Impulse oscillometry may be of value in detecting early manifestations of COPD

SummaryBackgroundSpirometry is used to diagnose chronic obstructive pulmonary disease (COPD). The Impulse oscillometry system (IOS) allows determination of respiratory impedance indices, which might be of potential value in early COPD, although previous experience is limited. We examined pulmonary resistance and reactance measured by IOS in subjects with or without self-reported chronic bronchitis or emphysema or COPD (Q+ or Q−) and subjects with or without COPD diagnosed according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria (G+ or G−).MethodsFrom a previous population-based study 450 subjects were examined with spirometry and IOS and answered a questionnaire on respiratory symptoms and diseases.ResultsSeventy-seven subjects were Q+, of whom 34 also were G+. Q+/G− subjects (n = 43) reported respiratory symptoms more frequently (35–40% vs 8–14%) but had higher FEV1 (100% vs 87%) than Q−/G+ subjects (n = 90), p < 0.05 for both comparisons. Q+ subjects had higher pulmonary resistance and lower pulmonary reactance than Q− subjects (p < 0.01 for all comparisons). The same pattern was seen both in G+ subjects ((Q+/Q−) R5 0.39/0.32, R5–R20 0.10/0.07, X5 0.13/0.09, AX 0.55/0.27, p < 0.05 for all) and G− subjects ((Q+/Q−) R5 0.35/0.29, R5–R20 0.08/0.06, X5 0.10/0.08, AX 0.31/0.19 p < 0.05 for all) except for R20 (adjusted for gender and age).ConclusionsSelf-reported chronic bronchitis or emphysema or COPD was associated with higher pulmonary resistance and lower pulmonary reactance measured by IOS, both among subjects with and without COPD according to GOLD criteria. IOS may have the potential to detect pathology associated with COPD earlier than spirometry

Lobar Dementia due to Extreme Widening of Virchow-Robin Spaces in One Hemisphere

Widened perivascular spaces known as Virchow-Robin spaces (VRS) are often seen on MRI and are usually incidental findings. It is unclear if enlarged VRS can be associated with neurological deficits. In this report, we describe a case of lobar dementia associated with unusual VRS widening in one cerebral hemisphere. A 77-year-old woman, seen at a memory clinic, presented with progressive cognitive decline, left hemianopsia, and mild pyramidal signs on the left side. On MRI, unusually wide VRS were visible, predominantly in the right centrum semiovale and the right temporo-occipital white matter. The clinical syndrome was consistent with the extent and location of the abnormally dilated VRS. The high MR signal in white matter bridges between the VRS suggested parenchymal damage, possibly representing gliotic white matter. No evidence for another etiology was found on cerebral MRI and rCBF SPECT. As a conclusion, enlarged VRS in one cerebral hemisphere may be associated with cognitive change and neurological deficits

Data-Driven Audio Feature Space Clustering for Automatic Sound Recognition in Radio Broadcast News

This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License. Further distribution of this work is permitted, provided the original work is properly cited. T. Theodorou, I. Mpoas, A. Lazaridis, N. Fakotakis, 'Data-Driven Audio Feature Space Clustering for Automatic Sound Recognition in Radio Broadcast News', International Journal on Artificial Intelligence Tools, Vol. 26 (2), April 2017, 1750005 (13 pages), DOI: 10.1142/S021821301750005. © The Author(s).In this paper we describe an automatic sound recognition scheme for radio broadcast news based on principal component clustering with respect to the discrimination ability of the principal components. Specifically, streams of broadcast news transmissions, labeled based on the audio event, are decomposed using a large set of audio descriptors and project into the principal component space. A data-driven algorithm clusters the relevance of the components. The component subspaces are used by sound type classifier. This methodology showed that the k-nearest neighbor and the artificial intelligent network provide good results. Also, this methodology showed that discarding unnecessary dimension works in favor on the outcome, as it hardly deteriorates the effectiveness of the algorithms.Peer reviewe

Speech Emotion Recognition Considering Local Dynamic Features

Recently, increasing attention has been directed to the study of the speech emotion recognition, in which global acoustic features of an utterance are mostly used to eliminate the content differences. However, the expression of speech emotion is a dynamic process, which is reflected through dynamic durations, energies, and some other prosodic information when one speaks. In this paper, a novel local dynamic pitch probability distribution feature, which is obtained by drawing the histogram, is proposed to improve the accuracy of speech emotion recognition. Compared with most of the previous works using global features, the proposed method takes advantage of the local dynamic information conveyed by the emotional speech. Several experiments on Berlin Database of Emotional Speech are conducted to verify the effectiveness of the proposed method. The experimental results demonstrate that the local dynamic information obtained with the proposed method is more effective for speech emotion recognition than the traditional global features.Comment: 10 pages, 3 figures, accepted by ISSP 201

Учет оплаты труда на примере ООО «Клининговая компания Моррис»

В работе рассмотрены теоретические аспекты начисления заработной платы, начисления и удержания. Приведена практическая реализация на примере ООО. Выявлены ошибки и предложены рекомендации предприятию.The paper considers the theoretical aspects of payroll, accrual and retention. The practical implementation of the example of LLC. Errors were identified and recommendations made to the enterprise

Airspace Dimension Assessment (AiDA) by inhaled nanoparticles: benchmarking with hyperpolarised 129Xe diffusion-weighted lung MRI

Enlargements of distal airspaces can indicate pathological changes in the lung, but accessible and precise techniques able to measure these regions are lacking. Airspace Dimension Assessment with inhaled nanoparticles (AiDA) is a new method developed for in vivo measurement of distal airspace dimensions. The aim of this study was to benchmark the AiDA method against quantitative measurements of distal airspaces from hyperpolarised 129Xe diffusion-weighted (DW)-lung magnetic resonance imaging (MRI). AiDA and 129Xe DW-MRI measurements were performed in 23 healthy volunteers who spanned an age range of 23–70 years. The relationship between the 129Xe DW-MRI and AiDA metrics was tested using Spearman’s rank correlation coefficient. Significant correlations were observed between AiDA distal airspace radius (rAiDA) and mean 129Xe apparent diffusion coefficient (ADC) (p < 0.005), distributed diffusivity coefficient (DDC) (p < 0.001) and distal airspace dimension (LmD) (p < 0.001). A mean bias of − 1.2 µm towards rAiDA was observed between 129Xe LmD and rAiDA, indicating that rAiDA is a measure of distal airspace dimension. The AiDA R0 intercept correlated with MRI 129Xe α (p = 0.02), a marker of distal airspace heterogeneity. This study demonstrates that AiDA has potential to characterize the distal airspace microstructures and may serve as an alternative method for clinical examination of the lungs