Incorporation Of Recovery Research Articles

Mathematical analysis of affinity hemodialysis on T-Cell depletion

Investigation into the mathematical analysis of affinity hemodialysis on T-cell depletion is considered to give more significant understanding on the infection dynamics of HIV. Our model revealed the possibility of more than two infected equilibriums with the incorporation of recovery through the affinity hemodialysis. The conditions for stable infected equilibrium to prevent full-blown of AIDS are obtained and stated as hypothesis. This work has, therefore, open the way for partnerships among modelers and clinicians to strengthening the insight into the nature and process of viral multiphasic decay noticed in some treated patients. The initial growth of virus, infected cells and glycoprotein as well as possibility of total viral clearance are examined in the study.

Housing interventions and health: Quantifying the impact of indoor particles on mortality and morbidity with disease recovery

Housing interventions for energy efficiency and greenhouse gas emission reduction have the potential to reduce exposure to indoor air pollution if they are implemented correctly. This work assessed the health impacts of home energy efficiency measures in England and Wales resulting in a reduction in average indoor PM2.5 exposures of 3μgm−3. The assessment was performed using a new multistate life table model which allows transition into and between multiple morbid states, including recovery to disease-free status and relapse, with transition rates informed by age- and cause-specific disease prevalence, incidence and mortality data. Such models have not previously included disease recovery. The results demonstrate that incorporation of recovery in the model is necessary for conditions such as asthma which have high incidence in early life but likelihood of recovery in adulthood. The impact assessment of the home energy efficiency intervention showed that the reduction in PM2.5 exposure would be associated with substantial benefits for mortality and morbidity from asthma, coronary heart disease and lung cancer. The overall impact would be an increase in life expectancy of two to three months and approximately 13 million QALYs gained over the 90year follow-up period. Substantial quality-of-life benefits were also observed, with a decrease in asthma over all age groups and larger benefits due to reduced coronary heart disease and lung cancer, particularly in older age groups. The multistate model with recovery provides important additional information for assessing the impact on health of environmental policies and interventions compared with mortality-only life tables, allowing more realistic representation of diseases with substantial non-mortality burdens.

A “characteristic-strain” model for creep

The paper describes the construction of a model of creep that is very simple to implement and lends itself to engineering applications for steady or relaxing loads. The model encompasses primary, secondary and tertiary creep behaviour without requiring separate representation of each phase. The evolution of creep strain at constant stress is described in terms of three coefficients, each of self-evident physical significance, at any given temperature. The validity of the model is demonstrated by reference to a P91 dataset and assessed statistically. The incorporation of recovery, via an additional coefficient, is described and its significance is demonstrated by reference to relaxation data.

A “characteristic-strain” model for creep

The paper describes the construction of a model of creep that is very simple to implement and lends itself to engineering applications for steady or relaxing loads. The model encompasses primary, secondary and tertiary creep behaviour without requiring separate representation of each phase. The evolution of creep strain at constant stress is described in terms of three coefficients, each of self-evident physical significance, at any given temperature. The validity of the model is demonstrated by reference to a P91 dataset and assessed statistically. The incorporation of recovery, via an additional coefficient, is described and its significance is demonstrated by reference to relaxation data.

Modeling recrystallization of microalloyed austenite: effect of coupling recovery, precipitation and recrystallization

In this contribution, existing models for precipitation, recovery and recrystallization have been coupled, with their interdependencies explained, to describe the microstructural evolution in a supersaturated alloy after hot deformation. Microalloyed austenite has been used as an example system and the time evolution of the precipitate diameter and the recrystallization and softening fractions are compared with the available experimental data. The model predictions are in excellent quantitative agreement with the experimental observations. Particular attention is paid to the occurrence of ‘plateaus’ or ‘humps’ in the softening and recrystallization fraction plots. In both cases, the incorporation of recovery is an essential ingredient for a quantitative description of the microstructural evolution in the hot-worked structure.

Incorporation of Recovery and Repair Time in the Reliability Modelling of Fault-Tolerant System

During recovery, the system is not performing tasks that are directly related to its operational objective. This time will contribute to the overall computational unavailability of the system. When the computational availability is specified as one of the performance measures, recovery time cannot be neglected in the modelling of the system.In this paper, we set up a model incorporating recovery time and distinguish between two sources of unavailability: (i) Unavailability Due to System Failure (UDSF) and (ii) Unavailability Due To Recovery (UDTR). We proceed to show that the contribution of UDTR to the overall unavailability could in fact be significant and should not be neglected. We also present some important results relating to the sensitivity of UDSF and UDTR to variations in system parameters such as coverage, number of spares and different architecture etc. This leads to a better understanding of the significance of recovery time for such systems.