Cerebral microbleeds and cognitive decline in a hemodialysis patient: Case report and review of literature

Cerebral microbleeds (CMBs) are small hemosiderin deposits indicative of prior cerebral microscopic hemorrhage and previously thought to be clinically silent. Recent population‐based cross‐sectional studies and prospective longitudinal cohort studies have revealed association between CMB and cognitive dysfunction. In the general population, CMBs are associated with age, hypertension, and cerebral amyloid angiopathy. In the chronic kidney disease (CKD) population, diminished estimated glomerular filtration rate has been found to be an independent risk factor for CMB, raising the possibility that a uremic milieu may predispose to microbleeds. In the end‐stage renal disease (ESRD) population on hemodialysis, the incidence of microbleeds is significantly higher compared with a control group without history of CKD or stroke. We present an ESRD patient on chronic hemodialysis with a history of gradual cognitive decline and progressive CMBs. Through this case and literature review, we illustrate the need to develop detection and prediction models to treat this frequent development in ESRD patients.     

A 1-V 10.7-MHz switched-opamp bandpass /spl Sigma//spl Delta/ modulator using double-sampling finite-gain-compensation technique

A 1 V switched-capacitor (SC) bandpass sigma-delta (/spl Sigma//spl Delta/) modulator is realized using a high-speed switched-opamp (SO) technique with a sampling frequency of up to 50 MHz, which is improved ten times more than prior 1 V SO designs and comparable to the performance of the state-of-the-art SC circuits that operate at much higher supply voltages. On the system level, a fast-settling double-sampling SC biquadratic filter architecture is proposed to achieve high-speed operation. A low-voltage double-sampling finite-gain-compensation technique is employed to realize a high-resolution /spl Sigma//spl Delta/ modulator using only low-DC-gain opamps to maximize the speed and to reduce power dissipation. On the circuit level, a fast-switching methodology is proposed for the design of the switchable opamps to achieve a switching frequency up to 50 MHz. Implemented in a 0.35-/spl mu/m CMOS process (V/sub TP/=0.82 V and V/sub TN/=0.65 V) and at 1 V supply, the modulator achieves a measured peak signal-to-noise-and-distortion ratio (SNDR) of 42.3 dB at 10.7 MHz with a signal bandwidth of 200 kHz, while dissipating 12 mW and occupying a chip area of 1.3 mm/sup 2/.     

Coronary bypass in vascular patients: a relatively high-risk procedure

A premise of cardiac risk stratification is that the added risk of coronary artery bypass grafting (CABG) is offset by the improved safety of subsequent vascular reconstruction (VR). We questioned if elective CABG is patients with severe peripheral vascular disease (PVD) is a relatively high-risk procedure. A cohort study of 680 elective CABG patients from January 1993 to December 1994 was performed using three mutually exclusive outcomes of complication-free survival, morbidity, and mortality. Patient characteristic, operative, and outcome data were prospectively collected. Retrospective review determined that 58 patients had either a standard indication for or a history of VR. Overall CABG mortality was 2.5%, with statistically similar but relatively higher rates for PVD as compared to non-PVD patients. In contrast, major morbidity occurred at rates 3.6-fold higher in PVD patients (39.7%) than in disease-free patients (16.7%) after adjustment for the effects of patient and operative variables (odds ratio [OR] 3.67, 95% confidence interval [CI] 1.93-6.99). CABG morbidity in the PVD patient was most likely in those patients with aortoiliac (OR 9.51, CI 3.20-28.27) and aortic aneurysmal (OR 5.24, CI 1.28-21.41) disease types. CABG in PVD patients is associated with significant major morbidity. Such morbidity may preclude or alter the timing of subsequent VR.     

The double-reversing Z-plasty in primary palatoplasty: operative experience and early results

The double-reversing Z-plasty of Furlow for closure of the soft palate was used in 34 children with various types of cleft palate. Mean age at repair was 12.8 months. Intraoperative experience was favorable, with acceptable operating time and blood loss. Length of hospitalization averaged 1.9 days. Postoperatively, two children experienced temporary stridor, which resolved within 24 to 48 hours. One child had dehiscence of the hard palate (Von Lagenbeck repair) 4 weeks postoperatively, and three children developed small oronasal fistulae. Early speech evaluation demonstrated adequate soft palate mobility in 33 of 34 patients, with observable velopharyngeal function. Twelve children had mild velar compromise, with eight exhibiting slight nasal air escape.     

A high-linearity 100-element diode grid mixer

Grid-mixer arrays can achieve high linearity and dynamic range through quasi-optical power combining. We present a 100-element single-ended diode grid mixer operating at 2.45 GHz. Each element incorporates two diodes in series. We measure an input third-order intercept of 11 W (40.5 dBm), and output third-order intercept of 3.4 W (35.4 dBm), and an associated conversion loss of 5.1 dB. The power-handling capability of the array is 100 times larger than that of a microstrip mixer using a single element. The local oscillator (LO) drive requirement for the entire array is 1.4 W (31.6 dBm). The angular dependence of the array's IF power is also presented and is in agreement with theory     

Solution of Helmholtz equation by Trefftz method

The application of the Trefftz method for calculating wave forces on offshore structures is presented. Indirect and direct formulations using complete and non-singular systems of Trefftz functions for the Helmholtz equation are posed in this paper. An effective technique using different interpolation functions for the velocity potential and wave force are suggested to improve the computational accuracy of the wave force. The numerical examples show that the present method is highly efficient and accurate.     

Optimal transfer trees and distinguishing trees for testing observable nondeterministic finite-state machines

The fault-state detection approach for blackbox testing consists of two phases. The first is to bring the system under test (SUT) from its initial state to a targeted state t and the second is to check various specified properties of the SUT at t. This paper investigates the first phase for testing systems specified as observable nondeterministic finite-state machines with probabilistic and weighted transitions. This phase involves two steps. The first step transfers the SUT to some state t' and the second step identifies whether t' is indeed the targeted state t or not. State transfer is achieved by moving the SUT along one of the paths of a transfer tree (TT) and state identification is realized by using diagnosis trees (DT). A theoretical foundation for the existence and characterization of TT and DT with minimum weighted height or minimum average weight is presented. Algorithms for their computation are proposed.     

A new method to estimate parameters of linear compartmental models using artificial neural networks

At present, the preferred tool for parameter estimation in compartmental analysis is an iterative procedure; weighted nonlinear regression. For a large number of applications, observed data can be fitted to sums of exponentials whose parameters are directly related to the rate constants/coefficients of the compartmental models. Since weighted nonlinear regression often has to be repeated for many different data sets, the process of fitting data from compartmental systems can be very time consuming. Furthermore the minimization routine often converges to a local (as opposed to global) minimum. In this paper, we examine the possibility of using artificial neural networks instead of weighted nonlinear regression in order to estimate model parameters. We train simple feed-forward neural networks to produce as outputs the parameter values of a given model when kinetic data are fed to the networks' input layer. The artificial neural networks produce unbiased estimates and are orders of magnitude faster than regression algorithms. At noise levels typical of many real applications, the neural networks are found to produce lower variance estimates than weighted nonlinear regression in the estimation of parameters from mono- and biexponential models. These results are primarily due to the inability of weighted nonlinear regression to converge. These results establish that artificial neural networks are powerful tools for estimating parameters for simple compartmental models.     

Modeling electromigration lifetime under bidirectional currentstress

Electromigration reliability of interconnect under bidirectional current stress has been studied in a wide frequency range (mHz to 200 MHz). Experimental results show that the AC lifetime rises with the stress current frequency. The current density exponent and the activation energy of AC lifetime are found to be twice that of DC lifetime. Pure AC current stress failure at extremely high current density is believed to result from thermal migration of metal at hot/cold transition points