# University Ibn Zohr - Agadir

Recent publications
Sign language is the native form of expression used by deaf people in the world. With the recognition techniques applied to sign language, a significant need for developing tools to facilitate the accessibility of information to the deaf public has arisen. Little work deals with recognizing Moroccan sign language (MoSL) for the Moroccan deaf community. In this paper, a deep learning architecture is presented to be used to recognize MoSL signs. The proposed system uses 3D convolution neural networks to describe effectively video sequences containing Moroccan signs. Experiments showed that the system is able reliably to recognize Moroccan word signs, with 99.60% of accuracy.
Background The implementation of coronavirus disease of 2019 (COVID-19) lockdown has affected the daily practices of subjects with chronic diseases such as diabetes and caused negative impact on their lifestyle and habits such as physical activity, dietary habits and accessibility to medications. Diabetic people are considered the most vulnerable groups to COVID-19, and the lockdown measure has disturbed the diabetes self-management. In our study, we aimed to assess, for the first time at the regional level (Souss Massa Region), the COVID-19 lockdown impact on HbA1c levels in patients with type 1 diabetes (T1D) and type 2 diabetes (T2D). We carried out a cross-sectional quantitative analysis at the health center of the industrial district in Agadir City. Results We found a significant improvement in post-lockdown mean ± SD HbA1c in 150 subjects suffering from T1D and T2D; p = 0.005). Our analysis revealed a significant association of HbA1c deviation with educational level and medical coverage ( p = 0.01). No significant association was detected between HbA1c deviation and age, gender, weight, height, current BMI status, fasting blood sugar, family history, urban or rural areas, marital status, professional activity, socioeconomic income, type of diabetes, dietary, comorbidities, diabetic complications, housing, adherence to the dietary recommendations, physical activity, medical appointments, stopping medication, self-monitoring, fasting and anxiety about getting COVID-19. Conclusions COVID-19 lockdown had no deleterious effect on HbA1c levels in Moroccan patients with T1D and T2D.
Background Renal lesion is a very frequent location of tuberculosis disease, the diagnosis of which is often difficult and delayed due to its atypical clinical presentations, especially in its pseudo-tumoral form. Case presentation Patient of 54 year old was referred after a kidney mass was found on an abdominal ultrasound. In addition, the patient reported the notion of minimal intermittent low back pain with weight loss. On computed tomography, it was a nodular lesion of the superior pole of the right kidney, and it has a heterogeneous density and a suspicious appearance. A total nephrectomy was performed by subcostal incision. Pathological examination of the specimen revealed the presence of diffuse gigantocellular granulomas with caseous necrosis suggestive of renal tuberculosis. Conclusion Despite the rarity of this form, renal tuberculosis should always be thought in order to avoid radical treatment.
We study the stochastic control-stopping problem when the data are path-dependent and of polynomial growth. The approach is based on backward stochastic differential equations (BSDEs for short). The problem turns into the study of a specific reflected BSDE with a stochastic Lipschitz coefficient for which we show existence and uniqueness of the solution. We then establish its relationship with the value function of the control-stopping problem. The optimal strategy is exhibited. Finally in the Markovian framework we prove that the value function is the unique viscosity solution of the associated Hamilton-Jacobi-Bellman equation.
Tracheobronchomegaly, or Mounier-Kuhn syndrome, is a clinical and radiological entity characterized by marked dilatation of the trachea and bronchi as a result of severe atrophy of the elastic fibers, with thinning of the muscularis, and the formation of diverticula between the cartilaginous rings. The etiopathogenesis is uncertain and may be congenital or acquired. The clinical signs are not specific and are frequently revealed by recurrent respiratory infections and chronic cough. The diagnosis of Mounier-Kuhn syndrome is based on well-documented measurements of the trachea and main bronchi performed on a chest computed tomography scan. The management of patients is based on symptomatic treatment and may require, in severe cases, the use of endoscopic treatment by stent placement or surgical tracheobronchoplasty. We present a case of a 59yearold patient with recurrent respiratory infections that required several hospitalizations. Diagnosed with Mounier Kuhn syndrome, the thoracic computed tomography scan demonstrated a dilated trachea until the bifurcation and focal points of bronchial dilatation. Bronchoscopic examination showed a dilated and deformed trachea with the presence of diverticula on the tracheal anterior wall. The diameter of the trachea was reduced by more than 50% during expiration and coughing. For this reason, Mounier-Kuhn syndrome should be considered in cases of recurrent respiratory infection or persistent respiratory symptoms.
Climate change is expected to exacerbate drought conditions over many global regions. However, the future risk posed by droughts depends not only on the climate-induced changes but also on the changes in societal exposure and vulnerability to droughts. Here we illustrate how the consideration of human vulnerability alters global drought risk associated with runoff (hydrological) and soil moisture (agriculture) droughts during the 21st-century. We combine the changes in drought frequency, population growth, and human development as a proxy of vulnerability to project global drought risk under plausible climate and socioeconomic development pathways. Results indicate that the shift toward a pathway of high greenhouse gas emissions and socioeconomic inequality leads to i) increased population exposure to runoff and soil moisture droughts by 81% and seven folds, respectively, and ii) a stagnation of human development. These consequences are more pronounced for populations living in low than in very high human development countries. In particular, Sub-Saharan Africa and South Asia, where the majority of the world's less developed countries are located, fare the worst in terms of future drought risk. The disparity in risk between low and very high human development countries can be substantially reduced in the presence of a shift toward a world of rapid and sustainable development that actively reduces social inequality and emissions. Our results underscore the importance of rapid human development in hotspots of drought risk where effective adaptation is most needed to reduce future drought impacts.
Modern technologies continuously need special materials with specific properties to adopt the desired application. Recently, numerous researches have been dedicated to the development of new food packaging materials that can ensure optimum protection of the packaged product. In this context, conducting polymers-based coatings were considered promising materials to be used as contact compounds in the packaging industries. Poly(3, 4-ethylenedioxythiophene) (PEDOT) films were electrochemically synthesized on two different metallic food packaging substrates, namely, tinplate and aluminum. The electrosynthesis was achieved in two electrolytic media using cyclic voltammetry, chronoamperometry, and chronopotentiometry. The elaborated coatings were then subjected to several microscopic and spectroscopic analyses. The characterization allowed a detailed description of the morphology and the chemical composition of PEDOT coatings and confirms the electrochemical modification of the metals. Besides, the surface wettability was examined as it has a great interest in the present work since the packaged product can be in direct contact with the metallic food container which, depending on its wettability, can be a site of corrosion. Afterward, the corrosion performances of the elaborated coatings were investigated over time in 3% sodium chloride solution by open circuit potential (OCP), potentiodynamic polarization, and electrochemical impedance spectroscopy (EIS). The results clearly showed that PEDOT films can serve as a stable matrix on tinplate and aluminum against corrosion. Graphical Abstract
In this work, we study the effect of vacuum annealing and position of metal Cu on structural, optical, electrical and thermoelectrical properties of ITO/Cu/ITO multilayers prepared on glass substrates, at room temperature by Radio Frequency (RF) sputtering. ITO (80 nm)/Cu(5 nm)/ITO (80 nm) ICI(a) and ITO (150 nm)/Cu(5 nm)/ITO (10 nm) ICI(b) multilayers were studied. The effect of vacuum annealing and position of metal Cu on ITO/Cu/ITO multilayers were investigated. The structure of ICI was analyzed by X-Ray Diffraction (XRD), X-Ray Reflectivity (XRR), scanning electron microscopy (SEM) and energy dispersive X-ray (EDX). Moreover, the electrical and optical properties were characterized by the four-point probes method and UV–Vis–NIR transmission measurement, respectively. Effect of the annealing temperature and position of metal Cu on the structural, optical, electrical and thermoelectrical properties were investigated.
Periventricular focal nodular heterotopia is a rare secondary cerebral distortion caused by the interruption of neuronal migration from the periventricular germinal zone to the cortex during the fetal period. Clinically, it may manifest as epilepsy resistant to pharmacological treatments or rarely as mental retardation. We report a case of a six years-old male child who was subject to the intensive care unit for the management of refractory epilepsy. The diagnosis was done by magnetic resonance imaging of the brain, which revealed a nodular periventricular heterotopia of the gray matter. After the management of the status of epilepticus, the child remained spastic, aphasic with no contact with his environment.
Autoimmune diseases are caused by the overactivity of the immune system towards self-constituents. Risk factors of autoimmune diseases are multiple and include genetic, epigenetic, environmental, and psychological. Autoimmune chronic inflammatory bowel diseases, including celiac and inflammatory diseases (Crohn's disease and ulcerative colitis), constitute a significant health problem worldwide. Besides the complexity of the symptoms of these diseases, their treatments have only been palliative. Numerous investigations showed that natural phytochemicals could be promising strategies to fight against these autoimmune diseases. In this respect, plant-derived natural compounds such as flavonoids, phenolic acids, and terpenoids exhibited significant effects against three autoimmune diseases affecting the intestine, particularly bowel diseases. This review focuses on the role of natural compounds obtained from medicinal plants in modulating inflammatory auto-immune diseases of the intestine. It covers the most recent literature related to the effect of these natural compounds in the treatment and prevention of auto-immune diseases of the intestine.
We are interested in the $L^2$-holomorphic automorphic functions on a $g$-dimensional complex space $V^g_{\mathbb{C}}$ endowed with a positive definite hermitian form and associated to isotropic discrete subgroups $\Gamma$ of rank $2\leq r \leq g$. We show that they form an infinite reproducing kernel Hilbert space which looks like a tensor product of a theta Fock-Bargmann space on $V^{r}_{\mathbb{C}}=Span_{\mathbb{C}}(\Gamma)$ and the classical Fock-Bargmann space on $V^{g-r}_{\mathbb{C}}$. Moreover, we provide an explicit orthonormal basis using Fourier series and we give the expression of its reproducing kernel function in terms of Riemann theta function of several variables with special characteristics.
In the field of diagnosis and treatment planning of Coronavirus disease 2019 (COVID-19), accurate infected area segmentation is challenging due to the significant variations in the COVID-19 lesion size, shape, and position, boundary ambiguity, as well as complex structure. To bridge these gaps, this study presents a robust deep learning model based on a novel multi-scale contextual information fusion strategy, called Multi-Level Context Attentional Feature Fusion (MLCA2F), which consists of the Multi-Scale Context-Attention Network (MSCA-Net) blocks for segmenting COVID-19 lesions from Computed Tomography (CT) images. Unlike the previous classical deep learning models, the MSCA-Net integrates Multi-Scale Contextual Feature Fusion (MC2F) and Multi-Context Attentional Feature (MCAF) to learn more lesion details and guide the model to estimate the position of the boundary of infected regions, respectively. Practically, extensive experiments are performed on the Kaggle CT dataset to explore the optimal structure of MLCA2F. In comparison with the current state-of-the-art methods, the experiments show that the proposed methodology provides efficient results. Therefore, we can conclude that the MLCA2F framework has the potential to dramatically improve the conventional segmentation methods for assisting clinical decision-making.
Daucosterol is a saponin present in various natural sources, including medicinal plant families. This secondary metabolite is produced at different contents depending on species, extraction techniques, and plant parts used. Currently, daucosterol has been tested and explored for its various biological activities. The results reveal potential pharmacological properties such as antioxidant, antidiabetic, hypolipidemic, anti-inflammatory, immunomodulatory, neuroprotective, and anticancer. Indeed, daucosterol possesses important anticancer effects in many signaling pathways, such as an increase in pro-apoptotic proteins Bax and Bcl2, a decrease in the Bcl-2/Bax ratio, upregulation of the phosphatase and tensin homolog (PTEN) gene, inhibition of the PI3K/Akt pathway, and distortion of cell-cycle progression and tumor cell evolution. Its neuroprotective effect is via decreased caspase-3 activation in neurons and during simulated reperfusion (OGD/R), increased IGF1 protein expression (decreasing the downregulation of p-AKT3 and p-GSK-3b4), and activation of the AKT5 signaling pathway. At the same time, daucosterol inhibits key glucose metabolism enzymes to keep blood sugar levels within normal ranges. Therefore, this review describes the principal research on the pharmacological activities of daucosterol and the mechanisms of action underlying some of these effects. Moreover, further investigation of pharmacodynamics, pharmacokinetics, and toxicology are suggested.
Prickly pear, Opuntia ficus-indica (L.) Miller (Caryophyllales: Cactaceae), cultivations in Morocco have been aggressively infested in recent years by the prickly pear cochineal, Dactylopius opuntiae (Cockerell) (Hemiptera: Dactylopiidae). An integrated pest management program that takes a holistic approach at the agroecosystem level, rather than piecemeal pesticide applications, is likely to improve cochineal control in Morocco. The pest protection plan should include the use of natural extracts, biorational insecticides, and natural enemies to biologically control D. opuntiae infestations. Mechanical methods, such as pruning and uprooting, are potential control measures in areas where the first evidence of D. opuntiae infestation occurs. Using resistant cactus varieties to the prickly pear cochineal will also minimize the spread of this pest. Eight resistant cultivars to D. opuntiae were identified, registered, and multiplied, and plantation on a large scale is underway in Morocco’s cactus area. This paper provides an overview of present information on prickly pear cochineal for Moroccan farmers and stakeholders in order to suggest the best way to limit or counter the spread of this pest, particularly in freshly cactus cultivated areas.
This paper treats the inverse denoising problem which aims to compute simultaneously the clean image and the weighting parameter λ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda$$\end{document}. The formulated denoising problem is posed using a partial differential equation (PDE)-constrained optimization model. The minimized function imposes a Tikhonov regularization on the estimated λ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda$$\end{document}, while the proposed PDE encompasses two high-order diffusive tensors. The particularity of this PDE is that it does not over-smooth homogeneous regions and preserves sharp edges during the denoising process, even if its degree is high. A new optimization procedure to compute the weighting parameter is also elaborated inspired from the nonsmooth Primal-dual algorithm. This leads to control of the diffusivity rate generated by the two diffusive operators. Finally, expressive results show that the computed spatial parameter λ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda$$\end{document} leads to obtain a pleasant clean image. This is also confirmed by numerous comparisons with other competitive denoising approaches.
Background removal of an identity (ID) picture consists in separating the foreground (face, body, hair and clothes) from the background of the image. It is a necessary groundwork for all modern identity documents that also has many benefits for improving ID security. State of the art image processing techniques encountered several segmentation issues and offer only partial solutions. It is due to the presence of erratic components like hairs, poor contrast, luminosity variation, shadow, color overlap between clothes and background. In this paper, a knowledge infused approach is proposed that hybridizes smart image processing tasks and prior knowledge. The research is based on a divide and conquer strategy aiming at simulating the sequential attention of human when performing a manual segmentation. Knowledge is infused by considering the spatial relation between anatomic elements of the ID image (face feature, forehead, body and hair) as well as their “signal properties”. The process consists in first determining a convex hull around the person’s body including all the foreground while keeping very close to the contour between the background and the foreground. Then, a body map generated from biometric analysis associated to an automatic grab cut process is applied to reach a finer segmentation. Finally, a heuristic-based post-processing step consisting in correcting potential hair and fine boundary issues leads to the final segmentation. Experimental results show that the newly proposed architecture achieves better performances than tested current state-of-the-art methodologies including active contours, generalist popular deep learning techniques, and also two other ones considered as the smartest for portrait segmentation. This new technology has been adopted by an international company as its industrial ID foreground solution.
Coffee is one of the most popular and preferred drinks in the world, being consumed for its refreshing and energizing properties. As a result, the consumption of coffee generates millions of tons of waste, in particular, spent coffee grounds (SCG). On the contrary, food waste recovery is an incredibly sustainable and convenient solution to the growing need for materials, fuels, and chemicals. SCG has been developed as a precious resource of several high value‐added products (oil, proteins, minerals, fatty acids, sterols….). Thus, a transformative pathway to a circular economy that involves the valorization of coffee wastes and by‐products is currently attracting the attention of researchers worldwide. The potential growth of scientific papers and publications promotes a comprehensive review to determine the research hotspots, knowledge structure, and to consider future avenues and challenges. Therefore, in this paper, we conducted a systematic review based on 275 indexed papers on the composition and valorization of SCG as a prospective environmental source. Practical applications SCG can be applied in agro‐food industries.
Purpose Pollution from oil operations; exploration, drilling, transfer, transport, refinery and distribution reduce soil quality, and results in the removal of a large amount of soil from annual utilization cycles. Soil quality is an essential asset of sustainable development and is negatively affected by erosion and anthropogenic activity. Co-composting is a biological technique used in the bioremediation of soils, which was investigated in this study. Materials and methods This study focused on the remediation of 1200 m³ of saline contaminated soil from an oil-polluted operational area in Iran. The initial total petroleum hydrocarbon (TPH) content of the soil was between 6.9 and 17.1 g kg⁻¹ and was contaminated with heavy oil. Initial water repellency of the soil was between 1500 and 12,500 S. The remediation procedure commenced with trials in which organic waste of a local sugarcane sugar factory, mixed urea, sugar, and compost mixtures was added to contaminated soils. Results After irrigation and aeration of piles of organic materials and soil over 3 months of operation, the TPH reduced from 4.86, 6.52, and 9.89 to 0.068, 0.080, and 0.109 g kg⁻¹, in the moderately, highly, and very highly polluted soil piles respectively. At the end of the remediation project, following gas chromatography analysis of contaminant content, and in accordance with governmental authorities, recovered soils were added to the surrounding environment to the support growth of the natural ecosystem. Conclusion Soil recovery and remediation utilizing valorization and complimentary local industries have a transferable quality that may be adapted to additional vulnerable sites in droughted and variable edaphic and climatic conditions.
3-(4-hydroxybutyl)-1-phenethyl-1H-imidazol-3-ium chloride ([HB-Imid] Cl), and 3-(2-chlorobenzyl)-1-phenethyl-1H-imidazol-3-ium chloride ([CB-Imid] Cl) were investigated as corrosion inhibitors for mild steel in 1.0 M hydrochloric acid solution. Electrochemical techniques (PDP and EIS) were performed as experimental studies while DFT at B3LYP 6-311G (df,pd), and molecular dynamic simulation were used as theoretical approach. PDP experiments revealed that the studied ionic liquids (ILs) behaved as mixture type inhibitors. EIS results indicated that these compounds showed good inhibition performance with inhibition efficiency around 95% at the optimum concentration of 1.0 × 10⁻³ M. According to Langmuir isotherm model and the thermodynamic parameters, these ILs were adsorbed onto the mild steel surface through physical and chemical bonds. SEM and EDX examinations proved the formation of a protective layer of adsorbed inhibitors at the steel surface. The DFT/B3LYP/6-311G(df,pd) computations in both the gas and water environments disclosed that [HB-Imid] Cl molecule was softer and had a lower energy gap, electrodonating power, and polarizability indexes.
The objective of this work is the use of cellulose fibers extracted from coir fibers as Janus nanocylinders to suppress the phase retraction and coalescence in poly(lactic) acid/polypropylene bio-blend polymers via prompting the selective localization of cellulose fibers at the interface using chemical modification. The untreated and modified cellulose fibers extracted from coir fibers using a silane molecule (tetraethoxysilane) were used as reinforcement and as Janus nanocylinder at two weight contents (2.5 wt% and 5 wt%) to manipulate the morphology of the bio-blends. Their bio-composites with PLA-PP matrix were prepared via melt compounding (at PLA/PP: 50/50). The treatment effect on component interaction and the bio-composites properties have been studied via Scanning electron microscopy, infrared spectroscopy, and differential calorimetry analysis. The mechanical and rheological properties of nanocomposites were similarly assessed. Young's modulus and tensile strength of PLA-PP nanocomposites reinforced by silanized cellulose fibers show a great enhancement as compared to a neat matrix. In particular, there was a gain of 18.5% in Young's modulus and 11.21% in tensile strength for silanized cellulose fiber-based bio-blend composites at 5 wt%. From the rheological point of view, it was found that the silanized cellulose fibers in PLA-PP at both fibers loading enhances the adhesion between both polymers leading to tuning their morphology from sea-island to the continuous structures with the appearance of PLA microfibrillar inside of bio-composites. This change was reflected in the relaxation of the chain mobility of the bio-blend composites.
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• Genie civil et mécanique
• Faculty of Applied Sciences
• Department of Chemistry
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