Air traffic flow management has been a major means for balancing air traffic demandand airport or airspace capacity to reduce congestion and flight delays.However,unpredictable fac-tors,such as weather and equipment m...Air traffic flow management has been a major means for balancing air traffic demandand airport or airspace capacity to reduce congestion and flight delays.However,unpredictable fac-tors,such as weather and equipment malfunctions,can cause dynamic changes in airport and sectorcapacity,resulting in significant alterations to optimized flight schedules and the calculated pre-departure slots.Therefore,taking into account capacity uncertainties is essential to create a moreresilient flight schedule.This paper addresses the flight pre-departure sequencing issue and intro-duces a capacity uncertainty model for optimizing flight schedule at the airport network level.The goal of the model is to reduce the total cost of flight delays while increasing the robustnessof the optimized schedule.A chance-constrained model is developed to address the capacity uncer-tainty of airports and sectors,and the significance of airports and sectors in the airport network isconsidered when setting the violation probability.The performance of the model is evaluated usingreal flight data by comparing them with the results of the deterministic model.The development ofthe model based on the characteristics of this special optimization mechanism can significantlyenhance its performance in addressing the pre-departure flight scheduling problem at the airportnetwork level.展开更多
This paper focuses on the optimization of the evaluation index system for the value of transportation infrastructure assets.It analyzes the shortcomings of the current system and explores the directions for optimizing...This paper focuses on the optimization of the evaluation index system for the value of transportation infrastructure assets.It analyzes the shortcomings of the current system and explores the directions for optimizing the index system from the perspectives of functionality,economy,social impact,environmental impact,and sustainability.The paper also discusses the application of the optimized index system in practical evaluation and the measures to ensure its effectiveness.The research aims to enhance the evaluation mechanism for the value of transportation infrastructure assets,providing a more scientific basis for decision-making,addressing challenges in asset management,improving the level of asset management in transportation infrastructure,and meeting the demands of high-quality development in the transportation sector in the new era.展开更多
The development of artificial intelligence has brought tremendous changes to enterprises and also pose higher demands on financial professionals.Through literature research,this paper explores the viewpoints of domest...The development of artificial intelligence has brought tremendous changes to enterprises and also pose higher demands on financial professionals.Through literature research,this paper explores the viewpoints of domestic and foreign scholars and industry experts on the impact of Artificial Intelligence(AI)on corporate financial management and the role transformation of financial professionals.It analyzes the current application status of AI technology in finance.The results indicate that AI will replace some repetitive and highly procedural tasks,such as simple data entry and bookkeeping.AI can improve the processing speed and accuracy of corporate financial data.With its learning capabilities,AI can assist financial professionals in addressing knowledge gaps.However,AI cannot completely replace human thinking,judgment,and decision-making,especially in areas like emotional communication and aesthetic experience.This requires financial professionals to continuously improve their overall qualities,leverage their strengths,and achieve complementary advantages with machines,jointly promoting innovative financial development in the era of artificial intelligence.展开更多
BACKGROUND Cardiovascular(CV)complications are common in intensive care unit(ICU)patients after gastrointestinal surgery and are associated with increased mortality and prolonged hospital stay.The optimization of post...BACKGROUND Cardiovascular(CV)complications are common in intensive care unit(ICU)patients after gastrointestinal surgery and are associated with increased mortality and prolonged hospital stay.The optimization of postoperative nursing interventions,particularly pain management,is crucial for reducing such complications.AIM To investigate the effects of enhanced recovery nursing on CV complications after gastrointestinal surgery in ICU patients and associated risk factors.METHODS A retrospective analysis was conducted on 78 adult patients who underwent gastrointestinal surgery in the ICU of our hospital between February 2023 and September 2024.Among them,40 patients received standard care(control group),while 38 received enhanced recovery nursing(observation group).We compared the incidence of CV complications and nursing satisfaction between the two groups.Patients were divided into CV complication and non-complication groups based on complication occurrence,and logistic regression analysis was used to identify risk factors.RESULTS In the control and observation groups,the incidence of CV complications was 30.0%(12/40)and 18.4%(7/38),with a nursing satisfaction rate of 70.0%(28/40)and 92.1%(35/38),respectively.The postoperative pain score at 14 days was significantly lower in the observation group(0.27±0.15)compared to the control group(1.65±0.37),with all differences being statistically significant(P<0.05).Univariate analysis indicated significant differences in age,body mass index,hypertension,diabetes,smoking history,history of heart failure,and previous myocardial infarction(P<0.05).Multivariate logistic regression identified heart failure history,previous myocardial infarction,age,hypertension,and diabetes as independent risk factors,with odds ratios of 1.195,1.528,1.062,1.836,and 1.942,respectively(all P<0.05).CONCLUSION Implementing enhanced recovery nursing for ICU patients after gastrointestinal surgery is beneficial in reducing the incidence of CV complications and improving nursing satisfaction.展开更多
Malaria is a significant global health challenge.This devastating disease continues to affect millions,especially in tropical regions.It is caused by Plasmodium parasites transmitted by female Anopheles mosquitoes.Thi...Malaria is a significant global health challenge.This devastating disease continues to affect millions,especially in tropical regions.It is caused by Plasmodium parasites transmitted by female Anopheles mosquitoes.This study introduces a nonlinear mathematical model for examining the transmission dynamics of malaria,incorporating both human and mosquito populations.We aim to identify the key factors driving the endemic spread of malaria,determine feasible solutions,and provide insights that lead to the development of effective prevention and management strategies.We derive the basic reproductive number employing the next-generation matrix approach and identify the disease-free and endemic equilibrium points.Stability analyses indicate that the disease-free equilibrium is locally and globally stable when the reproductive number is below one,whereas an endemic equilibrium persists when this threshold is exceeded.Sensitivity analysis identifies the most influential mosquito-related parameters,particularly the bite rate and mosquito mortality,in controlling the spread of malaria.Furthermore,we extend our model to include a treatment compartment and three disease-preventive control variables such as antimalaria drug treatments,use of larvicides,and the use of insecticide-treated mosquito nets for optimal control analysis.The results show that optimal use of mosquito nets,use of larvicides for mosquito population control,and treatment can lower the basic reproduction number and control malaria transmission with minimal intervention costs.The analysis of disease control strategies and findings offers valuable information for policymakers in designing cost-effective strategies to combat malaria.展开更多
To improve the accuracy of thermal response estimation and overcome the limitations of the linear regression model and Artificial Neural Network(ANN)model,this study introduces a deep learning estimation method specif...To improve the accuracy of thermal response estimation and overcome the limitations of the linear regression model and Artificial Neural Network(ANN)model,this study introduces a deep learning estimation method specifically based on the Long Short-Term Memory(LSTM)network,to predict temperature-induced girder end displacements of the Dasha Waterway Bridge,a suspension bridge in China.First,to enhance data quality and select target sensors,preprocessing based on the sigma rule and nearest neighbor interpolation is applied to the raw data.Furthermore,to eliminate the high-frequency components from the displacement signal,the wavelet transform is conducted.Subsequently,the linear regression model and ANN model are established,whose results do not meet the requirements and fail to address the time lag effect between temperature and displacements.The study proceeds to develop the LSTM network model and determine the optimal parameters through hyperparameter sensitivity analysis.Finally,the results of the LSTM network model are discussed by a comparative analysis against the linear regression model and ANN model,which indicates a higher accuracy in predicting temperatureinduced girder end displacements and the ability to mitigate the time-lag effect.To be more specific,in comparison between the linear regression model and LSTM network,the mean square error decreases from 6.5937 to 1.6808 and R^(2) increases from 0.683 to 0.930,which corresponds to a 74.51%decrease in MSE and a 36.14%improvement in R^(2).Compared to ANN,with an MSE of 4.6371 and an R^(2) of 0.807,LSTM shows a decrease in MSE of 63.75%and an increase in R^(2) of 13.23%,demonstrating a significant enhancement in predictive performance.展开更多
Lithium-rich layered oxides (LLOs) are increasingly recognized as promising cathode materials for nextgeneration high-energy-density lithium-ion batteries (LIBs).However,they suffer from voltage decay and low initial ...Lithium-rich layered oxides (LLOs) are increasingly recognized as promising cathode materials for nextgeneration high-energy-density lithium-ion batteries (LIBs).However,they suffer from voltage decay and low initial Coulombic efficiency (ICE) due to severe structural degradation caused by irreversible O release.Herein,we introduce a three-in-one strategy of increasing Ni and Mn content,along with Li/Ni disordering and TM–O covalency regulation to boost cationic and anionic redox activity simultaneously and thus enhance the electrochemical activity of LLOs.The target material,Li_(1.2)Ni_(0.168)Mn_(0.558)Co_(0.074)O_(2)(L1),exhibits an improved ICE of 87.2%and specific capacity of 293.2 mA h g^(-1)and minimal voltage decay of less than 0.53 m V cycle-1over 300 cycles at 1C,compared to Li_(1.2)Ni_(0.13)Mn_(0.54)Co_(0.13)O_(2)(Ls)(274.4 mA h g^(-1)for initial capacity,73.8%for ICE and voltage decay of 0.84 mV/cycle over 300 cycles at 1C).Theoretical calculations reveal that the density of states (DOS) area near the Fermi energy level for L1 is larger than that of Ls,indicating higher anionic and cationic redox reactivity than Ls.Moreover,L1 exhibits increased O-vacancy formation energy due to higher Li/Ni disordering of 4.76%(quantified by X-ray diffraction Rietveld refinement) and enhanced TM–O covalency,making lattice O release more difficult and thus improving electrochemical stability.The increased Li/Ni disordering also leads to more Ni^(2+)presence in the Li layer,which acts as a pillar during Li+de-embedding,improving structural stability.This research not only presents a viable approach to designing low-Co LLOs with enhanced capacity and ICE but also contributes significantly to the fundamental understanding of structural regulation in high-performance LIB cathodes.展开更多
Due to the rapid adoption of Building Information Modeling (BIM) in the architecture, engineering and construction (AEC) industry, many construction management (CM) programs in the US have introduced BIM in their curr...Due to the rapid adoption of Building Information Modeling (BIM) in the architecture, engineering and construction (AEC) industry, many construction management (CM) programs in the US have introduced BIM in their curriculum. Previous research has revealed that most of the BIM courses offered in CM programs have mainly focused on modeling skills as well as BIM applications in scheduling and estimating. While these topics appear to be important to apply BIM technology, students will not be able to fully understand the BIM process in a construction project without knowing the fundamental workflow of BIM. This paper presents a modular BIM course which was developed to help CM students better understand the BIM workflow and focuses on advanced uses of BIM in construction projects. The course contains three modules: BIM workflow, basic BIM applications, and advanced BIM applications. The BIM workflow module discusses how BIM is addressed in project delivery method, contract, the execution plan, and team building. The basic BIM applications module explains the typical BIM applications in coordination, scheduling, estimating, logistics, visualization, etc. The advanced BIM applications module demonstrates the latest technology advances in the AEC industry that utilizes BIM applications, including laser scanning, virtual reality, and mixed reality. The course objectives and assessment methods ensure that CM students’ understanding of BIM will be considerably improved from as a modeling tools or software program to an efficient process, and their insights into BIM will be significantly broadened beyond the existing 3D, 4D, and 5D applications. The highly positive course evaluation demonstrates the effectiveness of these approaches in meeting course objectives, delivering course materials, as well as raising students’ interest. This paper will serve as a case study of an advanced level BIM course in CM programs.展开更多
As BIM （building information modeling） became the gold standard of the architecture, construction, and engineering industry, lack of skilled BIM professionals is considered one of the major challenges. It is theref...As BIM （building information modeling） became the gold standard of the architecture, construction, and engineering industry, lack of skilled BIM professionals is considered one of the major challenges. It is therefore of significant importance that CM （construction management） programs train future construction professionals in the capabilities and advantages of BIM technology. This paper presents the findings of a comprehensive review of the implementation of BIM education in CM programs and summarizes the process of BIM adoption, existing educational approaches, and identified challenges in the implementation process. The information presented in this paper serves as a guide to CM programs that are new to and in the progress of implementing BIM education.展开更多
BACKGROUND The optimal approach for managing hepatic hemangioma is controversial.AIM To evaluate a clinical grading system for management of hepatic hemangioma based on our 17-year of single institution experience.MET...BACKGROUND The optimal approach for managing hepatic hemangioma is controversial.AIM To evaluate a clinical grading system for management of hepatic hemangioma based on our 17-year of single institution experience.METHODS A clinical grading system was retrospectively applied to 1171 patients with hepatic hemangioma from January 2002 to December 2018.Patients were classified into four groups based on the clinical grading system and treatment:(1)Observation group with score<4(Obs score<4);(2)Surgical group with score<4(Sur score<4);(3)Observation group with score≥4(Obs score≥4);and(4)Surgical group with score≥4(Sur score≥4).The clinico-pathological index and outcomes were evaluated.RESULTS There were significantly fewer symptomatic patients in surgical groups(Sur score≥4 vs Obs score≥4,P<0.001;Sur score<4 vs Obs score<4,χ^(2)=8.60,P=0.004;Sur score≥4 vs Obs score<4,P<0.001).The patients in Sur score≥4 had a lower rate of in need for intervention and total patients with adverse event than in Obs score≥4(P<0.001;P<0.001).Nevertheless,there was no significant difference in need for intervention and total patients with adverse event between the Sur score<4 and Obs score<4(P>0.05;χ^(2)=1.68,P>0.05).CONCLUSION This clinical grading system appeared as a practical tool for hepatic hemangioma.Surgery can be suggested for patients with a score≥4.For those with<4,follow-up should be proposed.展开更多
AlCrCuFeMnx(x=0,0.5,1,1.5,and 2)high-entropy alloys were prepared using the vacuum arc melting technology.The microstructure and mechanical properties of AlCrCuFeMnxwere analyzed and tested by XRD,SEM,TEM,nanoindentat...AlCrCuFeMnx(x=0,0.5,1,1.5,and 2)high-entropy alloys were prepared using the vacuum arc melting technology.The microstructure and mechanical properties of AlCrCuFeMnxwere analyzed and tested by XRD,SEM,TEM,nanoindentation,and electronic universal testing.The results indicate that the AlCrCuFeMnxhigh-entropy alloy exhibits a dendritic structure,consisting of dendrites with a BCC structure,interdendrite regions with an FCC structure,and precipitates with an ordered BCC structure that form within the dendrite.Manganese(Mn)has a strong affinity for dendritic,interdendritic,and precipitate structures,allowing it to easily enter these areas.With an increase in Mn content,the size of the precipitated nanoparticles in the dendritic region initially increases and then decreases.Similarly,the area fraction initially decreases and then increases.Additionally,the alloy’s strength and wear resistance decrease,while its plasticity increases.The Al Cr Cu Fe Mn1.5alloy boasts excellent mechanical properties,including a hardness of 360 HV and a wear rate of 2.4×10^(-5)mm^(3)·N^(-1)·mm^(-1).It also exhibits impressive yield strength,compressive strength,and deformation rates of 960 MPa,1,700 MPa,and 27.5%,respectively.展开更多
To evaluate the regularity of resilient modulus for hot-mix asphalt(HMA) under large temperature fluctuations,back propagation(BP) neural network technology was used to analyze the continuous change of HMA resilient m...To evaluate the regularity of resilient modulus for hot-mix asphalt(HMA) under large temperature fluctuations,back propagation(BP) neural network technology was used to analyze the continuous change of HMA resilient modulus.Firstly,based on the abundant data,the training model of HMA resilient modulus was established by using BP neural network technology.Subsequently,BP neural network prediction and regression analysis were performed,and the prediction model of HMA resilient modulus at different temperatures(-50℃ to 60℃) was obtained,which fully considered multi-factor and nonlinearity.Finally,the fitted theoretical model can be used to evaluate the HMA performance under the condition of large temperature fluctuations,and the rationality of theoretical model was verified by taking Harbin region as an example.It was found that the relationship between HMA resilient modulus and temperatures can be described by inverse tangent function.And the key parameters of theoretical model can be used to evaluate the continuous change characteristics of HMA resilient modulus with large temperature fluctuations.The results can further improve the HMA performance evaluation system and have certain theoretical value.展开更多
Co-free Li-rich layered oxides(LLOs)are emerging as promising cathode materials for Li-ion batteries due to their low cost and high capacity.However,they commonly face severe structural instability and poor electroche...Co-free Li-rich layered oxides(LLOs)are emerging as promising cathode materials for Li-ion batteries due to their low cost and high capacity.However,they commonly face severe structural instability and poor electrochemical activity,leading to diminished capacity and voltage performance.Herein,we introduce a Co-free LLO,Li_(1.167)Ni_(0.222)Mn_(0.611)O_(2)(Cf-L1),which features a cooperative structure of Li/Ni mixing and stacking faults.This structure regulates the crystal and electronic structures,resulting in a higher discharge capacity of 300.6 mA h g^(-1)and enhanced rate capability compared to the typical Co-free LLO,Li_(1.2)Ni_(0.2)Mn_(0.6)O_(2)(Cf-Ls).Density functional theory(DFT)indicates that Li/Ni mixing in LLOs leads to increased Li-O-Li configurations and higher anionic redox activities,while stacking faults further optimize the electronic interactions of transition metal(TM)3d and non-bonding O 2p orbitals.Moreover,stacking faults accommodate lattice strain,improving electrochemical reversibility during charge/discharge cycles,as demonstrated by the in situ XRD of Cf-L1 showing less lattice evolution than Cf-Ls.This study offers a structured approach to developing Co-free LLOs with enhanced capacity,voltage,rate capability,and cyclability,significantly impacting the advancement of the next-generation Li-ion batteries.展开更多
Neurological disorders,including headaches(tension-type headaches,medication-overuse headaches,and migraines)and dementias that include Alzheimer’s disease,are among the most prevalent and debilitating global conditi...Neurological disorders,including headaches(tension-type headaches,medication-overuse headaches,and migraines)and dementias that include Alzheimer’s disease,are among the most prevalent and debilitating global conditions.In 2016,these disorders affected 276 million people worldwide and were the second leading cause of death that year[1].This highlights the urgent need for effective prevention,treatment,and support strategies.The etiology of neurological disorders is multifaceted and involves genetic,environmental,physiological,and social factors[2].展开更多
The repeated failures of any equipment or systems are modeled as a renewal process. The management needs an assessment of the number of future failures to allocate the resources needed for fast repairs. Based on the i...The repeated failures of any equipment or systems are modeled as a renewal process. The management needs an assessment of the number of future failures to allocate the resources needed for fast repairs. Based on the idea of expectation by conditioning, special Volterra-type integral equations are derived for general types of repairs, considering the length of repair and reduced degradation of the idle object. In addition to minimal repair and failure replacement, partial repairs are also discussed when the repair results in reduction of the number of future failures or decreases the effective age of the object. Numerical integration-based algorithm and simulation study are performed to solve the resulting integral equation. Since the geometry degradation in different dimensions of a rail track and controlling and maintaining defects are of importance, a numerical example using the rail industry data is conducted. Expected number of failures of different failure type modes in rail track is calculated within a two-year interval. Results show that within a two-year period, anticipated occurrences of cross level failures, surface failures, and DPI failures are 2.4, 3.8, and 5.8, respectively.展开更多
Purpose This study aims to identify which determinants are responsible for impacting the user experience of three peer-to-peer(P2P)payment services in the Spanish market.Design/methodology/approach A sample of all onl...Purpose This study aims to identify which determinants are responsible for impacting the user experience of three peer-to-peer(P2P)payment services in the Spanish market.Design/methodology/approach A sample of all online reviews(n=16,048)published in Google Play of three paytech apps—Bizum,Twyp,and Verse—was analyzed using text mining and sentiment analysis.Findings A holistic interpretation of the seed terms included in each aspect allowed to label them based on the preferences expressed by paytech app users in their reviews.Six latent aspects were identified:ease of use,usefulness,perceived value,performance expectancy,perceived quality,and user experience.In addition,the results of the analysis suggest a positivity bias in the online reviews of fintech P2P app users.Our results also show that online reviews of apps associated with banks or financial institutions,such as Bizum(to a greater extent)or Twyp,show more negative emotions,whereas independent apps(Verse)show more positive emotions.Moreover,the most critical users are those of unidentified gender,while women remain in a more neutral position,and men tend to express their opinions more positively regarding P2P payment apps.Practical implications Paytech providers should analyze the problems faced by users immediately after an encounter.By applying text mining analysis,service providers can gain efficiency in understanding user sentiments and emotions without tedious and time-consuming reviews.Originality/value This is a pioneering study on peer-to-peer(P2P)mobile payment systems from the user’s perspective because it investigates the emotions and sentiments that users convey through bank reviews.展开更多
Disruptive innovations caused by FinTech(i.e.,technology-assisted customized financial services)have brought digital peer-to-peer(P2P)payments to the fore.In this challenging environment and based on theories about cu...Disruptive innovations caused by FinTech(i.e.,technology-assisted customized financial services)have brought digital peer-to-peer(P2P)payments to the fore.In this challenging environment and based on theories about customer behavior in response to technological innovations,this paper identifies the drivers of consumer adoption of mobile P2P payments and develops a machine learning model to predict the use of this thriving payment option.To do so,we use a unique data set with information from 701 participants(observations)who completed a questionnaire about the adoption of Bizum,a leading mobile P2P platform worldwide.The respondent profile was the average Spanish citizen within the framework of European culture and lifestyle.We document(in this order of priority)the usefulness of mobile P2P payments,influence of peers and other social groups such as friends,family,and colleagues on individual behavior(that is,subjective norms),perceived trust,and enjoyment of the user experience within the digital context and how those attributes better classify(potential)users of mobile P2P payments.We also find that nonparametric approaches based on machine learning algorithms outperform traditional parametric methods.Finally,our results show that feature selection based on random forest,such as the Boruta procedure,as a preprocessing technique substantially increases prediction performance while reducing noise,redundancy of the resulting model,and computational costs.The main limitation of this research is that it only has a place within the sociocultural and institutional framework of the Spanish population.It is therefore desirable to replicate this study by surveying people from other countries to analyze the effects of the institutional environment on the adoption of mobile P2P payments.展开更多
In China, meteorological forecasting relies on meteorological data obtained from regional and national stations. However, there were discrepancies between the data collected from the meteorological station at the pass...In China, meteorological forecasting relies on meteorological data obtained from regional and national stations. However, there were discrepancies between the data collected from the meteorological station at the passion fruit growing base and the data from regional and national stations. Consequently, the high and low temperature disaster indicators determined by the meteorological station at the passion fruit growing base cannot be applied to meteorological forecasting. To address this issue and facilitate the monitoring and early warning of high and low temperature disasters in passion fruit cultivation in Fujian, China, we used multi-source hourly temperature data (including the data from meteorological observation stations in passion fruit growing bases, the nearest regional stations, and national surface conventional meteorological observation stations) in three cities in southwestern Fujian (Longyan, Sanming, and Zhangzhou) spanning the years 2020 to 2022. By employing comprehensive statistical analysis methods (0.5 interval division and Cumulative frequency), we identified that passion fruit in southwestern Fujian was susceptible to high temperature disasters during the blooming-fruiting period, as well as low temperature disasters during the sprouting period. Consequently, we developed high and low temperature disaster indicators based on data from regional and national stations for different phenological periods of passion fruit in this region.展开更多
The remaining useful life(RUL) prediction of mechanical products has been widely studied for online system performance reliability, device remanufacturing, and product safety(safety awareness and safety improvement). ...The remaining useful life(RUL) prediction of mechanical products has been widely studied for online system performance reliability, device remanufacturing, and product safety(safety awareness and safety improvement). These studies incorporated many di erent models, algorithms, and techniques for modeling and assessment. In this paper, methods of RUL assessment are summarized and expounded upon using two major methods: physics model based and data driven based methods. The advantages and disadvantages of each of these methods are deliberated and compared as well. Due to the intricacy of failure mechanism in system, and di culty in physics degradation observation, RUL assessment based on observations of performance variables turns into a science in evaluating the degradation. A modeling method from control systems, the state space model(SSM), as a first order hidden Markov, is presented. In the context of non-linear and non-Gaussian systems, the SSM methodology is capable of performing remaining life assessment by using Bayesian estimation(sequential Monte Carlo). Being e ective for non-linear and non-Gaussian dynamics, the methodology can perform the assessment recursively online for applications in CBM(condition based maintenance), PHM(prognostics and health management), remanufacturing, and system performance reliability. Finally, the discussion raises concerns regarding online sensing data for SSM modeling and assessment of RUL.展开更多
基金supported by the National Natural Science Foundation of China(Nos.U2033203,U1833126,61773203,61304190)。
文摘Air traffic flow management has been a major means for balancing air traffic demandand airport or airspace capacity to reduce congestion and flight delays.However,unpredictable fac-tors,such as weather and equipment malfunctions,can cause dynamic changes in airport and sectorcapacity,resulting in significant alterations to optimized flight schedules and the calculated pre-departure slots.Therefore,taking into account capacity uncertainties is essential to create a moreresilient flight schedule.This paper addresses the flight pre-departure sequencing issue and intro-duces a capacity uncertainty model for optimizing flight schedule at the airport network level.The goal of the model is to reduce the total cost of flight delays while increasing the robustnessof the optimized schedule.A chance-constrained model is developed to address the capacity uncer-tainty of airports and sectors,and the significance of airports and sectors in the airport network isconsidered when setting the violation probability.The performance of the model is evaluated usingreal flight data by comparing them with the results of the deterministic model.The development ofthe model based on the characteristics of this special optimization mechanism can significantlyenhance its performance in addressing the pre-departure flight scheduling problem at the airportnetwork level.
文摘This paper focuses on the optimization of the evaluation index system for the value of transportation infrastructure assets.It analyzes the shortcomings of the current system and explores the directions for optimizing the index system from the perspectives of functionality,economy,social impact,environmental impact,and sustainability.The paper also discusses the application of the optimized index system in practical evaluation and the measures to ensure its effectiveness.The research aims to enhance the evaluation mechanism for the value of transportation infrastructure assets,providing a more scientific basis for decision-making,addressing challenges in asset management,improving the level of asset management in transportation infrastructure,and meeting the demands of high-quality development in the transportation sector in the new era.
文摘The development of artificial intelligence has brought tremendous changes to enterprises and also pose higher demands on financial professionals.Through literature research,this paper explores the viewpoints of domestic and foreign scholars and industry experts on the impact of Artificial Intelligence(AI)on corporate financial management and the role transformation of financial professionals.It analyzes the current application status of AI technology in finance.The results indicate that AI will replace some repetitive and highly procedural tasks,such as simple data entry and bookkeeping.AI can improve the processing speed and accuracy of corporate financial data.With its learning capabilities,AI can assist financial professionals in addressing knowledge gaps.However,AI cannot completely replace human thinking,judgment,and decision-making,especially in areas like emotional communication and aesthetic experience.This requires financial professionals to continuously improve their overall qualities,leverage their strengths,and achieve complementary advantages with machines,jointly promoting innovative financial development in the era of artificial intelligence.
文摘BACKGROUND Cardiovascular(CV)complications are common in intensive care unit(ICU)patients after gastrointestinal surgery and are associated with increased mortality and prolonged hospital stay.The optimization of postoperative nursing interventions,particularly pain management,is crucial for reducing such complications.AIM To investigate the effects of enhanced recovery nursing on CV complications after gastrointestinal surgery in ICU patients and associated risk factors.METHODS A retrospective analysis was conducted on 78 adult patients who underwent gastrointestinal surgery in the ICU of our hospital between February 2023 and September 2024.Among them,40 patients received standard care(control group),while 38 received enhanced recovery nursing(observation group).We compared the incidence of CV complications and nursing satisfaction between the two groups.Patients were divided into CV complication and non-complication groups based on complication occurrence,and logistic regression analysis was used to identify risk factors.RESULTS In the control and observation groups,the incidence of CV complications was 30.0%(12/40)and 18.4%(7/38),with a nursing satisfaction rate of 70.0%(28/40)and 92.1%(35/38),respectively.The postoperative pain score at 14 days was significantly lower in the observation group(0.27±0.15)compared to the control group(1.65±0.37),with all differences being statistically significant(P<0.05).Univariate analysis indicated significant differences in age,body mass index,hypertension,diabetes,smoking history,history of heart failure,and previous myocardial infarction(P<0.05).Multivariate logistic regression identified heart failure history,previous myocardial infarction,age,hypertension,and diabetes as independent risk factors,with odds ratios of 1.195,1.528,1.062,1.836,and 1.942,respectively(all P<0.05).CONCLUSION Implementing enhanced recovery nursing for ICU patients after gastrointestinal surgery is beneficial in reducing the incidence of CV complications and improving nursing satisfaction.
基金supported by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia[Grant No.KFU252959].
文摘Malaria is a significant global health challenge.This devastating disease continues to affect millions,especially in tropical regions.It is caused by Plasmodium parasites transmitted by female Anopheles mosquitoes.This study introduces a nonlinear mathematical model for examining the transmission dynamics of malaria,incorporating both human and mosquito populations.We aim to identify the key factors driving the endemic spread of malaria,determine feasible solutions,and provide insights that lead to the development of effective prevention and management strategies.We derive the basic reproductive number employing the next-generation matrix approach and identify the disease-free and endemic equilibrium points.Stability analyses indicate that the disease-free equilibrium is locally and globally stable when the reproductive number is below one,whereas an endemic equilibrium persists when this threshold is exceeded.Sensitivity analysis identifies the most influential mosquito-related parameters,particularly the bite rate and mosquito mortality,in controlling the spread of malaria.Furthermore,we extend our model to include a treatment compartment and three disease-preventive control variables such as antimalaria drug treatments,use of larvicides,and the use of insecticide-treated mosquito nets for optimal control analysis.The results show that optimal use of mosquito nets,use of larvicides for mosquito population control,and treatment can lower the basic reproduction number and control malaria transmission with minimal intervention costs.The analysis of disease control strategies and findings offers valuable information for policymakers in designing cost-effective strategies to combat malaria.
基金The National Key Research and Development Program of China grant No.2022YFB3706704 received by Yuan Renthe National Natural and Science Foundation of China grant No.52308150 received by Xiang Xu.
文摘To improve the accuracy of thermal response estimation and overcome the limitations of the linear regression model and Artificial Neural Network(ANN)model,this study introduces a deep learning estimation method specifically based on the Long Short-Term Memory(LSTM)network,to predict temperature-induced girder end displacements of the Dasha Waterway Bridge,a suspension bridge in China.First,to enhance data quality and select target sensors,preprocessing based on the sigma rule and nearest neighbor interpolation is applied to the raw data.Furthermore,to eliminate the high-frequency components from the displacement signal,the wavelet transform is conducted.Subsequently,the linear regression model and ANN model are established,whose results do not meet the requirements and fail to address the time lag effect between temperature and displacements.The study proceeds to develop the LSTM network model and determine the optimal parameters through hyperparameter sensitivity analysis.Finally,the results of the LSTM network model are discussed by a comparative analysis against the linear regression model and ANN model,which indicates a higher accuracy in predicting temperatureinduced girder end displacements and the ability to mitigate the time-lag effect.To be more specific,in comparison between the linear regression model and LSTM network,the mean square error decreases from 6.5937 to 1.6808 and R^(2) increases from 0.683 to 0.930,which corresponds to a 74.51%decrease in MSE and a 36.14%improvement in R^(2).Compared to ANN,with an MSE of 4.6371 and an R^(2) of 0.807,LSTM shows a decrease in MSE of 63.75%and an increase in R^(2) of 13.23%,demonstrating a significant enhancement in predictive performance.
基金National Natural Science Foundation of China (No.52202046)Natural Science Foundation of Shaanxi Province (No.2021JQ-034)。
文摘Lithium-rich layered oxides (LLOs) are increasingly recognized as promising cathode materials for nextgeneration high-energy-density lithium-ion batteries (LIBs).However,they suffer from voltage decay and low initial Coulombic efficiency (ICE) due to severe structural degradation caused by irreversible O release.Herein,we introduce a three-in-one strategy of increasing Ni and Mn content,along with Li/Ni disordering and TM–O covalency regulation to boost cationic and anionic redox activity simultaneously and thus enhance the electrochemical activity of LLOs.The target material,Li_(1.2)Ni_(0.168)Mn_(0.558)Co_(0.074)O_(2)(L1),exhibits an improved ICE of 87.2%and specific capacity of 293.2 mA h g^(-1)and minimal voltage decay of less than 0.53 m V cycle-1over 300 cycles at 1C,compared to Li_(1.2)Ni_(0.13)Mn_(0.54)Co_(0.13)O_(2)(Ls)(274.4 mA h g^(-1)for initial capacity,73.8%for ICE and voltage decay of 0.84 mV/cycle over 300 cycles at 1C).Theoretical calculations reveal that the density of states (DOS) area near the Fermi energy level for L1 is larger than that of Ls,indicating higher anionic and cationic redox reactivity than Ls.Moreover,L1 exhibits increased O-vacancy formation energy due to higher Li/Ni disordering of 4.76%(quantified by X-ray diffraction Rietveld refinement) and enhanced TM–O covalency,making lattice O release more difficult and thus improving electrochemical stability.The increased Li/Ni disordering also leads to more Ni^(2+)presence in the Li layer,which acts as a pillar during Li+de-embedding,improving structural stability.This research not only presents a viable approach to designing low-Co LLOs with enhanced capacity and ICE but also contributes significantly to the fundamental understanding of structural regulation in high-performance LIB cathodes.
文摘Due to the rapid adoption of Building Information Modeling (BIM) in the architecture, engineering and construction (AEC) industry, many construction management (CM) programs in the US have introduced BIM in their curriculum. Previous research has revealed that most of the BIM courses offered in CM programs have mainly focused on modeling skills as well as BIM applications in scheduling and estimating. While these topics appear to be important to apply BIM technology, students will not be able to fully understand the BIM process in a construction project without knowing the fundamental workflow of BIM. This paper presents a modular BIM course which was developed to help CM students better understand the BIM workflow and focuses on advanced uses of BIM in construction projects. The course contains three modules: BIM workflow, basic BIM applications, and advanced BIM applications. The BIM workflow module discusses how BIM is addressed in project delivery method, contract, the execution plan, and team building. The basic BIM applications module explains the typical BIM applications in coordination, scheduling, estimating, logistics, visualization, etc. The advanced BIM applications module demonstrates the latest technology advances in the AEC industry that utilizes BIM applications, including laser scanning, virtual reality, and mixed reality. The course objectives and assessment methods ensure that CM students’ understanding of BIM will be considerably improved from as a modeling tools or software program to an efficient process, and their insights into BIM will be significantly broadened beyond the existing 3D, 4D, and 5D applications. The highly positive course evaluation demonstrates the effectiveness of these approaches in meeting course objectives, delivering course materials, as well as raising students’ interest. This paper will serve as a case study of an advanced level BIM course in CM programs.
文摘As BIM （building information modeling） became the gold standard of the architecture, construction, and engineering industry, lack of skilled BIM professionals is considered one of the major challenges. It is therefore of significant importance that CM （construction management） programs train future construction professionals in the capabilities and advantages of BIM technology. This paper presents the findings of a comprehensive review of the implementation of BIM education in CM programs and summarizes the process of BIM adoption, existing educational approaches, and identified challenges in the implementation process. The information presented in this paper serves as a guide to CM programs that are new to and in the progress of implementing BIM education.
文摘BACKGROUND The optimal approach for managing hepatic hemangioma is controversial.AIM To evaluate a clinical grading system for management of hepatic hemangioma based on our 17-year of single institution experience.METHODS A clinical grading system was retrospectively applied to 1171 patients with hepatic hemangioma from January 2002 to December 2018.Patients were classified into four groups based on the clinical grading system and treatment:(1)Observation group with score<4(Obs score<4);(2)Surgical group with score<4(Sur score<4);(3)Observation group with score≥4(Obs score≥4);and(4)Surgical group with score≥4(Sur score≥4).The clinico-pathological index and outcomes were evaluated.RESULTS There were significantly fewer symptomatic patients in surgical groups(Sur score≥4 vs Obs score≥4,P<0.001;Sur score<4 vs Obs score<4,χ^(2)=8.60,P=0.004;Sur score≥4 vs Obs score<4,P<0.001).The patients in Sur score≥4 had a lower rate of in need for intervention and total patients with adverse event than in Obs score≥4(P<0.001;P<0.001).Nevertheless,there was no significant difference in need for intervention and total patients with adverse event between the Sur score<4 and Obs score<4(P>0.05;χ^(2)=1.68,P>0.05).CONCLUSION This clinical grading system appeared as a practical tool for hepatic hemangioma.Surgery can be suggested for patients with a score≥4.For those with<4,follow-up should be proposed.
基金supported by the China Postdoctoral Science Foundation Project(2018M633650XB)Gansu Province Young Doctoral Fund Project(2021QB-043)the CNNC Operations Management Limited R&D Project(QS4FY-22003224)。
文摘AlCrCuFeMnx(x=0,0.5,1,1.5,and 2)high-entropy alloys were prepared using the vacuum arc melting technology.The microstructure and mechanical properties of AlCrCuFeMnxwere analyzed and tested by XRD,SEM,TEM,nanoindentation,and electronic universal testing.The results indicate that the AlCrCuFeMnxhigh-entropy alloy exhibits a dendritic structure,consisting of dendrites with a BCC structure,interdendrite regions with an FCC structure,and precipitates with an ordered BCC structure that form within the dendrite.Manganese(Mn)has a strong affinity for dendritic,interdendritic,and precipitate structures,allowing it to easily enter these areas.With an increase in Mn content,the size of the precipitated nanoparticles in the dendritic region initially increases and then decreases.Similarly,the area fraction initially decreases and then increases.Additionally,the alloy’s strength and wear resistance decrease,while its plasticity increases.The Al Cr Cu Fe Mn1.5alloy boasts excellent mechanical properties,including a hardness of 360 HV and a wear rate of 2.4×10^(-5)mm^(3)·N^(-1)·mm^(-1).It also exhibits impressive yield strength,compressive strength,and deformation rates of 960 MPa,1,700 MPa,and 27.5%,respectively.
基金support from the projects of Science and Technology Project of Transportation Department of Heilongjiang Province (No. HJK2019B009)the Fundamental Research Funds for the Cornell University (No. 2572021AW10)the Ludong University to Introduce Talents Research Start-up Funding Project (No. 20240050)
文摘To evaluate the regularity of resilient modulus for hot-mix asphalt(HMA) under large temperature fluctuations,back propagation(BP) neural network technology was used to analyze the continuous change of HMA resilient modulus.Firstly,based on the abundant data,the training model of HMA resilient modulus was established by using BP neural network technology.Subsequently,BP neural network prediction and regression analysis were performed,and the prediction model of HMA resilient modulus at different temperatures(-50℃ to 60℃) was obtained,which fully considered multi-factor and nonlinearity.Finally,the fitted theoretical model can be used to evaluate the HMA performance under the condition of large temperature fluctuations,and the rationality of theoretical model was verified by taking Harbin region as an example.It was found that the relationship between HMA resilient modulus and temperatures can be described by inverse tangent function.And the key parameters of theoretical model can be used to evaluate the continuous change characteristics of HMA resilient modulus with large temperature fluctuations.The results can further improve the HMA performance evaluation system and have certain theoretical value.
基金financially supported by the National Natural Science Foundation of China(52202046,51602246,and 51801144)the Natural Science Foundation of Shanxi Provincial(2021JQ-034)。
文摘Co-free Li-rich layered oxides(LLOs)are emerging as promising cathode materials for Li-ion batteries due to their low cost and high capacity.However,they commonly face severe structural instability and poor electrochemical activity,leading to diminished capacity and voltage performance.Herein,we introduce a Co-free LLO,Li_(1.167)Ni_(0.222)Mn_(0.611)O_(2)(Cf-L1),which features a cooperative structure of Li/Ni mixing and stacking faults.This structure regulates the crystal and electronic structures,resulting in a higher discharge capacity of 300.6 mA h g^(-1)and enhanced rate capability compared to the typical Co-free LLO,Li_(1.2)Ni_(0.2)Mn_(0.6)O_(2)(Cf-Ls).Density functional theory(DFT)indicates that Li/Ni mixing in LLOs leads to increased Li-O-Li configurations and higher anionic redox activities,while stacking faults further optimize the electronic interactions of transition metal(TM)3d and non-bonding O 2p orbitals.Moreover,stacking faults accommodate lattice strain,improving electrochemical reversibility during charge/discharge cycles,as demonstrated by the in situ XRD of Cf-L1 showing less lattice evolution than Cf-Ls.This study offers a structured approach to developing Co-free LLOs with enhanced capacity,voltage,rate capability,and cyclability,significantly impacting the advancement of the next-generation Li-ion batteries.
基金supported by the National Key Research and Development Program of China[2018YFE0206900].
文摘Neurological disorders,including headaches(tension-type headaches,medication-overuse headaches,and migraines)and dementias that include Alzheimer’s disease,are among the most prevalent and debilitating global conditions.In 2016,these disorders affected 276 million people worldwide and were the second leading cause of death that year[1].This highlights the urgent need for effective prevention,treatment,and support strategies.The etiology of neurological disorders is multifaceted and involves genetic,environmental,physiological,and social factors[2].
文摘The repeated failures of any equipment or systems are modeled as a renewal process. The management needs an assessment of the number of future failures to allocate the resources needed for fast repairs. Based on the idea of expectation by conditioning, special Volterra-type integral equations are derived for general types of repairs, considering the length of repair and reduced degradation of the idle object. In addition to minimal repair and failure replacement, partial repairs are also discussed when the repair results in reduction of the number of future failures or decreases the effective age of the object. Numerical integration-based algorithm and simulation study are performed to solve the resulting integral equation. Since the geometry degradation in different dimensions of a rail track and controlling and maintaining defects are of importance, a numerical example using the rail industry data is conducted. Expected number of failures of different failure type modes in rail track is calculated within a two-year interval. Results show that within a two-year period, anticipated occurrences of cross level failures, surface failures, and DPI failures are 2.4, 3.8, and 5.8, respectively.
基金funded by the University of Seville under grant to the Research Group[SEJ-566].
文摘Purpose This study aims to identify which determinants are responsible for impacting the user experience of three peer-to-peer(P2P)payment services in the Spanish market.Design/methodology/approach A sample of all online reviews(n=16,048)published in Google Play of three paytech apps—Bizum,Twyp,and Verse—was analyzed using text mining and sentiment analysis.Findings A holistic interpretation of the seed terms included in each aspect allowed to label them based on the preferences expressed by paytech app users in their reviews.Six latent aspects were identified:ease of use,usefulness,perceived value,performance expectancy,perceived quality,and user experience.In addition,the results of the analysis suggest a positivity bias in the online reviews of fintech P2P app users.Our results also show that online reviews of apps associated with banks or financial institutions,such as Bizum(to a greater extent)or Twyp,show more negative emotions,whereas independent apps(Verse)show more positive emotions.Moreover,the most critical users are those of unidentified gender,while women remain in a more neutral position,and men tend to express their opinions more positively regarding P2P payment apps.Practical implications Paytech providers should analyze the problems faced by users immediately after an encounter.By applying text mining analysis,service providers can gain efficiency in understanding user sentiments and emotions without tedious and time-consuming reviews.Originality/value This is a pioneering study on peer-to-peer(P2P)mobile payment systems from the user’s perspective because it investigates the emotions and sentiments that users convey through bank reviews.
文摘Disruptive innovations caused by FinTech(i.e.,technology-assisted customized financial services)have brought digital peer-to-peer(P2P)payments to the fore.In this challenging environment and based on theories about customer behavior in response to technological innovations,this paper identifies the drivers of consumer adoption of mobile P2P payments and develops a machine learning model to predict the use of this thriving payment option.To do so,we use a unique data set with information from 701 participants(observations)who completed a questionnaire about the adoption of Bizum,a leading mobile P2P platform worldwide.The respondent profile was the average Spanish citizen within the framework of European culture and lifestyle.We document(in this order of priority)the usefulness of mobile P2P payments,influence of peers and other social groups such as friends,family,and colleagues on individual behavior(that is,subjective norms),perceived trust,and enjoyment of the user experience within the digital context and how those attributes better classify(potential)users of mobile P2P payments.We also find that nonparametric approaches based on machine learning algorithms outperform traditional parametric methods.Finally,our results show that feature selection based on random forest,such as the Boruta procedure,as a preprocessing technique substantially increases prediction performance while reducing noise,redundancy of the resulting model,and computational costs.The main limitation of this research is that it only has a place within the sociocultural and institutional framework of the Spanish population.It is therefore desirable to replicate this study by surveying people from other countries to analyze the effects of the institutional environment on the adoption of mobile P2P payments.
文摘In China, meteorological forecasting relies on meteorological data obtained from regional and national stations. However, there were discrepancies between the data collected from the meteorological station at the passion fruit growing base and the data from regional and national stations. Consequently, the high and low temperature disaster indicators determined by the meteorological station at the passion fruit growing base cannot be applied to meteorological forecasting. To address this issue and facilitate the monitoring and early warning of high and low temperature disasters in passion fruit cultivation in Fujian, China, we used multi-source hourly temperature data (including the data from meteorological observation stations in passion fruit growing bases, the nearest regional stations, and national surface conventional meteorological observation stations) in three cities in southwestern Fujian (Longyan, Sanming, and Zhangzhou) spanning the years 2020 to 2022. By employing comprehensive statistical analysis methods (0.5 interval division and Cumulative frequency), we identified that passion fruit in southwestern Fujian was susceptible to high temperature disasters during the blooming-fruiting period, as well as low temperature disasters during the sprouting period. Consequently, we developed high and low temperature disaster indicators based on data from regional and national stations for different phenological periods of passion fruit in this region.
基金Supported by Fundamental Research Funds for the Central Universities of China(Grant No.DUT17GF214)
文摘The remaining useful life(RUL) prediction of mechanical products has been widely studied for online system performance reliability, device remanufacturing, and product safety(safety awareness and safety improvement). These studies incorporated many di erent models, algorithms, and techniques for modeling and assessment. In this paper, methods of RUL assessment are summarized and expounded upon using two major methods: physics model based and data driven based methods. The advantages and disadvantages of each of these methods are deliberated and compared as well. Due to the intricacy of failure mechanism in system, and di culty in physics degradation observation, RUL assessment based on observations of performance variables turns into a science in evaluating the degradation. A modeling method from control systems, the state space model(SSM), as a first order hidden Markov, is presented. In the context of non-linear and non-Gaussian systems, the SSM methodology is capable of performing remaining life assessment by using Bayesian estimation(sequential Monte Carlo). Being e ective for non-linear and non-Gaussian dynamics, the methodology can perform the assessment recursively online for applications in CBM(condition based maintenance), PHM(prognostics and health management), remanufacturing, and system performance reliability. Finally, the discussion raises concerns regarding online sensing data for SSM modeling and assessment of RUL.
