Proton magnetic resonance spectroscopy of brain in obstructive sleep apnea in Egyptian subjects

AbstractObjectiveThe overall objective of this work is to study the cerebral metabolic changes in patients with OSA and to determine the usefulness of MRS as an objective method for evaluation of CNS impairment in these patients.Materials and methodsThis study included two groups; group1 fifteen (15) patients diagnosed with obstructive sleep apnea hypopnea syndrome, and group 2 ten (10) healthy volunteers of comparable age.Magnetic resonance spectra were obtained from frontal periventricular white matter.For all subjects, height, body weight, and BMI were assessed. Waist and hip circumference were measured and waist/hip ratio (W/H ratio) was calculated.Overnight polysomnography (PSG) to identify sleep apnea was done. Daytime sleepiness was evaluated by the Epworth Sleepiness Scale. Symptoms of anxiety and depression were measured with the Hospital Anxiety and Depression Scale (HADS).ResultsN-acetylaspartate-to-creatine (NAA/Cr) and choline-to-creatine (Cho/Cr) ratios were significantly lower in the frontal white matter of obstructive sleep apnea patients when compared to controls. Absolute concentrations of N-acetylaspartate (NAA) and choline (Cho) were also significantly reduced in the frontal white matter of patients with sleep apnea. Statistically significant negative correlations existed between AHI and metabolites concentrations and ratios in patients with OSAHS. Significant positive correlations existed in patients with OSAHS between Hospital and depression scale for depression (HAD-D) and AHI (r=0.764, p=0.001), ODI (r=0.571, p=0.026), and ESS (r=0.644, p=0.010), respectively. Significant positive correlations existed in patients with OSAHS between Hospital and depression scale for anxiety (HAD-A) and AHI (r=0.753, p=0.001), and ESS (r=0.537, p=0.039), respectively. Multivariate Linear regression model of factors predictive showed AHI as the main predictor factor for choline to creatine ratio in patients with OSAHS with t=5.180, at p<0.001.ConclusionOSA patients show abnormal brain metabolites related to neuronal damage due to intermittent chronic hypoxemia. Anxious and depressive symptoms are highly prevalent in patients with severe untreated OSAS. The severity of depressive and anxious symptoms may be related to excessive daytime sleepiness and to nocturnal hypoxemia both of which are strongly correlated to brain metabolites. AHI seems to be the main predictor factor for choline to creatine ratio in patients with OSAHS

Transition Experiments on Blunt Bodies with Isolated Roughness Elements in Hypersonic Free Flight

Smooth titanium hemispheres with isolated three-dimensional (3D) surface roughness elements were flown in the NASA Ames hypersonic ballistic range through quiescent CO2 and air environments. Global surface intensity (temperature) distributions were optically measured and thermal wakes behind individual roughness elements were analyzed to define tripping effectiveness. Real-gas Navier-Stokes calculations of model flowfields, including laminar boundary layer development in these flowfields, were conducted predict key dimensionless parameters used to correlate transition on blunt bodies in hypersonic flow. For isolated roughness elements totally immersed within the laminar boundary layer, critical roughness Reynolds numbers for flights in air were found to be higher than those measured for flights in CO2, i.e., it was easier to trip the CO2 boundary layer to turbulence. Tripping effectiveness was found to be dependent on trip location within the subsonic region of the blunt body flowfield, with effective tripping being most difficult to achieve for elements positioned closest to the stagnation point. Direct comparisons of critical roughness Reynolds numbers for 3D isolated versus 3D distributed roughness elements for flights in air showed that distributed roughness patterns were significantly more effective at tripping the blunt body laminar boundary layer to turbulence

Pengaruh Keefektifan Pengendalian Internal, Kesesuaian Kompensasi, Moralitas Aparat dan Asimetri Informasi terhadap Kecenderungan Kecurangan Akuntansi

This study aims to examine the effect of Influence Effectiveness of Internal Control, Compliance Compensation, Morality Apparatus and Information Asymmetry on Accounting Fraud Trends. This research was conducted by using descriptive method survey. Collecting data in this study are primary data obtained from questionnaires distributed directly to the respondents. Sample selection technique is purposive sampling. The sample used in this study were 61 respondents who served as the fourth echelon in the regional work units (SKPD) in Siak Sri Indrapura. Management and analysis of data using multiple linear regression analysis with the help of software SPSS version 20 (Statistical Product and Service Solution). Hypothesis testing results indicate that effectiveness of internal control, suitability of the compensation and apparatus morality negative effect on the tendency of accounting fraud and information asymmetry positive effect on the tendency of accounting fraud. The coefficient of determination in this study was 62.2%, while 37.8% is influenced by other variables.Keywords: Internal Control, Compensation, Morality, Information and Accounting Frau

Transition Experiments on Blunt Bodies with Distributed Roughness in Hypersonic Free Flight in Carbon Dioxide

Blunt-body geometries were flown through carbon dioxide in the NASA Ames Hypervelocity Free Flight Aerodynamic Facility to investigate the influence of distributed surface roughness on transition to turbulence in CO2-dominated atmospheres, such as those of Mars and Venus. Tests were also performed in air for direct comparison with archival results. Models of hemispherical and spherically-blunted large-angle conical geometries were flown at speeds between 2.8 km/s and 5.1 km/s and freestream pressures between 50 Torr and 228 Torr. Transition fronts were determined from global surface heat flux distributions measured using thermal imaging techniques. Distributed surface roughness was produced by grit-blasting the model surfaces. Real-gas Navier-Stokes solutions were used to calculate non-dimensional correlating parameters at the measured transition onset locations. Transition-onset locations correlated well with a constant roughness Reynolds number based on the mean roughness element height. The critical roughness Reynolds number for transition onset determined for flight in CO2 was 223 +/- 25%. This mean value is lower than the critical value of 250 +/- 20% previously-established from tests conducted in air, but within the bounds of the expected measurement uncertainty

A Hybrid COVID-19 Detection Model Using an Improved Marine Predators Algorithm and a Ranking-Based Diversity Reduction Strategy

Many countries are challenged by the medical resources required for COVID-19 detection which necessitates the development of a low-cost, rapid tool to detect and diagnose the virus effectively for a large numbers of tests. Although a chest X-Ray scan is a useful candidate tool the images generated by the scans must be analyzed accurately and quickly if large numbers of tests are to be processed. COVID-19 causes bilateral pulmonary parenchymal ground-glass and consolidative pulmonary opacities, sometimes with a rounded morphology and a peripheral lung distribution. In this work, we aim to extract rapidly from chest X-Ray images the similar small regions that may contain the identifying features of COVID-19. This paper therefore proposes a hybrid COVID-19 detection model based on an improved marine predators algorithm (IMPA) for X-Ray image segmentation. The ranking-based diversity reduction (RDR) strategy is used to enhance the performance of the IMPA to reach better solutions in fewer iterations. RDR works on finding the particles that couldn't find better solutions within a consecutive number of iterations, and then moving those particles towards the best solutions so far. The performance of IMPA has been validated on nine chest X-Ray images with threshold levels between 10 and 100 and compared with five state-of-art algorithms: equilibrium optimizer (EO), whale optimization algorithm (WOA), sine cosine algorithm (SCA), Harris-hawks algorithm (HHA), and salp swarm algorithms (SSA). The experimental results demonstrate that the proposed hybrid model outperforms all other algorithms for a range of metrics. In addition, the performance of our proposed model was convergent on all numbers of thresholds level in the Structured Similarity Index Metric (SSIM) and Universal Quality Index (UQI) metrics.</p

An Efficient Marine Predators Algorithm for Solving Multi-Objective Optimization Problems:Analysis and Validations

Recently, a new strong optimization algorithm called marine predators algorithm (MPA) has been proposed for tackling the single-objective optimization problems and could dramatically fulfill good outcomes in comparison to the other compared algorithms. Those dramatic outcomes, in addition to our recently-proposed strategies for helping meta-heuristic algorithms in fulfilling better outcomes for the multi-objective optimization problems, motivate us to make a comprehensive study to see the performance of MPA alone and with those strategies for those optimization problems. Specifically, This paper proposes four variants of the marine predators' algorithm (MPA) for solving multi-objective optimization problems. The first version, called the multi-objective marine predators' algorithm (MMPA) is based on the behavior of marine predators in finding their prey. In the second version, a novel strategy called dominance strategy-based exploration-exploitation (DSEE) recently-proposed is effectively incorporated with MMPA to relate the exploration and exploitation phase of MPA to the dominance of the solutions - this version is called M-MMPA. DSEE counts the number of dominated solutions for each solution - the solutions with high dominance undergo an exploitation phase; the others with small dominance undergo the exploration phase. The third version integrates M-MMPA with a novel strategy called Gaussian-based mutation, which uses the Gaussian distribution-based exploration and exploitation strategy to search for the optimal solution. The fourth version uses the Nelder-Mead simplex method with M-MMPA (M-MMPA-NMM) at the start of the optimization process to construct a front of the non-dominated solutions that will help M-MMPA to find more good solutions. The effectiveness of the four versions is validated on a large set of theoretical and practical problems. For all the cases, the proposed algorithm and its variants are shown to be superior to a number of well-known multi-objective optimization algorithms. </p

A simple and effective approach for tackling the permutation flow shop scheduling problem

In this research, a new approach for tackling the permutation flow shop scheduling problem (PFSSP) is proposed. This algorithm is based on the steps of the elitism continuous genetic algorithm improved by two strategies and used the largest rank value (LRV) rule to transform the continuous values into discrete ones for enabling of solving the combinatorial PFSSP. The first strategy is combining the arithmetic crossover with the uniform crossover to give the algorithm a high capability on exploitation in addition to reducing stuck into local minima. The second one is re-initializing an individual selected randomly from the population to increase the exploration for avoiding stuck into local minima. Afterward, those two strategies are combined with the proposed algorithm to produce an improved one known as the improved efficient genetic algorithm (IEGA). To increase the exploitation capability of the IEGA, it is hybridized a local search strategy in a version abbreviated as HIEGA. HIEGA and IEGA are validated on three common benchmarks and compared with a number of well-known robust evolutionary and meta-heuristic algorithms to check their efficacy. The experimental results show that HIEGA and IEGA are competitive with others for the datasets incorporated in the comparison, such as Carlier, Reeves, and Heller.</p

Microscale 3-D capacitance tomography with a CMOS sensor array

Electrical capacitance tomography (ECT) is a non-optical imaging technique in which a map of the interior permittivity of a volume is estimated by making capacitance measurements at its boundary and solving an inverse problem. While previous ECT demonstrations have often been at centimeter scales, ECT is not limited to macroscopic systems. In this paper, we demonstrate ECT imaging of polymer microspheres and bacterial biofilms using a CMOS microelectrode array, achieving spatial resolution of 10 microns. Additionally, we propose a deep learning architecture and an improved multi-objective training scheme for reconstructing out-of-plane permittivity maps from the sensor measurements. Experimental results show that the proposed approach is able to resolve microscopic 3-D structures, achieving 91.5% prediction accuracy on the microsphere dataset and 82.7% on the biofilm dataset, including an average of 4.6% improvement over baseline computational methods.1019304.01 - Burroughs Wellcome Fund; 000000000000000000000000000000000000000000000000000000001612 - Brown UniversityFirst author draf