Enzymatic pretreatment of grey cotion fabric for improving dye uptake, lustur and hand feel using fungal cellulase

Cellulase enzyme was extracted from pineapple peel substrate using Aspergiluss niger.  Because enzymes are sustainable alternatives to harsh toxic chemicals used in the Textile Industries. Cotton fabrics were treated with cellulase at variable concentrations at a pH of 5.5 and 55°C. Changes in various properties of the treated fabrics like weight loss, lusture, soft touch and overall dyeing properties were investigated. The results obtained show that cellulase have successfully removed staple fibres from the fabrics and thus, yield a glabrous appearance and soft touch of the treated fabrics; furthermore, it was established that percentage dye uptake and fastness properties of the fabrics were greatly improved as confirmed by the FTIR spectral analysis and UV- visible spectrophotometric analysis of the absorbance maximum of the dye liquor before and after dying.Key Words: Cellulase, Aspergillus niger, pre- treatment, cotton fabric and dye uptake

Numerical Analysis of Defects Caused by Thermolysis in an Infinite Cylindrical Ceramic Moulding

The second-order parabolic (diffusion) equation, which governs the concentration of monomer during pyrolysis of a cylindrical ceramic moulding containing a polymer which degrades to monomer only, is solved: an infinite cylinder is considered. The method of lines is used to transform the partial differential equation into a system of first-order linear ordinary differential equations, the solution of which is seen to satisfy a recurrence relation. The concentration profile at a given time is computed by replacing the matrix exponential terms in this recurrence relation by a high-order Pade approximate. A parallel algorithm using two processors is developed by taking the partial fraction decomposition of the Pade approximate and a (matrix) rational expression in the recurrence relation

Incremental role of male circumcision on a generalised HIV epidemic through its protective effect against other sexually transmitted infections: from efficacy to effectiveness to population-level impact.

The protection of MC against STI contributes little to the overall effect of MC on HIV. Additional work is needed to determine whether, and under what conditions, the protective effect of MC efficacy against STIs can have a significant incremental benefit on the HIV epidemic

Numerical Methods for a Non-linear System Arising in Chemical Kinetics

Two numerical methods are proposed for the solution of a system of two dimensional reaction-diffusion equations with cubic non-linearity, known as the "Brusselator" system. The first method is derived using finite difference techniques and the solution is obtained in paralled using two processors running concurrently. The second method is based on a predictor-eorrector technique. This system of equations has important applications in chemical kinetics

RISK-INDUCED BACKWARD BIFURCATION IN HSV-2 TRANSMISSION DYNAMICS

Abstract. A risk-structured, two-sex, model for the transmission dynamics of herpes simplex virus type 2 (HSV-2) in a population is designed and qualitatively analysed. It is shown that adding risk structure (i.e., the risk of transmitting or acquiring HSV-2 infection) to an HSV-2 transmission model causes the phenomenon of backward bifurcation when the associated reproduction threshold is less than unity. This dynamical feature, which has non-trivial consequence on the persistence or elimination of the disease (when the reproduction threshold is less than unity), can be removed if the susceptible male and female sub populations are not stratified according to the risk of acquiring HSV-2 infection

Cross-immunity-induced backward bifurcation for a model of transmission dynamics of two strains of influenza

A new deterministic model for the transmission dynamics of two strains of in- uenza is designed and used to qualitatively assess the role of cross-immunity on the transmission process. It is shown that incomplete cross-immunity could in- duce the phenomenon of backward bifurcation when the associated reproduction number is less than unity. The model undergoes competitive exclusion (where Strain i drives out Strain j to extinction whenever R0i > 1 > R0j ; i; j = 1; 2; i ̸= j). For the case where infection with one strain confers complete im- munity against infection with the other strain, it is shown that the disease-free equilibrium of the model is globally-asymptotically stable whenever the repro- duction number is less than unity. In the absence of cross-immunity, the model can have a continuum of co-existence endemic equilibria (which is shown to be globally-asymptotically stable for a special case). When infection with one strain confers incomplete immunity against the other. Numerical simulations of the model show that the two strains co-exist, with Strain i dominating (but not driving out Strain j), whenever R0i > R0j > 1.http://www.elsevier.com/locate/nonrwaam201

A primer on using mathematics to understand COVID-19 dynamics : modeling, analysis and simulations

The novel coronavirus (COVID-19) pandemic that emerged from Wuhan city in December 2019 overwhelmed health systems and paralyzed economies around the world. It became the most important public health challenge facing mankind since the 1918 Spanish flu pandemic. Various theoretical and empirical approaches have been designed and used to gain insight into the transmission dynamics and control of the pandemic. This study presents a primer for formulating, analysing and simulating mathematical models for understanding the dynamics of COVID-19. Specifically, we introduce simple compartmental, Kermack-McKendrick-type epidemic models with homogeneously- and heterogeneously-mixed populations, an endemic model for assessing the potential population-level impact of a hypothetical COVID-19 vaccine. We illustrate how some basic non-pharmaceutical interventions against COVID-19 can be incorporated into the epidemic model. A brief overview of other kinds of models that have been used to study the dynamics of COVID-19, such as agent-based, network and statistical models, is also presented. Possible extensions of the basic model, as well as open challenges associated with the formulation and theoretical analysis of models for COVID-19 dynamics, are suggested.The Simons Foundation and the National Science Foundation.http://www.keaipublishing.com/idmam2022Mathematics and Applied Mathematic

Reconstructing disease transmission dynamics from animal movements and test data

Disease outbreaks are often accompanied by a wealth of data, usually in the form of movements, locations and tests. This data is a valuable resource in which data scientists and epidemiologists can reconstruct the transmission pathways and parameters and thus devise control strategies. However, the spatiotemporal data gathered can be both vast whilst at the same time incomplete or contain errors frustrating the effort to accurately model the transmission processes. Fortunately, several techniques exist that can be used to infer the relevant information to help explain these processes. The aim of this article is to provide the reader with a user friendly introduction to the techniques used in dealing with the large datasets that exists in epidemiological and ecological science and the common pitfalls that are to be avoided as well as an introduction to inference techniques for estimating parameter values for mathematical models from spatiotemporal datasets

A systematic review to identify areas of enhancements of pandemic simulation models for operational use at provincial and local levels

<p>Abstract</p> <p>Background</p> <p>In recent years, computer simulation models have supported development of pandemic influenza preparedness policies. However, U.S. policymakers have raised several <it>concerns </it>about the practical use of these models. In this review paper, we examine the extent to which the current literature already addresses these <it>concerns </it>and identify means of enhancing the current models for higher operational use.</p> <p>Methods</p> <p>We surveyed PubMed and other sources for published research literature on simulation models for influenza pandemic preparedness. We identified 23 models published between 1990 and 2010 that consider single-region (e.g., country, province, city) outbreaks and multi-pronged mitigation strategies. We developed a plan for examination of the literature based on the concerns raised by the policymakers.</p> <p>Results</p> <p>While examining the concerns about the adequacy and validity of data, we found that though the epidemiological data supporting the models appears to be adequate, it should be validated through as many updates as possible during an outbreak. Demographical data must improve its interfaces for access, retrieval, and translation into model parameters. Regarding the concern about credibility and validity of modeling assumptions, we found that the models often simplify reality to reduce computational burden. Such simplifications may be permissible if they do not interfere with the performance assessment of the mitigation strategies. We also agreed with the concern that social behavior is inadequately represented in pandemic influenza models. Our review showed that the models consider only a few social-behavioral aspects including contact rates, withdrawal from work or school due to symptoms appearance or to care for sick relatives, and compliance to social distancing, vaccination, and antiviral prophylaxis. The concern about the degree of accessibility of the models is palpable, since we found three models that are currently accessible by the public while other models are seeking public accessibility. Policymakers would prefer models scalable to any population size that can be downloadable and operable in personal computers. But scaling models to larger populations would often require computational needs that cannot be handled with personal computers and laptops. As a limitation, we state that some existing models could not be included in our review due to their limited available documentation discussing the choice of relevant parameter values.</p> <p>Conclusions</p> <p>To adequately address the concerns of the policymakers, we need continuing model enhancements in critical areas including: updating of epidemiological data during a pandemic, smooth handling of large demographical databases, incorporation of a broader spectrum of social-behavioral aspects, updating information for contact patterns, adaptation of recent methodologies for collecting human mobility data, and improvement of computational efficiency and accessibility.</p

Trends in parameterization, economics and host behaviour in influenza pandemic modelling: a review and reporting protocol.

BACKGROUND: The volume of influenza pandemic modelling studies has increased dramatically in the last decade. Many models incorporate now sophisticated parameterization and validation techniques, economic analyses and the behaviour of individuals. METHODS: We reviewed trends in these aspects in models for influenza pandemic preparedness that aimed to generate policy insights for epidemic management and were published from 2000 to September 2011, i.e. before and after the 2009 pandemic. RESULTS: We find that many influenza pandemics models rely on parameters from previous modelling studies, models are rarely validated using observed data and are seldom applied to low-income countries. Mechanisms for international data sharing would be necessary to facilitate a wider adoption of model validation. The variety of modelling decisions makes it difficult to compare and evaluate models systematically. CONCLUSIONS: We propose a model Characteristics, Construction, Parameterization and Validation aspects protocol (CCPV protocol) to contribute to the systematisation of the reporting of models with an emphasis on the incorporation of economic aspects and host behaviour. Model reporting, as already exists in many other fields of modelling, would increase confidence in model results, and transparency in their assessment and comparison