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Abstract Background Accurately predicting the walking independence of stroke patients is important. Our objective was to determine and compare the performance of logistic regression (LR) and three machine learning models (eXtreme Gradient Boosting (XGBoost), Support Vector Machines (SVM), and Random Forest (RF)) in predicting walking independence at discharge in stroke patients, as well as to explore the variables that predict prognosis. Methods 778 (80% for the training set and 20% for the test set) stroke patients admitted to China Rehabilitation Research Center between February 2020 and January 2023 were retrospectively included. The training set was used for training models. The test set was used to validate and compare the performance of the four models in terms of area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1 score. Results Among the three ML models, the AUC of the XGBoost model is significantly higher than that of the SVM and RF models (P

To date, no specific treatments have been developed for high-salt-induced hypertensive vascular damage, emphasizing the need to elucidate its underlying molecular mechanisms for therapeutic innovation. Kaempferol (Kae), a natural flavonol belonging to the flavonoid family, has demonstrated significant vascular protective effects in previous studies. However, its impact on high-salt-induced hypertensive vascular injury remains unclear. This study aimed to explore the pharmacological effects and underlying mechanisms of Kae in mitigating hypertensive vascular damage. Using an 8 % high-salt diet model, we evaluated the effects of Kae (200 mg/kg/day) in wild-type (WT) and activating transcription factor 4 (ATF4+/−) knockout mice. Additionally, human aortic endothelial cells (HAECs) cultured under high-salt conditions were used to assess Kae's protective effects, with ATF4 and acyl-CoA synthetase long-chain family member 4 (ACSL4) knocked down via siRNA transfection. Our results showed that Kae significantly reduced high-salt-induced hypertension, improved vascular endothelial dysfunction, inhibited ferroptosis, and suppressed ATF4 expression. Compared to ATF4+/−mice on a high-salt diet, ATF4+/−mice treated with Kae exhibited greater reductions in blood pressure and endothelial damage and more pronounced inhibition of ferroptosis. Surface plasmon resonance and molecular docking analyses revealed that Kae directly binds to ATF4, while proteome microarray and co-immunoprecipitation assays demonstrated that ATF4 interacts with ACSL4 in HAECs. Furthermore, inhibition of ATF4 or ACSL4 effectively alleviated endothelial ferroptosis induced by high-salt stress. In summary, our findings suggest that Kae mitigates high-salt-induced hypertension by inhibiting endothelial ferroptosis via the ATF4/ACSL4 pathway, providing a potential therapeutic strategy for hypertensive vascular injury.

As the penetration of renewable energy continues to rise, the occurrence of ramp events in renewable generation poses significant challenges to power system security and efficient renewable energy utilization. To optimize the power allocation of hybrid energy storage systems (HESS) and enhance adjustable reserves to mitigate ramp events, a day-ahead and intraday two-stage multi-objective optimal dispatch strategy is proposed for hybrid power generation systems containing wind, photovoltaic, battery and hydrogen energy storage system (ESS). First, a novel optimization objective is presented to regulate the response priorities of different ESS by minimizing the energy loss, and balance the conservatism by a penalty factor. Then, a two-stage optimal dispatch model is proposed including two sub-models. The day-ahead multi-objective dispatch model considers generation plan, available storage capacity and energy loss, which identifies time slots when adjustable reserves is insufficient; the intraday dispatch model dynamically adjusts penalty factor for each time slot based on the day-ahead results to enhance adjustable reserves in advance. This combination of day-ahead and intraday dispatch models improves the farsightedness and computational efficiency. Finally, a non-isometric scaling method is presented to improve the distribution of Pareto optimal solutions for the non-dominated sorting genetic algorithm III (NSGA-III). Simulation results based on the actual data from Belgium and China demonstrate that the proposed method effectively mitigates the ramp stress and improves renewable energy utilization, with high computational efficiency and robustness to parameters.

Osteoarthritis (OA) is a degenerative joint disease caused by chronic inflammation that damages articular cartilage. In addition to the wear and tear of joints, aberrant remodelling driven by a significant presence of inflammatory mediators within the joint is one of the key mechanisms in the pathogenesis of OA. Among these factors, hyperactivation of Teffs subsets plays a crucial role in promoting this pathological process. The immune imbalance between proinflammatory CD4+ effector T cells (proinflammatory Teffs) and Tregs could be a crucial factor in the pathogenesis of OA. Therefore, correcting the imbalance of Tregs/proinflammatory Teffs may slow or inhibit the occurrence and development of OA, which could be a potential target for the treatment of OA. Mesenchymal stem cells (MSCs) possess anti-inflammatory and immunomodulatory properties, regulating both adaptive and innate immunity through mechanisms involving soluble factors such as IDO, PGE2, and TGF-β, as well as cell-to-cell contact and exosomes. Correcting the imbalance between Tregs and proinflammatory Teffs may be one of the mechanisms of MSCs in the treatment of OA. Therefore, this review aims to summarize the relationship between OA and the immune imbalance between Tregs and proinflammatory Teffs, the immunoregulatory role of Tregs in OA, and the role of MSCs and their exosomes in correcting the imbalance between Tregs and proinflammatory Teffs.

Salinity stress poses a major obstacle to agricultural productivity. Employing plant growth-promoting rhizobacteria (PGPR) has attracted significant attention due to its potential to improve plant development in challenging conditions. Yet, additional investigation is essential to fully understand the potential of PGPR in mitigating salinity stress, especially in field applications. Hence, this study investigated the resistance mechanisms of soybean (Glycine max (L.) Merr.) under salt stress with PGPR application through a field experiment with four treatments: normal soybean planting (NN), normal planting + PGPR (NP), salt stress planting (SN), and salt stress planting + PGPR (SP). This research investigated how applying PGPR under salt stress influences soybean photosynthetic traits, osmotic regulation, rhizosphere microbial communities, and yield quality. The results demonstrated that salt stress enhanced leaf temperature and significantly reduced the leaf area index, SPAD value, stomatal conductance, photosynthetic rate, and transpiration rate of soybeans. Compared to SN treatment, SP treatment significantly improved the stomatal conductance, photosynthetic rate, and transpiration rate by 10.98%, 16.28%, and 35.59%, respectively. Salt stress substantially increased sodium (Na+) concentration and Na+/K+ ratio in leaves, roots, and grains while reducing potassium (K+) concentration in roots and leaves. Under salinity stress, PGPR application significantly minimized Na+ concentration in leaves and enhanced K⁺ concentration in leaves, roots, and grains by 47.05%, 25.72%, and 14.48%, respectively. PGPR application boosted carbon assimilation (starch synthesis) by enhancing the activities of sucrose synthase, fructokinase, and ADP-glucose pyrophosphorylase. It improved physiological parameters and increased soybean yield by 32.57% compared to SN treatment. Additionally, PGPR enhanced antioxidant enzyme activities, including glutathione reductase, peroxidase, ascorbate peroxidase, and monodehydroascorbate reductase, reducing oxidative damage from salt stress. Analysis of rhizosphere microbial communities revealed that PGPR application enriched beneficial bacterial phyla such as Bacteroidetes, Firmicutes, Nitrospirae, and Patescibacteria and fungal genera like Metarhizium. These microbial shifts likely contributed to improved nutrient cycling and plant–microbe interactions, further enhancing soybean resilience to salinity. This study demonstrates that PGPR enhances soybean growth, microbial diversity, and salt tolerance under salinity stress, while future efforts should optimize formulations, explore synergies, and scale up for sustainable productivity.

Osteoarthritis (OA) is a degenerative joint disease caused by chronic inflammation that damages articular cartilage. At present, the treatment of OA includes drug therapy to relieve symptoms and joint replacement therapy for advanced OA. However, these palliatives cannot truly block the progression of the disease from the immunological pathogenesis of OA. In recent years, bone marrow mesenchymal stem cell (BMSC) transplantation has shown great potential in tissue engineering repair. In addition, many studies have shown that BMSC paracrine signals play an important role in the treatment of OA through immune regulation and suppressing inflammation. At present, the mechanism of inflammation-induced OA and the use of BMSC transplantation in joint repair have been reviewed, but the mechanism and significance of BMSC paracrine signals in the treatment of OA have not been fully reviewed. Therefore, this article focused on the latest research progress on the paracrine effects of BMSCs in the treatment of OA and the related mechanisms by which BMSCs secrete cytokines to inhibit the inflammatory response, regulate immune balance, and promote cell proliferation and differentiation. In addition, the application potential of BMSC-Exos as a new type of cell-free therapy for OA is described. This review aimed to provide systematic theoretical support for the clinical application of BMSC transplantation in the treatment of OA.

This study investigates the ethanol gas-sensing mechanisms of ZnO nanocrystals with distinct morphologies, synthesized via a hydrothermal method using various alkali sources. Significant differences in the gas-sensing performance and morphology of ZnO samples synthesized with ammonium carbonate (Na2CO3), hexamethylenetetramine (HMTA), ammonia solution (NH3·H2O), and sodium hydroxide (NaOH) were observed. ZnO were confirmed to be impurity-free through XRD analysis, and their morphological features were characterized by SEM. TEM, XPS, and FTIR were employed to further analyze the crystal structure and binding energy of ZnO. To elucidate the underlying mechanisms, density functional theory (DFT) calculations combined with electron depletion layer theory were applied to assess charge transfer processes and identify the most sensitive ZnO crystal planes for ethanol detection. Experimental gas-sensing tests, conducted across 5–1000 ppm ethanol concentrations within a 150–350 °C range, showed that ZnO prepared with Na2CO3, HMTA, and NaOH was responsive at high ethanol concentrations as low as 100 °C, while ZnO synthesized with ammonia required 250 °C to exhibit sensitivity. All ZnO samples demonstrated excellent recovery at low concentrations at 250 °C. By integrating experimental findings with theoretical insights, this study provides a comprehensive understanding of ethanol gas-sensing mechanisms in ZnO, highlighting the role of crystal plane engineering and charge transfer dynamics as critical factors influencing gas response.

Background: The injection of bone mesenchymal stem cells (BMSCs) for osteoarthritis (OA) treatment fails to address the disrupted extracellular microenvironment, limiting the differentiation and paracrine functions of BMSCs and resulting in suboptimal therapeutic outcomes. Proteoglycans (PGs) promote cell differentiation, tissue repair, and microenvironment remodeling. This study investigated the potential of combining PGs with BMSCs to increase the efficacy of OA treatment. Methods: We evaluated the effects of PG on BMSC and chondrocyte functions by adding various PG concentrations to the culture media. Additionally, a Transwell system was used to assess the impact of PG on the communication between BMSCs and chondrocytes. The results of the in vitro experiment were verified by tissue staining and immunohistochemistry following the treatment of OA model rats. Results: Our findings indicate that PG effectively induces Col II expression in BMSCs and enhances the paracrine secretion of TGF-β1, thereby activating the TGF-β signaling pathway in chondrocytes and increasing PRG4 gene expression. Compared with the other groups, the BMSC/PG treatment group presented a smoother articular surface and more robust extracellular matrix than the other groups in vivo, with significantly increased expression and distribution of Smad2/3 and PRG4. Conclusions: PG enhances BMSC differentiation into chondrocytes and stimulates paracrine TGF-β1 secretion. Proteoglycans not only promote chondrocyte differentiation and paracrine TGF-β1 signaling in BMSCs but also increase the sensitivity of chondrocytes to TGF-β1 secreted from BMSCs, leading to PRG4 expression through the TGFR/Smad2/3 pathway. Proteoglycans can enhance the therapeutic effect of BMSC treatment on OA and have the potential to delay the degeneration of OA cartilage.

In recent years, with the progress of new energy conversion technology, especially an increasing number of gas turbine units applied to the market, the connection between the natural gas system and the electric system has become increasingly close. Initially the gas and electricity markets operated relatively independently. Therefore, it is necessary to establish the coupling architecture of natural gas market and electricity market to meet the energy demand of users. This paper attempts to propose a power and gas coupling system based on clearing market structure. Firstly, the difference between natural gas–electricity coupling market and joint settlement market is discussed. The combined market considered in this paper is somewhat different from the associated electricity market and natural gas market. The calculations are easier and the results more reliable than those of the traditional linked gas markets and electric power market. Then, a mathematical model of joint clearing market is established based on bilateral energy contracts. Then, the piecewise linearization approximation (PLA) algorithm is proposed to solve the nonlinear problem. The locational piecewise price (LMEP) and locational marginal gas price (LMGP) are identified respectively, and the bilateral contracts are processed. The solution proposed in this paper guarantees strong duality and clear meaning of dual variables, making PLA easy to apply and solve market clearing problems based on dual variables or Lagrange multiplier pricing, as well as easy to deal with bilateral contract problems. Finally, the proposed joint clearing market is verified by an improved 3-electric bus and 6-gas node system.

Background and aimsLiver hepatocellular carcinoma (LIHC) exhibits a multifactorial etiology, insidious onset, and a significantly low 5-year survival rate. We aimed to evaluate the causal impact of exposure factors (Alzheimer’s disease, platelet count, ambidextrousness, cigarettes smoked per day, alcohol consumption, and endocarditis) on the risk of LIHC using a two-sample Mendelian randomization (MR) study.MethodsIndependent single nucleotide polymorphisms (SNPs) strongly associated with Alzheimer’s disease, platelet count, ambidextrousness, daily cigarette consumption, alcohol intake, and endocarditis were selected as instrumental variables (IVs) from the corresponding genome-wide association studies (GWAS). Genetic summary statistics for LIHC came from a GWAS that included 168 cases and 372,016 controls of European individuals. Multivariable MR analyses were performed to find the causal association between 6 exposure factors and LIHC risk. The inverse-variance weighted (IVW)-MR was employed as the primary analysis, and the MR-Egger regression, LASSO regression, and weighted Median approaches were performed as complementary analyses.ResultsMultivariable MR analysis showed causal association between Alzheimer’s disease [Odds ratio (OR) = 0.9999, 95% confidence intervals (CI) = 0.9998-0.9999, p = 0.0010], platelet count (OR = 0.9997, 95% CI = 0.9995-0.9999, p = 0.0066), alcohol consumption (OR = 0.9994, 95% CI = 0.9990-0.9999, p = 0.0098) and the LIHC outcome. After IVW-MR, MR-Egger and LASSO tests, the results are still significant. Next, we used different MR Methods to analyze platelet count, alcohol consumption, and Alzheimer’s disease separately. Moreover, both funnel plots and MR-Egger intercepts provided compelling evidence to refute the presence of directional pleiotropy in the association between platelet count, alcohol consumption, Alzheimer’s disease and the risk of LIHC. The IVW-MR analysis revealed a significant causal association between an elevated platelet count and a reduced risk of LIHC (OR = 0.9996, 95% CI= 0.9995-0.9998, p = 0.0005). Similarly, the analysis of weighted median revealed a negative correlation between platelet count and the risk of LIHC (OR = 0.9995, 95% CI = 0.9993-0.9999; p = 0.0160). Conversely, we observed a positive causal effect of alcohol consumption on the incidence of LIHC (OR = 1.0004, 95% CI = 0.9999-1.0009). However, no significant causal relationship was found between alcohol assumption, Alzheimer’s disease, and LIHC susceptibility.ConclusionsA significant causal relationship exists between platelet count, alcohol consumption, Alzheimer’s disease, and an increased risk of LIHC. The study presents compelling evidence for a genetically predicted decreased susceptibility to LIHC based on platelet count. The research implies that elevated platelet count may serve as a protective mechanism against LIHC. These findings may inform clinical strategies for LIHC prevention

As a canonical cytoplasmic DNA sensor, cyclic GMP-AMP synthase (cGAS) plays a key role in innate immunity. In recent years, a growing number of studies have shown that cGAS can also be located in the nucleus and plays new functions such as regulating DNA damage repair, nuclear membrane repair, chromosome fusion, DNA replication, angiogenesis and other non-canonical functions. Meanwhile, the mechanisms underlying the nucleo-cytoplasmic transport and the regulation of cGAS activation have been revealed in recent years. Based on the current understanding of the structure, subcellular localization and canonical functions of cGAS, this review focuses on summarizing the mechanisms underlying nucleo-cytoplasmic transport, activity regulation and non-canonical functions of cGAS in the nucleus. We aim to provide insights into exploring the new functions of cGAS in the nucleus and advance its clinical translation.

Inertial navigation systems experience error accumulation over time, leading to the use of integrated navigation as a classical solution to mitigate inertial drift. This provides a novel approach to navigation and positioning by using the combined advantages of inertial and geomagnetic navigation systems. However, inertial/geomagnetic navigation is affected by significant magnetic interference in practical scenarios, resulting in reduced navigation accuracy. This research introduces a new neural network-assisted integrated inertial–geomagnetic navigation method (IM-NN), and utilizes the adaptive cubature Kalman filter to integrate attitude information from geomagnetism and inertial sensors. A model was created utilizing a Long Short-Term Memory Network (LSTM) to represent the relationship between specific force, angular velocity, and integrated navigation attitude information. The dynamics were estimated based on current and previous Inertial Measurement Unit (IMU) data using IM-NN. This study demonstrated that the method effectively corrected inertial accumulation errors and mitigated geomagnetic disruption, resulting in a more accurate and dependable navigation solution in environments with geomagnetic rejection compared to conventional single inertial navigation methods.

Coseismic landslides have the potential to cause catastrophic disasters. Thus, it is of crucial importance to conduct a comprehensive regional assessment of susceptibility to coseismic landslides. This study rigorously interprets 13,759 coseismic landslides triggered by the 2022 Luding earthquake within the seismic zone. Employing the Newmark method, we systematically assess the susceptibility to coseismic landslides through the application of six distinct displacement regression models. The efficacy of these models is validated against the actual landslide inventory using the area under the receiver operating characteristic (ROC) curve. A hazard map of coseismic landslides is generated based on the displacement regression model with the highest degree of fit. The results show that Moxi Town, Detuo Town, the flanks of the Daduhe River, Wandonghe River, Hailuogou River, and Yanzigou River are high-susceptibility areas for coseismic landslides. This study explores factors influencing model fit, revealing that the inclusion of the epicentral distance and the distance to the seismogenic fault in displacement prediction enhances model performance. Nevertheless, in close proximity to fault zones, the distance to the seismogenic fault exerts a more significant influence on the spatial distribution density of coseismic landslides compared to the epicentral distance. Conversely, in regions situated further from fault zones, the epicentral distance has a greater impact on the spatial distribution density of coseismic landslides compared to the distance to the seismogenic fault. These findings contribute to a nuanced understanding of coseismic landslide susceptibility and offer valuable insights for future Newmark method-based coseismic landslide displacement calculations.

This study presents the Fast Fruit 3D Detector (FF3D), a novel framework that contains a 3D neural network for fruit detection and an anisotropic Gaussian-based next-best view estimator. The proposed one-stage 3D detector, which utilizes an end-to-end 3D detection network, shows superior accuracy and robustness compared to traditional 2D methods. The core of the FF3D is a 3D object detection network based on a 3D convolutional neural network (3D CNN) followed by an anisotropic Gaussian-based next-best view estimation module. The innovative architecture combines point cloud feature extraction and object detection tasks, achieving accurate real-time fruit localization. The model is trained on a large-scale 3D fruit dataset and contains data collected from an apple orchard. Additionally, the proposed next-best view estimator improves accuracy and lowers the collision risk for grasping. Thorough assessments on the test set and in a simulated environment validate the efficacy of our FF3D. The experimental results show an AP of 76.3%, an AR of 92.3%, and an average Euclidean distance error of less than 6.2 mm, highlighting the framework’s potential to overcome challenges in orchard environments.

BackgroundIonizing radiation can cause intestinal microecological dysbiosis, resulting in changes in the composition and function of gut microbiota. Altered gut microbiota is closely related to the development and progression of radiation-induced intestinal damage. Although microbiota-oriented therapeutic options such as fecal microbiota transplantation (FMT) have shown some efficacy in treating radiation toxicity, safety concerns endure. Therefore, fecal bacteria-free filtrate transplantation (FFT), which has the potential to become a possible alternative therapy, is well worth investigating. Herein, we performed FFT in a mouse model of radiation exposure and monitored its effects on radiation damage phenotypes, gut microbiota, and metabolomic profiles to assess the effectiveness of FFT as an alternative therapy to FMT safety concerns.ResultsFFT treatment conferred radioprotection against radiation-induced toxicity, representing as better intestinal integrity, robust proinflammatory and anti-inflammatory cytokines homeostasis, and accompanied by significant shifts in gut microbiome. The bacterial compartment of recipients following FFT was characterized by an enrichment of radioprotective microorganisms (members of family Lachnospiraceae). Furthermore, metabolome data revealed increased levels of microbially generated short-chain fatty acids (SCFAs) in the feces of FFT mice.ConclusionsFFT improves radiation-induced intestinal microecological dysbiosis by reshaping intestinal mucosal barrier function, gut microbiota configurations, and host metabolic profiles, highlighting FFT regimen as a promising safe alternative therapy for FMT is effective in the treatment of radiation intestinal injury.

We argue that information from countries who had earlier COVID-19 surges can be used to inform another country's current model, then generating what we call back-to-the-future (BTF) projections. We show that these projections can be used to accurately predict future COVID-19 surges prior to an inflection point of the daily infection curve. We show, across 12 different countries from all populated continents around the world, that our method can often predict future surges in scenarios where the traditional approaches would always predict no future surges. However, as expected, BTF projections cannot accurately predict a surge due to the emergence of a new variant. To generate BTF projections, we make use of a matching scheme for asynchronous time series combined with a response coaching SIR model.

Background: Previous study confirmed that both TaohongSiwu decoction (THSWD) and Dubosiella newyorkensis improved hypertension-induced endothelial dysfunction. However, the mechanism of THSWD combined with Dubosiella newyorkensis remains unclear. Purpos: e: We aimed to investigate the microecological mechanism underlying the THSWD combined with Dubosiella newyorkensis for the prevention of hypertensive vascular endothelial dysfunction. Methods: Eight percent high-salt diet was applied to induce hypertension in a mouse model for 4 weeks. THSWD, Dubosiella newyorkensis and THSWD combined with Dubosiella newyorkensis were used to intervene in the model mice to observe the changes of systolic blood pressure (SBP), body weight, blood routine, endothelial function, gut contents microbiota and bile acid metabolites. Results: Results revealed that THSWD combined with Dubosiella newyorkensis significantly restored blood pressure and regulated body weight, and markedly downregulating serum and vascular levels of endothelin-1 (ET-1), thrombin regulatory protein (TM), vascular hemophilia factor (vWF) and vascular endothelial growth factor (VEGF), and upregulating nitric oxide (NO) levels compared with the model group. Notably, It altered the diversity and community structure of gut contents microbiota in mice. Lactobacillus and Allobaculum was enormously up-regulated at the genus level. Serum bile acid differential metabolites cholic acid and chenodeoxycholic acid were markedly altered. Futhermore, there was a close relationship between Lactobacillus, Allobaculum and endothelial function indexes in mice. Conclusion: Lactobacillus and Allobaculum play important roles in the prevention of vascular endothelial dysfunction in hypertension during the THSWD combined with Dubosiella newyorkensis.

BackgroundUpper limb motor recovery is one of the important goals of stroke rehabilitation. Intermittent theta burst stimulation (iTBS), a new type of repetitive transcranial magnetic stimulation (rTMS), is considered a potential therapy. However, there is still no consensus on the efficacy of iTBS for upper limb motor dysfunction after stroke. Stimulus dose may be an important factor affecting the efficacy of iTBS. Therefore, we aim to investigate and compare the effects and neural mechanisms of three doses of iTBS on upper limb motor recovery in stroke patients, and our hypothesis is that the higher the dose of iTBS, the greater the improvement in upper limb motor function.MethodsThis prospective, randomized, controlled trial will recruit 56 stroke patients with upper limb motor dysfunction. All participants will be randomized in a 1:1:1:1 ratio to receive 21 sessions of 600 pulses active iTBS, 1,200 pulses active iTBS, 1,800 pulses active iTBS, or 1,800 pulses sham iTBS in addition to conventional rehabilitation training. The primary outcome is the Fugl-Meyer Assessment of the Upper Extremity (FMA-UE) score from baseline to end of intervention, and the secondary outcomes are the Wolf Motor Function Test (WMFT), Grip Strength (GS), Modified Barthel Index (MBI), and Stroke Impact Scale (SIS). The FMA-UE, MBI, and SIS are assessed pre-treatment, post-treatment, and at the 3-weeks follow-up. The WMFT, GS, and resting-state functional magnetic resonance imaging (rs-fMRI) data will be obtained pre- and post-treatment.DiscussionThe iTBS intervention in this study protocol is expected to be a potential method to promote upper limb motor recovery after stroke, and the results may provide supportive evidence for the optimal dose of iTBS intervention.

We propose and demonstrate a general method to calibrate the frequency-dependent response of self-compensating noble-gas–alkali-metal comagnetometers to arbitrary spin perturbations. This includes magnetic and nonmagnetic perturbations such as rotations and exotic spin interactions. The method is based on a fit of the magnetic field response to an analytical model. The frequency-dependent response of the comagnetometer to arbitrary spin perturbations can be inferred using the fit parameters. We demonstrate the effectiveness of this method by comparing the inferred rotation response to an experimental measurement of the rotation response. Our results show that experiments relying on zero-frequency calibration of the comagnetometer response can over- or underestimate the comagnetometer sensitivity by orders of magnitude over a wide frequency range. Moreover, this discrepancy accumulates over time as operational parameters tend to drift during comagnetometer operation. The demonstrated calibration protocol enables accurate prediction and control of comagnetometer sensitivity to, for example, ultralight bosonic dark-matter fields coupling to electron or nuclear spins, as well as accurate monitoring and control of the relevant system parameters.

Mine water disaster is closely related to the geological structure of the mine. A scientific evaluation of the complexity of the minefield structure can greatly contribute to mining safety. In this study, we optimized the fault impact index in the study area and proposed an improved local linear embedding (LLE) algorithm by investigating the Shengquan coal mine. We analyzed the fault formation age and connectivity between faults in the study area, combined with topology theory, and based on previous studies. The mechanical properties of faults and the influence of small faults on the strata can be combined to derive a quantitative evaluation model of the structural complexity of mines. Based on the evaluation model, the study area was divided into a simple structural area, a medium structural area, and a complex structural area. By comparing the location of water inrush points in recent years with the three-dimensional high-density electrical exploration of the 21,304 working face, the effectiveness and rationality of structural complexity zoning were determined.

With the rapid development of Internet of vehicles, 5G and artificial intelligence technologies, intelligent transportation has become the development trend of transportation technology.As a vehicle-vehicle and vehicle-road information interaction platform, the Internet of vehicles is the basic support platform for intelligent traffic information sharing and processing.At the same time, the security of Internet of vehicles has attracted much attention, especially data security which may cause user privacy leakage.The blockchain technology has become a solution, but it still faces new challenges in efficiency, security and other aspects.With the increase of vehicle nodes and information, how to efficiently achieve information consensus in high-speed vehicle moving environment has become a key problem.Then a bottom-up RSU (road side unit) chain consensus protocol was proposed based on blockchain and trust value.Several typical consensus structures were compared, and bottom-up two-layer consensus structure was adopted according to the actual scenarios of the Internet of vehicles.Moreover, a group leader node election algorithm was proposed which is based on node participation, work completion and message value.The system security was ensured by assigning trust value to each vehicle.Following the consensus structure and algorithm work mentioned above, the specific process of the protocol was comprehensively described, which was divided into six steps: region division, group leader node selection, local consensus, leader primary node selection, global consensus, and intra-domain broadcast.Then the experiments were analyzed from four aspects: security, communication complexity, consensus algorithm delay and fault tolerance rate.Experiments showed that, compared with other schemes, the proposed protocol can effectively reduce communication complexity and shorten consensus delay under the condition of resisting conspiracy attack, witch attack and other attacks.On the premise of security, the protocol improves fault tolerance rate and enables more nodes to participate in information sharing to satisfy the requirements of Internet of vehicles scenarios.

The functionalization of noble metals is an effective approach to lowering the sensing temperature and improving the sensitivity of metal oxide semiconductor (MOS)-based gas sensors. However, there is a dearth of comparative analyses regarding the differences in sensitization mechanisms between the two functionalization modes of noble metal loading and doping. In this investigation, we synthesized Pt-doped CuO gas-sensing materials using a one-pot hydrothermal method. And for Pt-loaded CuO, Pt was deposited on the synthesized pristine CuO surface by using a dipping method. We found that both functionalization methods can considerably enhance the response and selectivity of CuO toward NO2 at low temperatures. However, we observed that CuO with Pt loading had superior sensing performance at 25 °C, while CuO with Pt doping showed more substantial response changes with an increase in the operating temperature. This is mainly due to the different dominant roles of electron sensitization and chemical sensitization resulting from the different forms of Pt present in different functionalization modes. For Pt doping, electron sensitization is stronger, and for Pt loading, chemical sensitization is stronger. The results of this study present innovative ideas for understanding the optimization of noble metal functionalization for the gas-sensing performance of metal oxide semiconductors.

It has been shown that increased concentrations of zinc oxide nanoparticles (nano-ZnO) in the soil are harmful to plant growth. However, the sensitivity of different wheat cultivars to nano-ZnO stress is still unclear. To detect the physiological response process of wheat varieties with different tolerance to nano-ZnO stress, four wheat cultivars (viz., cv. TS1, ZM18, JM22, and LM6) with different responses to nano-ZnO stress were selected, depending on previous nano-ZnO stress trials with 120 wheat cultivars in China. The results found that nano-ZnO exposure reduced chlorophyll concentrations and photosynthetic electron transport efficiency, along with the depressed carbohydrate metabolism enzyme activities, and limited plant growth. Meanwhile, the genotypic variation in photosynthetic carbon assimilation under nano-ZnO stress was found in wheat plants. Wheat cv. JM22 and LM6 possessed relatively lower Zn concentrations and higher leaf nitrogen per area, less reductions in their net photosynthetic rate, a maximum quantum yield of the PS II (Fv/Fm), electron transport flux per cross-section (ETo/CSm), trapped energy flux per cross-section (TRo/CSm), and total soluble sugar and sucrose concentrations under nano-ZnO stress, showing a better tolerance to nano-ZnO stress than wheat cv. TS1 and ZM18. In addition, the chlorophyll a fluorescence parameters Fv/Fm, ETo/CSm, and TRo/CSm could be used to rapidly screen wheat varieties resistant to nano-ZnO stress. The results here provide a new approach for solving the issues of crop yield decline in regions polluted by heavy metal nanoparticles and promoting the sustainable utilization of farmland with heavy metal pollution.

Dapagliflozin, an inhibitor of sodium-glucose cotransporter 2 (SGLT2), is a new type of oral hypoglycemic drugs which can promote glucose excretion in the kidney. Studies have shown that dapagliflozin has renoprotective effect in the treatment of type 2 diabetes. However, the underlying mechanism remains unclear. Here, we combined integrated RNA sequencing and network pharmacology approach to investigate the molecular mechanism of dapagliflozin for diabetic nephropathy (DN). Dapagliflozin significantly relieved glucose intolerance, urinary albumin/creatinine ratio (UACR) and renal pathological injuries of db/db mice. The LncRNA and mRNA expression in kidney tissues from control group (CR), db/db group (DN) and dapagliflozin group (DG) were assessed by RNA sequencing. We identified 7 LncRNAs and 64 mRNAs common differentially expressed in CR vs DN and DN vs DG, which were used to construct co-expression network to reveal significantly correlated expression patterns in DN. In addition, network pharmacology was used to predict the therapeutic targets of dapagliflozin and we constructed component-target-pathway network according to the results of RNA sequencing and network pharmacology. We found that SMAD9, PPARG, CD36, CYP4A12A, CYP4A12B, CASP3, H2-DMB2, MAPK1, MAPK3, C3 and IL-10 might be the pivotal targets of dapagliflozin for treating DN and these genes were mainly enriched in pathways including TGF-β signaling pathway, PPAR signaling pathway, Chemokine signaling pathway, etc. Our results have important implication and provide novel insights into the protective mechanism of dapagliflozin for treating DN.

This paper introduces a new method of estimating the variation interval and the expected value of optimal economic operation cost for the energy hub (EH) model considering load and renewable energy uncertainties in the residential district. Firstly, renewable energy and load uncertainties are defined as uncertain sets of historical data. Due to dispatch factors, the traditional EH model is non-linear and difficult to calculate and analyze. In this paper, a multi-step modeling method is developed for the breakdown of a complex EH model (CEH) into several simple EH (SEH) models and variable substitutions in each SEH, to eliminate the non-linearity of CEH. The upper and lower bound of the operating costs are then obtained based on the duality theorem and the expected value is calculated by expected value model. Finally, the case study in Beijing residential district is carried out to confirm the efficiency of the proposed method.

The distribution characteristics and evolution law of rock mass fissures induced by mining are a key scientific issue in the study of deep rock mechanics. In this study, a series of uniaxial compression experiments was conducted on rock-like specimens containing double V-shaped prefabricated fissures at dip angles of α = β = 45°, α = 45°

Voltage sag is one of the most common power quality disturbance in industry, which causes huge inrush current and inrush torque of induction motors, and has serious impacts on the safe and stable operation of induction motor. To further study the detailed transient characteristics of induction motors during sag events, an improved 2-D multi-slice field-circuit-motion coupling time-stepping finite element method (FEM) is proposed. Then, taking a 5.5 kW, a 55 kW and a 135 kW induction motors as examples, the influence of phase-angle jumps and initial point-on-wave on the stator current peak, torque peak, speed loss and critical clearing time of the induction motor are discussed by using the proposed model. The simulation results show that stator current peak and torque peak increase obviously, while speed and critical clearing time decrease apparently, when considering the phase angle jump. And different initial points have little influence on these operation indicators. Finally, the proposed method is verified by comparing the measured and calculation data of the 5.5 kW three-phase squirrel-cage motor, respectively. The results show that the proposed method can reach higher precision with considering nonlinear characteristics.

Voltage sag is one of the most common power quality disturbances in industry, which causes huge inrush currents in stator windings of induction motors, and adversely impacts the motor secure operation. This paper firstly introduces a 2D Time-Stepping multi-slice finite element method (2D T-S multi-slice FEM) which is used for calculating the magnetic field distribution in induction motors under different sag events. Then the paper deduces the transient analytical expression of stator inrush current based on the classical theory of AC motors and presents a separation method for the positive, negative and zero sequence values based on instantaneous currents. With this method, the paper studies the influences of voltage sag amplitude, phase-angle jump and initial phase angle on the stator positive- and negative-sequence peak currents of 5.5 kW and 55 kW induction motors. This paper further proposes a motor protection method under voltage sag condition with the stator negative-sequence peak currents as the protection threshold, so that the protection false trip can be avoided effectively. Finally, the calculation and analysis results are validated by the comparison of calculated and measured stator peak value of the 5.5 kW induction motor.

ABSTRACT: During manufacturing and operation, different kinds of defects, e.g., delamination or surface cracks, may be generated in the plasma-facing components (PFCs) of a Tokamak device. To ensure the safety of the PFCs, various kinds of nondestructive testing (NDT) techniques are needed for different defect and failure mode. This paper gives a review of the recently developed ultrasonic testing (UT) and laser thermography methods for inspection of the delamination and surface cracks in PFCs. For monoblock W/Cu PFCs of divertor, the bonding quality at both W-Cu and Cu-CuCrZr interfaces was qualified by using UT with a focus probe during manufacturing. A noncontact, coupling-free and flexible ultrasonic scanning testing system with use of an electromagnetic acoustic transducer and a robotic inspection manipulator was introduced then for the in-vessel inspection of delamination defect in first wall (FW). A laser infrared thermography testing method is highlighted for the on-line inspection of delamination defect in FW through the vacuum vessel window of the Tokamak reactor. Finally, a new laser spot thermography method using laser spot array source was described for the online inspection of the surface cracks in FW. Keywords: Plasma-facing components, Ultrasonic testing, Laser thermography, Delamination, Surface crack

A three-step model for calculating the magnetic field generated by coils inside cuboid-shaped shields like magnetically shielded rooms (MSRs) is presented. The shield is modeled as two parallel plates of infinite width and one tube of infinite height. We propose an improved mirror method that considers the effect of the parallel plates of finite thickness. A reaction factor is introduced to describe the influence of the vertical tube, which is obtained from finite element method (FEM) simulations. By applying the improved mirror method and then multiplying the result with the reaction factor, the magnetic flux density within the shielded volume can be determined in a fast computation. The three-step model is verified with both FEM and measurements of the field of a Helmholtz coil inside an MSR with a superconducting quantum interference device. The model allows a fast optimization of shield-coupled coil spacings compared to repetitive, time-consuming FEM calculations. As an example, we optimize the distance between two parallel square coils attached to the MSR walls. Measurements of a coil prototype of 2.75 m side length show a magnetic field change of 18 pT over the central 5 cm at the field strength of 2.7 µT. This obtained relative field change of 6 ppm is a factor of 5.4 smaller than our previously used Helmholtz coil.

Voltage sag is one of the most common power quality disturbances in industry, which causes huge inrush current in the windings of induction motors, and adversely impacts the motor's secure operation. For better understanding of the operation and protection of induction motors, there is a need for a detailed research of the transient characteristics of induction motors during sag events. In this paper, we first proposed a novel 2-D multi-slice field-circuit-motion coupling time-stepping finite element method (2-D multi-slice FCM coupling T-S FEM) for calculating the transient performance of the induction motor with skewed rotor bars. In the proposed method, the equations of field, circuit, and motion are expressed in a nodal matrix and coupled together. Based on this method, we have analyzed the electromagnetic properties of a 5.5-kW induction motor with skewed rotor bars under symmetrical voltage sag conditions. Then, the influences of voltage sag's sag magnitude, phase-angle jump, and initial phase angle on the stator inrush peak currents of the 5.5 kW and a 55-kW induction motors is studied. Finally, the proposed method is compared with 3-D FEM, the traditional 2-D multi-slice FEM and the measured data. The results show that the proposed method can reduce the computation time significantly with high precision.

Accurate prediction of the water-bearing capacity of aquifers is crucial for protecting the surface ecological environment and ensuring safety during coal mining. In this study, a macro–micro combination was used to investigate the water-bearing capacity of bedrock aquifers. At the micro-level, the micro pore parameters of various sandstones were determined through cast sheeting. At the macro-level, the porosity and water absorption rate of various sandstones were determined experimentally. After that, a new index weighting method was proposed to comprehensively evaluate the water-bearing capacity index of sandstone. According to this method, the water-bearing capacity of aquifers in the Guojiahe coalmine were evaluated. The research results revealed that the water-bearing capacity of sandstone was mainly related to its pore connectivity, and the water-bearing capacity of sandstone in the Luo’he and Zhi’luo formation was considerably greater than that in the Yan’an formation. The water bearing capacity of strata in the eastern part of the mining area is lower than that in the western part of the mining area. The research results can provide considerable money savings for coal mining and protect the ecological environment and groundwater resources in the region.

By measuring the spin precession frequencies of polarized ^129 Xe and ^3 He, a new upper limit on the ^129 Xe atomic electric dipole moment (EDM) ${d}_{\text{A}}\left({}^{129}\mathrm{X}\mathrm{e}\right)$ was reported in Sachdev et al (2019 Phys. Rev. Lett. 123 , 143003). Here, we propose a new evaluation method based on global phase fitting (GPF) for analyzing the continuous phase development of the ^3 He– ^129 Xe comagnetometer signal. The Cramer–Rao lower bound on the ^129 Xe EDM for the GPF method is theoretically derived and shows the potential benefit of our new approach. The robustness of the GPF method is verified with Monte-Carlo studies. By optimizing the analysis parameters and adding data that could not be analyzed with the former method, we obtain a result of ${d}_{\text{A}}\left({}^{129}\mathrm{X}\mathrm{e}\right)=\left[1.1{\pm}3.6\enspace \left(\mathrm{s}\mathrm{t}\mathrm{a}\mathrm{t}\right){\pm}2.0\enspace \left(\mathrm{s}\mathrm{y}\mathrm{s}\mathrm{t}\right)\right]{\times}1{0}^{-28}\enspace \text{e}\enspace \mathrm{c}\mathrm{m}$ in an unblinded analysis. For the systematic uncertainty analyses, we adopted all methods from the aforementioned PRL publication except the comagnetometer phase drift, which can be omitted using the GPF method. The updated null result can be interpreted as a new upper limit of $\vert {d}_{\text{A}}\left({}^{129}\mathrm{X}\mathrm{e}\right)\vert {< }8.3\enspace {\times}1{0}^{-28}\enspace \text{e}\enspace \mathrm{c}\mathrm{m}$ at the 95% C.L.