This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou Ci...This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.展开更多
In this editorial,we comment on the article by Wang and Long,published in a recent issue of the World Journal of Clinical Cases.The article addresses the challenge of predicting intensive care unit-acquired weakness(I...In this editorial,we comment on the article by Wang and Long,published in a recent issue of the World Journal of Clinical Cases.The article addresses the challenge of predicting intensive care unit-acquired weakness(ICUAW),a neuromuscular disorder affecting critically ill patients,by employing a novel processing strategy based on repeated machine learning.The editorial presents a dataset comprising clinical,demographic,and laboratory variables from intensive care unit(ICU)patients and employs a multilayer perceptron neural network model to predict ICUAW.The authors also performed a feature importance analysis to identify the most relevant risk factors for ICUAW.This editorial contributes to the growing body of literature on predictive modeling in critical care,offering insights into the potential of machine learning approaches to improve patient outcomes and guide clinical decision-making in the ICU setting.展开更多
Intensive care unit-acquired weakness(ICU-AW)significantly hampers patient recovery and increases morbidity.With the absence of established preventive strategies,this study utilizes advanced machine learning methodolo...Intensive care unit-acquired weakness(ICU-AW)significantly hampers patient recovery and increases morbidity.With the absence of established preventive strategies,this study utilizes advanced machine learning methodologies to unearth key predictors of ICU-AW.Employing a sophisticated multilayer perceptron neural network,the research methodically assesses the predictive power for ICU-AW,pinpointing the length of ICU stay and duration of mechanical ventilation as pivotal risk factors.The findings advocate for minimizing these elements as a preventive approach,offering a novel perspective on combating ICU-AW.This research illuminates critical risk factors and lays the groundwork for future explorations into effective prevention and intervention strategies.展开更多
Upregulation of vascular endothelial growth factor A/basic fibroblast growth factor(VEGFA/b FGF)expression in the penumbra of cerebral ischemia can increase vascular volume,reduce lesion volume,and enhance neural cell...Upregulation of vascular endothelial growth factor A/basic fibroblast growth factor(VEGFA/b FGF)expression in the penumbra of cerebral ischemia can increase vascular volume,reduce lesion volume,and enhance neural cell proliferation and differentiation,thereby exerting neuroprotective effects.However,the beneficial effects of endogenous VEGFA/b FGF are limited as their expression is only transiently increased.In this study,we generated multilayered nanofiber membranes loaded with VEGFA/b FGF using layer-by-layer self-assembly and electrospinning techniques.We found that a membrane containing 10 layers had an ideal ultrastructure and could efficiently and stably release growth factors for more than 1 month.This 10-layered nanofiber membrane promoted brain microvascular endothelial cell tube formation and proliferation,inhibited neuronal apoptosis,upregulated the expression of tight junction proteins,and improved the viability of various cellular components of neurovascular units under conditions of oxygen/glucose deprivation.Furthermore,this nanofiber membrane decreased the expression of Janus kinase-2/signal transducer and activator of transcription-3(JAK2/STAT3),Bax/Bcl-2,and cleaved caspase-3.Therefore,this nanofiber membrane exhibits a neuroprotective effect on oxygen/glucose-deprived neurovascular units by inhibiting the JAK2/STAT3 pathway.展开更多
Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss pos...Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.展开更多
Artificial neural networks(ANN) have been extensively researched due to their significant energy-saving benefits.Hardware implementations of ANN with dropout function would be able to avoid the overfitting problem. Th...Artificial neural networks(ANN) have been extensively researched due to their significant energy-saving benefits.Hardware implementations of ANN with dropout function would be able to avoid the overfitting problem. This letter reports a dropout neuronal unit(1R1T-DNU) based on one memristor–one electrolyte-gated transistor with an ultralow energy consumption of 25 p J/spike. A dropout neural network is constructed based on such a device and has been verified by MNIST dataset, demonstrating high recognition accuracies(> 90%) within a large range of dropout probabilities up to40%. The running time can be reduced by increasing dropout probability without a significant loss in accuracy. Our results indicate the great potential of introducing such 1R1T-DNUs in full-hardware neural networks to enhance energy efficiency and to solve the overfitting problem.展开更多
This research proposes a novel nature-based design of a new concrete armour unit for the cover layer of a rubblemoundbreakwater. Armour units are versatile with respect to shape, orientation, surface condition details...This research proposes a novel nature-based design of a new concrete armour unit for the cover layer of a rubblemoundbreakwater. Armour units are versatile with respect to shape, orientation, surface condition details, and porosity.Therefore, a detailed analysis is required to investigate the exact state of their hydraulic interactions and structuralresponses. In this regard, the performance results of several traditional armour units, including the Antifer cube,Tetrapod, X-block and natural stone, are considered for the first step of this study. Then, the related observed resultsare compared with those obtained for a newly designed (artificial coral) armour unit. The research methodology utilizesthe common wave flume test procedure. Furthermore, several verified numerical models in OpenFOAM code areused to gain the extra required data. The proposed armour is configured to provide an effective shore protection as anenvironmental-friendly coastal structure. Thus it is designed with a main trunk including deep grooves to imitate thetypical geometry of a coral type configuration, so as to attain desirable performance. The observed results and ananalytic hierarchy process (AHP) concept are used to compare the hydraulic performance of the studied traditionaland newly proposed (artificial coral) armour units. The results indicate that the artificial coral armour unit demonstratesacceptable performance. The widely used traditional armour units might be replaced by newer designs for betterwave energy dissipation, and more importantly, for fewer adverse effects on the marine environment.展开更多
Corrosion leakages often occur in the air cooler of a hydrocracking unit,with the failure sites mainly located in the entrance area of the tubes.An analysis of the macroscopic morphology and corrosion products confirm...Corrosion leakages often occur in the air cooler of a hydrocracking unit,with the failure sites mainly located in the entrance area of the tubes.An analysis of the macroscopic morphology and corrosion products confirmed that the damage was caused by erosion-corrosion(E-C).Numerical and experimental methods were applied to investigate the E-C mechanism in the air cooler.Computational fluid dynamics(CFD)was used to calculate the hydrodynamic parameters of the air cooler.The results showed that there was a biased flow in the air cooler,which led to a significant increase in velocity,turbulent kinetic energy and wall shear within 0.2 m of the tube entrance.A visualization experiment was then performed to determine the principles of migration and transformation of multiphase flow in the air cooler tubes.Various flow patterns(pure droplet flow,mist flow,and annular flow)and their evolutionary processes were clearly depicted experimentally.The initiation mechanism and processes leading to the development of E-C in the air cooler were also determined.This study provided a comprehensive explanation for the E-C failures that occur in air coolers during operation.展开更多
The Nianzi granite unit,which includes the Nianzi,Xiaolianghou and Xiawopu granitic intrusions,is a significant component of the northern part of the North China Craton(NCC)and is situated in the Yanshan fold and thru...The Nianzi granite unit,which includes the Nianzi,Xiaolianghou and Xiawopu granitic intrusions,is a significant component of the northern part of the North China Craton(NCC)and is situated in the Yanshan fold and thrust belt(YFTB).However,there is still debate regarding the tectonic evolutionary history of the YFTB during the late Permian to Triassic period,specifically regarding the timing of subduction and collision between the NCC and the Paleo-Asian Ocean.The Nianzi granite unit exhibits unique petrological,geochronological and geochemical signatures that shed light on the tectonic evolutionary history of the YFTB.This study presents detailed petrology,whole-rock geochemistry,together with Sr-Nd isotopic,zircon U-Pb dating and Lu-Hf isotopic data of the granites within the Nianzi granite unit.Our findings demonstrate that the granites primarily consist of subhedral K-feldspar,plagioclase,quartz,minor biotite and hornblende,with accessory titanite,apatite,magnetite and zircon.Zircon U-Pb dating indicates that the Xiaolianghou granite was emplaced at 247.5±0.62 Ma.Additionally,the adakitic characteristics of the Nianzi,Xiawopu and Xiaolianghou granitic intrusions,such as high Sr and Ba contents and high ratios of Sr/Y and(La/Yb)N,combined with negative Sr-Nd and Lu-Hf isotopes(87Sr/86Sr)i=0.705681–0.7057433,εNd(t)=−21.98 to−20.97,zirconεHf(t)=−20.26 to−9.92,as well as the I-type granite features of high SiO_(2),Na_(2)O and K_(2)O/Na_(2)O ratios,enriched Rb,K,Sr and Ba,along with depleted Th,U,Nb,Ta,P and Ti,suggest that the Nianzi granitic unit was mainly derived from the partial melting of a thickened lower crust containing hydrous,calc-alkaline to high-K calc-alkaline,mafic to intermediate metamorphic rocks.In light of these parameters,we further integrate our data with previous studies and conclude that the Nianzi granitic unit was generated in a post-collisional extensional environment during the Early Triassic.展开更多
Galloping cheetahs,climbing mountain goats,and load hauling horses all show desirable locomotion capability,which motivates the development of quadruped robots.Among various quadruped robots,hydraulically driven quadr...Galloping cheetahs,climbing mountain goats,and load hauling horses all show desirable locomotion capability,which motivates the development of quadruped robots.Among various quadruped robots,hydraulically driven quadruped robots show great potential in unstructured environments due to their discrete landing positions and large payloads.As the most critical movement unit of a quadruped robot,the limb leg unit(LLU)directly affects movement speed and reliability,and requires a compact and lightweight design.Inspired by the dexterous skeleton–muscle systems of cheetahs and humans,this paper proposes a highly integrated bionic actuator system for a better dynamic performance of an LLU.We propose that a cylinder barrel with multiple element interfaces and internal smooth channels is realized using metal additive manufacturing,and hybrid lattice structures are introduced into the lightweight design of the piston rod.In addition,additive manufacturing and topology optimization are incorporated to reduce the redundant material of the structural parts of the LLU.The mechanical properties of the actuator system are verified by numerical simulation and experiments,and the power density of the actuators is far greater than that of cheetah muscle.The mass of the optimized LLU is reduced by 24.5%,and the optimized LLU shows better response time performance when given a step signal,and presents a good trajectory tracking ability with the increase in motion frequency.展开更多
The neurovascular unit and stem cell therapy in ischemic stroke:Ischemic stroke,accounts for approximately 85% of all stroke incidents and is a major global health burden.It is the leading cause of disability and deat...The neurovascular unit and stem cell therapy in ischemic stroke:Ischemic stroke,accounts for approximately 85% of all stroke incidents and is a major global health burden.It is the leading cause of disability and death worldwide,posing immense societal and economic challenges due to the long-term care required for stro ke survivors and the significant healthcare costs associated with its treatment and management(Amarenco et al.,2009).展开更多
In this paper,we investigate sufficient and necessary conditions such that generalized Forelli-Rudin type operators T_(λ,τ,k),S_(λ,τ,k),Q_(λ,τ,k)and R_(λ,τ,k)are bounded between Lebesgue type spaces.In order t...In this paper,we investigate sufficient and necessary conditions such that generalized Forelli-Rudin type operators T_(λ,τ,k),S_(λ,τ,k),Q_(λ,τ,k)and R_(λ,τ,k)are bounded between Lebesgue type spaces.In order to prove the main results,we first give some bidirectional estimates for several typical integrals.展开更多
Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to spe...Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical behaviors.In this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error an-alyses.The GRU model showed the proper trends,and the model data ranges were wider than previous ones.The GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other models.The GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,respectively.The group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.展开更多
Beyond-5G(B5G)aims to meet the growing demands of mobile traffic and expand the communication space.Considering that intelligent applications to B5G wireless communications will involve security issues regarding user ...Beyond-5G(B5G)aims to meet the growing demands of mobile traffic and expand the communication space.Considering that intelligent applications to B5G wireless communications will involve security issues regarding user data and operational data,this paper analyzes the maximum capacity of the multi-watermarking method for multimedia signal hiding as a means of alleviating the information security problem of B5G.The multiwatermarking process employs spread transform dither modulation.During the watermarking procedure,Gram-Schmidt orthogonalization is used to obtain the multiple spreading vectors.Consequently,multiple watermarks can be simultaneously embedded into the same position of a multimedia signal.Moreover,the multiple watermarks can be extracted without affecting one another during the extraction process.We analyze the effect of the size of the spreading vector on the unit maximum capacity,and consequently derive the theoretical relationship between the size of the spreading vector and the unit maximum capacity.A number of experiments are conducted to determine the optimal parameter values for maximum robustness on the premise of high capacity and good imperceptibility.展开更多
Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenario...Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios,which threatens the robustness of stochastic unit commitment and hinders its application. This paper providesa stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming andBenders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouplesthe primal problem into the master problem and two types of subproblems. In the master problem, the committedgenerator is determined, while the feasibility and optimality of generator output are checked in these twosubproblems. Scenarios are dynamically clustered during the subproblem solution process through the multiparametric programming with respect to the solution of the master problem. In other words, multiple scenariosare clustered into several representative scenarios after the subproblem is solved, and the Benders cut obtainedby the representative scenario is generated for the master problem. Different from the conventional stochasticunit commitment, the proposed approach integrates scenario clustering into the Benders decomposition solutionprocess. Such a clustering approach could accurately cluster representative scenarios that have impacts on theunit commitment. The proposed method is tested on a 6-bus system and the modified IEEE 118-bus system.Numerical results illustrate the effectiveness of the proposed method in clustering scenarios. Compared withthe conventional clustering method, the proposed method can accurately select representative scenarios whilemitigating computational burden, thus guaranteeing the robustness of unit commitment.展开更多
Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties ...Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features.Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.展开更多
BACKGROUND Wilson disease(WD)is a progressive,potentially fatal degenerative disease affecting the liver and central nervous system.Given its low prevalence,collecting data on large cohorts of patients with WD is chal...BACKGROUND Wilson disease(WD)is a progressive,potentially fatal degenerative disease affecting the liver and central nervous system.Given its low prevalence,collecting data on large cohorts of patients with WD is challenging.Comprehensive insur-ance claims databases provide powerful tools to collect retrospective data on large numbers of patients with rare diseases.AIM To describe patients with WD in the United States,their treatment and clinical outcome,using a large insurance claims database.METHODS This retrospective,longitudinal study was performed in the Clarivate Real-World Data Product database.All patients with≥2 claims associated with an Interna-tional Classification of Diseases 10(ICD-10)diagnostic code for WD(E83.01)between 2016 and 2021 were included and followed until death or study end.Patients were divided into two groups by whether or not they were documented to have received a specific treatment for WD.Clinical manifestations,hospital-isations,liver transplantation and death were documented.RESULTS Overall,5376 patients with an ICD-10 diagnostic code for WD were identified.The mean age at inclusion was 41.2 years and 52.0%were men.A specific WD treatment was documented for 885 patients(15.1%),although the number of patients taking zinc salts may be underestimated due to over the counter purchase.At inclusion,the mean age of patients with a documented treatment was 36.6±17.8 years vs 42.2±19.6 years in those without a documented treatment.During follow-up,273 patients(5.1%)died.Compared with the American general population,the standardised mortality ratio was 2.19.The proportion of patients with a documented WD-specific treatment who died during follow-up was 4.0%and the mean age at death 52.7 years.CONCLUSION Patients treated for WD in the United States had an excess early mortality compared with the American population.These findings indicate that there is a significant unmet need for effective treatment for WD in the United States.展开更多
BACKGROUND Liver cirrhosis patients admitted to intensive care unit(ICU)have a high mortality rate.AIM To establish and validate a nomogram for predicting in-hospital mortality of ICU patients with liver cirrhosis.MET...BACKGROUND Liver cirrhosis patients admitted to intensive care unit(ICU)have a high mortality rate.AIM To establish and validate a nomogram for predicting in-hospital mortality of ICU patients with liver cirrhosis.METHODS We extracted demographic,etiological,vital sign,laboratory test,comorbidity,complication,treatment,and severity score data of liver cirrhosis patients from the Medical Information Mart for Intensive Care IV(MIMIC-IV)and electronic ICU(eICU)collaborative research database(eICU-CRD).Predictor selection and model building were based on the MIMIC-IV dataset.The variables selected through least absolute shrinkage and selection operator analysis were further screened through multivariate regression analysis to obtain final predictors.The final predictors were included in the multivariate logistic regression model,which was used to construct a nomogram.Finally,we conducted external validation using the eICU-CRD.The area under the receiver operating characteristic curve(AUC),decision curve,and calibration curve were used to assess the efficacy of the models.RESULTS Risk factors,including the mean respiratory rate,mean systolic blood pressure,mean heart rate,white blood cells,international normalized ratio,total bilirubin,age,invasive ventilation,vasopressor use,maximum stage of acute kidney injury,and sequential organ failure assessment score,were included in the multivariate logistic regression.The model achieved AUCs of 0.864 and 0.808 in the MIMIC-IV and eICU-CRD databases,respectively.The calibration curve also confirmed the predictive ability of the model,while the decision curve confirmed its clinical value.CONCLUSION The nomogram has high accuracy in predicting in-hospital mortality.Improving the included predictors may help improve the prognosis of patients.展开更多
BACKGROUND Nutritional support for patients hospitalized in the intensive care unit(ICU)is an important part of clinical treatment and care,but there are significant implementation difficulties.AIM To introduce a modi...BACKGROUND Nutritional support for patients hospitalized in the intensive care unit(ICU)is an important part of clinical treatment and care,but there are significant implementation difficulties.AIM To introduce a modified nutritional support management system for ICU patients based on closed-loop information management and psychological counseling.METHODS The division of functions,personnel training,system construction,development of an intelligent decision-making software system,quality control,and improvement of the whole process were carried out to systematically manage nutritional support for ICU patients.RESULTS Following the implementation of the whole process management system,the scores of ICU medical staff’s knowledge,attitudes/beliefs,and practices regarding nutritional support were comprehensively enhanced.The proportion of hospital bed-days of total enteral nutrition(EN)in ICU patients increased from 5.58%to 11.46%,and the proportion of EN plus parenteral nutrition increased from 42.71%to 47.07%.The rate of EN initiation within 48 h of ICU admission increased from 37.50%to 48.28%,and the EN compliance rate within 72 h elevated from 20.59%to 31.72%.After the implementation of the project,the Self-rating Anxiety Scale score decreased from 61.07±9.91 points to 52.03±9.02 points,the Self-rating Depression Scale score reduced from 62.47±10.50 points to 56.34±9.83 points,and the ICU stay decreased from 5.76±2.77 d to 5.10±2.12 d.CONCLUSION The nutritional support management system based on closed-loop information management and psychological counseling achieved remarkable results in clinical applications in ICU patients.展开更多
基金the Natural Science Foundation of China(41807285)Interdisciplinary Innovation Fund of Natural Science,NanChang University(9167-28220007-YB2107).
文摘This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.
文摘In this editorial,we comment on the article by Wang and Long,published in a recent issue of the World Journal of Clinical Cases.The article addresses the challenge of predicting intensive care unit-acquired weakness(ICUAW),a neuromuscular disorder affecting critically ill patients,by employing a novel processing strategy based on repeated machine learning.The editorial presents a dataset comprising clinical,demographic,and laboratory variables from intensive care unit(ICU)patients and employs a multilayer perceptron neural network model to predict ICUAW.The authors also performed a feature importance analysis to identify the most relevant risk factors for ICUAW.This editorial contributes to the growing body of literature on predictive modeling in critical care,offering insights into the potential of machine learning approaches to improve patient outcomes and guide clinical decision-making in the ICU setting.
文摘Intensive care unit-acquired weakness(ICU-AW)significantly hampers patient recovery and increases morbidity.With the absence of established preventive strategies,this study utilizes advanced machine learning methodologies to unearth key predictors of ICU-AW.Employing a sophisticated multilayer perceptron neural network,the research methodically assesses the predictive power for ICU-AW,pinpointing the length of ICU stay and duration of mechanical ventilation as pivotal risk factors.The findings advocate for minimizing these elements as a preventive approach,offering a novel perspective on combating ICU-AW.This research illuminates critical risk factors and lays the groundwork for future explorations into effective prevention and intervention strategies.
基金supported by the National Natural Science Foundation of China,Nos.81974207(to JH),82001383(to DW)the Special Clinical Research Project of Health Profession of Shanghai Municipal Health Commission,No.20204Y0076(to DW)。
文摘Upregulation of vascular endothelial growth factor A/basic fibroblast growth factor(VEGFA/b FGF)expression in the penumbra of cerebral ischemia can increase vascular volume,reduce lesion volume,and enhance neural cell proliferation and differentiation,thereby exerting neuroprotective effects.However,the beneficial effects of endogenous VEGFA/b FGF are limited as their expression is only transiently increased.In this study,we generated multilayered nanofiber membranes loaded with VEGFA/b FGF using layer-by-layer self-assembly and electrospinning techniques.We found that a membrane containing 10 layers had an ideal ultrastructure and could efficiently and stably release growth factors for more than 1 month.This 10-layered nanofiber membrane promoted brain microvascular endothelial cell tube formation and proliferation,inhibited neuronal apoptosis,upregulated the expression of tight junction proteins,and improved the viability of various cellular components of neurovascular units under conditions of oxygen/glucose deprivation.Furthermore,this nanofiber membrane decreased the expression of Janus kinase-2/signal transducer and activator of transcription-3(JAK2/STAT3),Bax/Bcl-2,and cleaved caspase-3.Therefore,this nanofiber membrane exhibits a neuroprotective effect on oxygen/glucose-deprived neurovascular units by inhibiting the JAK2/STAT3 pathway.
文摘Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.
基金Project supported by the National Key Research and Development Program of China (Grant Nos. 2021YFA1202600 and 2023YFE0208600)in part by the National Natural Science Foundation of China (Grant Nos. 62174082, 92364106, 61921005, 92364204, and 62074075)。
文摘Artificial neural networks(ANN) have been extensively researched due to their significant energy-saving benefits.Hardware implementations of ANN with dropout function would be able to avoid the overfitting problem. This letter reports a dropout neuronal unit(1R1T-DNU) based on one memristor–one electrolyte-gated transistor with an ultralow energy consumption of 25 p J/spike. A dropout neural network is constructed based on such a device and has been verified by MNIST dataset, demonstrating high recognition accuracies(> 90%) within a large range of dropout probabilities up to40%. The running time can be reduced by increasing dropout probability without a significant loss in accuracy. Our results indicate the great potential of introducing such 1R1T-DNUs in full-hardware neural networks to enhance energy efficiency and to solve the overfitting problem.
文摘This research proposes a novel nature-based design of a new concrete armour unit for the cover layer of a rubblemoundbreakwater. Armour units are versatile with respect to shape, orientation, surface condition details, and porosity.Therefore, a detailed analysis is required to investigate the exact state of their hydraulic interactions and structuralresponses. In this regard, the performance results of several traditional armour units, including the Antifer cube,Tetrapod, X-block and natural stone, are considered for the first step of this study. Then, the related observed resultsare compared with those obtained for a newly designed (artificial coral) armour unit. The research methodology utilizesthe common wave flume test procedure. Furthermore, several verified numerical models in OpenFOAM code areused to gain the extra required data. The proposed armour is configured to provide an effective shore protection as anenvironmental-friendly coastal structure. Thus it is designed with a main trunk including deep grooves to imitate thetypical geometry of a coral type configuration, so as to attain desirable performance. The observed results and ananalytic hierarchy process (AHP) concept are used to compare the hydraulic performance of the studied traditionaland newly proposed (artificial coral) armour units. The results indicate that the artificial coral armour unit demonstratesacceptable performance. The widely used traditional armour units might be replaced by newer designs for betterwave energy dissipation, and more importantly, for fewer adverse effects on the marine environment.
基金supported by the National Key R&D Program of China(2021YFB3301100)Beijing University of Chemical Technology Interdisciplinary Program(XK2023-07).
文摘Corrosion leakages often occur in the air cooler of a hydrocracking unit,with the failure sites mainly located in the entrance area of the tubes.An analysis of the macroscopic morphology and corrosion products confirmed that the damage was caused by erosion-corrosion(E-C).Numerical and experimental methods were applied to investigate the E-C mechanism in the air cooler.Computational fluid dynamics(CFD)was used to calculate the hydrodynamic parameters of the air cooler.The results showed that there was a biased flow in the air cooler,which led to a significant increase in velocity,turbulent kinetic energy and wall shear within 0.2 m of the tube entrance.A visualization experiment was then performed to determine the principles of migration and transformation of multiphase flow in the air cooler tubes.Various flow patterns(pure droplet flow,mist flow,and annular flow)and their evolutionary processes were clearly depicted experimentally.The initiation mechanism and processes leading to the development of E-C in the air cooler were also determined.This study provided a comprehensive explanation for the E-C failures that occur in air coolers during operation.
基金funded by the National Natural Science Foundation of China(41872232)the Beijing Geological Survey Project(PXM 2016-158203-000008,PXM 2018-158203-000014)the Beijing Innovation Studio(Urban Geology,Active Structure,and Monitoring).
文摘The Nianzi granite unit,which includes the Nianzi,Xiaolianghou and Xiawopu granitic intrusions,is a significant component of the northern part of the North China Craton(NCC)and is situated in the Yanshan fold and thrust belt(YFTB).However,there is still debate regarding the tectonic evolutionary history of the YFTB during the late Permian to Triassic period,specifically regarding the timing of subduction and collision between the NCC and the Paleo-Asian Ocean.The Nianzi granite unit exhibits unique petrological,geochronological and geochemical signatures that shed light on the tectonic evolutionary history of the YFTB.This study presents detailed petrology,whole-rock geochemistry,together with Sr-Nd isotopic,zircon U-Pb dating and Lu-Hf isotopic data of the granites within the Nianzi granite unit.Our findings demonstrate that the granites primarily consist of subhedral K-feldspar,plagioclase,quartz,minor biotite and hornblende,with accessory titanite,apatite,magnetite and zircon.Zircon U-Pb dating indicates that the Xiaolianghou granite was emplaced at 247.5±0.62 Ma.Additionally,the adakitic characteristics of the Nianzi,Xiawopu and Xiaolianghou granitic intrusions,such as high Sr and Ba contents and high ratios of Sr/Y and(La/Yb)N,combined with negative Sr-Nd and Lu-Hf isotopes(87Sr/86Sr)i=0.705681–0.7057433,εNd(t)=−21.98 to−20.97,zirconεHf(t)=−20.26 to−9.92,as well as the I-type granite features of high SiO_(2),Na_(2)O and K_(2)O/Na_(2)O ratios,enriched Rb,K,Sr and Ba,along with depleted Th,U,Nb,Ta,P and Ti,suggest that the Nianzi granitic unit was mainly derived from the partial melting of a thickened lower crust containing hydrous,calc-alkaline to high-K calc-alkaline,mafic to intermediate metamorphic rocks.In light of these parameters,we further integrate our data with previous studies and conclude that the Nianzi granitic unit was generated in a post-collisional extensional environment during the Early Triassic.
基金The work is supported by the National Natural Science Foundation of China(Nos.U21A20124 and 52205059)the Key Research and Development Program of Zhejiang Province(No.2022C01039)。
文摘Galloping cheetahs,climbing mountain goats,and load hauling horses all show desirable locomotion capability,which motivates the development of quadruped robots.Among various quadruped robots,hydraulically driven quadruped robots show great potential in unstructured environments due to their discrete landing positions and large payloads.As the most critical movement unit of a quadruped robot,the limb leg unit(LLU)directly affects movement speed and reliability,and requires a compact and lightweight design.Inspired by the dexterous skeleton–muscle systems of cheetahs and humans,this paper proposes a highly integrated bionic actuator system for a better dynamic performance of an LLU.We propose that a cylinder barrel with multiple element interfaces and internal smooth channels is realized using metal additive manufacturing,and hybrid lattice structures are introduced into the lightweight design of the piston rod.In addition,additive manufacturing and topology optimization are incorporated to reduce the redundant material of the structural parts of the LLU.The mechanical properties of the actuator system are verified by numerical simulation and experiments,and the power density of the actuators is far greater than that of cheetah muscle.The mass of the optimized LLU is reduced by 24.5%,and the optimized LLU shows better response time performance when given a step signal,and presents a good trajectory tracking ability with the increase in motion frequency.
基金supported by the NIH National Cancer Institute career development award(K25CA201545,to WL)。
文摘The neurovascular unit and stem cell therapy in ischemic stroke:Ischemic stroke,accounts for approximately 85% of all stroke incidents and is a major global health burden.It is the leading cause of disability and death worldwide,posing immense societal and economic challenges due to the long-term care required for stro ke survivors and the significant healthcare costs associated with its treatment and management(Amarenco et al.,2009).
基金supported by the Natural Science Foundation of Hunan Province of China(2022JJ30369)the Education Department Important Foundation of Hunan Province in China(23A0095)。
文摘In this paper,we investigate sufficient and necessary conditions such that generalized Forelli-Rudin type operators T_(λ,τ,k),S_(λ,τ,k),Q_(λ,τ,k)and R_(λ,τ,k)are bounded between Lebesgue type spaces.In order to prove the main results,we first give some bidirectional estimates for several typical integrals.
基金The authors thank the Yayasan Universiti Teknologi PETRONAS(YUTP FRG Grant No.015LC0-428)at Universiti Teknologi PETRO-NAS for supporting this study.
文摘Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical behaviors.In this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error an-alyses.The GRU model showed the proper trends,and the model data ranges were wider than previous ones.The GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other models.The GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,respectively.The group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.
基金funded by The National Natural Science Foundation of China under Grant(No.62273108,62306081)The Youth Project of Guangdong Artificial Intelligence and Digital Economy Laboratory(Guangzhou)(PZL2022KF0006)+3 种基金The National Key Research and Development Program of China(2022YFB3604502)Special Fund Project of GuangzhouScience and Technology Innovation Development(202201011307)Guangdong Province Industrial Internet Identity Analysis and Construction Guidance Fund Secondary Node Project(1746312)Special Projects in Key Fields of General Colleges and Universities in Guangdong Province(2021ZDZX1016).
文摘Beyond-5G(B5G)aims to meet the growing demands of mobile traffic and expand the communication space.Considering that intelligent applications to B5G wireless communications will involve security issues regarding user data and operational data,this paper analyzes the maximum capacity of the multi-watermarking method for multimedia signal hiding as a means of alleviating the information security problem of B5G.The multiwatermarking process employs spread transform dither modulation.During the watermarking procedure,Gram-Schmidt orthogonalization is used to obtain the multiple spreading vectors.Consequently,multiple watermarks can be simultaneously embedded into the same position of a multimedia signal.Moreover,the multiple watermarks can be extracted without affecting one another during the extraction process.We analyze the effect of the size of the spreading vector on the unit maximum capacity,and consequently derive the theoretical relationship between the size of the spreading vector and the unit maximum capacity.A number of experiments are conducted to determine the optimal parameter values for maximum robustness on the premise of high capacity and good imperceptibility.
基金the Science and Technology Project of State Grid Corporation of China,Grant Number 5108-202304065A-1-1-ZN.
文摘Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios,which threatens the robustness of stochastic unit commitment and hinders its application. This paper providesa stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming andBenders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouplesthe primal problem into the master problem and two types of subproblems. In the master problem, the committedgenerator is determined, while the feasibility and optimality of generator output are checked in these twosubproblems. Scenarios are dynamically clustered during the subproblem solution process through the multiparametric programming with respect to the solution of the master problem. In other words, multiple scenariosare clustered into several representative scenarios after the subproblem is solved, and the Benders cut obtainedby the representative scenario is generated for the master problem. Different from the conventional stochasticunit commitment, the proposed approach integrates scenario clustering into the Benders decomposition solutionprocess. Such a clustering approach could accurately cluster representative scenarios that have impacts on theunit commitment. The proposed method is tested on a 6-bus system and the modified IEEE 118-bus system.Numerical results illustrate the effectiveness of the proposed method in clustering scenarios. Compared withthe conventional clustering method, the proposed method can accurately select representative scenarios whilemitigating computational burden, thus guaranteeing the robustness of unit commitment.
基金supported by the National Natural Science Foundation of China (6202201562088101)+1 种基金Shanghai Municipal Science and Technology Major Project (2021SHZDZX0100)Shanghai Municip al Commission of Science and Technology Project (19511132101)。
文摘Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features.Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.
文摘BACKGROUND Wilson disease(WD)is a progressive,potentially fatal degenerative disease affecting the liver and central nervous system.Given its low prevalence,collecting data on large cohorts of patients with WD is challenging.Comprehensive insur-ance claims databases provide powerful tools to collect retrospective data on large numbers of patients with rare diseases.AIM To describe patients with WD in the United States,their treatment and clinical outcome,using a large insurance claims database.METHODS This retrospective,longitudinal study was performed in the Clarivate Real-World Data Product database.All patients with≥2 claims associated with an Interna-tional Classification of Diseases 10(ICD-10)diagnostic code for WD(E83.01)between 2016 and 2021 were included and followed until death or study end.Patients were divided into two groups by whether or not they were documented to have received a specific treatment for WD.Clinical manifestations,hospital-isations,liver transplantation and death were documented.RESULTS Overall,5376 patients with an ICD-10 diagnostic code for WD were identified.The mean age at inclusion was 41.2 years and 52.0%were men.A specific WD treatment was documented for 885 patients(15.1%),although the number of patients taking zinc salts may be underestimated due to over the counter purchase.At inclusion,the mean age of patients with a documented treatment was 36.6±17.8 years vs 42.2±19.6 years in those without a documented treatment.During follow-up,273 patients(5.1%)died.Compared with the American general population,the standardised mortality ratio was 2.19.The proportion of patients with a documented WD-specific treatment who died during follow-up was 4.0%and the mean age at death 52.7 years.CONCLUSION Patients treated for WD in the United States had an excess early mortality compared with the American population.These findings indicate that there is a significant unmet need for effective treatment for WD in the United States.
基金Supported by Natural Science Foundation of Sichuan Province,No.2022NSFSC1378.
文摘BACKGROUND Liver cirrhosis patients admitted to intensive care unit(ICU)have a high mortality rate.AIM To establish and validate a nomogram for predicting in-hospital mortality of ICU patients with liver cirrhosis.METHODS We extracted demographic,etiological,vital sign,laboratory test,comorbidity,complication,treatment,and severity score data of liver cirrhosis patients from the Medical Information Mart for Intensive Care IV(MIMIC-IV)and electronic ICU(eICU)collaborative research database(eICU-CRD).Predictor selection and model building were based on the MIMIC-IV dataset.The variables selected through least absolute shrinkage and selection operator analysis were further screened through multivariate regression analysis to obtain final predictors.The final predictors were included in the multivariate logistic regression model,which was used to construct a nomogram.Finally,we conducted external validation using the eICU-CRD.The area under the receiver operating characteristic curve(AUC),decision curve,and calibration curve were used to assess the efficacy of the models.RESULTS Risk factors,including the mean respiratory rate,mean systolic blood pressure,mean heart rate,white blood cells,international normalized ratio,total bilirubin,age,invasive ventilation,vasopressor use,maximum stage of acute kidney injury,and sequential organ failure assessment score,were included in the multivariate logistic regression.The model achieved AUCs of 0.864 and 0.808 in the MIMIC-IV and eICU-CRD databases,respectively.The calibration curve also confirmed the predictive ability of the model,while the decision curve confirmed its clinical value.CONCLUSION The nomogram has high accuracy in predicting in-hospital mortality.Improving the included predictors may help improve the prognosis of patients.
基金Supported by Research Project of Zhejiang Provincial Department of Education,No.Y202045115.
文摘BACKGROUND Nutritional support for patients hospitalized in the intensive care unit(ICU)is an important part of clinical treatment and care,but there are significant implementation difficulties.AIM To introduce a modified nutritional support management system for ICU patients based on closed-loop information management and psychological counseling.METHODS The division of functions,personnel training,system construction,development of an intelligent decision-making software system,quality control,and improvement of the whole process were carried out to systematically manage nutritional support for ICU patients.RESULTS Following the implementation of the whole process management system,the scores of ICU medical staff’s knowledge,attitudes/beliefs,and practices regarding nutritional support were comprehensively enhanced.The proportion of hospital bed-days of total enteral nutrition(EN)in ICU patients increased from 5.58%to 11.46%,and the proportion of EN plus parenteral nutrition increased from 42.71%to 47.07%.The rate of EN initiation within 48 h of ICU admission increased from 37.50%to 48.28%,and the EN compliance rate within 72 h elevated from 20.59%to 31.72%.After the implementation of the project,the Self-rating Anxiety Scale score decreased from 61.07±9.91 points to 52.03±9.02 points,the Self-rating Depression Scale score reduced from 62.47±10.50 points to 56.34±9.83 points,and the ICU stay decreased from 5.76±2.77 d to 5.10±2.12 d.CONCLUSION The nutritional support management system based on closed-loop information management and psychological counseling achieved remarkable results in clinical applications in ICU patients.