Generating a Performance Stochastic Model from UML Specifications

Since its initiation by Connie Smith, the process of Software Performance Engineering (SPE) is becoming a growing concern. The idea is to bring performance evaluation into the software design process. This suitable methodology allows software designers to determine the performance of software during design. Several approaches have been proposed to provide such techniques. Some of them propose to derive from a UML (Unified Modeling Language) model a performance model such as Stochastic Petri Net (SPN) or Stochastic process Algebra (SPA) models. Our work belongs to the same category. We propose to derive from a UML model a Stochastic Automata Network (SAN) in order to obtain performance predictions. Our approach is more flexible due to the SAN modularity and its high resemblance to UML' state-chart diagram

Deep pain sensitivity is correlated with oral-health-related quality of life but not with prosthetic factors in complete denture wearers

Low pressure Pain Threshold (PPT) is considered a risk factor for Temporomandibular Disorders (TMD) and is influenced by psychological variables. Objectives To correlate deep pain sensitivity of masticatory muscles with prosthetic factors and Oral-Health-Related Quality of Life (OHRQoL) in completely edentulous subjects. Material and Methods A total of 29 complete denture wearers were recruited. The variables were: a) Pressure Pain Threshold (PPT) of the masseter and temporalis; b) retention, stability, and tooth wear of dentures; c) Vertical Dimension of Occlusion (VDO); d) Oral Health Impact Profile (OHIP) adapted to orofacial pain. The Kolmogorov-Smirnov test, the Pearson Product-Moment correlation coefficient, the Spearman Rank correlation coefficient, the Point-Biserial correlation coefficient, and the Bonferroni correction (α=1%) were applied to the data. Results The mean age (standard deviation) of the participants was of 70.1 years (9.5) and 82% of them were females. There were no significant correlations with prosthetic factors, but significant negative correlations were found between the OHIP and the PPT of the anterior temporalis (r=-0.50, 95% CI-0.73 to 0.17, p=0.005). Discussion The deep pain sensitivity of masticatory muscles in complete dentures wearers is associated with OHRQoL, but not with prosthetic factors

Simcluster: clustering enumeration gene expression data on the simplex space

Transcript enumeration methods such as SAGE, MPSS, and sequencing-by-synthesis EST "digital northern", are important high-throughput techniques for digital gene expression measurement. As other counting or voting processes, these measurements constitute compositional data exhibiting properties particular to the simplex space where the summation of the components is constrained. These properties are not present on regular Euclidean spaces, on which hybridization-based microarray data is often modeled. Therefore, pattern recognition methods commonly used for microarray data analysis may be non-informative for the data generated by transcript enumeration techniques since they ignore certain fundamental properties of this space.

Here we present a software tool, Simcluster, designed to perform clustering analysis for data on the simplex space. We present Simcluster as a stand-alone command-line C package and as a user-friendly on-line tool. Both versions are available at: http://xerad.systemsbiology.net/simcluster.

Simcluster is designed in accordance with a well-established mathematical framework for compositional data analysis, which provides principled procedures for dealing with the simplex space, and is thus applicable in a number of contexts, including enumeration-based gene expression data

Optimizing NV magnetometry for Magnetoneurography and Magnetomyography applications

Magnetometers based on color centers in diamond are setting new frontiers for sensing capabilities due to their combined extraordinary performances in sensitivity, bandwidth, dynamic range, and spatial resolution, with stable operability in a wide range of conditions ranging from room to low temperatures. This has allowed for its wide range of applications, from biology and chemical studies to industrial applications. Among the many, sensing of bio-magnetic fields from muscular and neurophysiology has been one of the most attractive applications for NV magnetometry due to its compact and proximal sensing capability. Although SQUID magnetometers and optically pumped magnetometers (OPM) have made huge progress in Magnetomyography (MMG) and Magnetoneurography (MNG), exploring the same with NV magnetometry is scant at best. Given the room temperature operability and gradiometric applications of the NV magnetometer, it could be highly sensitive in the pT/Hz-range even without magnetic shielding, bringing it close to industrial applications. The presented work here elaborates on the performance metrics of these magnetometers to the state-of-the-art techniques by analyzing the sensitivity, dynamic range, and bandwidth, and discusses the potential benefits of using NV magnetometers for MMG and MNG applications

Eficácia do tratamento empírico da prostatite crônica na redução do PSA em pacientes com PSA 4NG/ML

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Protocolos de encaminhamento para genética médica

Telemedicin