Streamlined Global and Local Features Combinator (SGLC) for High Resolution Image Dehazing

Image Dehazing aims to remove atmospheric fog or haze from an image. Although the Dehazing models have evolved a lot in recent years, few have precisely tackled the problem of High-Resolution hazy images. For this kind of image, the model needs to work on a downscaled version of the image or on cropped patches from it. In both cases, the accuracy will drop. This is primarily due to the inherent failure to combine global and local features when the image size increases. The Dehazing model requires global features to understand the general scene peculiarities and the local features to work better with fine and pixel details. In this study, we propose the Streamlined Global and Local Features Combinator (SGLC) to solve these issues and to optimize the application of any Dehazing model to High-Resolution images. The SGLC contains two successive blocks. The first is the Global Features Generator (GFG) which generates the first version of the Dehazed image containing strong global features. The second block is the Local Features Enhancer (LFE) which improves the local feature details inside the previously generated image. When tested on the Uformer architecture for Dehazing, SGLC increased the PSNR metric by a significant margin. Any other model can be incorporated inside the SGLC process to improve its efficiency on High-Resolution input data.Comment: Accepted in CVPR 2023 Workshop

Guided Frequency Loss for Image Restoration

Image Restoration has seen remarkable progress in recent years. Many generative models have been adapted to tackle the known restoration cases of images. However, the interest in benefiting from the frequency domain is not well explored despite its major factor in these particular cases of image synthesis. In this study, we propose the Guided Frequency Loss (GFL), which helps the model to learn in a balanced way the image's frequency content alongside the spatial content. It aggregates three major components that work in parallel to enhance learning efficiency; a Charbonnier component, a Laplacian Pyramid component, and a Gradual Frequency component. We tested GFL on the Super Resolution and the Denoising tasks. We used three different datasets and three different architectures for each of them. We found that the GFL loss improved the PSNR metric in most implemented experiments. Also, it improved the training of the Super Resolution models in both SwinIR and SRGAN. In addition, the utility of the GFL loss increased better on constrained data due to the less stochasticity in the high frequencies' components among samples

Prevalence and risk factors of low back pain among undergraduate students of a sports and physical education institute in Tunisia

Introduction: For obvious reasons, athletes are at greater risk of sustaining a lumber (lower) spine injury due to physical activity. To our knowledge, no previous studies have examined the prevalence of low back pain (LBP) in a Tunisian sports and physical education institute.Aim: To assess the prevalence of LBP in different sports among students studying in a sports and physical education institute in Tunisia, to determine the causes of the injuries, and to propose solutions.Methods: A total of 3,379 boys and 2,579 girls were studied. A retrospective cross-sectional survey was conducted on a group of students aged 18.524.5 years at the Higher Institute of Sport and Physical Education of Sfax to estimate the prevalence of LBP and its relation to the type of sports. Data on age, weight, height, smoking, and the sport in which the student was injured in the low back were collected from the institute health service records from 2005 until 2013.Results: LBP was reported by 879 of the 5,958 study participants (14.8%). The prevalence of LBP was significantly higher (pB0.001) in females (17.6%) than in males (12.5%). LBP prevalence did not differ by body mass index or smoking habit (p0.05). The sports associated with the higher rates of LBP were gymnastics, judo, handball, and volleyball, followed by basketball and athletics.Conclusion: LBP is frequent among undergraduate students of a sports and physical education institute in Tunisia. It is strongly associated with fatigue after the long periods of training in different sports. Gymnastics, judo, handball, and volleyball were identified as high-risk sports for causing LBP.Keywords: low back pain; sports students; sports training; risk factor

Effect of Forest Biomass Pretreatment on Essential Oil Yield and Properties

Essential oils (EOs) are natural and economically valuable aromatic compounds obtained from a variety of crops and trees, including forest trees, which have different therapeutic and biological activities. This project aims to assess the impact of different residual forest biomass pretreatments on the yield and the properties of EOs, including their antibacterial and antioxidant characteristics. Forest biomass from black spruce (BS, Picea mariana Mill.), balsam fir (BF, Abies balsamea), and jack pine (JP, Pinus banksiana Lamb.) was processed mechanically by (i) shredding, (ii) grinding, (iii) pelletizing, and (iv) bundling. EOs were then extracted by hydro- and steam distillation. The densification into bundles was found to improve EOs yield compared to the other residual forest biomass pretreatments. For example, the yield of bundled BF was improved by 68%, 83%, and 93% compared to shredded, ground, and granulated biomass, respectively. The highest yield was obtained when densification into bundles was combined with extraction through hydrodistillation. As for EOs' chemical composition, JP had the highest polyphenol content and consequently the greatest antioxidant activity. EOs derived from BS inhibited the growth of Grampositive Staphylococcus aureus bacteria and Gram-negative Salmonella typhimurium and Escherichia coli bacteria. The densification of forest biomass into bundles did not affect the antioxidant capacity or the antibacterial activity of EOs, thereby preserving both properties. Thus, the pretreatment of forest biomass residue could have an impact on the volume and the transport costs and therefore improve the bioproducts market and the bioeconomy in Canada

License Plate Super-Resolution Using Diffusion Models

In surveillance, accurately recognizing license plates is hindered by their often low quality and small dimensions, compromising recognition precision. Despite advancements in AI-based image super-resolution, methods like Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs) still fall short in enhancing license plate images. This study leverages the cutting-edge diffusion model, which has consistently outperformed other deep learning techniques in image restoration. By training this model using a curated dataset of Saudi license plates, both in low and high resolutions, we discovered the diffusion model's superior efficacy. The method achieves a 12.55\% and 37.32% improvement in Peak Signal-to-Noise Ratio (PSNR) over SwinIR and ESRGAN, respectively. Moreover, our method surpasses these techniques in terms of Structural Similarity Index (SSIM), registering a 4.89% and 17.66% improvement over SwinIR and ESRGAN, respectively. Furthermore, 92% of human evaluators preferred our images over those from other algorithms. In essence, this research presents a pioneering solution for license plate super-resolution, with tangible potential for surveillance systems

HTTU-Net: Hybrid Two Track U-Net for Automatic Brain Tumor Segmentation

Brain cancer is one of the most dominant causes of cancer death; the best way to diagnose and treat brain tumors is to screen early. Magnetic Resonance Imaging (MRI) is commonly used for brain tumor diagnosis; however, it is a challenging problem to achieve higher accuracy and performance, which is a vital problem in most of the previously presented automated medical diagnosis. In this paper, we propose a Hybrid Two-Track U-Net(HTTU-Net) architecture for brain tumor segmentation. This architecture leverages the use of Leaky Relu activation and batch normalization. It includes two tracks; each one has a different number of layers and utilizes a different kernel size. Then, we merge these two tracks to generate the final segmentation. We use the focal loss, and generalized Dice (GDL), loss functions to address the problem of class imbalance. The proposed segmentation method was evaluated on the BraTS’2018 datasets and obtained a mean Dice similarity coefficient of 0.865 for the whole tumor region, 0.808 for the core region and 0.745 for the enhancement region and a median Dice similarity coefficient of 0.883, 0.895, and 0.815 for the whole tumor, core and enhancing region, respectively. The proposed HTTU-Net architecture is sufficient for the segmentation of brain tumors and achieves highly accurate results. Other quantitative and qualitative evaluations are discussed, along with the paper. It confirms that our results are very comparable expert human-level performance and could help experts to decrease the time of diagnostic.This work was supported in part by the Robotics and Internet-of-Things Laboratory of Prince Sultan University, Saudi Arabia, and in part by the National Natural Science Foundation of China under Grant 61375081.info:eu-repo/semantics/publishedVersio

Efecto del extracto de cáscara de granada tunecina sobre la estabilidad oxidativa del aceite de maíz en condiciones de calentamiento

The effect of pomegranate peel extract (PPE) on the oxidative stability of corn oil during heating was studied. Oxidation was followed by determining peroxide value (PV), p-anisidine value (p-AV), free fatty acid value (FFA), conjugated dienes (CD), conjugated trienes hydroperoxides (CT) and the calculated total oxidation value (TOTOX). Polyphenol (TPC) and ortho-diphenol (TOPC) contents as well as the antioxidant activity of each oil sample were evaluated before and after heating. PPE showed a significant inhibitory effect on lipid oxidation. Heating samples for 8 hours supplemented by PPE to a level of 1000 ppm resulted in the highest significant decreases in investigated indices compared to the control and BHT values. It was concluded that the antioxidant activity of PPE delayed oxidation and can be used in the food industry to prevent and reduce lipid deterioration in oil.Se estudió el efecto del extracto de cáscara de granada (ECG) sobre la estabilidad oxidativa del aceite de maíz durante condiciones de calentamiento. La oxidación se siguió mediante la determinación del índice de peróxido (IP), el índice de p-anisidina (p-AV), el índice de acidez (IA), los dienos conjugados (DC), los hidroperóxidos de trienos conjugados (TC) y el valor calculado de la oxidación total (TOTOX). Se evaluó el contenido de polifenoles totales (PT) y de orto-difenoles (o-DF), así como la actividad antioxidante de cada muestra de aceite, antes y después del calentamiento. El ECG mostró un efecto inhibidor significativo sobre la oxidación de lípidos. El calentamiento de las muestras, durante 8 horas suplementadas con ECG a un nivel de 1000 ppm, dio como resultado una significativa disminución de los índices investigados en relación con los valores de control y con BHT. Se concluyó que la actividad antioxidante de los ECG retrasó la oxidación y que se puede utilizar en la industria alimentaria para prevenir y reducir el deterioro de los lípidos del aceite

Lung function profiles and aerobic capacity of adult cigarette and hookah smokers after 12 weeks intermittent training

Introduction: Pulmonary function is compromised in most smokers. Yet it is unknown whether exercise training improves pulmonary function and aerobic capacity in cigarette and hookah smokers and whether these smokers respond in a similar way as do non-smokers.Aim: To evaluate the effects of an interval exercise training program on pulmonary function and aerobic capacity in cigarette and hookah smokers.Methods: Twelve cigarette smokers, 10 hookah smokers, and 11 non-smokers participated in our exercise program. All subjects performed 30 min of interval exercise (2 min of work followed by 1 min of rest) three times a week for 12 weeks at an intensity estimated at 70% of the subject’s maximum aerobic capacity (VO2max). Pulmonary function was measured using spirometry, and maximum aerobic capacity was assessed by maximal exercise testing on a treadmill before the beginning and at the end of the exercise training program.Results: As expected, prior to the exercise intervention, the cigarette and hookah smokers had significantly lower pulmonary function than the non-smokers. The 12-week exercise training program did not significantly affect lung function as assessed by spirometry in the non-smoker group. However, it significantly increased both forced expiratory volume in 1 second and peak expiratory flow (PEF) in the cigarette smoker group, and PEF in the hookah smoker group. Our training program had its most notable impact on the cardiopulmonary system of smokers. In the non-smoker and cigarette smoker groups, the training program significantly improved VO2max (4.4 and 4.7%, respectively), v VO2max (6.7 and 5.6%, respectively), and the recovery index (7.9 and 10.5%, respectively).Conclusions: After 12 weeks of interval training program, the increase of VO2max and the decrease of recovery index and resting heart rate in the smoking subjects indicated better exercise tolerance. Although the intermittent training program altered pulmonary function only partially, both aerobic capacity and life quality were improved. Intermittent training should be advised in the clinical setting for subjects with adverse health behaviors.Keywords: cigarette smokers; hookah smokers; pulmonary function; aerobic capacity; interval trainin

Adaptive fuzzy model-free control for 3D trajectory tracking of quadrotor

This paper presents a novel adaptive control strategy with rejection ability for unmanned aerial vehicles (UAVs), namely fuzzy model-free control (FMFC). It is based on the model-free control (MFC) concept, where the control parameters are tuned online using fuzzy logic. The controller assumes an ultra-local model that can compensate unknown/unmodelled dynamics, uncertainties and external disturbances, ensuring a good robustness level. Moreover, the fuzzy logic system is used to tune online the proportional-derivative terms due to its heuristic aspect. These compensation and adaptation mechanisms allow ensuring good compromise robustness-performance even in the presence of disturbances. Several experiments, using RotorS Gazebo micro aerial vehicle (MAV) simulator, are provided to demonstrate the effectiveness of the proposed controller compared with other techniques. The fuzzy model-free controller shows superior performance without the time-consuming and tedious tuning task

La maladie de cowden a propos d’un cas

La maladie de Cowden est une maladie héréditaire à transmission autosomique dominante caractérisée par des lésions associant des atteintes cutanées constantes et caractéristiques (lésions papuleuses au niveau de la face et des extrémités) et des lésions viscérales inconstantes notamment thyroïdiennes, mammaires, intestinales et rénales à haut risque de dégénérescence. Nous rapportons un cas chez une femme de 30 ans porteuse d’une craniomégalie, de polypes intestinaux, d’un fibroadénome des seins, de lésions papuleuses des gencives et d’un goitre multi-nodulaire. Elle a eu dans notre service une thyroïdectomie totale dont l’analyse anatomopathologique définitive de la pièce a révélé un micro-carcinome vésiculaire du lobe gauche de la thyroïde. Les lésions thyroïdiennes sont habituellement bien limitées, mais devant la multifocalité, le risque accru de récidive et de dégénérescence maligne, une thyroïdectomie totale doit être préconisée.Mots clès : Maladie de Cowden, Cancer de la thyro