A grey-box modelling framework was developed for the estimation of cut point temperature of a crude distillation unit(CDU)under uncertainty in crude composition and process conditions.First principle(FP)model of CDU w...A grey-box modelling framework was developed for the estimation of cut point temperature of a crude distillation unit(CDU)under uncertainty in crude composition and process conditions.First principle(FP)model of CDU was developed for Pakistani crudes from Zamzama and Kunnar fields.A hybrid methodology based on the integration of Taguchi method and genetic algorithm(GA)was employed to estimate the optimal cut point temperature for various sets of process variables.Optimised datasets were utilised to develop an artificial neural networks(ANN)model for the prediction of optimum values of cut points.The ANN model was then used to replace the hybrid framework of the Taguchi method and the GA.The integration of the ANN and FP model makes it a grey-box(GB)model.For the case of Zamama crude,the GB model helped in the decrease of up to 38.93%in energy required per kilo barrel of diesel and an 8.2%increase in diesel production compared to the stand-alone FP model under uncertainty.Similarly,for Kunnar crude,up to 18.87%decrease in energy required per kilo barrel of diesel and a 33.96%increase in diesel production was observed in comparison to the stand-alone FP model.展开更多
Recrystallization stands as an essential process that influences the microstructure and properties of magnesium(Mg)alloys,yet its mechanisms remain complex and multifaceted.This review explores the key factors affecti...Recrystallization stands as an essential process that influences the microstructure and properties of magnesium(Mg)alloys,yet its mechanisms remain complex and multifaceted.This review explores the key factors affecting the recrystallization behavior of Mg alloys,emphasizing how their unique structural characteristics impact the driving forces and dynamics of recrystallization.Unlike conventional alloys,Mg alloys exhibit distinctive recrystallization kinetics,which is significantly affected by deformation conditions,such as strain rate,temperature,and processing methods(e.g.,rolling,forging,and extrusion).The process is also influenced by material characteristics,including initial grain size,texture,dislocation density,solute clustering,and stacking fault energy.Additionally,uneven strain distribution,stress concentrations,and stored energy play crucial roles in shaping the formation of recrystallized grains,particularly near grain boundaries.Notably,recrystallization is driven by dislocation accumulation and the availability of slip systems,with new strain-free grains typically forming in regions of high dislocation density.This paper synthesizes the existing literature to provide a comprehensive understanding of the mechanisms and kinetics of recrystallization in Mg alloys,highlighting the influence of microstructural features such as second-phase particles and grain boundary characteristics.It also identifies key challenges and suggests promising directions for future research,including optimizing material compositions and the interaction between deformation conditions via machine learning.展开更多
Lithium-based batteries(LiBs)are integral components in operating electric vehicles to renewable energy systems and portable electronic devices,thanks to their unparalleled energy density,minimal self-discharge rates,...Lithium-based batteries(LiBs)are integral components in operating electric vehicles to renewable energy systems and portable electronic devices,thanks to their unparalleled energy density,minimal self-discharge rates,and favorable cycle life.However,the inherent safety risks and performance degradation of LiB over time impose continuous monitoring facilitated by sophisticated battery management systems(BMS).This review comprehensively analyzes the current state of sensor technologies for smart LiBs,focusing on their advancements,opportunities,and potential challenges.Sensors are classified into two primary groups based on their application:safety monitoring and performance optimization.Safety monitoring sensors,including temperature,pressure,strain,gas,acoustic,and magnetic sensors,focus on detecting conditions that could lead to hazardous situations.Performance optimization sensors,such as optical-based and electrochemical-based,monitor factors such as state of charge and state of health,emphasizing operational efficiency and lifespan.The review also highlights the importance of integrating these sensors with advanced algorithms and control approaches to optimize charging and discharge cycles.Potential advancements driven by nanotechnology,wireless sensor networks,miniaturization,and machine learning algorithms are also discussed.However,challenges related to sensor miniaturization,power consumption,cost efficiency,and compatibility with existing BMS need to be addressed to fully realize the potential of LiB sensor technologies.This comprehensive review provides valuable insights into the current landscape and future directions of sensor innovations in smart LiBs,guiding further research and development efforts to enhance battery performance,reliability,and safety.Integration of advanced sensor technologies for smart LiBs:integrating non-optical multi-parameter,optical-based,and electrochemical sensors within the BMS to achieve higher safety,improved efficiency,early warning mechanisms,and TR prevention.Potential advancements are driven by nanotechnology,wireless sensor networks,miniaturization,and advanced algorithms,addressing key challenges to enhance battery performance and reliability.展开更多
In this study,a Grey-box(GB)model was developed to predict the optimum mass flow rates of inlet streams of a Shell and Tube Heat Exchanger(STHE)under varying process conditions.Aspen Exchanger Design and Rating(Aspen-...In this study,a Grey-box(GB)model was developed to predict the optimum mass flow rates of inlet streams of a Shell and Tube Heat Exchanger(STHE)under varying process conditions.Aspen Exchanger Design and Rating(Aspen-EDR)was initially used to construct a first principle model(FP)of the STHE using industrial data.The Genetic Algorithm(GA)was incorporated into the FP model to attain the minimum exit temperature for the hot kerosene process stream under varying process conditions.A dataset comprised of optimum process conditions was generated through FP-GA integration and was utilised to develop an Artificial Neural Networks(ANN)model.Subsequently,the ANN model was merged with the FP model by substituting the GA,to form a GB model.The developed GB model,that is,ANN and FP integration,achieved higher effectiveness and lower outlet temperature than those derived through the standalone FP model.Performance of the GB framework was also comparable to the FP-GA approach but it significantly reduced the computation time required for estimating the optimum process conditions.The proposed GB-based method improved the STHE's ability to extract energy from the process stream and strengthened its resilience to cope with diverse process conditions.展开更多
Twinning is widely recognized as an effective and cost-efficient method for controlling the microstructure and properties of wrought magnesium(Mg)alloys.Specifically,twins play a crucial role in initiating dynamic rec...Twinning is widely recognized as an effective and cost-efficient method for controlling the microstructure and properties of wrought magnesium(Mg)alloys.Specifically,twins play a crucial role in initiating dynamic recrystallization(DRX),while twin regions experience rapid recrystallization during static recrystallization(SRX).The activation of twinning can lead to changes in lattice orientation,significantly impacting the final texture in Mg alloys.The active roles of twinning are influenced by various factors during the activation process,and the mobility of twin boundaries(TB)can be amplified by stress effects,dislocation interactions,and thermal effects.Conversely,annealing treatments that involve proper segregation or precipitation on TBs serve to stabilize them,restraining their motion.Events such as segregation may also alter the twinning propensity in Magnesium-rare earth(Mg-RE)alloys.While{10–11}contraction twins(CT)and{10–11}-{10–12}double twins(DT)can promote dynamic recrystallization(DRX),they also pose a risk as potential sources of voids and cracks.Additionally,understanding the nucleation and growth mechanisms of twinning is crucial,and these aspects are briefly reviewed in this article.Considering the factors mentioned above,this article summarizes the recent research progress in this field,shedding light on advancements in recent eras.展开更多
Cerebellopontine angle (CPA) lesions account for up to 10% of all intracranial tumors. Most CPA tumors are benign, but can cause nerve damage or compress the surrounding structures if left untreated. The typical prese...Cerebellopontine angle (CPA) lesions account for up to 10% of all intracranial tumors. Most CPA tumors are benign, but can cause nerve damage or compress the surrounding structures if left untreated. The typical presentation is with adult-onset sensorineural hearing loss or non-pulsatile tinnitus. In some patients, this goes unnoticed, and presentation is delayed until the lesion is much larger and presents with symptoms related to mass effect. We present the case study of 63 years old gentleman, who had suspected left CPA lesion on CT head done few years ago for dizziness and left-sided facial numbness. MRI could not be done at that time due to his MRI incompatible pacemaker leading to delay in his management eventually causing loss of patient to the follow up. He later developed progressive difficulty in walking which was initially attributed to as secondary to vasovagal syncope and postural hypotension. He eventually presented to us with intractable nausea and vomiting, worsening headache and ataxia. He had an urgent CT head which showed significant growth in the lesion with compression of the surrounding structures and obstructive hydrocephalus. He was given steroids which improved his nausea and vomiting, followed by undergoing surgery in regional center leading to significant improvement in his gait within few days of surgery. He unfortunately continued to have a degree of ataxia and facial numbness. This case illustrates a rare presentation of CPA tumor with symptoms of nausea and vomiting as a result of mass effect of the growing tumor. In addition, this review also shows the importance of regularly following up the patients with suspected CPA lesions on initial scans which will help with identifying the increase in size of lesion promptly and potentially preventing advanced complications of CPA tumors. We suggest regular monitoring of these patients to timely manage the lesion and avoid the potential life-threatening complications.展开更多
Hypophosphataemia is defined as low level of phosphate in the blood (normal range 0.8 - 1.4 mmol/l), which can be drug-induced such as uniphyline. We present a case of elderly female patient with known chronic obstruc...Hypophosphataemia is defined as low level of phosphate in the blood (normal range 0.8 - 1.4 mmol/l), which can be drug-induced such as uniphyline. We present a case of elderly female patient with known chronic obstructive pulmonary disease, admitted with acute respiratory failure and low serum phosphate level, her clinical signs and serum phosphate level did not improve with conventional therapy and intravenous phosphate replacement, until her recently commenced uniphyline was discontinued. This highlights the importance of awareness amongst the clinicians about this rare but potential side effect of uniphyline. We suggest monitoring phosphate levels in patients admitted with acute respiratory failure especially those on extended bronchodilator therapy.展开更多
The problem of a disk rotating in a viscous fluid has been investigated. The disk is accelerated with angular velocity proportional to time. Employing suitable similarity transformations the governing partial differen...The problem of a disk rotating in a viscous fluid has been investigated. The disk is accelerated with angular velocity proportional to time. Employing suitable similarity transformations the governing partial differential equations are transformed in to ordinary differential form. The resulting equations are solved numerically using SOR method and Simpson’s (1/3) rule. The results have been improved by using Richardson’s extrapolation. The effect of the non-dimensional parameter s which measures unsteadiness is observed on velocity components, skin friction coefficient and torque of the disk.展开更多
Oxidation of sulfide in aqueous solution by hydrogen peroxide was investigated in the presence of hydrated ferric oxide catalyst. The ferric oxide catalyst was synthesized by sol gel technique from ferric chloride and...Oxidation of sulfide in aqueous solution by hydrogen peroxide was investigated in the presence of hydrated ferric oxide catalyst. The ferric oxide catalyst was synthesized by sol gel technique from ferric chloride and ammonia. The synthesized catalyst was characterized by Fourier transform infrared spectroscopy, X-Ray diffraction analysis, scanning electrom microscope and energy dispersive X-ray analysis. The catalyst was quite effective in oxidizing the sulfide by hydrogen peroxide. The effects of sulfide concentration, catalyst loading, H2O2 dosing and temperature on the kinetics of sulfide oxidation were investigated. Kinetic equations and activation energies for the catalytic oxidation reaction were calculated based on the experimental results.展开更多
Calotropis procera(Aiton)W.T.Aiton,belonging to the family Apocynaceae,is C3 evergreen plant species in arid and semi-arid areas of the Punjab Province,Pakistan.It grows in a variety of habitats like salt affected and...Calotropis procera(Aiton)W.T.Aiton,belonging to the family Apocynaceae,is C3 evergreen plant species in arid and semi-arid areas of the Punjab Province,Pakistan.It grows in a variety of habitats like salt affected and waterlogged area,desert/semi-desert,roadside,wasteland,graveyard,forest,crop field,coastline,and river/canal bank.A total of 12 populations growing in different ecological regions were sampled to evaluate their growth,physio-biochemical,and anatomical responses to specific environmental condition.Population adapted to desert/semi-desert showed vigorous growth(plant height,shoot length,and number of leaves),enhanced photosynthetic level(chlorophyll a,chlorophyll b,carotenoids,and total chlorophyll),and apparent anatomical modifications such as increased stem radius,cuticle thickness,storage parenchyma tissues(cortex and pith),and vascular bundles in stems,while the maximum of midrib and lamina thickness,epidermal cells,cuticle thickness,cortical proportion,abaxial stomatal density,and its area in leaves.There was high plasticity in structural and functional features of these populations,which enable them to survive and tolerate under such hot and dry desert environment.Population of saline areas exhibited very critical modifications to sustain under salt prone environment.At physiological level,it possesses the maximum amount of organic osmolytes(glycine betaine and proline)and antioxidants(superoxide dismutase(SOD),catalase(CAT),and peroxidase(POD)),while at anatomical level,it showed intensive sclerification,large phloem region(inner and outer),pith parenchyma cells,and metaxylem vessels in stems and leaves.The population of dry mountains showed very distinctive features,such as increased shoot ionic contents(K+and Ca2+),collenchyma and sclerenchyma thickness in stems,trichomes size,and numerous small stomata on abaxial surface of leaves.It is concluded that no definite or precise single character can be taken as a yardstick for adjudging the biomass production in this rubber bush weed population.展开更多
In the paper [1], authors have suggested and analyzed a predictor-corrector Halley method for solving nonlinear equations. In this paper, we modified this method by using the finite difference scheme, which had a quan...In the paper [1], authors have suggested and analyzed a predictor-corrector Halley method for solving nonlinear equations. In this paper, we modified this method by using the finite difference scheme, which had a quantic convergence. We have compared this modified Halley method with some other iterative methods of ninth order, which shows that this new proposed method is a robust one. Some examples are given to illustrate the efficiency and the performance of this new method.展开更多
In account of the famous Cebysev inequality, a rich theory has appeared in the literature. We establish some new weighted Cebysev type integral inequalities. Our proofs are of independent interest and provide new esti...In account of the famous Cebysev inequality, a rich theory has appeared in the literature. We establish some new weighted Cebysev type integral inequalities. Our proofs are of independent interest and provide new estimates on these types of inequalities.展开更多
The need for the analysis of modern businesses is rapidly increasing as the supporting enterprise systems generate more and more data.This data can be extremely valuable for executing organizations because the data al...The need for the analysis of modern businesses is rapidly increasing as the supporting enterprise systems generate more and more data.This data can be extremely valuable for executing organizations because the data allows constant monitoring,analyzing,and improving the underlying processes,which leads to the reduction of cost and the improvement of the quality.Process mining is a useful technique for analyzing enterprise systems by using an event log that contains behaviours.This research focuses on the process discovery and refinement using real-life event log data collected from a large multinational organization that deals with coatings and paints.By investigating and analyzing their order handling pro-cesses,this study aims at learning a model that gives insight inspection of the processes and performance analysis.Furthermore,the animation is also performed for the better inspection,diagnostics,and compliance-related questions to specify the system.The configuration of the system and the conformance checking for further enhancement is also addressed in this research.To achieve the objectives,this research uses process mining techniques,i.e.process discovery in the form of formal Petri nets models with the help of process maps,and process refinement through conformance checking and enhancement.Initially,the identified executed process is reconstructed by using the process discovery techniques.Following the reconstruction,we perform a deep analysis for the underlying process to ensure the process improvement and redesigning.Finally,some recommendations are made to improve the enterprise management system processes.展开更多
Numerical solutions are obtained for non-steady, incompressible fluid flow between two parallel disks which at time t are separated by a distance H(1-αt)1/2 and a magnetic field proportional to B0(1-αt) -1/2 is appl...Numerical solutions are obtained for non-steady, incompressible fluid flow between two parallel disks which at time t are separated by a distance H(1-αt)1/2 and a magnetic field proportional to B0(1-αt) -1/2 is applied perpendicular to the disks where H denotes a representative length, BO denotes a representative magnetic field and α-1 denotes a representative time. Similarity transformations are used to convert the governing partial differential equations of motion in to ordinary differential form. The resulting ordinary differential equations are solved numerically using SOR method, Richardson extrapolation and Simpson’s (1/3) Rule. Our numerical scheme is straightforward, efficient and easy to program.展开更多
The problem of a micropolar fluid about an accelerated disk rotating with angular velocity Ω proportional to time has been studied. By means of the usual similarity transformations, the governing equations are reduce...The problem of a micropolar fluid about an accelerated disk rotating with angular velocity Ω proportional to time has been studied. By means of the usual similarity transformations, the governing equations are reduced to ordinary non-linear differential equations and then solved numerically, using SOR method and Simpson’s (1/3) rule for s ≥ 0, where s is non-dimensional parameter which measures unsteadiness. The calculations have been carried out using three different grid sizes to check the accuracy of the results. The results have been improved by using Richardson’s extrapolation.展开更多
Non-spherical particles are extensively encountered in the process industry such as feedstock or catalysts e.g.,energy,food,pharmaceuticals,and chemicals.The design of equipment used to process these particles is high...Non-spherical particles are extensively encountered in the process industry such as feedstock or catalysts e.g.,energy,food,pharmaceuticals,and chemicals.The design of equipment used to process these particles is highly dependent upon the accurate and reliable modeling of hydrodynamics of particulate media involved.Drag coefficient of these particles is the most significant of all parameters.A universal model to predict the drag coefficient of such particles has not yet been developed due to the diversity and complexity of particle shapes and sizes.Taking this into consideration,we propose a unique approach to model the drag coefficient of non-spherical particles using machine learning(ML)to move towards generalization.A comprehensive database of approximately five thousand data points from reliable experiments and high-resolution simulations was compiled,covering a wide range of conditions.The drag coefficient was modeled as a function of Reynolds number,sphericity,Corey Shape Factor,aspect ratio,volume fraction,and angle of incidence.Three ML techniques—Artificial Neural Networks,Random Forest,and AdaBoost—were used to train the models.All models demonstrated strong generalization when tested on unseen data.However,AdaBoost outperformed the others with the lowest MAPE(20.1%)and MRD(0.069).Additional analysis on excluded data confirmed the robust predictive abilities and generalization of the proposed model.The models were also evaluated across three flow regimes—Stokes,transitional,and turbulent—to further assess their generalization.A comparative analysis with well-known empirical correlations,such as Haider and Levenspiel and Chien,showed that all ML models outperformed traditional approaches,with AdaBoost achieving the best results.The current work demonstrates that new generated ML techniques can be reliably used to predict drag coefficient of non-spherical particles paving way towards generalization of ML approach.展开更多
基金Higher Education Commission,Pakistan,under the National Research Program for Universities Project,Grant/Award Number:NBU-FPEJ-2024-1243-02。
文摘A grey-box modelling framework was developed for the estimation of cut point temperature of a crude distillation unit(CDU)under uncertainty in crude composition and process conditions.First principle(FP)model of CDU was developed for Pakistani crudes from Zamzama and Kunnar fields.A hybrid methodology based on the integration of Taguchi method and genetic algorithm(GA)was employed to estimate the optimal cut point temperature for various sets of process variables.Optimised datasets were utilised to develop an artificial neural networks(ANN)model for the prediction of optimum values of cut points.The ANN model was then used to replace the hybrid framework of the Taguchi method and the GA.The integration of the ANN and FP model makes it a grey-box(GB)model.For the case of Zamama crude,the GB model helped in the decrease of up to 38.93%in energy required per kilo barrel of diesel and an 8.2%increase in diesel production compared to the stand-alone FP model under uncertainty.Similarly,for Kunnar crude,up to 18.87%decrease in energy required per kilo barrel of diesel and a 33.96%increase in diesel production was observed in comparison to the stand-alone FP model.
基金funding by the National Natural Science Foundation of China(Grant number U22A20187)(Grant No.52271147,No.52471175)China Postdoctoral Science Foundation(grant number 2024M751172)。
文摘Recrystallization stands as an essential process that influences the microstructure and properties of magnesium(Mg)alloys,yet its mechanisms remain complex and multifaceted.This review explores the key factors affecting the recrystallization behavior of Mg alloys,emphasizing how their unique structural characteristics impact the driving forces and dynamics of recrystallization.Unlike conventional alloys,Mg alloys exhibit distinctive recrystallization kinetics,which is significantly affected by deformation conditions,such as strain rate,temperature,and processing methods(e.g.,rolling,forging,and extrusion).The process is also influenced by material characteristics,including initial grain size,texture,dislocation density,solute clustering,and stacking fault energy.Additionally,uneven strain distribution,stress concentrations,and stored energy play crucial roles in shaping the formation of recrystallized grains,particularly near grain boundaries.Notably,recrystallization is driven by dislocation accumulation and the availability of slip systems,with new strain-free grains typically forming in regions of high dislocation density.This paper synthesizes the existing literature to provide a comprehensive understanding of the mechanisms and kinetics of recrystallization in Mg alloys,highlighting the influence of microstructural features such as second-phase particles and grain boundary characteristics.It also identifies key challenges and suggests promising directions for future research,including optimizing material compositions and the interaction between deformation conditions via machine learning.
基金supported by the National Natural Science Foundation of China(NSFC,52130601)the Joint Research Center for Multi-energy Complementation and Conversion of USTC.
文摘Lithium-based batteries(LiBs)are integral components in operating electric vehicles to renewable energy systems and portable electronic devices,thanks to their unparalleled energy density,minimal self-discharge rates,and favorable cycle life.However,the inherent safety risks and performance degradation of LiB over time impose continuous monitoring facilitated by sophisticated battery management systems(BMS).This review comprehensively analyzes the current state of sensor technologies for smart LiBs,focusing on their advancements,opportunities,and potential challenges.Sensors are classified into two primary groups based on their application:safety monitoring and performance optimization.Safety monitoring sensors,including temperature,pressure,strain,gas,acoustic,and magnetic sensors,focus on detecting conditions that could lead to hazardous situations.Performance optimization sensors,such as optical-based and electrochemical-based,monitor factors such as state of charge and state of health,emphasizing operational efficiency and lifespan.The review also highlights the importance of integrating these sensors with advanced algorithms and control approaches to optimize charging and discharge cycles.Potential advancements driven by nanotechnology,wireless sensor networks,miniaturization,and machine learning algorithms are also discussed.However,challenges related to sensor miniaturization,power consumption,cost efficiency,and compatibility with existing BMS need to be addressed to fully realize the potential of LiB sensor technologies.This comprehensive review provides valuable insights into the current landscape and future directions of sensor innovations in smart LiBs,guiding further research and development efforts to enhance battery performance,reliability,and safety.Integration of advanced sensor technologies for smart LiBs:integrating non-optical multi-parameter,optical-based,and electrochemical sensors within the BMS to achieve higher safety,improved efficiency,early warning mechanisms,and TR prevention.Potential advancements are driven by nanotechnology,wireless sensor networks,miniaturization,and advanced algorithms,addressing key challenges to enhance battery performance and reliability.
基金National Research Program for Universities,Grant/Award Number:10215/FederalNorthern Border University,Arar,KSA,Grant/Award Number:NBU-FPEJ-2024-1243-01。
文摘In this study,a Grey-box(GB)model was developed to predict the optimum mass flow rates of inlet streams of a Shell and Tube Heat Exchanger(STHE)under varying process conditions.Aspen Exchanger Design and Rating(Aspen-EDR)was initially used to construct a first principle model(FP)of the STHE using industrial data.The Genetic Algorithm(GA)was incorporated into the FP model to attain the minimum exit temperature for the hot kerosene process stream under varying process conditions.A dataset comprised of optimum process conditions was generated through FP-GA integration and was utilised to develop an Artificial Neural Networks(ANN)model.Subsequently,the ANN model was merged with the FP model by substituting the GA,to form a GB model.The developed GB model,that is,ANN and FP integration,achieved higher effectiveness and lower outlet temperature than those derived through the standalone FP model.Performance of the GB framework was also comparable to the FP-GA approach but it significantly reduced the computation time required for estimating the optimum process conditions.The proposed GB-based method improved the STHE's ability to extract energy from the process stream and strengthened its resilience to cope with diverse process conditions.
基金supported by the National Natural Science Foundation of China(No.U22A20187,No.52271147,No.12261160364).
文摘Twinning is widely recognized as an effective and cost-efficient method for controlling the microstructure and properties of wrought magnesium(Mg)alloys.Specifically,twins play a crucial role in initiating dynamic recrystallization(DRX),while twin regions experience rapid recrystallization during static recrystallization(SRX).The activation of twinning can lead to changes in lattice orientation,significantly impacting the final texture in Mg alloys.The active roles of twinning are influenced by various factors during the activation process,and the mobility of twin boundaries(TB)can be amplified by stress effects,dislocation interactions,and thermal effects.Conversely,annealing treatments that involve proper segregation or precipitation on TBs serve to stabilize them,restraining their motion.Events such as segregation may also alter the twinning propensity in Magnesium-rare earth(Mg-RE)alloys.While{10–11}contraction twins(CT)and{10–11}-{10–12}double twins(DT)can promote dynamic recrystallization(DRX),they also pose a risk as potential sources of voids and cracks.Additionally,understanding the nucleation and growth mechanisms of twinning is crucial,and these aspects are briefly reviewed in this article.Considering the factors mentioned above,this article summarizes the recent research progress in this field,shedding light on advancements in recent eras.
文摘Cerebellopontine angle (CPA) lesions account for up to 10% of all intracranial tumors. Most CPA tumors are benign, but can cause nerve damage or compress the surrounding structures if left untreated. The typical presentation is with adult-onset sensorineural hearing loss or non-pulsatile tinnitus. In some patients, this goes unnoticed, and presentation is delayed until the lesion is much larger and presents with symptoms related to mass effect. We present the case study of 63 years old gentleman, who had suspected left CPA lesion on CT head done few years ago for dizziness and left-sided facial numbness. MRI could not be done at that time due to his MRI incompatible pacemaker leading to delay in his management eventually causing loss of patient to the follow up. He later developed progressive difficulty in walking which was initially attributed to as secondary to vasovagal syncope and postural hypotension. He eventually presented to us with intractable nausea and vomiting, worsening headache and ataxia. He had an urgent CT head which showed significant growth in the lesion with compression of the surrounding structures and obstructive hydrocephalus. He was given steroids which improved his nausea and vomiting, followed by undergoing surgery in regional center leading to significant improvement in his gait within few days of surgery. He unfortunately continued to have a degree of ataxia and facial numbness. This case illustrates a rare presentation of CPA tumor with symptoms of nausea and vomiting as a result of mass effect of the growing tumor. In addition, this review also shows the importance of regularly following up the patients with suspected CPA lesions on initial scans which will help with identifying the increase in size of lesion promptly and potentially preventing advanced complications of CPA tumors. We suggest regular monitoring of these patients to timely manage the lesion and avoid the potential life-threatening complications.
文摘Hypophosphataemia is defined as low level of phosphate in the blood (normal range 0.8 - 1.4 mmol/l), which can be drug-induced such as uniphyline. We present a case of elderly female patient with known chronic obstructive pulmonary disease, admitted with acute respiratory failure and low serum phosphate level, her clinical signs and serum phosphate level did not improve with conventional therapy and intravenous phosphate replacement, until her recently commenced uniphyline was discontinued. This highlights the importance of awareness amongst the clinicians about this rare but potential side effect of uniphyline. We suggest monitoring phosphate levels in patients admitted with acute respiratory failure especially those on extended bronchodilator therapy.
文摘The problem of a disk rotating in a viscous fluid has been investigated. The disk is accelerated with angular velocity proportional to time. Employing suitable similarity transformations the governing partial differential equations are transformed in to ordinary differential form. The resulting equations are solved numerically using SOR method and Simpson’s (1/3) rule. The results have been improved by using Richardson’s extrapolation. The effect of the non-dimensional parameter s which measures unsteadiness is observed on velocity components, skin friction coefficient and torque of the disk.
文摘Oxidation of sulfide in aqueous solution by hydrogen peroxide was investigated in the presence of hydrated ferric oxide catalyst. The ferric oxide catalyst was synthesized by sol gel technique from ferric chloride and ammonia. The synthesized catalyst was characterized by Fourier transform infrared spectroscopy, X-Ray diffraction analysis, scanning electrom microscope and energy dispersive X-ray analysis. The catalyst was quite effective in oxidizing the sulfide by hydrogen peroxide. The effects of sulfide concentration, catalyst loading, H2O2 dosing and temperature on the kinetics of sulfide oxidation were investigated. Kinetic equations and activation energies for the catalytic oxidation reaction were calculated based on the experimental results.
文摘Calotropis procera(Aiton)W.T.Aiton,belonging to the family Apocynaceae,is C3 evergreen plant species in arid and semi-arid areas of the Punjab Province,Pakistan.It grows in a variety of habitats like salt affected and waterlogged area,desert/semi-desert,roadside,wasteland,graveyard,forest,crop field,coastline,and river/canal bank.A total of 12 populations growing in different ecological regions were sampled to evaluate their growth,physio-biochemical,and anatomical responses to specific environmental condition.Population adapted to desert/semi-desert showed vigorous growth(plant height,shoot length,and number of leaves),enhanced photosynthetic level(chlorophyll a,chlorophyll b,carotenoids,and total chlorophyll),and apparent anatomical modifications such as increased stem radius,cuticle thickness,storage parenchyma tissues(cortex and pith),and vascular bundles in stems,while the maximum of midrib and lamina thickness,epidermal cells,cuticle thickness,cortical proportion,abaxial stomatal density,and its area in leaves.There was high plasticity in structural and functional features of these populations,which enable them to survive and tolerate under such hot and dry desert environment.Population of saline areas exhibited very critical modifications to sustain under salt prone environment.At physiological level,it possesses the maximum amount of organic osmolytes(glycine betaine and proline)and antioxidants(superoxide dismutase(SOD),catalase(CAT),and peroxidase(POD)),while at anatomical level,it showed intensive sclerification,large phloem region(inner and outer),pith parenchyma cells,and metaxylem vessels in stems and leaves.The population of dry mountains showed very distinctive features,such as increased shoot ionic contents(K+and Ca2+),collenchyma and sclerenchyma thickness in stems,trichomes size,and numerous small stomata on abaxial surface of leaves.It is concluded that no definite or precise single character can be taken as a yardstick for adjudging the biomass production in this rubber bush weed population.
文摘In the paper [1], authors have suggested and analyzed a predictor-corrector Halley method for solving nonlinear equations. In this paper, we modified this method by using the finite difference scheme, which had a quantic convergence. We have compared this modified Halley method with some other iterative methods of ninth order, which shows that this new proposed method is a robust one. Some examples are given to illustrate the efficiency and the performance of this new method.
文摘In account of the famous Cebysev inequality, a rich theory has appeared in the literature. We establish some new weighted Cebysev type integral inequalities. Our proofs are of independent interest and provide new estimates on these types of inequalities.
文摘The need for the analysis of modern businesses is rapidly increasing as the supporting enterprise systems generate more and more data.This data can be extremely valuable for executing organizations because the data allows constant monitoring,analyzing,and improving the underlying processes,which leads to the reduction of cost and the improvement of the quality.Process mining is a useful technique for analyzing enterprise systems by using an event log that contains behaviours.This research focuses on the process discovery and refinement using real-life event log data collected from a large multinational organization that deals with coatings and paints.By investigating and analyzing their order handling pro-cesses,this study aims at learning a model that gives insight inspection of the processes and performance analysis.Furthermore,the animation is also performed for the better inspection,diagnostics,and compliance-related questions to specify the system.The configuration of the system and the conformance checking for further enhancement is also addressed in this research.To achieve the objectives,this research uses process mining techniques,i.e.process discovery in the form of formal Petri nets models with the help of process maps,and process refinement through conformance checking and enhancement.Initially,the identified executed process is reconstructed by using the process discovery techniques.Following the reconstruction,we perform a deep analysis for the underlying process to ensure the process improvement and redesigning.Finally,some recommendations are made to improve the enterprise management system processes.
文摘Numerical solutions are obtained for non-steady, incompressible fluid flow between two parallel disks which at time t are separated by a distance H(1-αt)1/2 and a magnetic field proportional to B0(1-αt) -1/2 is applied perpendicular to the disks where H denotes a representative length, BO denotes a representative magnetic field and α-1 denotes a representative time. Similarity transformations are used to convert the governing partial differential equations of motion in to ordinary differential form. The resulting ordinary differential equations are solved numerically using SOR method, Richardson extrapolation and Simpson’s (1/3) Rule. Our numerical scheme is straightforward, efficient and easy to program.
文摘The problem of a micropolar fluid about an accelerated disk rotating with angular velocity Ω proportional to time has been studied. By means of the usual similarity transformations, the governing equations are reduced to ordinary non-linear differential equations and then solved numerically, using SOR method and Simpson’s (1/3) rule for s ≥ 0, where s is non-dimensional parameter which measures unsteadiness. The calculations have been carried out using three different grid sizes to check the accuracy of the results. The results have been improved by using Richardson’s extrapolation.
文摘Non-spherical particles are extensively encountered in the process industry such as feedstock or catalysts e.g.,energy,food,pharmaceuticals,and chemicals.The design of equipment used to process these particles is highly dependent upon the accurate and reliable modeling of hydrodynamics of particulate media involved.Drag coefficient of these particles is the most significant of all parameters.A universal model to predict the drag coefficient of such particles has not yet been developed due to the diversity and complexity of particle shapes and sizes.Taking this into consideration,we propose a unique approach to model the drag coefficient of non-spherical particles using machine learning(ML)to move towards generalization.A comprehensive database of approximately five thousand data points from reliable experiments and high-resolution simulations was compiled,covering a wide range of conditions.The drag coefficient was modeled as a function of Reynolds number,sphericity,Corey Shape Factor,aspect ratio,volume fraction,and angle of incidence.Three ML techniques—Artificial Neural Networks,Random Forest,and AdaBoost—were used to train the models.All models demonstrated strong generalization when tested on unseen data.However,AdaBoost outperformed the others with the lowest MAPE(20.1%)and MRD(0.069).Additional analysis on excluded data confirmed the robust predictive abilities and generalization of the proposed model.The models were also evaluated across three flow regimes—Stokes,transitional,and turbulent—to further assess their generalization.A comparative analysis with well-known empirical correlations,such as Haider and Levenspiel and Chien,showed that all ML models outperformed traditional approaches,with AdaBoost achieving the best results.The current work demonstrates that new generated ML techniques can be reliably used to predict drag coefficient of non-spherical particles paving way towards generalization of ML approach.
