Abstract This work presents investigation of chemical composition and antioxidant activity of ethanolic extracts of leaves with flowers and berries prepared by ultrasound and Soxhlet extractions of Crataegus monogyna from Bosnia and Herzegovina. Total phenolic, flavonoid, and anthocyanin contents were measured by spectrophotometric methods. The sample of leaves with flowers extracted by Soxhlet extraction was the richest in the content of total phenolic compounds (14.43 mg GAE/g DW) and total flavonoids (2.22 mg QE/g DW). Same extract showed the best antioxidant activity with an IC50 value of 0.71 mg/mL for DPPH and 0.38 mg/mL for ABTS assay, as well as the highest content of gallic acid, caffeic acid, and hyperoside 0.04 mg GAE/g DW, 0.60 mg CA/g DW and 2.61 mg HYP/g DW, respectively, determined by HPLC-ED. Vitexin was not detected. The extract of berries obtained by ultrasound extraction had the highest amount of total anthocyanins (1.69 mg/100 g DW). Graphical Abstract

Visual impairment can occur in different periods of life, and each person reacts differently in a way that corresponds to their personality, abilities, goals, as well as the life situation in which they find themselves. The aim of this research paper was to show, according to the available literature, the impact of individual educational-rehabilitation treatment on visual perception in students with visual impairment. The sample of respondents included a student, male, aged 9 years, diagnosed with nystagmus, amblyopia, and astigmatism. The student was included in an educational-rehabilitation program in order to improve his visual functioning. For the purpose of assessment and evaluation, the Beery-Buktenica Developmental Test of Visual-Motor Integration (VMI) fifth edition was used, which is intended for the assessment of visual-motor integration, visual perception, and motor coordination. An initial and final assessment was conducted with the student, and the Visual Perception subtest, consisting of 30 tasks, was used for the same. After the initial assessment, an individual educational-rehabilitation treatment was carried out for 2 months. The research data were processed by frequency analysis. On the basis of statistical processing and data analysis, the results showed an improvement in the area of visual perception, thereby confirming the need to implement an educational-rehabilitation program for a student with visual impairment.Keywords: visual perception,visual impairment, individual educational-rehabilitation program.

The targeted compounds in this research, resveratrol analogs 1–14, were synthesized as mixtures of isomers by the Wittig reaction using heterocyclic triphenylphosphonium salts and various benzaldehydes. The planned compounds were those possessing the trans-configuration as the biologically active trans-resveratrol. The pure isomers were obtained by repeated column chromatography in various isolated yields depending on the heteroaromatic ring. It was found that butyrylcholinesterase (BChE) was more sensitive to the heteroaromatic resveratrol analogs than acetylcholinesterase (AChE), except for 6, the methylated thiophene derivative with chlorine, which showed equal inhibition toward both enzymes. Compounds 5 and 8 achieved the highest BChE inhibition with IC50 values of 22.9 and 24.8 μM, respectively. The same as with AChE and BChE, methylated thiophene subunits of resveratrol analogs showed better enzyme inhibition than unmethylated ones. Two antioxidant spectrophotometric methods, DPPH and CUPRAC, were applied to determine the antioxidant potential of new heteroaromatic resveratrol analogs. The molecular docking of these compounds was conducted to visualize the ligand-active site complexes’ structure and identify the non-covalent interactions responsible for the complex’s stability, which influence the inhibitory potential. As ADME properties are crucial in developing drug product formulations, they have also been addressed in this work. The potential genotoxicity is evaluated by in silico studies for all compounds synthesized.

This research explores into the utilization of synthetic data within image classification tasks and evaluates its efficiency in comparison to the utilization of real data. To facilitate this investigation, we employ the CIFAKE dataset, comprising the well-established CIFAR10 dataset and an equivalent number of images synthetically generated using the Latent Diffusion Model (LDM). The increasing demand for diverse and abundant labeled datasets has prompted the emergence of synthetic data as a potential solution to address data scarcity. Within this study, we scrutinize the performance of image classification models trained on both real and synthetic datasets. To ensure a comprehensive evaluation, we alternately apply test data across different models. Our analysis encompasses diverse factors, including classification accuracy, generalization capabilities, and robustness in various scenarios. The findings provide valuable insights into the efficacy of synthetic data as a viable alternative or complement to real data in the realm of image classification.

Artificial intelligence, Machine Learning, and Deep Learning are increasingly making significant contributions to the field of medicine. Individual patient conditions, disease localization, and various influencing factors underscore the complexity of disease diagnosis and treatment planning. Introducing new technologies can revolutionize medical diagnostics, facilitating swift and accurate assessments. Among the noninvasive diagnostic methods, Magnetic Resonance Imaging (MRI) stands out, particularly in tumor diagnosis. UNet, renowned for its effectiveness in medical image analysis, serves as a robust model for semantic segmentation, as does DeepLabV3+. However, these models are inherently complex, and their inference process can be time-consuming. By leveraging the OpenVINO toolkit, the inference process is significantly reduced. In this study, nearly a 2-fold acceleration is achieved in inference time with the DeepLabV3+ model and a roughly 1.2-fold improvement with the UNet model on CPU. Moreover, when employing GPU with FP16 precision, the acceleration reached almost 2.5fold for UNet and nearly 3-fold for DeepLabV3+, showcasing the substantial performance enhancements attainable through optimized hardware utilization.

Noise removal in image processing and computer vision is a crucial preprocessing step employing a spectrum of techniques. In recent years, autoencoders exhibit remarkable efficacy in mapping noisy images to clean counterparts, capturing intricate relationships for effective noise removal. Motivated by the challenges posed by noise in real-world images, this research focuses on the denoising preprocessing step, crucial for tasks like object detection and segmentation. The study explores the application of autoencoders in removing artificially added noise from images within the MNIST dataset. The MNIST dataset’s simplicity and historical significance facilitate focused examinations on specific aspects, such as the impact of different types and levels of noise. The efficacy of autoencoders for noise removal is assessed through the evaluation of results using various metrics, including SSIM, PSNR, MSE, and RMSE. In one remarkable instance, the reconstruction process achieved an impressive peak SSIM score of 99.06%, showcasing the efficacy of the method in preserving image fidelity despite the challenging presence of noise. This comprehensive analysis provides valuable insights into the performance and effectiveness of autoencoders in the context of noise reduction in various domains.

Background/Objectives: The aim of this study was to evaluate brain metabolism using MR spectroscopy (MRS) after recovery from Coronavirus disease (COVID-19) and to test the impact of disease severity on brain metabolites. Methods: We performed MRS on 81 individuals (45 males, 36 females, aged 40–60), who had normal MRI findings and had recovered from COVID-19, classifying them into mild (17), moderate (36), and severe (28) groups based on disease severity during the acute phase. The study employed two-dimensional spectroscopic imaging above the corpus callosum, focusing on choline (Cho), creatine (Cr), and N-acetylaspartate (NAA). We analyzed Cho/Cr and NAA/Cr ratios as well as absolute concentrations using water as an internal reference. Results: Results indicated that the Cho/Cr ratio was higher with increasing disease severity, while absolute Cho and NAA/Cr ratios showed no significant differences across the groups. Notably, absolute Cr and NAA levels were significantly lower in patients with severe disease. Conclusions: These findings suggest that the severity of COVID-19 during the acute phase is associated with significant changes in brain metabolism, marked by an increase in Cho/Cr ratios and a reduction in Cr and NAA levels, reflecting substantial metabolic alterations post-recovery.

Abstract Let S be a groupoid (magma) with zero 0, and let R=⊕s∈SRs be a contracted S-graded ring, that is, an S-graded ring with R0=0. By G(HR) we denote the undirected power graph of a multiplicative subsemigroup HR=∪s∈SRs of R, and by G*(HR)a graph obtained from G(HR) by removing 0 and its incident edges. If Re is a nonzero ring component of R, then G*(Re) denotes a subgraph of G*(HR), induced by Re*. In this paper we address a problem raised in [Abawajy, J., Kelarev, A., Chowdhury, M.: Power Graphs: A Survey. Electron. J. Graph Theory Appl. 1(2), 125–147 (2013)]. Namely, let S be torsion-free, that is, sn=tn implies s = t for all s, t∈S, and all positive integers n, and let S be 0-cancellative, that is, for all s, t, u∈S,su=tu≠0 implies s=t, and us=ut≠0 implies s=t. Also, let R be semisimple Artinian. We prove that if G*(Re) is connected for every nonzero ring component Re of R, then the connected components of G*(HR) are precisely the graphs G*(Re).

In this case report, we describe the diagnostic modality of sinus of Valsalva aneurysm (SOVA) in combination with congenital cardiac defect, aortic valve involvement, and conduction abnormality in a 19-year-old patient. Aim of article was to understand the importance of clinicians being cautious about SOVA presenting in young patients, despite cases being rare, and that SOVA requires a thorough SOVA diagnostic approach. We further provide a review of literature highlighting and comparing the treatment options for both unruptured and ruptured SOVAs. The patient presented for examination due to tachycardia and palpitations. A murmur was heard, and the patient was found to have an atrioventricular nodal reentry tachycardia. Echocardiographic evaluation, magnetic resonance imaging, and computed tomography angiography confirmed an aneurysmally dilated aortic root, aortic regurgitation, and ventricular septal defect. Surgical intervention was indicated; however, the patient refused to undergo surgery.