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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.

Background Diabetic kidney disease (DKD), a prevalent complication of diabetes mellitus, is often associated with acute kidney injury (AKI). Thus, the development of preventive and therapeutic strategies is crucial for delaying the progression of AKI and DKD.Methods The GSE183276 dataset, comprising the data of 20 healthy controls and 12 patients with AKI, was downloaded from the Gene Expression Omnibus (GEO) database to analyze the AKI group. For analyzing the DKD group, the GSE131822 dataset, comprising the data of 3 healthy controls and 3 patients with DKD, was downloaded from the GEO database. The common differentially expressed genes (DEGs) in renal tubular epithelial cells (TECs) were subjected to enrichment analyses. Next, a protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes database to analyze gene-related regulatory networks. Finally, the AKI animal models and the DKD and AKI cell models were established, and the reliability of the identified genes was validated using quantitative real-time polymerase chain reaction analysis.Results Functional analysis was performed with 40 common DEGs in TECs. Eight hub genes were identified using the PPI and gene-related networks. Finally, validation experiments with the in vivo animal model and the in vitro cellular model revealed the four common DEGs. Four DEGs that share molecular mechanisms in the pathogenesis of DKD and AKI were identified. In particular, the expression of Integrin Subunit Beta 6(ITGB6), a hub and commonly upregulated gene, was upregulated in the in vitro models.Conclusion ITGB6 may serve as a biomarker for early AKI diagnosis in patients with DKD and as a target for early intervention therapies.

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.

Shale laminae influence shale reservoir quality and fracturing, whereas previous studies are simply based on geological materials. Taking full advantage of geophysical logging data could provide novel insights for shale laminae evaluation in drilled boreholes. Methods Cored boreholes in the Wufeng-Longmaxi formations in the southern Sichuan Basin are utilized in this study. Shale cores, CT scanning based on full-diameter cores, large-sized thin sections, X-ray diffraction, and TOC content are first integrated to clarify shale laminae fabrics. Elemental scanning, microresistivity electrical imaging, multipole array acoustic, conventional and nuclear magnetic resonance logging techniques are interpreted to characterize shale laminae by geological calibration, and the methodology of logging evaluation on shale laminae has been set out. Results It is concluded that the target formation has developed four types of bed, includingthe silicic bed (lamina poorly developed), silicic lamina, calcareous lamina, and argillaceous lamina. Elemental scanning is implemented to determine laminae minerals and TOC content. Electrical imaging and the anisotropy index derived from multipole array acoustic and conventional logs are used to evaluate lamina density or development degree. Besides, electrical imaging is able to reflect the lamina thickness. Nuclear magnetic resonance is performed to analyze the variation in lamina pore structure. Conclusion Although logging resolution and response complexity can significantly affect the accuracy of logging interpretation of shale laminae, logging techniques rooted in petrophysical properties are valuable supplements for the evaluation of shale laminae and lamina associations.

Abstract GBA1 variants are important risk factors for Parkinson’s disease (PD). Most studies assessing GBA1-related PD risk have been performed in European-derived populations. Although the coding region of the GBA1 gene in the Chinese population has been analyzed, the sample sizes were not adequate. In this study, we aimed to investigate GBA1 variants in a large Chinese cohort of patients with PD and healthy control and explore the associated clinical characteristics. GBA1 variants in 4034 patients and 2931 control participants were investigated using whole-exome and whole-genome sequencing. The clinical features of patients were evaluated using several scales. Regression analysis, chi-square, and Fisher exact tests were used to analyze GBA1 variants and the clinical symptoms of different groups. We identified 104 variants, including 8 novel variants, expanding the spectrum of GBA1 variants. The frequency of GBA1 variants in patients with PD was 7.46%, higher than that in the control (1.81%) (P

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.

Abstract Introduction Refractory cough, a chronic cough with an unclear diagnosis or poor treatment response. The symptoms are often stubborn and persistent, causing serious complications and lowering the patient's quality of life. Cough hypersensitivity syndrome (CHS) is proposed as a potential cause, and reducing sensory nerve hyperresponsiveness is suggested as an effective treatment. However, current drugs have low efficacy and benefit rates and numerous side effects. This trail proposes using duloxetine, a selective 5-HT and norepinephrine reuptake inhibitor, as a potential treatment for refractory cough, which has shown promise in treating pain and depression. Duloxetine may inhibit pain conduction and oxidative stress in peripheral nerves by inhibiting the activity of TRPV1 channels, which play an important role in the peripheral afferent pathway of refractory cough. Meanwhile, the antidepressant effects of duloxetine may also play a role in the treatment of refractory cough. Methods and analysis This is a single-center, prospective, randomized, double-blind, and controlled trial. A total of 98 individuals will be randomized in a 1:1 ratio to duloxetine group and placebo control group (starting with 20 mg QD, increasing 20 mg daily until 20 mg TID). After a screening period, the second stage runs from baseline to the 42nd (last) day of treatment, with follow-up visits on the 3rd, 7th, 14th, 21st, 28th, 35th, 42nd and 49th days. The main end-stage observation indicators include objective cough frequency, cough visual analog scale (VAS), cough symptom score, Leicester Cough Questionnaire (LCQ), and cough evaluation test (CET); the secondary end-stage observation indicators include capsaicin cough sensitivity, Patient Health Questionnaire-9 (PHQ-9), Major Depression Inventory (MDI), the Generalized Anxiety Disorder-7 scale (GAD-7), Life Events Scale (LES-32), induced sputum supernatant. The safety measures will be AEs/SAEs, vital signs, liver and kidney function, fecal occult blood test. Discussion This study is the first randomized, double-blind, and controlled clinical trial investigating the use of duloxetine in the treatment of refractory coughs. The study aims to provide a high-quality basis for evaluating the efficacy and safety of duloxetine for this condition. Trial registration Our study was registered in the Chinese Clinical Trials Register ( www.chictr.org.cn/ ) (ChiCTR2000037429) in 28/08/2020.

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.

Abstract Considerable evidence suggests that insulin resistance is closely linked to Parkinson's disease (PD), leading to agents aiming at treating diabetes can be regarded as new neuroprotective strategies in PD, notably glucagon‐like peptide‐1 (GLP‐1). However, the extremely short half‐life of GLP‐1 due to degradation by the ubiquitous proteolytic enzyme limits its clinical application. In this study, we engineered the recombinant integrant probiotic strain Escherichia coli Nissle 1917 (EcN) to create a strain EcN‐GLP‐1 that effectively delivers the heterologous GLP‐1 molecule. Subsequently, we assessed its neuroprotective effects on 1‐methyl‐4‐phenyl‐1, 2, 3, 6‐tetrahydropyridine (MPTP)‐induced PD mice. We demonstrated that EcN‐GLP‐1 treatment could improve motor deficits, increase tyrosine hydroxylase‐positive neurons, suppress microglia and astrocyte activation, reduce brain and colon inflammation, and ameliorate colonic barrier function damaged by MPTP induction. Meanwhile, we confirmed that the oral administration of EcN‐GLP‐1 could restore the disturbance of gut microbiota in the MPTP‐induced PD mice, by reducing the relative abundances of Akkermansia and Oscillospira, and increasing the level of Prevotella in the gut. These results support further development of an engineered probiotic platform in which production of GLP‐1 for gut‐brain disorders, such as PD.

Abstract Background Lung cancer screening may provide a “teachable moment” for the smoking cessation and relapse prevention. However, the impact of lung cancer screening on smoking initiation in non‐smokers has not been reported. Methods A baseline smoking behavior survey was conducted in 2000 participants who were screened by low‐dose computed tomography (LDCT) from 2014 to 2018. All participants were re‐surveyed on their smoking behavior in 2019. Of these, 312 participants were excluded, leaving 1688 participants in the final analysis. The smoking initiation rate in baseline non‐smokers, the relapse rate in baseline former smokers, and the abstinence rate in baseline current smokers were calculated, respectively. The associations between screening results, demographic characteristics, and smoking behavior change were analyzed using multivariable logistic regression. Results From 2014 to 2019, smoking prevalence significantly decreased from 52.6% to 49.1%. The prevalence of smoking initiation, relapse, and abstinence in baseline non‐smokers, former, and current smokers was 16.8%, 22.9%, and 23.7%, respectively. The risk of smoking initiation in baseline non‐smokers was significantly higher in those with negative screening result (adjusted OR = 2.97, 95% CI: 1.27–6.94). Compared to smokers who only received baseline screening, the chance of smoking abstinence in baseline current smokers was reduced by over 80% in those who attended 5 rounds of screening (adjusted OR = 0.15, 95% CI:0.08–0.27). No significant associations were found between smoking relapse and prior screening frequency, with at least one positive screening result. Age, gender, occupational exposure, income, and smoking pack years were also associated with smoking behavior changes. Conclusions The overall decreased smoking prevalence indicated an overwhelming effect of “teachable moment” on “license to smoke.” A tailored smoking cessation strategy should be integrated into lung cancer screening.

Abstract Background Inflammatory response is an essential part of secondary injury after spinal cord injury (SCI). During this period, the injury may be exacerbated through the release of a large number of inflammatory factors and the polarization of infiltrating macrophages and microglia towards M1. Ang-(1–7), mainly generated by Ang II via angiotensin-converting enzyme 2 (ACE2), can specifically bind to the G protein-coupled receptor Mas (MasR) and plays an important role in regulating inflammation and alleviating oxidative stress. Methods We aimed to investigate whether activating the Ang-(1–7)/MasR axis in rats after SCI can regulate local neuroinflammation to achieve functional recovery and obtain its potential mechanism. MasR expression of bone marrow-derived macrophages was determined by Western blot. Immunofluorescence, Western blot, Flow cytometry, and RT-qPCR were applied to evaluate the polarization of Ang-(1–7) on macrophages and the regulation of inflammatory cytokines. Previous evaluation of the spinal cord and bladder after SCI was conducted by hematoxylin–eosin staining, Basso, Beattie, and Bresnahan (BBB) score, inclined plate test, electrophysiology, and catwalk were used to evaluate the functional recovery of rats. Results MasR expression increased in macrophages under inflammatory conditions and further elevated after Ang-(1–7) treatment. Both in vivo and in vitro results confirmed that Ang-(1–7) could regulate the expression of inflammatory cytokines by down-regulating proinflammatory cytokines and up-regulating anti-inflammatory cytokines, and bias the polarization direction of microglia/macrophages to M2 phenotypic. After SCI, Ang-(1–7) administration in situ led to better histological and functional recovery in rats, and this recovery at least partly involved the TLR4/NF-κB signaling pathway. Conclusion As shown in our data, activating Ang-(1–7)/MasR axis can effectively improve the inflammatory microenvironment after spinal cord injury, promote the polarization of microglia/macrophages towards the M2 phenotype, and finally support the recovery of motor function. Therefore, we suggest using Ang-(1–7) as a feasible treatment strategy for spinal cord injury to minimize the negative consequences of the inflammatory microenvironment after spinal cord injury.

When a renewable energy station (RES) connects to the rectifier station (RS) of a modular multilevel converter-based high-voltage direct current (MMC-HVDC) system, the voltage at the point of common coupling (PCC) is determined by RS control methods. For example, RS control may become saturated under fault, and causes the RS to change from an equivalent voltage source to an equivalent current source, making fault analysis more complicated. In addition, the grid code of the fault ride-through (FRT) requires the RES to output current according to its terminal voltage. This changes the fault point voltage and leads to RES voltage regulation and current redistribution, resulting in fault response interactions. To address these issues, this study describes how an MMC-integrated system has five operation modes and three common characteristics under the duration of the fault. The study also reveals several instances of RS performance degradation such as AC voltage loop saturation, and shows that RS power reversal can be significantly improved. An enhanced AC FRT control method is proposed to achieve controllable PCC voltage and continuous power transmission by actively reducing the PCC voltage amplitude. The robustness of the method is theoretically proven under parameter variation and operation mode switching. Finally, the feasibility of the proposed method is verified through MAT-LAB/Simulink results.

In order to tackle the robot trajectory planning problem with the short running time as the optimization goal, a time-optimal trajectory planning algorithm was presented based on improved simplified particle swarm optimization (ISPSO). The robot’s trajectory was constructed by 3-5-3 polynomial interpolation in the joint space of the robot. Under the condition of satisfying the velocity constraint, the objective function was constructed by the sum of the time intervals between each node. ISPSO was used to optimize the objective function. The algorithm was improved by optimizing the inertia weight updating method and introducing a golden sine segmentation algorithm as an optimization operator. Compared with other particle swarm optimization algorithms, ISPSO had higher search velocity and accuracy. The effectiveness of the proposed algorithm was demonstrated through simulations using the PUMA 560 industrial robot, which resulted in a 19% reduction in time compared to the simplified particle swarm algorithm. The simulation results show that ISPSO achieved time optimization under the condition of velocity constraint, which proved its superiority in trajectory planning.

Multi-terminal HVDC projects are increasingly developed in recent years to enhance the flexibility of energy transmission. Differing from the point-to-point HVDC systems, it is more challenging to design the multi-terminal HVDC system and ensure stable interoperability among converter systems, especially when the converters are manufactured from different vendors. Although impedance-based stability analysis allows for analyzing such systems based on black-box models, it is still difficult to utilize those black-box models to identify the root cause of potential instability. To tackle this challenge, this paper proposes a multi-level sensitivity analysis approach using frequency-domain sensitivity functions based on the impedance-based stability criterion. The proposed method differs from the classical sensitivity analysis based on state-space or transfer-function models, as it is purely based on black-box impedance models. Case studies on a four-terminal HVDC system are carried out for stability and sensitivity analysis based on the impedance measurement in PSCAD, through which the most sensitive HVDC station can be identified. The proposed theory and the analyzed results are finally validated by electromagnetic transient simulations.

Abstract Good interfacial coupling between each constituent of van der Waals Heterostructures (vdWHs) is the prerequisite for the distinguished performance of related devices. Since vdWHs-based devices commonly consist of three or more constituents, an effective evaluation of interfacial coupling quality in multiple heterointerfaces is critical during the device fabrication process. Here, in ternary vdWHs composed of hBN, graphene (Gr) and transition metal dichalcogenide (TMD) flakes, which are essential building blocks for low-dimensional vdWHs-based electronic and optoelectronic devices, we realized probe and quantification of the interfacial coupling by low-frequency Raman spectroscopy under resonant excitation through the C exciton energy in TMD constituents. Based on the frequencies of emerging interlayer vibration modes in hBN/TMD/Gr ternary vdWHs, the interfacial coupling force constants of hBN/TMD and TMD/Gr interfaces are estimated as parameters to quantitatively evaluate the interfacial coupling strength at the corresponding interfaces. Moreover, the interfacial coupling strength at Gr/hBN interface is also successfully revealed in Gr/hBN/MoTe2 ternary vdWHs, which cannot be directly characterized from Gr/hBN binary vdWH due to its unobservable interlayer modes with weak electron-phonon coupling. This general strategy can be further extended to probe and quantify the interfacial coupling quality in polynary vdWHs and related devices.

Abstract Background Bodily distress syndrome (BDS) is a new, empirical-based diagnosis of functional somatic symptoms. This study aimed to explore the prevalence of BDS and its association with psychosocial variables in a Chinese clinical population. Methods A multicentre cross-sectional study of 1269 patients was conducted in 9 different Chinese tertiary outpatient hospitals. The BDS was identified by trained interviewers face-to face, based on a brief version of the Schedules for Assessment in Neuropsychiatry (RIFD) and the BDS Checklist-25. Sociodemographic data and further information were characterised from psychometric questionnaires (The Patient Health Questionnaire-15, the Patient Health Questionnaire-9, the General Anxiety Disorder-7, the Whiteley scale-8) . Results Complete data were available for 697 patients. The prevalence of BDS was 26.8% (95% confidence interval (CI): 23.5–30.1). Among the participants, 5.8% (95% CI: 4.1–7.6) fulfilled the criteria for single-organ BDS, while 20.9% (95%CI: 17.9–24.0) had multi-organ BDS. Comparison of the PHQ-15, PHQ-9, GAD-7, and WI-8 scores revealed higher scores on all dimensions for patients with BDS. In a binary logistic regression analysis, BDS was significantly associated with increased health-related anxiety (WI-8) and depression (PHQ-9). The explained variance was Nagelkerke’s R 2 = 0.42. Conclusions In China, the BDS is a common clinical condition in tertiary outpatient hospital settings with high prevalence, and is associated with health anxiety and depressive symptoms. In this clinical population, the severe multi-organ subtype of BDS was the most frequent.

Parkinson’s disease (PD) is a well-known neurodegenerative disorder characterized by the degeneration of dopaminergic neurons, and oxidative stress and neuroinflammation are also associated with the pathogenesis of PD. Mitochonic acid 5 (MA-5), an analogue of indole-3-acetic acid, exerts key protective roles in inhibiting apoptosis, oxidative stress and neuroinflammation in multiple diseases. However, whether MA-5 can be beneficial for PD remains unclear. Hence, the aim of this study was to investigate the neuroprotective role of MA-5 in PD. In the current study, MPTP-challenged mice were treated as the in vivo model, and the effect of MA-5 on the motor function, neuronal survival, oxidative stress, neuroinflammation and the underlying mechanisms involved with AMPK and autophagy were determined. We revealed that MA-5 obviously up-regulated the phosphorylation of AMPK and promoted the autophagy (indicated by the increased LC3II/LC3I, parkin, pink and decreased p62) in substantia nigra (SN), ameliorated the motor deficits, up-regulated the expression of TH, suppressed the inflammation (indicated by the decreased protein levels of interleukin (IL)-1b, IL-6, tumour necrosis factor a) in SN in MPTP-induced mice. However, these patterns were reversed after the treatment of Compound C, an inhibitor of AMPK; also, after the application of CSA, an inhibitor of autophagy, MA-5 cannot play against the neurotoxicity of MPTP in mice. These combined results suggest that MA-5 can protect against MPTP-induced neurotoxicity to ameliorate the impaired motor function, which may be modulated via activation of AMPK-induced autophagy.

Bread and soup are two of the most important foods in daily life, thus dough fermentation and nutrient soup elaboration are more and more popular, but there is a lack of relevant low-cost and high-reliable household appliances on the market. Therefore, this paper proposes automatic control methods for dough fermentation and nutrient soup elaboration based on a special microwave oven. Fermentation theory, run-up microwave fermentation principle, microwave extraction principle, NTC temperature probe design and scalable fuzzy control algorithm are described in detail. Besides, the experimental platform is set up with a temperature chamber, an optical fiber thermometer and a power meter. Experimental results demonstrate that the relationship between the heating time and flour's mass is linear. For different ambient temperature tests, the volume ratios of the fermented dough to unfermented dough of different cases range from 2.2 to 2.62, and the inside of the dough after fermentation is fluffy, with small and dense cavities. Meanwhile, there is no acid taste and skin dryness, and the power consumption of microwave fermentation is less than half of that induced by grill, convection or steam fermentation. The detection error of the NTC temperature probe with microwave shielded is 0.48 °C, and the control error of the closed loop system is less than 0.5 °C. The temperature-rise slope of water is lower than that of ingredient, and the water's temperature is about 1 °C less than that of the ingredient. The soup after microwave elaboration is amber and clear, the ingredients are intact, the water loss is less than 50 g, and the total power consumption is 684 Wh. In short, microwave-based control methods for dough fermentation and nutrient soup elaboration are effective.

ObjectiveThe aim of this study is to investigate the psychometric characteristics of outpatients diagnosed with somatic symptom disorder (SSD) in biomedical, Traditional Chinese Medicine (TCM) and psychosomatic settings.Materials and methodsA total of 697 participants who completed SCID-5 and questionnaires were presented in our former study, as 3 of them had missed questionnaire data, a total of 694 participants are presented in this study. A secondary analysis of the psychometric characteristics of Somatic Symptom Disorder–B Criteria Scale (SSD-12), Somatic Symptom Severity Scale of the Patient-Health Questionnaire (PHQ-15), Patient Health Questionnaire-9 (PHQ-9) and General Anxiety Disorder-7 (GAD-7) is done to compare differences among outpatients from the three settings of medical specialties.ResultsBased on the DSM-5 criteria, 90 out of 224 (40.2%) participants enrolled in biomedical departments (represented by neurology and gastroenterology departments), 44/231 (19.0%) in TCM departments, and 101/239 (42.3%) in the psychosomatic medicine departments were diagnosed with SSD. The scores of PHQ-15 in the biomedical, TCM and psychosomatic settings were 11.08 (± 4.54), 11.02 (± 5.27) and 13.26 (± 6.20); PHQ-9 were 10.43 (± 6.42), 11.20 (± 5.46) and 13.42 (± 7.32); GAD-7 were 8.52 (± 6.22), 9.57 (± 5.06) and 10.83 (± 6.24); SSD-12 were 22.26 (± 11.53), 22.98 (± 10.96) and 25.03 (± 11.54) respectively. The scores of PHQ-15, PHQ-9 and GAD-7 in SSD patients were significantly higher in psychosomatic departments than that in biomedical settings (p

Nausea and vomiting (CINV) are distressful and widespread side effects of chemotherapy, and additional efficient regimens to alleviate CINV are urgently needed. In the present study, colorectal cancer (CRC) mice model induced by Azoxymethane (AOM)/Dextran Sodium Sulfate (DSS) was employed to evaluate the cancer suppression and CINV amelioration effect of the combination of thalidomide (THD) and Clostridium butyricum. Our results suggested that the combination of THD and C. butyricum abundantly enhanced the anticancer effect of cisplatin via activating the caspase-3 apoptosis pathway, and also ameliorated CINV via inhibiting the neurotransmitter (e.g., 5-HT and tachykinin 1) and its receptor (e.g., 5-HT3R and NK-1R) in brain and colon. Additionally, the combination of THD and C. butyricum reversed the gut dysbacteriosis in CRC mice by increasing the abundance of Clostridium, Lactobacillus, Bifidobacterium, and Ruminococcus at the genus level, and also led to increased expression of occludin and Trek1 in the colon, while decreased expression of TLR4, MyD88, NF-κB, and HDAC1, as well as the mRNA level of IL-6, IL-1β, and TNF-α. In all, these results suggest that the combination of THD and C. butyricum had good efficacy in enhancing cancer treatments and ameliorating CINV, which thus provides a more effective strategy for the treatment of CRC.

Somatic symptom disorder (SSD) is a new diagnosis introduced into the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), which is expected to solve the diagnostic difficulties of patients with medically unexplained symptoms.Based on the previous work, this review aims to comprehensively synthesise updated evidence related to SSD from recent years in English publications and, more extensively, from data published in Chinese language journals.The scoping review update was based on an earlier scoping review and included Chinese language publication data from China National Knowledge Internet (CNKI), WANFANG and WEIPU between January 2013 and May 2022 and data from PubMed, PsycINFO, and Cochrane Library between June 2020 and May 2022.Initially, 2 984 articles were identified, of which 63 full texts were included for analysis. In China, SSD is mainly applied in scientific research, but it also shows good predictive validity and clinical application potential. The mean frequency of SSD was 4.5% in the general population, 25.2% in the primary care population and 33.5% in diverse specialised care settings. Biological factors, such as brain region changes and heart rate variability, are associated with the onset of SSD. Psychological impairment related to somatic symptoms is the best predictor of prognosis. While adolescent SSD was significantly associated with family function, SSD overall is associated with an increased dysfunction of cognition and emotion, decreased quality of life, and high comorbidity with anxiety and depressive disorders. Further research is needed on suicide risk and cultural and gender-related issues.Updating the data of Chinese language studies, our research enriches the evidence-based findings related to the topics addressed in the text sections of the SSD chapter of DSM-5. However, research gaps remain about SSD reliability, population-based prevalence, suicide risk, and cultural and gender-related issues.

Background: The clinical characteristics of chronic cough with pre-existing psychological co-morbidity (PCC) and chronic cough with secondary anxiety and depression (SCC) were compared to provide a basis for diagnosing and treating psychological co-morbidities in people with chronic cough. Methods: A prospective study was conducted to analyze the general clinical data between the PCC, SCC, and the chronic cough without anxiety and depression (CC) groups. A total of 203 patients with chronic cough were enrolled in the study. The final diagnosis was made in all cases using a combination of psychosomatic and respiratory diagnoses. The three groups’ general clinical data, capsaicin cough sensitivity, cough symptom score, Leicester cough questionnaire (LCQ), and psychosomatic scale scores were compared among the three groups. The diagnostic value of the patient health questionnaire (PHQ)-9 and general anxiety disorder (GAD)-7 in patients with PCC and the follow-up information were analyzed. Results: Compared with the SCC group, the duration of cough in the PCC group was shorter (H = −3.54, p = 0.001), the night cough symptoms were milder (H = −4.60, p

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.

Abstract Introduction Neuroendocrine differentiation (NED) in colorectal cancer (CRC) cells has been known for decades, and our previous meta-analysis indicated that CRC patients with neuroendocrine differentiation have a lower 5-year survival rate. In recent years, an increasing number of studies have found that exosome-derived long non-coding RNAs (lncRNAs) play important roles in cancer progression and metastasis. However, the functions and mechanism of exosome-derived lncRNAs in CRC with neuroendocrine differentiation are not yet fully clear. Materials and methods The clinical significance of NED was assessed in a retrospective study of 105 patients. Next-generation sequencing and bioinformatics analysis were conducted to select lnc-HOXB8-1:2 for further study. Using immunohistochemistry, qRT–PCR, western blot, transwell assay, immunofluorescence assay, fluorescence in situ hybridization assay and dual-luciferase reporter assay, the oncogenic role of exosome-derived lnc-HOXB8-1:2 was determined in CRC with NED. The mechanism underlying the lnc-HOXB8-1:2/hsa-miR-6825-5p/CXCR3 axis was also explored. Results NED was a risk factor for the progression and mortality of CRC. lnc-HOXB8-1:2, derived from exosomes secreted by neuroendocrine differentiated colon cancer cells, was identified in our study. The proportion of M2 macrophages and the migration and invasion capacities of tumor-associated macrophages (TAMs) markedly increased after the addition of neuroendocrine differentiated CRC cell-derived exosomes. More excitingly, the expression of lnc-HOXB8-1:2 and the protein level of CXCR3 were also upregulated in TAMs. The lnc-HOXB8-1:2/hsa-miR-6825-5p/CXCR3 axis was predicted via miRanda software and confirmed by the dual-luciferase reporter assay. Furthermore, the increased expression of lnc-HOXB8-1:2 was accompanied by downregulation of hsa-miR-6825-5p expression and upregulation of CXCR3 protein levels. Overexpression of hsa-miR-6825-5p also reduced CXCR3 expression. Conclusion lnc-HOXB8-1:2 in exosomes derived from neuroendocrine differentiated CRC cells acted as a ceRNA competitively binding hsa-miR-6825-5p to upregulate CXCR3 expression and leading to TAM infiltration and M2 polarization, which promotes neuroendocrine differentiated CRC progression.

BackgroundUnderstanding the effects of demographic drivers on lung cancer mortality trends is critical for lung cancer control. We have examined the drivers of lung cancer mortality at the global, regional, and national levels.MethodsData on lung cancer death and mortality were extracted from the Global Burden of Disease (GBD) 2019. Estimated annual percentage change (EAPC) in the age-standardized mortality rate (ASMR) for lung cancer and all-cause mortality were calculated to measure temporal trends in lung cancer from 1990 to 2019. Decomposition analysis was used to analyze the contributions of epidemiological and demographic drivers to lung cancer mortality.ResultsDespite a non-significant decrease in ASMR [EAPC = −0.31, 95% confidence interval (CI): −1.1 to 0.49], the number of deaths from lung cancer increased by 91.8% [95% uncertainty interval (UI): 74.5–109.0%] between 1990 and 2019. This increase was due to the changes in the number of deaths attributable to population aging (59.6%), population growth (56.7%), and non-GBD risks (3.49%) compared with 1990 data. Conversely, the number of lung cancer deaths due to GBD risks decreased by 19.8%, mainly due to tobacco (−12.66%), occupational risks (−3.52%), and air pollution (−3.47%). More lung cancer deaths (1.83%) were observed in most regions, which were due to high fasting plasma glucose levels. The temporal trend of lung cancer ASMR and the patterns of demographic drivers varied by region and gender. Significant associations were observed between the contributions of population growth, GBD risks and non-GBD risks (negative), population aging (positive), and ASMR in 1990, the sociodemographic index (SDI), and the human development index (HDI) in 2019.ConclusionPopulation aging and population growth increased global lung cancer deaths from 1990 to 2019, despite a decrease in age-specific lung cancer death rates due to GBD risks in most regions. A tailored strategy is needed to reduce the increasing burden of lung cancer due to outpacing demographic drivers of epidemiological change globally and in most regions, taking into account region- or gender-specific risk patterns.