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« Élever collectivement le niveau de performance de la filière »
No full textForte de 1 500 experts et d’une vision désormais intégrée des achats, de la qualité et du contract management, la toute récente direction Supply Chain d’EDF redéfinit la relation industrielle au moment où la filière engage une accélération historique. Sa directrice Nora Signor détaille les leviers mis en oeuvre pour renforcer toute la chaîne de fournisseurs
Revolution in cultivated proteins and emerging biotechnologies for sustainable food
No full textConsidering environmental, climate, economic and nutritional challenges, the food transformation’s systems has become a global strategic priority. Additionally, owing to its natural resource’s intensity, greenhouse gas emissions and dependence on vulnerable agricultural ecosystems, protein production, including those of animal origin, is identified as one of the main contributors to the overall human’s food ecological footprint. Besides, plant proteins have been partially reduced this footprint, and their large-scale development faces technological, functional and environmental limitations related to extraction and industrial processing. Nevertheless, crop proteins, microbial proteins and fermentation products are emerging as new generation of protein solutions, based on controlled biotechnological processes and potentially separated from traditional agricultural constraints. These approaches are part of a protein transition, combining environmental sustainability, food security, industrial innovation and climate change’s resilience. This article provides a comprehensive synthesis of the conceptual foundations, production technologies, and socio-economic constraints and environmental impacts combined with cultivated proteins and aims to reposition them as a structural pillar of alternative proteins, linked to sustainable agriculture, the circular bioeconomy and the emerging principles of industry 5.0 based on recent scientific literature
The effect of urea mole fraction on the solvation structure using molecular dynamics simulations
No full textWe examine the local structure and solvation properties of urea in water at various mole fractions using molecular dynamics simulations. The study investigates the radial distribution and the nearest neighbor radial distribution functions between urea and water atoms, including O(urea)-H(water), H(urea)-O(water) and N(urea)-H(water) interactions. These interactions contribute to a better understanding of the local structure as well as the hydrogen bonding behaviors within the mixture. Our results indicate that the local structure around urea is preserved and provide molecular level information on the effect of urea molar fractions on the hydrogen bond network and solvation structure of aqueous urea solutions
Biohydrogen production from agro-industrial waste: Toward clean energy and a circular economy
No full textThe growing world need of clean and renewable energy requires formulation of sustainable strategies that are capable of effectively converting organic waste into substitutes. Agro-industrial residues which include beet pulp, used coffee grounds and whey, in this case form an enormous unused biomass with high bioenergetic potential. This paper presents a combined discussion of the main biological routes to biohydrogen generation based on agro-industrial wastes and dark fermentation, photofermentation, and coupled H2-CH 4. Dark fermentation is based on the capability of anaerobic microorganisms to quickly transform organic material to hydrogen, whereas the ratio of photofermentation improves the product by recovering organic acids of the first step with the aid of photosynthetic bacteria. Moreover, the biohydrogen generation in combination with anaerobic digestion would allow the complete valorization of organic waste to biomethane, hence, maximizing the total energy balance and reducing environmental costs. The effect of important operating parameters such as pH, temperature, substrate composition, and fermentation time are also talked about in order to streamline the process performance. All in all, combined biological methods of agro-industrial waste include the integrated valorization of waste, which is a promising concept in terms of sustainable energy generation, greenhouse gas emissions, and the concept of a circular economy
Towards sustainable management of medicinal and aromatic plants in Morocco: Typology and priority actions
No full textThreats from overharvesting, habitat degradation, and climate change have made the sustainable management of medicinal and aromatic plants (MAPs) in Morocco increasingly important. These species are essential in traditional medicine, biodiversity, and the livelihoods of local communities. In response, the Moroccan government has expanded its network of protected areas, enacted new laws, and made international commitments to improve its institutional and legal frameworks. The study focused on 20 MAPs and used 22 interviews from 12 stakeholder organizations—86.4% of which are in the public sector—to evaluate the effectiveness of these initiatives. According to the findings, 75% of the taxa require conservation actions, while the remaining 25% need measures aimed at enhancing knowledge. Typifying these actions enables to develop specific measures that are adapted to the specific needs of each species. The results highlight the importance of a coordinated approach involving several actors in order to protect ecosystems and traditional knowledge
Quantifying carbon storage decline under land degradation in the Central High Atlas: A case study of the Oued Ahansal watershed (2000–2022)
No full textCarbon sequestration is an essential ecosystem service that contributes to climate regulation and enhances ecosystem resilience. This study evaluates changes in carbon storage in the Oued Ahansal watershed, Central High Atlas, Morocco, from 2000 to 2022 using the InVEST model. Land use and land cover maps derived from Landsat 5 and Landsat 8 images were classified into four categories: dense forest, open forest, agricultural land, and bare soil. Carbon stocks were estimated for aboveground biomass, belowground biomass, soil, and dead organic matter. Results show a marked decline in high-carbon storage areas, which decreased from 55.5% in 2000 to 11.9% in 2022, while low-carbon zones increased from 5.1% to 80.8%. This reflects accelerated land degradation linked to vegetation loss, overgrazing, and recurrent droughts. The findings highlight the urgent need for reforestation, assisted natural regeneration, and sustainable land management to restore the carbon sink capacity of degraded mountain ecosystems
Adaptive Neuro-Fuzzy Energy Management of Grid-Connected PV Systems with Hybrid Storage for Voltage and Frequency Stability
No full textThe paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS)- smart energy management scheme for a grid-connected hybrid power conversion system integrating photovoltaic (PV) generation, battery, and supercapacitor storage. The devised control maintains stability of the DC-side voltage stability, smooths PV power fluctuations, and ensures reliable operation under variable load and irradiance. Synergistic storage system utilizes a battery for long-term energy balancing and a supercapacitor for transient stabilization. The ANFIS controller adaptively manages power sharing between PV, grid, and storage elements, enhancing power quality and reducing Harmonic content ratio. Simulation results Evident that the proposed ANFIS-based Controller sustains THD at 0.24%, outperforming conventional PI and fuzzy controllers in dynamic response, settling time, and voltage regulation
AI - Powered Medical Chatbot for Symptom Check
No full textThis paper discusses the design and development of an AI-powered medical chatbot that acts as an intelligent symptom checker and initial healthcare advisor. The system uses Natural Language Processing (NLP) to preprocess user input through tokenization, stemming, and Bag-of-Words (BoW) vectorization, converting unstructured text into a machine-readable format. It employs a Decision Tree Classifier and K-Nearest Neighbors (KNN) model trained on a dataset containing over 130 symptoms and more than 40 diseases to accurately predict the likely disease based on user-reported or selected symptoms. Additionally, it provides precautionary measures, medicine recommendations, and context-aware suggestions for nearby doctors using local datasets. All interactions are securely stored in a MySQL database, allowing users to track their medical history over time. The chatbot operates on a Flask backend that integrates the trained machine learning models, ensuring real-time response generation and smooth data flow from input to prediction. Experimental results demonstrate a 94.2% accuracy with minimal overfitting, validating the model’s reliability and scalability. This system offers an affordable, accessible, and user-friendly digital healthcare solution, particularly beneficial for early disease detection and timely consultation in remote or resource-limited areas, thereby reducing the burden on healthcare professionals
Implementation of tailored CTS techniques for PPA enhancement in lower technology nodes
No full textClock Tree Synthesis is a critical stage in VLSI design, ensuring reliable and efficient clock signal distribution. An optimized clock tree minimizes skew and insertion delay, crucial for timing closure in high-frequency designs. Smaller technology nodes increase design complexity and impose stricter PPA constraints. This research emphasizes the importance of Clock Tree Synthesis in advanced technology nodes and highlights the adverse effects of suboptimal clock tree designs. Key design metrics such as silicon area, timing margins, and dynamic power are directly influenced by CTS. We propose systematic timing path balancing and architectural enhancements aimed at maximizing performance while minimizing resource overhead, thereby improving overall design robustness
A novel compact dual-band microstrip patch antenna achieving high gain and enhanced cross-polarization discrimination for IoT devices and next-generation wireless systems
No full textThe escalating demand for high-performance antennas in advanced wireless systems, driven by the rapid increase of 4G/5G networks, IoT, smart cities, and automated vehicles, presents significant design challenges. Existing antenna designs often struggle to balance compactness, dual-band operation, high gain, and crucial Cross-Polarization Discrimination (XPD), which is vital for efficient Multiple-Input Multiple-Output (MIMO) systems. This paper introduces a novel compact dual-band microstrip parasitic circular patch antenna engineered to overcome these limitations. The proposed antenna, featuring a unique “flower-shaped” radiating element and utilizing a low-loss Rogers RO3003™ substrate, achieves stable dual-band operation at 2.62 GHz and 3.91 GHz. Through careful simulation and optimization, including a parametric study of substrate height, the design demonstrates excellent performance reflection coefficients (S11) of -16.9 dB and -17.7 dB, VSWR values well below 2 (1.6 and 1.48), and high total gains of 5.93 dBi and 6.8 dBi at the respective bands. Crucially, the antenna exhibits outstanding XPD values of 35.44 dB at 2.62 GHz and 22.21 dB at 3.91 GHz, ensuring superior polarization purity. The findings confirm that the strategic integration of parasitic elements, optimized material selection, and precise geometry results in an antenna highly suitable for compact and reliable 4G/5G and IoT wireless communication systems, offering enhanced data capacity and reduced interference