Run-time model evaluation for requirements model-driven self-adaptation

A self-adaptive system adjusts its configuration to tolerate changes in its operating environment. To date, requirements modeling methodologies for self-adaptive systems have necessitated analysis of all potential system configurations, and the circumstances under which each is to be adopted. We argue that, by explicitly capturing and modelling uncertainty in the operating environment, and by verifying and analysing this model at runtime, it is possible for a system to adapt to tolerate some conditions that were not fully considered at design time. We showcase in this paper our tools and research results. © 2012 IEEE.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

Análise de resíduos em modelos de tempo de falha acelerado com efeito aleatório

We present residual analysis techniques to assess the fit of correlated survival data by Accelerated Failure Time Models (AFTM) with random effects. We propose an imputation procedure for censored observations and consider three types of residuals to evaluate different model characteristics. We illustrate the proposal with the analysis of AFTM with random effects to a real data set involving times between failures of oil well equipment

Assessment of a New Experimental Model of Isolated Right Ventricular Failure

We assessed a new experimental model of isolated right ventricular (RV) failure, achieved by means of intramyocardial injection of ethanol. RV dysfunction was induced in 13 mongrel dogs via multiple injections of 96% ethanol (total dose 1 mL/kg), all over the inlet and trabecular RV free walls. Hemodynamic and metabolic parameters were evaluated at baseline, after ethanol injection, and on the 14th postoperative day (POD). Echocardiographic parameters were evaluated at baseline, on the sixth POD, and on the 13th POD. The animals were then euthanized for histopathological analysis of the hearts. There was a 15.4% mortality rate. We noticed a decrease in pulmonary blood flow right after RV failure (P = 0.0018), as well as during reoperation on the 14th POD (P = 0.002). The induced RV dysfunction caused an increase in venous lactate levels immediately after ethanol injection and on the 14th POD (P < 0.0003). The echocardiogram revealed a decrease in the RV ejection fraction on the sixth and 13th PODs (P = 0.0001). There was an increased RV end-diastolic volume on the sixth (P = 0.0001) and 13th PODs (P = 0.0084). The right ventricle showed a 74% +/- 0.06% transmural infarction area, with necrotic lesions aged 14 days. Intramyocardial ethanol injection has allowed the creation of a reproducible and inexpensive model of RV failure. The hemodynamic, metabolic, and echocardiographic parameters assessed at different protocol times are compatible with severe RV failure. This model may be useful in understanding the pathophysiology of isolated right-sided heart failure, as well as in the assessment of ventricular assist devices.

Long-term survivor mixture model with random effects: application to a multi-centre clinical trial of carcinoma

A mixture model incorporating long-term survivors has been adopted in the field of biostatistics where some individuals may never experience the failure event under study. The surviving fractions may be considered as cured. In most applications, the survival times are assumed to be independent. However, when the survival data are obtained from a multi-centre clinical trial, it is conceived that the environ mental conditions and facilities shared within clinic affects the proportion cured as well as the failure risk for the uncured individuals. It necessitates a long-term survivor mixture model with random effects. In this paper, the long-term survivor mixture model is extended for the analysis of multivariate failure time data using the generalized linear mixed model (GLMM) approach. The proposed model is applied to analyse a numerical data set from a multi-centre clinical trial of carcinoma as an illustration. Some simulation experiments are performed to assess the applicability of the model based on the average biases of the estimates formed. Copyright (C) 2001 John Wiley & Sons, Ltd.

An Extension to the Tactical Planning Model for a Job Shop: Continuous-Time Control

We develop an extension to the tactical planning model (TPM) for a job shop by the third author. The TPM is a discrete-time model in which all transitions occur at the start of each time period. The time period must be defined appropriately in order for the model to be meaningful. Each period must be short enough so that a job is unlikely to travel through more than one station in one period. At the same time, the time period needs to be long enough to justify the assumptions of continuous workflow and Markovian job movements. We build an extension to the TPM that overcomes this restriction of period sizing by permitting production control over shorter time intervals. We achieve this by deriving a continuous-time linear control rule for a single station. We then determine the first two moments of the production level and queue length for the workstation.

A bivariate regression model for matched paired survival data: local influence and residual analysis

The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.

Comments, with reply on 'Continuous time relay-controlled model reference adaptive-system' by A. Abdulkareem and R. Nagarajam

An adaptive scheme is shown by the authors of the above paper (ibid. vol. 71, no. 2, pp. 275-276, Feb. 1983) for continuous time model reference adaptive systems (MRAS), where relays replace the usual multipliers in the existing MRAS. The commenter shows an error in the analysis of the hyperstability of the scheme, such that the validity of this configuration becomes an open question.

A general threshold stress hybrid hazard model for lifetime data

In this paper we propose a hybrid hazard regression model with threshold stress which includes the proportional hazards and the accelerated failure time models as particular cases. To express the behavior of lifetimes the generalized-gamma distribution is assumed and an inverse power law model with a threshold stress is considered. For parameter estimation we develop a sampling-based posterior inference procedure based on Markov Chain Monte Carlo techniques. We assume proper but vague priors for the parameters of interest. A simulation study investigates the frequentist properties of the proposed estimators obtained under the assumption of vague priors. Further, some discussions on model selection criteria are given. The methodology is illustrated on simulated and real lifetime data set.

Robust Inferences For Covariate Effects On Survival Time With Censored Linear Regression Models

Various inference procedures for linear regression models with censored failure times have been studied extensively. Recent developments on efficient algorithms to implement these procedures enhance the practical usage of such models in survival analysis. In this article, we present robust inferences for certain covariate effects on the failure time in the presence of "nuisance" confounders under a semiparametric, partial linear regression setting. Specifically, the estimation procedures for the regression coefficients of interest are derived from a working linear model and are valid even when the function of the confounders in the model is not correctly specified. The new proposals are illustrated with two examples and their validity for cases with practical sample sizes is demonstrated via a simulation study.

Dormancy release in Lolium rigidum seeds is a function of thermal after-ripening time and seed water content

Dormancy release in seeds of Lolium rigidum Gaud. (annual ryegrass) was investigated in relation to temperature and seed water content. Freshly matured seeds were collected from cropping fields at Wongan Hills and Merredin, Western Australia. Seeds from Wongan Hills were equilibrated to water contents between 6 and 18% dry weight and after-ripened at constant temperatures between 9 and 50degreesC for up to 23 weeks. Wongan Hills and Merredin seeds at water contents between 7 and 17% were also after-ripened in full sun or shade conditions. Dormancy was tested at regular intervals during after-ripening by germinating seeds on agar at 12-h alternating 15degreesC (dark) and 25degreesC (light) periods. Rate of dormancy release for Wongan Hills seeds was a positive linear function of after-ripening temperature above a base temperature (T-b) of 5.4degreesC. A thermal after-ripening time model for dormancy loss accounting for seed moisture in the range 6-18% was developed using germination data for Wongan Hills seeds after-ripened at constant temperatures. The model accurately predicted dormancy release for Wongan Hills seeds after-ripened under naturally fluctuating temperatures. Seeds from Merredin responded similarly but had lower dormancy at collection and a faster rate of dormancy release in seeds below 9% water content.

Physical Training Leads to Remodeling of Diaphragm Muscle in Asthma Model

Matrix metalloproteinases (MMPs) are crucial to the development and maintenance of healthy tissue and are mainly involved in extracellular matrix (ECM) remodeling of skeletal muscle. This study evaluated the effects of chronic allergic airway inflammation (CAAI), induced by ovalbumin, and aerobic training in the MMPs activity in mouse diaphragm muscle. Thirty mice were divided into 6 groups: 1) control; 2) ovalbumin; 3) treadmill trained at 50% of maximum speed; 4) ovalbumin and trained at 50%; 5) trained at 75%; 6) ovalbumin and trained at 75%. CAAI did not after MMPs activities in diaphragm muscle. Nevertheless, both treadmill aerobic trainings, associated with CAAI increased the MMP-2 and -1 activities. Furthermore, MMP-9 was not detected in any group. Together, these findings suggest an ECM remodeling in diaphragm muscle of asthmatic mice submitted to physical training. This result may be useful for a better understanding of functional significance of changes in the MMPs activity in response to physical training in asthma.

Time to Left Ventricular Reverse Remodeling after Cardiac Resynchronization Therapy: Better Late than Never

INTRODUCTION: Left ventricular reverse remodeling (LVRR), defined as reduction of end-diastolic and end-systolic dimensions and improvement of ejection fraction, is associated with the prognostic implications of cardiac resynchronization therapy (CRT). The time course of LVRR remains poorly characterized. Nevertheless, it has been suggested that it occurs ≤6 months after CRT. OBJECTIVE: To characterize the long-term echocardiographic and clinical evolution of patients with LVRR occurring >6 months after CRT and to identify predictors of a delayed LVRR response. METHODS: A total of 127 consecutive patients after successful CRT implantation were divided into three groups according to LVRR response: Group A, 19 patients (15%) with LVRR after >6 months (late LVRR); Group B, 58 patients (46%) with LVRR before 6 months (early LVRR); and Group C, 50 patients (39%) without LVRR during follow-up (no LVRR). RESULTS: The late LVRR group was older, more often had ischemic etiology and fewer patients were in NYHA class ≤II. Overall, group A presented LVRR between group B and C. This was also the case with the percentage of clinical response (68.4% vs. 94.8% vs. 38.3%, respectively, p<0.001), and hospital readmissions due to decompensated heart failure (31.6% vs. 12.1% vs. 57.1%, respectively, p<0.001). Ischemic etiology (OR 0.044; p=0.013) and NYHA functional class