Prediction of mortality in patients without angina: Use of an exercise score and exercise echocardiography

Background Exercise testing has limited efficacy for identifying coronary artery disease (CAD) in the absence of anginal. symptoms. Exercise echocardiography is more accurate than standard exercise testing, but its efficacy in this situation has not been defined. We sought to identify whether the Duke treadmill. score or exercise echocardiography (ExE) could be used to identify risk in patients without anginal symptoms. Methods We studied 1859 patients without typical or atypical angina, heart failure, or a history or ECG evidence of infarction or CAD, who were referred for ExE, of whom 1832 (age 51 15 years, 944 men) were followed for up to 10 years. The presence and extent of ischaemia and scar were interpreted by expert reviewers at the time of the original study. Results Exercise provoked significant (>0.1 mV) ST segment depression in 215 patients (12%), and wall motion abnormalities in 137 (8%). Seventy-eight patients (4%) died before revascularization, only 17 from known cardiac causes. The independent predictors of death were age (RR 1.1, p

Prediction of multilayer adsorption and capillary condensation phenomena in cylindrical mesopores

MCM-41 periodic mesoporous silicates with a high degree of structural ordering are synthesized and used as model adsorbents to study the isotherm prediction of nitrogen adsorption. The nitrogen adsorption isotherm at 77 K for a macroporous silica is measured and used in high-resolution alpha(s)-plot comparative analysis to determine the external surface area, total surface area and primary mesopore volume of the MCM-41 materials. Adsorption equilibrium data of nitrogen on the different pore size MCM-41 samples (pore diameters from 2.40 to 4.92 nm) are also obtained. Based on the Broekhoff and de Boer' thermodynamic analysis, the nitrogen adsorption isotherms for the different pore size MCM-41 samples are interpreted using a novel strategy, in which the parameters of an empirical expression, used to represent the potential of interaction between the adsorbate and adsorbent, are obtained by fitting only the multilayer region prior to capillary condensation for C-16 MCM-41. Subsequently the entire isotherm, including the phase transition, is predicted for all the different pore size MCM-41 samples without any fitting. The results show that the prediction of multilayer adsorption and total adsorbed amount are in good agreement with the experimental isotherms. The predictions of the relative pressure corresponding to capillary equilibrium (coexistence) transition agree remarkably with experimental data on the adsorption branch even for hysteretic isotherms, confirming that this is the branch appropriate for pore size distribution analysis. The impact of pore radius on the adsorption film thickness and capillary coexistence pressure is also investigated, and found to agree with the experimental data. (C) 2003 Elsevier Inc. All rights reserved.

Fatigue Prediction on Fibrin Poly-ε-caprolactone Macroporous Scaffolds

Tissue engineering applications rely on scaffolds that during its service life, either for in-vivo or in vitro applications, are under mechanical solicitations. The variation of the mechanical condition of the scaffold is strongly relevant for cell culture and has been scarcely addressed. Fatigue life cycle of poly-ε-caprolactone, PCL, scaffolds with and without fibrin as filler of the pore structure were characterized both dry and immersed in liquid water. It is observed that the there is a strong increase from 100 to 500 in the number of loading cycles before collapse in the samples tested in immersed conditions due to the more uniform stress distributions within the samples, the fibrin loading playing a minor role in the mechanical performance of the scaffolds

Combining Formal Methods and Functional Strategies Regarding the Reverse Engineering of Interactive Applications

Abstract. Graphical user interfaces (GUIs) make software easy to use by providing the user with visual controls. Therefore, correctness of GUI’s code is essential to the correct execution of the overall software. Models can help in the evaluation of interactive applications by allowing designers to concentrate on its more important aspects. This paper describes our approach to reverse engineer an abstract model of a user interface directly from the GUI’s legacy code. We also present results from a case study. These results are encouraging and give evidence that the goal of reverse engineering user interfaces can be met with more work on this technique.

Higher-order lazy functional slicing

Program slicing is a well known family of techniques intended to identify and isolate code fragments which depend on, or are depended upon, specific program entities. This is particularly useful in the areas of reverse engineering, program understanding, testing and software maintenance. Most slicing methods, and corresponding tools, target either the imperative or the object oriented paradigms, where program slices are computed with respect to a variable or a program statement. Taking a complementary point of view, this paper focuses on the slicing of higher-order functional programs under a lazy evaluation strategy. A prototype of a Haskell slicer, built as proof-of-concept for these ideas, is also introduced

Identifying clones in functional programs for refactoring

Clone detection is well established for imperative programs. It works mostly on the statement level and therefore is ill-suited for func- tional programs, whose main constituents are expressions and types. In this paper we introduce clone detection for functional programs using a new intermediate program representation, dubbed Functional Control Tree. We extend clone detection to the identi cation of non-trivial func- tional program clones based on the recursion patterns from the so-called Bird-Meertens formalism

SHACC: a functional prototyper for a component calculus

Over the last decade component-based software development arose as a promising paradigm to deal with the ever increasing complexity in software design, evolution and reuse. SHACC is a prototyping tool for component-based systems in which components are modelled coinductively as generalized Mealy machines. The prototype is built as a HASKELL library endowed with a graphical user interface developed in Swing

Prediction of genetic gain from selection indices for disease resistance in papaya hybrids

In order to select superior hybrids for the concentration of favorable alleles for resistance to papaya black spot, powdery mildew and phoma spot, 67 hybrids were evaluated in two seasons, in 2007, in a randomized block design with two replications. Genetic gains were estimated from the selection indices of Smith & Hazel, Pesek & Baker, Williams, Mulamba & Mock, with selection intensity of 22.39%, corresponding to 15 hybrids. The index of Mulamba & Mock showed gains more suitable for the five traits assessed when it was used the criterion of economic weight tentatively assigned. Together, severity of black spot on leaves and on fruits, characteristics considered most relevant to the selection of resistant materials, expressed percentage gain of -44.15%. In addition, there were gains for other characteristics, with negative predicted selective percentage gain. The results showed that the index of Mulamba & Mock is the most efficient procedure for simultaneous selection of papaya hybrid resistant to black spot, powdery mildew and phoma spot.

Slicing functional programs by calculation

Program slicing is a well known family of techniques used to identify code fragments which depend on or are depended upon specific program entities. They are particularly useful in the areas of reverse engineering, program understanding, testing and software maintenance. Most slicing methods, usually targeting either the imperative or the object oriented paradigms, are based on some sort of graph structure representing program dependencies. Slicing techniques amount, therefore, to (sophisticated) graph transversal algorithms. This paper proposes a completely different approach to the slicing problem for functional programs. Instead of extracting program information to build an underlying dependencies’ structure, we resort to standard program calculation strategies, based on the so-called Bird- Meertens formalism. The slicing criterion is specified either as a projection or a hiding function which, once composed with the original program, leads to the identification of the intended slice. Going through a number of examples, the paper suggests this approach may be an interesting, even if not completely general alternative to slicing functional programs

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Surface plasmon resonance as a tool in the functional analisys of an immunodominant site in foot-and-mouth disease virus

A fast and direct surface plasmon resonance (SPR) method for the kinetic analysis of the interactions between peptide antigens and immobilised monoclonal antibodies (mAb) has been established. Protocols have been developed to overcome the problems posed by the small size of the analytes (< 1600 Da). The interactions were well described by a simple 1:1 bimolecular interaction and the rate constants were self-consistent and reproducible. The key features for the accuracy of the kinetic constants measured were high buffer flow rates, medium antibody surface densities and high peptide concentrations. The method was applied to an extensive analysis of over 40 peptide analogues towards two distinct anti-FMDV antibodies, providing data in total agreement with previous competition ELISA experiments. Eleven linear 15-residue synthetic peptides, reproducing all possible combinations of the four replacements found in foot-and-mouth disease virus (FMDV) field isolate C-S30, were evaluated. The direct kinetic SPR analysis of the interactions between these peptides and three anti-site A mAbs suggested additivity in all combinations of the four relevant mutations, which was confirmed by parallel ELISA analysis. The four-point mutant peptide (A15S30) reproducing site A from the C-S30 strain was the least antigenic of the set, in disagreement with previously reported studies with the virus isolate. Increasing peptide size from 15 to 21 residues did not significantly improve antigenicity. Overnight incubation of A15S30 with mAb 4C4 in solution showed a marked increase in peptide antigenicity not observed for other peptide analogues, suggesting that conformational rearrangement could lead to a stable peptide-antibody complex. In fact, peptide cyclization clearly improved antigenicity, confirming an antigenic reversion in a multiply substituted peptide. Solution NMR studies of both linear and cyclic versions of the antigenic loop of FMDV C-S30 showed that structural features previously correlated with antigenicity were more pronounced in the cyclic peptide. Twenty-six synthetic peptides, corresponding to all possible combinations of five single-point antigenicity-enhancing replacements in the GH loop of FMDV C-S8c1, were also studied. SPR kinetic screening of these peptides was not possible due to problems mainly related to the high mAb affinities displayed by these synthetic antigens. Solution affinity SPR analysis was employed and affinities displayed were generally comparable to or even higher than those corresponding to the C-S8c1 reference peptide A15. The NMR characterisation of one of these multiple mutants in solution showed that it had a conformational behaviour quite similar to that of the native sequence A15 and the X-ray diffraction crystallographic analysis of the peptide ? mAb 4C4 complex showed paratope ? epitope interactions identical to all FMDV peptide ? mAb complexes studied so far. Key residues for these interactions are those directly involved in epitope ? paratope contacts (141Arg, 143Asp, 146His) as well as residues able to stabilise a particular peptide global folding. A quasi-cyclic conformation is held up by a hydrophobic cavity defined by residues 138, 144 and 147 and by other key intrapeptide hydrogen bonds, delineating an open turn at positions 141, 142 and 143 (corresponding to the Arg-Gly-Asp motif).

Body composition, muscle strength, functional capacity, and physical disability risk in liver transplanted familial amyloidotic polyneuropathy patients

Abstract: Background: Familial amyloidotic polyneuropathy (FAP) is a neurodegenerative disease leading to sensory and motor polyneuropathies, and functional limitations. Liver transplantation is the only treatment for FAP, requiring medication that negatively affects bone and muscle metabolism. The aim of this study was to compare body composition, levels of specific strength, level of physical disability risk, and functional capacity of transplanted FAP patients (FAPTx) with a group of healthy individuals (CON). Methods: A group of patients with 48 FAPTx (28 men, 20 women) was compared with 24 CON individuals (14 men, 10 women). Body composition was assessed by dual-energy X-ray absorptiometry, and total skeletal muscle mass (TBSMM) and skeletal muscle index (SMI) were calculated. Handgrip strength was measured for both hands as was isometric strength of quadriceps. Muscle quality (MQ) was ascertained by the ratio of strength to muscle mass. Functional capacity was assessed by the six-minute walk test. Results: Patients with FAPTx had significantly lower functional capacity, weight, body mass index, total fat mass, TBSMM, SMI, lean mass, muscle strength, MQ, and bone mineral density. Conclusion: Patients with FAPTx appear to be at particularly high risk of functional disability, suggesting an important role for an early and appropriately designed rehabilitation program.

Strength, muscle quality and functional capacity in liver transplanted familial amyloidotic polineuropathy patients

Liver transplantation is the unique treatment for several end-stage diseases. Familial Amiloidotic Polineuropathy (FAP) is a neurodegenerative disease related with systemic deposition of amyloidal fiber mainly on peripheral nervous system, clinically translated by an autonomous sensitive-motor neuropathy with severe functional limitations in some cases. The unique treatment for FAP disease is a liver transplant with a very aggressive medication to muscle metabolism and force production. To our knowledge there are no quantitative characterizations of body composition, strength or functional capacity in this population.

Assessment and prediction of asthma and its severity in the pediatric community

Seventy four asthmatic children aged 7 to 11 years were examined along with controls matched by age and sex. Clinical and laboratory investigations preceded a 28-day follow-up where data about morning and evening peak expiratory flow rate (PEF), symptoms and treatment were recorded. The coefficient of variation of PEF was found to be an objective measurement of asthma severity that has statistically significant correlation with both symptoms (r s= .36) and treatment (r s= .60). Moreover, it separates mild and severe asthmatics, as confirmed by statistically significant differences (p= .008 or less) in symptoms, treatment, skin allergy and airways response to exercise. Skin allergy and airways responsiveness to exercise were found to be predictors of both disease and severity. By means of logistic regression analysis it was possible to establish the probabilities for both asthma and severe asthma when children presenting and not presenting these characteristics are compared. One single positive skin test represent a probability of 88% for the development of asthma and a probability of 70% for severe disease. A PEF reduction of 10% after an exercise test implies a probability of 73% for disease and a probability of 64% for severe disease. Increases in these variables imply geometrically increased risks and their presence together have a multiplicative effect in the final risk.