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The NLRP3 inflammasome is a cellular multimeric protein complex that plays a crucial role in inflammation and immune responses. It consists of three main components: Nod-like receptor protein 3(NLRP3), apoptosis-associated speck-like protein containing(ASC)and cysteine protease 1(caspase-1). Uveitis is a broad term encompassing a range of inflammatory diseases that primarily affect the iris, ciliary body, vitreous, retina and choroid. It is considered a major cause of blindness globally. Numerous studies have demonstrated the involvement of NLRP3 inflammasome in the onset and progression of uveitis, indicating its potential as a significant therapeutic target for uveitis in the future. This article provides an overview of the structure, biological functions and activation pathways of the NLRP3 inflammasome, as well as the current research progress on its association with different types of uveitis. Additionally, it discusses the application potential of the NLRP3 inflammasome in the treatment of uveitis.

In this paper, an end-to-end system framework is proposed for the Digital Twin study of spaceborne ATI-SAR ocean current velocity inversion. Within this framework, a fitting inversion approach is proposed to enhance the conventional spaceborne ATI-SAR ocean current velocity inversion algorithm. Consequently, the issue of possible local inversion errors stemming from the mismatch between the traditional spaceborne ATI-SAR inversion algorithm and various dual-antenna configurations is resolved to a certain extent. A simulated spaceborne ATI-SAR system, featuring a dual-antenna configuration comprising a baseline direction perpendicular to the track and a squint angle, is presented to validate the efficacy of the Digital Twin methodology. Under the specified simulation parameters, the average inversion error for the final ocean current velocity is recorded at 0.0084 m/s, showcasing a reduction of 0.0401 m/s compared with the average inversion error prior to optimization.

Objective: To compare the effects of different oil preparation processes on the active ingredients and oxidation activity of Akebia trifoliate seed oil. Methods: Akebia trifoliata seed oil was prepared from Akebia trifoliata seed by four oil extraction processes: cold pressing, hot pressing, supercritical CO2 extraction and extraction. The fatty acid composition, active ingredients （carotenoids, tocopherols, polyphenols, flavonoids） and DPPH free radical scavenging capacity of Akebia trifoliata seed oil were analyzed. Results: The fatty acid composition of Akebia trifoliata seed oil prepared by the four processes was similar. The content of palmitic acid was 20.62%~21.42%, the content of stearic acid was 2.68%~3.08%, the content of oleic acid was 47.03%~47.37%, the content of linoleic acid was 27.75%~28.07%, and the content of other fatty acids did not exceed 0.5%; In terms of the content of active components, the content of total tocopherol, flavonoids and polyphenols in Akebia trifoliata seed oil prepared by cold pressing was the highest, reaching 349.05, 103.37 and 51.78 mg/kg respectively, while the content of total tocopherol, flavonoids and polyphenols in Akebia trifoliata seed oil prepared by extraction was significantly lower than that of the other three extraction methods, only 220.24, 57.73 and 23.45 mg/kg; In terms of DPPH free radical scavenging capacity, cold pressing Akebia trifoliate seed oil has the best scavenging effect, and the extraction method is the worst. Conclusion: Akebia trifoliate seed oil is rich in oleic acid and linoleic acid, and has the ability of scavenging DPPH free radicals. It can be used as food ingredients, cosmetics and pharmaceutical base oils.

In recent years, the detection performance of SAR-GMTI (synthetic aperture radar-ground moving target indication) algorithm based on deep learning has always been limited by insufficient measured data due to the heavy operation complexity and high cost of real SAR systems. To solve this problem, this paper proposes an overall DT-based implementation framework for SAR ground moving target intelligent detection tasks. In particular, by virtue of a SAR imaging algorithm, a high-fidelity twin replica of SAR moving targets is established in digital space through parameter traversal based on the prior target characteristics of the obtained measured datasets. Then, the constructed SAR twin datasets is fed into the neural network model to train an intelligent detector by fully learning features of the moving targets and preset the SAR scene in the twin space, which can realize the robust detection of ground moving targets in related practical scenarios with no need for multiple and complex field experiments. Moreover, the effectiveness of the proposed framework is verified on the MiniSAR measured system, and a comparison with traditional CFAR detection method is given simultaneously.

Synthetic aperture radar (SAR) can detect moving targets on the ground/sea, and high-resolution imaging on the ground/sea has critical applications in both military and civilian fields. This paper attempts to use a spaceborne SAR system to detect and image moving targets in the air for the first time. Due to the high velocity of aerial targets, they usually appear as two-dimensional range and azimuth direction defocus in SAR images, and clutter will also have a profound impact on target detection. To solve the above problems, a method of detecting and focusing on a spaceborne SAR target based on a two-dimensional velocity search is proposed by combining the BP algorithm. According to the current environment of the aerial target and the number of system channels, the clutter suppression methods are set and combined with two-dimensional velocity search with different precision, the Shannon entropy under different search velocity groups is used to obtain the search velocity group closest to the actual velocity and realize the integrated processing of moving target detection–focused imaging parameter estimation. Combined with simulation data, the effectiveness of the proposed method is verified.

The rapid development of information technology has entered the era of network big data, online shopping for young people has become a fashion, and social media platforms have gathered a large amount of consumer purchase data. In this paper, for the current social media facing the problem of user consumption behavior prediction accuracy, data mining technology is referenced to analyze and predict user consumption behavior. The entropy weight method is used to segment e-commerce consumers based on RFM, and on this basis, the simple Bayesian method is used to model consumer behavior and construct an algorithm suitable for analyzing and predicting consumer behavior using social media data. Consumers are categorized into important value customers (7.21%), important development customers (18.76%), important retention customers (7.32%), general value customers (9.86%), general development customers (37.14%), and general retention customers (19.71%). The accuracy rate (ACC) for social media-based e-commerce consumer behavior is 84.92%, which allows for more accurate predictions. The study provides a scientific foundation for e-commerce platforms or enterprise decision-making, incubates emerging industries by analyzing big data, addresses major user needs, and becomes a new engine for promoting social progress.

Forecasting the number of hospitalization patients is important for hospital management. The number of hospitalization patients depends on three types of patients, namely admission patients, discharged patients, and inpatients. However, previous works focused on one type of patients rather than the three types of patients together. In this paper, we propose a multi-task forecasting model to forecast the three types of patients simultaneously. We integrate three neural network modules into a unified model for forecasting. Besides, we extract date features of admission and discharged patient flows to improve forecasting accuracy. The algorithm is trained and evaluated on a real-world data set of a one-year daily observation of patient numbers in a hospital. We compare the performance of our model with eight baselines over two real-word data sets. The experimental results show that our approach outperforms other baseline algorithms significantly.

Background/Aim. Pericapsular nerve group block (PNGB) does not affect the motor nerve while blocking the obturator and femoral nerves. The aim of the study was to determine the application value of PNGB for hip replacement in the elderly. Methods. Ninety elderly patients who underwent hip replacement from March 2019 to October 2020 were randomly divided into the fascia iliaca compartment block (FICB) group and the PNGB group. FICB and PNGB were performed prior to subarachnoid block (SAB). Their baseline data, operation conditions, incidence of adverse reactions, visual analog scale (VAS) score, heart rate (HR), mean arterial pressure (MAP), plasma cortisol (COR), and epinephrine (E) levels were compared. Results. VAS score, E, and plasma COR levels in the PNGB group were lower than those in the FICB group at time points T2–T4 (T2: 10 min after nerve block; T3: at position changing; T4: after position changing) (p < 0.001). There were no significant differences in HR and MAP between the two groups at any time point (p > 0.05). In the PNGB group, the ultrasonic imaging time was shorter, the time point of pressing patient-controlled analgesia (PCA) for the first time was later, and the numbers of pressing PCA were fewer than those of the FICB group (p < 0.001). No local anesthetic poisoning took place after the nerve block, and no hematoma at the puncture site, nerve injury, nausea and vomiting, dizziness, or delirium occurred. Conclusion. Both FICB and PNGB prior to SAB were highly safe for hip replacement in the elderly; however, PNGB has shorter ultrasonic imaging time, better analgesic effect, and milder oxidative stress, so it is worth applying it clinically.

Objective: This study focuses on in-depth research and development of the utilization of Coreopsis tinctoria resources. Methods: The Coreopsis samples from Hetian, Urumqi, Aba, Luding and Xining were hydrolyzed with hydrochloric acid, and the contents of 17 kinds of amino acids were determined by automatic amino acid analyzer. On this basis, the characteristics of amino acid flavor were analyzed and compared with the amino acid pattern spectrum issued by FAO/WHO. RAA, RC and SRC were calculated, and correlation analysis and cluster analysis were performed on 17 kinds of amino acids of chrysanthemum. Thereafter, the nutritional value of Coreopsis protein was comprehensively evaluated. Results: 17 kinds of amino acids were detected in all the 5 species from different habitats. The taste characteristics of Luding and Aba Coreopsis was mainly bitter, while the other three kinds of Coreopsis showed umami, bitter and sweet taste from the highest to the lowest. Compared with the amino acid pattern profile, the Met+Cys in Coreopsis from the five producing areas were lower than the pattern spectrum standard, and the proportions of other essential amino acids in the total amino acids in Luding, Hetian and Urumqi were close to and higher than the pattern spectrum standard. According to the RC value, Met and Cys were identified as as the first limiting amino acids of Coreopsis. The SRC value ranged from 75 to 80, the ratio of essential amino acids to total amino acids (E/T value) ranged from 31% to 36%, and the ratio of essential amino acids to non-essential amino acids (E/N value) ranged from 46% to 55%. The E/N values of Coreopsis in all five regions are slightly lower than the FAO/WHO ideal protein standard. Conclusion: Coreopsis is rich in amino acids and has high nutritional value with certain medicinal value. It has good taste and can be used as a beneficial product resource for human body.

As a key safety component of automobiles, automobile steering knuckles must be subjected to strict quality control. Currently, the identification of cracks in finished products primarily relies on manual identification of fluorescent penetrant detection. Owing to the complex shape of the workpiece, the interference of the displayed image and the small sample size, the accuracy of the automatic discrimination result of the fluorescent penetrant detection image is directly reduced. Therefore, this study proposed a data augmentation method based on deep convolutional generative adversarial networks (DCGAN) for crack identification in automotive steering knuckle fluorescent penetration inspection images. An image acquisition platform was built for fluorescence penetration detection of automobile steering knuckles, and fluorescence display images of various parts of the workpiece were collected. Based on the feature analysis of the displayed image, the image was preprocessed to suppress relevant interference and extract crack candidate regions. Further, using the original crack image to train DCGAN, several crack image samples were generated, the ResNet network was trained with the expanded dataset, and the extracted candidate regions were identified. Finally, the experimental results show that the recall rate of the crack recognition method used in this paper is 95.1%, and the accuracy rate is 90.8%, which can better identify the crack defects in the fluorescent penetrant inspection image, compared with the non-generative data enhancement method.

Urban vitality is a spatial phenomenon and a public service. Previous studies often did not measure the fairness of the accessibility of urban vitality. This research analyzed the spatial distribution of urban vitality in Wuhan as a case study area using big data from multiple sources. The study used the two-step floating catchment area method (2SFCA) to measure the accessibility level of each residential district to the vibrant zones (VZs). Furthermore, the inequality in the level of accessibility of residential areas with different housing prices was assessed on the basis of the Gini coefficient. The main conclusions are as follows: (1) the Gini coefficient of reaching the accessibility level of high-grade VZs is 0.426, and the corresponding sub-high-grade Gini coefficient is 0.274. This shows that the inequality in accessibility of different residential areas is more obvious as the level of vitality is higher and (2) residential areas with high housing prices have greater accessibility than those areas with low housing prices. It was also noticed that the level of accessibility and fairness in vitality is generally higher in central urban areas than in suburban areas. The Gini coefficient of high-grade vitality is generally higher than that of sub-high-grade. The results of this study provide a reference for researching the accessibility level of urban vitality, which considers the needs of population, and can also provide guidelines in urban planning regarding the allocation of services and resources.

Adipose tissue reconstruction is an important technique for soft tissue defects caused by facial plastic surgery and trauma. Adipose tissue reconstruction can be repaired by fat transplantation and biomaterial filling, but there are some problems in fat transplantation, such as second operation and limited resources. The application of advanced artificial biomaterials is a promising strategy. In this paper, injectable biomaterials and three-dimensional (3D) tissue-engineered scaffold materials for adipose tissue reconstruction in plastic surgery are reviewed. Injectable biomaterials include natural biomaterials and artificial biomaterials, which generally have problems such as high absorptivity of fillers, repeated injection, and rejection. In recent years, the technology of new 3D tissue-engineering scaffold materials with adipose-derived stem cells (ADSCs) and porous scaffold as the core has made good progress in fat reconstruction, which is expected to solve the current problem of clinical adipose tissue reconstruction, and various biomaterials preparation technology and transformation research also provide the basis for clinical transformation of fat tissue reconstruction.

As China’s population keeps aging, the hollowing-out problem in villages and towns gradually becomes prominent, accompanied by the increasing number of residents in aged care architecture. As one social occasion, the interaction space of aged care architecture is of great significance for the elderly. The present study, therefore, collects and analyzes relevant evaluation indicators from the perspective of inclusiveness. The AHP-Fuzzy comprehensive evaluation method was adopted to construct an evaluation system for the interaction space of aged care architecture in villages and towns in China. In order to verify the system’s accuracy and effectiveness, the evaluation of Xin’an Town in Wuyang County was carried out. The research is helpful for the design of interaction space of future aged care architecture in China and the improvement of the existing buildings, providing a certain reference for the inclusive evaluation of the interaction space of aged care architecture in villages and towns.

Fluorescent magnetic particle inspection (MPI) is a conventional non-destructive testing process for railway bearing rings that still needs to be completed manually. Due to the complexity of bearing ring surfaces in inspection, automatic detection for bearing rings based on image processing is difficult to apply. Therefore, we proposed a bearing ring defect identification method based on visual characteristics and high-level features. Inspired by the mechanism of human visual perception, defects can be identified from the complex background conveniently by human eyes. According to the linear structure characteristics and greyscale distribution characteristics of cracks in the acquired images, we introduce the centerline extraction and Gaussian similarity measure to reduce background noise and obtain the crack candidate regions. Then, an improved MobileNetV3 is used to extract high-level features of the candidate regions and determine whether they are defective, which uses a new attention module, Coordinate Attention (CA), to substitute the Squeeze-and-Excitation (SE) attention to improve the performance. The experimental results show that the detection accuracy rate of the proposed method is 96.5%. Compared with traditional methods, the proposed method can efficiently extract crack defects in a complex textured background and shows high-quality performance in recall and precision.

With the development of society, crowds in public buildings are dense, and the subsequent spread of diseases in places with high population density has attracted widespread attention. In the real situation, the spread of the disease has its complexity, such as the influence of factors such as the movement of people and the intervention of external measures, so it is necessary to further refine the description of the process of infection transmission. Based on the social force model, this article focuses on the impact of microscopic crowd movement in public places on the dynamics of infection. Taking a typical pedestrian exit process in a subway station as an example, we numerically simulated the infection problem among small-scale people in public places, observed the impact of pedestrian movement characteristics on infection transmission, put forward corresponding prevention and control measures, and verified the effectiveness of the measures.

The East Tianshan Mountain is one of the most important gold ore forming zones in northwestern China and central Asia. The Chinese GaoFen-1 (GF-1), the first Chinese high resolution satellite, is characterized by its 2-m resolution PAN data. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the well-known earth observation satellite, is advanced by its finer spectral resolution owing 9 bands in the visible and near infrared (VNIR) to the short-wave infrared (SWIR) region. In this study, we fused the GF-1 PAN and the ASTER multispectral data using the well-known Gram-Schmidt Pan Sharpening (G-S) method to produce a new data with both high spatial and spectral resolution. Then different lithological units were mapped respectively using the fusion data, the ASTER data and the WorldView-3 data by support vector machine (SVM) method. In order to assess this fusion data, a comparison work was executed among the three mapping results. The comparison work indicated that lithological classification using the new fusion data is an efficient, robust and low cost method, and it could replace the WV-3 data in some large sale geological work.

Acute kidney injury (AKI) is a significant medical problem worldwide. Ischemia-reperfusion (I/R) injury of the kidney is a major cause of AKI. However, the pathogenesis that contributes to renal I/R injury is still unclear. Apoptosis repressor with caspase recruitment domain (ARC) is abundantly expressed in various tissues, and has been reported to play a strong protective role during pathological processes. Our results indicated that ARC expression was decreased in the reperfused kidneys. ARC deficiency markedly accelerated renal dysfunction, promoted reperfusion-regulated tubular epithelial cell apoptosis, and enhanced the vulnerability of kidney to I/R damage. Furthermore, in the kidney samples of mice underwent renal I/R injury, ARC knockout significantly accelerated the expression levels of inflammatory factors, including interleukin (IL)-1β, IL-6, tumor necrosis factor a (TNF-α), monocyte chemoattractant protein-1 (MCP-1) and IL-2. In addition, renal I/R injury-induced apoptosis was further exacerbated in ARC-deficient mice through promoting the expression of cleaved Caspase-3 and poly (ADP-ribose) polymerase (PARP). From the molecular level, ARC deletion obviously accelerated mitochondrial injury, as evidenced by the further decreased adenosine triphosphate (ATP) levels and mitochondrial potential in hypoxia-reoxygenation (H/R)-treated cells. Moreover, ARC knockout exacerbated AKI through activating phosphorylated protein kinase B (AKT), mammalian target of Rapamycin (mTOR) and p53, whereas reducing phosphorylated glycogen synthase kinase 3β (GSK3β). Of note, blocking AKT/mTOR signaling markedly attenuated inflammation, mitochondrial damage and apoptosis stimulated by H/R in ARC knockdown cells. In summary, our results suggested that ARC played a pivotal role in the pathogenesis of AKI induced by renal I/R operation through regulating AKT/mTOR signaling.

Background" Autism spectrum disorder (ASD) is a serious neurodevelopmental disorder that impairs a child’s ability to communicate with others. It also includes restricted repetitive behaviors, interests and activities. Symptoms manifest before the age of 3. In the previous studies, we found structural abnormalities of the temporal lobe cortex. High spine densities were most commonly found in ASD subjects with lower levels of cognitive functioning. In the present study, we retrospectively analyzed medical records in relation to the neonatal levels of total serum bilirubin (TSB), neuron-specific enolase (NSE), creatine kinase brain band isoenzyme (CK-BB), and neonatal behavior in ASD patients from Southern China. Methods: A total of 80 patients with ASD (ASD group) were screened for this retrospective study. Among them, 34 were low-functioning ASD (L-ASD group) and 46 were high-functioning ASD (H-ASD group). Identification of the ASD cases was confirmed with a Revised Autism Diagnostic Inventory. For comparison with ASD cases, 80 normal neonates (control group) were selected from the same period. Biochemical parameters, including TSB, NSE and CK-BB in the neonatal period and medical records on neonatal behavior were collected. Results: The levels of serum TSB, NSE and CK-BB in the ASD group were significantly higher when compared with those from the control group (P < 0.01, or P < 0.05). The amounts of serum TSB, NSE and CK-BB in the L-ASD group were significantly higher when compared with those in the H-ASD group (P < 0.01, or P < 0.05). The Neonatal Behavioral Assessment Scale (NBAS) scores in the ASD group were significantly lower than that in the control group (P < 0.05). Likewise, the NBAS scores in the L-ASD group were significantly lower than that in the H-ASD group (P < 0.05). There was no association between serum TSB, NSE, CK-BB and NBAS scores (P > 0.05) in the ASD group. Conclusions: The neonatal levels of TSB, NSE and CK-BB in ASD from Southern China were significantly higher than those of healthy controls. These findings need to be investigated thoroughly by future studies with large sample.

Few studies have investigated current English-medium Instruction (EMI) programmes for international students studying in universities in China's mainland. The present study applies Spolsky's language policy framework to analyze Chinese EMI programmes in terms of language ideology, language management, and language practices on the national level, the university level and the individual level. Data are collected from policy statements, interviews, and questionnaires. This study finds that in EMI programmes for international students, language belief lays the foundation for meso-level language management. Guided by macro beliefs, meso institutions use the management tools of curriculum design, instructional staff management, and evaluation to implement EMI programmes. Language practice is influenced by and modifies beliefs and management. In practice, professional learning is prioritised, and a slight mismatch between the language support provided by the institutions and international students' actual expectations is found. This study contributes to the development and implementation of EMI in Chinese higher education.