Outcome analysis of 245 CarboMedics and St. Jude valves implanted at the same institution

BACKGROUND: Thromboembolism and valve-related death are major complications associated with prosthetic valve implants, but it is difficult to evaluate the relative incidence of these complications based on studies in which the implantation of only one valve is reported from any given institution. We therefore report the outcome of patients implanted at our institution during the same time period with either the recently released CarboMedics (CM) or the St. Jude Medical (SJ) valve prostheses. METHODS: Between October 1994 and January 1996, 245 consecutive patients received either SJ (116 patients) or CM (129 patients) valves at our institution. Follow up of these patients was 99.6% complete, for a total of 318.5 cumulative patient-years (median follow-up, 1.4 years). RESULTS: The 30-day mortality rates for SJ and CM implants were 3.4% and 3.1%, respectively. Actuarial survival and freedom from valve related mortality rates at 1.5 years for SJ and CM valves were 94%+/-2% versus 86%+/-3% (p = 0.03) and 100% versus 94%+/-2% (p = 0.005), respectively. There was no structural valve failure for either implant, but there were five thrombosed valves in the CM group and none in the SJ group (p = 0.04). All thrombosed valves were mitral (four mitral valve replacement, one aortic and mitral valve replacement). Two of the thrombosed valves were successfully explanted, whereas the three remaining patients died. Freedom from a thromboembolic event in the mitral position at 1.5 years, including thrombosed valves was 97%+/-3% and 83%+/-5% for SJ and CM valves, respectively (p = 0.04). CONCLUSIONS: The results of this study suggest that further evaluation of thromboembolic outcomes after CM compared with SJ valve implantation is warranted.     

Modelling and experimental verification of physical and chemical processes during pyrolysis of a large biomass particle

A mathematical model of wood pyrolysis is presented that is in satisfactory agreement with experimental reaction product distributions over a range of conditions of practical importance for gasification and combustion. Both chemical and physical processes are described, using fundamental principles. Inclusion of water release, tar cracking and char deposition chemical reactions results in predictions of ultimate product distributions (gas, tar and char yields) that are in good agreement with experiment and can aid in optimization of processes to maximize or minimize tar production. Predictions of the rate at which products are instantaneously released from a single wood pellet are also in agreement with experiment. This capability is important for combustion modelling and gasifier simulation. The study provides both extensive data and a fundamental modelling approach that will enhance understanding of the effects of physical properties and processes on the chemistry of devolatilizing biomass. The work emphasizes the need for information both on char deposition rates during carbonization of a range of fuel types and on char thermal properties over a wide range of temperatures and porosities.     

Constrained adaptive filtering algorithms: asymptotic convergenceproperties for dependent data

The convergence properties of constrained adaptive filtering algorithms are established. The constraint is in the form of a bounded set in which the filter's coefficients must lie. A recursive procedure that converges to the deterministic solution of the constrained linear mean-square estimation problem is obtained, using an appropriate contraction mapping. The recursion is used to derive the adaptive algorithm for the filter coefficients. Bounds on the mean-square error of the coefficients. Bounds on the mean-square error of the estimates of the filter coefficients and on the excess error of the input signal estimate are derived for processes that are either strong mixing or asymptotically uncorrelated. The algorithms use a moving window of size n on the data from one adaptation step to the next. However, tighter bounds can be obtained when a skipped sampling mechanism is used     

Metabolism and excretion of dimethoate following ingestion of overtolerance peas and a bolus dose

Data to guide an exposure assessment were obtained by giving sugar peas containing overtolerance dimethoate residues (17 ppm; 8% oxon) and a bolus dose of dimethoate to a healthy adult male. The dimethoate tolerance on peas was and remains 2 ppm. Serial total urine samples were collected and analysed for dimethoate and its oxon, dimethylphosphate, dimethylphosphorothioate (DMTP) and dimethylphosphorodithioate. The dose of dimethoate administered was approx. 0.1 mg/kg body weight and produced no symptoms of toxicity. Dimethylphosphates appeared in the urine within 2 hr. The major metabolite (about 60%) was DMTP. Only traces (< 0.5%) of dimethoate and oxon were recovered from urine. Acetylcholinesterase inhibition was not observed although urinary metabolites were prominent, indicating that they are better indicators of acute exposure than cholinesterase inhibition. The results obtained using a bolus dose were virtually identical to those from the trial with overtolerance peas, and indicated that dimethoate is readily absorbed and its urinary metabolites are readily eliminated following exposures to low doses (0.1 mg/kg body weight).     

Convergence analysis of adaptive linear estimation for dependentstationary processes

The convergence properties of an adaptive linear mean-square estimator that uses a modified LMS algorithm are established for generally dependent processes. Bounds on the mean-square error of the estimates of the filter coefficients and on the excess error of the estimate of the signal are derived for input processes which are either strong mixing or asymptotically uncorrelated. It is shown that the mean-square deviation is bounded by a constant multiple of the adaptation step size and that the same holds for the excess error of the signal estimation. The present findings extend earlier results in the literature obtained for independent and M-dependent input data     

A simple technique to induce and control short pulses of deepdrain-source breakdown conditions

A simple method to induce drain-source breakdown, followed by the parasitic bipolar action, is reported for time intervals and energies sufficiently small to avoid thermal runaway. A relatively large capacitor, connected in parallel to the device under test, is charged up using a sufficiently large resistor and discharges automatically as the breakdown voltage (BV_DSS) is reached, thus eliminating the need for a fast and `ringing-free' switch in the test setup. Since the discharge process is controlled by the small dynamic device resistance, rather than the large external resistor, the resulting transitions are fast enough and therefore compatible with electrostatic discharge (ESD) or latch-up turn-on conditions. Such pulses were successfully used to study soft ESD damage in lightly-doped-drain (LDD) devices, using simple on-wafer probing     

Nonlinear image operators for the evaluation of local intrinsicdimensionality

Local intrinsic dimensionality is shown to be an elementary structural property of multidimensional signals that cannot be evaluated using linear filters. We derive a class of polynomial operators for the detection of intrinsically 2-D image features like curved edges and lines, junctions, line ends, etc. Although it is a deterministic concept, intrinsic dimensionality is closely related to signal redundancy since it measures how many of the degrees of freedom provided by a signal domain are in fact used by an actual signal. Furthermore, there is an intimate connection to multidimensional surface geometry and to the concept of ;Gaussian curvature'. Nonlinear operators are inevitably required for the processing of intrinsic dimensionality since linear operators are, by the superposition principle, restricted to OR-combinations of their intrinsically 1-D eigenfunctions. The essential new feature provided by polynomial operators is their potential to act on multiplicative relations between frequency components. Therefore, such operators can provide the AND-combination of complex exponentials, which is required for the exploitation of intrinsic dimensionality. Using frequency design methods, we obtain a generalized class of quadratic Volterra operators that are selective to intrinsically 2-D signals. These operators can be adapted to the requirements of the signal processing task. For example, one can control the "curvature tuning" by adjusting the width of the stopband for intrinsically 1-D signals, or the operators can be provided in isotropic and in orientation-selective versions. We first derive the quadratic Volterra kernel involved in the computation of Gaussian curvature and then present examples of operators with other arrangements of stop and passbands. Some of the resulting operators show a close relationship to the end-stopped and dot-responsive neurons of the mammalian visual cortex.     

Effect of protein source and resistance training on body composition and sex hormones

Background  

Evidence suggests an inverse relationship between soy protein intake and serum concentrations of male sex hormones. Anecdotal evidence indicates that these alterations in serum sex hormones may attenuate changes in lean body mass following resistance training. However, little empirical data exists regarding the effects of soy and milk-based proteins on circulating androgens and exercise induced body composition changes.