White matter fractional anisotrophy predicts balance performance in older adults

Aging is characterized by brain structural changes that may compromise motor functions. In the context of postural control, white matter integrity is crucial for the efficient transfer of visual, proprioceptive and vestibular feedback in the brain. To determine the role of age-related white matter decline as a function of the sensory feedback necessary to correct posture, we acquired diffusion weighted images in young and old subjects. A force platform was used to measure changes in body posture under conditions of compromised proprioceptive and/or visual feedback. In the young group, no significant brain structure-balance relations were found. In the elderly however, the integrity of a cluster in the frontal forceps explained 21% of the variance in postural control when proprioceptive information was compromised. Additionally, when only the vestibular system supplied reliable information, the occipital forceps was the best predictor of balance performance (42%). Age-related white matter decline may thus be predictive of balance performance in the elderly when sensory systems start to degrade.

Core-based Methodology: An Automated Approach for Implementing a Complete System From Algorithms to a Heterogeneous Network Including FPGAs

In this paper, we present a methodology for implementing a complete Digital Signal Processing (DSP) system onto a heterogeneous network including Field Programmable Gate Arrays (FPGAs) automatically. The methodology aims to allow design refinement and real time verification at the system level. The DSP application is constructed in the form of a Data Flow Graph (DFG) which provides an entry point to the methodology. The netlist for parts that are mapped onto the FPGA(s) together with the corresponding software and hardware Application Protocol Interface (API) are also generated. Using a set of case studies, we demonstrate that the design and development time can be significantly reduced using the methodology developed.

Semiring induced valuation algebras: Exact and approximate local computation algorithms

Local computation in join trees or acyclic hypertrees has been shown to be linked to a particular algebraic structure, called valuation algebra.There are many models of this algebraic structure ranging from probability theory to numerical analysis, relational databases and various classical and non-classical logics. It turns out that many interesting models of valuation algebras may be derived from semiring valued mappings. In this paper we study how valuation algebras are induced by semirings and how the structure of the valuation algebra is related to the algebraic structure of the semiring. In particular, c-semirings with idempotent multiplication induce idempotent valuation algebras and therefore permit particularly efficient architectures for local computation. Also important are semirings whose multiplicative semigroup is embedded in a union of groups. They induce valuation algebras with a partially defined division. For these valuation algebras, the well-known architectures for Bayesian networks apply. We also extend the general computational framework to allow derivation of bounds and approximations, for when exact computation is not feasible.

The Utility of Fractional Exhaled Nitric Oxide Suppression in the Identification of Nonadherence in Difficult Asthma

Rationale: Nonadherence to inhaled corticosteroid therapy (ICS) is a major contributor to poor control in difficult asthma, yet it is challenging to ascertain. Objectives: Identify a test for nonadherence using fractional exhaled nitric oxide (FENO) suppression after directly observed inhaled corticosteroid (DOICS) treatment. Methods: Difficult asthma patients with an elevated FENO (>45 ppb) were recruited as adherent (ICS prescription filling >80%) or nonadherent (filling <50%). They received 7 days of DOICS (budesonide 1,600 µg) and a test for nonadherence based on changes in FENO was developed. Using this test, clinic patients were prospectively classified as adherent or nonadherent and this was then validated against prescription filling records, prednisolone assay, and concordance interview. Measurements and Main Results: After 7 days of DOICS nonadherent (n = 9) compared with adherent subjects (n = 13) had a greater reduction in FENO to 47 ± 21% versus 79 ± 26% of baseline measurement (P = 0.003), which was also evident after 5 days (P = 0.02) and a FENO test for nonadherence (area under the curve = 0.86; 95% confidence interval, 0.68-1.00) was defined. Prospective validation in 40 subjects found the test identified 13 as nonadherent; eight confirmed nonadherence during interview (three of whom had excellent prescription filling but did not take medication), five denied nonadherence, two had poor inhaler technique (unintentional nonadherence), and one also denied nonadherence to prednisolone despite nonadherent blood level. Twenty-seven participants were adherent on testing, which was confirmed in 21. Five admitted poor ICS adherence but of these, four were adherent with oral steroids and one with omalizumab. Conclusions: FENO suppression after DOICS provides an objective test to distinguish adherent from nonadherent patients with difficult asthma. Clinical trial registered with www.clinicaltrials.gov (NCT 01219036). Copyright © 2012 by the American Thoracic Society.

Algorithms and architectures for high performance recursive filtering

Recently, a number of most significant digit (msd) first bit parallel multipliers for recursive filtering have been reported. However, the design approach which has been used has, in general, been heuristic and consequently, optimality has not always been assured. In this paper, msd first multiply accumulate algorithms are described and important relationships governing the dependencies between latency, number representations, etc are derived. A more systematic approach to designing recursive filters is illustrated by applying the algorithms and associated relationships to the design of cascadable modules for high sample rate IIR filtering and wave digital filtering.

Fast VLSI algorithms for division and square root

Real time digital signal processing demands high performance implementations of division and square root. This can only be achieved by the design of fast and efficient arithmetic algorithms which address practical VLSI architectural design issues. In this paper, new algorithms for division and square root are described. The new schemes are based on pre-scaling the operands and modifying the classical SRT method such that the result digits and the remainders are computed concurrently and the computations in adjacent rows are overlapped. Consequently, their performance exceeds that of the SRT methods. The hardware cost for higher radices is considerably more than that of the SRT methods but for many applications, this is not prohibitive. A system of equations is presented which enables both an analysis of the method for any radix and the parameters of implementations to be easily determined. This is illustrated for the case of radix 2 and radix 4. In addition, a highly regular array architecture combining the division and square root method is described. © 1994 Kluwer Academic Publishers.