Search

The prediction of oscillators is usually employed in various industrial and technological problems; such as car shock absorbers, bungee jumping, earthquake-proof buildings, musical instruments, metronome and the process of hearing. This manuscript investigates the effects of newly presented fractional operators on free and forced linear oscillators. The second order nonlinear classical governing differential equation of Duffing oscillator is reduced into second order linear classical governing differential equation of free and forced linear oscillators by invoking non-integer order differential operators namely Atangana-Baleanu and Caputo-Fabrizio. The fractionalized differential equation is solved by invoking Laplace transform method for finding the optimal solutions of displacement based on infinite series approach. The solutions of displacement are obtained via Atangana-Baleanu and Caputo-Fabrizio differential operators separately then expressed in terms of elementary and gamma functions. Finally the parametric analysis is depicted graphically on the basis of comparison of modern fractional operators subject to the emerging rheological parameters.

Abstract A comprehensive study about the spread of COVID-19 cases in Turkey and South Africa has been presented in this paper. An exhaustive statistical analysis was performed using data collected from Turkey and South Africa within the period of 11 March 2020 to 3 May 2020 and 05 March and 3 of May, respectively. It was observed that in the case of Turkey, a negative Spearman correlation for the number of infected class and a positive Spearman correlation for both the number of deaths and recoveries were obtained. This implied that the daily infections could decrease, while the daily deaths and number of recovered people could increase under current conditions. In the case of South Africa, a negative Spearman correlation for both daily deaths and daily infected people were obtained, indicating that these numbers may decrease if the current conditions are maintained. The utilization of a statistical technique predicted the daily number of infected, recovered, and dead people for each country; and three results were obtained for Turkey, namely an upper boundary, a prediction from current situation and lower boundary. The histograms of the daily number of newly infected, recovered and death showed a sign of lognormal and normal distribution, which is presented using the Bell curving method parameters estimation. A new mathematical model COVID-19 comprised of nine classes was suggested; of which a formula of the reproductive number, well-poseness of the solutions and the stability analysis were presented in detail. The suggested model was further extended to the scope of nonlocal operators for each case; whereby a numerical method was used to provide numerical solutions, and simulations were performed for different non-integer numbers. Additionally, sections devoted to control optimal and others dedicated to compare cases between Turkey and South Africa with the aim to comprehend why there are less numbers of deaths and infected people in South Africa than Turkey were presented in detail.

In this study, we present new numerical scheme for modified Chua attractor model with fractional operators. However we give numerical solution of the considered model with fractal-fractional operators. Also, we offer error analysis for a general Cauchy problem with fractional and fractal-fractional operators. For numerical solution of the considered equation, we use new numerical scheme which is established with an efficient polynomial known as Newton interpolation polynomial. The results are discussed with some examples and simulations.

Humans are part of nature, and as nature existed before mankind, mathematics was created by humans with the main aim to analyze, understand and predict behaviors observed in nature. However, besides this aspect, mathematicians have introduced some laws helping them to obtain some theoretical results that may not have physical meaning or even a representation in nature. This is also the case in the field of fractional calculus in which the main aim was to capture more complex processes observed in nature. Some laws were imposed and some operators were misused, such as, for example, the Riemann–Liouville and Caputo derivatives that are power-law-based derivatives and have been used to model problems with no power law process. To solve this problem, new differential operators depicting different processes were introduced. This article aims to clarify some misunderstandings about the use of fractional differential and integral operators with non-singular kernels. Additionally, we suggest some numerical discretizations for the new differential operators to be used when dealing with initial value problems. Applications of some nature processes are provided.

Abstract In this study, a wavelet method is developed to solve a system of nonlinear variable-order (V-O) fractional integral equations using the Chebyshev wavelets (CWs) and the Galerkin method. For this purpose, we derive a V-O fractional integration operational matrix (OM) for CWs and use it in our method. In the established scheme, we approximate the unknown functions by CWs with unknown coefficients and reduce the problem to an algebraic system. In this way, we simplify the computation of nonlinear terms by obtaining some new results for CWs. Finally, we demonstrate the applicability of the presented algorithm by solving a few numerical examples.

In this paper, a new version of the strongly coupled nonlinear fractal-fractional Schrödinger equations is introduced by using the fractal-fractional derivatives in the Riemann-Liouville sense with Mittag-Leffler kernel. An accurate operational matrix method based on the shifted Chebyshev cardinal functions is established for solving this new class of problems. Along the way, a new operational matrix of fractal-fractional derivative is derived for these basis functions. The main characteristic of the proposed method is that it transforms solving the original problem to an algebraic system of equations by exploiting the operational matrix techniques.

The presence of heavy metals such as chromium within water sources are considered as one of the most vital problem to the environment. Accumulating of chromium within the human body, can cause various diseases and disorders. Chitosan cross-linked glutaraldehyde adsorbent (formed from the acetyl group of chitin from alkaline solution) is widely a well-known adsorbent fore chromium metal removal present in solution. In the current study, mathematical modelling and the stimulation of thermodynamic parameters were done on crab chitosan cross-linked glutaraldehyde adsorbent for chromium (VI), Cr6+ removal. This was obtained through the prepared dichromate wastewater solution of 0.81 mg/L of Cr6+ per litre of distilled water. Adsorption experiments were also conducted in a bath system and the effect of stirring speed, chitosan cross-linked glutarladehyde dosages, contact time and temperature on the adsorption of Cr6+ were in investigated. The effectiveness of the cross-linked adsorbent at an optimum dosage (0.16 mg/L) for Cr6+) removal, from wastewater solution which was 82.3% of the initial concentration (0.81 mg/L) was found to be 0.8 g at 30 °C. The time required for the latter adsorption process to attain equilibrium was 80 min. For the thermodynamic study of the process of adsorption, properties such as Gibbs free energy (ΔGads), entropy (ΔSads) and enthalpy (ΔHads) values in the temperature ranges from 25 to 65 °C were also calculated in order to characterize the process. The free sorption energy was −47.56 kJ/mol which suggests the process was physical. The enthalpy of adsorption was −18.09 kJ/mol and the Gibbs free energies were all negative, thus the process was spontaneous and exothermic. The observed results in the current study indicated strange behavior that could not be depicted using the classical decay mathematical model. We concluded that only fractional differential operators with different kernels including the exponential decay, the power law and the generalized Mittag-Leffler function could be used to depict such observations.

The present paper describes the mathematical modeling and dynamics of a novel corona virus (2019-nCoV). We describe the brief details of interaction among the bats and unknown hosts, then among the peoples and the infections reservoir (seafood market). The seafood marked are considered the main source of infection when the bats and the unknown hosts (may be wild animals) leaves the infection there. The purchasing of items from the seafood market by peoples have the ability to infect either asymptomatically or symptomatically. We reduced the model with the assumptions that the seafood market has enough source of infection that can be effective to infect people. We present the mathematical results of the model and then formulate a fractional model. We consider the available infection cases for January 21, 2020, till January 28, 2020 and parameterized the model. We compute the basic reproduction number for the data is R0≈2.4829. The fractional model is then solved numerically by presenting many graphical results, which can be helpful for the infection minimization.

In this paper, an extension is paid to an idea of fractal and fractional derivatives which has been applied to a number of ordinary differential equations to model a system of partial differential equations. As a case study, the fractal fractional Schnakenberg system is formulated with the Caputo operator (in terms of the power law), the Caputo-Fabrizio operator (with exponential decay law) and the Atangana-Baleanu fractional derivative (based on the Mittag-Liffler law). We design some algorithms for the Schnakenberg model by using the newly proposed numerical methods. In such schemes, it worth mentioning that the classical cases are recovered whenever α=1 and β=1. Numerical results obtained for different fractal-order (β∈(0,1)) and fractional-order (α∈(0,1)) are also given to address any point and query that may arise.

In the last decades artificial recharge has attracted the attention of many countries where groundwater has been depleted or as a means of enhancing aquifer recharge where natural recharge is being severely affected by climate change. In this work, mathematical models depicting the flow of water within a fractured aquifer with permeable and impermeable rock matrices were considered to depict the flow of water within an artificially recharged aquifer. Using two different types of differential operators, two models were suggested. A model based on the classical differentiation, which does not consider the heterogeneity of the geological formation. A model based on nonlocal differential operator, which is able to include into mathematical formulation the effect of long-range dependency expressing the memory. For the classical case, the Laplace transform operator was used to derive the exact solution. For the nonlocal case, new numerical methods including Adams-Bashforth and Atangana-Seda scheme were used to provide approximate solutions. For each numerical scheme stability and convergence analysis were presented with numerical simulation for different values of fractional order.

Effluent from abattoir industries containing metals ions is known to adversely affect the quality fresh water. Water pollution is a global concern and its effects are difficult to reverse. This study evaluates the efficiency of the use of the shrimp chitosan cross-linked with glutaraldehyde as an adsorbent for the removal of cations in poultry and red meat effluent. The effluent was collected from different abattoirs in the Free State Province in the month of September 2019. Analysis of the physiochemical parameters of both effluent water samples revealed average pH values of between 8.6 and 8.8, electric conductivity (EC) of between 321 and 188 mS/m, turbidity (NTU) values of between 410 and 520, chemical oxygen demand (COD) of between 38 and 259 mg/L and total dissolved solutes (TDS) values of between 1663 and 1813 mg/L. ICP-MS results of both effluent samples showed the presence of alkali (Na and K), alkaline earth metals (Mg, Ca, Sr and Ba) of less than 10 mg/L and transition elements (Cu, Ni, Fe, Cd, Mn and Zn) of ±5 mg/L. The shrimp chitosan cross-linked with glutaraldehyde was first tested on a certified reference material (CRM) to determine the traceability measurement. Results obtained from the CRM revealed an increased adsorption from Sr

The main purpose of this manuscript is to present a new approximation method to find the numerical solution of partial differential equations with Caputo fractional derivatives. We have also included the stability analysis of the proposed technique. To illustrate the effectiveness and reliability of the method, we have examined the method with several numerical examples. The high computational efficiency of the proposed method can be seen by observing the accurate approximate solutions obtained from the process. The suggested procedure is a potent tool and it can be used to solve other similar problems in modeling real-world problems.

In the last past year researchers have relied on the ability of Laplace transform to solve partial, ordinary linear equations with great success. Important analysis in signal analysis including the transfer function, Bode diagram, Nyquist plot and Nichols plot are obtained based on the Laplace transform. The output of the analysis depends only on the results obtained from Laplace transform. However, one weakness of Laplace transform is that the Laplace transform of even function is odd while the Laplace transform of an old function is even which is lack of conservation of properties. On the other hand there exist a similar integral transform known as Sumudu transform has the ability to conserve the properties of the function from real space to complex space. The question that arises in the work, is the following: Can we apply the Sumudu transform to construct new transfer functions that will lead to new Bode, Nichols and Nyquist plots? this question is answered in this work.

The present paper consider a newly introduced operator known as fractal-fractional where the fractional operator considered is Caputo-Fabrizio. We consider a competition system and propose the field data of banks for 2004–2014 of Indonesia banks of the type rural and commercial. The model with fractal-fractional operator known as fractal-fractional Caputo-Fabrizio derivative is formulated and show their analysis. We give a novel method to solve the model numerically and present the graphical results. We consider different values of the fractal and fractional order parameters and compare the results with integer order fitting for real data. We show keeping fractal order fix and varying fractional order, keeping fractional order fix and varying fractal, varying both fractional and fractal order for fixed values, varying values arbitrarily, and for long term, we achieve better results for fitting than that of integer order for commercial and rural data. This new definition of fractal-fractional in the form of Caputo-Fabrizio derivative provide better results than that of the ordinary integer order.

In this study, we extend newly introduced numerical method to partial differential and integral equations with integer and non-integer order. This numerical approximation suggested by Atangana and Seda was constructed with Newton polynomial. Moreover it is accurate and efficient for solving partial differential and integral equations. Also, we present numerical simulation for solution of the considered equation. The numerical results show that this numerical approach is useful and accurate for obtaining numerical solution of such equations.

Abstract Computers and electronics play an enormous role in today’s society, impacting everything from communication and medicine to science. The development of computer-related technologies has led to the emergence of many new important interdisciplinary fields, including the field of image processing. Image processing tries to find new ways to access and extract information from digital images or videos. Due to this great importance, many researchers have tried to utilize new and powerful tools introduced in pure and applied mathematics to develop new concepts in imaging science. One of these valuable research areas is the contents of fractional differential calculus. In recent years, extensive applications to the new fractional operators have been employed in real-world problems. This article attempts to address a practical aspect of this era of research in the edge detecting of an image. For this purpose, two general structures are first proposed for making new fractional masks. Then the components in these two structures are evaluated using the fractional integral Atangana–Baleanu operator. The performance and effectiveness of these proposed designs are illustrated by several numerical simulations. A comparison of the results with the results of several well-known masks in the literature indicates that the results presented in this article are much more accurate and efficient. This is the main achievement of this article. These fractional masks are all novel and have been introduced for the first time in this contribution. Moreover, in terms of computational cost, the proposed fractional masks require almost the same amount of computations as the existing conventional ones. By observing the numerical simulations presented in the paper, it is easily understood that with proper adjustment for the fractional-order parameter, the accuracy of the obtained results can be significantly improved. Each of the new suggested structures in this article can be regarded as a valid and effective alternative for the well-known existing kernels in identifying the edges of an image.

Abstract In the present paper, we formulate a new mathematical model for the dynamics of COVID-19 with quarantine and isolation. Initially, we provide a brief discussion on the model formulation and provide relevant mathematical results. Then, we consider the fractal-fractional derivative in Atangana–Baleanu sense, and we also generalize the model. The generalized model is used to obtain its stability results. We show that the model is locally asymptotically stable if R 0 < 1 $\mathcal{R}_{0}

Abstract In this work, optimal control for a fractional-order nonlinear mathematical model of cancer treatment is presented. The suggested model is determined by a system of eighteen fractional differential equations. The fractional derivative is defined in the Atangana–Baleanu Caputo sense. Necessary conditions for the control problem are derived. Two control variables are suggested to minimize the number of cancer cells. Two numerical methods are used for simulating the proposed optimal system. The methods are the iterative optimal control method and the nonstandard two-step Lagrange interpolation method. In order to validate the theoretical results, numerical simulations and comparative studies are given.

Abstract We consider a nonlinear Cauchy problem involving the Ψ-Hilfer stochastic fractional derivative with uncertainty, and we give a stability result. Using fixed point theory, we are able to provide a fuzzy Ulam–Hyers–Rassias stability for the considered nonlinear stochastic fractional differential equations.

Nonlocal differential and integral operators with fractional order and fractal dimension have been recently introduced and appear to be powerful mathematical tools to model complex real world problems that could not be modeled with classical and nonlocal differential and integral operators with single order. To stress further possible application of such operators, we consider in this work an advection-dispersion model, where the velocity is considered to be 1. We consider three cases of the models, when the kernels are power law, exponential decay law and the generalized Mittag-Leffler kernel. For each case, we present a detailed analysis including, numerical solution, stability analysis and error analysis. We present some numerical simulation.

In this article, we propose a generalization of both b-metric and dislocated metric, namely, dislocated extended b-metric space. After getting some fixed point results, we suggest a relatively simple solution for a Volterra integral equation by using the technique of fixed point in the setting of dislocated extended b-metric space.

Abstract Background The cell-surface attachment protein (Env) of the HERV-K(HML-2) lineage of endogenous retroviruses is a potentially attractive tumour-associated antigen for anti-cancer immunotherapy. The human genome contains around 100 integrated copies (called proviruses or loci) of the HERV-K(HML-2) virus and we argue that it is important for therapy development to know which and how many of these contribute to protein expression, and how this varies across tissues. We measured relative provirus expression in HERV-K(HML-2), using enriched RNA-Seq analysis with both short- and long-read sequencing, in three Mantle Cell Lymphoma cell lines (JVM2, Granta519 and REC1). We also confirmed expression of the Env protein in two of our cell lines using Western blotting, and analysed provirus expression data from all other relevant published studies. Results Firstly, in both our and other reanalysed studies, approximately 10% of the transcripts mapping to HERV-K(HML-2) came from Env-encoding proviruses. Secondly, in one cell line the majority of the protein expression appears to come from one provirus (12q14.1). Thirdly, we find a strong tissue-specific pattern of provirus expression. Conclusions A possible dependency of Env expression on a single provirus, combined with the earlier observation that this provirus is not present in all individuals and a general pattern of tissue-specific expression among proviruses, has serious implications for future HERV-K(HML-2)-targeted immunotherapy. Further research into HERV-K(HML-2) as a possible tumour-associated antigen in blood cancers requires a more targeted, proteome-based, screening protocol that will consider these polymorphisms within HERV-K(HML-2). We include a plan (and necessary alignments) for such work.

The increasing use of composites reinforced with vegetable fibers in the industrial field poses a serious problem of the reliability of the structures produced. For us, this credibility can be ensured when developing the composite, by a judicious choice of matrix and reinforcement, a choice leading to obtaining a material having acceptable mechanical and physicochemical characteristics. The main objective of this study is to characterize a composite material with a clay matrix reinforced with coconut and palm nut fibers. To achieve this objective, we first opted for the implementation of this composite by contact molding, at different fiber percentages (2.5%, 5%, 7.5%, and 10%), and we then subjected our specimens to mechanical tests (three-point bending and compression). The mechanical characterization allowed us to have a Young’s modulus in compression varying between 63.82 and 68.82 MPa for palm nut fibers and from 68.28 to 74.43 MPa for coconut fibers (this allows us to note that our coconut fibers make the material rigid in compression), and a Young’s modulus in bending varying between 5.71 and 6.51 MPa for palm nut fibers and from 6.50 to 6.525 MPa for coconut fibers (this allows us to see that our coconut fibers make the material rigid in bending). The results also show that the rate of water absorption of the composite increases with the increase in the fiber content, which is explained in particular by the fact that the fibers of plant origin are hydrophilic and have a porous character; therefore, they absorb water. This study also shows that there is a reduction in the density of the fiber composite with increasing fiber content.

In the last few months, the spread of COVID-19 among humans has caused serious damages around the globe letting many countries economically unstable. Results obtained from conducted research by epidemiologists and virologists showed that, COVID-19 is mainly spread from symptomatic individuals to others who are in close contact via respiratory droplets, mouth and nose, which are the primary mode of transmission. World health organization regulations to help stop the spread of this deadly virus, indicated that, it is compulsory to utilize respiratory protective devices such as facemasks in the public. Indeed, the use of these facemasks around the globe has helped reduce the spread of COVID-19. The primary aim of facemasks, is to avoid inhaling air that could contain droplets with COVID-19. We should note that, respiration process is the movement of oxygen from external atmosphere to the cells within tissue and the transport of carbon dioxide outside. However, the rebreathing of carbon dioxide using a facemask has not been taken into consideration. The hypercapnia (excess inhaled content of CO2) has been recognized to be related to symptoms of fatigue, discomfort, muscular weakness, headaches as well as drowsiness. Rebreathing of CO2 has been a key to concern regarding the use of a facemask. Rebreathing usually occur when an expired air that is rich in CO2 stays long than normal in the breathing space of the respirator after a breath. The increase of the arterial CO2 concentration leads to symptoms that are aforementioned. Studies have been conducted on facemask shortages and on the appropriate facemask required to reduce the spread of COVID-19; however no study has been conducted to assess the possible relationship between CO2 inhalation due to facemask, to determine and recommend which mask is appropriate in the reduction of the spread of the coronavirus while simultaneously avoid CO2 inhalation by the facemask users. In the current paper, we provided a literature review on the use of facemasks with the aim to determine which facemasks could be used to avoid re-inhaling rejected CO2. Additionally, we presented mathematical models depicting the transport of COVID-19 spread through wind with high speed. We considered first mathematical models for which the effect air-heterogeneity is neglected, such that air flow follows Markovian process with a retardation factor, these models considered two different scenarios, the speed of wind is constant and time–space dependent. Secondly, we assumed that the wind movement could follow different processes, including the power law process, fading memory process and a two-stage processes, these lead us to use differential operators with power law, exponential decay and the generalized Mittag-Leffler function with the aim to capture these processes. A numerical technique based on the Lagrange polynomial interpolation was used to solve some of these models numerically. The numerical solutions were coded in MATLAB software for simulations. The results obtained from the mathematical simulation showed that a wind with speed of 100 km/h could transport droplets as far as 300 m. The results obtained from these simulations together with those presented by other researchers lead us to conclude that, the wind could have helped spread COVID-19 in some places around the world, especially in coastal areas. Therefore, appropriate facemasks that could help avoid re-inhaling enough CO2 should be used every time one is in open air even when alone especially in windy environment.

It is widely known that Tuberculosis (TB) and Human Immunodeficiency Virus (HIV) diseases are closely linked to each other, but the dynamic of TB epidemic in our communities is usually faster than the dynamic of HIV epidemic. In this work, we use the geometric singular perturbation method to sub-divide, investigate and analyze a model of TB-HIV co-infection. The full model is divided into two sub-models: one characterized by a slower dynamic of an HIV transmission and the other by the fast dynamic of the TB infection. The focus here is on the slow dynamic on which non local operators are applied to assess their effects and where a comprehensive stability analysis is performed. We show that it is possible to establish and analyze the dynamic of the original model by only studying the reduced one. This result is corroborated by numerical simulations. Furthermore, non-local operators applied to the slow model show similar results with even a better approximation. However, such approximation is a bit inaccurate when the basic reproduction number of the slow model is greater than one and associated with its endemic equilibrium.

Several collected data representing the spread of some infectious diseases have demonstrated that the spread does not really exhibit homogeneous spread. Clear examples can include the spread of Spanish flu and Covid-19. Collected data depicting numbers of daily new infections in the case of Covid-19 from countries like Turkey, Spain show three waves with different spread patterns, a clear indication of crossover behaviors. While modelers have suggested many mathematical models to depicting these behaviors, it becomes clear that their mathematical models cannot really capture the crossover behaviors, especially passage from deterministic resetting to stochastics. Very recently Atangana and Seda have suggested a concept of piecewise modeling consisting in defining a differential operator piece-wisely. The idea was first applied in chaos and outstanding patterns were captured. In this paper, we extend this concept to the field of epidemiology with the aim to depict waves with different patterns. Due to the novelty of this concept, a different approach to insure the existence and uniqueness of system solutions are presented. A piecewise numerical approach is presented to derive numerical solutions of such models. An illustrative example is presented and compared with collected data from 3 different countries including Turkey, Spain and Czechia. The obtained results let no doubt for us to conclude that this concept is a new window that will help mankind to better understand nature.

Background: Buruli ulcer (BU) is a cutaneous infectious disease caused by Mycobacterium ulcerans. In this prospective study, we aim to clarify the main histopathological features of cutaneous BU based on 4-mm skin punch biopsies and to evaluate the diagnostic value of this method. Methods: Between 2011 and 2013, a prospective study was conducted in Cameroon. Dry swabs from ulcerative lesions and fine-needle aspirates of nonulcerative lesions were examined for Ziehl-Neelsen (ZN) staining, followed by PCR targeting IS2404 and culture. Two 4-mm punch biopsies were performed in the center and in the periphery of each lesion. Results: The 364 patients included in the study had 422 lesions (381 were ulcerative and 357 lesions were biopsied). Among the 99 ulcerated lesions with a final diagnosis of BU, histological features for BU were fulfilled in 32 lesions. 32/32 showed subcutaneous necrosis with a neutrophilic inflammatory infiltrate. 26/32 presented alcohol-resistant bacilli confirmed by ZN stain on histology. Conclusion: Punch biopsies help in establishing the correct diagnosis of BU and also in the differential diagnosis of chronic ulcers. The main histological feature for BU is diffuse coagulative necrosis of subcutaneous tissue, with acid-fast bacilli detected by ZN stain.

Mucosal-associated invariant T (MAIT) cells are a population of innate-like T cells that utilize a semi-invariant T cell receptor (TCR) α chain and are restricted by the highly conserved antigen presenting molecule MR1. MR1 presents microbial riboflavin biosynthesis derived metabolites produced by bacteria and fungi. Consistent with their ability to sense ligands derived from bacterial sources, MAIT cells have been associated with the immune response to a variety of bacterial infections, such as Mycobacterium spp., Salmonella spp. and Escherichia coli. To date, MAIT cells have been studied in humans, non-human primates and mice. However, they have only been putatively identified in cattle by PCR based methods; no phenotypic or functional analyses have been performed. Here, we identified a MAIT cell population in cattle utilizing MR1 tetramers and high-throughput TCR sequencing. Phenotypic analysis of cattle MAIT cells revealed features highly analogous to those of MAIT cells in humans and mice, including expression of an orthologous TRAV1-TRAJ33 TCR α chain, an effector memory phenotype irrespective of tissue localization, and expression of the transcription factors PLZF and EOMES. We determined the frequency of MAIT cells in peripheral blood and multiple tissues, finding that cattle MAIT cells are enriched in mucosal tissues as well as in the mesenteric lymph node. Cattle MAIT cells were responsive to stimulation by 5-OP-RU and riboflavin biosynthesis competent bacteria in vitro. Furthermore, MAIT cells in milk increased in frequency in cows with mastitis. Following challenge with virulent Mycobacterium bovis, a causative agent of bovine tuberculosis and a zoonosis, peripheral blood MAIT cells expressed higher levels of perforin. Thus, MAIT cells are implicated in the immune response to two major bacterial infections in cattle. These data suggest that MAIT cells are functionally highly conserved and that cattle are an excellent large animal model to study the role of MAIT cells in important zoonotic infections.

Outbreaks that occur as a result of zoonotic spillover from an animal reservoir continue to highlight the importance of studying the disease interface between species. One Health approaches recognise the interdependence of human and animal health and the environmental interplay. Improving the understanding and prevention of zoonotic diseases may be achieved through greater consideration of these relationships, potentially leading to better health outcomes across species. In this review, special emphasis is given on the emerging and outbreak pathogen Crimean-Congo Haemorrhagic Fever virus (CCHFV) that can cause severe disease in humans. We discuss the efforts undertaken to better understand CCHF and the importance of integrating veterinary and human research for this pathogen. Furthermore, we consider the use of closely related nairoviruses to model human disease caused by CCHFV. We discuss intervention approaches with potential application for managing CCHFV spread, and how this concept may benefit both animal and human health.

Very recently, the concept of instantaneous change was extended with the aim to accommodate prediction of more complex real world problems that could not be predicted or depicted by the existing rate of change. The extension gave birth to a more general differential operator that to be a derivative associate to the well-known Riemann-Stieltjes integral. In addition to this, using specific functions, one is able to recover all existing local differential operators defined as rate of change. This extended concept is still at its genesis and more works need to be done to establish a Riemann-Stieltjes calculus. In this paper, we aim to present a detailed analysis of an important class of differential equations called stochastic equations with the new classes of differential operators with the global derivative with integer and non-integer orders. We considered many classes as nonlinear Cauchy problems, then we presented existence and the uniqueness of their solutions using the linear growth and the Lipchitz conditions. We derived numerical solutions for each class and presented the error analysis. To show the applicability of these operators, we considered three epidemiological problems, including the zombie virus spread model, the zika virus spread model and Ebola model. We solved each model using the suggested numerical scheme and presented the numerical solutions for different values of fractional order and the global function gt. Our results showed that, more complex real world problems could be depicted using these classes of differential equations.

Background and objectives: Epilepsy is the most prevalent neurological disorder in humans which is characterized by recurrent seizures resulting in neurologic, cognitive, psychological and social consequences. In addition, the automatic identification of brain conditions can be helpful in eye-brain-computer interface. That is why during these last few decades, many researchers focused on the development of classification systems for the automatic analysis and detection of epileptic seizures and eye states, which then can be integrated into implantable devices intended to detect the onset of seizures and trigger a focal treatment to block or suppress the seizures progression and to improve the living conditions of patients. In this impetus, this work aims to develop a novel automated classification system which can be performed to detect and identify whether electroencephalogram (EEG) signals belong to epileptic patients in seizure or seizure-free conditions, or to normal individuals with opened or closed eyes. Methods: The proposed classification system consisted of models based on Jacobi polynomial transforms (JPTs). Discrete Legendre transform (DLT) and discrete Chebychev transform (DChT) firstly extract the beta (β) and gamma (γ) rhythms of EEG signals. Thereafter, different measures of complexity are computed from the EEG signals and their extracted rhythms, and applied as inputs of the least-square support vector machine (LS-SVM) classifier with radial basis function (RBF) kernel. Results: The Kruskal-Wallis statistical test is performed and demonstrated that computed JPTs-based measures of complexity sufficiently discriminate EEG signals since their values are significantly higher for seizure EEG signals as compared to those of seizure-free and normal EEG signals with opened or closed eyes. In addition, these measures are used to construct eleven relevant classification problems using the LS-SVM which gained out area under curve (AUC) between 0.983 and 1 which is still proportional to maximum classification accuracies of 88.75% and 100% for normal with opened eyes versus normal with closed eyes, and normal versus seizure or seizure-free versus seizure classification problems, respectively. Conclusion: Overall, it is found that the proposed classification system extends to be less complex for practical applications and can be suitable for automatic epileptic seizures detection and eye states identification.

Background and objective: Initially, analysis of Electroencephalogram (EEG) signals was purely visual, tedious, time-consuming, and required a physician. Changing this old approach to classification proves to be an extraordinary task that gained much attention and a great deal of effort. With this intention, this comparison study focused on the development of polynomial-based feature extraction methods for epileptic and eye states EEG signals detection using kernel machines. Method: Polynomial transforms are applied to decompose EEG signals in the frequency domain before their analysis using linear and non-linear measures. Thereafter, the standard and kernel extension methods are applied to determine principal components and discriminants which help to extract informative and discriminative low-dimensional features. For direct detection of EEG signals, extracted features are fed into kernel machines namely simple multilayer perceptron neural network (sMLPNN) and least-square support vector machine (LS-SVM). Results: Using the publicly available Bonn-University database, experimental results demonstrated that features extracted using kernel methods are more discriminative than the ones using standard methods. In addition, compared to the LS-SVM, polynomial-based features with sMLPNN gained higher performances. Moreover, obtained predictivity, accuracy, and area under receiver operating curve also demonstrate that kernel machines can detect epileptic and eye states EEG signals with highest performances of 100%, 100% and 1, respectively. Conclusion: Thus, the proposed framework can be efficient for EEG diagnosis. Overall, given the complexity and heterogeneity of the brain, it is likely frameworks of this type that will be required to configure intelligent devices for treating epilepsy and to configure eye-brain-computer interface.

The concept of rate of change gave birth to numerous important theories and applications in mathematics, applied mathematics and other related academic disciplines. For example, differential calculus which is linked to integral calculus via the fundamental theorem of calculus. On one hand, differential calculus provides information regarding the instantaneous speed of change and the inclines of the curvatures. While integral calculus covers the study of accumulations of quantities and regions under or amid curvatures. The founders of the concept of derivative defined the derivative of a function y with a variable x and called it derivative of y with respect to x. In this paper, we define, with the concept of rate of change, a derivative of a function f with respect of a function g. The concept is more general as several newly defined differential operators based on the rate of change can be recovered with an appropriate choice of the function g. Several important properties of this concept are presented in details. Before the presentation of the associated integral, we present a discussion underpinning difference between the Caputo and the Riemann-Liouville derivative. We argue that, it is mathematically incorrect to expect the Caputo derivative to satisify the fundamental theorem of calculus with the Riemann-Liouville since this integral is not the anti-derivative. To overcome this misunderstanding, we introduce a fractional integral operator in Caputo sense and verify the fundamental theorem of calculus with each derivative from Caputo derivative to Atangana-Baleanu derivative in Caputo sense. We present in details the existence and uniqueness of the Cauchy problem with Caputo and Atangana-Baleanu derivatives. We derive the associated integral of the suggested derivative which happens to be the Riemann-Stieltjes integral. This turns to be a clear indication that the conformable and its variants and fractal are derivatives and have as anti-derivative the Riemann-Stieltjes integral. We extend the concept to fractional calculus and present several important properties. Numerical approximations are presented for each case and applications to some real world problems.

This study presents an evaluation of climate and land-use changes induced impacts on water resources of Multan City, Pakistan. Statistical Down Scaling Model (SDSM) and Geographical Information System (GIS) are used for climate change scenario and spatial analyses. Hydrologic Engineering Center’s Hydraulic Modeling System (HEC-HMS) model is used for rainfall-runoff simulation. The investigated results show significant changes in climatological parameters, i.e., an increase in temperature and decrease in precipitation over the last 40 years, and a significant urban expansion is also observed from 2000 to 2020. The increase in temperature and urbanization has reduced the infiltration rate into the soil and increased the runoff flows. The HEC-HMS results indicate that surface runoff gradually increased over the last two decades. Consequently, the depth of the water table in the shallow aquifer has declined by about 0.3 m/year. Projected climate indices stipulate that groundwater depletion will occur in the future. Arsenic levels have exceeded the permissible limit owing to unplanned urban expansion and open dumping of industrial effluents. The results can help an efficient water resources management in Multan.