The Lambert-G Family:Properties,Inference,and Applications

This study proposes a new flexible family of distributions called the Lambert-G family.The Lambert family is very flexible and exhibits desirable properties.Its three-parameter special sub-models provide all significantmonotonic and non-monotonic failure rates.A special sub-model of the Lambert family called the Lambert-Lomax(LL)distribution is investigated.General expressions for the LL statistical properties are established.Characterizations of the LL distribution are addressed mathematically based on its hazard function.The estimation of the LL parameters is discussed using six estimation methods.The performance of this estimation method is explored through simulation experiments.The usefulness and flexibility of the LL distribution are demonstrated empirically using two real-life data sets.The LL model better fits the exponentiated Lomax,inverse power Lomax,Lomax-Rayleigh,power Lomax,and Lomax distributions.

Numerical Analysis of Bacterial Meningitis Stochastic Delayed Epidemic Model through Computational Methods

Based on theWorld Health Organization(WHO),Meningitis is a severe infection of the meninges,the membranes covering the brain and spinal cord.It is a devastating disease and remains a significant public health challenge.This study investigates a bacterial meningitis model through deterministic and stochastic versions.Four-compartment population dynamics explain the concept,particularly the susceptible population,carrier,infected,and recovered.The model predicts the nonnegative equilibrium points and reproduction number,i.e.,the Meningitis-Free Equilibrium(MFE),and Meningitis-Existing Equilibrium(MEE).For the stochastic version of the existing deterministicmodel,the twomethodologies studied are transition probabilities and non-parametric perturbations.Also,positivity,boundedness,extinction,and disease persistence are studiedrigorouslywiththe helpofwell-known theorems.Standard and nonstandard techniques such as EulerMaruyama,stochastic Euler,stochastic Runge Kutta,and stochastic nonstandard finite difference in the sense of delay have been presented for computational analysis of the stochastic model.Unfortunately,standard methods fail to restore the biological properties of the model,so the stochastic nonstandard finite difference approximation is offered as an efficient,low-cost,and independent of time step size.In addition,the convergence,local,and global stability around the equilibria of the nonstandard computational method is studied by assuming the perturbation effect is zero.The simulations and comparison of the methods are presented to support the theoretical results and for the best visualization of results.

Tea Production Response to Seasonal Rainfall Variability: Evidence from Rwanda

Tea is a very important cash crop in Rwanda, as it provides crucial income and employment for farmers in poor rural areas. From 2017 to 2020, this study was intended to determine the impact of seasonal rainfall on tea output in Rwanda while still considering temperature, plot size (land), and fertiliser for tea plantations in three of Rwanda’s western, southern, and northern provinces, western province with “Gisovu” and “Nyabihu”, southern with “Kitabi”, and northern with “Mulindi” tea company. The study tested the level of statistical significance of all considered variables in different formulation of panel data models to assess individual behaviour of independent variables that would affect tea production. According to this study, a positive change in rainfall of 1 mm will increase tea production by 0.215 percentage points of tons of fresh leaves. Rainfall is a statistically significant variable among all variables with a positive impact on tea output Qitin Rwanda’s Western, Southern, and Northern provinces. Rainfall availability favourably affects tea output and supports our claim. Therefore, there is a need for collaboration efforts towards developing sustainable adaptation and mitigation options against climate change, targeting tea farming and the government to ensure that tea policy reforms are targeted towards raising the competitiveness of Rwandan tea at local and global market.

Mathematical Analysis of Novel Coronavirus (2019-nCov) Delay Pandemic Model

In this manuscript,the mathematical analysis of corona virus model with time delay effect is studied.Mathematical modelling of infectious diseases has substantial role in the different disciplines such as biological,engineering,physical,social,behavioural problems and many more.Most of infectious diseases are dreadful such as HIV/AIDS,Hepatitis and 2019-nCov.Unfortunately,due to the non-availability of vaccine for 2019-nCov around the world,the delay factors like,social distancing,quarantine,travel restrictions,holidays extension,hospitalization and isolation are used as key tools to control the pandemic of 2019-nCov.We have analysed the reproduction number𝐑𝐑𝐧𝐧𝐧𝐧𝐧𝐧𝐧𝐧of delayed model.Two key strategies from the reproduction number of 2019-nCov model,may be followed,according to the nature of the disease as if it is diminished or present in the community.The more delaying tactics eventually,led to the control of pandemic.Local and global stability of 2019-nCov model is presented for the strategies.We have also investigated the effect of delay factor on reproduction number𝐑R_(nCov).Finally,some very useful numerical results are presented to support the theoretical analysis of the model.

Dynamical Behavior and Sensitivity Analysis of a Delayed Coronavirus Epidemic Model

Mathematical delay modelling has a significant role in the different disciplines such as behavioural,social,physical,biological engineering,and bio-mathematical sciences.The present work describes mathematical formulation for the transmission mechanism of a novel coronavirus(COVID-19).Due to the unavailability of vaccines for the coronavirus worldwide,delay factors such as social distance,quarantine,travel restrictions,extended holidays,hospitalization,and isolation have contributed to controlling the coronavirus epidemic.We have analysed the reproduction number and its sensitivity to parameters.If,R_(covid)>1then this situation will help to eradicate the disease and if,R_(covid)>1 the virus will spread rapidly in the human beings.Well-known theorems such as Routh Hurwitz criteria and Lasalle invariance principle have presented for stability.The local and global stabilizes for both equilibria of the model have also been presented.Also,we have analysed the effect of delay reason on the reproduction number.In the last,some very useful numerical consequences have presented in support of hypothetical analysis.

Simulation, Modeling, and Optimization of Intelligent Kidney Disease Predication Empowered with Computational Intelligence Approaches

Artificial intelligence(AI)is expanding its roots in medical diagnostics.Various acute and chronic diseases can be identified accurately at the initial level by using AI methods to prevent the progression of health complications.Kidney diseases are producing a high impact on global health and medical practitioners are suggested that the diagnosis at earlier stages is one of the foremost approaches to avert chronic kidney disease and renal failure.High blood pressure,diabetes mellitus,and glomerulonephritis are the root causes of kidney disease.Therefore,the present study is proposed a set of multiple techniques such as simulation,modeling,and optimization of intelligent kidney disease prediction(SMOIKD)which is based on computational intelligence approaches.Initially,seven parameters were used for the fuzzy logic system(FLS),and then twenty-five different attributes of the kidney dataset were used for the artificial neural network(ANN)and deep extreme machine learning(DEML).The expert system was proposed with the assistance of medical experts.For the quick and accurate evaluation of the proposed system,Matlab version 2019 was used.The proposed SMOIKD-FLSANN-DEML expert system has shown 94.16%accuracy.Hence this study concluded that SMOIKD-FLS-ANN-DEML system is effective to accurately diagnose kidney disease at initial levels.

An Effective Numerical Method for the Solution of a Stochastic Coronavirus(2019-nCovid)Pandemic Model

Nonlinear stochastic modeling plays a significant role in disciplines such as psychology,finance,physical sciences,engineering,econometrics,and biological sciences.Dynamical consistency,positivity,and boundedness are fundamental properties of stochastic modeling.A stochastic coronavirus model is studied with techniques of transition probabilities and parametric perturbation.Well-known explicit methods such as Euler Maruyama,stochastic Euler,and stochastic Runge–Kutta are investigated for the stochastic model.Regrettably,the above essential properties are not restored by existing methods.Hence,there is a need to construct essential properties preserving the computational method.The non-standard approach of finite difference is examined to maintain the above basic features of the stochastic model.The comparison of the results of deterministic and stochastic models is also presented.Our proposed efficient computational method well preserves the essential properties of the model.Comparison and convergence analyses of the method are presented.

Local perceptions of the conversion of cropland to forestland program in Jiangxi, Shaanxi, and Sichuan, China

Numerous land-use policies have been implemented in China in recent decades for ecological restoration and conservation to reduce environmental disasters and promote environmental sustainability.Many of these policies follow a top-down approach to implementation and as such,emphasize the hierarchical control within government structures.An understanding of local perceptions of land-use policies is important if the disconnect between policy makers and the target population is to be reduced and if program support is to improve.This study aimed to help improve local implementation,attitude toward,and engagement by examining the influence of socio-economic characteristics on the target population’s(local farmers)perception of the conversion of cropland to forestland program(CFPP)land use policy in Jiangxi,Sichuan,and Shaanxi provinces.It uses logistical regression models,with robust aspects of perception including confidence,support,transparency,prospects,fairness,and willingness to participate.Results indicate that social aspects as well as economic aspects are most important in influencing farmers’perceptions towards the CFPP.The farmers who have received technical support,rural male habitants,educated,and non-middle-aged farmers exhibit more positive perceptions of the program and are much more likely to support it,whereas farmers without any technical support or formal education,and female and middle-aged farmers are less likely to support the program.Importantly,this study also reveals the differences in responses,experiences and perceptions of the farmers living across different provinces.These empirical results provide insight into the influence of socio-economic characteristics on the perception of farmers towards land-use policies,which has important implications for designing targeted policy instruments and increasing farmer support for these policies.This knowledge can be harnessed and further evaluated in future research to improve citizen engagement,support,and understanding in order to help ecological restoration and conservation objectives be more effectively achieved.

Numerical Analysis of Novel Coronavirus (2019-nCov) Pandemic Model with Advection

Recently,the world is facing the terror of the novel corona-virus,termed as COVID-19.Various health institutes and researchers are continuously striving to control this pandemic.In this article,the SEIAR(susceptible,exposed,infected,symptomatically infected,asymptomatically infected and recovered)infection model of COVID-19 with a constant rate of advection is studied for the disease propagation.A simple model of the disease is extended to an advection model by accommodating the advection process and some appropriate parameters in the system.The continuous model is transposed into a discrete numerical model by discretizing the domains,finitely.To analyze the disease dynamics,a structure preserving non-standard finite difference scheme is designed.Two steady states of the continuous system are described i.e.,virus free steady state and virus existing steady state.Graphical results show that both the steady states of the numerical design coincide with the fixed points of the continuous SEIAR model.Positivity of the state variables is ensured by applying the M-matrix theory.A result for the positivity property is established.For the proposed numerical design,two different types of the stability are investigated.Nonlinear stability and linear stability for the projected scheme is examined by applying some standard results.Von Neuman stability test is applied to ensure linear stability.The reproductive number is described and its pivotal role in stability analysis is also discussed.Consistency and convergence of the numerical model is also studied.Numerical graphs are presented via computer simulations to prove the worth and efficiency of the quarantine factor is explored graphically,which is helpful in controlling the disease dynamics.In the end,the conclusion of the study is also rendered.

Systematic Analysis of Safety and Security Risks in Smart Homes

The revolution in Internet of Things(IoT)-based devices and applications has provided smart applications for humans.These applications range from healthcare to traffic-flow management,to communication devices,to smart security devices,and many others.In particular,government and private organizations are showing significant interest in IoT-enabled applications for smart homes.Despite the perceived benefits and interest,human safety is also a key concern.This research is aimed at systematically analyzing the available literature on smart homes and identifying areas of concern or risk with a view to supporting the design of safe and secure smart homes.For this systematic review process,relevant work in the most highly regarded journals published in the period 2016–2020(a section of 2020 is included)was analyzed.A final set of 99 relevant articles(journal articles,book sections,conference papers,and survey papers)was analyzed in this study.This analysis is focused on three research questions and relevant keywords.The systematic analysis results and key insights will help researchers and practitioners to make more informed decisions when dealing with the safety and security risks of smart homes,especially in emergency situations.

An Overview of Information and Communication Technology (ICT) in Jordan: Review the Literature of Usage, Benefits and Barriers

This paper presented a background of the extent of the ICT, IT, and EC-B2B in Jordan. It was mentioned that the development of the ICT in Jordan brings benefits to the enterprises and their TPs. In this paper the EC-B2B systems’ readiness in Jordan is defined as the degree of preparation of a nation or community to participate in and benefits from ICT development. The government in Jordan has taken forceful measures towards adoption IT and IS applications and Internet awareness. In 2010, it was reported from the DOS in Jordanthat the percentage of individual Internet usage did not exceed 4.7 percent of the population inJordan[1]. This paper highlighted through subsections on the benefits and risks faced EC-B2B system adoption in Jordan. Based on the recent studies and reports in Jordan, the EC-B2B system adoption was mainly adopted by large enterprises in the supply chain rather than by SMEs. The study concluded that the main two barriers of ICT development and adoption inJordanare organizational readiness including lack of new education methods, and lack of information and knowledge.

The Internet-EDI Systems Adoption by Enterprises in Jordan: Descriptive analysis of Adoption, Strategies and Benefits

This paper reviewed and explored the current extent of the Internet Electronic Data Interchange systems adoption in Jordan particularly in the SME sector. Also the paper presented the benefits of IEDI adoption and showed the main obstacles facing the SME in Jordan to adopt. This paper used the descriptive and theoretical analysis approaches for collecting and analysis the historical and archived data. The literature showed that Jordan, as a developing country, has achieved forward steps in introducing the Internet to the different sectors of life. The adoption of the electronic tools in business became a governmental target in recent years to make it possible for SMEs to be able to continue to achieve success in their business [1]. Most of Jordanian SMEs have little or no competitive pressure to use I-EDI systems, since most suppliers, customers and other competitors do not seem to promote I-EDI systems. The study concluded that SMEs in Jordan could grow and become larger companies, and supporting national economy. Thus it is very important to develop and grow Jordanian SMEs by doing more research.

Stock Repurchase and the Role of Signaling： A Comparative Analysis between U.S. and China

This paper compares different methods used for stock repurchase and examines the role of signaling in the U.S. and China＇s capital markets. We find that the ways to buyback stocks are very different in the two countries. Most U.S. stocks are repurchased through open market and the signals sent to the market through open market repurchase are getting weaker. Even though stock repurchases are at their early stage in the Chinese stock market and the dominated way to buyback is through a negotiated repurchase agreement for non-floating shares, the power of signaling seems much stronger. Examining stock prices pre- and post-repurchase, we find that stock repurchase records an average abnormal return of 3.42% on the announcement date and 3.24% on the date of actual renurchase.

Governance in the exploration of global and regional determinants of ICT development

The present study assesses how governance affects information and communication technology(IcT)at the global level contingent on macroeconomic policy factors such as trade,foreign direct investment(FDI),manufacturing value added,and agricultural value added.The study focuses on 183 countries from 2003 to 2021,and the empirical evidence is based on the generalized method of moments(GMM).The following main findings are established.For the full sample,governance unconditionally promotes ICT development,while trade openness(industrial added value)moderates governance to promote(dampen)ICT development.In sub-Saharan Africa,only trade openness effectively moderates governance to induce an overall positive effect on ICT,while in the Middle East and North Africa(MENA)region,all policy variables moderate governance for an overall positive incidence on ICT sector development.The findings for the MENA region are confirmed in the Europe and Central Asia(ECA)region,with the exception of the moderating role of industrial added value,which engenders an overall negative effect.In the East and South Asia and the Pacific(ESAP)countries,one overall positive incidence is apparent in the role of trade openness,while net negative effects are established from the moderating roles of industrial added value and agricultural added value.In the American sub-sample,a positive(negative)net effect is apparent from the role of industrial added value(trade)in moderating the incidence of gover-nance on ICT sector development.Finally,policy implications are discussed.

Impact of climate-smart agricultural technology on multidimensional poverty in rural Ethiopia

A large body of empirical literature showed that the adoption of agricultural technologies reduces poverty. However, dominants of those studies so far used one-dimensional income or expenditure-based measures of poverty which may not reflect other types of deprivations. Therefore, the major objective of this study is to examine the impact of adopting climate-smart agricultural technology, which refers to a joint application of row planting methods and the use of chemical fertilizers, on the multidimensional poverty status of rural households in Ethiopia. To estimate the impact of the stated technologies, this study employs propensity score matching and endogenous switching regression methods. To measure the multidimensional poverty index, the study also uses the Alkire and Foster counting approach. Using the Ethiopian Socioeconomic Survey(ESS), collected in 2015-Wave 3, the results of the study show that the adoption of these technologies reduces deprivation score and one of its component, the standard of living part. Regionally, a high reduction in deprivation is observed in Amhara and Oromiya regions. The results also show that the impact is significantly higher in severely deprived households. It is also observed that the reduction in multidimensional poverty due to the technology is through an increase in income/consumption via improvement in production gain. The impact channels more through the non-food expenditure pathway. Finally, this study also sheds light on the effects that technology adoption has on multidimensional poverty reduction.

A Numerical Efficient Technique for the Solution of Susceptible Infected Recovered Epidemic Model

The essential features of the nonlinear stochastic models are positivity,dynamical consistency and boundedness.These features have a significant role in different fields of computational biology and many more.The aim of our paper,to achieve the comparison analysis of the stochastic susceptible,infected recovered epidemic model.The stochastic modelling is a realistic way to study the dynamics of compartmental modelling as compared to deterministic modelling.The effect of reproduction number has also observed in the stochastic susceptible,infected recovered epidemic model.For comparison analysis,we developed some explicit stochastic techniques,but they are the time-dependent techniques.The implicitly driven explicit technique has developed for the stochastic susceptible,infected recovered epidemic model.In the support,some theorems and graphical illustration has presented.Also,the time efficiency of this method makes it easy to find the solution of the stochastic system.The comparison with other techniques shows the efficacy and reliability of the designed technique.

Essential Features Preserving Dynamics of Stochastic Dengue Model

Nonlinear stochasticmodelling plays an important character in the different fields of sciences such as environmental,material,engineering,chemistry,physics,biomedical engineering,and many more.In the current study,we studied the computational dynamics of the stochastic dengue model with the real material of the model.Positivity,boundedness,and dynamical consistency are essential features of stochastic modelling.Our focus is to design the computational method which preserves essential features of the model.The stochastic non-standard finite difference technique is most efficient as compared to other techniques used in literature.Analysis and comparison were explored in favour of convergence.Also,we address the comparison between the stochastic and deterministic models.

Intelligent Breast Cancer Prediction Empowered with Fusion and Deep Learning

Breast cancer is the most frequently detected tumor that eventually could result in a significant increase in female mortality globally.According to clinical statistics,one woman out of eight is under the threat of breast cancer.Lifestyle and inheritance patterns may be a reason behind its spread among women.However,some preventive measures,such as tests and periodic clinical checks can mitigate its risk thereby,improving its survival chances substantially.Early diagnosis and initial stage treatment can help increase the survival rate.For that purpose,pathologists can gather support from nondestructive and efficient computer-aided diagnosis(CAD)systems.This study explores the breast cancer CAD method relying on multimodal medical imaging and decision-based fusion.In multimodal medical imaging fusion,a deep learning approach is applied,obtaining 97.5%accuracy with a 2.5%miss rate for breast cancer prediction.A deep extreme learning machine technique applied on feature-based data provided a 97.41%accuracy.Finally,decisionbased fusion applied to both breast cancer prediction models to diagnose its stages,resulted in an overall accuracy of 97.97%.The proposed system model provides more accurate results compared with other state-of-the-art approaches,rapidly diagnosing breast cancer to decrease its mortality rate.

Central bank digital currency,loan supply,and bank failure risk:a microeconomic approach

Central bank digital currencies(CBDCs),which are legal tenders in digital form,are expected to reduce currency issuance and circulation costs and broaden the scope of monetary policy.In addition,these currencies may also reduce consumers’need for conventional demand deposits,which,in turn,increases banks’loan provision costs because deposits require higher rates of return.We use a microeconomic banking model to investigate the effects of introducing an economy-wide,account-type CBDC on a bank’s loan supply and its failure risk.Given that a CBDC is expected to lower the cost of liquidity circulation and become a strong substitute for demand deposits,both the loan supply and the bank failure risk increase.These increases are countered by subsequent increases in the rates of return on term deposits and loans,which,in turn,reduce the loan supply and thus bank failure risk.These offsetting forces lead to no significant change in banking,as long as the rate of return on loans is below a certain threshold.However,once the rate is above the threshold,bank failure risk increases,thereby undermining banking stability.The problem is more pronounced when the degree of pass-through of funding costs to the loan rate is high and the profitability of a successful project is low.Our results imply that central banks wishing to introduce an economy-wide,account-type CBDC should first monitor yields on bank loans and consider policy measures that induce banks to maintain adequate liquidity reserve levels.

A Structure Preserving Numerical Method for Solution of Stochastic Epidemic Model of Smoking Dynamics

In this manuscript,we consider a stochastic smoking epidemic model from behavioural sciences.Also,we develop a structure preserving numerical method to describe the dynamics of stochastic smoking epidemic model in a human population.The structural properties of a physical system include positivity,boundedness and dynamical consistency.These properties play a vital role in non-linear dynamics.The solution for nonlinear stochastic models necessitates the conservation of these properties.Unfortunately,the aforementioned properties of the model have not been restored in the existing stochastic methods.Therefore,it is essential to construct a structure preserving numerical method for a reliable analysis of stochastic smoking model.The usual explicit stochastic numerical methods are time-dependent and violate most of the structural properties.In this work,we have developed the implicitly driven explicit method for the solution of stochastic smoking model.It is also proved that the newly developed method sustains all the aforementioned properties of the system.Finally,the convergence analysis of the newly developed method and graphical illustrations are presented.