Traffic forecasting with high precision aids Intelligent Transport Systems(ITS)in formulating and optimizing traffic management strategies.The algorithms used for tuning the hyperparameters of the deep learning models...Traffic forecasting with high precision aids Intelligent Transport Systems(ITS)in formulating and optimizing traffic management strategies.The algorithms used for tuning the hyperparameters of the deep learning models often have accurate results at the expense of high computational complexity.To address this problem,this paper uses the Tree-structured Parzen Estimator(TPE)to tune the hyperparameters of the Long Short-term Memory(LSTM)deep learning framework.The Tree-structured Parzen Estimator(TPE)uses a probabilistic approach with an adaptive searching mechanism by classifying the objective function values into good and bad samples.This ensures fast convergence in tuning the hyperparameter values in the deep learning model for performing prediction while still maintaining a certain degree of accuracy.It also overcomes the problem of converging to local optima and avoids timeconsuming random search and,therefore,avoids high computational complexity in prediction accuracy.The proposed scheme first performs data smoothing and normalization on the input data,which is then fed to the input of the TPE for tuning the hyperparameters.The traffic data is then input to the LSTM model with tuned parameters to perform the traffic prediction.The three optimizers:Adaptive Moment Estimation(Adam),Root Mean Square Propagation(RMSProp),and Stochastic Gradient Descend with Momentum(SGDM)are also evaluated for accuracy prediction and the best optimizer is then chosen for final traffic prediction in TPE-LSTM model.Simulation results verify the effectiveness of the proposed model in terms of accuracy of prediction over the benchmark schemes.展开更多
In order to solve the problems of high experimental cost of ammunition,lack of field test data,and the difficulty in applying the ammunition hit probability estimation method in classical statistics,this paper assumes...In order to solve the problems of high experimental cost of ammunition,lack of field test data,and the difficulty in applying the ammunition hit probability estimation method in classical statistics,this paper assumes that the projectile dispersion of ammunition is a two-dimensional joint normal distribution,and proposes a new Bayesian inference method of ammunition hit probability based on normal-inverse Wishart distribution.Firstly,the conjugate joint prior distribution of the projectile dispersion characteristic parameters is determined to be a normal inverse Wishart distribution,and the hyperparameters in the prior distribution are estimated by simulation experimental data and historical measured data.Secondly,the field test data is integrated with the Bayesian formula to obtain the joint posterior distribution of the projectile dispersion characteristic parameters,and then the hit probability of the ammunition is estimated.Finally,compared with the binomial distribution method,the method in this paper can consider the dispersion information of ammunition projectiles,and the hit probability information is more fully utilized.The hit probability results are closer to the field shooting test samples.This method has strong applicability and is conducive to obtaining more accurate hit probability estimation results.展开更多
Mongolia is a landlocked country with limited infrastructure and high dependence on the Xingang Tianjin port in China for imports. This research examines the potential impacts of establishing a dry port in Zamyn-Uud, ...Mongolia is a landlocked country with limited infrastructure and high dependence on the Xingang Tianjin port in China for imports. This research examines the potential impacts of establishing a dry port in Zamyn-Uud, Mongolia, utilizing a system dynamics modeling approach via Vensim software. The study evaluates transportation time, costs, inflation, and logistics performance index improvements, revealing that the establishment of the dry port can reduce transportation costs and delays significantly while enhancing economic growth. The findings offer actionable insights for policymakers and stakeholders in addressing logistical inefficiencies and fostering sustainable development in landlocked regions.展开更多
Background:The rapid integration of generative artificial intelligence(genAI)into medical education offers significant opportunities for personalized learning,efficiency,and access.However,its implementation also rais...Background:The rapid integration of generative artificial intelligence(genAI)into medical education offers significant opportunities for personalized learning,efficiency,and access.However,its implementation also raises complex ethical concerns that,if unaddressed,may compromise academic integrity,professional identity,and learner equity.This review aimed to identify the primary ethical risks associated with genAI use in medical education and propose solid measures to mitigate these issues.Methods:A structured narrative review was conducted in accordance with the Scale for the Assessment of Narrative Review Articles(SANRA).A focused literature search was performed across PubMed/MEDLINE and Google Scholar for peer-reviewed,English-language articles published from January 2023 to May 2025.Studies were included if they addressed ethical issues in the use of genAI in undergraduate or postgraduate medical education.Data were extracted into related themes,and findings were synthesized into risk and mitigation categories.Results:A total of 27 records were included.Eight principal categories of ethical risks associated with genAI in medical education emerged:(1)academic integrity erosion,(2)cognitive deskilling,(3)algorithmic bias and opacity,(4)privacy and surveillance concerns,(5)moral and humanistic diminishment,(6)faculty role displacement,(7)commercialization and inequity,and(8)legal-regulatory ambiguity.Each risk was matched with targeted mitigation strategies proposed in the literature,including institutional genAI governance frameworks,genAI literacy training,reinforcement of humanistic pedagogy,establishment of ethical oversight bodies,curricular integration of ethical reflexivity,equity-centered implementation policies,faculty development for genAI integration,and transparent data governance protocols.Conclusion:Generative AI presents both transformative promise and substantial ethical risks in medical education.Proactive,ethically grounded integration-guided by institutional oversight,curriculum reform,and equity safeguards-is essential to realize its benefits while protecting the integrity and humanity of medical training.展开更多
The increasing global demand for energy,coupled with concerns about environmental sustainability,has underscored the need for a transition toward renewable energy sources.A well-structured teaching program under the f...The increasing global demand for energy,coupled with concerns about environmental sustainability,has underscored the need for a transition toward renewable energy sources.A well-structured teaching program under the framework of sustainable development in renewable energy seeks to give students the information,abilities,and critical thinking needed to solve energy-related problems sustainably.This research proposes AI-powered personalized learning,innovative real-time integration of diverse data,and adaptive teaching strategies to enhance student understanding regarding renewable energy concepts.The sheep flock-optimized innovative recurrent neural network(SFO-IRNN)will recommend relevant topics and resources based on students’performance.Renewable energy teaching data from assessmethments are combined with real-time IoT-based renewable energy data.This dataset contains renewable energy education using AI-driven teaching methods and internet-based learning.The data was preprocessed by handling missing values and min-max scaling.The data features were extracted using Fourier Transform(FT).Further application of 10-fold cross-validation will increase the reliability of the model as it can evaluate its performance metrics like accuracy,F1-score,recall,and precision on different subsets of student data,which improves its robustness and prevents overfitting.The findings showed that the proposed method is significantly better,which ensures that the students have a deeper theoretical and practical understanding of renewable energy technologies.In addition,integrating real-time IoT data from renewable energy sources gives students a chance to do live simulations and problems that would enhance analytical thinking and hands-on learning.The research shows that AI provides context-aware guidance on sustainable energy infrastructure,enhancing interactive and personalized learning.展开更多
Additive manufacturing(AM)has emerged as one of the most utilized processes in manufacturing due to its ability to produce complex geometries with minimal material waste and greater design freedom.Laser-based AM(LAM)t...Additive manufacturing(AM)has emerged as one of the most utilized processes in manufacturing due to its ability to produce complex geometries with minimal material waste and greater design freedom.Laser-based AM(LAM)technologies use high-power lasers to melt metallic materials,which then solidify to form parts.However,it inherently induces self-equilibrating residual stress during fabrication due to thermal loads and plastic deformation.These residual stresses can cause defects such as delamination,cracking,and distortion,as well as premature failure under service conditions,necessitating mitigation.While post-treatment methods can reduce residual stresses,they are often costly and time-consuming.Therefore,tuning the fabrication process parameters presents a more feasible approach.Accordingly,in addition to providing a comprehensive view of residual stress by their classification,formation mechanisms,measurement methods,and common post-treatment,this paper reviews and compares the studies conducted on the effect of key parameters of the LAM process on the resulting residual stresses.This review focuses on proactively adjusting LAM process parameters as a strategic approach to mitigate residual stress formation.It provides a result of the various parameters influencing residual stress outcomes,such as laser power,scanning speed,beam diameter,hatch spacing,and scanning strategies.Finally,the paper identifies existing research gaps and proposes future studies needed to deepen understanding of the relationship between process parameters and residual stress mitigation in LAM.展开更多
Additive manufacturing(AM),as an advanced manufacturing technology,enables the production of personalized orthopedic implant devices with complex geometries that closely resemble bone structures.Titanium and its alloy...Additive manufacturing(AM),as an advanced manufacturing technology,enables the production of personalized orthopedic implant devices with complex geometries that closely resemble bone structures.Titanium and its alloys are extensively employed in biomedical fields like orthopedics and dentistry,thanks to the excellent compatibility with the human body and high corrosion resistance due to the existence of a thin protective oxide layer known as TiO_(2) upon exposure to oxygen on the surface.However,in joint inflammation,reactive oxygen species like hydrogen peroxide and radicals can damage the passive film on Ti implants,leading to their deterioration.Although AM technology for metallic implants is still developing,advancements in printing and new alloys are crucial for widespread use.This work aims to investigate the corrosion resistance of in-situ alloyed Ti536(Ti5Al3V6Cu)alloy produced through electron beam powder bed fusion(EB-PBF)under simulated peri-implant inflammatory conditions.The corrosion resistance was evaluated using electrochemical experiments conducted in the presence of 0.1%H_(2)O_(2) in a physiological saline solution(0.9%NaCl)to replicate the conditions that may occur during post-operative inflammation.The findings demonstrate that the micro-environment surrounding the implant during peri-implant inflammation is highly corrosive and can lead to the degradation of the TiO_(2) passive layer.Physiological saline with H_(2)O_(2) significantly increased biomaterial open circuit potential up to 0.36 mV vs.Ag/AgCl compared to physiological saline only.Potentiodynamic polarization(PDP)plots confirm this increase,as well.The PDP and electrochemical impedance spectroscopy(EIS)tests indicated that adding Cu does not impact the corrosion resistance of the Ti536 alloy initially under simulated inflammatory conditions,but prolonged immersion leads to enhanced corrosion resistance for all biomaterials tested,indicating the formation of an oxide layer after the reduction of the solution oxidizing power.These results suggest that modifying custom alloys by adding appropriate elements significantly enhances corrosion resistance,particularly in inflammatory conditions.展开更多
With the rapid advancement of robotics and Artificial Intelligence(AI),aerobics training companion robots now support eco-friendly fitness by reducing reliance on nonrenewable energy.This study presents a solar-powere...With the rapid advancement of robotics and Artificial Intelligence(AI),aerobics training companion robots now support eco-friendly fitness by reducing reliance on nonrenewable energy.This study presents a solar-powered aerobics training robot featuring an adaptive energy management system designed for sustainability and efficiency.The robot integrates machine vision with an enhanced Dynamic Cheetah Optimizer and Bayesian Neural Network(DynCO-BNN)to enable precise exercise monitoring and real-time feedback.Solar tracking technology ensures optimal energy absorption,while a microcontroller-based regulator manages power distribution and robotic movement.Dual-battery switching ensures uninterrupted operation,aided by light and I/V sensors for energy optimization.Using the INSIGHT-LME IMU dataset,which includes motion data from 76 individuals performing Local Muscular Endurance(LME)exercises,the system detects activities,counts repetitions,and recognizes human movements.To minimize energy use during data processing,Min-Max normalization and two-dimensional Discrete Fourier Transform(2D-DFT)are applied,boosting computational efficiency.The robot accurately identifies upper and lower limb movements,delivering effective exercise guidance.The DynCO-BNN model achieved a high tracking accuracy of 96.8%.Results confirm improved solar utilization,ecological sustainability,and reduced dependence on fossil fuels—positioning the robot as a smart,energy-efficient solution for next-generation fitness technology.展开更多
Atrium spaces,common in modern construction,provide significant fire safety challenges due to their large vertical openings,which facilitate rapid smoke spread and reduce sprinkler effectiveness.Traditional smoke mana...Atrium spaces,common in modern construction,provide significant fire safety challenges due to their large vertical openings,which facilitate rapid smoke spread and reduce sprinkler effectiveness.Traditional smoke management systems primarily rely on make-up air to replace the air expelled through vents.Inadequate calibration,particularly with air velocity,can worsen fire conditions by enhancing oxygen supply,increasing soot production,and reducing visibility,so endangering safe evacuation.This study investigates the impact of make-up air velocity on smoke behaviour in atrium environments through 24 simulations performed using the FireDynamics Simulator(FDS).Scenarios include various fire intensities(1,3,5 MW)and make-up air velocities(1–3.5 m/s),with fire sources located at the centre,northeast,and southwest corners.The simulation model was validated using updated full-scale fire test data with polystyrene fuel,leading to heightened soot density and reduced smoke clear height.This Research design diverges from other studies that predominantly utilized propane pool fires and concentrated on axisymmetric(Fire at the center of the atrum),Northeast and Southeast corners of the atrium scenarios by using polystyrene-a widely accessible construction material and examining several asymetric fire sites,so providing a more authentic depiction of atrium fire settings.Research reveals that increased air velocities,especially when directed at the fire,result in greater soot density and reduced smoke clearance due to intensified combustion.The northeastern region consistently displayed high temperature readings,highlighting the importance of fire source positioning in smoke behaviour.The study recommends limiting make-up air velocity to 1 m/s to avert turbulence and guarantee safety.This research provides critical insights for fire safety design and aligns with the United Nations Sustainable Development Goals,namely SDG 9 and SDG 11,by promoting safer and more resilient construction practices in urban environments.展开更多
Corporate environmental sustainability has become a critical concern,particularly in resource-intensive industries such as pharmaceuticals,where regulatory pressures and stakeholder expectations continue to rise.Despi...Corporate environmental sustainability has become a critical concern,particularly in resource-intensive industries such as pharmaceuticals,where regulatory pressures and stakeholder expectations continue to rise.Despite increasing attention to green leadership,limited research has explored how environmentally responsible leadership(ERL)influences corporate environmental performance(CEP)through employee-driven sustainability behaviors.This study addresses this gap by examining the mediating roles of green knowledge-sharing behavior(GKSB),green innovative behavior(GIB),and voluntary green behavior(VGB),as well as the moderating role of green shared vision(GSV)in the ERL-CEP relationship.The study is grounded in Resource-Based View(RBV),Knowledge-Based View(KBV),Environmental-Based View(EBV),and Triple Bottom Line(TBL)theories,which collectively explain how leadership-driven sustainability efforts create long-term competitive advantages,drive environmental responsibility,and balance economic,social,and environmental sustainability.A quantitative research design was employed,using survey data from 384 employees in Bangladesh’s pharmaceutical sector.Data were analyzed using Partial Least Squares Structural Equation Modeling(PLS-SEM)in Smart-PLS 4.0 to assess direct,indirect,and moderating effects.The results confirm that ERL has a significant positive impact on CEP,with GKSB,GIB,and VGB acting as mediators,while GSV strengthens the ERL-CEP relationship.This study provides novel empirical evidence on the mechanisms linking green leadership to corporate sustainability,extending the application of RBV,KBV,EBV,and TBL to leadership-driven environmental management.The findings emphasize the importance of leadership training programs,sustainability-focused organizational cultures,and shared environmental visions.Policymakers should consider incentives for companies adopting ERL practices,ensuring that sustainability becomes a strategic,rather than compliance-driven,priority.This study contributes to leadership and sustainability literature by offering a comprehensive framework for integrating ERL into corporate governance and environmental strategies.展开更多
This review aims to analyze the development and impact of Artificial Intelligence(AI)in the context of Saudi Arabia’s public healthcare system to fulfill Vision 2030 objectives.It is extensively devoted to AI technol...This review aims to analyze the development and impact of Artificial Intelligence(AI)in the context of Saudi Arabia’s public healthcare system to fulfill Vision 2030 objectives.It is extensively devoted to AI technology deployment relevant to disease management,healthcare delivery,epidemiology,and policy-making.However,its AI is culturally sensitive and ethically grounded in Islam.Based on the PRISMA framework,an SLR evaluated primary academic literature,cases,and practices of Saudi Arabia’s AI implementation in the public healthcare sector.Instead,it categorizes prior research based on how AI can work,the issues it poses,and its implications for the Kingdom’s healthcare system.The Saudi Arabian context analyses show that AI has increased the discreet prediction of diseases,resource management,and monitoring outbreaks during mass congregations such as hajj.Therefore,the study outlines critical areas for defining the potential for artificial intelligence and areas for enhancing digital development to support global healthcare progress.The key themes emerging from the review include Saudi Arabia:(i)the effectiveness of AI with human interaction for sustainable health services;(ii)conditions and quality control to enhance the quality of health care services using AI;(iii)environmental factors as influencing factors for public health care;(iv)Artificial Intelligence,and advanced decision-making technology for Middle Eastern health care systems.For policymakers,healthcare managers,and researchers who will engage with AI innovation,the review proclaims that AI applications should respect the country’s socio-cultural and ethical practices and pave the way for sustainable healthcare provision.More empirical research is needed on the implementation issues with AI,creating culturally appropriate models of AI,and finding new applications of AI to address the increasing demand for healthcare services in Saudi Arabia.展开更多
The increase in the population as a whole gradually requires solving the issues of continuous development of the agro-industrial complex in all directions and components.This development is accompanied by an increase ...The increase in the population as a whole gradually requires solving the issues of continuous development of the agro-industrial complex in all directions and components.This development is accompanied by an increase in energy consumption,in the total balance of which electricity occupies a significant share.The purpose of this study is to develop a mathematical model of the use of infrared means for heating agro-industrial premises,which affects the formation of energy-saving and energy-saving processes of enterprises.The agrarian potential of Ukraine was analyzed and compared with other countries of the world for awareness,analysis and relevant conclusions regarding energy consumption and frugality.This helped,based on calculations and foreign experience,to prove the effectiveness of the proposed mathematical model.And its empiric results of application in the form of the use of a copper plate allowed to prove efficiency due to the reduction of electricity consumption in the conditions of maintaining the temperature regime of industrial-type premises not higher than 22–26°C when the equipment is operating at an output power of 40 W.The results of the research are the development of the existing theoretical foundations of ensuring the effective use of energy resources in agricultural organizations and can be used by economic entities and regional authorities for the purpose of making informed decisions in the field of energy-saving policy development in the agricultural sector.展开更多
Ursodeoxycholic acid(UDCA)is a naturally occurring,low-toxicity,and hydrophilic bile acid(BA)in the human body that is converted by intestinal flora using primary BA.Solute carrier family 7 member 11(SLC7A11)functions...Ursodeoxycholic acid(UDCA)is a naturally occurring,low-toxicity,and hydrophilic bile acid(BA)in the human body that is converted by intestinal flora using primary BA.Solute carrier family 7 member 11(SLC7A11)functions to uptake extracellular cystine in exchange for glutamate,and is highly expressed in a variety of human cancers.Retroperitoneal liposarcoma(RLPS)refers to liposarcoma originating from the retroperitoneal area.Lipidomics analysis revealed that UDCA was one of the most significantly downregulated metabolites in sera of RLPS patients compared with healthy subjects.The augmentation of UDCA concentration(≥25 mg/mL)demonstrated a suppressive effect on the proliferation of liposarcoma cells.[15N2]-cystine and[13C5]-glutamine isotope tracing revealed that UDCA impairs cystine uptake and glutathione(GSH)synthesis.Mechanistically,UDCA binds to the cystine transporter SLC7A11 to inhibit cystine uptake and impair GSH de novo synthesis,leading to reactive oxygen species(ROS)accumulation and mitochondrial oxidative damage.Furthermore,UDCA can promote the anti-cancer effects of ferroptosis inducers(Erastin,RSL3),the murine double minute 2(MDM2)inhibitors(Nutlin 3a,RG7112),cyclin dependent kinase 4(CDK4)inhibitor(Abemaciclib),and glutaminase inhibitor(CB839).Together,UDCA functions as a cystine exchange factor that binds to SLC7A11 for antitumor activity,and SLC7A11 is not only a new transporter for BA but also a clinically applicable target for UDCA.More importantly,in combination with other antitumor chemotherapy or physiotherapy treatments,UDCA may provide effective and promising treatment strategies for RLPS or other types of tumors in a ROS-dependent manner.展开更多
Firstly,I point out the problems in the fruit supply chain management.Then through field survey,we know that busywork flow plays a very important role in the fruit supply chain management.I establish the mathematical ...Firstly,I point out the problems in the fruit supply chain management.Then through field survey,we know that busywork flow plays a very important role in the fruit supply chain management.I establish the mathematical model,to derive that the supply chain management of corporate procurement and supply network is the optimal economic model.In terms of the performance of supply chain,I draw the following conclusions:(i) Busywork flow can achieve the supply chain management,and reduces logistics costs in the whole process of circulation;(ii) Busywork flow can improve logistics services for the customers and reduces coordination costs;(iii) The establishment of modern information system can reduce logistics costs;(iv) Busywork flow can improve distribution efficiency and reduce costs;(v) Busywork flow can reduce and avoid the costs of return of goods;(vi) The operation of the busywork flow can achieve integrated transport and business outsourcing to third-party logistics,thereby reducing costs,reducing transport links,reasonably choosing the means of transport,formulating the optimal transportation plan,improving the mode of transport,and increasing the cargo loading amount.(vii) Busywork flow promotes the use of e-commerce.I also express my own views on upgrade version of corporate procurement and supply network.Finally I point out some problems in the existing corporate procurement and supply network,and put forward the following recommendations:developing township-level 4S fruit shop according to the business development,with the functions of purchasing apple,supplying means of agricultural production,providing technical services and developing market;building " corporate ecological orchard" through holding.展开更多
To achieve high performance and reliability in video streaming over wireless local area networks （WLANs）, one must jointly consider both optimized association to access points （APs） and handover management based o...To achieve high performance and reliability in video streaming over wireless local area networks （WLANs）, one must jointly consider both optimized association to access points （APs） and handover management based on dynamic scanning of alternate APs. In this article, we propose a new architecture within the software-defined networking （SDN） framework, which allows stations to be connected to several APs simultaneously and to switch fast between them. We evaluate our system in a real-time testbed and demonstrate that our SDN-based handover mechanism significantly reduces the number and duration of video freeze events and allows for smaller playout buffers.展开更多
Aircraft on ground or down-time for its maintenance is a clear loss in revenue for an airline operation. With never ending competition and growing operating costs of aircraft, airlines continuously need to explore opp...Aircraft on ground or down-time for its maintenance is a clear loss in revenue for an airline operation. With never ending competition and growing operating costs of aircraft, airlines continuously need to explore opportunities to reduce the aircraft down-time in order to remain sustainable. Due to round the clock operation feature of scheduled airlines, aircraft maintenance operations are generally carried out using traditional management methodologies instead of considering it as a project. Though aircraft heavy maintenance checks consist of several major tasks that can last from few weeks to a year, the maintenance organisations do not adopt modern project management methodologies. Therefore, this paper models a heavy maintenance check of an Airbus aircraft as a typical project and adopts contemporary project management methodology to explore the possibility of reducing the downtime. To this end, a case study has been done at an aircraft maintenance company to analyse the potential of this project management method in aircraft maintenance industry.展开更多
Indirect additive manufacturing(AM)methods have recently attracted attention from researchers thanks to their great potential for cheap,straightforward,and small-scale production of metallic components.Atomic diffusio...Indirect additive manufacturing(AM)methods have recently attracted attention from researchers thanks to their great potential for cheap,straightforward,and small-scale production of metallic components.Atomic diffusion additive manufacturing(ADAM),a variant of indirect AM methods,is a layer-wise indirect AM process recently developed based on fused deposition modeling and metal injection molding.However,there is still limited knowledge of the process conditions and material properties fabricated through this process,where sintering plays a crucial role in the final consolidation of parts.Therefore,this research,for the first time,systematically investigates the impact of various sintering conditions on the shrinkage,relative density,microstructure,and hardness of the 17-4PH ADAM samples.For this reason,as-washed samples were sintered under different time-temperature combinations.The sample density was evaluated using Archimedes,computed tomography,and image analysis methods.The outcomes revealed that sintering variables significantly impacted the density of brown 17-4PH Stainless Steel samples.The results indicated more than 99% relative densities,higher than the value reported by Markforged Inc.(~96%).Based on parallel porosities observed in the computed tomography results,it can be suggested that by modifying the infill pattern during printing,it would be possible to increase the final relative density.The microhardness of the sintered samples in this study was higher than that of the standard sample provided by Markforged Inc.Sintering at 1330℃ for 4 h increased the density of the printed sample without compromising its mechanical properties.According to X-ray diffraction analysis,the standard sample provided by Markforged Inc.and“1330℃—4 h”one had similar stable phases,although copper-rich intermetallics were more abundant in the microstructure of reference samples.This study is expected to facilitate the adoption of indirect metal AM methods by different sectors,thanks to the high achievable relative densities reported here.展开更多
Recent research and studies have shown that Information Technology(IT)has a significant impact on service quality,customer satisfaction,and customer relationship development.With the proliferation and penetration of t...Recent research and studies have shown that Information Technology(IT)has a significant impact on service quality,customer satisfaction,and customer relationship development.With the proliferation and penetration of technology in all aspects of life,organizations are responding to the implications and opportunities that IT creates in relation to customer services.The main objective of using information technology in organizations is to increase customer satisfaction,service quality,and customer relationship management,which the authors will focus on here.Enhancing service quality,improving customer satisfaction,and establishing close and sustainable customer relationships are key advantages of leveraging information technology in this field.This article examines the impact of information technology on service quality,customer satisfaction,and customer relationship development and provides strategies and models for organizations to improve customer satisfaction and establish closer connections with them through the use of information technology.Seventy individuals from the IT field were used to evaluate the proposed model.The proposed model was compared with three models:SEM,regression,and decision tree,and the results demonstrated better performance of this approach.展开更多
Revealing the oxidation behavior of superalloys is crucial for optimizing material properties and extending service life.This study investigated the oxidation behavior of superalloy GH4738 under stress states at 850℃...Revealing the oxidation behavior of superalloys is crucial for optimizing material properties and extending service life.This study investigated the oxidation behavior of superalloy GH4738 under stress states at 850℃.High-throughput specimens were fabricated to withstand different stresses at the same time.Isothermal oxidation s amples were analyzed using the mass gain method to obtain oxidation kinetic curves.The results show that the external stress below 200 MPa could improve the oxidation resistance of the GH4738.With tensile stress increasing,the oxide layer becomes thinner,denser and more complete,while internal oxidation decreases.The tensile stress alters the structure of the external oxide layer from a two-layer to a threelayer configuration.The Cr_(2)O_(3) oxide layer inhibits the outward diffusion of Ti,leading to Ti enrichment at the oxide-matrix interface and altering the oxidation mechanism of GH4738.展开更多
文摘Traffic forecasting with high precision aids Intelligent Transport Systems(ITS)in formulating and optimizing traffic management strategies.The algorithms used for tuning the hyperparameters of the deep learning models often have accurate results at the expense of high computational complexity.To address this problem,this paper uses the Tree-structured Parzen Estimator(TPE)to tune the hyperparameters of the Long Short-term Memory(LSTM)deep learning framework.The Tree-structured Parzen Estimator(TPE)uses a probabilistic approach with an adaptive searching mechanism by classifying the objective function values into good and bad samples.This ensures fast convergence in tuning the hyperparameter values in the deep learning model for performing prediction while still maintaining a certain degree of accuracy.It also overcomes the problem of converging to local optima and avoids timeconsuming random search and,therefore,avoids high computational complexity in prediction accuracy.The proposed scheme first performs data smoothing and normalization on the input data,which is then fed to the input of the TPE for tuning the hyperparameters.The traffic data is then input to the LSTM model with tuned parameters to perform the traffic prediction.The three optimizers:Adaptive Moment Estimation(Adam),Root Mean Square Propagation(RMSProp),and Stochastic Gradient Descend with Momentum(SGDM)are also evaluated for accuracy prediction and the best optimizer is then chosen for final traffic prediction in TPE-LSTM model.Simulation results verify the effectiveness of the proposed model in terms of accuracy of prediction over the benchmark schemes.
基金supported by the National Natural Science Foundation of China(No.71501183).
文摘In order to solve the problems of high experimental cost of ammunition,lack of field test data,and the difficulty in applying the ammunition hit probability estimation method in classical statistics,this paper assumes that the projectile dispersion of ammunition is a two-dimensional joint normal distribution,and proposes a new Bayesian inference method of ammunition hit probability based on normal-inverse Wishart distribution.Firstly,the conjugate joint prior distribution of the projectile dispersion characteristic parameters is determined to be a normal inverse Wishart distribution,and the hyperparameters in the prior distribution are estimated by simulation experimental data and historical measured data.Secondly,the field test data is integrated with the Bayesian formula to obtain the joint posterior distribution of the projectile dispersion characteristic parameters,and then the hit probability of the ammunition is estimated.Finally,compared with the binomial distribution method,the method in this paper can consider the dispersion information of ammunition projectiles,and the hit probability information is more fully utilized.The hit probability results are closer to the field shooting test samples.This method has strong applicability and is conducive to obtaining more accurate hit probability estimation results.
文摘Mongolia is a landlocked country with limited infrastructure and high dependence on the Xingang Tianjin port in China for imports. This research examines the potential impacts of establishing a dry port in Zamyn-Uud, Mongolia, utilizing a system dynamics modeling approach via Vensim software. The study evaluates transportation time, costs, inflation, and logistics performance index improvements, revealing that the establishment of the dry port can reduce transportation costs and delays significantly while enhancing economic growth. The findings offer actionable insights for policymakers and stakeholders in addressing logistical inefficiencies and fostering sustainable development in landlocked regions.
文摘Background:The rapid integration of generative artificial intelligence(genAI)into medical education offers significant opportunities for personalized learning,efficiency,and access.However,its implementation also raises complex ethical concerns that,if unaddressed,may compromise academic integrity,professional identity,and learner equity.This review aimed to identify the primary ethical risks associated with genAI use in medical education and propose solid measures to mitigate these issues.Methods:A structured narrative review was conducted in accordance with the Scale for the Assessment of Narrative Review Articles(SANRA).A focused literature search was performed across PubMed/MEDLINE and Google Scholar for peer-reviewed,English-language articles published from January 2023 to May 2025.Studies were included if they addressed ethical issues in the use of genAI in undergraduate or postgraduate medical education.Data were extracted into related themes,and findings were synthesized into risk and mitigation categories.Results:A total of 27 records were included.Eight principal categories of ethical risks associated with genAI in medical education emerged:(1)academic integrity erosion,(2)cognitive deskilling,(3)algorithmic bias and opacity,(4)privacy and surveillance concerns,(5)moral and humanistic diminishment,(6)faculty role displacement,(7)commercialization and inequity,and(8)legal-regulatory ambiguity.Each risk was matched with targeted mitigation strategies proposed in the literature,including institutional genAI governance frameworks,genAI literacy training,reinforcement of humanistic pedagogy,establishment of ethical oversight bodies,curricular integration of ethical reflexivity,equity-centered implementation policies,faculty development for genAI integration,and transparent data governance protocols.Conclusion:Generative AI presents both transformative promise and substantial ethical risks in medical education.Proactive,ethically grounded integration-guided by institutional oversight,curriculum reform,and equity safeguards-is essential to realize its benefits while protecting the integrity and humanity of medical training.
文摘The increasing global demand for energy,coupled with concerns about environmental sustainability,has underscored the need for a transition toward renewable energy sources.A well-structured teaching program under the framework of sustainable development in renewable energy seeks to give students the information,abilities,and critical thinking needed to solve energy-related problems sustainably.This research proposes AI-powered personalized learning,innovative real-time integration of diverse data,and adaptive teaching strategies to enhance student understanding regarding renewable energy concepts.The sheep flock-optimized innovative recurrent neural network(SFO-IRNN)will recommend relevant topics and resources based on students’performance.Renewable energy teaching data from assessmethments are combined with real-time IoT-based renewable energy data.This dataset contains renewable energy education using AI-driven teaching methods and internet-based learning.The data was preprocessed by handling missing values and min-max scaling.The data features were extracted using Fourier Transform(FT).Further application of 10-fold cross-validation will increase the reliability of the model as it can evaluate its performance metrics like accuracy,F1-score,recall,and precision on different subsets of student data,which improves its robustness and prevents overfitting.The findings showed that the proposed method is significantly better,which ensures that the students have a deeper theoretical and practical understanding of renewable energy technologies.In addition,integrating real-time IoT data from renewable energy sources gives students a chance to do live simulations and problems that would enhance analytical thinking and hands-on learning.The research shows that AI provides context-aware guidance on sustainable energy infrastructure,enhancing interactive and personalized learning.
文摘Additive manufacturing(AM)has emerged as one of the most utilized processes in manufacturing due to its ability to produce complex geometries with minimal material waste and greater design freedom.Laser-based AM(LAM)technologies use high-power lasers to melt metallic materials,which then solidify to form parts.However,it inherently induces self-equilibrating residual stress during fabrication due to thermal loads and plastic deformation.These residual stresses can cause defects such as delamination,cracking,and distortion,as well as premature failure under service conditions,necessitating mitigation.While post-treatment methods can reduce residual stresses,they are often costly and time-consuming.Therefore,tuning the fabrication process parameters presents a more feasible approach.Accordingly,in addition to providing a comprehensive view of residual stress by their classification,formation mechanisms,measurement methods,and common post-treatment,this paper reviews and compares the studies conducted on the effect of key parameters of the LAM process on the resulting residual stresses.This review focuses on proactively adjusting LAM process parameters as a strategic approach to mitigate residual stress formation.It provides a result of the various parameters influencing residual stress outcomes,such as laser power,scanning speed,beam diameter,hatch spacing,and scanning strategies.Finally,the paper identifies existing research gaps and proposes future studies needed to deepen understanding of the relationship between process parameters and residual stress mitigation in LAM.
基金Open access funding provided by Politecnico di Torino within the CRUI-CARE Agreement.
文摘Additive manufacturing(AM),as an advanced manufacturing technology,enables the production of personalized orthopedic implant devices with complex geometries that closely resemble bone structures.Titanium and its alloys are extensively employed in biomedical fields like orthopedics and dentistry,thanks to the excellent compatibility with the human body and high corrosion resistance due to the existence of a thin protective oxide layer known as TiO_(2) upon exposure to oxygen on the surface.However,in joint inflammation,reactive oxygen species like hydrogen peroxide and radicals can damage the passive film on Ti implants,leading to their deterioration.Although AM technology for metallic implants is still developing,advancements in printing and new alloys are crucial for widespread use.This work aims to investigate the corrosion resistance of in-situ alloyed Ti536(Ti5Al3V6Cu)alloy produced through electron beam powder bed fusion(EB-PBF)under simulated peri-implant inflammatory conditions.The corrosion resistance was evaluated using electrochemical experiments conducted in the presence of 0.1%H_(2)O_(2) in a physiological saline solution(0.9%NaCl)to replicate the conditions that may occur during post-operative inflammation.The findings demonstrate that the micro-environment surrounding the implant during peri-implant inflammation is highly corrosive and can lead to the degradation of the TiO_(2) passive layer.Physiological saline with H_(2)O_(2) significantly increased biomaterial open circuit potential up to 0.36 mV vs.Ag/AgCl compared to physiological saline only.Potentiodynamic polarization(PDP)plots confirm this increase,as well.The PDP and electrochemical impedance spectroscopy(EIS)tests indicated that adding Cu does not impact the corrosion resistance of the Ti536 alloy initially under simulated inflammatory conditions,but prolonged immersion leads to enhanced corrosion resistance for all biomaterials tested,indicating the formation of an oxide layer after the reduction of the solution oxidizing power.These results suggest that modifying custom alloys by adding appropriate elements significantly enhances corrosion resistance,particularly in inflammatory conditions.
文摘With the rapid advancement of robotics and Artificial Intelligence(AI),aerobics training companion robots now support eco-friendly fitness by reducing reliance on nonrenewable energy.This study presents a solar-powered aerobics training robot featuring an adaptive energy management system designed for sustainability and efficiency.The robot integrates machine vision with an enhanced Dynamic Cheetah Optimizer and Bayesian Neural Network(DynCO-BNN)to enable precise exercise monitoring and real-time feedback.Solar tracking technology ensures optimal energy absorption,while a microcontroller-based regulator manages power distribution and robotic movement.Dual-battery switching ensures uninterrupted operation,aided by light and I/V sensors for energy optimization.Using the INSIGHT-LME IMU dataset,which includes motion data from 76 individuals performing Local Muscular Endurance(LME)exercises,the system detects activities,counts repetitions,and recognizes human movements.To minimize energy use during data processing,Min-Max normalization and two-dimensional Discrete Fourier Transform(2D-DFT)are applied,boosting computational efficiency.The robot accurately identifies upper and lower limb movements,delivering effective exercise guidance.The DynCO-BNN model achieved a high tracking accuracy of 96.8%.Results confirm improved solar utilization,ecological sustainability,and reduced dependence on fossil fuels—positioning the robot as a smart,energy-efficient solution for next-generation fitness technology.
文摘Atrium spaces,common in modern construction,provide significant fire safety challenges due to their large vertical openings,which facilitate rapid smoke spread and reduce sprinkler effectiveness.Traditional smoke management systems primarily rely on make-up air to replace the air expelled through vents.Inadequate calibration,particularly with air velocity,can worsen fire conditions by enhancing oxygen supply,increasing soot production,and reducing visibility,so endangering safe evacuation.This study investigates the impact of make-up air velocity on smoke behaviour in atrium environments through 24 simulations performed using the FireDynamics Simulator(FDS).Scenarios include various fire intensities(1,3,5 MW)and make-up air velocities(1–3.5 m/s),with fire sources located at the centre,northeast,and southwest corners.The simulation model was validated using updated full-scale fire test data with polystyrene fuel,leading to heightened soot density and reduced smoke clear height.This Research design diverges from other studies that predominantly utilized propane pool fires and concentrated on axisymmetric(Fire at the center of the atrum),Northeast and Southeast corners of the atrium scenarios by using polystyrene-a widely accessible construction material and examining several asymetric fire sites,so providing a more authentic depiction of atrium fire settings.Research reveals that increased air velocities,especially when directed at the fire,result in greater soot density and reduced smoke clearance due to intensified combustion.The northeastern region consistently displayed high temperature readings,highlighting the importance of fire source positioning in smoke behaviour.The study recommends limiting make-up air velocity to 1 m/s to avert turbulence and guarantee safety.This research provides critical insights for fire safety design and aligns with the United Nations Sustainable Development Goals,namely SDG 9 and SDG 11,by promoting safer and more resilient construction practices in urban environments.
文摘Corporate environmental sustainability has become a critical concern,particularly in resource-intensive industries such as pharmaceuticals,where regulatory pressures and stakeholder expectations continue to rise.Despite increasing attention to green leadership,limited research has explored how environmentally responsible leadership(ERL)influences corporate environmental performance(CEP)through employee-driven sustainability behaviors.This study addresses this gap by examining the mediating roles of green knowledge-sharing behavior(GKSB),green innovative behavior(GIB),and voluntary green behavior(VGB),as well as the moderating role of green shared vision(GSV)in the ERL-CEP relationship.The study is grounded in Resource-Based View(RBV),Knowledge-Based View(KBV),Environmental-Based View(EBV),and Triple Bottom Line(TBL)theories,which collectively explain how leadership-driven sustainability efforts create long-term competitive advantages,drive environmental responsibility,and balance economic,social,and environmental sustainability.A quantitative research design was employed,using survey data from 384 employees in Bangladesh’s pharmaceutical sector.Data were analyzed using Partial Least Squares Structural Equation Modeling(PLS-SEM)in Smart-PLS 4.0 to assess direct,indirect,and moderating effects.The results confirm that ERL has a significant positive impact on CEP,with GKSB,GIB,and VGB acting as mediators,while GSV strengthens the ERL-CEP relationship.This study provides novel empirical evidence on the mechanisms linking green leadership to corporate sustainability,extending the application of RBV,KBV,EBV,and TBL to leadership-driven environmental management.The findings emphasize the importance of leadership training programs,sustainability-focused organizational cultures,and shared environmental visions.Policymakers should consider incentives for companies adopting ERL practices,ensuring that sustainability becomes a strategic,rather than compliance-driven,priority.This study contributes to leadership and sustainability literature by offering a comprehensive framework for integrating ERL into corporate governance and environmental strategies.
基金funded by the Scientific ResearchDeanship at theUniversity ofHa’il-Saudi Arabia through project number-RG-23251.
文摘This review aims to analyze the development and impact of Artificial Intelligence(AI)in the context of Saudi Arabia’s public healthcare system to fulfill Vision 2030 objectives.It is extensively devoted to AI technology deployment relevant to disease management,healthcare delivery,epidemiology,and policy-making.However,its AI is culturally sensitive and ethically grounded in Islam.Based on the PRISMA framework,an SLR evaluated primary academic literature,cases,and practices of Saudi Arabia’s AI implementation in the public healthcare sector.Instead,it categorizes prior research based on how AI can work,the issues it poses,and its implications for the Kingdom’s healthcare system.The Saudi Arabian context analyses show that AI has increased the discreet prediction of diseases,resource management,and monitoring outbreaks during mass congregations such as hajj.Therefore,the study outlines critical areas for defining the potential for artificial intelligence and areas for enhancing digital development to support global healthcare progress.The key themes emerging from the review include Saudi Arabia:(i)the effectiveness of AI with human interaction for sustainable health services;(ii)conditions and quality control to enhance the quality of health care services using AI;(iii)environmental factors as influencing factors for public health care;(iv)Artificial Intelligence,and advanced decision-making technology for Middle Eastern health care systems.For policymakers,healthcare managers,and researchers who will engage with AI innovation,the review proclaims that AI applications should respect the country’s socio-cultural and ethical practices and pave the way for sustainable healthcare provision.More empirical research is needed on the implementation issues with AI,creating culturally appropriate models of AI,and finding new applications of AI to address the increasing demand for healthcare services in Saudi Arabia.
文摘The increase in the population as a whole gradually requires solving the issues of continuous development of the agro-industrial complex in all directions and components.This development is accompanied by an increase in energy consumption,in the total balance of which electricity occupies a significant share.The purpose of this study is to develop a mathematical model of the use of infrared means for heating agro-industrial premises,which affects the formation of energy-saving and energy-saving processes of enterprises.The agrarian potential of Ukraine was analyzed and compared with other countries of the world for awareness,analysis and relevant conclusions regarding energy consumption and frugality.This helped,based on calculations and foreign experience,to prove the effectiveness of the proposed mathematical model.And its empiric results of application in the form of the use of a copper plate allowed to prove efficiency due to the reduction of electricity consumption in the conditions of maintaining the temperature regime of industrial-type premises not higher than 22–26°C when the equipment is operating at an output power of 40 W.The results of the research are the development of the existing theoretical foundations of ensuring the effective use of energy resources in agricultural organizations and can be used by economic entities and regional authorities for the purpose of making informed decisions in the field of energy-saving policy development in the agricultural sector.
基金supported by grants from the National Natural Science Foundation of China(Grant NOs.:82272935,91957120 and 21974114)the Postdoctoral Fellowship Program of CPSF(Program No.:GZC20240901)+5 种基金the Xiamen Medical Industry Combined Guidance Project,China(Project No.:3502Z20244ZD2022)the Scientific Research Foundation for Advanced Talents,Xiang'an Hospital of Xiamen University,China(Grant No.:PM20180917008)the Fundamental Research Funds for the Central Universities,China(Grant No.:20720210001)Major Science and Technology Special Project of Fujian Province,China(Project No.:2022YZ036012)Joint Laboratory of School of Medicine,Xiamen University-Shanghai Jiangxia Blood Technology Co.,Ltd.,China(Grant No.:XDHT2020010C)Joint Research Center of School of Medicine,Xiamen University-Jiangsu Charity Biotech Co.,Ltd.,China(Grant No.:20233160C0002).
文摘Ursodeoxycholic acid(UDCA)is a naturally occurring,low-toxicity,and hydrophilic bile acid(BA)in the human body that is converted by intestinal flora using primary BA.Solute carrier family 7 member 11(SLC7A11)functions to uptake extracellular cystine in exchange for glutamate,and is highly expressed in a variety of human cancers.Retroperitoneal liposarcoma(RLPS)refers to liposarcoma originating from the retroperitoneal area.Lipidomics analysis revealed that UDCA was one of the most significantly downregulated metabolites in sera of RLPS patients compared with healthy subjects.The augmentation of UDCA concentration(≥25 mg/mL)demonstrated a suppressive effect on the proliferation of liposarcoma cells.[15N2]-cystine and[13C5]-glutamine isotope tracing revealed that UDCA impairs cystine uptake and glutathione(GSH)synthesis.Mechanistically,UDCA binds to the cystine transporter SLC7A11 to inhibit cystine uptake and impair GSH de novo synthesis,leading to reactive oxygen species(ROS)accumulation and mitochondrial oxidative damage.Furthermore,UDCA can promote the anti-cancer effects of ferroptosis inducers(Erastin,RSL3),the murine double minute 2(MDM2)inhibitors(Nutlin 3a,RG7112),cyclin dependent kinase 4(CDK4)inhibitor(Abemaciclib),and glutaminase inhibitor(CB839).Together,UDCA functions as a cystine exchange factor that binds to SLC7A11 for antitumor activity,and SLC7A11 is not only a new transporter for BA but also a clinically applicable target for UDCA.More importantly,in combination with other antitumor chemotherapy or physiotherapy treatments,UDCA may provide effective and promising treatment strategies for RLPS or other types of tumors in a ROS-dependent manner.
文摘Firstly,I point out the problems in the fruit supply chain management.Then through field survey,we know that busywork flow plays a very important role in the fruit supply chain management.I establish the mathematical model,to derive that the supply chain management of corporate procurement and supply network is the optimal economic model.In terms of the performance of supply chain,I draw the following conclusions:(i) Busywork flow can achieve the supply chain management,and reduces logistics costs in the whole process of circulation;(ii) Busywork flow can improve logistics services for the customers and reduces coordination costs;(iii) The establishment of modern information system can reduce logistics costs;(iv) Busywork flow can improve distribution efficiency and reduce costs;(v) Busywork flow can reduce and avoid the costs of return of goods;(vi) The operation of the busywork flow can achieve integrated transport and business outsourcing to third-party logistics,thereby reducing costs,reducing transport links,reasonably choosing the means of transport,formulating the optimal transportation plan,improving the mode of transport,and increasing the cargo loading amount.(vii) Busywork flow promotes the use of e-commerce.I also express my own views on upgrade version of corporate procurement and supply network.Finally I point out some problems in the existing corporate procurement and supply network,and put forward the following recommendations:developing township-level 4S fruit shop according to the business development,with the functions of purchasing apple,supplying means of agricultural production,providing technical services and developing market;building " corporate ecological orchard" through holding.
文摘To achieve high performance and reliability in video streaming over wireless local area networks （WLANs）, one must jointly consider both optimized association to access points （APs） and handover management based on dynamic scanning of alternate APs. In this article, we propose a new architecture within the software-defined networking （SDN） framework, which allows stations to be connected to several APs simultaneously and to switch fast between them. We evaluate our system in a real-time testbed and demonstrate that our SDN-based handover mechanism significantly reduces the number and duration of video freeze events and allows for smaller playout buffers.
文摘Aircraft on ground or down-time for its maintenance is a clear loss in revenue for an airline operation. With never ending competition and growing operating costs of aircraft, airlines continuously need to explore opportunities to reduce the aircraft down-time in order to remain sustainable. Due to round the clock operation feature of scheduled airlines, aircraft maintenance operations are generally carried out using traditional management methodologies instead of considering it as a project. Though aircraft heavy maintenance checks consist of several major tasks that can last from few weeks to a year, the maintenance organisations do not adopt modern project management methodologies. Therefore, this paper models a heavy maintenance check of an Airbus aircraft as a typical project and adopts contemporary project management methodology to explore the possibility of reducing the downtime. To this end, a case study has been done at an aircraft maintenance company to analyse the potential of this project management method in aircraft maintenance industry.
文摘Indirect additive manufacturing(AM)methods have recently attracted attention from researchers thanks to their great potential for cheap,straightforward,and small-scale production of metallic components.Atomic diffusion additive manufacturing(ADAM),a variant of indirect AM methods,is a layer-wise indirect AM process recently developed based on fused deposition modeling and metal injection molding.However,there is still limited knowledge of the process conditions and material properties fabricated through this process,where sintering plays a crucial role in the final consolidation of parts.Therefore,this research,for the first time,systematically investigates the impact of various sintering conditions on the shrinkage,relative density,microstructure,and hardness of the 17-4PH ADAM samples.For this reason,as-washed samples were sintered under different time-temperature combinations.The sample density was evaluated using Archimedes,computed tomography,and image analysis methods.The outcomes revealed that sintering variables significantly impacted the density of brown 17-4PH Stainless Steel samples.The results indicated more than 99% relative densities,higher than the value reported by Markforged Inc.(~96%).Based on parallel porosities observed in the computed tomography results,it can be suggested that by modifying the infill pattern during printing,it would be possible to increase the final relative density.The microhardness of the sintered samples in this study was higher than that of the standard sample provided by Markforged Inc.Sintering at 1330℃ for 4 h increased the density of the printed sample without compromising its mechanical properties.According to X-ray diffraction analysis,the standard sample provided by Markforged Inc.and“1330℃—4 h”one had similar stable phases,although copper-rich intermetallics were more abundant in the microstructure of reference samples.This study is expected to facilitate the adoption of indirect metal AM methods by different sectors,thanks to the high achievable relative densities reported here.
文摘Recent research and studies have shown that Information Technology(IT)has a significant impact on service quality,customer satisfaction,and customer relationship development.With the proliferation and penetration of technology in all aspects of life,organizations are responding to the implications and opportunities that IT creates in relation to customer services.The main objective of using information technology in organizations is to increase customer satisfaction,service quality,and customer relationship management,which the authors will focus on here.Enhancing service quality,improving customer satisfaction,and establishing close and sustainable customer relationships are key advantages of leveraging information technology in this field.This article examines the impact of information technology on service quality,customer satisfaction,and customer relationship development and provides strategies and models for organizations to improve customer satisfaction and establish closer connections with them through the use of information technology.Seventy individuals from the IT field were used to evaluate the proposed model.The proposed model was compared with three models:SEM,regression,and decision tree,and the results demonstrated better performance of this approach.
基金financially supported by the National Key R&D Program of China(No.2021YFB3700401)Shandong Provincial Natural Science Foundation for Youths(No.ZR2022QE234)+1 种基金Zhejiang Provincial Natural Science Foundation(No.LQ21E030002)the Youth Innovation team Project of Higher Education Institutions in Shandong Province(No.2022KJ272)。
文摘Revealing the oxidation behavior of superalloys is crucial for optimizing material properties and extending service life.This study investigated the oxidation behavior of superalloy GH4738 under stress states at 850℃.High-throughput specimens were fabricated to withstand different stresses at the same time.Isothermal oxidation s amples were analyzed using the mass gain method to obtain oxidation kinetic curves.The results show that the external stress below 200 MPa could improve the oxidation resistance of the GH4738.With tensile stress increasing,the oxide layer becomes thinner,denser and more complete,while internal oxidation decreases.The tensile stress alters the structure of the external oxide layer from a two-layer to a threelayer configuration.The Cr_(2)O_(3) oxide layer inhibits the outward diffusion of Ti,leading to Ti enrichment at the oxide-matrix interface and altering the oxidation mechanism of GH4738.
