Association between mean platelet volume levels and inflammation in SLE patients presented with arthritis

Background: Systemic lupus erythematosus (SLE) may be characterized by periods of remissions and chronic or acute relapses. The complexity of clinical presentation of the SLE patients leads to incorrect evaluation of disease activity. Mean platelet volume (MPV) has been studied as a simple inflammatory marker in several diseases. There is no study in the literature about MPV levels in adult SLE patients with arthritis.Objectives: We aimed to investigate the MPV levels in the SLE population with arthritis during and between activations.Methods: The study consisted of 44 SLE patients with arthritis in activation period (Group 1), the same 44 SLE patients with arthritis in remission period (Group 2) and 44 healthy controls (Group 3). Erythrocyte sedimentation rate (ESR), creactive protein (CRP), white blood cell count, platelet count, and mean platelet volume (MPV) levels were retrospectively recorded from patient files.Results: The mean ages of the SLE subjects were 42 ± 16 years, while the mean ages of controls was 41 ± 17 years. MPV was significantly lower in Group 1(7.66±0.89fL) than in Group 2 (8.61±1.06 fL) and Group 3(8.62±1.11fL) (p<0.0001). The differences between groups reached statistical significance.Conclusions: We suggest that MPV levels decrease in patients with arthritis of SLE activation when compared to the same patients in remission and healthy controls.Key words: Systemic lupus erythematosus, Arthritis, Mean platelet volum

Real-Time Vehicle Accident Recognition from Traffic Video Surveillance using YOLOV8 and OpenCV

The automatic detection of traffic accidents is a significant topic in traffic monitoring systems. It can reduce irresponsible driving behavior, improve emergency response, improve traffic management, and encourage safer driving practices. Computer vision can be a promising technique for automatic accident detection because it provides a reliable, automated, and speedy accident detection system that can improve emergency response times and ultimately save lives. This paper proposed an ensemble model that uses the YOLOv8 approach for efficient and precise event detection. The model framework's robustness is evaluated using YouTube video sequences with various lighting circumstances. The proposed model has been trained using the open-source dataset Crash Car Detection Dataset, and its produced precision, recall, and mAP are 93.8% and 98%, 96.1%, respectively, which is a significant improvement above the prior precision, recall, and mAP figures of 91.3%, 87.6%, and 93.8%. The effectiveness of the proposed approach in real-time traffic surveillance applications is proved by experimental results using actual traffic video data

Asymptotic adaptive methods for multi-scale problems in fluid mechanics

This paper reports on the results of a three-year research effort aimed at investigating and exploiting the role of physically motivated asymptotic analysis in the design of numerical methods for singular limit problems in fluid mechanics. Such problems naturally arise, among others, in combustion, magneto-hydrodynamics and geophysical fluid mechanics. Typically, they are characterized by multiple space and/or time scales and by the disturbing fact that standard computational techniques fail entirely, are unacceptably expensive, or both. The challenge here is to construct numerical methods which are robust, uniformly accurate, and efficient through different asymptotic regimes and over a wide range of relevant applications. Summaries of multiple scales asymptotic analyses for low Mach number flows, magnetohydrodynamics at small Mach and Alfv´en numbers, and of multiple scales atmospheric flows are provided. These reveal singular balances between selected terms in the respective governing equations within the considered flow regimes. These singularities give rise to problems of severe stiffness, stability, or to dynamic range issues in straightforward numerical discretizations. Aformal mathematical framework for the multiple scales asymptotics is then summarized using the example of multiple length scale – single time scale asymptotics for low Mach number flows. The remainder of the paper focuses on the construction of numerical discretizations for the respective full governing equation systems. These discretizations avoid the pitfalls of singular balances by exploiting the asymptotic results. Importantly, the asymptotics are not used here to derive simplified equation systems, which are then solved numerically. Rather, we aim at numerically integrating the full equation sets and at using the asymptotics only to construct discretizations that do not deteriorate as a singular limit is approached. One important ingredient of this strategy is the numerical identification of a singular limit regime given a set of discrete numerical state variables. This problem is addressed in an exemplary fashion for multiple length – single time scale low Mach number flows in one space dimension. The strategy allows a dynamic determination of an instantaneous relevant Mach number, and it can thus be used to drive the appropriate adjustment of the numerical discretizations when the singular limit regime is approached

Oxidation of Alcohols and Activated Alkanes with Lewis Acid-Activated TEMPO

The reactivity of MCl3(η(1)-TEMPO) (M = Fe, 1; Al, 2; TEMPO = 2,2,6,6-tetramethylpiperidine-N-oxyl) with a variety of alcohols, including 3,4-dimethoxybenzyl alcohol, 1-phenyl-2-phenoxyethanol, and 1,2-diphenyl-2-methoxyethanol, was investigated using NMR spectroscopy and mass spectrometry. Complex 1 was effective in cleanly converting these substrates to the corresponding aldehyde or ketone. Complex 2 was also able to oxidize these substrates; however, in a few instances the products of overoxidation were also observed. Oxidation of activated alkanes, such as xanthene, by 1 or 2 suggests that the reactions proceed via an initial 1-electron concerted proton-electron transfer (CPET) event. Finally, reaction of TEMPO with FeBr3 in Et2O results in the formation of a mixture of FeBr3(η(1)-TEMPOH) (23) and [FeBr2(η(1)-TEMPOH)]2(μ-O) (24), via oxidation of the solvent, Et2O