The solid electrolyte interphase(SEI)layer,formed on the electrode through electrolyte decomposition,has garnered significant attention over the past several decades.Numerous characterization studies have shown that t...The solid electrolyte interphase(SEI)layer,formed on the electrode through electrolyte decomposition,has garnered significant attention over the past several decades.Numerous characterization studies have shown that the SEI enhances the stability of both the electrolyte and electrode,particularly by mitigating the well-known cation-solvent co-intercalation in graphite electrodes in lithium-ion batteries.However,recent electrolyte exchange experiments have revealed that variations in electrolyte solvation structure and the resulting desolvation behaviors play a more dominant role than the SEI in influencing electrolyte and electrode stability,which in turn critically impacts battery performance.In addition to contributing to the ongoing debate,electrolyte exchange experiments have proven to be a valuable tool for analyzing failures in electrolytes,electrodes,and batteries.This review highlights the application of electrolyte exchange experiments across various metal-ion batteries,incorporating diverse combinations of electrolytes and electrodes.It examines the influence of electrolyte solvation structures and desolvation behaviors on the stability of both electrolytes and electrodes.The aim is to enhance the methodology of electrolyte exchange experiments to deepen the understanding of the molecular interactions among metal ions,anions,and solvents within the electrolyte.This approach complements existing insights into SEI effects,providing a more thorough and accurate framework for battery failure analysis.展开更多
We propose a fractional-order improved Fitz Hugh–Nagumo(FHN)neuron model in terms of a generalized Caputo fractional derivative.Following the existence of a unique solution for the proposed model,we derive the numeri...We propose a fractional-order improved Fitz Hugh–Nagumo(FHN)neuron model in terms of a generalized Caputo fractional derivative.Following the existence of a unique solution for the proposed model,we derive the numerical solution using a recently proposed L1 predictor–corrector method.The given method is based on the L1-type discretization algorithm and the spline interpolation scheme.We perform the error and stability analyses for the given method.We perform graphical simulations demonstrating that the proposed FHN neuron model generates rich electrical activities of periodic spiking patterns,chaotic patterns,and quasi-periodic patterns.The motivation behind proposing a fractional-order improved FHN neuron model is that such a system can provide a more nuanced description of the process with better understanding and simulation of the neuronal responses by incorporating memory effects and non-local dynamics,which are inherent to many biological systems.展开更多
This research examines the transmission dynamics of the Omicron variant of COVID-19 using SEIQIcRVW and SQIRV models,considering the delay in converting susceptible individuals into infected ones.The significant delay...This research examines the transmission dynamics of the Omicron variant of COVID-19 using SEIQIcRVW and SQIRV models,considering the delay in converting susceptible individuals into infected ones.The significant delays eventually resulted in the pandemic’s containment.To ensure the safety of the host population,this concept integrates quarantine and the COVID-19 vaccine.We investigate the stability of the proposed models.The fundamental reproduction number influences stability conditions.According to our findings,asymptomatic cases considerably impact the prevalence of Omicron infection in the community.The real data of the Omicron variant from Chennai,Tamil Nadu,India,is used to validate the outputs.展开更多
Landslide susceptibility map delineates the potential zones for landslides occurrence. The paper presents a statistical approach through spatial data analysis in GIS for landslide susceptibility mapping in parts of Si...Landslide susceptibility map delineates the potential zones for landslides occurrence. The paper presents a statistical approach through spatial data analysis in GIS for landslide susceptibility mapping in parts of Sikkim Himalaya. Six important causative factors for landslide occurrences were selected and corresponding thematic data layers were prepared in GIS. Topographic maps,satellite image,field data and published maps constitute the input data for thematic layer preparation. Numerical weights for different categories of these factors were determined based on a statistical approach and the weighted thematic layers were integrated in GIS environment to generate the landslide susceptibility map of the area. The landslide susceptibility map classifies the area into five different landslide susceptible zones i.e.,very high,high,moderate,low and very low. This map was validated using the existing landslide distribution in the area.展开更多
The aim of this research is to develop a mechanism to help medical practitioners predict and diagnose liver disease.Several systems have been proposed to help medical experts by diminishing error and increasing accura...The aim of this research is to develop a mechanism to help medical practitioners predict and diagnose liver disease.Several systems have been proposed to help medical experts by diminishing error and increasing accuracy in diagnosing and predicting diseases.Among many existing methods,a few have considered the class imbalance issues of liver disorder datasets.As all the samples of liver disorder datasets are not useful,they do not contribute to learning about classifiers.A few samples might be redundant,which can increase the computational cost and affect the performance of the classifier.In this paper,a model has been proposed that combines noise filter,fuzzy sets,and boosting techniques(NFFBTs)for liver disease prediction.Firstly,the noise filter(NF)eliminates the outliers from the minority class and removes the outlier and redundant pair from the majority class.Secondly,the fuzzy set concept is applied to handle uncertainty in datasets.Thirdly,the AdaBoost boosting algorithm is trained with several learners viz,random forest(RF),support vector machine(SVM),logistic regression(LR),and naive Bayes(NB).The proposed NFFBT prediction system was applied to two datasets(i.e.,ILPD and MPRLPD)and found that AdaBoost with RF yielded 90.65%and 98.95%accuracy and F1 scores of 92.09%and 99.24%over ILPD and MPRLPD datasets,respectively.展开更多
In this article,we introduce a nonlinear Caputo-type snakebite envenoming model with memory.The well-known Caputo fractional derivative is used to generalize the previously presented integer-order model into a fractio...In this article,we introduce a nonlinear Caputo-type snakebite envenoming model with memory.The well-known Caputo fractional derivative is used to generalize the previously presented integer-order model into a fractionalorder sense.The numerical solution of the model is derived from a novel implementation of a finite-difference predictor-corrector(L1-PC)scheme with error estimation and stability analysis.The proof of the existence and positivity of the solution is given by using the fixed point theory.From the necessary simulations,we justify that the first-time implementation of the proposedmethod on an epidemicmodel shows that the scheme is fully suitable and time-efficient for solving epidemic models.This work aims to show the novel application of the given scheme as well as to check how the proposed snakebite envenoming model behaves in the presence of the Caputo fractional derivative,including memory effects.展开更多
In this work,we use a Predictor–Corrector method to implement and derive an iterative solution of an existing Tuberculosis(TB)model with two fractional derivatives,namely,Caputo–Fabrizio fractional derivative and th...In this work,we use a Predictor–Corrector method to implement and derive an iterative solution of an existing Tuberculosis(TB)model with two fractional derivatives,namely,Caputo–Fabrizio fractional derivative and the new generalized Caputo fractional derivative.We begin by recalling some existing results such as the basic reproduction number R0 and the equilibrium points of the model.Then,we study the global asymptotic stability of disease-free equilibrium of the fractional models.We also prove,for each fractional model,the existence and uniqueness of solutions.An iterative solution of the two models is computed using the Predictor–Corrector method.Using realistic parameter values,we perform numerical simulations for different values of the fractional order.Simulation results permit to conclude that the new generalized Caputo fractional derivative provides a more realistic analysis than the Caputo–Fabrizio fractional derivative and the classical integer-order TB model.展开更多
In this paper,we study two fractional models in the Caputo–Fabrizio sense and Atangana–Baleanu sense,in which the effects of malaria infection on mosquito biting behavior and attractiveness of humans are considered....In this paper,we study two fractional models in the Caputo–Fabrizio sense and Atangana–Baleanu sense,in which the effects of malaria infection on mosquito biting behavior and attractiveness of humans are considered.Using Lyapunov theory,we prove the global asymptotic stability of the unique endemic equilibrium of the integer-order model,and the fractional models,whenever the basic reproduction number R0 is greater than one.By using fixed point theory,we prove existence,and conditions of the uniqueness of solutions,as well as the stability and convergence of numerical schemes.Numerical simulations for both models,using fractional Euler method and Adams–Bashforth method,respectively,are provided to confirm the effectiveness of used approximation methods for different values of the fractional-orderγ.展开更多
A stochastic SIR influenza vertical transmission model is examined in this paper where vaccination and an incidence rate that is not linear are considered.To determine whether testosterone regulates lower sintering HP...A stochastic SIR influenza vertical transmission model is examined in this paper where vaccination and an incidence rate that is not linear are considered.To determine whether testosterone regulates lower sintering HPA axis function in males,we used a stochastic SIR epidemic procedure with divergent influences on ACTH and cortisol.The suppressive effects on cortisol can be attributed to a peripheral(adrenal)locus.Following that,we came to the conclusion that experimental solutions have been discovered and the requisite statistical findings have been examined.Finally,we deduce that the given mathematical model and the results are relevant to medical research.In the future,this research can be further extended to simulate more results in the medical field.展开更多
In this research collection,we estimate the existence of the unique solution for the boundary value problem of nonlinear fractional q-difference equation having the given form c D^(ζ)_(q) v(t)−h(t,v(t))=0,0≤t≤1,α_...In this research collection,we estimate the existence of the unique solution for the boundary value problem of nonlinear fractional q-difference equation having the given form c D^(ζ)_(q) v(t)−h(t,v(t))=0,0≤t≤1,α_(1)v(0)+β_(1)D_(q)v(0)=v(η1),α_(2)v(1)−β_(2)D_(q)v(1)=v(η2),where 1<ζ≤2,(η1,η2)∈(0,1)^(2),α_(i),β_(i)∈R(i=1,2),h∈C([0,1]×R,R)and c Dζq represents the Caputo-type nonclassical q-derivative of orderζ.We use well-known principal of Banach contraction,and Leray–Schauder nonlinear alternative to vindicate the unique solution existence of the given problem.Regarding the applications,some examples are solved to justify our outcomes.展开更多
New atypical pneumonia caused by a virus called Coronavirus(COVID-19)appeared in Wuhan,China in December 2019.Unlike previous epidemics due to the severe acute respiratory syndrome(SARS)and the Middle East respiratory...New atypical pneumonia caused by a virus called Coronavirus(COVID-19)appeared in Wuhan,China in December 2019.Unlike previous epidemics due to the severe acute respiratory syndrome(SARS)and the Middle East respiratory syndrome coronavirus(MERS-CoV),COVID-19 has the particularity that it is more contagious than the other previous ones.In this paper,we try to predict the COVID-19 epidemic peak in Japan with the help of real-time data from January 15 to February 29,2020 with the uses of fractional derivatives,namely,Caputo derivatives,the Caputo–Fabrizio derivatives,and Atangana–Baleanu derivatives in the Caputo sense.The fixed point theory and Picard–Lindel of approach used in this study provide the proof for the existence and uniqueness analysis of the solutions to the noninteger-order models under the investi-gations.For each fractional model,we propose a numerical scheme as well as prove its stability.Using parameter values estimated from the Japan COVID-19 epidemic real data,we perform numerical simulations to confirm the effectiveness of used approxima-tion methods by numerical simulations for different values of the fractional-orderγ,and to give the predictions of COVID-19 epidemic peaks in Japan in a specific range of time intervals.展开更多
In some of the previous decades, we have observed that mathematical modeling hasbecome one of the most interesting research fields and has attracted many researchers.In this regard, thousands of researchers have propo...In some of the previous decades, we have observed that mathematical modeling hasbecome one of the most interesting research fields and has attracted many researchers.In this regard, thousands of researchers have proposed different varieties of mathematicalmodels to study the dynamics of a number of real-world problems. This research workis framed to analyzing the structure of the well-known Lassa hemorrhagic epidemic;adangerous epidemic for pregnant women, via new generalized Caputo type nonintegerorder derivative with the help of a modified Predictor–Corrector scheme. Lassa hemorrhagic disease is an epidemical and biocidal fever, whose negative impacts were initiallyrecognized in the countries of Africa. This virus has killed many pregnant women ascompared to the Ebola epidemic. It was noticed that Lassa virus was isolated in Verocell cultures from a blood pattern, and after 12 days it was ejective, after the climb ofthe sickness. In this research study, necessary theorems and lemmas are reminded toprove the existence of a unique solution and stability of given fractional approximationscheme. All necessary results are reminded to confirm the effectiveness of the proposedapproximation algorithm by graphical observations for various fractional-order values.In our practical calculations, we plotted the graphs for two different values of naturaldeath rate along with various values of given fractional-order operator. Our major target is to show the importance of the proposed modified version of the Predictor–Correctoralgorithm in epidemic studies by exploring the given Lassa hemorrhagic fever dynamics.展开更多
基金supported by the Jilin Provincial Scientific and Technological Development Program(YDZJ202401572ZYTS)the Overseas Expertise Introduction Project for Discipline Innovation of China(D18012)+1 种基金Education Department of Jilin Province(JJKH20240678KJ)the National Natural Science Foundation of China(22122904,22109155,22379136)。
文摘The solid electrolyte interphase(SEI)layer,formed on the electrode through electrolyte decomposition,has garnered significant attention over the past several decades.Numerous characterization studies have shown that the SEI enhances the stability of both the electrolyte and electrode,particularly by mitigating the well-known cation-solvent co-intercalation in graphite electrodes in lithium-ion batteries.However,recent electrolyte exchange experiments have revealed that variations in electrolyte solvation structure and the resulting desolvation behaviors play a more dominant role than the SEI in influencing electrolyte and electrode stability,which in turn critically impacts battery performance.In addition to contributing to the ongoing debate,electrolyte exchange experiments have proven to be a valuable tool for analyzing failures in electrolytes,electrodes,and batteries.This review highlights the application of electrolyte exchange experiments across various metal-ion batteries,incorporating diverse combinations of electrolytes and electrodes.It examines the influence of electrolyte solvation structures and desolvation behaviors on the stability of both electrolytes and electrodes.The aim is to enhance the methodology of electrolyte exchange experiments to deepen the understanding of the molecular interactions among metal ions,anions,and solvents within the electrolyte.This approach complements existing insights into SEI effects,providing a more thorough and accurate framework for battery failure analysis.
文摘We propose a fractional-order improved Fitz Hugh–Nagumo(FHN)neuron model in terms of a generalized Caputo fractional derivative.Following the existence of a unique solution for the proposed model,we derive the numerical solution using a recently proposed L1 predictor–corrector method.The given method is based on the L1-type discretization algorithm and the spline interpolation scheme.We perform the error and stability analyses for the given method.We perform graphical simulations demonstrating that the proposed FHN neuron model generates rich electrical activities of periodic spiking patterns,chaotic patterns,and quasi-periodic patterns.The motivation behind proposing a fractional-order improved FHN neuron model is that such a system can provide a more nuanced description of the process with better understanding and simulation of the neuronal responses by incorporating memory effects and non-local dynamics,which are inherent to many biological systems.
基金supported via funding from Prince Sattam bin Abdulaziz University Project Number(PSAU/2023/R/1444)The first author is partially supported by the University Research Fellowship(PU/AD-3/URF/21F37237/2021 dated 09.11.2021)of PeriyarUniversity,SalemThe second author is supported by the fund for improvement of Science and Technology Infrastructure(FIST)of DST(SR/FST/MSI-115/2016).
文摘This research examines the transmission dynamics of the Omicron variant of COVID-19 using SEIQIcRVW and SQIRV models,considering the delay in converting susceptible individuals into infected ones.The significant delays eventually resulted in the pandemic’s containment.To ensure the safety of the host population,this concept integrates quarantine and the COVID-19 vaccine.We investigate the stability of the proposed models.The fundamental reproduction number influences stability conditions.According to our findings,asymptomatic cases considerably impact the prevalence of Omicron infection in the community.The real data of the Omicron variant from Chennai,Tamil Nadu,India,is used to validate the outputs.
文摘Landslide susceptibility map delineates the potential zones for landslides occurrence. The paper presents a statistical approach through spatial data analysis in GIS for landslide susceptibility mapping in parts of Sikkim Himalaya. Six important causative factors for landslide occurrences were selected and corresponding thematic data layers were prepared in GIS. Topographic maps,satellite image,field data and published maps constitute the input data for thematic layer preparation. Numerical weights for different categories of these factors were determined based on a statistical approach and the weighted thematic layers were integrated in GIS environment to generate the landslide susceptibility map of the area. The landslide susceptibility map classifies the area into five different landslide susceptible zones i.e.,very high,high,moderate,low and very low. This map was validated using the existing landslide distribution in the area.
文摘The aim of this research is to develop a mechanism to help medical practitioners predict and diagnose liver disease.Several systems have been proposed to help medical experts by diminishing error and increasing accuracy in diagnosing and predicting diseases.Among many existing methods,a few have considered the class imbalance issues of liver disorder datasets.As all the samples of liver disorder datasets are not useful,they do not contribute to learning about classifiers.A few samples might be redundant,which can increase the computational cost and affect the performance of the classifier.In this paper,a model has been proposed that combines noise filter,fuzzy sets,and boosting techniques(NFFBTs)for liver disease prediction.Firstly,the noise filter(NF)eliminates the outliers from the minority class and removes the outlier and redundant pair from the majority class.Secondly,the fuzzy set concept is applied to handle uncertainty in datasets.Thirdly,the AdaBoost boosting algorithm is trained with several learners viz,random forest(RF),support vector machine(SVM),logistic regression(LR),and naive Bayes(NB).The proposed NFFBT prediction system was applied to two datasets(i.e.,ILPD and MPRLPD)and found that AdaBoost with RF yielded 90.65%and 98.95%accuracy and F1 scores of 92.09%and 99.24%over ILPD and MPRLPD datasets,respectively.
文摘In this article,we introduce a nonlinear Caputo-type snakebite envenoming model with memory.The well-known Caputo fractional derivative is used to generalize the previously presented integer-order model into a fractionalorder sense.The numerical solution of the model is derived from a novel implementation of a finite-difference predictor-corrector(L1-PC)scheme with error estimation and stability analysis.The proof of the existence and positivity of the solution is given by using the fixed point theory.From the necessary simulations,we justify that the first-time implementation of the proposedmethod on an epidemicmodel shows that the scheme is fully suitable and time-efficient for solving epidemic models.This work aims to show the novel application of the given scheme as well as to check how the proposed snakebite envenoming model behaves in the presence of the Caputo fractional derivative,including memory effects.
文摘In this work,we use a Predictor–Corrector method to implement and derive an iterative solution of an existing Tuberculosis(TB)model with two fractional derivatives,namely,Caputo–Fabrizio fractional derivative and the new generalized Caputo fractional derivative.We begin by recalling some existing results such as the basic reproduction number R0 and the equilibrium points of the model.Then,we study the global asymptotic stability of disease-free equilibrium of the fractional models.We also prove,for each fractional model,the existence and uniqueness of solutions.An iterative solution of the two models is computed using the Predictor–Corrector method.Using realistic parameter values,we perform numerical simulations for different values of the fractional order.Simulation results permit to conclude that the new generalized Caputo fractional derivative provides a more realistic analysis than the Caputo–Fabrizio fractional derivative and the classical integer-order TB model.
文摘In this paper,we study two fractional models in the Caputo–Fabrizio sense and Atangana–Baleanu sense,in which the effects of malaria infection on mosquito biting behavior and attractiveness of humans are considered.Using Lyapunov theory,we prove the global asymptotic stability of the unique endemic equilibrium of the integer-order model,and the fractional models,whenever the basic reproduction number R0 is greater than one.By using fixed point theory,we prove existence,and conditions of the uniqueness of solutions,as well as the stability and convergence of numerical schemes.Numerical simulations for both models,using fractional Euler method and Adams–Bashforth method,respectively,are provided to confirm the effectiveness of used approximation methods for different values of the fractional-orderγ.
文摘A stochastic SIR influenza vertical transmission model is examined in this paper where vaccination and an incidence rate that is not linear are considered.To determine whether testosterone regulates lower sintering HPA axis function in males,we used a stochastic SIR epidemic procedure with divergent influences on ACTH and cortisol.The suppressive effects on cortisol can be attributed to a peripheral(adrenal)locus.Following that,we came to the conclusion that experimental solutions have been discovered and the requisite statistical findings have been examined.Finally,we deduce that the given mathematical model and the results are relevant to medical research.In the future,this research can be further extended to simulate more results in the medical field.
文摘In this research collection,we estimate the existence of the unique solution for the boundary value problem of nonlinear fractional q-difference equation having the given form c D^(ζ)_(q) v(t)−h(t,v(t))=0,0≤t≤1,α_(1)v(0)+β_(1)D_(q)v(0)=v(η1),α_(2)v(1)−β_(2)D_(q)v(1)=v(η2),where 1<ζ≤2,(η1,η2)∈(0,1)^(2),α_(i),β_(i)∈R(i=1,2),h∈C([0,1]×R,R)and c Dζq represents the Caputo-type nonclassical q-derivative of orderζ.We use well-known principal of Banach contraction,and Leray–Schauder nonlinear alternative to vindicate the unique solution existence of the given problem.Regarding the applications,some examples are solved to justify our outcomes.
文摘New atypical pneumonia caused by a virus called Coronavirus(COVID-19)appeared in Wuhan,China in December 2019.Unlike previous epidemics due to the severe acute respiratory syndrome(SARS)and the Middle East respiratory syndrome coronavirus(MERS-CoV),COVID-19 has the particularity that it is more contagious than the other previous ones.In this paper,we try to predict the COVID-19 epidemic peak in Japan with the help of real-time data from January 15 to February 29,2020 with the uses of fractional derivatives,namely,Caputo derivatives,the Caputo–Fabrizio derivatives,and Atangana–Baleanu derivatives in the Caputo sense.The fixed point theory and Picard–Lindel of approach used in this study provide the proof for the existence and uniqueness analysis of the solutions to the noninteger-order models under the investi-gations.For each fractional model,we propose a numerical scheme as well as prove its stability.Using parameter values estimated from the Japan COVID-19 epidemic real data,we perform numerical simulations to confirm the effectiveness of used approxima-tion methods by numerical simulations for different values of the fractional-orderγ,and to give the predictions of COVID-19 epidemic peaks in Japan in a specific range of time intervals.
文摘In some of the previous decades, we have observed that mathematical modeling hasbecome one of the most interesting research fields and has attracted many researchers.In this regard, thousands of researchers have proposed different varieties of mathematicalmodels to study the dynamics of a number of real-world problems. This research workis framed to analyzing the structure of the well-known Lassa hemorrhagic epidemic;adangerous epidemic for pregnant women, via new generalized Caputo type nonintegerorder derivative with the help of a modified Predictor–Corrector scheme. Lassa hemorrhagic disease is an epidemical and biocidal fever, whose negative impacts were initiallyrecognized in the countries of Africa. This virus has killed many pregnant women ascompared to the Ebola epidemic. It was noticed that Lassa virus was isolated in Verocell cultures from a blood pattern, and after 12 days it was ejective, after the climb ofthe sickness. In this research study, necessary theorems and lemmas are reminded toprove the existence of a unique solution and stability of given fractional approximationscheme. All necessary results are reminded to confirm the effectiveness of the proposedapproximation algorithm by graphical observations for various fractional-order values.In our practical calculations, we plotted the graphs for two different values of naturaldeath rate along with various values of given fractional-order operator. Our major target is to show the importance of the proposed modified version of the Predictor–Correctoralgorithm in epidemic studies by exploring the given Lassa hemorrhagic fever dynamics.
