Therapeutic hypothermia after cardiac arrest : Studies on neurological and cardiological outcome and prediction of outcome in hypothermia-treated patients resuscitated from out-of-hospital cardiac arrest

The outcome of the successfully resuscitated patient is mainly determined by the extent of hypoxic-ischemic cerebral injury, and hypothermia has multiple mechanisms of action in mitigating such injury. The present study was undertaken from 1997 to 2001 in Helsinki as a part of the European multicenter study Hypothermia after cardiac arrest (HACA) to test the neuroprotective effect of therapeutic hypothermia in patients resuscitated from out-of-hospital ventricular fibrillation (VF) cardiac arrest (CA). The aim of this substudy was to examine the neurological and cardiological outcome of these patients, and especially to study and develop methods for prediction of outcome in the hypothermia-treated patients. A total of 275 patients were randomized to the HACA trial in Europe. In Helsinki, 70 patients were enrolled in the study according to the inclusion criteria. Those randomized to hypothermia were actively cooled externally to a core temperature 33 ± 1ºC for 24 hours with a cooling device. Serum markers of ischemic neuronal injury, NSE and S-100B, were sampled at 24, 36, and 48 hours after CA. Somatosensory and brain stem auditory evoked potentials (SEPs and BAEPs) were recorded 24 to 28 hours after CA; 24-hour ambulatory electrocardiography recordings were performed three times during the first two weeks and arrhythmias and heart rate variability (HRV) were analyzed from the tapes. The clinical outcome was assessed 3 and 6 months after CA. Neuropsychological examinations were performed on the conscious survivors 3 months after the CA. Quantitative electroencephalography (Q-EEG) and auditory P300 event-related potentials were studied at the same time-point. Therapeutic hypothermia of 33ºC for 24 hours led to an increased chance of good neurological outcome and survival after out-of-hospital VF CA. In the HACA study, 55% of hypothermia-treated patients and 39% of normothermia-treated patients reached a good neurological outcome (p=0.009) at 6 months after CA. Use of therapeutic hypothermia was not associated with any increase in clinically significant arrhythmias. The levels of serum NSE, but not the levels of S-100B, were lower in hypothermia- than in normothermia-treated patients. A decrease in NSE values between 24 and 48 hours was associated with good outcome at 6 months after CA. Decreasing levels of serum NSE but not of S-100B over time may indicate selective attenuation of delayed neuronal death by therapeutic hypothermia, and the time-course of serum NSE between 24 and 48 hours after CA may help in clinical decision-making. In SEP recordings bilaterally absent N20 responses predicted permanent coma with a specificity of 100% in both treatment arms. Recording of BAEPs provided no additional benefit in outcome prediction. Preserved 24- to 48-hour HRV may be a predictor of favorable outcome in CA patients treated with hypothermia. At 3 months after CA, no differences appeared in any cognitive functions between the two groups: 67% of patients in the hypothermia and 44% patients in the normothermia group were cognitively intact or had only very mild impairment. No significant differences emerged in any of the Q-EEG parameters between the two groups. The amplitude of P300 potential was significantly higher in the hypothermia-treated group. These results give further support to the use of therapeutic hypothermia in patients with sudden out-of-hospital CA.

A numerical study of crack tip constraint in ductile single crystals

In this work, the effect of crack tip constraint on near-tip stress and deformation fields in a ductile FCC single crystal is studied under mode I, plane strain conditions. To this end, modified boundary layer simulations within crystal plasticity framework are performed, neglecting elastic anisotropy. The first and second terms of the isotropic elastic crack tip field, which are governed by the stress intensity factor K and T-stress, are prescribed as remote boundary conditions and solutions pertaining to different levels of T-stress are generated. It is found that the near-tip deformation field, especially, the development of kink or slip shear bands, is sensitive to the constraint level. The stress distribution and the size and shape of the plastic zone near the crack tip are also strongly influenced by the level of T-stress, with progressive loss of crack tip constraint occurring as T-stress becomes more negative. A family of near-tip fields is obtained which are characterized by two terms (such as K and T or J and a constraint parameter Q) as in isotropic plastic solids.

A numerical study of the effect of loading conditions on tubular hydroforming

In this work, the mechanics of tubular hydroforming under various types of loading conditions is investigated. The main objective is to contrast the effects of prescribing fluid pressure or volume flow rate, in conjunction with axial displacement, on the stress and strain histories experienced by the tube and the process of bulging. To this end, axisymmetric finite element simulations of free hydroforming (without external die contact) of aluminium alloy tubes are carried out. Hill’s normally anisotropic yield theory along with material properties determined in a previous experimental study [A. Kulkarni, P. Biswas, R. Narasimhan, A. Luo, T. Stoughton, R. Mishra, A.K. Sachdev, An experimental and numerical study of necking initiation in aluminium alloy tubes during hydroforming, Int. J. Mech. Sci. 46 (2004) 1727–1746] are employed in the computations. It is found that while prescribed fluid pressure leads to highly non-proportional strain paths, specified fluid volume flow rate may result in almost proportional ones for the predominant portion of loading. The peak pressure increases with axial compression for the former, while the reverse trend applies under the latter. The implication of these results on failure by localized necking of the tube wall is addressed in a subsequent investigation.

CAE-based prediction of projectile residual velocity for impact on single and multi-layered metallic armour plates

The present, paper deals with the CAE-based study Of impact of jacketed projectiles on single- and multi-layered metal armour plates using LS-DYNA. The validation of finite element modelling procedure is mainly based on the mesh convergence study using both shell and solid elements for representing single-layered mild steel target plates. It, is shown that the proper choice of mesh density and the strain rate-dependent material properties are essential for all accurate prediction of projectile residual velocity. The modelling requirements are initially arrived at by correlating against test residual velocities for single-layered mild steel plates of different depths at impact velocities in the ran.-c of approximately 800-870 m/s. The efficacy of correlation is adjudged, in terms of a 'correlation index', defined in the paper: for which values close to unity are desirable. The experience gained for single-layered plates is next; used in simulating projectile impacts on multi-layered mild steel target plates and once again a high degree of correlation with experimental residual velocities is observed. The study is repeated for single- and multi-layered aluminium target plates with a similar level of success in test residual velocity prediction. TO the authors' best knowledge, the present comprehensive study shows in particular for the first time that, with a. proper modelling approach, LS-DYNA can be used with a great degree of confidence in designing perforation-resistant single and multi-layered metallic armour plates.

Acute renal failure in critically ill patients : With special reference to prediction of outcome

Acute renal failure (ARF) is a clinical syndrome characterized by rapidly decreasing glomerular filtration rate, which results in disturbances in electrolyte- and acid-base homeostasis, derangement of extracellular fluid volume, and retention of nitrogenous waste products, and is often associated with decreased urine output. ARF affects about 5-25% of patients admitted to intensive care units (ICUs), and is linked to high mortality and morbidity rates. In this thesis outcome of critically ill patients with ARF and factors related to outcome were evaluated. A total of 1662 patients from two ICUs and one acute dialysis unit in Helsinki University Hospital were included. In study I the prevalence of ARF was calculated and classified according to two ARF-specific scoring methods, the RIFLE classification and the classification created by Bellomo et al. (2001). Study II evaluated monocyte human histocompatibility leukocyte antigen-DR (HLA-DR) expression and plasma levels of one proinflammatory (interleukin (IL) 6) and two anti-inflammatory (IL-8 and IL-10) cytokines in predicting survival of critically ill ARF patients. Study III investigated serum cystatin C as a marker of renal function in ARF and its power in predicting survival of critically ill ARF patients. Study IV evaluated the effect of intermittent hemodiafiltration (HDF) on myoglobin elimination from plasma in severe rhabdomyolysis. Study V assessed long-term survival and health-related quality of life (HRQoL) in ARF patients. Neither of the ARF-specific scoring methods presented good discriminative power regarding hospital mortality. The maximum RIFLE score for the first three days in the ICU was an independent predictor of hospital mortality. As a marker of renal dysfunction, serum cystatin C failed to show benefit compared with plasma creatinine in detecting ARF or predicting patient survival. Neither cystatin C nor plasma concentrations of IL-6, IL-8, and IL-10, nor monocyte HLA-DR expression were clinically useful in predicting mortality in ARF patients. HDF may be used to clear myoglobin from plasma in rhabdomyolysis, especially if the alkalization of diuresis does not succeed. The long-term survival of patients with ARF was found to be poor. The HRQoL of those who survive is lower than that of the age- and gender-matched general population.

Fuzzy-logic-based health monitoring and residual-life prediction for composite helicopter rotor

A health-monitoring and life-estimation strategy for composite rotor blades is developed in this work. The cross-sectional stiffness reduction obtained by physics-based models is expressed as a function of the life of the structure using a recent phenomenological damage model. This stiffness reduction is further used to study the behavior of measurable system parameters such as blade deflections, loads, and strains of a composite rotor blade in static analysis and forward flight. The simulated measurements are obtained using an aeroelastic analysis of the composite rotor blade based on the finite element in space and time with physics-based damage modes that are then linked to the life consumption of the blade. The model-based measurements are contaminated with noise to simulate real data. Genetic fuzzy systems are developed for global online prediction of physical damage and life consumption using displacement- and force-based measurement deviations between damaged and undamaged conditions. Furthermore, local online prediction of physical damage and life consumption is done using strains measured along the blade length. It is observed that the life consumption in the matrix-cracking zone is about 12-15% and life consumption in debonding/delamination zone is about 45-55% of the total life of the blade. It is also observed that the success rate of the genetic fuzzy systems depends upon the number of measurements, type of measurements and training, and the testing noise level. The genetic fuzzy systems work quite well with noisy data and are recommended for online structural health monitoring of composite helicopter rotor blades.

Generalized survival in step fluctuations

The properties of the generalized survival probability, that is, the probability of not crossing an arbitrary location R during relaxation, have been investigated experimentally (via scanning tunneling microscope observations) and numerically. The results confirm that the generalized survival probability decays exponentially with a time constant tau(s)(R). The distance dependence of the time constant is shown to be tau(s)(R)=tau(s0)exp[-R/w(T)], where w(2)(T) is the material-dependent mean-squared width of the step fluctuations. The result reveals the dependence on the physical parameters of the system inherent in the prior prediction of the time constant scaling with R/L-alpha, with L the system size and alpha the roughness exponent. The survival behavior is also analyzed using a contrasting concept, the generalized inside survival S-in(t,R), which involves fluctuations to an arbitrary location R further from the average. Numerical simulations of the inside survival probability also show an exponential time dependence, and the extracted time constant empirically shows (R/w)(lambda) behavior, with lambda varying over 0.6 to 0.8 as the sampling conditions are changed. The experimental data show similar behavior, and can be well fit with lambda=1.0 for T=300 K, and 0.5

Experimental study on shrinkage behaviour and prediction of shrinkage magnitudes of residual soils

The present study examines the shrinkage behaviour of residually derived black cotton (BC) soil and red soil compacted specimens that were subjected to air-drying from the swollen state. The soil specimens were compacted at varying dry density and moisture contents to simulate varied field conditions. The void ratio and moisture content of the swollen specimens were monitored during the drying process and relationship between them is analyzed. Shrinkage is represented as reduction in void ratio with decrease in water content of soil specimens. It is found to occur in three distinct stages. Total shrinkage magnitude depends on the type of clay mineral present. Variation in compaction conditions effect marginally total shrinkage magnitudes of BC soil specimens but have relatively more effect on red soil specimens. A linear relation is obtained between total shrinkage magnitude and volumetric water content of soil specimens in swollen state and can be used to predict the shrinkage magnitude of soils.

Concrete-filled double skin tube columns subjected to lateral impact loading: Experimental and numerical study

This research treats the lateral impact behaviour of composite columns, which find increasing use as bridge piers and building columns. It offers (1) innovative experimental methods for testing structural columns, (2) dynamic computer simulation techniques as a viable tool in analysis and design of such columns and (3) significant new information on their performance which can be used in design. The research outcomes will enable to protect lives and properties against the risk of vehicular impacts caused either accidentally or intentionally.

Numerical Simulation of Groundwater Flow with Gradually Increasing Heterogeneity due to Clogging

Well injection replenishes depleting water levels in a well field. Observation well water levels some distance away from the injection well are the indicators of the success of a well injection program. Simulation of the observation well response, located a few tens of meters from the injection well, is likely to be affected by the effects of nonhomogeneous medium, inclined initial water table, and aquifer clogging. Existing algorithms, such as the U.S. Geological Survey groundwater flow software MODFLOW, are capable of handling the first two conditions, whereas time-dependent clogging effects are yet to be introduced in the groundwater flow models. Elsewhere, aquifer clogging is extensively researched in theory of filtration; scope for its application in a well field is a potential research problem. In the present paper, coupling of one such filtration theory to MODFLOW is introduced. Simulation of clogging effects during “Hansol” well recharge in the parts of western India is found to be encouraging.

Memory-efficient spatial prediction image compression scheme

In prediction phase, the hierarchical tree structure obtained from the test image is used to predict every central pixel of an image by its four neighboring pixels. The prediction scheme generates the predicted error image, to which the wavelet/sub-band coding algorithm can be applied to obtain efficient compression. In quantization phase, we used a modified SPIHT algorithm to achieve efficiency in memory requirements. The memory constraint plays a vital role in wireless and bandwidth-limited applications. A single reusable list is used instead of three continuously growing linked lists as in case of SPIHT. This method is error resilient. The performance is measured in terms of PSNR and memory requirements. The algorithm shows good compression performance and significant savings in memory. (C) 2006 Elsevier B.V. All rights reserved.

OCR Prediction Using Support Vector Machine Based on Piezocone Data

The determination of the overconsolidation ratio (OCR) of clay deposits is an important task in geotechnical engineering practice. This paper examines the potential of a support vector machine (SVM) for predicting the OCR of clays from piezocone penetration test data. SVM is a statistical learning theory based on a structural risk minimization principle that minimizes both error and weight terms. The five input variables used for the SVM model for prediction of OCR are the corrected cone resistance (qt), vertical total stress (sigmav), hydrostatic pore pressure (u0), pore pressure at the cone tip (u1), and the pore pressure just above the cone base (u2). Sensitivity analysis has been performed to investigate the relative importance of each of the input parameters. From the sensitivity analysis, it is clear that qt=primary in situ data influenced by OCR followed by sigmav, u0, u2, and u1. Comparison between SVM and some of the traditional interpretation methods is also presented. The results of this study have shown that the SVM approach has the potential to be a practical tool for determination of OCR.

How Effective Is The Data On Co-Occurrence Of Domains In Multi-Domain Proteins In Prediction Of Protein-Protein Interactions?

We explore the fuse of information on co-occurrence of domains in multi-domain proteins in predicting protein-protein interactions. The basic premise of our work is the assumption that domains co-occurring in a polypeptide chain undergo either structural or functional interactions among themselves. In this study we use a template dataset of domains in multidomain proteins and predict protein-protein interactions in a target organism. We note that maximum number of correct predictions of interacting protein domain families (158) is made in S. cerevisiae when the dataset of closely related organisms is used as the template followed by the more diverse dataset of bacterial proteins (48) and a dataset of randomly chosen proteins (23). We conclude that use of multi-domain information from organisms closely-related to the target can aid prediction of interacting protein families.