaizeHT) that combines a convolutional algorithmic structure with self-attention for maize growth stage recognition. The MaizeHT model utilizes a ResNet34 convolutional neural network to extract image features to self-attention, which are then transformed into sequence vectors (tokens) using Patch Embedding. It simultaneously inserts category information and location information as a token. A Transformer architecture with multi-head self-attention is employed to extract token features and predict maize growth stage categories using a linear layer. In addition, the MaizeHT model is standardized and encapsulated, and a prototype platform for intelligent maize growth stage recognition is developed for deployment on a website. Finally, the performance validation test of MaizeHT was carried out. To be specific, MaizeHT has an accuracy of 97.71% when the input image resolution is 224 × 224 and 98.71% when the input image resolution is 512 × 512 on the self-built dataset, the number of parameters is 15.446 M, and the floating-point operations are 4.148 G. The proposed maize growth stage recognition method could provide computational support for maize farm intelligence.

With the continuous progress of image processing technology and deep neural networks, image style conversion has a wide range of applications in game production. This paper focuses on the application of silk screen printmaking technology in animation game production, using the DiracNet algorithm to express the features of image data, to realize the feature extraction of silk screen printmaking, and add attention mechanism and auxiliary classifier on the AnimeGANv2 model for improvement, to complete the style migration process of silk screen printmaking in animation game production, and to complete the silk screen printmaking technology’s pattern recognition and automatic rendering. Through the key point matching test of the model and the subjective and objective quantitative evaluation of the style migration of screen prints, the model is mined for its effect in pattern recognition and automatic rendering of screen prints technology. The model in this paper has better performance in feature extraction in multi-scenes, and the matching scores and mAP values are improved by 7.14%~25.82% and 11.51%~35.14% over the comparison algorithms, respectively. Most of the SSIM values of the sample screen print style migration images are greater than 0.3, and the overall aesthetic and migration effect evaluations are greater than 3.5. The model in this paper is capable of recognizing screen print patterns and auto-rendering effects, and it has a wide range of potential applications in the production of animation games.

The retention of rural teachers is crucial not only for enhancing the quality of education in rural areas but also for the cultivation of talent and broader social development. This article conducts a detailed analysis of rural teachers’ willingness to remain in their positions by constructing and comparing various statistical models, including multi-level linear models and logistic regression models. Based on the results of model fitting, it specifically derives a logistic regression model that identifies the factors influencing rural teachers’ intentions to stay at the conclusion of their terms. Finally, 250 rural teachers as a survey research object, using the research method of this paper to analyze and explore. After the study, it is concluded that social support will have a significant positive impact on the willingness to stay when B = 0.121, 95% confidence interval is [0.298, 0.434], β = 0.532, t = 18.326, p < 0.001. Work pressure and working hours negatively predicted rural teachers’ willingness to stay in the profession, while social support positively predicted rural teachers’ desire to remain in the profession. The higher the level of social support, the higher the degree of recognition of rural teachers’ profession in the family, school, and society.

Accurate analysis of the strength of steel-fiber-reinforced concrete (SFRC) is important for ensuring construction quality and safety. Cube compression and splitting tensile tests of steel fiber with different varieties, lengths, and dosages were performed, and the effects of different varieties, lengths, and dosages on the compressive and splitting properties of secondary concrete were obtained. It was determined that the compression and splitting strengths of concrete could be effectively improved by the addition of end-hooked and milled steel fibers. The compressive and splitting strengths of concrete can be enhanced by increasing the fiber length and content. However, concrete also exhibits obvious uncertainty owing to the comprehensive influence of steel fiber variety, fiber length, and fiber content. In order to solve this engineering uncertainty, the traditional RBF neural network is improved by using central value and weight learning strategy especially. On this basis, the RBF fuzzy neural network prediction model of the strength of secondary steel fiber-reinforced concrete was innovatively established with the type, length and content of steel fiber as input information and the compressive strength and splitting tensile strength as output information. In order to further verify the engineering reliability of the prediction model, the compressive strength and splitting tensile strength of steel fiber reinforced concrete with rock anchor beams are predicted by the prediction model. The results show that the convergence rate of the prediction model is increased by 15%, and the error between the predicted value and the measured value is less than 10%, which is more efficient and accurate than the traditional one. Additionally, the improved model algorithm is efficient and reasonable, providing technical support for the safe construction of large-volume steel fiber concrete projects, such as rock anchor beams. The fuzzy random method can also be applied to similar engineering fields.

In the context of the comprehensive implementation of rural revitalization strategy, ecological protection and sustainable territorial spatial pattern are important elements of spatial planning and ecological civilization construction. With this as the starting point, this paper can use spatial analysis, hierarchical analysis, entropy method, integrated learning and other technical methods to divide the national spatial evaluation units under the MOLA model. Carry out spatial suitability evaluation of national land based on double constraints as well as spatial planning and design. The test results show that the villagers’ trust in the implementation of rural revitalization policies reached 78%, and most of them agree more with various policies on rural construction and development, which illustrates the necessity of territorial spatial planning in rural revitalization. The research data have good score validity when the observed variable of the questionnaire under the experimental test is greater than 0.4, which indicates the spatial planning layout under the proposed model. On the basis of mastering the current situation and problems facing rural revitalization, it not only proposes an effective path, but also scientifically adjusts and optimizes the space of rural areas, providing a boost to promote the construction and sustainable and healthy development of new rural areas.

Graphite materials，as the commonly used materials in the hot field of single crystal furnace，directly affect the growth rate and quality of single crystal silicon.The use of C/C composite materials instead of graphite materials in a single crystal furnace has defect that are prone to oxidation.Therefore，Ni coatings were prepared on the surface of the C/C composite materials using electroplating methods.Using orthogonal experiments to determine the optimal electroplating test parameters.The phase composition，microscopic morphology，and chemical composition of the coating were analyzed by X-ray diffractometer，scanning electron microscope，EDS and other testing methods.Besides，the thermal shock resistance of the prepared coating was investigated using thermal shock experiments and thermal shock resistance experiments.Results showed that under the conditions of current density of 0.4 A/dm2，electroplating time of 40 min，plating solution temperature of 55 ℃，and pH value of 6，the prepared coating had the best wear resistance.After plating treatment，a uniform and rounded coating which was tightly bonded to the fiber surface was formed on the surface of the C/C composite materials.There was a large amount of Ni in the composition of the film.Furthermore，Ni coating improved the high temperature oxidation resistance of C/C composite materials.

Mucopolysaccharidosis is a series of rare diseases where a lack of an enzyme affecting mucopolysaccharides metabolism in the patients′ lysosome induces the intracellular deposition of the mucopolysaccharides, and causes ocular and organ-related complications. Ocular complications included corneal opacity, glaucoma, ametropia, strabismus, and chorioretinopathy. This review summarizes the mechanisms, clinical manifestations, specific ophthalmological examinations, and treatments for offering the ophthalmological knowledge to diagnose and begin treatment earlier.

An innovative framework for peach tree disease recognition and segmentation is proposed in this paper, with the aim of significantly enhancing model performance in complex agricultural settings through deep learning techniques and data fusion strategies. The core innovations include a tiny feature attention mechanism backbone network, an aligned-head module, a Transformer-based semantic segmentation network, and a specially designed alignment loss function. The integration of these technologies not only optimizes the model’s ability to capture subtle disease features but also improves the efficiency of integrating sensor and image data, further enhancing the accuracy of the segmentation tasks. Experimental results demonstrate the superiority of this framework. For disease detection, the proposed method achieved a precision of 94%, a recall of 92%, and an accuracy of 92%, surpassing classical models like AlexNet, GoogLeNet, VGGNet, ResNet, and EfficientNet. In lesion segmentation tasks, the proposed method achieved a precision of 95%, a recall of 90%, and an mIoU of 94%, significantly outperforming models such as SegNet, UNet, and UNet++. The introduction of the aligned-head module and alignment loss function provides an effective solution for processing images lacking sensor data, significantly enhancing the model’s capability to process real agricultural image data. Through detailed ablation experiments, the study further validates the critical role of the aligned-head module and alignment loss function in enhancing model performance, particularly in the attention-head ablation experiment where the aligned-head configuration surpassed other configurations across all metrics, highlighting its key role in the overall framework. These experiments not only showcase the theoretical effectiveness of the proposed method but also confirm its practical value in agricultural disease management practices.

BackgroundLaser simulation technology is widely used in the research of transient ionizing radiation effects in semiconductor devices. Fully dielectrically isolated silicon-on-insulator (SOI) devices exhibit different responses to dose-rate gamma irradiation compared to bulk-Si devices.PurposeThis study aims to examine the photocurrents of both Si-based and SOI NMOS transistors, and investigate the performance of a SOI MCU with varying dose rates.MethodAn irradiation experiment was conducted on three types of transistors by using a 1 064 nm/12 ns laser device, and the photocurrent was tested under various laser energies. A pulsed γ-ray source was employed to perform the transient γ dose rate radiation test on an SOI-integrated circuit. The function, electrical parameters, and flipflop chain status of the SOI-integrated circuit under different dose rates were measured. Based on theoretical model for the generation of photocurrent in SOI transistor, the dose-rate threshold for logic flipping and corresponding critical charge were estimated based on theoretical model for the generation of photocurrent in SOI transistor.ResultsThe results indicate that the peak photocurrent of the SOI transistor is approximately 20 times lower than that of the bulk silicon transistor with the same feature size under identical irradiation conditions. This reduction is attributed to the decreased charge collection sensitive area of the SOI transistor. Within a dose rate range from 1.0×109 rad(Si)·s-1 to 4.2×1011 rad(Si)·s-1, the SOI-integrated circuit exhibites no latch-up effect. However, irradiation-induced upsets are observed in the SOI-integrated circuit.ConclusionsThese upsets caused by transient radiation effects manifest as transient functional interruptions, variations in operating current and voltage, and erroneous flip-flop statuses. These irradiation-induced upsets in the SOI-integrated circuit are likely attributable to, among other factors, transistor upsets and circuit-level voltage fluctuations on printed circuit board.

Micro-arc oxidation films were prepared on the surface of SiCp/Al matrix composites in (NaPO3)6, Na2SiO3-NaOH and NaAlO2-NaOH electrolyte.The microstructure and phase composition of the films were characterized by scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD).The wear resistance and corrosion resistance of the substrate and films were analyzed by friction and wear test and electrochemical workstation. The results show that the uniform micro-arc oxidation films can be prepared in all the three electrolytes. The roughness and thickness of the film prepared in NaAlO2-NaOH is the largest. The phases of the films prepared in the three electrolytes are different. The microhardness of SiCp/Al matrix composites is improved by micro-arc oxidation, and the hardness of the film prepared in NaAlO2-NaOH reaches 1125HV. The friction coefficient of SiCp/Al matrix composites is reduced by micro-arc oxidation. According to the friction coefficient and wear condition, the film prepared in NaAlO2-NaOH has excellent wear resistance. The micro-arc oxidation film prepared in three kinds of electrolyte can improve the corrosion resistance of SiCp/Al matrix composites. The corrosion resistance of the film prepared in Na2SiO3-NaOH is excellent, the corrosion potential and current density of the film prepared in Na2SiO3-NaOH are -0.6122 V and 2.704×10-7 A·cm-2, respectively.

Abstract Mixed-space cluster expansion (MSCE), a first-principles method to simultaneously model the configuration-dependent short-ranged chemical and long-ranged strain interactions in alloy thermodynamics, has been successfully applied to binary FCC and BCC alloys. However, the previously reported MSCE method is limited to binary alloys with cubic crystal symmetry on a single sublattice. In the current work, MSCE is generalized to systems with multiple sublattices by formulating compatible reciprocal space interactions and combined with a crystal-symmetry-agnostic algorithm for the calculation of constituent strain energy. This generalized approach is then demonstrated in a hypothetical HCP system and Mg-Zn alloys. The current MSCE can significantly improve the accuracy of the energy parameterization and account for all the fully relaxed structures regardless of lattice distortion. The generalized MSCE method makes it possible to simultaneously analyze the short- and long-ranged configuration-dependent interactions in crystalline materials with arbitrary lattices with the accuracy of typical first-principles methods.

For low-illumination video sequences, some existing enhancement algorithms have some problems, such as image over-enhancement, color distortion, and inadequate detail processing. Based on luminance detection, we add logarithmic tone mapping to optimize the existing algorithms. The color space of low-illumination video image is converted from the red, green, blue mode to the hue-saturation-intensity mode, and then, logarithmic tone enhancement is applied to the image. Algorithm in this study has an obvious effect on image luminance enhancement and details processing, which makes the low-illumination video show a clear image with more natural visual effect, thus improving the quality of low-illumination video. This algorithm can avoid the problems of overexposure, color distortion, and blurring of detail processing under low illumination. The infrared spectrum of the object can be captured by infrared detection equipment, and the purpose of image enhancement can be achieved by applying the infrared spectrum of the object.

In the manned space flight mission, the ground commanders and medical experts shall timely grasp the physiological conditions of astronauts in the cabin to ensure the safety of them. The heart rate and respiratory rate of astronauts are important physiological indexes to evaluate the health status of astronauts. How to calculate the heart rate and respiratory rate of astronauts quickly and accurately is one of the difficult problems faced by engineering tasks. Comprehensively considering the computing power under the condition of domestic autonomous controllable software and hardware, this paper presents a heart rate calculation R-wave detection algorithm based on self-learning threshold, and the zero-detection algorithm of respiratory rate calculation, and also designs a set of visual display software of heart rate and respiratory rate. It improves the real-time and accuracy of astronauts′ physiological data processing, and provides intuitive and reliable decision-making basis for the commanders and experts. The calculation and analysis of data shows that the algorithm has high accuracy and low computational requirements. It can meet the needs of medical support and medical supervision for astronauts in the waiting and ascending stages.

Abstract Sustainable intensification needs to optimize irrigation and fertilization strategies while increasing crop yield. To enable more precision and effective agricultural management, a bi-level screening and bi-level optimization framework is proposed. Irrigation and fertilization dates are obtained by upper-level screening and upper-level optimization. Subsequently, due to the complexity of the problem, the lower-level optimization uses a data-driven evolutionary algorithm, which combines the fast non-dominated sorting genetic algorithm (NSGA-II), surrogate-assisted model of radial basis function and Decision Support System for Agrotechnology Transfer to handle the expensive objective problem and produce a set of optimal solutions representing a trade-off between conflicting objectives. Then, the lower-level screening quickly finds better irrigation and fertilization strategies among thousands of solutions. Finally, the experiment produces a better irrigation and fertilization strategy, with water consumption reduced by 44%, nitrogen application reduced by 37%, and economic benefits increased by 7 to 8%.

As a fruit with high economic value, strawberry has a short ripeness period, and harvesting at an incorrect time will seriously affect the quality of strawberries, thereby reducing economic benefits. Therefore, the timing of its harvesting is very demanding. A fine ripeness recognition can provide more accurate crop information, and guide strawberry harvest management more timely and effectively. This study proposes a fine recognition method for field strawberry ripeness that combines deep learning and image processing. The method is divided into three stages: In the first stage, self-calibrated convolutions are added to the Mask R-CNN backbone network to improve the model performance, and then the model is used to extract the strawberry target in the image. In the second stage, the strawberry target is divided into four sub-regions by region segmentation method, and the color feature values of B, G, L, a and S channels are extracted for each sub-region. In the third stage, the strawberry ripeness is classified according to the color feature values and the results are visualized. Experimental results show that with the incorporation of self-calibrated convolutions into the Mask R-CNN, the model’s performance has been substantially enhanced, leading to increased robustness against diverse occlusion interferences. As a result, the final average precision (AP) has improved to 0.937, representing a significant increase of 0.039 compared to the previous version. The strawberry ripeness classification effect is the best on the SVM classifier, and the accuracy under the combined channel BGLaS reaches 0.866. The classification results are better than common manual feature extraction methods and AlexNet, ResNet18 models. In order to clarify the role of the region segmentation method, the contribution of different sub-regions to each ripeness is also explored. The comprehensive results demonstrate that the proposed method enables the evaluation of six distinct ripeness levels of strawberries in the complex field environment. This method can provide accurate decision support for strawberry refined planting management.

Abstract To improve the thermal properties of thermite safely and stably, electrostatic spraying was used to prepare the Al/MoO3 thermite. The Al/MoO3 thermites were detected and characterized by scanning electron microscopy (SEM) and X‐ray diffraction (XRD), and thermal decomposition experiments were carried out by differential scanning calorimetry (DSC). The heat release of the Al/MoO3 thermite prepared by the electrostatic spray (1044 J g−1) is significantly higher than that of the thermite prepared by the ultrasonic (692 J g−1), which is due to more uniform dispersion between Al and MoO3. The initial reaction temperature and activation energy (Ea) of the former keep it steady. Electrostatic spray ensures the safety and stability of the Al/MoO3 thermite. This study provides a new idea for safely and stably improving the thermal properties of thermite by enhancing surface homogenization, which is of great significance for practical applications.

The long noncoding RNA DARS-AS1 was aberrantly expressed and participated in several human cancer progressions, whereas whether DARS-AS1 is involved in human gastric cancer remains unclear. This study aimed to investigate the influence of DARS-AS1 on gastric cancer progression and explore the potential regulatory network of DARS-AS1/miR-330-3p/NAT10. The expression levels of DARS-AS1, miR-330-3p, and NAT10 were measured by quantitative real-time polymerase chain reaction. The CCK-8 assay and Transwell assay were used to determine the cell viability, migration, and invasion capacities, respectively. The target association between miR-330-3p and DARS-AS1 or NAT10 was confirmed using a luciferase reporter assay. In result, DARS-AS1 levels were elevated in tumor tissues and associated with shorter overall survival in patients with gastric cancer. Knockdown of DARS-AS1 could hamper cell viability, migration, and invasion in gastric cancer cells. DARS-AS1 acts as a competitive endogenous RNA to regulate the NAT10 expression by sponging miR-330-3p in gastric cancer cells. In conclusion, DARS-AS1 was elevated in gastric cancer, and DARS-AS1/miR-330-3p/NAT10 signaling offered some new horizons for predicting prognosis and a novel therapeutic method for the treatment of gastric cancer.

Intervertebral disc degeneration (IVDD) is a general disorder that results in low back pain and disability among many affected individuals. However, the current treatments for IVDD are limited to relieving the symptoms but do not solve the fundamental issue. In this study, the role of USP14 in mediating the activation of the NLRP3 inflammasome and the pyroptosis of AF cells from IVDD patients is determined in vitro, and gain- and loss-of-function assays of USP14 and the NLRP3 inflammasome are conducted. Pyroptosis of AF cells is detected by flow cytometry. The inflammatory cytokines (IL-1β and IL-18) and protein levels of NLRP3, active Caspase-1, Aggrecan, MMP3 and ADAMTS-5 are determined by ELISA and western blot analysis, respectively. The correlation between USP14 and NLRP3 is measured by coimmunoprecipitation and ubiquitination analysis. Upregulation of USP14 is accompanied by increased level of the NLRP3 inflammasome in AF cells from IVDD patients; furthermore, a positive correlation between them is observed. USP14 knockdown inhibits pyroptosis in AF cells by inducing ubiquitination of NLRP3, while overexpression of USP14 has the opposite effect, which is inhibited by the NLRP3 inflammasome inhibitor INF39. USP14 exerts its positive regulatory effect on AF cell pyroptosis by modulating the NLRP3/Caspase-1/IL-1β and IL-18 signaling axes.

The low-velocity impact and compression after the impact of the composite stiffened panels were carried out after damp-heat aging. The experimental results show that reinforcing the ribs can enhance the impact resistance of test pieces after damp-heat aging. After impacting, the specimens were tested in an axial compression. The results show that the ultimate bearing capacity of the specimen is also affected by different located positions of the impact and different aging times. Compared with the intact specimen, the ultimate load-bearing capacity was reduced to 16.83, 12.10, and 17.10% with the specimen aging for 0, 45, and 90 days, respectively, while the impact position located at the intersection of longitudinal and transverse bars has the greatest influence on the damp-heat aging of specimens.

This paper aimed to investigate the extraction process of total flavonoids and triterpenes in Inonotus obliquus by ultrasound-assisted enzymatic extraction. The UV spectrophotometric method was used as the detection method, the extraction rate of total triterpenes and flavonoids was used as the evaluation index, the effects of enzyme addition, enzymatic digestion time, liquid to material ratio and ethanol concentration on the extraction rate were investigated, and the best extraction process was obtained by NSGA-II genetic algorithm combined with response surface analysis. Finally, the main chemical components in Inonotus obliquus were analyzed and identified using ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). The optimal extraction process for simultaneous extraction of total triterpenes and flavonoids from Inonotus obliquus was obtained by the Pareto front surface B region scheme, and the optimal extraction conditions were determined as enzyme addition of 1.9%, enzymatic digestion time of 45 min, liquid to material ratio of 20 mL/g, and ethanol concentration of 64%. The average extraction rates of total triterpenes and flavonoids were 2.670%±0.05% and 5.356%±0.09%, and the relative errors were 0.75% and 0.70% with the predicted average extraction rates. It was identified that Inonotus obliquus contained four active ingredients: Betulin, lanosterol, osmundacetone and quercetin. The above proved that the test indexes of NSGA-II genetic algorithm combined with response surface optimization of Inonotus obliquus fungus extraction process fitted well with the predicted results.

ObjectiveTo investigate effect of conducting training of autism spectrum disorder （ASD） early screening skill on improving the ability to early identify ASD of medical staffs in primary care hospitals.MethodsIn September 2021， the training of ASD early screening skills was carried out for medical staffs from 20 primary care hospitals in Chengdu. After training， the training effect was evaluated. The numbers of referrals from primary care hospitals to superior hospitals， confirmed ASD as well as their average diagnostic age of children with ASD before and after training were used as evaluation indicators.ResultsAfter training， the number of children with suspected ASD referred by primary care hospitals was more than that before training ［（16.65±11.60） vs. （3.40±2.23）， t=5.431， P

The laser quenching treatment of 42CrMo steel surface was carried out with a RFL - C3300 fiber laser, and the relations between the microstructure, hardness, depth, wear resistance of the hardened layer and the laser process parameters were analyzed by scanning electron microscope, optical microscope, stereomicroscope, vickers hardness tester and vertical universal friction and wear tester. Results showed that after laser quenching, the surface microstructure of the sample was refined, and the surface hardness and wear resistance were improved. When the laser power was 2 200 W, the scanning speed was 20 mm/s and the spot size was 12 mm × 2 mm, the surface microstructure of the sample was composed of fine martensites, a small amount of retained austenites and dispersed fine carbides. The average surface hardness reached 660 HV2 N, which was about 2.6 times that of the matrix. The friction coefficient stabilized at 0.4～0.6, which was about 25% lower than that of the matrix. The wear amount was 0.5 mg, which was 23.8% of that of the matrix.

Contactless and non-destructive measuring tools can facilitate the moisture monitoring of bagged or bulk grain during transportation and storage. However, accurate target recognition and size prediction always impede the effectiveness of contactless monitoring in actual use. This paper developed a novel 3D reconstruction method upon multi-angle point clouds using a binocular depth camera and a proper Yolo-based neural model to resolve the problem. With this method, this paper developed an embedded and low-cost monitoring system for the in-warehouse grain bags, which predicted targets’ 3D size and boosted contactless grain moisture measuring. Identifying and extracting the object of interest from the complex background was challenging in size prediction of the grain silo-bag on a conveyor. This study first evaluated a series of Yolo-based neural network models and explored the most appropriate neural network structure for accurately extracting the grain bag. In point-cloud processing, this study constructed a rotation matrix to fuse multi-angle point clouds to generate a complete one. This study deployed all the above methods on a Raspberry Pi-embedded board to perform the grain bag’s 3D reconstruction and size prediction. For experimental validation, this study built the 3D reconstruction platform and tested grain bags’ reconstruction performance. First, this study determined the appropriate positions (−60°, 0°, 60°) with the least positions and high reconstruction quality. Then, this study validated the efficacy of the embedded system by evaluating its speed and accuracy and comparing it to the original Torch model. Results demonstrated that the NCNN-accelerated model significantly enhanced the average processing speed, nearly 30 times faster than the Torch model. The proposed system predicted the objects’ length, width, and height, achieving accuracies of 97.76%, 97.02%, and 96.81%, respectively. The maximum residual value was less than 9 mm. And all the root mean square errors were less than 7 mm. In the future, the system will mount three depth cameras for achieving real-time size prediction and introduce a contactless measuring tool to finalize grain moisture detection.

The effects of pre-rolling and pre-stretching deformation on microstructure, mechanical properties and corrosion behavior of Al-Cu-Li alloy in subsequent peak-aging were investigated by means of microstructure observation with mechanical and intergranular properties tests. The test results show that the pre-deformation treatment before aging promotes the precipitation of a large number of uniform and fine T1 phase with dispersed distribution in the alloy grain, and reduces the number of precipitates on the grain boundary, so as to improve the comprehensive mechanical properties of the alloy. In addition, this precipitate microstructure can balance the potential difference between the grain boundary and the grain interior, reduce the intergranular corrosion sensitivity of the alloy, reduce the corrosion rate and enhance the intergranular corrosion resistance of the alloy.

Though ionic liquids (ILs) are considered potential materials for CO2 capture because of their unique properties, it is time-consuming and costly to choose task-specific and suitable IL using the traditional “try-and-error” method. From the point of molecular design view, 25 cations and 20 anions are combined and screened using COSMOtherm to predict CO2 solubility at 298 K and 100 kPa. The prediction result showed that ILs with bFAP(tris(nonafluorobutyl)trifluorophosphate) anion could dissolve more CO2 than any others. To further understand the absorption performance of CO2 in ILs, molecular dynamic simulations are carried out to explore the interactions between CO2 and the four selected ILs, namely, [EMPyr][bFAP](1-ethyl-2-methylpyrazolium tris(nonafluorobutyl)trifluorophosphate), [B(Hex)3P][bFAP](butyl-trihexyl-phosphonium tris(nonafluorobutyl) trif-luorobutyl trifluorophosphate), [(Me)5isobuGua][bFAP](n,n,n,n,n-pentamethyl-n-isopropylguanidinium tris(nona-fluorobutyl)-trifluorophosphate), and [BEIM][bFAP] (1-butyl-3-ethyl-imidazolium tris(nonafluorobutyl)trifluo-rophosphate), at the atomic and molecular levels.

Background: Spontaneous intracerebral hemorrhage (ICH) is the second most common cause of stroke and accounts for approximately 15–20% of all new stroke cases. Hematoma expansion is a potentially important therapeutic target that is amenable to treatment and independently predict outcome. Hyperglycemia is frequent in ICH patients, and affects cerebrovascular function, increasing the risk of cerebral vascular rupture. We recruited 170 ICH patients to explore the high risk factors of mortality and the association between hyperglycemia and early hematoma expansion. Methods: A retrospective analysis of 170 patients with ICH who were grouped by survival and blood glucose level, death group (35 cases) and survival group (135 cases); 77 cases in the hyperglycemic group and 93 cases in the normoglycemic group. Recorded parameters, such as age, gender, past medical history, blood glucose, serum calcium, hematoma volume, and hematoma expansion. Group comparison used t-test, rank sum test and Fisher exact test. After these, logistic regression analysis and receiver operating characteristic (ROC) curves were performed. Results: Among 170 ICH subjects(130 males and 40 females)，35 died and 77 exhibited hyperglycaemia. Compared with the survival group, the death group presented with higher Original Intracerebral Hemorrhage Scale (OICH) score, greater blood glucose, larger hemorrhage volume and lower Glasgow Coma Scale (GCS) score. The occurrence of hematoma expansion and massive hemorrhage volume in the hyperglycemic group were higher than in the normoglycemic group(P

Background. Enteral nutrition (EN) is often used in patients with traumatic brain injury (TBI), but some studies have shown that EN has its disadvantages. However, it is not clear which nutritional support is appropriate to reduce mortality, improve prognosis, and improve nutritional status in patients with TBI. We performed this Bayesian network meta-analysis to evaluate the improvement of nutritional indicators and the clinical outcomes of patients with TBI. Methods. We systematically searched PubMed, Embase, Cochrane Library, and Web of Science from inception until December 2021. All randomized controlled trials (RCTs) which compared the effects of different nutritional supports on clinical outcomes and nutritional indicators in patients with TBI were included. The co-primary outcomes included mortality and the value of serum albumin. The secondary outcomes were nitrogen balance, the length of study (LOS) in the ICU, and feeding-related complications. The network meta-analysis was performed to adjust for indirect comparison and mixed treatment analysis. Results. 7 studies enroll a total of 456 patients who received different nutritional supports including parenteral nutrition (PN), enteral nutrition (EN), and PN + EN. No effects on in-hospital mortality (Median RR = 1.06, 95% Crl = 0.12 to 1.77) and the value of 0-1 days of serum albumin were found between the included regimens. However, the value of 11–13 days of serum albumin of EN was better than that of PN (WMD = −4.95, 95% CI = −7.18 to −2.72, P

In this article, the Ansys Workbench was used to carry out the finite element analysis of 15 kW wind turbine blades with different damaged positions and different damaged degrees. The results show that the change rate of natural frequency, displacement modes, and strain modes of the blades increased with the increase in the damage degree; the change rate of the natural frequency and displacement modes of the blade decreased with the increase in the speed, while the change rate of the strain modes increased; the change allocation ratio of the displacement modes and strain modes after the damage was more obvious at the damage location than other positions, which can be used to locate the damage position of the blade; the change allocation ratio of strain modes is higher than the change allocation ratio of displacement modes when the damage degree is the same, which means that the recognition effect of the strain modes is more significant than that of the displacement modes.

ObjectiveTo investigate the current status of sleep quality among adult residents in urban areas of Mianyang， and to explore the influencing factors.MethodsA cross-sectional survey was conducted on 126 adult residents from three communities in Mianyang. The selected individuals were assessed using self-made general information questionnaire， Pittsburgh Sleep Quality Index （PSQI）， the sleep-hygiene awareness activities subsection and sleep-hygiene practice sections of Sleep Hygiene Awareness and Practice （SHAP）. Then the sleep quality among residents of different demographic characteristics， sleep-hygiene awareness activities and sleep-hygiene practices was compared， meantime， the influencing factors of sleep quality were screened via multiple linear regression model.ResultsThe PSQI score was （7.51±4.05） among urban adults in Mianyang. Correlation analysis yielded that the sleep-hygiene awareness score was positively correlated with the daytime dysfunction dimension score in PSQI （r=0.232， P=0.009）， and the sleep-hygiene habit score was positively correlated with PSQI score， the dimension scores of sleep latency， sleep quality， sleep duration， use of sleeping medication and daytime dysfunction （r=0.188~0.362， P

Hypoxia-induced epigenetic regulation calls for more effective therapeutic targets for esophageal cancer. We used GEPIA and UALCAN databases to screen survival-related and cancer stage-associated genes. Eca109 and KYSE450 esophageal cancer cell lines were cultured under normoxia, hypoxia, or CoCl2-induced hypoxia conditions, which were further transfected with plasmids expressing RB binding protein 7 (RBBP7), hypoxia-inducible factor 1 (HIF1)-α, or RBBP7 shRNA. Colony formation and MTT assays were used to detect cell proliferation. Tumor sphere formation and stemness marker detection were applied to assess cell stemness. RT-PCR and western blot analysis were used to detect the relative mRNA level and protein expression, respectively. Luciferase assay was utilized to detect the direct interaction between HIF1α and RBBP7. Up-regulated RBBP7 was identified as one of the most prominent survival-related genes, which is negatively correlated with the overall survival (OS), disease recurrence-free survival (DFS), and tumor stages. Hypoxia-induced HIF1α up-regulates RBBP7 expression, which promotes esophagus cancer cell viability, proliferation, and stemness with increased cyclin-dependent kinase 4 (CDK4) expression. Luciferase reporter assay verified that HIF1α transcriptionally regulates the expression of RBBP7. We conclude that hypoxia induces high expression of RBBP7 which is at least partially mediated by HIF1α, up-regulates the expression of downstream CDK4, and thereby promotes tumor progression in esophageal cancer cells.

In order to solve the limitations of traditional methods in the reliability assessment of complex systems with multi-states and difficult to obtain accurate failure rates, and the problems of T-S fault tree in the system reliability analysis, such as complex calculation and inverse reasoning, etc., a reliability assessment method based on T-S fault tree and interval-valued fuzzy multi-state Bayesian network is proposed. Based on the analysis of the T-S fault tree, it is mapped into a Bayesian network. In the existing fuzzy Bayesian network reliability analysis method, the interval variable is introduced. Fuzzy processing is carried out to construct an interval-valued triangular fuzzy Bayesian network. Combining the characteristics of interval fuzzy subsets and Bayesian networks, a solution algorithm for leaf node failure probability, interval fuzzy importance, and interval fuzzy posterior probability is obtained under the condition of knowing only the root node failure status. Finally, the method is used to evaluate the reliability of the expansion system of the tunnel stacker, and it is verified that this method can accurately and effectively identify the weak links of the polymorphic system, and provide guidance for maintenance and diagnosis.