Minimum quantity lubrication(MQL),as a new sustainable and eco-friendly alternative cooling/lubrication technology that addresses the limitations of dry and wet machining,utilizes a small amount of lubricant or coolan...Minimum quantity lubrication(MQL),as a new sustainable and eco-friendly alternative cooling/lubrication technology that addresses the limitations of dry and wet machining,utilizes a small amount of lubricant or coolant to reduce friction,tool wear,and heat during cutting processes.MQL technique has witnessed significant developments in recent years,such as combining MQL with other sustainable techniques to achieve optimum results,using biodegradable lubricants,and innovations in nozzle designs and delivery methods.This review presents an in-depth analysis of machining characteristics(e.g.,cutting forces,temperature,tool wear,chip morphology and surface integrity,etc.)and sustainability characteristics(e.g.,energy consumption,carbon emissions,processing time,machining cost,etc.)of conventional MQL and hybrid MQL techniques like cryogenic MQL,Ranque-Hilsch vortex tube MQL,nanofluids MQL,hybrid nanofluid MQL and ultrasonic vibration assisted MQL in machining of aeronautical materials.Subsequently,the latest research and developments are analyzed and summarized in the field of MQL,and provide a detailed comparison between each technique,considering advantages,challenges,and limitations in practical implementation.In addition,this review serves as a valuable source for researchers and engineers to optimize machining processes while minimizing environmental impact and operational costs.Ultimately,the potential future aspects of MQL for research and industrial execution are discussed.展开更多
Nano-zinc oxides(ZnO)demonstrate remarkable antibacterial properties.To further enhance the corrosion resistance and antibacterial efficiency of magnesium alloy micro-arc oxidation(MAO)coatings,this study investigates...Nano-zinc oxides(ZnO)demonstrate remarkable antibacterial properties.To further enhance the corrosion resistance and antibacterial efficiency of magnesium alloy micro-arc oxidation(MAO)coatings,this study investigates the preparation of ZnO-containing micro-arc oxidation coatings with dual functionality by incorporating nano-ZnO into MAO electrolyte.The influence of varying ZnO concentrations on the microstructure,corrosion resistance,and antibacterial properties of the coating was examined through microstructure analysis,immersion tests,electrochemical experiments,and antibacterial assays.The findings revealed that the addition of nano-ZnO significantly enhanced the corrosion resistance of the MAO-coated alloy.Specifically,when the ZnO concentration in the electrolyte was 5 g/L,the corrosion rate was more than ten times lower compared to the MAO coatings without ZnO.Moreover,the antibacterial efficacy of ZnO+MAO coating,prepared with a ZnO concentration of 5 g/L,surpassed 95%after 24 h of co-culturing with Staphylococcus aureus(S.aureus).The nano-ZnO+MAO-coated alloy exhibited exceptional degradation resistance,corrosion resistance,and antibacterial effectiveness.展开更多
Neodymium chromium oxide(NdCrO_(3))and NdCrO_(3)/graphene oxide(GO)nanocomposite were synthesized via sol-gel and co-precipitation techniques for being used in high-perfo rmance supercapacitors and for the possible ap...Neodymium chromium oxide(NdCrO_(3))and NdCrO_(3)/graphene oxide(GO)nanocomposite were synthesized via sol-gel and co-precipitation techniques for being used in high-perfo rmance supercapacitors and for the possible application in ultraviolet(UV)materials.Herein the systematic synthesis approach was adopted,which enhances the optical and electrical properties of the grown wide band-gap composite nanomaterial.Structural characterization of the grown materials was attempted using X-ray diffraction(XRD)and scanning electron microscopy(SEM).Most importantly the electrochemical analysis of the grown samples was carried out by employing a glassy carbon electrode and 3 mol/L KOH electrolyte,which demonstrates significant improvements in a specific capacitance of approximately360 F/g,an energy density of approximately 18 Wh/kg,and a maximum power density of approximately 257 W/kg,respectively.Moreover,NdCrO_(3)/GO nanocomposite maintains a cyclic stability of 97.6%after4000 cycles.Photoluminescence(PL)spectroscopy confirms the wide bandgap nature of the NdCrO_(3)and NdCrO_(3)/GO nanocomposite,indicating its potential application in UVC devices.These findings emphasize the potential of the NdCrO_(3)/GO nanocomposite in advancing efficient energy storage solutions and the possibility of being used in UVC technology.展开更多
Hard carbon(HC)is broadly recognized as an exceptionally prospective candidate for the anodes of sodium-ion batteries(SIBs),but their practical implementation faces substantial limitations linked to precursor factors,...Hard carbon(HC)is broadly recognized as an exceptionally prospective candidate for the anodes of sodium-ion batteries(SIBs),but their practical implementation faces substantial limitations linked to precursor factors,such as reduced carbon yield and increased cost.Herein,a cost-effective approach is proposed to prepare a coal-derived HC anode with simple pre-oxidation followed by a post-carbonization process which effectively expands the d_(002)layer spacing,generates closed pores and increases defect sites.Through these modifications,the resulting HC anode attains a delicate equilibrium between plateau capacity and sloping capacity,showcasing a remarkable reversible capacity of 306.3 mAh·g^(-1)at 0.03 A·g^(-1).Furthermore,the produ ced HC exhibits fast reaction kinetics and exceptional rate performance,achieving a capacity of 289 mAh·g^(-1)at 0.1 A·g^(-1),equivalent to~94.5%of that at 0.03 A·g^(-1).When implemented in a full cell configuration,the impressive electrochemical performance is evident,with a notable energy density of 410.6 Wh·kg^(-1)(based on cathode mass).In short,we provide a straightforward yet efficient method for regulating coal-derived HC,which is crucial for the widespread use of SIBs anodes.展开更多
This research systematically examined the degradation,antibacterial effects,and biocompatibility of micro-arc oxidation(MAO)coatings with nano CuO and ZnO on extruded Mg alloys.Both copper(Cu)and Zinc(Zn)possess antib...This research systematically examined the degradation,antibacterial effects,and biocompatibility of micro-arc oxidation(MAO)coatings with nano CuO and ZnO on extruded Mg alloys.Both copper(Cu)and Zinc(Zn)possess antibacterial properties.The findings demonstrated that adding ZnO will appreciably reduce the degradation rate of MAO-coating alloy due to the self-sealing micro holes.CuO+MAO coating exhibited excellent antibacterial performance,with an antibacterial rate of over 90%within 6 h co-cultured with Staphylococcus aureus.Similarly,the antibacterial rate of ZnO+MAO coating reached 90%after 12 h co-culture.Cytotoxicity test using MG63 cell indicated that the incorporation of CuO and ZnO did not notably affect the cell viability rate of the coating.Moreover,after 14 days of culture,the CuO+MAO and ZnO+MAO coated samples exhibited higher alkaline phosphatase(ALP)activity than the MAO-coated and uncoated samples,suggesting favorable osteogenic properties.展开更多
Routine immunization(RI)of children is the most effective and timely public health intervention for decreasing child mortality rates around the globe.Pakistan being a low-and-middle-income-country(LMIC)has one of the ...Routine immunization(RI)of children is the most effective and timely public health intervention for decreasing child mortality rates around the globe.Pakistan being a low-and-middle-income-country(LMIC)has one of the highest child mortality rates in the world occurring mainly due to vaccine-preventable diseases(VPDs).For improving RI coverage,a critical need is to establish potential RI defaulters at an early stage,so that appropriate interventions can be targeted towards such populationwho are identified to be at risk of missing on their scheduled vaccine uptakes.In this paper,a machine learning(ML)based predictivemodel has been proposed to predict defaulting and non-defaulting children on upcoming immunization visits and examine the effect of its underlying contributing factors.The predictivemodel uses data obtained from Paigham-e-Sehat study having immunization records of 3,113 children.The design of predictive model is based on obtaining optimal results across accuracy,specificity,and sensitivity,to ensure model outcomes remain practically relevant to the problem addressed.Further optimization of predictive model is obtained through selection of significant features and removing data bias.Nine machine learning algorithms were applied for prediction of defaulting children for the next immunization visit.The results showed that the random forest model achieves the optimal accuracy of 81.9%with 83.6%sensitivity and 80.3%specificity.The main determinants of vaccination coverage were found to be vaccine coverage at birth,parental education,and socioeconomic conditions of the defaulting group.This information can assist relevant policy makers to take proactive and effective measures for developing evidence based targeted and timely interventions for defaulting children.展开更多
Domain shift is when the data used in training does not match the ones it will be applied to later on under similar conditions.Domain shift will reduce accuracy in results.To prevent this,domain adaptation is done,whi...Domain shift is when the data used in training does not match the ones it will be applied to later on under similar conditions.Domain shift will reduce accuracy in results.To prevent this,domain adaptation is done,which adapts the pre-trained model to the target domain.In real scenarios,the availability of labels for target data is rare thus resulting in unsupervised domain adaptation.Herein,we propose an innovative approach where source-free domain adaptation models and Generative Adversarial Networks(GANs)are integrated to improve the performance of computer vision or robotic vision-based systems in our study.Cosine Generative Adversarial Network(CosGAN)is developed as a GAN that uses cosine embedding loss to handle issues associated with unsupervised source-relax domain adaptations.For less complex architecture,the CosGAN training process has two steps that produce results almost comparable to other state-of-the-art techniques.The efficiency of CosGAN was compared by conducting experiments using benchmarked datasets.The approach was evaluated on different datasets and experimental results show superiority over existing state-of-the-art methods in terms of accuracy as well as generalization ability.This technique has numerous applications including wheeled robots,autonomous vehicles,warehouse automation,and all image-processing-based automation tasks so it can reshape the field of robotic vision with its ability to make robots adapt to new tasks and environments efficiently without requiring additional labeled data.It lays the groundwork for future expansions in robotic vision and applications.Although GAN provides a variety of outstanding features,it also increases the risk of instability and over-fitting of the training data thus making the data difficult to converge.展开更多
Oil-based drilling fluids possess excellent properties such as shale inhibition, cuttings suspension, and superior lubrication, making them essential in the development of unconventional oil and gas reservoirs.However...Oil-based drilling fluids possess excellent properties such as shale inhibition, cuttings suspension, and superior lubrication, making them essential in the development of unconventional oil and gas reservoirs.However, wellbore instability, caused by the invasion of drilling fluids into shale formations, remains a significant challenge for the safe and efficient extraction of shale oil and gas. This work reports the preparation of mesoporous SiO2nanoparticles with low surface energy, utilized as multifunctional agents to enhance the performance of oil-based drilling fluids aimed at improving wellbore stability. The results indicate that the coating prepared from these nanoparticles exhibit excellent hydrophobicity and antifouling properties, increasing the water contact angle from 32°to 146°and oil contact angle from 24°to134.8°. Additionally, these nanoparticles exhibit exceptional chemical stability and thermal resistance.Incorporating these nanoparticles into oil-based drilling fluids reduced the surface energy of the mud cake from 34.99 to 8.17 m J·m-2and increased the roughness of shale from 0.26 to 2.39 μm. These modifications rendered the mud cake and shale surfaces amphiphobic, effectively mitigating capillary infiltration and delaying the long-term strength degradation of shale in oil-based drilling fluids. After 28days of immersion in oil-based drilling fluid, shale cores treated with MF-SiO2exhibited a 30.5% increase in compressive strength compared to untreated cores. Additionally, these nanoparticles demonstrated the ability to penetrate and seal rock pores, reducing the API filtration volume of the drilling fluid from11.2 to 7.6 m L. This study introduces a novel approach to enhance the development of shale gas and oil resources, offering a promising strategy for wellbore stabilization in oil-based drilling fluid systems.展开更多
The construction industry has always remained the economic and social backbone of any country in the world where occupational health and safety(OHS)is of prime importance.Like in other developing countries,this indust...The construction industry has always remained the economic and social backbone of any country in the world where occupational health and safety(OHS)is of prime importance.Like in other developing countries,this industry pays very little,rather negligible attention to OHS practices in Pakistan,resulting in the occurrence of a wide variety of accidents,mishaps,and near-misses every year.One of the major causes of such mishaps is the non-wearing of safety helmets(hard hats)at construction sites where falling objects from a height are unavoid-able.In most cases,this leads to serious brain injuries in people present at the site in general and the workers in particular.It is one of the leading causes of human fatalities at construction sites.In the United States,the Occupational Safety and Health Administration(OSHA)requires construction companies through safety laws to ensure the use of well-defined personal protective equipment(PPE).It has long been a problem to ensure the use of PPE because round-the-clock human monitoring is not possible.However,such monitoring through technological aids or automated tools is very much possible.The present study describes a systema-tic strategy based on deep learning(DL)models built on the You-Only-Look-Once(YOLOV5)architecture that could be used for monitoring workers’hard hats in real-time.It can indicate whether a worker is wearing a hat or not.The proposed system usesfive different models of the YOLOV5,namely YOLOV5n,YOLOv5s,YOLOv5 m,YOLOv5l,and YOLOv5x for object detection with the support of PyTorch,involving 7063 images.The results of the study show that among the DL models,the YOLOV5x has a high performance of 95.8%in terms of the mAP,while the YOLOV5n has the fastest detection speed of 70.4 frames per second(FPS).The proposed model can be successfully used in practice to recognize the hard hat worn by a worker.展开更多
Scrapped tires from vehicles are produced in large quantities. Despite numerous existing uses of scrapped tires, alarge quantity ends up at the landfill sites, which contributes to environmental degradation. The devel...Scrapped tires from vehicles are produced in large quantities. Despite numerous existing uses of scrapped tires, alarge quantity ends up at the landfill sites, which contributes to environmental degradation. The development ofmore applications of scrapped tire usage can reduce the disposal of tires at landfill sites. This research proposes anovel use of scrapped tires by using the strips taken from scrapped tires in replacement of steel bars as reinforcement. Manhole covers were produced using scrapped tires by completely replacing the steel with scrapped tires.Four different samples of manhole covers were prepared and tested. The highest bearing capacity of 25.5 kN wasrecorded with a sample of 100 mm thickness made with cementitious composite, which is 2.25 times higher thanthe bearing capacity of a conventional reinforced-concrete manhole cover. The use of manhole covers made withscrapped tires can effectively address the theft issue of manhole covers. The lifecycle cost analysis shows that themanhole cover made with scrapped tires is 3.4 times more cost-effective in comparison with the conventionalmanhole cover. This research shows a new avenue of the potential use of scrapped tires as reinforcement in structures, which can improve sustainable construction practices.展开更多
The unsteady flow of an incompressible fractional Maxwell fluid between two infinite coaxial cylinders is studied by means of integral transforms. The motion of the fluid is due to the inner cylinder that applies a ti...The unsteady flow of an incompressible fractional Maxwell fluid between two infinite coaxial cylinders is studied by means of integral transforms. The motion of the fluid is due to the inner cylinder that applies a time dependent tor- sional shear to the fluid. The exact solutions for velocity and shear stress are presented in series form in terms of some generalized functions. They can easily be particularized to give similar solutions for Maxwell and Newtonian fluids. Fi- nally, the influence of pertinent parameters on the fluid motion, as well as a comparison between models, is highlighted by graphical illustrations.展开更多
In the past few years,social media and online news platforms have played an essential role in distributing news content rapidly.Consequently.verification of the authenticity of news has become a major challenge.During...In the past few years,social media and online news platforms have played an essential role in distributing news content rapidly.Consequently.verification of the authenticity of news has become a major challenge.During the COVID-19 outbreak,misinformation and fake news were major sources of confusion and insecurity among the general public.In the first quarter of the year 2020,around 800 people died due to fake news relevant to COVID-19.The major goal of this research was to discover the best learning model for achieving high accuracy and performance.A novel case study of the Fake News Classification using ELECTRA model,which achieved 85.11%accuracy score,is thus reported in this manuscript.In addition to that,a new novel dataset called COVAX-Reality containing COVID-19 vaccine-related news has been contributed.Using the COVAX-Reality dataset,the performance of FNEC is compared to several traditional learning models i.e.,Support Vector Machine(SVM),Naive Bayes(NB),Passive Aggressive Classifier(PAC),Long Short-Term Memory(LSTM),Bi-directional LSTM(Bi-LSTM)and Bi-directional Encoder Representations from Transformers(BERT).For the evaluation of FNEC,standard metrics(Precision,Recall,Accuracy,and F1-Score)were utilized.展开更多
The adsorption behavior, antibacterial, and corrosion properties of a Ti-3 Cu alloy were studied in a phosphate-buffered saline solution containing 0, 1, 3, and 6 gL^(-1) bovine serum albumin protein at 37℃ and pH = ...The adsorption behavior, antibacterial, and corrosion properties of a Ti-3 Cu alloy were studied in a phosphate-buffered saline solution containing 0, 1, 3, and 6 gL^(-1) bovine serum albumin protein at 37℃ and pH = 7.4(±0.2). The protein adsorption behavior was examined via cyclic voltammetry, secondary ions mass spectroscopy(SIMS), and angle-resolved X-ray photoelectron spectroscopy(ARXPS). The corrosion property was analyzed by the open circuit potential(OCP), potentiodynamic polarization(PD),and electrochemical impedance spectroscopy(EIS) examinations. The antibacterial test was conducted according to the GB/T 21510 China Standard. It was observed that the surface charge density(QA DS) was directly proportional to the amount of the adsorbed BSA protein, signifying that the protein adsorption was accompanied by the charge transfer, pointing to chemisorptions phenomena. BSA amino groups and other organic species were observed in the surface analysis examinations. It was shown that the formation of barrier complexes between the TiO_(2) oxide-layer and PBS solution resulted in decreasing the release of Cu-ions, which consequently reduced the antibacterial activity. On the other hand, these barrier complexes improved the corrosion resistance by increasing the charge transfer resistance and double-layer capacitance of the Ti-3 Cu alloy.展开更多
Foreign body reactions to the wear debris and corrosion products from the implants,and bacterial infections are the main factors leading to the implant failures.In order to resolve these problems,the antibacterial TiN...Foreign body reactions to the wear debris and corrosion products from the implants,and bacterial infections are the main factors leading to the implant failures.In order to resolve these problems,the antibacterial TiN/Cu nanocomposite coatings with various N_(2) partial pressures were deposited on 304 stainless steels(SS)using an arc ion plating(AIP)system,named TiN/Cu-x(x=0.5,1.0,1.5 Pa).The results of X-ray diffraction analysis,energy-dispersive X-ray spectroscopy,and scanning electron microscopy showed that the N_(2) partial pressures determined the Cu contents,surface defects,and crystallite sizes of TiN/Cu nanocomposite coatings,which further influenced the comprehensive abilities.And the hardness and wear resistances of TiN/Cu coatings were enhanced with increase of the crystallite sizes.Under the co-actions of surface defects,crystallite sizes,and Cu content,TiN/Cu-1.0 and TiN/Cu-1.5 coatings possessed excellent corrosion resistance.Besides,the biological tests proved that all the TiN/Cu coatings showed no cytotoxicity with strong antibacterial ability.Among them,TiN/Cu-1.5 coating significantly promoted the cell proliferation,which is expected to be a novel antibacterial,corrosion-resistant,and wear-resistant coating on the surfaces of medical implants.展开更多
A thermoplastic based composite material is suitable for automobile and aerospace applications. The recyclability of thermoplastic and clean processing further enhance its use. The only limitation encountered in using...A thermoplastic based composite material is suitable for automobile and aerospace applications. The recyclability of thermoplastic and clean processing further enhance its use. The only limitation encountered in using this material is its high-melt viscosity. Various techniques have been developed to overcome this problem. Commingled materials are one of such methods adopted for making proper use of thermoplastic. A major problem observed during the use of a commingled material is its de-commingling, wherein, the uniform distribution of fiber and thermoplastic yam gets disturbed and affects the final quality of the composite. The effects of the braiding process on laminate quality were investigated. Flat plaques were produced by braiding the commingled yam, using a 48- carrier braiding machine. The braids （and control woven samples） were subsequently heated and consolidated in a nonisothermal compression molding operation. Prior to the manufacture of the ＇best quality＇ plaques, a series of moldings were produced under different consolidation conditions, to study the dependence of properties on the process variables. This enabled a processing window to be established for each material and helped to separate the respective effects of yam handling, textile processing, and consolidation on laminate properties.展开更多
Energy management benefits both consumers and utility companiesalike. Utility companies remain interested in identifying and reducing energywaste and theft, whereas consumers’ interest remain in lowering their energy...Energy management benefits both consumers and utility companiesalike. Utility companies remain interested in identifying and reducing energywaste and theft, whereas consumers’ interest remain in lowering their energyexpenses. A large supply-demand gap of over 6 GW exists in Pakistan asreported in 2018. Reducing this gap from the supply side is an expensiveand complex task. However, efficient energy management and distributionon demand side has potential to reduce this gap economically. Electricityload forecasting models are increasingly used by energy managers in takingreal-time tactical decisions to ensure efficient use of resources. Advancementin Machine-learning (ML) technology has enabled accurate forecasting ofelectricity consumption. However, the impact of computation cost affordedby these ML models is often ignored in favour of accuracy. This studyconsiders both accuracy and computation cost as concurrently significantfactors because together they shape the technology environment as well ascreate economic impact. Thus, a three-fold optimized load forecasting modelis proposed which includes (1) application specific parameters selection, (2)impact of different dataset granularities and (3) implementation of specificdata preparation. It deploys and compares the widely used back-propagationArtificial Neural Network (ANN) and Random Forest (RF) models for theprediction of electricity consumption of buildings within a university. In addition to the temporal and historical power consumption date as input parameters, the study also embeds weather data as well as university operationalcalendars resulting in improved performance. The outcomes are indicativethat the granularity i.e. the scale of details in data, and set of reduced and fullinput parameters impact performance accuracies differently for ANN and RFmodels. Experimental results show that overall RF model performed betterboth in terms of accuracy as well as computational time for a 1-min, 15-minand 1-h dataset granularities with the mean absolute percentage error (MAPE)of 2.42, 3.70 and 4.62 in 11.1 s, 1.14 s and 0.3 s respectively, thus well suitedfor a real-time energy monitoring application.展开更多
In this paper, a study related to the expected performance behaviour of present 3-level cache system for multi-core systems is presented. For this a queuing model for present 3-level cache system for multi-core proces...In this paper, a study related to the expected performance behaviour of present 3-level cache system for multi-core systems is presented. For this a queuing model for present 3-level cache system for multi-core processors is developed and its possible performance has been analyzed with the increase in number of cores. Various important performance parameters like access time and utilization of individual cache at different level and overall average access time of the cache system is determined. Results for up to 1024 cores have been reported in this paper.展开更多
The dynamic behavior,rapid mobility,abrupt changes in network topology,and numerous other flying constraints in unmanned aerial vehicle(UAV)networks make the design of a routing protocol a challenging task.The data ro...The dynamic behavior,rapid mobility,abrupt changes in network topology,and numerous other flying constraints in unmanned aerial vehicle(UAV)networks make the design of a routing protocol a challenging task.The data routing for communication between UAVs faces numerous challenges,such as low link quality,data loss,and routing path failure.This work proposes greedy perimeter stateless routing(GPSR)based design and implementation of a new adaptive communication routing protocol technique for UAVs,allowing multiple UAVs to communicate more effectively with each other in a group.Close imitation of the real environment is accomplished by considering UAVs’three-dimensional(3D)mobility in the simulations.The performance of the proposed intelligent greedy perimeter stateless routing(IGPSR)scheme has been evaluated based on end-to-end(E2E)delay,network throughput,and data loss ratio.The adapted scheme displayed on average 40%better results.The scenario has been implemented holistically on the network simulator software NS-3.展开更多
In many circumstances involving heat and mass transfer issues,it is considered impractical to measure the input flux and the resulting state distribution in the domain.Therefore,the need to develop techniques to provi...In many circumstances involving heat and mass transfer issues,it is considered impractical to measure the input flux and the resulting state distribution in the domain.Therefore,the need to develop techniques to provide solutions for such problems and estimate the inverse mass flux becomes imperative.Adaptive state estimator(ASE)is increasingly becoming a popular inverse estimation technique which resolves inverse problems by incorporating the semi-Markovian concept into a Bayesian estimation technique,thereby developing an inverse input and state estimator consisting of a bank of parallel adaptively weighted Kalman filters.The ASE is particularly designed for a system that encompasses independent unknowns and/or random switching of input and measurement biases.The present study describes the scheme to estimate the groundwater input contaminant flux and its transient distribution in a conjectural two-dimensional aquifer by means of ASE,which in particular is because of its unique ability to efficiently handle the process noise giving an estimation of keeping the relative error range within 10%in 2-dimensional problems.Numerical simulation results show that the proposed estimator presents decent estimation performance for both smoothly and abruptly varying input flux scenarios.Results also show that ASE enjoys a better estimation performance than its competitor,Recursive Least Square Estimator(RLSE)due to its larger error tolerance in greater process noise regimes.ASE's inherent deficiency of being slower than the RLSE,resulting from the complexity of algorithm,was also noticed.The chosen input scenarios are tested to calculate the effect of input area and both estimators show improved results with an increase in input flux area especially as sensors are moved closer to the assumed input location.展开更多
基金financially supported by the National Natural Science Foundation of China(Nos.92160301,92060203,52175415,and 52205475)the Science Center for Gas Turbine Project(Nos.P2022-AB-IV-002-001 and P2023-B-IV-003-001)+2 种基金the Natural Science Foundation of Jiangsu Province(No.BK20210295)the Superior Postdoctoral Project of Jiangsu Province(No.2022ZB215)the National Key Laboratory of Science and Technology on Helicopter Transmission in NUAA(No.HTL-A-22G12).
文摘Minimum quantity lubrication(MQL),as a new sustainable and eco-friendly alternative cooling/lubrication technology that addresses the limitations of dry and wet machining,utilizes a small amount of lubricant or coolant to reduce friction,tool wear,and heat during cutting processes.MQL technique has witnessed significant developments in recent years,such as combining MQL with other sustainable techniques to achieve optimum results,using biodegradable lubricants,and innovations in nozzle designs and delivery methods.This review presents an in-depth analysis of machining characteristics(e.g.,cutting forces,temperature,tool wear,chip morphology and surface integrity,etc.)and sustainability characteristics(e.g.,energy consumption,carbon emissions,processing time,machining cost,etc.)of conventional MQL and hybrid MQL techniques like cryogenic MQL,Ranque-Hilsch vortex tube MQL,nanofluids MQL,hybrid nanofluid MQL and ultrasonic vibration assisted MQL in machining of aeronautical materials.Subsequently,the latest research and developments are analyzed and summarized in the field of MQL,and provide a detailed comparison between each technique,considering advantages,challenges,and limitations in practical implementation.In addition,this review serves as a valuable source for researchers and engineers to optimize machining processes while minimizing environmental impact and operational costs.Ultimately,the potential future aspects of MQL for research and industrial execution are discussed.
基金supported by the National Natural Science Foundation of China(No.52001034)the China Postdoctoral Science Foundation(No.2023M731677)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX23_3032).
文摘Nano-zinc oxides(ZnO)demonstrate remarkable antibacterial properties.To further enhance the corrosion resistance and antibacterial efficiency of magnesium alloy micro-arc oxidation(MAO)coatings,this study investigates the preparation of ZnO-containing micro-arc oxidation coatings with dual functionality by incorporating nano-ZnO into MAO electrolyte.The influence of varying ZnO concentrations on the microstructure,corrosion resistance,and antibacterial properties of the coating was examined through microstructure analysis,immersion tests,electrochemical experiments,and antibacterial assays.The findings revealed that the addition of nano-ZnO significantly enhanced the corrosion resistance of the MAO-coated alloy.Specifically,when the ZnO concentration in the electrolyte was 5 g/L,the corrosion rate was more than ten times lower compared to the MAO coatings without ZnO.Moreover,the antibacterial efficacy of ZnO+MAO coating,prepared with a ZnO concentration of 5 g/L,surpassed 95%after 24 h of co-culturing with Staphylococcus aureus(S.aureus).The nano-ZnO+MAO-coated alloy exhibited exceptional degradation resistance,corrosion resistance,and antibacterial effectiveness.
基金support from the Deanship of Scientific Research at King Khalid University,Saudi Arabia(RGP2/505/45)。
文摘Neodymium chromium oxide(NdCrO_(3))and NdCrO_(3)/graphene oxide(GO)nanocomposite were synthesized via sol-gel and co-precipitation techniques for being used in high-perfo rmance supercapacitors and for the possible application in ultraviolet(UV)materials.Herein the systematic synthesis approach was adopted,which enhances the optical and electrical properties of the grown wide band-gap composite nanomaterial.Structural characterization of the grown materials was attempted using X-ray diffraction(XRD)and scanning electron microscopy(SEM).Most importantly the electrochemical analysis of the grown samples was carried out by employing a glassy carbon electrode and 3 mol/L KOH electrolyte,which demonstrates significant improvements in a specific capacitance of approximately360 F/g,an energy density of approximately 18 Wh/kg,and a maximum power density of approximately 257 W/kg,respectively.Moreover,NdCrO_(3)/GO nanocomposite maintains a cyclic stability of 97.6%after4000 cycles.Photoluminescence(PL)spectroscopy confirms the wide bandgap nature of the NdCrO_(3)and NdCrO_(3)/GO nanocomposite,indicating its potential application in UVC devices.These findings emphasize the potential of the NdCrO_(3)/GO nanocomposite in advancing efficient energy storage solutions and the possibility of being used in UVC technology.
基金financially supported by the National Natural Science Foundation of China(No.52173246)111 project(No.B13013)Shccig-Qinling Program(No.SMYJY20220574)。
文摘Hard carbon(HC)is broadly recognized as an exceptionally prospective candidate for the anodes of sodium-ion batteries(SIBs),but their practical implementation faces substantial limitations linked to precursor factors,such as reduced carbon yield and increased cost.Herein,a cost-effective approach is proposed to prepare a coal-derived HC anode with simple pre-oxidation followed by a post-carbonization process which effectively expands the d_(002)layer spacing,generates closed pores and increases defect sites.Through these modifications,the resulting HC anode attains a delicate equilibrium between plateau capacity and sloping capacity,showcasing a remarkable reversible capacity of 306.3 mAh·g^(-1)at 0.03 A·g^(-1).Furthermore,the produ ced HC exhibits fast reaction kinetics and exceptional rate performance,achieving a capacity of 289 mAh·g^(-1)at 0.1 A·g^(-1),equivalent to~94.5%of that at 0.03 A·g^(-1).When implemented in a full cell configuration,the impressive electrochemical performance is evident,with a notable energy density of 410.6 Wh·kg^(-1)(based on cathode mass).In short,we provide a straightforward yet efficient method for regulating coal-derived HC,which is crucial for the widespread use of SIBs anodes.
基金This work was supported by the National Natural Science Foundation of China(No.52001034)the China Postdoctoral Science Foundation(No.2023M731677)the Major Project of 2025 Sci&Tech Innovation of Ningbo(No.2020Z096).
文摘This research systematically examined the degradation,antibacterial effects,and biocompatibility of micro-arc oxidation(MAO)coatings with nano CuO and ZnO on extruded Mg alloys.Both copper(Cu)and Zinc(Zn)possess antibacterial properties.The findings demonstrated that adding ZnO will appreciably reduce the degradation rate of MAO-coating alloy due to the self-sealing micro holes.CuO+MAO coating exhibited excellent antibacterial performance,with an antibacterial rate of over 90%within 6 h co-cultured with Staphylococcus aureus.Similarly,the antibacterial rate of ZnO+MAO coating reached 90%after 12 h co-culture.Cytotoxicity test using MG63 cell indicated that the incorporation of CuO and ZnO did not notably affect the cell viability rate of the coating.Moreover,after 14 days of culture,the CuO+MAO and ZnO+MAO coated samples exhibited higher alkaline phosphatase(ALP)activity than the MAO-coated and uncoated samples,suggesting favorable osteogenic properties.
基金This study was funded by GCRF UK and was carried out as part of project CoNTINuE-Capacity building in technology-driven innovation in healthcare.
文摘Routine immunization(RI)of children is the most effective and timely public health intervention for decreasing child mortality rates around the globe.Pakistan being a low-and-middle-income-country(LMIC)has one of the highest child mortality rates in the world occurring mainly due to vaccine-preventable diseases(VPDs).For improving RI coverage,a critical need is to establish potential RI defaulters at an early stage,so that appropriate interventions can be targeted towards such populationwho are identified to be at risk of missing on their scheduled vaccine uptakes.In this paper,a machine learning(ML)based predictivemodel has been proposed to predict defaulting and non-defaulting children on upcoming immunization visits and examine the effect of its underlying contributing factors.The predictivemodel uses data obtained from Paigham-e-Sehat study having immunization records of 3,113 children.The design of predictive model is based on obtaining optimal results across accuracy,specificity,and sensitivity,to ensure model outcomes remain practically relevant to the problem addressed.Further optimization of predictive model is obtained through selection of significant features and removing data bias.Nine machine learning algorithms were applied for prediction of defaulting children for the next immunization visit.The results showed that the random forest model achieves the optimal accuracy of 81.9%with 83.6%sensitivity and 80.3%specificity.The main determinants of vaccination coverage were found to be vaccine coverage at birth,parental education,and socioeconomic conditions of the defaulting group.This information can assist relevant policy makers to take proactive and effective measures for developing evidence based targeted and timely interventions for defaulting children.
文摘Domain shift is when the data used in training does not match the ones it will be applied to later on under similar conditions.Domain shift will reduce accuracy in results.To prevent this,domain adaptation is done,which adapts the pre-trained model to the target domain.In real scenarios,the availability of labels for target data is rare thus resulting in unsupervised domain adaptation.Herein,we propose an innovative approach where source-free domain adaptation models and Generative Adversarial Networks(GANs)are integrated to improve the performance of computer vision or robotic vision-based systems in our study.Cosine Generative Adversarial Network(CosGAN)is developed as a GAN that uses cosine embedding loss to handle issues associated with unsupervised source-relax domain adaptations.For less complex architecture,the CosGAN training process has two steps that produce results almost comparable to other state-of-the-art techniques.The efficiency of CosGAN was compared by conducting experiments using benchmarked datasets.The approach was evaluated on different datasets and experimental results show superiority over existing state-of-the-art methods in terms of accuracy as well as generalization ability.This technique has numerous applications including wheeled robots,autonomous vehicles,warehouse automation,and all image-processing-based automation tasks so it can reshape the field of robotic vision with its ability to make robots adapt to new tasks and environments efficiently without requiring additional labeled data.It lays the groundwork for future expansions in robotic vision and applications.Although GAN provides a variety of outstanding features,it also increases the risk of instability and over-fitting of the training data thus making the data difficult to converge.
基金support from the National Natural:Science Foundation of China(NO.52174014)the National Natural Science Foundation Basic Science Center(NO.52288101).
文摘Oil-based drilling fluids possess excellent properties such as shale inhibition, cuttings suspension, and superior lubrication, making them essential in the development of unconventional oil and gas reservoirs.However, wellbore instability, caused by the invasion of drilling fluids into shale formations, remains a significant challenge for the safe and efficient extraction of shale oil and gas. This work reports the preparation of mesoporous SiO2nanoparticles with low surface energy, utilized as multifunctional agents to enhance the performance of oil-based drilling fluids aimed at improving wellbore stability. The results indicate that the coating prepared from these nanoparticles exhibit excellent hydrophobicity and antifouling properties, increasing the water contact angle from 32°to 146°and oil contact angle from 24°to134.8°. Additionally, these nanoparticles exhibit exceptional chemical stability and thermal resistance.Incorporating these nanoparticles into oil-based drilling fluids reduced the surface energy of the mud cake from 34.99 to 8.17 m J·m-2and increased the roughness of shale from 0.26 to 2.39 μm. These modifications rendered the mud cake and shale surfaces amphiphobic, effectively mitigating capillary infiltration and delaying the long-term strength degradation of shale in oil-based drilling fluids. After 28days of immersion in oil-based drilling fluid, shale cores treated with MF-SiO2exhibited a 30.5% increase in compressive strength compared to untreated cores. Additionally, these nanoparticles demonstrated the ability to penetrate and seal rock pores, reducing the API filtration volume of the drilling fluid from11.2 to 7.6 m L. This study introduces a novel approach to enhance the development of shale gas and oil resources, offering a promising strategy for wellbore stabilization in oil-based drilling fluid systems.
文摘The construction industry has always remained the economic and social backbone of any country in the world where occupational health and safety(OHS)is of prime importance.Like in other developing countries,this industry pays very little,rather negligible attention to OHS practices in Pakistan,resulting in the occurrence of a wide variety of accidents,mishaps,and near-misses every year.One of the major causes of such mishaps is the non-wearing of safety helmets(hard hats)at construction sites where falling objects from a height are unavoid-able.In most cases,this leads to serious brain injuries in people present at the site in general and the workers in particular.It is one of the leading causes of human fatalities at construction sites.In the United States,the Occupational Safety and Health Administration(OSHA)requires construction companies through safety laws to ensure the use of well-defined personal protective equipment(PPE).It has long been a problem to ensure the use of PPE because round-the-clock human monitoring is not possible.However,such monitoring through technological aids or automated tools is very much possible.The present study describes a systema-tic strategy based on deep learning(DL)models built on the You-Only-Look-Once(YOLOV5)architecture that could be used for monitoring workers’hard hats in real-time.It can indicate whether a worker is wearing a hat or not.The proposed system usesfive different models of the YOLOV5,namely YOLOV5n,YOLOv5s,YOLOv5 m,YOLOv5l,and YOLOv5x for object detection with the support of PyTorch,involving 7063 images.The results of the study show that among the DL models,the YOLOV5x has a high performance of 95.8%in terms of the mAP,while the YOLOV5n has the fastest detection speed of 70.4 frames per second(FPS).The proposed model can be successfully used in practice to recognize the hard hat worn by a worker.
文摘Scrapped tires from vehicles are produced in large quantities. Despite numerous existing uses of scrapped tires, alarge quantity ends up at the landfill sites, which contributes to environmental degradation. The development ofmore applications of scrapped tire usage can reduce the disposal of tires at landfill sites. This research proposes anovel use of scrapped tires by using the strips taken from scrapped tires in replacement of steel bars as reinforcement. Manhole covers were produced using scrapped tires by completely replacing the steel with scrapped tires.Four different samples of manhole covers were prepared and tested. The highest bearing capacity of 25.5 kN wasrecorded with a sample of 100 mm thickness made with cementitious composite, which is 2.25 times higher thanthe bearing capacity of a conventional reinforced-concrete manhole cover. The use of manhole covers made withscrapped tires can effectively address the theft issue of manhole covers. The lifecycle cost analysis shows that themanhole cover made with scrapped tires is 3.4 times more cost-effective in comparison with the conventionalmanhole cover. This research shows a new avenue of the potential use of scrapped tires as reinforcement in structures, which can improve sustainable construction practices.
文摘The unsteady flow of an incompressible fractional Maxwell fluid between two infinite coaxial cylinders is studied by means of integral transforms. The motion of the fluid is due to the inner cylinder that applies a time dependent tor- sional shear to the fluid. The exact solutions for velocity and shear stress are presented in series form in terms of some generalized functions. They can easily be particularized to give similar solutions for Maxwell and Newtonian fluids. Fi- nally, the influence of pertinent parameters on the fluid motion, as well as a comparison between models, is highlighted by graphical illustrations.
文摘In the past few years,social media and online news platforms have played an essential role in distributing news content rapidly.Consequently.verification of the authenticity of news has become a major challenge.During the COVID-19 outbreak,misinformation and fake news were major sources of confusion and insecurity among the general public.In the first quarter of the year 2020,around 800 people died due to fake news relevant to COVID-19.The major goal of this research was to discover the best learning model for achieving high accuracy and performance.A novel case study of the Fake News Classification using ELECTRA model,which achieved 85.11%accuracy score,is thus reported in this manuscript.In addition to that,a new novel dataset called COVAX-Reality containing COVID-19 vaccine-related news has been contributed.Using the COVAX-Reality dataset,the performance of FNEC is compared to several traditional learning models i.e.,Support Vector Machine(SVM),Naive Bayes(NB),Passive Aggressive Classifier(PAC),Long Short-Term Memory(LSTM),Bi-directional LSTM(Bi-LSTM)and Bi-directional Encoder Representations from Transformers(BERT).For the evaluation of FNEC,standard metrics(Precision,Recall,Accuracy,and F1-Score)were utilized.
基金financially supported by the National Key Research and Development Program of China(2018YFC1106601)Liaoning Revitalization Talents Program(XLYC1807069)+1 种基金National Natural Science Foundation(No.51631009,31870954)support of the CSC scholarship。
文摘The adsorption behavior, antibacterial, and corrosion properties of a Ti-3 Cu alloy were studied in a phosphate-buffered saline solution containing 0, 1, 3, and 6 gL^(-1) bovine serum albumin protein at 37℃ and pH = 7.4(±0.2). The protein adsorption behavior was examined via cyclic voltammetry, secondary ions mass spectroscopy(SIMS), and angle-resolved X-ray photoelectron spectroscopy(ARXPS). The corrosion property was analyzed by the open circuit potential(OCP), potentiodynamic polarization(PD),and electrochemical impedance spectroscopy(EIS) examinations. The antibacterial test was conducted according to the GB/T 21510 China Standard. It was observed that the surface charge density(QA DS) was directly proportional to the amount of the adsorbed BSA protein, signifying that the protein adsorption was accompanied by the charge transfer, pointing to chemisorptions phenomena. BSA amino groups and other organic species were observed in the surface analysis examinations. It was shown that the formation of barrier complexes between the TiO_(2) oxide-layer and PBS solution resulted in decreasing the release of Cu-ions, which consequently reduced the antibacterial activity. On the other hand, these barrier complexes improved the corrosion resistance by increasing the charge transfer resistance and double-layer capacitance of the Ti-3 Cu alloy.
基金financially supported by National Key Research and Development Program of China (Nos. 2018YFC1106601 and 2016YFC1100601)Liaoning Revitalization Talents Program (No. XLYC1807069)+1 种基金National Natural Science Foundation of China (Nos. 51631009 and 31870954)Key Projects for Foreign Cooperation of Bureau of International Cooperation Chinese Academy of Sciences (No. 174321KYSB20180006)
文摘Foreign body reactions to the wear debris and corrosion products from the implants,and bacterial infections are the main factors leading to the implant failures.In order to resolve these problems,the antibacterial TiN/Cu nanocomposite coatings with various N_(2) partial pressures were deposited on 304 stainless steels(SS)using an arc ion plating(AIP)system,named TiN/Cu-x(x=0.5,1.0,1.5 Pa).The results of X-ray diffraction analysis,energy-dispersive X-ray spectroscopy,and scanning electron microscopy showed that the N_(2) partial pressures determined the Cu contents,surface defects,and crystallite sizes of TiN/Cu nanocomposite coatings,which further influenced the comprehensive abilities.And the hardness and wear resistances of TiN/Cu coatings were enhanced with increase of the crystallite sizes.Under the co-actions of surface defects,crystallite sizes,and Cu content,TiN/Cu-1.0 and TiN/Cu-1.5 coatings possessed excellent corrosion resistance.Besides,the biological tests proved that all the TiN/Cu coatings showed no cytotoxicity with strong antibacterial ability.Among them,TiN/Cu-1.5 coating significantly promoted the cell proliferation,which is expected to be a novel antibacterial,corrosion-resistant,and wear-resistant coating on the surfaces of medical implants.
文摘A thermoplastic based composite material is suitable for automobile and aerospace applications. The recyclability of thermoplastic and clean processing further enhance its use. The only limitation encountered in using this material is its high-melt viscosity. Various techniques have been developed to overcome this problem. Commingled materials are one of such methods adopted for making proper use of thermoplastic. A major problem observed during the use of a commingled material is its de-commingling, wherein, the uniform distribution of fiber and thermoplastic yam gets disturbed and affects the final quality of the composite. The effects of the braiding process on laminate quality were investigated. Flat plaques were produced by braiding the commingled yam, using a 48- carrier braiding machine. The braids （and control woven samples） were subsequently heated and consolidated in a nonisothermal compression molding operation. Prior to the manufacture of the ＇best quality＇ plaques, a series of moldings were produced under different consolidation conditions, to study the dependence of properties on the process variables. This enabled a processing window to be established for each material and helped to separate the respective effects of yam handling, textile processing, and consolidation on laminate properties.
基金This research is funded by Neurocomputation Lab, National Center ofArtificial Intelligence, NED University of Engineering and Technology, Karachi, 75270, Pakistan(PSDP.263/2017-18).
文摘Energy management benefits both consumers and utility companiesalike. Utility companies remain interested in identifying and reducing energywaste and theft, whereas consumers’ interest remain in lowering their energyexpenses. A large supply-demand gap of over 6 GW exists in Pakistan asreported in 2018. Reducing this gap from the supply side is an expensiveand complex task. However, efficient energy management and distributionon demand side has potential to reduce this gap economically. Electricityload forecasting models are increasingly used by energy managers in takingreal-time tactical decisions to ensure efficient use of resources. Advancementin Machine-learning (ML) technology has enabled accurate forecasting ofelectricity consumption. However, the impact of computation cost affordedby these ML models is often ignored in favour of accuracy. This studyconsiders both accuracy and computation cost as concurrently significantfactors because together they shape the technology environment as well ascreate economic impact. Thus, a three-fold optimized load forecasting modelis proposed which includes (1) application specific parameters selection, (2)impact of different dataset granularities and (3) implementation of specificdata preparation. It deploys and compares the widely used back-propagationArtificial Neural Network (ANN) and Random Forest (RF) models for theprediction of electricity consumption of buildings within a university. In addition to the temporal and historical power consumption date as input parameters, the study also embeds weather data as well as university operationalcalendars resulting in improved performance. The outcomes are indicativethat the granularity i.e. the scale of details in data, and set of reduced and fullinput parameters impact performance accuracies differently for ANN and RFmodels. Experimental results show that overall RF model performed betterboth in terms of accuracy as well as computational time for a 1-min, 15-minand 1-h dataset granularities with the mean absolute percentage error (MAPE)of 2.42, 3.70 and 4.62 in 11.1 s, 1.14 s and 0.3 s respectively, thus well suitedfor a real-time energy monitoring application.
文摘In this paper, a study related to the expected performance behaviour of present 3-level cache system for multi-core systems is presented. For this a queuing model for present 3-level cache system for multi-core processors is developed and its possible performance has been analyzed with the increase in number of cores. Various important performance parameters like access time and utilization of individual cache at different level and overall average access time of the cache system is determined. Results for up to 1024 cores have been reported in this paper.
基金Shanghai Summit Discipline in Design,ChinaSpecial Project Funding for the Shanghai Municipal Commission of Economy and Information Civil-Military Inosculation Project,China(No.JMRH-2018-1042)。
文摘The dynamic behavior,rapid mobility,abrupt changes in network topology,and numerous other flying constraints in unmanned aerial vehicle(UAV)networks make the design of a routing protocol a challenging task.The data routing for communication between UAVs faces numerous challenges,such as low link quality,data loss,and routing path failure.This work proposes greedy perimeter stateless routing(GPSR)based design and implementation of a new adaptive communication routing protocol technique for UAVs,allowing multiple UAVs to communicate more effectively with each other in a group.Close imitation of the real environment is accomplished by considering UAVs’three-dimensional(3D)mobility in the simulations.The performance of the proposed intelligent greedy perimeter stateless routing(IGPSR)scheme has been evaluated based on end-to-end(E2E)delay,network throughput,and data loss ratio.The adapted scheme displayed on average 40%better results.The scenario has been implemented holistically on the network simulator software NS-3.
文摘In many circumstances involving heat and mass transfer issues,it is considered impractical to measure the input flux and the resulting state distribution in the domain.Therefore,the need to develop techniques to provide solutions for such problems and estimate the inverse mass flux becomes imperative.Adaptive state estimator(ASE)is increasingly becoming a popular inverse estimation technique which resolves inverse problems by incorporating the semi-Markovian concept into a Bayesian estimation technique,thereby developing an inverse input and state estimator consisting of a bank of parallel adaptively weighted Kalman filters.The ASE is particularly designed for a system that encompasses independent unknowns and/or random switching of input and measurement biases.The present study describes the scheme to estimate the groundwater input contaminant flux and its transient distribution in a conjectural two-dimensional aquifer by means of ASE,which in particular is because of its unique ability to efficiently handle the process noise giving an estimation of keeping the relative error range within 10%in 2-dimensional problems.Numerical simulation results show that the proposed estimator presents decent estimation performance for both smoothly and abruptly varying input flux scenarios.Results also show that ASE enjoys a better estimation performance than its competitor,Recursive Least Square Estimator(RLSE)due to its larger error tolerance in greater process noise regimes.ASE's inherent deficiency of being slower than the RLSE,resulting from the complexity of algorithm,was also noticed.The chosen input scenarios are tested to calculate the effect of input area and both estimators show improved results with an increase in input flux area especially as sensors are moved closer to the assumed input location.
