Spinal stiffness changes throughout the respiratory cycle

Posteroanterior stiffness of the lumbar spine is influenced by factors, including trunk muscle activity and intra-abdominal pressure (IAP). Because these factors vary with breathing, this study investigated whether stiffness is modulated in a cyclical manner with respiration. A further aim was to investigate the relationship between stiffness and IAP or abdominal and paraspinal muscle activity. Stiffness was measured from force-displacement responses of a posteroanterior force applied over the spinous process of L-2 and L-4. Recordings were made of IAP and electromyographic activity from L-4/L-2 erector spinae, abdominal muscles, and chest wall. Stiffness was measured with the lung volume held at the extremes of tidal volume and at greater and lesser volumes. Stiffness at L-4 and L-2 increased above base-level values at functional residual capacity (L-2 14.9 N/mm and L-4 15.3 N/mm) with both inspiratory and expiratory efforts. The increase was related to the respiratory effort and was greatest during maximum expiration (L-2 24.9 N/mm and L-4 23.9 N/mm). The results indicate that changes in trunk muscle activity and IAP with respiratory efforts modulate spinal stiffness. In addition, the diaphragm may augment spinal stiffness via attachment of its crural fibers to the lumbar vertebrae.

Theoretical and experimental studies of unbraced tubular trusses allowing for torsional stiffness

This paper describes the buckling phenomenon of a tubular truss with unsupported length through a full-scale test and presents a practical computational method for the design of the trusses allowing for the contribution of torsional stiffness against buckling, of which the effect has never been considered previously by others. The current practice for the design of a planar truss has largely been based on the linear elastic approach which cannot allow for the contribution of torsional stiffness and tension members in a structural system against buckling. The over-simplified analytical technique is unable to provide a realistic and an economical design to a structure. In this paper the stability theory is applied to the second-order analysis and design of the structural form, with detailed allowance for the instability and second-order effects in compliance with design code requirements. Finally, the paper demonstrates the application of the proposed method to the stability design of a commonly adopted truss system used in support of glass panels in which lateral bracing members are highly undesirable for economical and aesthetic reasons.

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

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.

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.

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.

A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

Stiffness da tibiotársica em sujeitos com Acidente Vascular Encefálico - processo de raciocínio clínico

regula a posição do corpo no espaço, sendo um pré-requisito para o movimento. À periferia este processo de Controlo Postural pode ser identificado também através da variação do stiffness. O Acidente Vascular Encefálico apresenta-se como a patologia onde os sujeitos são referenciados como tendo alteração do stiffness, e poderão verificar-se modificações nesta variável no âmbito da reabilitação neuro-motora. Objetivo: Descrever o comportamento do stiffness da tibiotársica, nos dois membros inferiores, em indivíduos pós Acidente Vascular Encefálico, face a uma intervenção em fisioterapia baseada num processo de raciocínio clínico. Métodos: 5 sujeitos participaram no estudo, tendo sido implementado um programa de reabilitação para cada um dos sujeitos, por um período de 3 meses, com 2 momentos de avaliação (M0 e M1). O torque e a amplitude articular da tibiotársica foi monitorizada, através do dinamómetro isocinético, durante o movimento passivo de dorsiflexão, a diferentes velocidades (5º/s, 1º/s e 0,25º/s) A atividade eletromiográfica dos músculos Gastrocnémio Interno e Solear foi também recolhida. O valor de stiffness foi calculado através da relação torque/posição. Resultados: Em todos os sujeitos em estudo verificou-se que de uma forma geral o stiffness do membro contralateral à lesão apresentou uma modificação no sentido da diminuição em todas as amplitudes em M1. Nos sujeitos A e C, verificou-se que o stiffness do membro ipsilateral apresentou uma modificação no sentido da diminuição em M1 (em amplitudes intermédias). Nos sujeitos B, D e E o stiffness não apresentou modificações. O stiffness não variou com a velocidade. Conclusão: O stiffness apontou para uma diminuição, nos sujeitos em estudo no membro contralateral à lesão e no membro ipsilateral à lesão nos sujeitos A e C em amplitudes intermédias.

Geostatistical Prediction of Ocean Outfall Plume Characteristics Based on an Autonomous Underwater Vehicle

Geostatistics has been successfully used to analyze and characterize the spatial variability of environmental properties. Besides giving estimated values at unsampled locations, it provides a measure of the accuracy of the estimate, which is a significant advantage over traditional methods used to assess pollution. In this work universal block kriging is novelty used to model and map the spatial distribution of salinity measurements gathered by an Autonomous Underwater Vehicle in a sea outfall monitoring campaign, with the aim of distinguishing the effluent plume from the receiving waters, characterizing its spatial variability in the vicinity of the discharge and estimating dilution. The results demonstrate that geostatistical methodology can provide good estimates of the dispersion of effluents that are very valuable in assessing the environmental impact and managing sea outfalls. Moreover, since accurate measurements of the plume’s dilution are rare, these studies might be very helpful in the future to validate dispersion models.

Optimization study of hybrid spot-welded/bonded single-lap joints

Joining of components with structural adhesives is currently one of the most widespread techniques for advanced structures (e.g., aerospace or aeronautical). Adhesive bonding does not involve drilling operations and it distributes the load over a larger area than mechanical joints. However, peak stresses tend to develop near the overlap edges because of differential straining of the adherends and load asymmetry. As a result, premature failures can be expected, especially for brittle adhesives. Moreover, bonded joints are very sensitive to the surface treatment of the material, service temperature, humidity and ageing. To surpass these limitations, the combination of adhesive bonding with spot-welding is a choice to be considered, adding a few advantages like superior static strength and stiffness, higher peeling and fatigue strength and easier fabrication, as fixtures during the adhesive curing are not needed. The experimental and numerical study presented here evaluates hybrid spot-welded/bonded single-lap joints in comparison with the purely spot-welded and bonded equivalents. A parametric study on the overlap length (LO) allowed achieving different strength advantages, up to 58% compared to spot-welded joints and 24% over bonded joints. The Finite Element Method (FEM) and Cohesive Zone Models (CZM) for damage growth were also tested in Abaqus® to evaluate this technique for strength prediction, showing accurate estimations for all kinds of joints.