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Wound healing is an ongoing concern for the medical community. The limitations of traditional dressings are being addressed by materials and manufacturing technology. Microneedles (MNs) are a novel type of drug delivery system that has been widely used in cancer therapy, dermatological treatment, and insulin and vaccine delivery. MNs locally penetrate necrotic tissue, eschar, biofilm and epidermis into deep tissues, avoiding the possibility of drug dilution and degradation and greatly improving administration efficiency with less pain. MNs represent a new direction for wound treatment and transdermal delivery. In this study, we summarise the skin wound healing process and the mechanical stimulation of MNs in the context of the wound healing process. We also introduce the structural design and manufacture of MNs. Subsequently, MNs are categorised according to the loaded drugs, where the design of the MNs according to the traumatic biological/biochemical microenvironment (pH, glucose, and bacteria) and the physical microenvironment (temperature, light, and ultrasound) is emphasised. Finally, the advantages of MNs are compared with traditional drug delivery systems and their prospects are discussed.

BackgroundSplenic littoral cell angioma (LCA) is an exceptionally uncommon malignant potential vascular tumor with infrequent occurrences in pediatric patients. Due to its reliance on histopathological analysis for diagnosis, LCA may be mistakenly identified as other splenic tumors. Patients with LCA may experience anemia or thrombocytopenia, but peripheral blood pancytopenia is infrequent.Case reportA 14-year-old boy presented with peripheral blood pancytopenia, necessitating hospitalization after splenomegaly was identified during a physical examination. Following the exclusion of hematological disorders, a splenectomy was conducted; histopathological examination confirmed the diagnoses of LCA. No metastases or recurrences were observed during the 8-month follow-up. To the best of our knowledge, this case represents the first instance of LCA associated with pancytopenia in a pediatric patient.ConclusionLCA can lead to iron-deficiency anemia or thrombocytopenia, with rare occurrences of pancytopenia, potentially resulting in misdiagnosis as a hematological disorder. Surgical intervention remains an effective treatment for LCA.

Drivers are more likely to feel fatigue when driving on the desert highway due to its single line, monotonous road side landscape, and small traffic volume, etc., so the method of setting fatigue warning signs on desert highway should be studied for. In this paper, field investigation and field test are carried out on the section of Uma Expressway crossing Tengger Desert, and the same road scene and line shape as the actual one are constructed by using uc-win road. Driving simulation experiments were carried out by using driving simulation cabin, collecting heart and muscle electric indexes and analyzing fatigue characteristic law. On this basis, simulation experiments of different fatigue warning signs and stimulation intervals were carried out in multiple groups, and the pattern of cardiac and electromyographic indexes and the interaction law were analyzed based on the artifact correction method after denoising the measured data, so that the optimal setting method was obtained according to the stimulation effect. Based on the artifact correction method, the measured data were de-noised and analyzed the changes of ECG and EMG indexes and the interaction law, and the best setting method was obtained according to the stimulation effect. Finally, the fatigue level was classified based on the cohesive hierarchical system cluster analysis method to verify the rationality of the fatigue warning sign setting scheme. The results show that the driver's psychological fatigue and physiological fatigue both show obvious fluctuation growth, and the growth trend exists in four stages, namely, smooth fluctuation (0–30min), initial fatigue (35–85min), adjustment stage (85–160min), and severe fatigue (after 160min), and psychological fatigue is earlier than physiological fatigue, and the driver's regulation effect on physiological fatigue is better than psychological fatigue. Analysis of the psychological indexes of the four groups of traffic signs shows that the fatigue warning signs with black characters on a white background and set at an interval of 60–80 km have the most obvious effect on driver stimulation in a desert highway with a design speed of 80–100 km/h.

Abstract In recent years, due to the shortage of blood products, some extensive burn patients were forced to adopt an “ultra-restrictive” transfusion strategy, in which the hemoglobin levels of RBC transfusion thresholds were 0.05). Among the ultra-restrictive transfusion group, patients with RBC transfusion threshold

Landslide are one of the most common types of geological disasters in China, posing a serious threat to the safety of people's lives and properties due to their propensity and frequency. The stability assessment of landslides is crucial in landslide disaster prevention and mitigation works. Considering the fuzzy nature of landslide inducing factors, a certain accumulation layer landslide in Xinpu Town, Mianxian County is taken as an example in this article. Based on the analysis of geological environmental conditions, a fuzzy mathematical method is employed for landslide stability assessment. The concept of "entropy" from thermodynamics is introduced, and the entropy weight method is used to determine the weights of landslide inducing factors. Consequently, a new method for landslide stability assessment based on the improved entropy weighting method in fuzzy mathematics is proposed. The results show that the proposed method overcomes the subjectivity in determining the weights of landslide influencing factors in traditional fuzzy comprehensive evaluation methods. Validation through quantitative analysis of landslide stability using numerical simulation method found that the evaluation conclusions of the two methods were in good consistent, indicating the reliability of the proposed new method. The improved fuzzy mathematical landslide stability assessment based on entropy weighting method is relatively fast and simple, making it suitable for landslide disaster prevention and mitigation works in emergency situations such as rapid disaster warning of impending disasters and emergency rescue.

The reliability of online monitoring device for metal oxide arrester (MOA) is the prerequisite for ensuring the MOA normal operation. For online monitoring device, this paper proposes the non-destructive calibration scheme which can improve maintenance efficiency. The on-site calibration device consists of current source, ammeter, micro-current detector and control unit. There are two key technologies involved in the on-site calibration device, the one is the phase locked loop (PLL) for current source, the other is the high precision current detection for ammeter and micro-current detector. The proposed PLL of the reference voltage can generate low delay orthogonal signals and eliminate the second harmonic disturbances caused by the crystal oscillator error of microcontroller unit (MCU). The experimental results show the effectiveness of the proposed calibration scheme.

Soil piping erosion is an underground soil erosion process that is significantly underestimated or overlooked. It can lead to intense soil erosion and trigger surface processes such as landslides, collapses, and channel erosion. Conducting susceptibility mapping is a vital way to identify the potential for soil piping erosion, which is of enormous significance for soil and water conservation as well as geological disaster prevention. This study utilized airborne radar drones to survey and map 1194 sinkholes in Sunjiacha basin, Huining County, on the Loess Plateau in Northwest China. We identified seventeen key hydrogeomorphological factors that influence sinkhole susceptibility and used six machine learning models—support vector machine (SVM), logistic regression (LR), Convolutional Neural Network (CNN), K-Nearest Neighbors (KNN), random forest (RF), and gradient boosting decision tree (GBDT)—for the susceptibility assessment and mapping of loess sinkholes. We then evaluated and validated the prediction results of various models using the area under curve (AUC) of the Receiver Operating Characteristic Curve (ROC). The results showed that all six of these machine learning algorithms had an AUC of more than 0.85. The GBDT model had the best predictive accuracy (AUC = 0.94) and model migration performance (AUC = 0.93), and it could find sinkholes with high and very high susceptibility levels in loess areas. This suggests that the GBDT model is well suited for the fine-scale susceptibility mapping of sinkholes in loess regions.

Abstract The inflammatory damage caused by thrombus formation and dissolution can increase the risk of thrombotic complications on top of cell death and organ dysfunction caused by thrombus itself. Therefore, a rapid and precise thrombolytic therapy strategy is in urgent need to effectively dissolve thrombus and resist oxidation simultaneously. In this study, Ce‐UiO‐66, a cerium‐based metal–organic framework (Ce‐MOF) with reactive oxygen species (ROS) scavenging properties, encapsulated by low‐immunogenic mesenchymal stem cell membrane with inflammation‐targeting properties, is used to construct a targeted nanomedicine Ce‐UiO‐CM. Ce‐UiO‐CM is applied in combination with external ultrasound stimulation for thrombolytic therapy in rat femoral artery. Ce‐UiO‐66 has abundant Ce (III)/Ce (IV) coupling sites that react with hydrogen peroxide (H2O2) to produce oxygen, exhibiting catalase (CAT) activity. The multi‐cavity structure of Ce‐UiO‐66 can generate electron holes, and its pore channels can act as micro‐reactors to further enhance its ROS scavenging capacity. Additionally, the porous structure of Ce‐UiO‐66 and the oxygen produced by its reaction with H2O2 may enhance the cavitation effects of ultrasound, thereby improving thrombolysis efficacy.

Abstract Acute lung injury/acute respiratory distress syndrome (ALI/ARDS) is characterised by an uncontrolled inflammatory response, and current treatment strategies have limited efficacy. Although the protective effect of M2‐like macrophages (M2φ) and their extracellular vesicles (EVs) has been well‐documented in other inflammatory diseases, the role of M2φ‐derived EVs (M2φ‐EVs) in the pathogenesis of ALI/ARDS remains poorly understood. The present study utilised a mouse model of lipopolysaccharide‐induced ALI to first demonstrate a decrease in endogenous M2‐like alveolar macrophage‐derived EVs. And then, intratracheal instillation of exogenous M2φ‐EVs from the mouse alveolar macrophage cell line (MH‐S) primarily led to a take up by alveolar macrophages, resulting in reduced lung inflammation and injury. Mechanistically, the M2φ‐EVs effectively suppressed the pyroptosis of alveolar macrophages and inhibited the release of excessive cytokines such as IL‐6, TNF‐α and IL‐1β both in vivo and in vitro, which were closely related to NF‐κB/NLRP3 signalling pathway inhibition. Of note, the protective effect of M2φ‐EVs was partly mediated by miR‐709, as evidenced by the inhibition of miR‐709 expression in M2φ‐EVs mitigated their protective effect against lipopolysaccharide‐induced ALI in mice. In addition, we found that the expression of miR‐709 in EVs derived from bronchoalveolar lavage fluid was correlated negatively with disease severity in ARDS patients, indicating its potential as a marker for ARDS severity. Altogether, our study revealed that M2φ‐EVs played a protective role in the pathogenesis of ALI/ARDS, partly mediated by miR‐709, offering a potential strategy for assessing disease severity and treating ALI/ARDS.

Liver impairment caused by VCM has been linked to irreversible damage such as fibrosis, necrosis, hepatocellular carcinoma, and liver angiosarcoma. However, the ability to detect abnormalities during initial phase have not been achieved so far. Thus, this study aimed to investigate the effect of interleukin 8 (IL-8) and C-X-C chemokines 2 (CXCR2) on screening for a VCM-exposed group (n = 227) from a PVC manufacturing factory compared to a control group (n = 110) in Tianjin City in 2020 with influence factors evaluation. Ambient concentrations of VCM and health archives from 2012 to 2018 were collected for establishing the dose-effect trend. A cross-sectional survey in 2020 was performed to measure TDGA, IL-8, CXCR2, 8-OHdG, SOD, GPX, CAT, MDA, and ROS levels. Results indicated a continuous increased incidence on liver abnormalities despite a fluctuated downward trend in cumulative time-weighted average (CTWA) VCM concentrations over the years. ALT, AST, and AST/ALT ratio all contributed to liver abnormalities that contained fatty liver, liver calcification, and liver cysts, IL-8 and CXCR2 correlated with each other strongly and showed significant associations with oxidative stress markers, even AST/ALT ratio. IL-8 (>1547 µg/m3) or CXCR2 (222 µg/m3), working years of 21 to 30 (a) and 11 to 20 (a), TDGA (>1.52 mg/L), alcohol consumption, smoking habit, and a less sleeping duration of

Abstract Advancing crop genomics requires efficient genetic systems enabled by high-quality personalized genome assemblies. Here, we introduce RagTag, a toolset for automating assembly scaffolding and patching, and we establish chromosome-scale reference genomes for the widely used tomato genotype M82 along with Sweet-100, a new rapid-cycling genotype that we developed to accelerate functional genomics and genome editing in tomato. This work outlines strategies to rapidly expand genetic systems and genomic resources in other plant species.

It's not just women who aspire to enhance their appearance; it's a universal human desire. An increasing number of men are gradually embracing beautification strategies as well. The impact of gender on perceptions of strategies users remains uncertain. This study focuses on the role of gender in beautification strategies and their influence on trustworthiness and morality evaluations. It aims to analyze the role played by both the gender of evaluators and the gender of targets, while also comparing the differences between the two most popular beautification strategies, makeup and cosmetic surgery, in shaping trustworthiness and morality evaluations. The results revealed male participants demonstrated a stronger negative bias towards these users, particularly male users. On the other hand, the research revealed that females exhibited greater tolerance when evaluating same-sex makeup users. Conversely, males gave more negative evaluations to same-sex strategies users. Furthermore, the results showed morality and trustworthiness evaluation for beautification targets was predicted by evaluators' acceptance of cosmetic surgery. This study not only contributes to the existing literature on gender differences in beautification strategies but also offers a gender-based perspective to help reduce the stigma associated with these strategies.

Abstract The vascularization of dermal substitutes is a key challenge in efforts to heal deep skin defects. In this study, dual gene‐activated dermal scaffolds (DGADSs‐1) were fabricated by loading nanocomposite particles of polyethylenimine (PEI)/multiple plasmid DNAs (pDNAs) encoding vascular endothelial growth factor and angiopoietin‐1 at a ratio of 1:1. In a similar manner, DGADSs‐2 were loaded with a chimeric plasmid encoding both VEGF and Ang‐1. In vitro studies showed that both types of DGADSs released PEI/pDNA nanoparticles in a sustained manner; they demonstrated effective transfection ability, leading to upregulated expression of VEGF and Ang‐1. Furthermore, both types of DGADSs promoted fibroblast proliferation and blood vessel formation, although DGADSs‐1 showed a more obvious promotion effect. A rat full‐thickness skin defect model showed that split‐thickness skin transplanted using a one‐step method could achieve full survival at the 12th day after surgery in both DGADSs‐1 and DGADSs‐2 groups, and the vascularization time of dermal substitutes was significantly shortened. Compared with the other three groups of scaffolds, the DGADSs‐1 group had significantly greater cell infiltration, collagen deposition, neovascularization, and vascular maturation, all of which promoted wound healing. Thus, compared with single‐gene‐activated dermal scaffolds, DGADSs show greater potential for enhancing angiogenesis. DGADSs with different loading modes also exhibited differences in terms of angiogenesis; the effect of loading two genes (DGADSs‐1) was better than the effect of loading a chimeric gene (DGADSs‐2). In summary, DGADSs, which continuously upregulate VEGF and Ang‐1 expression, offer a new functional tissue‐engineered dermal substitute with the ability to activate vascularization.

The reconstruction of the porous media model is crucial for researching the mesoscopic seepage characteristics of porous concrete. Based on a self-compiled MATLAB program, a porous concrete model was modeled by controlling four parameters (distribution probability, growth probability, probability density, and porosity) with clear physical meanings using a quartet structure generation set (QSGS) along with the lattice Boltzmann method (LBM) to investigate permeability. The rationality of the numerical model was verified through Poiseuille flow theory. The results showed that the QSGS model exhibited varied pore shapes and disordered distributions, resembling real porous concrete. Seepage velocity distribution showed higher values in larger pores, with flow rates reaching up to 0.012 lattice point velocity. The permeability–porosity relationship demonstrated high linearity (the Pearson correlation coefficient is 0.92), consistent with real porous concrete behavior. The integration of QSGS-LBM represents a novel approach, and the research results can provide new ideas and new means for subsequent research on the permeability of porous concrete or similar porous medium materials.

In mountainous regions, high-locality landslides have the characteristics of a latent disaster process with a wide disaster range, which can easily cause large casualties. Therefore, early landslide identification and dynamic stability evaluation are significant. We first used multi-temporal synthetic aperture radar data to detect potential landslides at Yezhi Site Area during the 2015–2020 period, identifying and mapping a total of 18 active landslides. The study area was found to have an average deformation rate between −15 and 10 mm/y during the period. Then, time series and spatiotemporal deformation characteristics of landslides were examined using interferogram stacking and small baseline interferometry techniques. The results show that the majority of the landslide deformations detected exhibit a periodic variation trend, and the study area was in a slow deformation state before 2017. Finally, combined with detection results, Google Earth optical images, and field investigations, it is concluded that the main factors affecting the time series deformation and spatial distribution of landslides in the study area are rainfall, geological factors, and engineering activities. The results of this study provide valuable technical references and support for early identification and dynamic stability evaluation of regional active landslides in complex terrain, especially for high-locality landslides.

Loess slopes are often prone to creeping after being subjected to rainfall, artificial irrigation, river water infiltration, etc. Eventually a landslide occurred, even causing a catastrophic accident. There are few studies on the creep properties of loess landslide soil under different water content in the existing literature, and there is a lack of quantitative analysis of the law. A series of triaxial creep tests of sliding zone soil of loess landslide in the Secaowan Village, Yulin City have been carried. The stress-strain-time curves and isochronous stress-strain curves with different water contents (w=10%，12%，14%，16%，18%, w represents the water content) are obtained and the influence of water content on the creep characteristics of loess is analyzed as well. The long-term strength of loess is obtained by using the isochronous curve method. The research results show that (1) When the water content of the sample is larger, the deviator stress required for the creep failure of the sample is smaller, and the axial strain is larger. This phenomenon can be explained by the electric double layer theory as follows: The thickness of free water increases, the degree of cementation among soil particles decreases, and the water film will lubricate the soil particles and make them easy to slip. (2) When the water content of the sample is larger, the time required for the creep strain to reach a stable state after each level of load is applied is longer. This phenomenon can be explained as follows: The increase of loess moisture reduces the structural integrity of the soil, and the adjustment of the internal structure of the soil is relatively slow under the action of stress. Therefore, it takes a longer time for the pore water pressure to dissipate during consolidation and creep. (3) By analyzing the surface morphology of the creep failure of the loess sample, it is found that when the water content is small, the sample after the creep failure has an obvious shear failure surface. When the water content of the sample is larger, the lateral swelling is more likely to occur, showing the characteristics of plastic failure, and indicating that when the moisture content is larger, the softening effect of water is greater than the effect of water on the crack expansion of the soil. (4) The long-term strength loss rate of loess is introduced. It reveals the law of long-term strength and long-term strength loss rate of loess landslide soil under different water content. The research results can provide a reference for the long-term stability analysis of loess landslides.

Power systems dominated by renewable energy encounter frequently large, random disturbances, and a critical challenge faced in power-system management is how to anticipate accurately whether the perturbed systems will return to the functional state after the transient or collapse. Whereas model-based studies show that the key to addressing the challenge lies in the attracting basins of the functional and dysfunctional states in the phase space, the finding of the attracting basins for realistic power systems remains a challenge, as accurate models describing the system dynamics are generally unavailable. Here we propose a new machine-learning technique, namely balanced reservoir computing, to infer the attracting basins of a typical power system based on measured data. Specifically, trained by the time series of a handful of perturbation events, we demonstrate that the trained machine can predict accurately whether the system will return to the functional state in response to a large, random perturbation, thereby reconstructing the attracting basin of the functional state. The working mechanism of the new machine is analyzed, and it is revealed that the success of the new machine is attributed to the new objective function adopted in optimizing the machine hyperparameters, which keeps a good balance between the echo and fading properties of the reservoir network; the effect of noisy signals on the prediction performance is also investigated, and it is found that the machine performance is improved by introducing a certain amount of noise. Finally, we demonstrate that the new technique can also be utilized to infer the attracting basins of coexisting attractors in typical chaotic systems.

This paper investigates the vibration bandgap properties of two-dimensional (2D) periodic composite beam frame structures with component defects. Combined with the topological characteristics of the structure, a generalized position coordinate system is proposed, and an assembly method of the stiffness matrix for the virtual full component model is presented. Then the spectral equations of motion of the whole 2D periodic composite beam frame structures and the ones with component defects are established. Compared with the frequency-domain solutions calculated using the finite element method, the accuracy and the feasibility of the spectral element method (SEM) solutions are verified. It can be shown that the SEM is suitable for analyzing the vibration bandgap properties, and the influence of different component defects and their combination on the bandgap characteristics of 2D periodic frame structures is studied. The results show that forbidden gap splitting will occur in the main bandgap of the structure, but the degree of influence varies. The results also show that the influence of component defects on unsymmetrical or irregular positions of the vibration bandgaps of periodic frame structures is greater than the one in symmetrical or regular positions.

Objective. Necrotizing soft-tissue infections (NSTIs) are rare clinical infections with surgical emergencies having a high mortality rate. This study aimed to investigate risk factors for mortality and amputation of patients with NSTI. Methods. We retrospectively analyzed critical factors for outcomes of 111 patients with NSTI hospitalized in our department from 1 January 1999 to 31 December 2018. NSTI diagnosis was based on the patient’s clinical characteristics, laboratory risk indicator for necrotizing fasciitis (LRINEC) score, laboratory test data, and microbiological findings in blood and wound culture. The risk factors for mortality and amputation of NSTI were determined using univariate or multivariate logistic regression analysis, receiver operating characteristics (ROC), and the area under the ROC curve (AUC) at 90 days after admission. Results. Diagnosis of 111 patients with NSTI was confirmed according to clinical features, LRINEC score, image data, laboratory findings, and microorganism culture in blood and wounds. The mortality rate was 9.91% (11/111) at day 90 follow-up. High white blood cell (WBC), low hematocrit (HCT), and multiple surgeries were identified to be critical risk factors for NSTI mortality in univariate and multivariate logistic analyses. AUCs, 95% confidence intervals (CI), and P values of risk factors were 0.699, 0.54–0.95, and P=0.0117 for high WBC; 0.788, 0.63–0.97, and P=0.0006 for low HCT; and 0.745, 0.59–0.90, and P=0.0018 for multiple surgeries, respectively. These patients also had high LRINEC scores. Amputation occurred in 34.23% (38/111) of patients. Risk factors for amputation were higher age, low hemoglobin (Hb), and multiple wounds. AUCs, 95% confidence intervals (CI), and P values were 0.713, 0.11–0.32, and P

Diabetic foot ulcers, typical non-healing wounds, represent a severe clinical problem. Advanced glycation end-products (AGEs), which create a prolonged pro-inflammatory micro-environment in defective sites, can be responsible for refractoriness of these ulcers. Macrophages are polarized to the M2 phenotype to facilitate the transition from a pro-inflammatory microenvironment to an anti-inflammatory microenvironment, which has been demonstrated to be an effective way to accelerate diabetic wound closure. Herein, we developed coaxial hydro-membranes mimicking the extracellular matrix structure that are capable of anti-inflammatory and antibacterial functions for diabetic wound repair. These fibrous membranes maintain a moist microenvironment to support cell proliferation. Macrophages grow in an elongated shape on the surface of the fibrous membranes. The fibrous membranes effectively impaired macrophage AGE-induced M1 polarization and induced macrophage polarization towards the M2 phenotype. The effects of the fibrous membranes on the interactions between macrophages and repair cells under a diabetic condition were also investigated. Furthermore, in vivo results from a full-thickness diabetic wound model confirmed the potential of the coaxial hydro-membranes to accelerate wound healing. This study's results indicate that the developed bioactive anti-inflammatory and antibacterial wound dressing can affect AGE-induced macrophage activation and crosstalk between macrophages and fibroblasts for treating diabetic wounds.

Acetylene hydrochlorination and ethylene oxychlorination are the two most common methods of producing vinyl chloride monomer (VCM), which has been linked to liver impairment, hepatocellular carcinoma (HCC), and angiosarcoma of the liver (ASL) in occupational settings. However, whether and how these impairments could be effectively improved from workplace root causes has yet to be discovered. This study aimed to evaluate whether improvements in protective measures in groups Y (408 subjects) and Z (349 subjects) could have an influential impact on the alleviation of liver impairment by comparing risk assessment levels under several semi-quantitative models and results from liver ultrasound detection and liver function tests before and after the improvement. Importantly, significant differences in constituent ratio involved in parameters among age, length of employment, weekly exposure time, smoking status, alcohol consumption, and sleeping quality were found between Y and Z before improvement took place in 2020 (P < 0.05 or P < 0.001), and population distribution by gender between Y and Z was in a large homogeneity with differences in age and length of employment. CSTE involves ore breaking, acetylene generation, steam stripping, outward processing, and welding maintenance, was disqualified in 2020 compared to OEL, and was said to have declined to meet OEL requirements by 2021. Further, a negative correction of fresh air requirement and ventilation air changing rate with ambient concentration toward hazards in Y was stronger in 2021 than in 2020. Significant differences in risk levels in Y between 2020 and 2021 were found as ore breaking, acetylene generation, steam stripping, outward processing, VCM polymerization, welding, and repairing, decreasing to relatively lower risk levels in 2021 from the original ones in 2020 only under the semi-quantitative comprehensive index model. Abnormal rates toward other hepatic symptoms decreased in the majority of positions after the improvement, as referred to by alterations such as ALT, AST, and GGT. Overall, the effect of improvements on protective measures effectively reduced positions' risk assessment levels through ventilation enhancement and airtight strengthening, which further affected abnormal rates toward other hepatic symptoms, and alterations such as ALT, AST, and GGT were much more significant in Y than effect in Z.

BackgroundMachine learning (ML) is a type of artificial intelligence (AI) and has been utilized in clinical research and practice to construct high-performing prediction models. Hidden blood loss (HBL) is prevalent during the perioperative period of spinal treatment and might result in a poor prognosis. The aim of this study was to develop a ML-based model for identifying perioperative HBL-related risk factors in patients with thoracolumbar burst fracture (TBF).MethodsIn this study, single-central TBF patients were chosen. The medical information on patients, including clinical characteristics, laboratory indicators, and surgery-related parameters, was extracted. After comparing various ML model algorithms, we selected the best model with high performance. The model was validated using the internal validation set before performing recursive feature elimination (RFE) to determine the importance of HBL-related risk factors. The area under the receiver operating characteristic (AUC) curve, accuracy (ACC), sensitivity, and specificity were reported as critical model measures for evaluating predictive performance.ResultsIn this study, 62 (38.5%) of the 161 TBF patients were positive for HBL. There was a significant statistical difference in age, body mass index (BMI), diabetes, hypertension, Beta (percentage of vertebral restoration), duration of operation, and other pre-operative laboratory indicators between the HBL-positive and HBL-negative groups. Nine ML-based models were built and validated, with the Random Forest model having the greatest AUC in both the training set (0.905) and internal validation set (0.864). Furthermore, following RFE, age, duration of operation, Beta, pre-operative fibrinogen (Fib), and activated partial thromboplastin time (APTT) were identified as the five main important risk factors in patients with TBF during the perioperative period.ConclusionIn this study, we built and validated ML algorithms for an individualized prediction of HBL-related risk factors in the perioperative period of TBF. The importance of HBL-related risk factors could be determined, which contributes to clinicians' decision-making and improves perioperative management.

ObjectiveWe aimed to explore the association between the triglyceride-glucose (TyG) index, a marker of insulin resistance (IR), and vascular target organ damage (TOD) in a Beijing community-based population, China.MethodsA total of 6,015 participants from an atherosclerosis cohort survey performed in the Shijingshan District in Beijing, China were included in our analysis. Vascular TOD, such as carotid-femoral pulse wave velocity (cfPWV), brachial-ankle pulse wave velocity (baPWV), and the urine albumin-to-creatinine ratio (UACR) were all evaluated.ResultsThe overall mean age of all the participants was 62.35 years, 3,951 (65.69%) were female, and mean TyG index was 8.81. In univariable regression analyzes, an increased TyG index was associated with higher cfPWV, baPWV, lnUACR, and higher risk of cfPWV ≥ 10 m/s, baPWV ≥ 1,800 cm/s, and UACR ≥ 30 mg/g, respectively. Multivariable regression analyzes showed subjects with the TyG index in top tertile had a significant increase in cfPWV (β = 0.29 m/s; 95% confidence interval [95% CI] 0.19–0.40; pfortrend < 0.001), baPWV (β = 69.28 cm/s; 95% CI 50.97–87.59; pfortrend < 0.001), lnUACR (β = 0.23; 95% CI 0.13–0.34; pfortrend < 0.001), and had a higher risk of cfPWV ≥ 10 m/s (odds ratio [OR] = 1.47; 95% CI 1.17–1.85; pfortrend < 0.001), baPWV ≥ 1,800 cm/s (OR = 1.79; 95% CI 1.48–2.17; pfortrend < 0.001), and UACR ≥ 30 mg/g (OR = 1.71; 95% CI 1.30–2.24; pfortrend < 0.001) after fully adjusting for age, sex, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), estimated glomerular filtration rate (eGFR), self-reported coronary heart disease (CHD) and stroke, antihypertensive drugs, hypoglycemic drugs, and lipid-lowering drugs. Consistent conclusions were obtained in the subgroups without hypoglycemic and lipid-lowering medications or aged younger than 65 years old.ConclusionsThe TyG index was positively associated with artery stiffness and nephric microvascular damage in a Beijing community-based population in China. This result provides evidence that the TyG index may serve as a simple and effective indicator to reflect vascular TOD.

BackgroundSpinocerebellar ataxia type 3 (SCA3) is a rare movement disorder characterized with ataxia. Previous studies on movement disorders show that the whole-brain functional network tends to be more regular, and these reconfigurations correlate with genetic and clinical variables.MethodsTo test whether the brain network in patients with SCA3 follows a similar reconfiguration course to other movement disorders, we recruited 41 patients with SCA3 (mean age = 40.51 ± 12.13 years; 23 male) and 41 age and sex-matched healthy individuals (age = 40.10 ± 11.56 years; 24 male). In both groups, the whole-brain network topology of resting-state functional magnetic resonance imaging (rs-fMRI) was conducted using graph theory, and the relationships among network topologies, cytosine-adenine-guanine (CAG) repeats, clinical symptoms, and functional connectivity were explored in SCA3 patients using partial correlation analysis, controlling for age and sex.ResultsThe brain networks tended to be more regular with a higher clustering coefficient, local efficiency, and modularity in patients with SCA3. Hubs in SCA3 patients were reorganized as the number of hubs increased in motor-related areas and decreased in cognitive areas. At the global level, small-worldness and normalized clustering coefficients were significantly positively correlated with clinical motor symptoms. At the nodal level, the clustering coefficient and local efficiency increased significantly in the visual (bilateral cuneus) and sensorimotor (right cerebellar lobules IV, V, VI) networks and decreased in the cognitive areas (right middle frontal gyrus). The clustering coefficient and local efficiency in the bilateral cuneus gyrus were negatively correlated with clinical motor symptoms. The functional connectivity between right caudate nucleus and bilateral calcarine gyrus were negatively correlated with disease duration, while connectivity between right posterior cingulum gyrus and left cerebellar lobule III, left inferior occipital gyrus and right cerebellar lobule IX was positively correlated.ConclusionOur results demonstrate that a more regular brain network occurred in SCA3 patients, with motor and visual-related regions, such as, cerebellar lobules and cuneus gyrus, both forayed neighbor nodes as “resource predators” to compensate for normal function, with motor and visual function having the higher priority comparing with other high-order functions. This study provides new information about the neurological mechanisms underlying SCA3 network topology impairments in the resting state, which give a potential guideline for future clinical treatments.Clinical Trial Registration[www.ClinicalTrials.gov], identifier [ChiCTR1800019901].

The mechanical properties of the slip zone soil play an important role in the evolution of the loess landslides. To further understand these characteristics, a series of ring shear tests was conducted on the slip zone soils obtained from Tianshuigou landslide, to investigate the influence of moisture content, dry density, shear rate and shear method on the mechanical characteristics of slip zone soils. The experimental results showed that: an increase in the moisture content of the slip zone loess causes a significant reduction in the residual strength. Specially, both the residual cohesion and residual internal friction angle show a deceasing tendency with moisture content. The change in the residual cohesion is more sensitive to the variation in moisture content. Additionally, a trend that strength increased with the increasing of dry density was observed, and the influence degree of dry density on the increased strength is more pronounced at low moisture contents. Thirdly, shear strength shows a negative relationship with shear rate when the shear rate ranges from 0.01 mm/min and 1 mm/min. When the shear rate increased up to 10 mm/min, a stepped shear band is developed and the strength increased. In addition, the strain-softening phenomenon was observed in the single-stage shear tests, which was not noticed in the multi-stage shear tests and pre-shear tests. The residual strength obtained in pre-shear test and multi-stage shear test is slightly greater than that in the single-stage shear test. The experimental results herein can provide an important basis for analyzing the evolution mechanism and prevention of loess landslides.

In light of the increasing demand for the reliability analysis of self-recovery products, with features of limited storage period and multistage degradation, a reliability evaluation model in whole life cycle is proposed. The degradation process comprises one storage phase and two working phases. On the basis of the idea of competitive failure, the shock process and the feature of self-recovery were introduced into the model. Furthermore, the problem of it being difficult to add variables to a reliability model is solved with the use of the Stieltjes integral. The influences of the parameters of model reliability are analyzed, and the results demonstrate that the new model could adequately describe the competing failure process. The model also exhibited certain feasibility and theoretical reference values.

Speech enhancement tasks for audio with a low SNR are challenging. Existing speech enhancement methods are mainly designed for high SNR audio, and they usually use RNNs to model audio sequence features, which causes the model to be unable to learn long-distance dependencies, thus limiting its performance in low-SNR speech enhancement tasks. We design a complex transformer module with sparse attention to overcome this problem. Different from the traditional transformer model, this model is extended to effectively model complex domain sequences, using the sparse attention mask balance model’s attention to long-distance and nearby relations, introducing the pre-layer positional embedding module to enhance the model’s perception of position information, adding the channel attention module to enable the model to dynamically adjust the weight distribution between channels according to the input audio. The experimental results show that, in the low-SNR speech enhancement tests, our models have noticeable performance improvements in speech quality and intelligibility, respectively.

Since most of the cable-driven parallel manipulators (CDPMs) are small in dimension or low in speed, the self-weight or inertia of the cable is neglected when dealing with the problems of kinematics, dynamics and workspace. The cable is treated as a massless straight line, and the inertia of the cable is not discussed. However, the camera robot is a large-span high-speed CDPM. Thus, the self-weight and inertia of the cable cannot be negligible. The curved cable due to the self-weight is modeled as a catenary to accurately account for its sagging effect. Moreover, the dynamic model of the camera robot is derived by decomposing the motion of the cable into an in-plane motion and an out-plane motion, based on which an iterative-based tension distribution algorithm and a workspace generation algorithm are presented. An optimization model is presented to simultaneously improve the workspace volume, anti-wind disturbance ability and impulse of tensions on the camera and pan–tilt device system (CPTDS) by selecting the proper optimal variables under the linear and nonlinear constraints. An improved genetic algorithm (GA) is proposed, and the simulation results demonstrate that the improved GA offers a stronger ability in global optimization compared to the standard genetic algorithm (SGA). The ideal-point method is employed to avoid the subjective influence of the designer when performing the multi-objective optimization, and a remarkable improvement of the performance is obtained through the optimization. Furthermore, the distribution characteristics of the optimization objects are studied, and some valuable conclusions are summarized, which will provide some valuable references in designing large-span high-speed CDPMs.

The prediction of bearing remaining useful life (RUL) plays a pivotal role in ensuring the safe operation of machinery and reducing maintenance loss. Traditional prediction methods only consider the features of one domain or integrate the features of multiple domains into a one-dimensional sequence as the model input, which leads to some inaccuracy in prediction. In order to improve the prediction accuracy, a bearing RUL prediction method based on the parallel deep residual convolution neural network (P-ResNet), which is considered both time-domain features and time–frequency features, is proposed in this paper. Synchronous wavelet transform (SWT) is adopted to extract time–frequency features from original vibration signals. Both the time domain features and time–frequency domain features after dimension reduction by PCA are used as input to P-ResNet, which contains two series of parallel convolution operations to learn the time–frequency features and time-domain features, respectively, to ensure the comprehensiveness of information-bearing degradation. The residual layers were added to enhance the learning ability of time–frequency features. Kalman filter algorithm was used to smooth the prediction results. The IEEE PHM 2012 Data Challenge datasets were used as data sources for model training and prediction. Compared with the traditional convolutional neural network (CNN), the P-ResNet model maintains the synchronization of global and local information and has a stronger learning ability. The experiment data validate the effectiveness of the proposed method, and the comparison between the prosed methods and the others proves the superiority of the proposed method.

Whereas the importance of transient dynamics to the functionality and management of complex systems has been increasingly recognized, most of the studies are based on models. Yet in realistic situations the mathematical models are often unknown and what is available are only measured time series. Meanwhile, many real-world systems are dynamically stable, in the sense that the systems return to their equilibria in a short time after perturbations. This increases further the difficulty of dynamics analysis, as many information of the system dynamics are lost once the system is settled onto the equilibrium states. The question we ask is: Given the transient time series of a complex dynamical system measured in the stable regime, can we infer from the data some properties of the system dynamics and make predictions, e.g., predicting the critical point where the equilibrium state becomes unstable? We show that for the typical transitions in system of coupled oscillators, including quorum sensing, amplitude death, and complete synchronization, this question can be addressed by the technique of reservoir computing in machine learning. More specifically, by the transient series acquired at several states in the stable regime, we demonstrate that the trained machine is able to predict accurately not only the transient behaviors of the system in the stable regime, but also the critical point where the stable state becomes unstable. Considering the ubiquitous existence of transient activities in natural and man-made systems, the findings may have broad applications.