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Abstract Patients on B cell immunosuppressive treatments have been shown to have persistent infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this report, a woman treated with ibrutinib for chronic lymphocytic leukemia experienced more than 40 days of coronavirus disease 2019 (COVID-19) infection. Unexpectedly, her peripheral blood experiments showed a normal SARS-CoV-2-specific antibody level and a relatively elevated percentage of CD19 + B cells, while an obvious decrease in the percentages of NK cells, CD4 + T cells and CD8 + T cells. Further SARS-CoV-2-specific T cell analysis in this patient indicated a significant decrease in the percentage of SARS-CoV-2-specific IFN-γ, TNF-α or IL-2 producing CD4 + T or CD8 + T cells. Most notably, ten days after the cease of ibrutinib, the PCR for SARS-CoV-2 turned negative and the reduced proportions of peripheral CD4 + T cells and CD8 + T cells recovered. Our research predicted that the depleted B-cell function therapies may play considerable role in the development of long COVID-19 and the abnormal T-cell subset distribution might be the underlying mechanism.

The pyrolysis behavior of biomass is critical for industrial process design, yet the complexity of pyrolysis models makes this task challenging. This paper introduces an innovative hybrid model to quantify the pyrolysis potential of pine needles, predicting the entire process of their pyrolysis behavior. Through experimental analyses and kinetic parameter calculations of pine needle pyrolysis, the study employs a kinetic model with a chemical reaction mechanism. Additionally, it introduces an improved dung beetle optimization algorithm to accurately capture the primary trends in pine needle pyrolysis. The developed artificial neural network model incorporates meta-heuristic algorithms to address process error factors. Validation is based on experimental data from TG at three different heating rates. The results demonstrate that the hybrid model exhibits strong predictive performance compared to the standalone model, with coefficients of determination (R²) of 0.9999 and 0.999 for predicting the conversion degree and conversion rate of untrained data, respectively. Additionally, the standard errors of prediction (SEP) are 0.249% and 0.449% for predicting the conversion degree and conversion rate of untrained data, respectively.

Abstract Utilizing the direct current‐side electrical data resources of the photovoltaic power generation system on the FusionSolar platform, this study investigates the impact of hot spot faults on the output characteristics of photovoltaic strings and proposes a hot spot fault diagnosis method based on time series waveform characteristics. By analyzing the mechanisms of hot spot generation and evolution, as well as the characteristic differences in I–V curves and time series compared to other types of faults, the waveform variation patterns of hot spots in current and voltage time series are obtained. A function form suitable for hot spot fault waveform characteristics in time series graphs is constructed, and fault diagnosis feature vectors are extracted. Combining field operation and maintenance experience, a fuzzy reasoning fault diagnosis system is established to determine the causes and estimate the severity of hot spot faults. Experimental results indicate that hot spot faults have unique and corresponding variations in the current/voltage time series waveforms of the string output. The constructed function form can clearly represent the waveform variation patterns, and the established fuzzy reasoning system can achieve effective and reliable diagnosis of hot spot faults.

The aim of this study is to investigate the impact of various ambient temperatures on the mechanical properties of full aeolian sand concrete (ASC100). Using ordinary concrete (ASC0) as the control group, we analyzed the effects of different ambient temperatures (−20, −15, −10, −5, 0, and 20°C) on the mechanical properties of both ASC0 and ASC100 through cube compression, splitting tensile, and uniaxial compression tests. The results demonstrate that the compressive strength and splitting tensile strength of concrete cubes increased with decreasing temperature. At −20°C, the compressive strength of ASC100 increased by 30.1% and that of ASC0 increased by 27.31% compared to that at 20°C. Additionally, compared to normal temperatures, the elastic modulus of ASC0 and ASC100 at subzero temperatures increased by 28.2–61.4% and 6.8–65.7%, respectively, while the peak stress increased by 7–35% and 6.8–38%, respectively. The stress–strain curve of ASC100 showed three stages: elastic, elastic-plastic, and yield failure, serving as the reference group. Finally, based on the classical constitutive model, we modified the constitutive parameters by axial compressive strength and temperature, proposing a constitutive model of concrete suitable for different low-temperature environments, which is in good agreement with experimental data.

Abstract Unicystic ameloblastoma (UAM) of the jaw can be effectively reduced in volume through decompression, which promotes bone regeneration and restores jaw symmetry. This study quantitatively evaluated changes in mandible volume and symmetry following decompression of mandibular UAM. This study included 17 patients who underwent surgical decompression followed by second-stage curettage for mandibular UAM. Preoperative and postoperative three-dimensional computed tomography (CT) images were collected. Bone volume and the area of cortical perforation were measured to assess bone growth during decompression. Mandibular volumetric symmetry was analyzed by calculating the volumetric ratio of the two sides of the mandible. Twelve pairs of landmarks were identified on the surface of the lesion regions, and their coordinates were used to calculate the mean asymmetry index (AI) of the mandible. Paired t-tests and the Mann–Whitney U test were used for statistical analysis, with p

In the field of drilling in coal mine underground, drilling rate (DR) is one of the most effective indicators for assessing drilling operations. Accurate prediction of DR is a prerequisite for the realization of intelligent drilling in coal mines, which is of great significance for optimizing drilling parameters, reducing operational costs, and ensuring safe and efficient drilling. In the present research, the influence of drilling parameters on DR are investigated and the intelligent prediction methods are developed to achieve accurate DR predictions with different machine learning algorithms based on several drilling parameters, including weight on bit, rotation speed, torque, and drilling depth. Initially, micro-drilling experiments are conducted to analyze the impact of coal rock mechanical properties, weight on bit, rotation speed, and drilling depth on torque and drilling rate. The experimental results indicate that during the underground coal mining drilling process, drilling rate gradually rises with the increasing weight on bit. Under higher rotation speed conditions, the influence of weight on bit on drilling speed becomes more pronounced. Increasing the rotational speed is advantageous for improving drilling speed, but the impact of rotational speed on drilling speed is more significant in softer coal seams. Subsequently, three different machine learning algorithms, namely K–Nearest Neighbors (KNN), Support Vector Regression (SVR), and Random Forest Regression (RFR), are used to build drilling rate prediction models based on on-site drilling data from underground coal mining, and the hyperparameters of those models are optimized with Particle Swarm Optimization (PSO) method. Finally, the prediction results of three drilling rate models, PSO–KNN, PSO–SVR, and PSO–RFR, are analyzed comparatively. The results show that PSO–RFR model offers the highest accuracy, with R2 of 0.963, MSE of 29.742. On the other hand, the PSO–SVR model exhibits the best robustness, with minimal changes in evaluation metrics after withstanding adversarial attacks. This study is beneficial for the realization of precise DR prediction, providing theoretical support for the optimization of intelligent drilling parameters in underground coal mining operations.

Intelligent shearer is a key equipment for a fully mechanized coal mine working face. For intelligent shearers, due to the internal space limitation of flameproof electric control box, there are usually mixed wiring situations with the cables of internal electronic and electrical components, inverter power, communication bus, etc., which seriously affects the stability and reliability of shearer bus by electromagnetic interference. As the installed power continues to increase and the shearer's intelligent demand becomes higher, the electromagnetic interference of the intelligent shearer's electronic and electrical control system bus becomes more severe. At present, the wiring process in the shearer’s electrical control box is mainly based on experience. There are still no effective estimation means for the electromagnetic environment and the research is limited on the coupling model of line field transmission in the shearer’s electrical control box, causing that it cannot provide technical support for improving the bus anti-interference ability of intelligent shearer control system. Therefore, to inhibit electromagnetic interference effectively and optimize the wiring process for improving the stability of bus communication has become an important problem to be solved urgently for intelligent shearer. According to the requirements of anti-interference technology of intelligent shearer bus, the radiation interference model of the power cable in the control box of intelligent shearer is established, and the rapid estimation method of the output-power-cable electromagnetic radiation is proposed. Furthermore, the electromagnetic radiation of the output power cable of the frequency converter is analyzed, which is influenced by switching frequency, output voltage, and starting state. Then, the analysis model of the shearer CAN bus crosstalk characteristics based on the double conductor transmission line is established, the crosstalk estimation method of the shearer CAN bus based on the crosstalk influence factor is proposed, and the relationship between the crosstalk effect of bus and wiring distance, cable type, height from the ground, and other factors is studied. Based on the analysis mentioned above, a bus anti-interference optimization wiring process and a shearer bus anti-interference test visual system are developed for an intelligent shearer electric control box. To verify the feasibility of the proposed method, the bus interference test experiments are designed and carried out before and after the wiring optimization of the electric control box. The results show that the deviation degree of the CAN bus data frame waveform before and after the optimization is 0.149 3 and 0.030 5, respectively, and the disturbance rate before and after optimization is 56.07% and 35.33%, respectively.

Abstract Background Esophageal cancer brings emotional changes, especially anxiety to patients. Co-existing anxiety makes the surgery difficult and may cause complications. This study aims to evaluate effects of anxiety in postoperative complications of esophageal cancer patients with chronic obstructive pulmonary disease (COPD). Methods Patients with esophageal cancer and co-existing COPD underwent tumor excision. Anxiety was measured using Hospital Anxiety and Depression Scale (HAD) before surgery. Clavien-Dindo criteria were used to grade surgical complications. A multiple regression model was used to analyze the relationship between anxiety and postoperative complications. The chi-square test was used to compare the differences in various types of complications between the anxiety group and the non-anxiety group. A multinomial logistic regression model was used to analyze the influencing factors of mild and severe complications. Results This study included a total of 270 eligible patients, of which 20.7% had anxiety symptoms and 56.6% experienced postoperative complications. After evaluation by univariate analysis and multivariate logistic regression models, the risk of developing complications in anxious patients was 4.1 times than non-anxious patients. Anxious patients were more likely to develop pneumonia, pyloric obstruction, and arrhythmia. The presence of anxiety, surgical method, higher body mass index (BMI), and lower preoperative oxygen pressure may increase the incidence of minor complications. The use of surgical methods, higher COPD assessment test (CAT) scores, and higher BMI may increase the incidence of major complications, while anxiety does not affect the occurrence of major complications (P = 0.054). Conclusion Preoperative anxiety is associated with postoperative complications in esophageal cancer patients with co-existing COPD. Anxiety may increase the incidence of postoperative complications, especially minor complications in patient with COPD and esophageal cancer.

Abstract Background External fixation is widely used in the treatment of traumatic fractures; however, orthopedic surgeons encounter challenges in deciding the optimal time for fixator removal. The axial load-share ratio (LS) of the fixator is a quantitative index to evaluate the stiffness of callus healing. This paper introduces an innovative method for measuring the LS and assesses the method’s feasibility and efficacy. Based on a novel hexapod LS-measurement system, the proposed method is to improve the convenience and precision of measuring LS in vivo, hence facilitating the safe removal of external fixators. Methods A novel hexapod system is introduced, including its composition, theoretical model, and method for LS measurement. We conducted a retrospective study on 82 patients with tibial fractures treated by the Taylor Spatial Frame in our hospital from September 2018 to June 2020, of which 35 took LS measurements with our novel method (Group I), and 47 were with the traditional method (Group II). The external fixator was removed when the measurement outcome (LS 0.05), frame-wearing duration (mean 25.5 weeks vs. 25.8 weeks, P > 0.05), or LS measurement frequency (mean 1.1 times vs. 1.2 times, P > 0.05). The measurement system installation time in Group I was significantly shorter compared to Group II (mean 14.8 min vs. 81.3 min, P 0.05). Conclusion The novel hexapod LS-measurement system and involved method demonstrated enhanced convenience and precision in measuring the LS of the external fixator in vivo. The LS measurement indicates the callus stiffness of fracture healing, and is applicable to evaluate the safety of removing the fixator. Consequently, it is highly recommended for widespread adoption in clinical practice.

Abstract Ca2+/calmodulin-dependent protein kinase II (CaMKII) is a family of broad substrate specificity serine (Ser)/threonine (Thr) protein kinases that play a crucial role in the Ca2+-dependent signaling pathways. Its significance as an intracellular Ca2+ sensor has garnered abundant research interest in the domain of neurodegeneration. Accumulating evidences suggest that CaMKII is implicated in the pathology of degenerative retinopathies such as diabetic retinopathy (DR), age-related macular degeneration (AMD), retinitis pigmentosa (RP) and glaucoma optic neuropathy. CaMKII can induce the aberrant proliferation of retinal blood vessels, influence the synaptic signaling, and exert dual effects on the survival of retinal ganglion cells and pigment epithelial cells. Researchers have put forth multiple therapeutic agents, encompassing small molecules, peptides, and nucleotides that possess the capability to modulate CaMKII activity. Due to its broad range isoforms and splice variants therapeutic strategies seek to inhibit specifically the CaMKII are confronted with considerable challenges. Therefore, it becomes crucial to discern the detrimental and advantageous aspects of CaMKII, thereby facilitating the development of efficacious treatment. In this review, we summarize recent research findings on the cellular and molecular biology of CaMKII, with special emphasis on its metabolic and regulatory mechanisms. We delve into the involvement of CaMKII in the retinal signal transduction pathways and discuss the correlation between CaMKII and calcium overload. Furthermore, we elaborate the therapeutic trials targeting CaMKII, and introduce recent developments in the zone of CaMKII inhibitors. These findings would enrich our knowledge of CaMKII, and shed light on the development of a therapeutic target for degenerative retinopathy.

Bitterness is a key factor that affects the consumption of quinoa products, even if they are nutritious. In this study, a non-targeted metabolomics approach based on UHPLC-Orbitrap-MS was applied to comprehensively profile the characteristic metabolites of twenty-two quinoas. A total of twenty key metabolites were identified correlated with bitterness, among which, fifteen were triterpenoid saponins. In addition, these metabolites bind to the active site of the human bitter taste receptor and are the main compounds that produce the bitter taste of quinoa. Our results contribute to a deeper understanding of the origin of quinoa bitterness and provide directions for optimizing its flavor to improve market acceptance.

Thermal rectification is a phenomenon similar to electrical rectification, in which heat transfer in one direction is favored and reverse heat transfer is hindered. In this study, the finite element method with interface thermal resistance for transient problems is proposed, and then transient thermal rectification of composite structures during the heating and cooling processes is investigated. Numerical results show that, in the initial 50 s of heating phase, increasing interface thermal resistance from 0 to 0.005 m2·K/W raised the average transient thermal rectification ratio from 1.32 to 1.46 for periodic boundaries, and from 1.22 to 1.31 for constant boundaries. During cooling, the ratio initially decreases due to resistance but then stabilizes, and the average thermal rectification ratio can be increased from 1.1 to 1.3 by increasing the interface thermal resistance. By changing the frequency, the oscillation frequency and amplitude of the thermal rectification ratio can be adjusted. In addition, a bimetallic structure with bi-directional heat transfer is designed, which includes the interface thermal resistance. The transient thermal rectification ratio is significantly increased by an order of magnitude through various interface heat transfer modes, and can be further improved through parameter optimization.

Posterior segment disease acts as a major cause of irreversible visual impairments. Successful treatment of posterior segment disease requires the efficient delivery of therapeutic substances to the targeted lesion. However, the complex ocular architecture makes the bioavailability of topically applied drugs extremely low. Invasive delivery approaches like intravitreal injection may cause adverse complications. To enhance the efficiency, several biomedical engineering systems have been developed to increase the penetration efficiency and improve the bioavailability of drugs at the posterior segments. Advantageously, biodegradable microspheres are found to deliver the therapeutic agents in a controlled fashion. The microspheres prepared from novel biomaterials can realize the prolonged release at the posterior segment with minimum side effects. Moreover, it will be degraded automatically into products that are non-toxic to the human body without the necessity of secondary operation to remove the residual polymer matrix. Additionally, biodegradable microspheres have decent thermoplasticity, adjustable hydrophilicity, controlled crystallinity, and high tensile strength, which make them suitable for intraocular delivery. In this review, we introduce the latest advancements in microsphere production technology and elaborate on the biomaterials that are used to prepare microspheres. We discuss systematically the pharmacological characteristics of biodegradable microspheres and compare their potential advantages and limitations in the treatment of posterior segment diseases. These findings would enrich our knowledge of biodegradable microspheres and cast light into the discovery of effective biomaterials for ocular drug delivery.

The drilling robot for rock-burst prevention is the key equipment for pressure relief in rock-burst mines, and its accurate map construction and stable navigation under complex working conditions are the basis and premise for realizing intelligent drilling operations. Based on the analysis of the causes of point cloud distortion of LiDAR and the defects of classical SLAM algorithm, a point cloud distortion correction method based on the IMU continuous time trajectory is proposed, a data fusion model of LiDAR and IMU is established, and the positioning and mapping process of drilling robot based on the IMU-LiDAR tight coupling is designed. A closed ramp model is built based on the characteristics of coal mine pressure relief roadways, and the simulation analysis of the mapping effect is conducted. The results show that the proposed mapping algorithm outperforms existing commonly used methods in terms of positioning accuracy and trajectory error. On this basis, a dynamic path planning method based on the improved artificial potential field and rapidly-exploring random tree is proposed, and a path planning and navigation fusion scheme suitable for drilling robot is designed. Two simulation motion scenarios are then designed, and the results indicate that the proposed path planning method has a better comprehensive performance in terms of average path length, average running time, and average number of generated nodes in both global and dynamic path planning. In order to further verify the practicality of the positioning and navigation method, multiple comparative experiments are conducted in a simulated roadway, ground experimental base and underground pressure relief roadway, and the results indicate that after tightly coupling IMU data with LiDAR data, the positioning accuracy of the proposed method is significantly improved and has a superior positioning performance in feature degradation scenarios. In addition, the planning path has better performance in terms of computational efficiency and cost. The results prove the feasibility and superiority of the proposed positioning and navigation method in various scenarios.

Abstract Pulmonary fibrosis (PF) is a severe pulmonary disease with limited available therapeutic choices. Recent evidence increasingly points to abnormal lipid metabolism as a critical factor in PF pathogenesis. Our latest research identifies the dysregulation of low-density lipoprotein (LDL) is a new risk factor for PF, contributing to alveolar epithelial and endothelial cell damage, and fibroblast activation. In this study, we first integrative summarize the published literature about lipid metabolite changes found in PF, including phospholipids, glycolipids, steroids, fatty acids, triglycerides, and lipoproteins. We then reanalyze two single-cell RNA-sequencing (scRNA-seq) datasets of PF, and the corresponding lipid metabolomic genes responsible for these lipids’ biosynthesis, catabolism, transport, and modification processes are uncovered. Intriguingly, we found that macrophage is the most active cell type in lipid metabolism, with almost all lipid metabolic genes being altered in macrophages of PF. In type 2 alveolar epithelial cells, lipid metabolic differentially expressed genes (DEGs) are primarily associated with the cytidine diphosphate diacylglycerol pathway, cholesterol metabolism, and triglyceride synthesis. Endothelial cells are partly responsible for sphingomyelin, phosphatidylcholine, and phosphatidylethanolamines reprogramming as their metabolic genes are dysregulated in PF. Fibroblasts may contribute to abnormal cholesterol, phosphatidylcholine, and phosphatidylethanolamine metabolism in PF. Therefore, the reprogrammed lipid profiles in PF may be attributed to the aberrant expression of lipid metabolic genes in different cell types. Taken together, these insights underscore the potential of targeting lipid metabolism in developing innovative therapeutic strategies, potentially leading to extended overall survival in individuals affected by PF.

For the technical problem of low intelligence in the process of drilling and pressure relief in high stress mines, the research status of pressure relief technology and equipment at home and abroad is summarized and analyzed in this study. It is pointed out that the development of high-performance, highly reliable, and efficient fully autonomous drilling system of anti-impact drilling robot is an important development direction to solve the problem of rock burst prevention and control. To this end, the five key technologies that affect the performance of the drilling system, namely “the precise recognition of hole position, the precise perception of drilling tool posture, the wireless electromagnetic intelligent detection, the intelligent recognition of drilling tool operation status, and the precise control of the drilling system” have been summarized, and the solutions and methods have been provided. In response to the problem of accurate identification of pressure relief holes in complex and harsh environments, a SinGAN model for pressure relief hole image sample expansion is developed, which integrates image size adjustment and multi-stage training modes. The Faster RCNN optimized by multi-layer feature fusion is introduced, and a hole position recognition model based on an improved SqueezeNet lightweight network architecture is constructed to achieve an accurate and fast recognition of pressure relief hole positions. To address the issue of precise perception of drilling tool posture, the unscented Kalman filter optimized by improved gradient descent algorithm is designed for the initial alignment of Inertial Measurement Unit (IMU). Multiple IMU spatial array layouts are designed, and a BP neural network-based compensation method for drilling tool posture error is studied, aiming to improve the accuracy of drilling tool posture calculation and achieve a precise drilling pressure relief. Aiming at the precise detection of drilling conditions in complex geological environments, a wireless elec-tromagnetic transmission system architecture for underground measurement while drilling in coal mines has been established. The principles of adaptive modulation of weak electromagnetic wave signals and high-speed bidirec-tional electromagnetic transmission technology have been explored, and the measurement principles and imple-mentation processes of geological parameters, geological parameters, and engineering parameters at the bottom of the hole have been investigated. To address the issue of identifying the operational status of drilling systems, a multi-domain feature extraction architecture for drilling signals in the time domain, frequency domain, and time frequency domain, as well as a deep network advanced feature extraction architecture, have been constructed. In addition, the key component health status assessment and fault diagnosis techniques for drilling systems have been proposed, and a prediction model for sticking risk factors based on an improved bat optimized long-term and short-term memory network has been built to accurately predict the stuck status of pressure relief drilling tools. In terms of the issue of precise control of drilling systems, the working principle of the hydraulic system of the drilling system is analyzed, and a precise control scheme for the drilling system considering the characteristics of coal and rock is formulated. The principle of solving the optimal control parameters of the drilling system based on torque and position is explored, aiming to achieve intelligent collaborative control and parallel operation of the drilling return system and feed system.

River sand was consumed in large quantities, and alternatives to river sand were urgently needed. There are a large number of natural resources of aeolian sand in western China. Aeolian sand was prepared into aeolian sand concrete (ASC). It can greatly reduce the consumption of river sand and inhibit the process of desertification to protect the environment. ASC is a new type of concrete material prepared by using aeolian sand as fine aggregate. To clarify the chloride ion transport behaviour in the ASC under long-term natural immersion, the aeolian sand was 100% substituted for the river sand to prepare the full ASC with three water–binder ratios. The ASC was naturally immersed in 3 and 6% NaCl solutions for a long time, and nuclear magnetic resonance and microscopic scanning electron microscopy techniques were used. The change rule of chloride ion content at different depths of the ASC was studied, and its microstructure characteristics under different erosion times were analysed. The results showed that the free chloride ion concentration at different depths of the ASC increased with increasing water–binder ratio, immersion time, and chloride concentration. After soaking in the salt solution, the hydration products in the ASC reacted with chloride ions to form Friedel salt, which filled the internal pores and microcracks of the ASC, improved its interface transition zone structure, and increased the compactness of the test piece. The porosity of the three groups of ASC with different water–binder ratios decreased by 0.95, 1.03, and 1.15% after soaking in 6% salt solution for 12 m. To study the diffusion law of chloride ions in ASC, combined with influencing factors such as temperature, humidity, D value, deterioration effect and chloride ion combination, Fick’s second law was modified, and a chloride ion diffusion model of ASC with high accuracy was established, with a fitting correlation number above 0.93, which provided a reference for the research and application of ASC in saline areas.

AIM: To observe the efficacy of phacoemulsification combined with capsular tension ring and intraocular lens implantation in the treatment of high myopia with cataract.METHODS: Retrospective study. A total of 82 cases(82 eyes)of high myopia complicated with cataract who admitted to the cataract department of our hospital from December 2021 to April 2023 were selected as study objects, and they were divided into control group(n=39)and combination group(n=43)according to whether or not the capsular tension ring was used intraoperatively. Patients in the control group were treated with intraocular lens implantation alone, and those in the combination group were treated with phacoemulsification combined with capsular tension ring and intraocular lens implantation. The preoperative and postoperative best corrected visual acuity, central anterior chamber depth, trabecular ciliary process, visual quality and complications were compared.RESULTS: At 1 mo after surgery, the best corrected visual acuity(LogMAR)of both groups increased significantly(combination group: 0.64±0.28 vs 0.12±0.14; control group: 0.62±0.26 vs 0.23±0.25, both P0.05). The visual quality scores of the combination group were all higher than the control group at 1 mo after surgery [watching TV: 3.00±0.38 vs 2.22±0.46 points; reading books: 2.85±0.42 vs 2.21±0.44 points; night vision: 2.71±0.34 vs 2.37±0.41 points; fine operation: 2.82±0.38 vs 2.33±0.40 points, all P

A sensitive and specific bioanalytical method was required to measure the exposure of a LAGA-mutated surrogate mouse IgG2a monoclonal antibody in mouse plasma, but the lack of highly specific reagents for the LAGA mutant hindered the development of a ligand-binding assay. Equally problematic is that no sensitive unique tryptic peptides suitable for quantitative mass spectrometric analysis could be identified in the mIgG2a complementarity-determining regions. To overcome these challenges, a trypsin alternative pepsin, an aspartic protease, was systematically investigated for its use in digesting the mutated mIgG2a antibody to allow generation of signature peptides for the bioanalytical quantification purpose. After a series of evaluations, a rapid one-hour pepsin digestion protocol was established for the mutated Fc backbone. Consequently, a new pepsin digestion-based liquid chromatography-tandem mass spectrometry (LC/MS/MS) method was successfully developed to support the mouse pharmacokinetic (PK) sample analysis. In brief, robust and reproducible C-terminal cleavage of both leucine and phenylalanine near the double mutation site of the mutated mIgG2a was accomplished at pH ≤2 and 37°C. Combined with a commercially available rat anti-mIgG2a heavy-chain antibody, the established immunoaffinity LC/MS/MS assay achieved a limit of quantitation of 20 ng/mL in the dynamic range of interest with satisfactory assay precision and accuracy. The successful implementation of this novel approach in discovery PK studies eliminates the need for tedious and costly generation of specific immunocapturing reagents for the LAGA mutants. The approach should be widely applicable for developing popular LAGA mutant-based biological therapeutics.

Multivariate time series anomaly detection is a crucial data mining technique with a wide range of applications in areas such as IT applications. Currently, the majority of anomaly detection methods for time series data rely on unsupervised approaches due to the rarity of anomaly labels. However, in real-world scenarios, obtaining a limited number of anomaly labels is feasible and affordable. Effective usage of these labels can offer valuable insights into the temporal characteristics of anomalies and play a pivotal role in guiding anomaly detection efforts. To improve the performance of multivariate time series anomaly detection, we proposed a novel deep learning model named EDD (Encoder-Decoder-Discriminator) that leverages limited anomaly samples. The EDD model innovatively integrates a graph attention network with long short term memory (LSTM) to extract spatial and temporal features from multivariate time series data. This integrated approach enables the model to capture complex patterns and dependencies within the data. Additionally, the model skillfully maps series data into a latent space, utilizing a carefully crafted loss function to cluster normal data tightly in the latent space while dispersing abnormal data randomly. This innovative design results in distinct probability distributions for normal and abnormal data in the latent space, enabling precise identification of anomalous data. To evaluate the performance of our EDD model, we conducted extensive experimental validation across three diverse datasets. The results demonstrate the significant superiority of our model in multivariate time series anomaly detection. Specifically, the average F1-Score of our model outperformed the second-best method by 2.7% and 73.4% in both evaluation approaches, respectively, highlighting its superior detection capabilities. These findings validate the effectiveness of our proposed EDD model in leveraging limited anomaly samples for accurate and robust anomaly detection in multivariate time series data.

White interferograms are signals recorded using the interference of light with positional information obtained using a white interferometer, which is a laser technology that uses light interference for the non-contact measurement of the surface topography of a sample. In long-range measurements, the reflected light weakens with increasing distance. When the peak-to-peak value of interference fringe signals is less than the noise level interference fringes cannot be visually confirmed. We propose a neural network-based supervised learning method to detect white interference fringes in noisy conditions. The interference fringes obtained were transformed into time series signals and stored as images. Some of the data was used to train the neural network. Some data was used to validate the trained neural network. The trained model could distinguish between the presence and absence of white interference fringes in noise-contaminated conditions with a certain probability. Numerical calculations and optical experiments validated the proposed method. This technique can be applied to detect weak reflections and extend the interferometry measurement range.

IntroductionThe Wuzhishan ant (MY) chicken exhibits significant differences from other chicken breeds. However, the molecular genetic relationship between the MY breed and other chicken breeds has not been assessed.MethodsWhole-genome resequencing was used to compare genetic diversity, nucleotide diversity, the fixation index, the linkage disequilibrium coefficient, and phylogenetic tree relationships between the MY breed and the Wenchang (WC), Danzhou (DZ), Bawangling (BW), and Longsheng Feng (LF) breeds.ResultsA total of 21,586,378 singlenucleotide polymorphisms and 4,253,341 insertions/deletions were screened out among the five breeds. The MY breed had the second highest genomic genetic diversity and nucleotide diversity and the lowest LD coefficient among the five breeds. Moreover, the phylogenetic tree analysis showed that individual birds of each breed clustered together with those of their respective breeds.DiscussionOur data indicated that the MY breed is distinct from the other breeds and can be considered a new genetic resource.

The nonlinear Talbot effect means formation of self-imaging of the periodic structure by utilizing the harmonic wave instead of the fundamental one. Electromagnetically induced optical lattices established in atomic ensembles by optical induction technique have received great attention in recent years. Here, we experimentally demonstrate the nonlinear four wave mixing (FWM) Talbot effect in the Rubidium medium, where the third-order susceptibility χ(3) has periodic distribution due to the modulation from the incident pump light. Two kinds of periodic structure, the square lattice and hexagonal lattice, are employed to investigate the nonlinear FWM Talbot effect. The integer and fractional Talbot images produced by the FWM field are all obtained. The experimental results are qualitatively consistent with theoretical simulations. Different from the self-imaging of the refractive index in the linear optics, the FWM Talbot effect is the self-imaging of the periodic χ(3). The results may offer a high-resolution lensless way for imaging various optical periodic structures.

Abstract Background Graves' disease increases bone resorption in hyperthyroidism, leading to elevated serum calcium levels and a negative bone balance. Thymic hyperplasia is observed in some Graves' disease patients. What's more, there have been a few reports of increased serum calcium and severe osteoporosis induced by Graves’ disease with thymic hyperplasia. It remains unclear whether Graves’ disease with thymic hyperplasia is associated with higher serum calcium levels. Our study aimed to investigate the possibility of elevated serum calcium levels and aggravated bone mobilization in Graves’ disease patients with thymic hyperplasia. Methods Newly diagnosed and untreated patients with Graves' disease (n = 96) were enrolled. They were divided into two groups based on the incidental detection of thymic hyperplasia during imaging. Albumin, alkaline phosphatase, calcium, free triiodothyronine, free thyroxine, thyroid-stimulating hormone, and thyrotrophin receptor antibody (TRAb) were measured, and a computerized tomography of the chest was obtained. Results Patients with Graves’ disease who had thymic hyperplasia were notably younger (P=0.018) and exhibited higher serum calcium levels (P=0.001) compared to those with Graves’ disease without thymic hyperplasia. In the multiple regression analysis, thymic hyperplasia, TRAb, and female gender were significant variables associated with elevated serum calcium levels in patients with Graves' disease, collectively accounting for 31.7% of the variation in serum calcium. Conclusions Graves’ disease patients with thymic hyperplasia showed higher serum calcium levels. thymic hyperplasia, TRAb, and female gender were found to be correlated with increased serum calcium levels in Graves’ disease, suggesting a potential association between thymic hyperplasia and bone mobilization in Graves’ disease.

This study examines the distribution patterns of rural settlements from a new perspective of ethnic inter-embeddedness. The Shannon-Wiener Index (SWI) and Moran’s I methods are employed to identify the spatial distribution characteristics of rural settlements in a typical multi-ethnic gathering area. The study results are as follows: Firstly, the distribution patterns of rural settlements of different ethnic groups exhibit significant heterogeneity and remarkable differences in ethnicity and region. Each ethnic group has its core settlement areas in geography. Secondly, the results of Moran’s I represent clustering characteristics and gradient variations of spatial distribution. All ethnic groups exhibit significant aggregation characteristics except for Hui. The Global Moran’s I of Han, Yi, Tibetan, Mongolian, Qiang, and Hui ethnic groups are 0.771, 0.726, 0.646, 0.225, 0.123, and 0.037, respectively. Thirdly, the SWI results are classified into five categories: very high, high, medium, low, and very low, accounting for 23.53%, 23.53%, 19.60%, 15.69%, and 17.65%, respectively. Finally, the study find a negative correlation between the equilibrium of the minority population and the degree of inter-embeddedness of rural settlements. The study provides significant implications for promoting ethnic integration and connection, as well as optimizing the spatial patterns of rural settlements in multi-ethnic gathering areas.

Hyperbolic metamaterials (HMMs) are highly anisotropic materials with the unique property of generating electromagnetic modes. Understanding how these materials can be applied to control the propagation of light waves remains a major focus in photonics. In this study, we inserted a finite-size HMM rod into the point defect of two-dimensional photonic crystals (PhCs) and investigated the unique cavity modes of this hybrid system. The HMM enhances the efficiency of the cavity system in controlling light transmission. Numerical results demonstrate that the cavity modes based on HMMs can be categorized into various types, showing high Q-factors and promising potential for resonant modulation. Furthermore, the switching performance of the cavity with an HMM rod was examined, revealing that the finite-size HMM modes are highly frequency-sensitive and suitable for nonlinear controlled all-optical switching. These switches, characterized by low power consumption and high extinction ratios, are highly suitable for integration into photonic systems. Our investigation on the new type of HMM cavity illustrates that anisotropic materials can be effectively applied in cavity systems to generate highly efficient modes for filtering and switching.

Excessive copper (Cu2+) causes adverse effects on human health and the ecological environment. Traditional methods for detecting Cu2+ have drawbacks such as high detection costs, complex operating conditions, and being time consuming. Therefore, there is an urgent need to develop simple detection methods to better meet specific health and environment quality needs. In this work, a paper-based fluorescence sensor was prepared (herein referred to as the as-prepared method) by immersing filter paper in aqueous polyethyleneimine (PEI) solution, and its potential use in Cu2+ detection was investigated. The results showed that the as-prepared paper samples, with fluorescence properties obtained by aggregation-induced luminescence of PEI, have selective recognition of Cu2+ based on the internal filtration effect, and the lowest detection limit is 0.03 μM. In addition, the relative error of this method is in the range of 1.80~2.23%, which is relatively comparable to the national standard method (0.63~630 μM), demonstrating high accuracy. Therefore, paper-based sensors with a simple preparation method have potential applications in the detection of Cu2+ in water.

BackgroundThe output signal quality of optical encoder in nuclear radiation environment is degraded due to the total ionizing dose (TID) effect of γ radiation.PurposeThis study aims to propose an improved adaptive line enhancer method (IALEM) that considers accuracy and efficiency to minimize the degradation of the output signal quality of photoelectric encoders in nuclear radiation environments caused by TID effect of γ radiation.MethodsFirstly, the Softsign function was introduced into the least mean square (LMS) algorithm to establish the nonlinear relationship between the error and the step size. Then, rapid convergence and small steady-state errors were achieved by introducing the previous step size value in the step-size-updating formula. Furthermore, this improved adaptive line enhancer method (IALEM) was compared with similar algorithms in terms of four aspects: convergence speed, steady-state error, low signal-to-noise input, and computational volume. Finally, the proposed algorithm was implemented in a field programmable gate array (FPGA) chip and verified on a photoelectric encoder platform, and its filtering effect was experimentally validated in a cobalt-60-source γ-radiation environment.ResultsThe results show that the proposed algorithm yields a higher convergence speed, lower steady-state error, and better filtering effect than that of other algorithms for low signal-to-noise ratio signals with less computational effort. Uniformity error and orthogonality error of the photoelectric encoder output signal after filtering by IALEM are reduced by 17.6% and 8.0%, respectively.ConclusionsThe experimental results show that the proposed algorithm can effectively filter out the noise generated through γ radiation and improve the output signal quality of the photoelectric encoder.

Abstract Zn–CO2 batteries are excellent candidates for both electrical energy output and CO2 utilization, whereas the main challenge is to design electrocatalysts for electrocatalytic CO2 reduction reactions with high selectivity and low cost. Herein, the three‐phase heterojunction Cu‐based electrocatalyst (Cu/Cu2O‐Sb2O3‐15) is synthesized and evaluated for highly selective CO2 reduction to CO, which shows the highest faradaic efficiency of 96.3% at −1.3 V versus reversible hydrogen electrode, exceeding the previously reported best values for Cu‐based materials. In situ spectroscopy and theoretical analysis indicate that the Sb incorporation into the three‐phase heterojunction Cu/Cu2O‐Sb2O3‐15 nanomaterial promotes the formation of key *COOH intermediates compared with the normal Cu/Cu2O composites. Furthermore, the rechargeable aqueous Zn–CO2 battery assembled with Cu/Cu2O‐Sb2O3‐15 as the cathode harvests a peak power density of 3.01 mW cm−2 as well as outstanding cycling stability of 417 cycles. This research provides fresh perspectives for designing advanced cathodic electrocatalysts for rechargeable Zn–CO2 batteries with high‐efficient electricity output together with CO2 utilization.

ObjectiveBrucellosis, a significant zoonotic disease, not only impacts animal health but also profoundly influences the host immune responses through gut microbiome. Our research focuses on whole genome sequencing and comparative genomic analysis of these Brucella strains to understand the mechanisms of their virulence changes that may deepen our comprehension of the host immune dysregulation.MethodsThe Brucella melitensis strain CMCC55210 and its naturally attenuated variant CMCC55210a were used as models. Biochemical identification tests and in vivo experiments in mice verified the characteristics of the strain. To understand the mechanism of attenuation, we then performed de novo sequencing of these two strains.ResultsWe discovered notable genomic differences between the two strains, with a key single nucleotide polymorphism (SNP) mutation in the manB gene potentially altering lipopolysaccharide (LPS) structure and influencing host immunity to the pathogen. This mutation might contribute to the attenuated strain's altered impact on the host's macrophage immune response, overing insights into the mechanisms of immune dysregulation linked to intracellular survival. Furthermore, we explore that manipulating the Type I restriction-modification system in Brucella can significantly impact its genome stability with the DNA damage response, consequently affecting the host's immune system.ConclusionThis study not only contributes to understanding the complex relationship between pathogens, and the immune system but also opens avenues for innovative therapeutic interventions in inflammatory diseases driven by microbial and immune dysregulation.

Background: Brachial plexus injury is a common severe peripheral nerve injury with high disability. At present, the bibliometric analysis of brachial plexus injury is basically unknown. Methods: This article analyzes the data retrieved to the web of science and uses the R language (version 4.2), Citespace (version 6.1.R3 Advanced), Vosviewer (Lei deng university) to make a scientific map. Specifically, we analyze the main publication countries, institutions, journals where the article is published, and the cooperative relationship between different institutions, the relationship between authors, main research directions in this field, and current research hotspots. Results: From 1980 to 2022, the total number of publications is 1542. In terms of countries where articles were published, 551 records were published in the United States, accounting for 35% of the total. With 74 articles, Fudan University ranks first in the world in terms of the number of articles issued by the institution, followed by 72 articles from Mayo Clinic. The magazine with the largest number of articles is JOURNAL OF HAND SURGERY-AMERICAN VOLUME, which has published 87 articles in total. GU YD (Gu Yu-Dong) team (Fudan University) and spinner RJ (Robert J Spinner) team (Mayo clinic) are in a leading position in this field. Nerve transfer and nerve reconstruction have been a hot topic of brachial plexus injury. ''Spinal nerve root repair and reimplantation of avulsed ventral roots into the spinal cord after brachial plexus injury'' has the strongest citation bursts. Conclusion: Research on brachial plexus injury shows a trend of increasing heat. At present, there is a lack of communication and cooperation between scholars from different countries. Nerve transfer and nerve reconstruction are the current and future research directions in the treatment of brachial plexus injury.

SignificanceThe scientific dataset of agricultural pests and diseases is the foundation for monitoring and warning of agricultural pests and diseases. It is of great significance for the development of agricultural pest control, and is an important component of developing smart agriculture. The quality of the dataset affecting the effectiveness of image recognition algorithms, with the discovery of the importance of deep learning technology in intelligent monitoring of agricultural pests and diseases. The construction of high-quality agricultural pest and disease datasets is gradually attracting attention from scholars in this field. In the task of image recognition, on one hand, the recognition effect depends on the improvement strategy of the algorithm, and on the other hand, it depends on the quality of the dataset. The same recognition algorithm learns different features in different quality datasets, so its recognition performance also varies. In order to propose a dataset evaluation index to measure the quality of agricultural pest and disease datasets, this article analyzes the existing datasets and takes the challenges faced in constructing agricultural pest and disease image datasets as the starting point to review the construction of agricultural pest and disease datasets.ProgressFirstly, disease and pest datasets are divided into two categories: private datasets and public datasets. Private datasets have the characteristics of high annotation quality, high image quality, and a large number of inter class samples that are not publicly available. Public datasets have the characteristics of multiple types, low image quality, and poor annotation quality. Secondly, the problems faced in the construction process of datasets are summarized, including imbalanced categories at the dataset level, difficulty in feature extraction at the dataset sample level, and difficulty in measuring the dataset size at the usage level. These include imbalanced inter class and intra class samples, selection bias, multi-scale targets, dense targets, uneven data distribution, uneven image quality, insufficient dataset size, and dataset availability. The main reasons for the problem are analyzed by two key aspects of image acquisition and annotation methods in dataset construction, and the improvement strategies and suggestions for the algorithm to address the above issues are summarized. The collection devices of the dataset can be divided into handheld devices, drone platforms, and fixed collection devices. The collection method of handheld devices is flexible and convenient, but it is inefficient and requires high photography skills. The drone platform acquisition method is suitable for data collection in contiguous areas, but the detailed features captured are not clear enough. The fixed device acquisition method has higher efficiency, but the shooting scene is often relatively fixed. The annotation of image data is divided into rectangular annotation and polygonal annotation. In image recognition and detection, rectangular annotation is generally used more frequently. It is difficult to label images that are difficult to separate the target and background. Improper annotation can lead to the introduction of more noise or incomplete algorithm feature extraction. In response to the problems in the above three aspects, the evaluation methods are summarized for data distribution consistency, dataset size, and image annotation quality at the end of the article.Conclusions and ProspectsThe future research and development suggestions for constructing high-quality agricultural pest and disease image datasets based are proposed on the actual needs of agricultural pest and disease image recognition:(1) Construct agricultural pest and disease datasets combined with practical usage scenarios. In order to enable the algorithm to extract richer target features, image data can be collected from multiple perspectives and environments to construct a dataset. According to actual needs, data categories can be scientifically and reasonably divided from the perspective of algorithm feature extraction, avoiding unreasonable inter class and intra class distances, and thus constructing a dataset that meets task requirements for classification and balanced feature distribution. (2) Balancing the relationship between datasets and algorithms. When improving algorithms, consider the more sufficient distribution of categories and features in the dataset, as well as the size of the dataset that matches the model, to improve algorithm accuracy, robustness, and practicality. It ensures that comparative experiments are conducted on algorithm improvement under the same evaluation standard dataset, and improved the pest and disease image recognition algorithm. Research the correlation between the scale of agricultural pest and disease image data and algorithm performance, study the relationship between data annotation methods and algorithms that are difficult to annotate pest and disease images, integrate recognition algorithms for fuzzy, dense, occluded targets, and propose evaluation indicators for agricultural pest and disease datasets. (3) Enhancing the use value of datasets. Datasets can not only be used for research on image recognition, but also for research on other business needs. The identification, collection, and annotation of target images is a challenging task in the construction process of pest and disease datasets. In the process of collecting image data, in addition to collecting images, attention can be paid to the collection of surrounding environmental information and host information. This method is used to construct a multimodal agricultural pest and disease dataset, fully leveraging the value of the dataset. In order to focus researchers on business innovation research, it is necessary to innovate the organizational form of data collection, develop a big data platform for agricultural diseases and pests, explore the correlation between multimodal data, improve the accessibility and convenience of data, and provide efficient services for application implementation and business innovation.

Gears fabricated using powder metallurgy technique (PMT) have the potential to replace traditional wrought gears due to their very high forming efficiency and relatively low cost. However, their practical applications are restricted due to the lack of understanding of their fatigue properties and failure mechanisms. This work investigates the contact fatigue performance and corresponding failure mechanism of a typical Fe-based small-module gears fabricated by PMT. The fatigue tests were conducted under grease lubrication condition, using a power-opened small-module gear testing rig. The experimental results show that the current PMT fabricated small-module gears exhibit contact fatigue properties comparable to those of traditional wrought steel gears. It has been found that the subsurface cracks induced from pores are the dominant cause of spalling of PMT fabricated small-module gears during rolling contact. The cracks tend to propagate between adjacent pores, playing a vital role in the overall fatigue life. Thus, this study suggests that PMT can be a successful method for fabricating Fe-based small-module gears with excellent contact fatigue property if formation of pores during fabrication is well inhibited.

Abstract Background Marine Lenhart syndrome is a rare disease and causes refractory hyperthyroidism. So far, little evidence on the combination of both Marine Lenhart syndrome and Hashimoto's thyroiditis is available. We suspect that Marine Lenhart syndrome when combined with Hashimoto's thyroiditis might have its particular features, which are not exactly the same as those of the isolated Marine Lenhart syndrome. Case presentation A 56-year-old middle-aged man presented with recurrent hyperthyroidism, and Graves' disease combined with Hashimoto's thyroiditis was considered. Radionuclide imaging showed a hot nodule, but ultrasonography suggested the possibility of malignancy with a category of 4B according to the Chinese-Thyroid Imaging-Reporting and Data System (C-TIRADS) model. Fine needle aspiration cytology (FNAC) revealed eosinophilic follicular lesions with papillary features, and prompted that papillary thyroid carcinoma could not be excluded. Partial thyroidectomy was performed and the nodule was proven to be benign by histopathology. The final diagnosis was atypical Marine Lenhart syndrome with Hashimoto's thyroiditis. Conclusions Marine Lenhart syndrome combined with Hashimoto's thyroiditis has its particular characteristics, showing some signs mimicking malignancy. Limitations of ultrasonography and FNAC in diagnosis should be noted in these scenarios.

It is of great significance for coal safety production and water resource protection in the Yuheng mining area to master the evolution law of water-conducting fractures under the condition of thick and hard overburden. This research focuses on the 2102 fully mechanized mining face in the Balasu Coal Mine as the research background. The fracture evolution and strata movement characteristics in thick and hard overlying strata are simulated and analyzed by combining numerical simulation with physical simulation, and the formation mechanism of a water-conducting fracture in the overlying strata is revealed and verified by field measurements of the development height of “two zones”. The results show that the anisotropy of fracture propagation in low-position overlying strata is high, and the fracture propagation in high-position overlying strata is mainly vertical, which indicates characteristics of leapfrog development. The number and development height of fractures undergo the change–growth process of “slow–rapid–uniform”. Multiple rock strata together form a complex force chain network with multiple strong chain arches. The local stress concentration leads to the initiation of micro-cracks in contact fractures, and the cracks gradually penetrate from bottom to top and then the strong chain arches are broken. The water-conducting cracks in overlying strata show a dynamic expansion process of “local micro-cracks–jumping cracks–through cracks–water-conducting cracks”. The fracture between the caving zone and fracture zone presents obvious layered characteristics, the overall shape of the water-conducting fracture zone is “saddle-shaped”, and the maximum development height lags behind the coal mining face by about 180 m. Through the observation of water injection leakage and borehole TV observation of three boreholes under underground construction, combined with the results of water pressure tests, it is comprehensively determined that the height of the water-conducting fracture zone is 103.68~107.58, and the fracture–production ratio is 31.42~32.60, which is basically consistent with the results of numerical simulation and physical simulation. This research provides theoretical guidance and a scientific basis for coal mine water disaster prevention under similar geological conditions.

Circ_0038467 and miR-203 exert important functions in lipopolysaccharide (LPS)-induced inflammation, which contributes to osteoarthritis (OA). Our preliminary deep sequencing analysis revealed altered expression of Circ_0038467 and miR-203 in OA and a close correlation between them. This study was therefore to explore crosstalk between them in OA. The expression of Circ_0038467, mature miR-203, and miR-203 precursor in OA patients and controls was determined using RT-qPCR. An overexpression assay was performed to explore the role of Circ_0038467 in regulating the expression of mature miR-203 and miR-203 precursor. Cell apoptosis was analyzed by cell apoptosis assay. Circ_0038467 was upregulated in OA and positively correlated with mature miR-203 but not that of miR-203 precursor. In chondrocytes, increased expression levels of both Circ_0038467 and miR-203 were observed after LPS treatment. In chondrocytes, overexpression of Circ_0038467 increased the expression levels of mature miR-203 but not that of miR-203 precursor. Overexpression of Circ_0038467 and miR-203 increased cell apoptosis. Then, the miR-203 inhibitor reversed the effects of overexpression of Circ_0038467 on cell apoptosis. Interestingly, Circ_0038467 was detected in both the cytoplasm and nucleus. Circ_0038467 directly interacted with the precursor miR-203. Therefore, Circ_0038467 is highly expressed in OA and it may promote the production of mature miR-203 to increase apoptosis of chondrocytes induced by LPS.

The problem of coal-gangue identification is one of the technical problems that have not been effectively solved for a long time in the coal industry. By analyzing the characteristics and limitations of existing coal-gangue identification methods, the feasibility of coal-gangue identification based on microwave detection technology is discussed. Firstly, the electromagnetic parameters of different coals and gangues are measured and analyzed to provide a basis for the subsequent analysis of sample test results. Then, in order to explore the influence of coal gangue size parameters on microwave propagation, the propagation law of coal gangue dielectric samples with different thickness and cross-sectional area on different frequency bands is studied. Because the coal-gangue mixture is a multi-scale medium composed of coal, gangue and air, the volume and shape are different, and the spatial distribution and mixing form are complex and changeable. The scattering effect in the microwave irradiation area is very complex, resulting in obvious differences in the transmission characteristics of electromagnetic waves in different coal-gangue mixtures. Finally, in order to explore the variation law of microwave propagation characteristics in different coal-gangue media, some microwave detection experiments of coal-gangue mixture under different microwave frequency bands, different particle sizes and different gangue contents are carried out. The results show that: the electromagnetic parameters, thickness and sectional area have obvious influence on the propagation law of microwave in the media. Different particle size and gangue rate have certain influence on microwave propagation in coal-gangue mixture. When microwave with frequency greater than 4 GHz irradiates the coal gangue mixture, the increase of particle size will gradually increase the intensity values of S11 and S21 and the amplitude of O21 signal. When the electromagnetic parameters of coal and gangue in the mixed medium are quite different, after the frequency is greater than 3.5 GHz, the increase of particle size reduces the S21 intensity from −35.3 dB to −38.2 dB, and the O21 signal amplitude from 1.6 mV to 1.26 mV, with certain time delay characteristics. Through the experimental analysis, the differences of the transmitted wave signal intensity value, the time-domain transmitted wave signal amplitude and the transmitted wave signal delay at the sensitive frequency points can be mastered, so as to provide a new idea and method for accurate identification of coal and gangue in top coal caving face.

Several studies have reported the efficacy of traditional Chinese medicine (TCM) for central serous chorioretinopathy (CSC), while some ophthalmologists are concerned that TCM may be a risk factor for CSC as some chinese herbs contain hormonal ingredients. This study aimed to evaluate the efficacy and safety of TCM in treating patients with CSC. Randomized controlled trials (RCTs) and observational studies of TCM for CSC were searched up to July 10, 2023 on the following biological databases without language and publication time restrictions: PubMed, Ovid Medline, Embase, Cochrane Library, The Chinese National Knowledge Infrastructure Database (CNKI), Technology Periodical Database (VIP), Wanfang, and Chinese Biomedical Literature Service System (SinoMed). Review Manager V.5.4.1 and Stata 14 software were used for data analysis. Finally, thirty-eight studies were finally included including 23 RCTs and 15 cohort studies. The meta-analysis showed that compared with the routine treatment alone, the combination of TCM can not only reduce the recurrence rate (OR = 0.29, 95% CI: 0.21,0.40; I2 = 0%) and central retinal thickness (CRT) (MD = - 35.63, 95% CI: - 45.96,-25.30; I2 = 89%) of CSC, but improve patients' best corrected visual acuity (BCVA) (SMD = 0.86, 95% CI: 0.62,1.11; I2 = 77%); additionally, it has no obvious side effects compared with routine treatment (OR = 0.72, 95% CI: 0.39,1.34; I2 = 10%). Overall, this study shows that the use of TCM does not increase the risk of CSC recurrence; on the contrary, the combination of TCM may reduce the recurrence of CSC and improve BCVA and CRT in patients with CSC compared with conventional treatment.

The development of intensive care medicine is inseparable from the diversified monitoring data. Intensive care medicine has been closely integrated with data since its birth. Critical care research requires an integrative approach that embraces the complexity of critical illness and the computational technology and algorithms that can make it possible. Considering the need of standardization of application of big data in intensive care, Intensive Care Medicine Branch of China Health Information and Health Care Big Data Society, Standard Committee has convened expert group, secretary group and the external audit expert group to formulate Chinese Experts’ Consensus on the Application of Intensive Care Big Data (2022). This consensus makes 29 recommendations on the following five parts: Concept of intensive care big data, Important scientific issues, Standards and principles of database, Methodology in solving big data problems, Clinical application and safety consideration of intensive care big data. The consensus group believes this consensus is the starting step of application big data in the field of intensive care. More explorations and big data based retrospective research should be carried out in order to enhance safety and reliability of big data based models of critical care field.

2,2′,7,7′-Tetrakis(N,N-di-p-methoxyphenyl)-amine-9,9′-spirobifluorene (Spiro-OMeTAD) represents the state-of-the-art hole-transporting material (HTM) in n-i-p perovskite solar cells (PSCs). However, its susceptibility to stability issues has been a long-standing concern. In this study, we embark on a comprehensive exploration of the untapped potential within the family of spiro-type HTMs using an innovative anisotropic regulation strategy. Diverging from conventional approaches that can only modify spirobifluorene with single functional group, this approach allows us to independently tailor the two orthogonal components of the spiro-skeleton at the molecular level. The newly designed HTM, SF-MPA-MCz, features enhanced thermal stability, precise energy level alignment, superior film morphology, and optimized interfacial properties when compared to Spiro-OMeTAD, which contribute to a remarkable power conversion efficiency (PCE) of 24.53% for PSCs employing SF-MPA-MCz with substantially improved thermal stability and operational stability. Note that the optimal concentration for SF-MPA-MCz solution is only 30 mg/ml, significantly lower than Spiro-OMeTAD (>70 mg/ml), which could remarkably reduce the cost especially for large-area processing in future commercialization. This work presents a promising avenue for the versatile design of multifunctional HTMs, offering a blueprint for achieving efficient and stable PSCs.

Summary: Poor skin wound healing, which is common in patients with diabetes, is related to imbalanced macrophage polarization. Here, we find that nutrition sensor GCN2 (general control nonderepressible 2) and its downstream are significantly upregulated in human skin wound tissue and mouse skin wound macrophages, but skin wound-related GCN2 expression and activity are significantly downregulated by diabetes and hyperglycemia. Using wound healing models of GCN2-deleted mice, bone marrow chimeric mice, and monocyte-transferred mice, we show that GCN2 deletion in macrophages significantly delays skin wound healing compared with wild-type mice by altering M1 and M2a/M2c polarization. Mechanistically, GCN2 inhibits M1 macrophages via OXPHOS-ROS-NF-κB pathway and promotes tissue-repairing M2a/M2c macrophages through eukaryotic translation initiation factor 2 (eIF2α)-hypoxia-inducible factor 1α (HIF1α)-glycolysis pathway. Importantly, local supplementation of GCN2 activator halofuginone efficiently restores wound healing in diabetic mice with re-balancing M1 and M2a/2c polarization. Thus, the decreased macrophage GCN2 expression and activity contribute to poor wound healing in diabetes and targeting GCN2 improves wound healing in diabetes.

We propose a novel approach to address the problem of measurement accuracy in analyzing the distance between the peak positions of interference envelopes in multi-pulse train (MPT) interferometry. In the frequency domain, a bandpass filter cannot remove all noise since the deterministic signal and noise overlap in the frequency domain. In the proposed method, by focusing on the differences in the statistical properties of deterministic signal and noise, matched filter processing eliminates any uncorrelated noise signals, thereby achieving noise reduction. This paper describes the procedure of the proposed method and its development based on a simple interference fringe model. The proposed approach is introduced within the framework of a MPT interferometer, and the experimental results demonstrate its superiority in determining the distance between peaks over the conventional Fourier transform method. This technique can be useful for high-precision measurement of distances for scientific purposes as well as industrial applications.

AbstractDelivery of drugs to special locations of ocular lesions, while minimizing systemic and local toxic effects, is recognized as a critical challenge in the ophthalmic practice. The special anatomy and physiology barriers within the eyeball entail effective drug delivery systems. Emerging attempts in drug delivery has led to developments in ocular iontophoresis, which acts as a noninvasive technology to enhance drug penetration using a small electric current. This technique offers greater flexibility to deliver desired drug dose in a controlled and tolerable manner. In previous studies, this technique has been testified to deliver antibiotics, corticoid, proteins and other gene drugs into the eye with the potency of treating or alleviating diverse ophthalmological diseases including uveitis, cataract, retinoblastoma, herpes simplex and cytomegalovirus retinitis (CMVR), etc. In this review, we will introduce the recent developments in iontophoresis device. We also summarize the latest progress in coulomb controlled iontophoresis (CCI), hydrogel ionic circuit (HIC) and EyeGate II delivery system (EGDS), as well as overview the potential toxicity of iontophoresis. We will discuss these factors that affect the efficacy of iontophoresis experiments, and focus on the latest progress in its clinical application in the treatment of eye diseases.

Crack detection plays a pivotal role in civil engineering applications, where vision-based methods find extensive use. In practice, crack images are sourced from Unmanned Aerial Vehicles (UAV) and handheld photography, and the balance between the utilization of global and local information is the key to detecting cracks from images of different sources: the former tends to eliminate interferences with a global perspective, whereas the latter pays more attention to the description of local details of cracks. However, many existing methods primarily target crack detection in handheld photographs and may not perform optimally on UAV-generated images or those with variable backgrounds or from different sources. In response to this challenge, we propose a robust and innovative method called Crack Detection with Structure Line (CDSL). The primary steps of this method can be summarized as follows: first, based on local information, an indicator called the “crack measure” is derived to directly generate a continuous crack map for effective image binarization; then, based on global information, the crack map is simplified in a unified and analyzable form using structure lines to perform a robust optimization for high-precision crack detection. The experiments we conducted on two publicly available datasets showed that CDSL provided competitive crack detection performance and outperformed four classical or current state-of-the-art methods by at least 13.0 % in the UAV dataset we collected.

Combat intent recognition refers to analyzing the enemy target's state information to interpret and judge the purpose of the enemy. With the increased knowledge of combat platforms, these time-series enemy state presents multi-dimensional and massive characteristics. Using neural networks to learn enemy state information has become a research trend in the face of such traits. To address these challenges, we propose a hierarchical aggregation model to recognize the intention of the target. The bottom layer of our model is based on convolutional neural network(CNN) to perceive behavior features, and the middle layer is based on Bi-LSTM(Bi-directional long short-term memory) to aggregate the long-time interdependence information between sub-intentions. The top layer focuses on higher-level features that contribute more to the recognition of intent through the attention mechanism and finally combines the global information to recognize the intention. Extensive experimental results show the superiority of our model in that the recognition accuracy achieves 88.83%, which can solve the problem of identifying air target intent on the modern battlefield.

This paper summarized the cluster nursing management for a patient with lumbar disc herniation induced low back pain combined with hyperglycemia. The patient received lumbar paravertebral nerve block, and was diagnosed with hyperglycemia before the surgery. Based on the nursing risk assessment, the cluster nursing management including perioperative blood sugar monitoring, postoperative observation and health education were carried out to ensure the surgical safety and improve the prognosis and postoperative rehabilitation of the patient. (本文总结1例腰椎间盘突出症腰痛合并血糖升高患者的集束化护理管理体会。患者接受椎旁神经单次阻滞镇痛治疗, 治疗前发现血糖升高。在完善护理评估的基础上, 加强围手术期血糖监测、术后观察和健康宣教, 旨在确保患者围手术期安全, 改善预后, 促进康复。)

This article summarized the nursing measures for a patient with insomnia treated by auricular acupoint sticking and pressing combined with stellate ganglion block. Based on nursing risk assessment, emotion care, dietary guidance and other routine nursing measures, the combination treatment of auricular acupoint sticking and pressing and stellate ganglion block was carried out to regulate the flow of blood and qi and dredge the channels and collaterals, relieve symptoms of insomnia and improve the sleeping quality of the patient. (本文总结耳穴贴压联合星状神经节阻滞治疗1例失眠患者的护理经验。在护理评估、情志护理、饮食调护等常规护理的基础上, 开展耳穴贴压联合星状神经节阻滞干预, 通过疏通气血经络, 调节神经系统, 从而改善患者失眠症状, 提高患者睡眠质。)

In this study, the dry–wet cycle test of chloride salt was carried out on aeolian sand concrete with different contents, and the chloride ion content in aeolian sand concrete was determined by taking powder from different depths on one side of the test block. And then combined with Monte Carlo stochastic statistical simulation and Weibull probability distribution function, the service life prediction model of aeolian sand concrete against chloride ion erosion is established. The results show that the free chloride ion content in aeolian sand concrete decreases with the increase in the depth from the surface of the specimen. At the same depth from the surface of the specimen, the free chloride ion content gradually increases with the increase in the number of dry–wet cycles. Through the analysis of life prediction, it is concluded that with the increase in aeolian sand content, the service life of aeolian sand concrete increases first and then decreases. The service life value of concrete with 75% aeolian sand content is the largest, and the greater the thickness of the protective layer, the more favorable the service life value.