Guaranteed parameter estimation of non-linear dynamic systems using high-order bounding techniques with domain and CPU-time reduction strategies

This paper is concerned with guaranteed parameter estimation of non-linear dynamic systems in a context of bounded measurement error. The problem consists of finding - or approximating as closely as possible - the set of all possible parameter values such that the predicted values of certain outputs match their corresponding measurements within prescribed error bounds. A set-inversion algorithm is applied, whereby the parameter set is successively partitioned into smaller boxes and exclusion tests are performed to eliminate some of these boxes, until a given threshold on the approximation level is met. Such exclusion tests rely on the ability to bound the solution set of the dynamic system for a finite parameter subset, and the tightness of these bounds is therefore paramount; equally important in practice is the time required to compute the bounds, thereby defining a trade-off. In this paper, we investigate such a trade-off by comparing various bounding techniques based on Taylor models with either interval or ellipsoidal bounds as their remainder terms. We also investigate the use of optimization-based domain reduction techniques in order to enhance the convergence speed of the set-inversion algorithm, and we implement simple strategies that avoid recomputing Taylor models or reduce their expansion orders wherever possible. Case studies of various complexities are presented, which show that these improvements using Taylor-based bounding techniques can significantly reduce the computational burden, both in terms of iteration count and CPU time

Set-membership nonlinear regression approach to parameter estimation

This paper introduces set-membership nonlinear regression (SMR), a new approach to nonlinear regression under uncertainty. The problem is to determine the subregion in parameter space enclosing all (global) solutions to a nonlinear regression problem in the presence of bounded uncertainty on the observed variables. Our focus is on nonlinear algebraic models. We investigate the connections of SMR with (i) the classical statistical inference methods, and (ii) the usual set-membership estimation approach where the model predictions are constrained within bounded measurement errors. We also develop a computational framework to describe tight enclosures of the SMR regions using semi-infinite programming and complete-search methods, in the form of likelihood contour and polyhedral enclosures. The case study of a parameter estimation problem in microbial growth is presented to illustrate various theoretical and computational aspects of the SMR approach

Renal association clinical practice guideline in post-operative care in the kidney transplant recipient

These guidelines cover the care of patients from the period following kidney transplantation until the transplant is no longer working or the patient dies. During the early phase prevention of acute rejection and infection are the priority. After around 3-6 months, the priorities change to preservation of transplant function and avoiding the long-term complications of immunosuppressive medication (the medication used to suppress the immune system to prevent rejection). The topics discussed include organization of outpatient follow up, immunosuppressive medication, treatment of acute and chronic rejection, and prevention of complications. The potential complications discussed include heart disease, infection, cancer, bone disease and blood disorders. There is also a section on contraception and reproductive issues.Immediately after the introduction there is a statement of all the recommendations. These recommendations are written in a language that we think should be understandable by many patients, relatives, carers and other interested people. Consequently we have not reworded or restated them in this lay summary. They are graded 1 or 2 depending on the strength of the recommendation by the authors, and AD depending on the quality of the evidence that the recommendation is based on

Influence of Bariatric Surgery on the Use and Pharmacokinetics of Some Major Drug Classes

<p>The purpose of this review is to evaluate the influence of bariatric surgery on the use and pharmacokinetics of some frequently used drugs. A PubMed literature search was conducted. Literature was included on influence of bariatric surgery on pharmacoepidemiology and pharmacokinetics. Drug classes to be searched for were antidepressants, antidiabetics, statins, antihypertensive agents, corticosteroids, oral contraceptives, and thyroid drugs. A reduction in the use of medication by patients after bariatric surgery has been reported for various drug classes. Very few studies have been published on the influence of bariatric surgery on the pharmacokinetics of drugs. After bariatric surgery, theoretically, reduced drug absorption may occur. Correct dosing and choosing the right dosage form for drugs used by patients after bariatric surgery are necessary for optimal pharmacotherapy. Therefore, more clinical studies are needed on the influence of bariatric surgery on the pharmacokinetics of major drugs.</p>