Search

Abstract Parkinson’s disease (PD) is the second most common neurodegenerative disease. The development of PD is closely linked to genetic and environmental factors, with GBA1 variants being the most common genetic risk. Mutations in the GBA1 gene lead to reduced activity of the coded enzyme, glucocerebrosidase, which mediates the development of PD by affecting lipid metabolism (especially sphingolipids), lysosomal autophagy, endoplasmic reticulum, as well as mitochondrial and other cellular functions. Clinically, PD with GBA1 mutations (GBA1-PD) is characterized by particular features regarding the progression of symptom severity. On the therapeutic side, the discovery of the relationship between GBA1 variants and PD offers an opportunity for targeted therapeutic interventions. In this review, we explore the genotypic and phenotypic correlations, etiologic mechanisms, biomarkers, and therapeutic approaches of GBA1-PD and summarize the current state of research and its challenges.

Abstract Background Clean energy hydrogen (H2) produced from abundant lignocellulose is an alternative to fossil energy. As an essential influencing factor, there is a lack of comparison between constant temperatures (35, 55 and 65 °C) and gradient heating temperature (35 to 65 °C) on the H2 production regulation potential from lignocellulose-rich straw via high-solid anaerobic digestion (HS-AD). More importantly, the microbial mechanism of temperature regulating H2 accumulation needs to be investigated. Results Constant 65 °C led to the lowest lignin residue (1.93%) and the maximum release of cellulose and hemicellulose, and the highest H2 production (26.01 mL/g VS). H2 production at 35 and 55 °C was only 14.56 and 24.13 mL/g VS, respectively. In order to further explore the potential of ultra-high temperature (65 °C), HS-AD was performed by gradient heating conditions (35 to 65 °C). However, compared to constant 65 °C, gradient heating conditions led to higher lignin residue (2.49%) and lower H2 production (13.53 mL/g VS) than gradient heating conditions (47.98%). In addition, metagenomic analysis showed the cellulose/hemicellulose hydrolyzing bacteria and genes (mainly Thermoclostridium, and xynA, xynB, abfA, bglB and xynD), H2-producing bacteria and related genes (mainly Thermoclostridium, and nifD, nifH and nifK), and microbial movement and metabolic functions were enriched at 65 °C. However, the enrichment of two-component systems under gradient heating conditions resulted in a lack of highly-enriched ultra-high-temperature cellulose/hemicellulose hydrolyzing genera and related genes but rather enriched H2 consumption genera and genes (mainly Acetivibrio, and hyaB and hyaA) resulting in a weaker H2 production. Conclusions The lignin degradation process does not directly determine H2 accumulation, which was actually regulated by bacteria/genes contributing to H2 production/consumption. In addition, it is temperature that enhances the hydrolysis process of lignin rather than lignin-degrading enzymes, bacteria and genes by promoting microbial material transfer and metabolism. In terms of temperature, one of the key parameters of HS-AD for H2 production, we developed an important regulatory strategy, enriched the theoretical basis of temperature regulation for H2 production to further expanded the research horizon in this field. Video Abstract

River scour and siltation, inherently prolonged and multifaceted phenomena, profoundly impact the hydraulic conductivity and navigational safety of waterways, thereby rendering the precise forecasting of their fluctuations a paramount and unresolved challenge. This study embarks on a novel investigative trajectory by examining energy dissipation in rivers, specifically through the scrutiny of empirical hydrological records. Employing the principles of energy balance theory, this study elucidates the intricate connection between energy losses and sedimentation volumes in the upper reaches of the Yangtze River and at its confluence with the significant tributary, the Jialing River.Our findings diverge from conventional wisdom, revealing that standard metrics of energy loss, encompassing kinetic, potential, and total mechanical energies, along with momentum losses, inadequately characterize the complexity of sediment deposition processes. In contrast, we demonstrate that the loss of suspension power is a more indicative measure of sedimentation quantity. Through meticulous comparisons of various formulations for calculating suspension power, we identified a formula grounded in the concept of minimal available power dissipation in river systems that exhibits superior accuracy in correlating suspension power losses with sedimentation patterns in river sections. This formula's efficacy is further enhanced when considering aggregate suspension power dissipation under the influence of tributary inflows, enabling refined predictions of sedimentation variations along river segments. In conclusion, the insights derived from this meticulous research contribute significantly to the realm of river resource management and the pursuit of sustainable, high-quality aquatic ecosystem development.

BackgroundThe relationship between serum uric acid (SUA) and osteoporosis (OP) has yielded conflicting results in observational studies. This Mendelian randomization (MR) study aims to elucidate the causal association between SUA and OP.MethodsA two-sample MR analysis was conducted using summary-level data from genome-wide association studies (GWAS). Two sets of polygenic instruments strongly associated (p < 5 × 10-8) with SUA were extracted from the CKDGen consortium and UK biobank. Polygenic instruments associated with OP (p < 5 × 10-8) were derived from FinnGen biobank and UK biobank. Inverse variance weighting (IVW) was employed as the primary analysis method. Additionally, we utilized MR-Egger, weighted median, the simple mode method, and the weighted mode as complementary analyses. Cochran’s Q statistics were used to assess heterogeneity, with MR-Egger intercept testing and MR pleiotropy residual sum and outlier (MR-PRESSO) to examine horizontal pleiotropy. Sensitivity analysis was performed using the leave-one-out method.ResultsThe IVW analysis conducted across four groups confirms no significant causal relationship between SUA concentration and OP: UKB-UKB (OR: 1.001, 95% CI: 0.999-1.003, p=0.464), CKD-UKB (OR: 1.001, 95% CI: 0.999-1.003, p=0.349), UKB-Fin (OR: 0.934, 95% CI: 0.747-1.168, p=0.549), CKD-Fin (OR: 1.041, 95%CI: 0.934-1.161, p=0.470). Furthermore, additional four MR analyses corroborated these findings. Upon excluding all outliers identified by the MR-PRESSO test, no significant directional pleiotropy was observed, except for some data heterogeneity noted in the UKB-UKB group (Q=50.65, P=0.002). Additionally, a leave-one-out analysis indicated that no single SNP exerted undue influence on the results.ConclusionThis MR analysis provides convincing genetic evidence that there is no causal association between SUA and OP, SUA is unlikely to increase or reduce the risk of OP.

Abstract As living standards improve, mental and physical health have been gaining increasing attention. Presently, depression is one of the most severe mental health issues. Depression affects the quality of life of affected individuals because it lasts for a very long time and is generally difficult to cure. Currently, pharmacotherapy and psychotherapy are the two main approaches for treating depression. However, some principles and characteristics of pharmacotherapy remain unclear, and its side effects are significant and noticeable. In addition, ordinary psychotherapy requires the assistance of a qualified psychotherapist, which is usually hard to find and expensive. Both methods are burdensome to the patients, making it difficult for them to benefit. As an easy‐to‐obtain therapy, music therapy has been recommended by physicians as an auxiliary therapy for various diseases to regulate patients' emotions and help the primary treatment methods to obtain better therapeutic effects. This review investigates and summarizes recent articles on the pathogenesis of depression and the effects of music therapy on depression. Its results show that music therapy is effective and available. However, a systematic treatment plan has not yet been formulated due to the lack of samples and short follow‐up times. Future studies should include more samples and follow‐up patients after the treatment period to address the continuous effect and principle of music therapy.

Abstract Background Volatile organic compounds (VOCs) encompass hundreds of high production volume chemicals and have been reported to be associated with adverse respiratory outcomes such as chronic obstructive pulmonary disease (COPD). However, research on the combined toxic effects of exposure to various VOCs on COPD is lacking. We aimed to assess the effect of VOC metabolite mixture on COPD risk in a large population sample. Methods We assessed the effect of VOC metabolite mixture on COPD risk in 5997 adults from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2020 (pre-pandemic) using multivariate logistic regression, Bayesian weighted quantile sum regression (BWQS), quantile-based g-Computation method (Qgcomp), and Bayesian kernel machine regression (BKMR). We explored whether these associations were mediated by white blood cell (WBC) count and total bilirubin. Results In the logistic regression model, we observed a significantly increased risk of COPD associated with 9 VOC metabolites. Conversely, N-acetyl-S-(benzyl)-L-cysteine (BMA) and N-acetyl-S-(n-propyl)-L-cysteine (BPMA) showed insignificant negative correlations with COPD risk. The overall mixture exposure demonstrated a significant positive relationship with COPD in both the BWQS model (adjusted odds ratio (OR) = 1.30, 95% confidence interval (CI): 1.06, 1.58) and BKMR model, and with marginal significance in the Qgcomp model (adjusted OR = 1.22, 95% CI: 0.98, 1.52). All three models indicated a significant effect of the VOC metabolite mixture on COPD in non-current smokers. WBC count mediated 7.1% of the VOC mixture associated-COPD in non-current smokers. Conclusions Our findings provide novel evidence suggesting that VOCs may have adverse associations with COPD in the general population, with N, N- Dimethylformamide and 1,3-Butadiene contributing most. These findings underscore the significance of understanding the potential health risks associated with VOC mixture and emphasize the need for targeted interventions to mitigate the adverse effects on COPD risk.

Abstract The growth of multimedia applications poses new challenges to software facilities in edge computing. Developers must effectively develop edge computing software to accommodate the rapid expansion of multimedia applications. Code search has become a prevalent practice to enhance the efficiency of the construction of edge software infrastructure. Researchers have proposed lots of approaches for code search, and employed deep learning technology to extract features from program representations, such as token, AST, graphs, method name, and API. Nevertheless, two prominent issues remain: 1) there are only a few studies on the effective use of graph representation for code search (especially in Java language), and 2) there is a lack of empirical study on the contributions of different program representations. To address these issues, we conduct an empirical study to explore program representations, especially program graphs. To the best of our knowledge, this is the first attempt to conduct code search with mixed graphs representation for Java language, containing the control flow graph and the program dependence graph. We also present a hybrid approach to capture and fuse the features of a program with representations of Token, AST, and Mixed Graphs (TAMG). The results of our experiment show that our approach possesses the best ability (R@1 with 37% and R@10 with 67.1%). Our graph representation exhibits a positive effect, and the token and AST also have a significant contribution to the code search. Our findings can aid developers in efficiently searching for the desired code while constructing the software infrastructure for edge computing, which is crucial for the rapid expansion of multimedia applications.

ABSTRACT To monitor the resistance rate and gain a deeper understanding of the resistance mechanisms, we conducted over a 2-year surveillance focusing on the Klebsiella pneumoniae associated with the clinical usage of ceftazidime-avibactam (CZA) in a teaching hospital. A total of 4,641 K. pneumoniae isolates were screened to identify the CZA resistance through antimicrobial susceptibility testing. Comprehensive analyses, including homology analysis, conjugation experiments, clone assays, and whole genome sequencing, were furtherly performed on the CZA-resistant strains. In total, four CZA-resistant K. pneumoniae (CZA-R-Kp) strains were separated from four patients, in which three of them received CZA treatment during the hospitalization, accounting for a 4% (3/75) resistance development rate of K. pneumoniae under CZA stress. All CZA-R-Kp isolates were found to possess variants of blaKPC-2. The identified mutations included blaKPC-33, blaKPC-86, and a novel variant designated as blaKPC-129, all of which were located in the Ω loop of the KPC enzyme. These mutations were found to impact the amino acid sequence and spatial structure of the enzyme’s active center, consequently affecting KPC carbapenemase activity. This study underscores the importance of active surveillance to monitor the emergence of resistance to CZA, highlighting the need for ongoing research to develop effective strategies for combating antimicrobial resistance. Understanding the mechanisms behind resistance is crucial in maintaining the efficacy of CZA, a vital tool in the battle against multidrug-resistant infections.IMPORTANCEAs an effective drug for the treatment of carbapenem-resistant Klebsiella pneumoniae, ceftazidime-avibactam (CZA) began to develop resistance in recent years and showed an increasing trend. In order to effectively monitor the resistance rate of CZA and understand its resistance mechanism, we monitored K. pneumoniae for more than 2 years to find CZA-resistant strains. Through comprehensive analysis of the selected CZA-resistant strains, it was found that all the CZA-resistant strains had mutation, which could affect the activity of KPC carbapenemase. This study highlights the importance of proactive surveillance to monitor the emergence of CZA resistance, which highlights the need for ongoing research to develop effective strategies to combat antimicrobial resistance. Understanding the mechanisms behind resistance is critical to maintaining the effectiveness of CZA, an important tool in the fight against multidrug-resistant infections.

Transparent exopolymer particles (TEP), a major component of coral mucus, are responsible for particle aggregation. These particles contribute substantially to the carbon cycle in coral reefs, and serve as an energy source for bacteria and other microorganisms. Water flows and induced turbulent mixing control material exchange between the coral canopy and the surrounding water, which is critical for coral health. However, how these factors affect TEP release by coral colonies has yet to be evaluated. Using a recirculating flume, we assessed TEP release by branching Acropora coral colonies and associated bacterial growth in the water column under different unidirectional flows. Changes in TEP and bacterial concentrations after 24-h incubation were quantified for flow speeds of 0, 5, 10, and 30 cm/s. Particle image velocimetry (PIV) measurements provided an estimate of turbulent mixing efficiency above the coral canopy. TEP and bacterial concentrations in the water column increased after 24 h of incubation. The increase in TEP and bacterial concentrations were 6.2–9.3 times and 3.4–5.1 times higher in the absence of flows, respectively, than mean values under water flows. Although mixing efficiency increased linearly with mean flow speeds, TEP release and bacterial growth differed only marginally at flows ranging from 5–30 cm/s. Detailed flow measurements combined with evaluation of TEP release suggest that the complex geometry of corals facilitates efficient material exchange at a range of flow speeds, and highlight the importance of considering these factors when estimating coral reef biogeochemistry.

About a quarter of the world's population suffers from insomnia, and the number of the insomniacs is gradually increasing. However, the current drug therapy and non-drug therapy sleep-aid methods have certain limitations. In general, the sleep-aid effect of drug therapy is better than that of Non-drug therapy, but western medicine may lead to some side effects and drug abuse. Although the side effects of Chinese Herbal Medicine (CHM) are relatively small, making the herbal decoction is complex and time-consuming. Therefore, exploring a novel sleep-aid method is very significant. In this paper, a flexible and dissolving Traditional Chinese Medicine (TCM) microneedle patch is proposed for sleep-aid intervention. The TCM microneedle patch is a micrometer-scale intrusive object, and the herbal extracts are carried by the patch. The materials, design method, and fabrication process of the microneedle patch have been described in detail. Besides, the mechanical characteristics of the microneedle patch, sleep-aid effect evaluation method, and experimental scheme have been presented. Three microneedle tips with radii of 5 μm, 15 μm, and 22 μm are selected for simulation analysis. Abaqus simulation results indicate that the smaller the radius of the microneedle tip, the smaller the piercing force. Considering that the microneedle should easily penetrate the skin without buckling, that is, the piercing force should be larger than the buckling force, thus 15 μm, instead of 5 μm or 22 μm, is more suitable to be adopted as the radius of the microneedle tip. For the microneedle with the radius of 15 μm, the piercing force is 0.033 N, and the difference between the piercing force and buckling force is 0.036 N. Experimental results demonstrate that the fracture force of the microneedle is about 0.29 N, which is far larger than the piercing force and buckling force. The single-lead EEG signals of the frontal lobe are used to evaluate the sleep-aid effect of the TCM microneedle patch. After sleep-aid intervention on the Anmian and Yintang acupoints using the patches, for most subjects, the ratios of the low-frequency brain wave energies to the high-frequency brain wave energies are increased obviously, indicating that the proposed sleep-aid method is effective.

People spend approximately one-third of their lives in sleep, but more and more people are suffering from sleep disorders. Sleep posture is closely related to sleep quality, so related detection is very significant. In our previous work, a smart flexible sleep monitoring belt with MEMS triaxial accelerometer and pressure sensor has been developed to detect the vital signs, snore events and sleep stages. However, the method for sleep posture detection has not been studied. Therefore, to achieve high performance, low cost and comfortable experience, this paper proposes a smart detection method for sleep posture based on a flexible sleep monitoring belt and vital sign signals measured by a MEMS Inertial Measurement Unit (IMU). Statistical analysis and wavelet packet transform are applied for the feature extraction of the vital sign signals. Then the algorithm of recursive feature elimination with cross-validation is introduced to further extract the key features. Besides, machine learning models with 10-fold cross validation process, such as decision tree, random forest, support vector machine, extreme gradient boosting and adaptive boosting, were adopted to recognize the sleep posture. 15 subjects were recruited to participate the experiment. Experimental results demonstrate that the detection accuracy of the random forest algorithm is the highest among the five machine learning models, which reaches 96.02 %. Therefore, the proposed sleep posture detection method based on the flexible sleep monitoring belt is feasible and effective.

For grid-forming (GFM) controlled voltage-source converters (VSCs), there is a challenge in addressing their fault ride-through (FRT) capability under large grid disturbances. Specifically, the challenge lies in achieving rapid and robust synchronization with the faulted grid while effectively limiting the fault current. To address this, this article proposes a direct current-synchronization control (DCSC) scheme in the converter synchronous reference frame, which directly regulates the VSC current for synchronization. The validity of DCSC is substantiated by analyzing the relationship between the VSC current and phase angle, where power serves as an intermediate variable. The analytical solution for the steady-state stability boundary of the DCSC-based VSC-grid system under fault conditions is derived, which demonstrates the enhanced synchronization stability of DCSC compared to the conventional power-balance-based synchronization (PBBS) after large grid disturbances. The stability boundary of DCSC under fault conditions exhibits a voltage-magnitude-independent characteristic, resulting in a wider power angle boundary. Furthermore, this stability boundary can be translated to determine the stable operating range of the power reference ratio so that a consistently stable DCSC-based VSC-grid system can be assured under fault conditions. To increase the dynamic synchronization speed after faults, a control gain self-adaptability (CGSA) approach is introduced into the DCSC scheme. The experimental results validate the theoretical findings, affirming the effectiveness of the proposed control scheme.

In this article, a small-signal model of grid-forming (GFM) converters that takes into account the presence of ac shunt capacitors in the power grid is presented. It is revealed that the inclusion of shunt ac capacitors in GFM converters leads to the emergence of two new resonant peaks in the loop gain of the active power control (APC) loop, in addition to the fundamental-frequency resonant peak that was previously identified in literature. Further analysis based on the equivalent APC considering P/Q coupling has confirmed the same destabilization effect of ac shunt capacitors by introducing two extra resonant peaks. Based on the insight, it is suggested that the active damping control needs to be adapted to effectively dampen all three resonant peaks to ensure the stable operation of GFM converters. Finally, simulations and real-time simulations are carried out to corroborate the theoretical findings.

This paper derives closed-form solutions for grid-forming converters with power synchronization control (PSC) by subtly simplifying and factorizing the complex closed-loop models. The solutions can offer clear analytical insights into control-loop interactions, enabling guidelines for robust controller design. It is proved that 1) the proportional gains of PSC and alternating voltage control (AVC) can introduce negative resistance, which aggravates synchronous resonance (SR) of power control, 2) the integral gain of AVC is the cause of sub-synchronous resonance (SSR) in stiff-grid interconnections, albeit the proportional gain of AVC can help dampen the SSR, and 3) surprisingly, the current controller that dampens SR actually exacerbates SSR. Controller design guidelines are given based on analytical insights. The findings are verified by simulations and experimental results.

The influence of carrier mobility on the space charge transport behavior inside the oil-impregnated pressboard insulation of converter transformers cannot be neglected. However, at present, current knowledge is usually derived from empirical or theoretical values, lacks experimental studies, and often ignores the effects of temperature and field strength under actual operating conditions. In this paper, based on the variable-temperature surface potential decay (SPD) method, a carrier mobility measurement platform for oil-impregnated pressboard is established, and the carrier mobility values for different combinations of oil and oil-impregnated pressboard are obtained experimentally to analyze and reveal the influence mechanisms of temperature and field strength on the carrier mobility. The results indicate the following: (1) The positive and negative carrier mobilities of oil-impregnated pressboard are in the range of 10−12–10−13 m2·V−1·s−1, and the negative carrier mobility is always higher than the positive carrier mobility. (2) The carrier mobility is positively correlated with the changes of temperature and field strength, and when the temperature increases from 20 °C to 80 °C, the positive and negative carrier mobilities increase by 4.01 times and 4.72 times, respectively; when the field strength increases from 1 kV/mm to 7 kV/mm, the positive and negative carrier mobility increases by 2.53 and 2.72 times, respectively. (3) The carrier mobility of the pressboard with a higher oil absorption rate changes more significantly with temperature; when the field strength is 7 kV/mm and the temperature increases from 20 °C to 80 °C, the positive polarity carrier mobility increases from 3.96 × 10−13 m2·V−1·s−1 to 2.64 × 10−11 m2·V−1·s−1, an increase of 66.67 times, while the increase in the carrier mobility of the pressboard with a lower oil absorption rate is only 1.59 times. (4) The carrier mobility of the naphthenic transformer oil-impregnated pressboard is higher than that of the paraffin-based transformer oil-impregnated pressboard, and the carrier mobility of two kinds of naphthenic transformer oil-impregnated pressboard is 3.16 times and 2.47 times higher than that of the paraffin-based transformer oil-impregnated pressboard, respectively, under the conditions of 60 °C and 7 kV/mm. (5) Utilizing the Darcy model and microscopic scanning results of the pressboard morphology, it was revealed that permeability and fiber structure are key factors influencing the variation in carrier mobility. The research results of this paper can provide theoretical basis for the calibration and optimization of the oil-pressboard insulation structure of converter transformers.

Circuit noise is a critical factor that affects the performances of an MEMS gyroscope. Therefore, it is essential to analyze and suppress the noises in the key analog circuits, which are the main noise sources. This study presents an optimized front-end readout circuit and noise suppression methods. First, the noise analysis of the front-end readout circuit is carried out with theoretical derivation to clarify the main noise contributors. To suppress the output noise, an improved readout circuit based on the T-resistor networks is proposed, and the corresponding noise equation is derived in detail. In addition, the noise analysis of the critical circuits of the detection and control system, such as the inverting amplifiers, the first-order low-pass filters, and the first-order high-pass filters, is carried out, and the noise suppression strategy with the optimization of the resistances and is proposed. Taking the inverting amplifier as an example, the theoretical derivation is verified by measuring and comparing the output noises of different resistance schemes. In addition, the output noises of the gyroscope before and after circuit optimization are measured. Experimental results demonstrate that the output noise with the circuit optimization is reduced from 60 μV/Hz1/2 to 30 μV/Hz1/2 and the bias instability is reduced from 3.8 deg/h to 1.38 deg/h. In addition, the ARW is significantly improved from 0.035 deg/h1/2 to 0.018 deg/h1/2, which indicates that the proposed noise analysis and suppression methods are effective and feasible.

Infrared and visible image fusion integrates complementary information from different modalities into a single image, providing sufficient imaging information for scene interpretation and downstream target recognition tasks. However, existing fusion methods often focus only on highlighting salient targets or preserving scene details, failing to effectively combine entire features from different modalities during the fusion process, resulting in underutilized features and poor overall fusion effects. To address these challenges, a global and local four-branch feature extraction image fusion network (GLFuse) is proposed. On one hand, the Super Token Transformer (STT) block, which is capable of rapidly sampling and predicting super tokens, is utilized to capture global features in the scene. On the other hand, a Detail Extraction Block (DEB) is developed to extract local features in the scene. Additionally, two feature fusion modules, namely the Attention-based Feature Selection Fusion Module (ASFM) and the Dual Attention Fusion Module (DAFM), are designed to facilitate selective fusion of features from different modalities. Of more importance, the various perceptual information of feature maps learned from different modality images at the different layers of a network is investigated to design a perceptual loss function to better restore scene detail information and highlight salient targets by treating the perceptual information separately. Extensive experiments confirm that GLFuse exhibits excellent performance in both subjective and objective evaluations. It deserves note that GLFuse effectively improves downstream target detection performance on a unified benchmark.

The reliability of MEMS inertial devices applied in complex environments involves interdisciplinary fields, such as structural mechanics, material mechanics and multi-physics field coupling. Nowadays, MEMS inertial devices are widely used in the fields of automotive industry, consumer electronics, aerospace and missile guidance, and a variety of reliability issues induced by complex environments arise subsequently. Hence, reliability analysis and design of MEMS inertial devices are becoming increasingly significant. Since the reliability issues of MEMS inertial devices are mainly caused by complex mechanical and thermal environments with intricate failure mechanisms, there are fewer reviews of related research in this field. Therefore, this paper provides an extensive review of the research on the reliability of typical failure modes and mechanisms in MEMS inertial devices under high temperature, temperature cycling, vibration, shock, and multi-physical field coupling environments in the last five to six years. It is found that though multiple studies exist examining the reliability of MEMS inertial devices under single stress, there is a dearth of research conducted under composite stress and a lack of systematic investigation. Through analyzing and summarizing the current research progress in reliability design, it is concluded that multi-physical field coupling simulation, theoretical modeling, composite stress experiments, and special test standards are important directions for future reliability research on MEMS inertial devices.

This study investigates the reservoir physical properties, present-day stress, hydraulic fracturing, and production capacity of No. 3 coal in the Shizhuang south block, Qinshui Basin. It analyzes the control of in situ stress on permeability and hydraulic fracturing, as well as the influence of geo-engineering parameters on coalbed methane (CBM) production capacity. Presently, the direction of maximum horizontal stress is northeast–southwest, with local variations. The stress magnitude increases with burial depth, while the stress gradient decreases. The stress field of strike-slip faults is dominant and vertically continuous. The stress field of normal faults is mostly found at depths greater than 800 m, whereas the stress field of reverse faults is typically found at depths shallower than 700 m. Permeability, ranging from 0.003 to 1.08 mD, is controlled by in situ stress and coal texture, both of which vary significantly with tectonics. Hydraulic fracturing design should consider variations in stress conditions, pre-existing fractures, depth, structural trends, and coal texture, rather than employing generic schemes. At greater depths, higher pumping rates and treatment pressures are required to reduce fracture complexity and enhance proppant filling efficiency. The Shizhuang south block is divided into five zones based on in situ stress characteristics. Zones III and IV exhibit favorable geological conditions, including high porosity, permeability, and gas content. These zones also benefit from shorter gas breakthrough times, relatively higher gas breakthrough pressures, lower daily water production, and a higher ratio of critical desorption pressure to initial reservoir pressure. Tailored fracturing fluid and proppant programs are proposed for different zones to optimize subsequent CBM development.

SLAM (simultaneous localization and mapping) is essential for accurate positioning and reasonable path planning in outdoor mobile robots. LiDAR SLAM is currently the dominant method for creating outdoor environment maps. However, the mainstream LiDAR SLAM algorithms have a single point cloud feature extraction process at the front end, and most of the loop closure detection at the back end is based on RNN (radius nearest neighbor). This results in low mapping accuracy and poor real-time performance. To solve this problem, we integrated the functions of point cloud segmentation and Scan Context loop closure detection based on the advanced LiDAR-inertial SLAM algorithm (LIO-SAM). First, we employed range images to extract ground points from raw LiDAR data, followed by the BFS (breadth-first search) algorithm to cluster non-ground points and downsample outliers. Then, we calculated the curvature to extract planar points from ground points and corner points from clustered segmented non-ground points. Finally, we used the Scan Context method for loop closure detection to improve back-end mapping speed and reduce odometry drift. Experimental validation with the KITTI dataset verified the advantages of the proposed method, and combined with Walking, Park, and other datasets comprehensively verified that the proposed method had good accuracy and real-time performance.

The fractal dimension (FD) is an effective indicator to characterize various signals in engineering. However, the FD is nearly twice that of its maximum value when examining high-frequency-dominant signals, such as those in milling chatter. Previous studies in the literature have generally employed signal-pre-processing methods that require a significant amount of time to lower the FD range, thus enabling the distinguishment of different states while disabling online monitoring. A new quantitative method based on the FD within a fixed interval was constructed in this study to address this issue. First, the relationship between the fixed-interval fractal dimension (FFD) and the energy ratio (ER), named the fractal complexity curve (FC-Curve), was established, and the sensitivity region of the FFD was determined. Second, a high-frequency suppression filter (HSF) with a high calculation speed was proposed to suppress the signal’s ER so the FFD could be adjusted within its sensitivity region. Moreover, a fast energy ratio (FER) correlated with the FFD was proposed using the FC-Curve and HSF to quantitatively analyze dominant high-frequency signals. Finally, the proposed method was verified via its application in milling chatter identification. The FER method accomplished signal analysis more quickly than the traditional energy ratio difference and entropy methods, demonstrating its feasibility for online monitoring and chatter suppression in practical engineering applications.

Two-wheeled mobile robots with deformed wheels face low stability when climbing steps, and their success rate in overcoming steps is affected by the trajectory. To address these challenges, we propose an improved hybrid genetic and adaptive particle swarm optimization (HGAPSO) algorithm to optimize the deformed wheels’ trajectory for overcoming steps. HGAPSO optimizes the maximum and minimum values of the inertial weight and learning factors of the adaptive particle swarm algorithm utilizing the region-wide search capabilities of the genetic algorithm, which substantially improves the convergence speed and adaptability. Furthermore, the analysis of the motion of the deformed wheel overcoming the steps and the examination of the potential interference during the operation are used to construct a wheel’s center-of-mass route based on fifth-order Bézier curves. Comparative simulation experiments of the trajectories optimized using different optimization algorithms under the same working conditions are designed to demonstrate the efficacy of the proposed HGAPSO algorithm in optimizing the trajectory of the deformed wheel overcoming the step. Simulation experiments were conducted using the HGAPSO algorithm to optimize the trajectories of deformation wheels for overcoming steps of various sizes. These optimized trajectories were then compared to unoptimized ones. The results showed that the HGAPSO-optimized trajectories significantly improved the success rate and stability of the mobile robot in overcoming steps.

Lamination is the predominant and widely developed sedimentary structure in mudstones. Similar to organic pores in shale gas reservoirs, the inorganic pores in the laminae of shale oil reservoirs are equivalently important high-quality reservoir spaces and flow channels. The laminae characteristics are strongly heterogeneous, being controlled by both deposition and diagenesis. However, the origin of this diversity is poorly understood. A detailed examination of cores, thin sections, and scanning electron microscopy analyses were conducted on the lacustrine mudstone of the Qingshankou Formation in the Songliao Basin to study the influence of deposition and diagenesis on laminae characteristics and their relationship to reservoir quality. Three types of laminae are mainly developed, namely thick siliceous laminae, thin siliceous laminae, and thin siliceous and argillaceous mixed laminae. Deposition controls the type and distribution of laminae. The thin siliceous and argillaceous mixed laminae are controlled by climate-driven seasonal flux variations. The thick siliceous laminae and thin siliceous laminae are controlled by bottom current or gravity-driven transport processes due to increased terrestrial input. The thin siliceous laminae have the optimum reservoir properties, followed by the thin siliceous and argillaceous mixed laminae, while the thick siliceous laminae have the worst properties. Diagenesis controls the pore evolution of the laminae. Different laminae have different paths of diagenesis. The thin siliceous laminae are mainly cemented by chlorite, preserving some primary porosity. The clay mineral content of the thin siliceous and argillaceous mixed laminae is high, and the primary pores are mainly destroyed by the strong deformation of the clay minerals during compaction. The thick siliceous laminae are intensely cemented by calcite, losing most of the porosity. The present study enhances the understanding of reservoir characteristics in laminae and provides a reference for shale oil exploration.

When there are dynamic obstacles in the environment, it is difficult for traditional path-generation algorithms to achieve desired obstacle-avoidance results. To solve this problem, we propose a robot navigation control method based on SAC (Soft Actor-Critic) Deep Reinforcement Learning. Firstly, we use a fast path-generation algorithm to control the robot to generate expert trajectories when the robot encounters danger as well as when it approaches a target, and we combine SAC reinforcement learning with imitation learning based on expert trajectories to improve the safety of training. Then, for the hybrid data consisting of agent data and expert data, we use an improved prioritized experience replay method to improve the learning efficiency of the policies. Finally, we introduce RNN (Recurrent Neural Network) units into the network structure of the SAC Deep Reinforcement-Learning navigation policy to improve the agent’s transfer inference ability in a new environment and obstacle-avoidance ability in dynamic environments. Through simulation and practical experiments, it is fully verified that our method has a higher training efficiency and navigation success rate compared to state-of-the-art reinforcement-learning algorithms, which further enhances the obstacle-avoidance capability of the robot system.

In this study, changes in abiotic environmental factors were analyzed based on measured data from Dawangtan Reservoir in Nanning City during 2021–2022. The Carlson Integrated Trophic State Index method was applied to evaluate water quality and eutrophication in the reservoir, considering both exogenous inputs and internal water quality conditions. Additionally, by investigating water quality and biological factors (zooplankton and fish) in the reservoir, this study identified the main drivers influencing phytoplankton outbreaks in Dawangtan Reservoir through redundancy analysis (RDA) and Pearson correlation analysis. The results showed that the combined trophic state index of the reservoir varied between 29.2 and 56.5 throughout the year, with each water quality indicator performing worse during the summer months when temperatures were higher. There was a positive correlation between zooplankton biomass and phytoplankton biomass, and the increase in the proportion of phytophagous fish contributed to the reduction in phytoplankton. The redundancy analysis revealed that the distribution of phytoplankton species was significantly correlated with total phosphorus (TP), pH, dissolved oxygen (DO), and chlorophyll a (Chl-a), with different phytoplankton species responding variably to these environmental factors. Finally, a multiple stepwise regression analysis was used to construct the optimal response equation between Chl-a concentration and environmental factors. The results indicated that pH, Secchi disk (SD), DO, and biological oxygen demand (BOD) were the main factors affecting Chl-a concentration. Therefore, the outcomes of abiotic environmental factors and lake biological resources should be considered in the restoration of eutrophic lakes to achieve the desired restoration effect.

Objective: Neck pain has emerged as a significant public health concern. This study is to unveil the present state of neck pain research, thereby furnishing invaluable insights for prospective research endeavours and clinical applications. Methods: The study was initiated by searching the Web of Science Core Collection database, focusing on ''neck pain''. From the amassed results, the top 100 most cited references were imported into CiteSpace and VOSviewer, enabling a rigorous bibliometric analysis. To ensure precision, synonymous terms conveying similar meanings were harmonized. The bibliometric study encompassed countries, research institutions, authors, journals, and keyword analysis. Results: The investigation centered on a curated compilation of 100 articles, disseminated across a diverse array of 36 scholarly journals. These seminal articles originated from 24 distinct countries, reflecting contributions from a wide spectrum of 188 research institutions. Impressively, a collaborative effort involving 385 authors emerged. Noteworthy core research countries included the United States and Australia, with the University of Queensland and the University of Toronto asserting notable influence. Prolific authors such as J. David Cassidy and Pierre Cote garnered attention. Present research endeavours pivot around the incidence of neck pain, the identification of risk factors, the efficacy evaluation of treatment modalities, and a pronounced focus on high-quality randomized controlled trials and systematic reviews. Conclusion: The study shines a light on key research countries, influential institutions, prominent authors, and prevalent trends, effectively contributing to comprehending the knowledge landscape and research dynamics in the field of neck pain.

Impact is the most important factor affecting the reliability of Micro-Electro-Mechanical System (MEMS) gyroscopes, therefore corresponding reliability design is very essential. This paper proposes a shock-protected structure (SPS) capable of withstanding a full temperature range from −40 °C to 80 °C to enhance the shock resistance of MEMS gyroscopes. Firstly, the shock transfer functions of the gyroscope and the SPS are derived using Single Degree-of-Freedom and Two Degree-of-Freedom models. The U-folded beam stiffness and maximum positive stress are deduced to evaluate the shock resistance of the silicon beam. Subsequently, the frequency responses of acceleration of the gyroscope and the SPS are simulated and analyzed in Matlab utilizing the theoretical models. Simulation results demonstrate that when the first-order natural frequency of the SPS is approximately one-fourth of the gyroscope’s resonant frequency, the impact protection effect is best, and the SPS does not affect the original performance of the gyroscope. The acceleration peak of the MEMS gyroscope is reduced by approximately 23.5 dB when equipped with the SPS in comparison to its counterpart without the SPS. The anti-shock capability of the gyroscope with the SPS is enhanced by approximately 13 times over the full-temperature range. After the shock tests under the worst case, the gyroscope without the SPS experiences a beam fracture failure, while the performance of the gyroscope with the SPS remains normal, validating the effectiveness of the SPS in improving the shock reliability of MEMS gyroscopes.

The conventional approach to phase reconstruction in Reflective Ghost Imaging (RGI) typically involves the introduction of three reference screens into the reference path, deeming the Fourier transform step indispensable. However, this method introduces complexity to the system and raises concerns regarding potential errors in phase retrieval. In response to these challenges, we advocate for adopting the Five-Step Phase-Shifting (FSPS) method in the RGI system. This method presents two key advantages over traditional approaches: (1) It streamlines the phase reconstruction process by eliminating the requirement for a Fourier inverse transform. (2) It avoids the need to insert objects into the reference optical path, simplifying the computation of reference optical path intensity and enabling seamless application to Computational Ghost Imaging (CGI), overcoming the constraints of Dual-Arm Ghost Imaging (DAGI). We substantiate the theoretical proposition through numerical simulations involving two intricate objects. Furthermore, our discussion delves into exploring the influence of varying reflective angles on the phase reconstruction performance.

Background: Premenstrual dysphoric disorder (PMDD) represents a significant psychiatric condition affecting women of reproductive age. It is characterized by cyclical emotional and physical symptoms that considerably impair psychosocial functioning. This study aims to investigate the prevalence of PMDD among adult working women and identify associated etiological factors. Methods: From January 2022 to March 2022, a crosssectional study utilizing cluster sampling methodology was conducted to investigate the prevalence of PMDD among adult working women in six communities in Hangzhou (China). A total of 1710 participants were selected for research through a questionnaire-based survey. To elucidate the factors associated with PMDD, logistic regression analysis was employed. Results: Among 1710 working women, 52 had PMDD, representing an incidence of 3.04%. Age (odds ratio (OR) = 3.196, p = 0.002), age at menarche (OR = 0.362, p = 0.011), income (OR = 0.449, p = 0.043), menstrual cycle (OR = 2.352, p = 0.022), menstrual symptoms (OR = 0.317, p = 0.003), physical activity (OR = 2.234, p = 0.028), and caffeine intake (OR = 2.318, p = 0.022) were independent influencing factors of PMDD in adult working women. Conclusions: The study highlights that PMDD, which has a prevalence of 3.04% in the surveyed population, is a notable concern among adult working women. Key factors, such as age, age at menarche, income level, menstrual cycle characteristics, menstrual symptom presence, physical activity, and caffeine intake, significantly contribute to the likelihood of developing PMDD. These findings underscore the importance of recognizing and monitoring the above risk factors by clinicians to identify and manage PMDD in working women. [ABSTRACT FROM AUTHOR]

Abstract Resistance to gemcitabine in pancreatic ductal adenocarcinoma (PDAC) leads to ineffective chemotherapy and, consequently, delayed treatment, thereby contributing to poor prognosis. Glycolysis is an important intrinsic reason for gemcitabine resistance as it competitively inhibits gemcitabine activity by promoting deoxycytidine triphosphate accumulation in PDAC. However, biomarkers are lacking to determine which patients can benefit significantly from glycolysis inhibition under the treatment of gemcitabine activity, and a comprehensive understanding of the molecular mechanisms that promote glycolysis in PDAC will contribute to the development of a strategy to sensitize gemcitabine chemotherapy. In this study, we aimed to identify a biomarker that can robustly indicate the intrinsic resistance of PDAC to gemcitabine and guide chemotherapy sensitization strategies. After establishing gemcitabine-resistant cell lines in our laboratory and collecting pancreatic cancer and adjacent normal tissues from gemcitabine-treated patients, we observed that circRNA hsa_circ_0008383 (namely cNEK6) was highly expressed in the peripheral blood and tumor tissues of patients and xenografts with gemcitabine-resistant PDAC. cNEK6 enhanced resistance to gemcitabine by promoting glycolysis in PDAC. Specifically, cNEK6 prevented K48 ubiquitination of small ribonucleoprotein peptide A from the BTRC, a ubiquitin E3 ligase; thus, the accumulated SNRPA stopped PP2Ac translation by binding to its G-quadruplexes in 5′ UTR of mRNA. mTORC1 pathway was aberrantly phosphorylated and activated owing to the absence of PP2Ac. The expression level of cNEK6 in the peripheral blood and tumor tissues correlated significantly and positively with the activation of the mTORC1 pathway and degree of glycolysis. Hence, the therapeutic effect of gemcitabine is limited in patients with high cNEK6 levels, and in combination with the mTORC1 inhibitor, rapamycin, can enhance sensitivity to gemcitabine chemotherapy.

Choerospondias axillaries (CA) is an important fast-growing afforestation tree species in southern China, and its fruit has medicinal and edible value. High performance liquid chromatography was used to determine the composition and content of sugar and acid in CA fruits from different provenances, and cluster analysis was conducted on different provenances. The results showed that the total sugar content of CA fruit ranged from 49.31 to 139.41 mg/g, with sucrose accounting for the highest proportion of total sugar, followed by glucose, and fructose was the lowest. The total acid content of CA fruit ranged from 47.97 to 82.81 mg/g, with citric acid accounting for 67.09% of the total acid, followed by ascorbic acid, quinic acid, tartaric acid, and malic acid. Cluster analysis was conducted on 20 CA fruits, which were divided into 4 categories. It was recommended to develop N19 fruit had the highest content of sucrose and glucose, and the highest sweetness value, sugar-acid ratio and sweet-acid ratio. It can be suggested to be developed as a high-sugar fresh food source. N02 fruit with high sugar and high acid content can be used as a raw material for fruit cake processing. This result provides an important reference for the quality evaluation and rational development and utilization of CA.

Abstract Background Lung adenocarcinoma is a high-mortality rate cancer. Within this category, Lung mucinous adenocarcinoma (LMAC) is a rare and distinct subtype of lung adenocarcinoma necessitating further investigation. The study was launched to compare the difference of survival features between LMAC and lung non-mucinous adenocarcinoma (LNMAC) and to investigate the significance and demand for developing a new staging system tailored to LMAC. Methods This retrospective study assessed the suitableness of the current staging system for LMAC. It compared the overall survival (OS) between LMAC and LNMAC from 2004 to 2020 (LNMAC: 160,387; LMAC: 6,341) and instituted a novel classification framework for LMAC based on US population. Verification group consisting of patients from two Chinese medical centers from 2010 to 2018 (n = 392) was set to ascertain the applicability of this novel system. The primary endpoint was OS. To minimize the bias, propensity score match (PSM) was employed. Survival analysis and Log-rank test were executed to explore the survival features of LMAC. Results The results indicated that the existed staging system was not suitable for LMAC. Patients diagnosed with LMAC exhibited a superior OS compared to those with LNMAC in stage IA2 (P

Abstract The COVID-19 pandemic has flooded open databases with population-level data. However, individual-level structured data, such as the course of disease and contact tracing information, is almost non-existent in open databases. Publish a structured and cleaned COVID-19 dataset with the course of disease and contact tracing information for easy benchmarking of COVID-19 models. We gathered data from Taiwanese open databases and daily news reports. The outcome is a structured quantitative dataset encompassing the course of the disease of Taiwanese individuals, alongside their contact tracing information. Our dataset comprises 579 confirmed cases covering the period from January 21, to November 9, 2020, when the original SARS-CoV-2 virus was most prevalent in Taiwan. The data include features such as travel history, age, gender, symptoms, contact types between cases, date of symptoms onset, confirmed, critically ill, recovered, and dead. We also include the daily summary data at population-level from January 21, 2020, to May 23, 2022. Our data can help enhance epidemiological modelling.

Abstract Background Vascular calcification (VC) is a complication in diabetes mellitus (DM) patients. Osteogenic phenotype switching of vascular smooth muscle cells (VSMCs) plays a critical role in diabetes-related VC. Mitophagy can inhibit phenotype switching in VSMCs. This study aimed to investigate the role of the glucagon-like peptide-1 receptor (GLP-1R) agonist exendin 4 (EX4) in mitophagy-induced phenotype switching. Materials and methods The status of VC in T2DM mice was monitored using Von Kossa and Alizarin Red S (ARS) staining in mouse aortic tissue. Human aortic smooth muscle cells were cultured in high glucose (HG) and β-glycerophosphate (β-GP) conditioned medium. Accumulation of LC3B and p62 was detected in the mitochondrial fraction. The effect of EX4 in vitro and in vivo was investigated by knocking down AMPKα1. Results In diabetic VC mice, EX4 decreased the percentage of von Kossa/ARS positive area. EX4 inhibited osteogenic differentiation of HG/β-GP-induced VSMCs. In HG/β-GP-induced VSMCs, the number of mitophagosomes was increased, whereas the addition of EX4 restored mitochondrial function, increased the number of mitophagosome-lysosome fusions, and reduced p62 in mitochondrial frictions. EX4 increased the phosphorylation of AMPKα (Thr172) and ULK1 (Ser555) in HG/β-GP-induced VSMCs. After knockdown of AMPKα1, ULK1 could not be activated by EX4. The accumulation of LC3B and p62 could not be reduced after AMPKα1 knockdown. Knockdown of AMPKα1 negated the therapeutic effects of EX4 on VC of diabetic mice. Conclusion EX4 could promote mitophagy by activating the AMPK signaling pathway, attenuate insufficient mitophagy, and thus inhibit the osteogenic phenotype switching of VSMCs.

Abstract Accurate forecasting of community outbreaks is crucial for governments to allocate healthcare resources correctly and implement suitable non-pharmaceutical interventions. Additionally, companies must address critical questions about stock and staff management. Society’s key concern is when businesses and organizations can resume normal operations. Between December 31st 2019 and 2021, Taiwan experienced three separate COVID-19 community outbreaks with significant time intervals in between, suggesting that each outbreak eventually came to an end. We identified the ratio of the 7-day average of local & unknown confirmed to suspected cases as the key control variable and forecasted the end of the third outbreak by the exponential model. We forecasted the end of the third outbreak on Aug. 16th with threshold ratios of $$1.2\cdot 10^{-4}$$ 1.2 · 10 - 4 . The real observations crossed the threshold on Aug. 27th, eleven days later than forecasted, with the last case of the third outbreak confirmed and quarantined on Sept. 20th. This demonstrated the accuracy of the proposed forecasting method in predicting the end of a local outbreak. Furthermore, we highlight that the ratio reflects the effectiveness of contact tracing. Effective contact tracing together with testing and isolation of infected individuals is crucial for ending community outbreaks.

Abstract Background Dynamical compensation (DC) provides robustness to parameter fluctuations. As an example, DC enables control of the functional mass of endocrine or neuronal tissue essential for controlling blood glucose by insulin through a nonlinear feedback loop. Researchers have shown that DC is related to the structural unidentifiability and the $$\mathbb {P}$$ P -invariance property. The $$\mathbb {P}$$ P -invariance property is a sufficient and necessary condition for the DC property. DC has been seen in systems with at least three dimensions. In this article, we discuss DC and $$\mathbb {P}$$ P -invariance from an adaptive control perspective. An adaptive controller automatically adjusts its parameters to optimise performance, maintain stability, and deal with uncertainties in a system. Results We initiate our analysis by introducing a simplified two-dimensional dynamical model with DC, fostering experimentation and understanding of the system’s behavior. We explore the system’s behavior with time-varying input and disturbance signals, with a focus on illustrating the system’s $$\mathbb {P}$$ P -invariance properties in phase portraits and step-like response graphs. Conclusions We show that DC can be seen as a case of ideal adaptive control since the system is invariant to the compensated parameter.

Abstract Classical and quantum space-to-ground communications necessitate highly sensitive receivers capable of extracting information from modulated photons to extend the communication distance from near-earth orbits to deep space explorations. To achieve gigabit data rates while mitigating strong background noise photons and beam drift in a highly attenuated free-space channel, a comprehensive design of a multi-functional detector is indispensable. In this study, we present an innovative compact multi-pixel superconducting nanowire single-photon detector array that integrates near-unity detection efficiency (91.6%), high photon counting rate (1.61 Gcps), large dynamic range for resolving different photon numbers (1–24), and four-quadrant position sensing function all within one device. Furthermore, we have constructed a communication testbed to validate the advantages offered by such an architecture. Through 8-PPM (pulse position modulation) format communication experiments, we have achieved an impressive maximum data rate of 1.5 Gbps, demonstrating sensitivities surpassing previous benchmarks at respective speeds. By incorporating photon number information into error correction codes, the receiver can tolerate maximum background noise levels equivalent to 0.8 photons/slot at a data rate of 120 Mbps—showcasing a great potential for daylight operation scenarios. Additionally, preliminary beam tracking tests were conducted through open-loop scanning techniques, which revealed clear quantitative dependence indicating sensitivity variations based on beam location. Based on the device characterizations and communication results, we anticipate that this device architecture, along with its corresponding signal processing and coding techniques, will be applicable in future space-to-ground communication tasks.

In directed energy deposition (DED), accurately controlling and predicting melt pool characteristics is essential for ensuring desired material qualities and geometric accuracies. This paper introduces a robust surrogate model based on recurrent neural network (RNN) architectures—Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Gated Recurrent Unit (GRU). Leveraging a time series dataset from multi-physics simulations and a three-factor, three-level experimental design, the model accurately predicts melt pool peak temperatures, lengths, widths, and depths under varying conditions. RNN algorithms, particularly Bi-LSTM, demonstrate high predictive accuracy, with an R-square of 0.983 for melt pool peak temperatures. For melt pool geometry, the GRU-based model excels, achieving R-square values above 0.88 and reducing computation time by at least 29%, showcasing its accuracy and efficiency. The RNN-based surrogate model built in this research enhances understanding of melt pool dynamics and supports precise DED system setups.

The ongoing COVID-19 pandemic, caused by SARS-CoV-2, continues to pose significant global health challenges. The results demonstrated that GB-2 at 200 μg/mL effectively increased the population of 293T-ACE2 cells with low RBD binding for both SARS-CoV-2 Omicron EG.5.1 and HV.1 variants by dual-color flow cytometry, indicating its ability to inhibit virus attachment. Further investigation revealed that (+)-catechin at 25 and 50 μg/mL did not significantly alter the ACE2–RBD interaction for the EG.5.1 variant. In contrast, theaflavin showed inhibitory effects at both 25 and 50 μg/mL for EG.5.1, while only the higher concentration was effective for HV.1. Notably, theaflavin 3-gallate exhibited a potent inhibition of ACE2–RBD binding for both variants at both concentrations tested. Molecular docking studies provided insight into the binding mechanisms of theaflavin and theaflavin 3-gallate with the RBD of EG.5.1 and HV.1 variants. Both compounds showed favorable docking scores, with theaflavin 3-gallate demonstrating slightly lower scores (−8 kcal/mol) compared to theaflavin (−7 kcal/mol) for both variants. These results suggest stable interactions between the compounds and key residues in the RBD, potentially explaining their inhibitory effects on virus attachment. In conclusion, GB-2, theaflavin, and theaflavin 3-gallate demonstrate significant potential as inhibitors of the ACE2–RBD interaction in Omicron variants, highlighting their therapeutic promise against COVID-19. However, these findings are primarily based on computational and in vitro studies, necessitating further in vivo research and clinical trials to confirm their efficacy and safety in humans.