Search Results (2,387)

The Union of the Comoros, located in the Indian Ocean, faces persistent energy challenges due to its geographic isolation, heavy dependence on imported fossil fuels, and underdeveloped electricity infrastructure. This study investigates the techno-economic optimization of a hybrid microgrid designed to supply electricity to a rural village in Grande Comore. The proposed system integrates photovoltaic (PV) panels, wind turbines, a diesel generator, and battery storage. Detailed modeling and simulation were conducted using HOMER Energy, accompanied by a sensitivity analysis on solar irradiance, wind speed, and diesel price. The results indicate that the optimal configuration consists solely of PV and battery storage, meeting 100% of the annual electricity demand with a competitive levelized cost of energy (LCOE) of 0.563 USD/kWh and zero greenhouse gas emissions. Solar PV contributes over 99% of the total energy production, while wind and diesel components remain unused under optimal conditions. Furthermore, the system generates a substantial energy surplus of 63.7%, which could be leveraged for community applications such as water pumping, public lighting, or future system expansion. This study highlights the technical viability, economic competitiveness, and environmental sustainability of 100% solar microgrids for non-interconnected island territories. The approach provides a practical and replicable decision-support framework for decentralized energy planning in remote and vulnerable regions. Full article

Electromagnetic and magnetic devices are increasingly prevalent in sectors such as transportation, industry, and renewable energy due to the ongoing electrification trend. These devices exhibit nonlinear behavior, particularly under signals rich in harmonics. They require precise and appropriate modeling for accurate sizing. Identifying model-specific parameters, which depend on frequency, is crucial. This article focuses on a specific frequency range where a circuit model with series resistance and inductance, along with a parallel resistance to account for iron losses (${\mathrm{R}}_{\mathrm{iron}}$), is applicable. While the determination of series elements is well documented, the determination of ${\mathrm{R}}_{\mathrm{iron}}$ remains complex and debated, with traditional methods neglecting operating conditions such as magnetic saturation. To address these limitations, an innovative experimental method is proposed, comprising two main steps: determining the complex impedance of the magnetic device and extracting ${\mathrm{R}}_{\mathrm{iron}}$ from the model. This method aims to provide a more precise and representative estimation of ${\mathrm{R}}_{\mathrm{iron}}$, improving the reliability and accuracy of electromagnetic and magnetic device simulations and designs. The obtained values of the iron loss equivalent resistance are different by at least 300% than those obtained by an impedance analyzer. The proposed method is expected to advance the understanding and modeling of losses in electromagnetic and magnetic devices, offering more robust tools for engineers and researchers in optimizing device performance and efficiency. Full article

Barium chloride (BaCl₂), a known environmental pollutant, induces organ-specific oxidative stress through disruption of redox homeostasis. This study evaluated the protective effects and safety profile of sodium copper chlorophyllin (SCC) and ascorbic acid (ASC) against BaCl₂-induced oxidative damage in the liver and brain of mice using a two-phase experimental protocol. Animals received either SCC (40 mg/kg), ASC (160 mg/kg), or their combination for 14 days prior to BaCl₂ exposure (150 mg/L in drinking water for 7 days), allowing evaluation of both preventive and therapeutic effects. Toxicological and behavioral assessments confirmed the absence of systemic toxicity or neurobehavioral alterations following supplementation. Body weight, liver and kidney indices, and biochemical markers (Aspartate Aminotransferase (ASAT), Alanine Aminotransferase (ALAT), creatinine) remained within physiological ranges, and no anxiogenic or locomotor effects were observed. In the brain, BaCl₂ exposure significantly increased SOD (+49%), CAT (+66%), GPx (+24%), and GSH (+26%) compared to controls, reflecting a robust compensatory antioxidant response. Although lipid peroxidation (MDA) showed a non-significant increase, SCC, ASC, and their combination reduced MDA levels by 42%, 37%, and 55%, respectively. These treatments normalized antioxidant enzyme activities and GSH, indicating an effective neuroprotective effect. In contrast, the liver exhibited a different oxidative profile. BaCl₂ exposure increased MDA levels by 80% and GSH by 34%, with no activation of SOD, CAT, or GPx. Histological analysis revealed extensive hepatocellular necrosis, vacuolization, and inflammatory infiltration. SCC significantly reduced hepatic MDA by 39% and preserved tissue architecture, while ASC alone or combined with SCC exacerbated inflammation and depleted hepatic GSH by 71% and 78%, respectively, relative to BaCl₂-exposed controls. Collectively, these results highlight a differential, organ-specific response to BaCl₂-induced oxidative stress and the therapeutic potential of SCC and ASC. SCC emerged as a safer and more effective agent, particularly in hepatic protection, while both antioxidants demonstrated neuroprotective effects when used individually or in combination. Full article

A combination of lattice Boltzmann method (LBM)-based computations and Lagrangian particle tracking simulations is presented to study the dispersion and clustering of inertial particles in a forced homogeneous and isotropic turbulent flow and to analyze the relative importance of the various forces acting on particles. The particle dynamics are investigated across a wide range of particle-to-fluid density ratios (from 0.01 to 1000) and Stokes numbers (from 1.4 × 10⁻⁶ to 55.4), at a Taylor microscale Reynolds number of 33.6. Particle clustering is quantified using Voronoï tessellations. Results confirm that clustering intensity is maximized at Stokes numbers around unity, where particles preferentially accumulate in low-vorticity regions. Particle dynamics within the turbulent flow considered here vary fundamentally with density and size, even among tracer-like particles. Low-density and neutrally buoyant particles mimic tracers via either velocity matching or acceleration balance, while dense particles follow inertia-dominated dynamics. Full article

The production of iron and steel plays a significant role in the anthropogenic carbon footprint, accounting for 7% of global GHG emissions. In the context of CO₂ mitigation, the steelmaking industry is looking to potentially replace traditional carbon-based ironmaking processes with hydrogen-based direct reduction of iron ore in shaft furnaces. Before industrialization, detailed modeling and parametric studies were needed to determine the proper operating parameters of this promising technology. The modeling approach selected here was to complement REDUCTOR, a detailed finite-volume model of the shaft furnace, which can simulate the gas and solid flows, heat transfers and reaction kinetics throughout the reactor, with an extension that describes the whole gas circuit of the direct reduction plant, including the top gas recycling set up and the fresh hydrogen production. Innovative strategies (such as the redirection of part of the bustle gas to a cooling inlet, the use of high nitrogen content in the gas, and the introduction of a hot solid burden) were investigated, and their effects on furnace operation (gas utilization degree and total energy consumption) were studied with a constant metallization target of 94%. It has also been demonstrated that complete metallization can be achieved at little expense. These strategies can improve the thermochemical state of the furnace and lead to different energy requirements. Full article

Gene therapy is a groundbreaking strategy in regenerative medicine, enabling precise cellular behavior modulation for tissue repair. In situ nucleic acid delivery systems aim to directly deliver nucleic acids to target cells or tissues to realize localized genetic reprogramming and avoid issues like donor cell dependency and immune rejection. The key to success relies on biomaterial-engineered delivery platforms that ensure tissue-specific targeting and efficient intracellular transport. Viral vectors and non-viral carriers are strategically modified to enhance nucleic acid stability and cellular uptake, and integrate them into injectable or 3D-printed scaffolds. These scaffolds not only control nucleic acid release but also mimic native extracellular microenvironments to support stem cell recruitment and tissue regeneration. This review explores three key aspects: the mechanisms of gene editing in tissue repair; advancements in viral and non-viral vector engineering; and innovations in biomaterial scaffolds, including stimuli-responsive hydrogels and 3D-printed matrices. We evaluate scaffold fabrication methodologies, nucleic acid loading–release kinetics, and their biological impacts. Despite progress in spatiotemporal gene delivery control, challenges remain in balancing vector biocompatibility, manufacturing scalability, and long-term safety. Future research should focus on multifunctional “smart” scaffolds with CRISPR-based editing tools, multi-stimuli responsiveness, and patient-specific designs. This work systematically integrates the latest methodological advances, outlines actionable strategies for future investigations and advances clinical translation perspectives beyond the existing literature. Full article

This study aimed to train and validate two artificial neural network (ANN) models, one with four hidden layers and the other with five hidden layers, to predict the daily photovoltaic power output of a 20 Kw photovoltaic power plant with bifacial photovoltaic modules with tilt angle variation from 0° to 90° in two Moroccan cities, Ouarzazate and Oujda. To validate the two proposed models, photovoltaic power data calculated using the System Advisor Model (SAM) software version 2023.12.17 were employed to predict the average daily power of the photovoltaic plant for December, utilizing MATLAB software Version R2020a 9.8, and for the tilt angles corresponding to the latitudes of the two cities studied. The results differ from one model to another according to their mean absolute error (MAE), root mean squared error (RMSE), and coefficient of determination (R²) values. The artificial neural network model with five hidden layers obtained better results with a R² value of 0.99354 for Ouarzazate and 0.99836 for Oujda. These two proposed models are trained using the Levenberg Marquardt (LM) optimizer, which is proven to be the best training procedure. Full article

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental pollutants that continue to raise concern owing to their ability to accumulate in living organisms. In recent years, a growing body of research has shown that PFAS can exert their toxicity through disruption of both DNA integrity and epigenetic regulation. This includes changes in DNA methylation patterns, histone modifications, chromatin remodeling, and interference with DNA repair mechanisms. These molecular-level alterations can impair transcriptional regulation and cellular homeostasis, contributing to genomic instability and long-term biological dysfunction. In neural systems, PFAS exposure appears particularly concerning. It affects key regulators of neurodevelopment, such as BDNF, synaptic plasticity genes, and inflammatory mediators. Importantly, epigenetic dysregulation extends to non-coding RNAs (ncRNAs), including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), which mediate post-transcriptional silencing and chromatin remodeling. Although direct evidence of transgenerational neurotoxicity is still emerging, animal studies provide compelling hints. Persistent changes in germline epigenetic profiles and transcriptomic alterations suggest that developmental reprogramming might be heritable by future generations. Additionally, PFAS modulate nuclear receptor signaling (e.g., PPARγ), further linking environmental cues to chromatin-level gene regulation. Altogether, these findings underscore a mechanistic framework in which PFAS disrupt neural development and cognitive function via conserved epigenetic and genotoxic mechanisms. Understanding how these upstream alterations affect long-term neurodevelopmental and neurobehavioral outcomes is critical for improving risk assessment and guiding future interventions. This review underscores the need for integrative research on PFAS-induced chromatin disruptions, particularly across developmental stages, and their potential to impact future generations. Full article

Functionally graded carbon nanotube reinforced composites (FG-CNTRCs) are a novel breed of polymer nanocomposite, in which the nonuniform distribution of the carbon nanotube (CNT) reinforcement is adopted to maximize the macro-mechanical performance of the polymer with a lower content of CNTs. Composite conical–cylindrical combined shells (CCCSs) are widely utilized as loading-bearing components in various engineering applications, and a comprehensive understanding of the vibration characteristics of these shells under different external excitations and boundary conditions is crucial for engineering applications. In this study, the free vibration behaviors of FG-CNTRC CCCSs supported by an elastic foundation are examined using the Haar wavelet discretization method (HWDM). First, by means of the HWDM, the equations of motion of each shell segment, the continuity and boundary conditions are converted into a system of algebraic equations. Subsequently, the natural frequencies and modes of the CCCSs are achieved by calculating the resultant algebraic equations. The convergence and accuracy are evaluated, and the results demonstrate that the proposed method has stable convergence, high efficiency, and excellent accuracy. Furthermore, an exhaustive parametric investigation is conducted to reveal the effects of foundation stiffnesses, boundary conditions, material mechanical properties, and geometric parameters on the vibration characteristics of the FG-CNTRC CCCS. Full article

This work was conducted within the framework of French university reforms undertaken since 2022. Regardless of learning level and target audience, project-based learning has proved its effectiveness as a teaching strategy for many years. The novelty of the present contribution lies in the gamification of this learning method. A popular game, Trivial Pursuit, was adapted to enable students to acquire knowledge in a playful manner while preparing for upcoming technical challenges. Various technical subjects were chosen to create new cards for the game. A total of 180 questions and their answers were created. The colored tokens were then used to trace manufactured products. This teaching experiment was conducted as part of a project-based learning program with third-year Bachelor students (Electrical Engineering and Industrial Computing Department). The game components associated with the challenge proposed to the students comprised six key elements: objectives, challenges, mechanics, components, rules, and environment. Within the framework of the Industry 4.0 concept, this pedagogical activity focused on the knowledge, understanding, development, and application of an RFID (Radio Frequency Identification) system demonstrating the capabilities of this technology. This contribution outlines the various stages of the work assigned to the students. An industrial partner was also involved in this work. Full article

The increasing adoption of electric vehicles (EVs) requires efficient management of charging infrastructure, particularly in optimizing the allocation of limited charging resources. This paper addresses the preemptive electric vehicle charging scheduling problem (EVCSP), where charging sessions can be interrupted to maximize the number of satisfied demands. The existing mathematical formulations often struggle with scalability and computational efficiency for even small problem instances. As a result, we propose an enhanced mathematical programming model, which is further refined to reduce decision variable complexity and improve computational performance. In addition, a constraint programming (CP) approach is explored as an alternative method for solving the EVCSP due to its strength in handling complex scheduling constraints. The experimental results demonstrate that the developed methods significantly outperform the existing models in the literature, providing scalable and efficient solutions for optimizing EV charging infrastructure. Full article

The use of aluminum honeycomb structures is fast expanding in advanced sectors such as the aeronautics, aerospace, marine, and automotive industries. However, processing these structures represents a major challenge for producing parts that meet the strict standards. To address this issue, an innovative manufacturing method using longitudinal ultrasonic vibration-assisted cutting, combined with a CDZ10 hybrid cutting tool, was developed to optimize the efficiency of traditional machining processes. To this end, a 3D numerical model was developed using the finite element method and Abaqus/Explicit 2017 software to simulate the complex interactions among the cutting tool and the thin walls of the structures. This model was validated by experimental tests, allowing the study of the influence of milling conditions such as feed rate, cutting angle, and vibration amplitude. The numerical results revealed that the hybrid technology significantly reduces the cutting force components, with a decrease ranging from 10% to 42%. In addition, it improves cutting quality by reducing plastic deformation and cell wall tearing, which prevents the formation of chips clumps on the tool edges, thus avoiding early wear of the tool. These outcomes offer new insights into optimizing industrial processes, particularly in fields with stringent precision and performance demands, like the aerospace sector. Full article

Chagas disease, caused by Trypanosoma cruzi, poses a significant public health challenge due to its widespread prevalence, limited therapeutic options, and adverse effects associated with available medications. In this study, we developed 13 novel pyrazole-imidazoline derivatives, inspired by a previously identified cysteine protease inhibitor, and evaluated their antiparasitic activity. Our in silico analyses predicted favorable physicochemical profiles and promising oral bioavailability for these derivatives. Upon phenotypic screening, we observed that these new derivatives exhibited low cytotoxicity (CC₅₀ > 100 µM) and marked efficacy against intracellular amastigotes. Derivative 1k showed high activity (IC₅₀ = 3.3 ± 0.2 µM), selectivity (SI = 73.9), and potency (pIC₅₀ = 5.4). In a 3D cardiac microtissue model, 1k significantly reduced parasite load, matching the efficacy of benznidazole (Bz) even at lower concentrations. Both 1k and Bz effectively prevented parasite recrudescence; however, neither resulted in parasite sterility under the experimental conditions employed. The combination of 1k–Bz yielded an additive interaction, highlighting its potential for in vivo combination therapy. While structural changes abolished cysteine protease inhibition, incorporating a CF₃ substituent at the para position and excluding the amino group enhanced antiparasitic activity. These findings reinforce the promise of the pyrazole-imidazoline scaffold and support further structural optimizations to develop innovative candidates for treating Chagas disease. Full article

Background: Tobacco use is disproportionately high in rural areas, contributing to elevated cancer mortality, yet it often goes untreated due to limited access to care, high poverty and uninsured rates, and co-occurring substance use disorders (SUDs). This study explored the utility of using rapid qualitative analysis (RQA) to guide the adaptation of a tobacco-free workplace program (TFWP) in Texas healthcare centers serving adults with SUDs in medically underserved areas. Methods: From September–December 2023 and May–July 2024, we conducted 11 pre-implementation, virtual semi-structured group interviews focused on adapting the TFWP to local contexts (N = 69); 7 with providers (n = 34) and managers (n = 12) and 4 with patients (n = 23) in 6 healthcare centers. Two qualified analysts independently summarized transcripts, using RQA templates of key domains drawn from interview guides to summarize and organize data in matrices, enabling systematic comparison. Results: The main themes identified were minimal organizational tobacco cessation support and practices, and attitudinal barriers, as follows: (1) the need for program materials tailored to local populations; (2) limited tobacco cessation practices and partial policies—staff requested guidance on enhancing tobacco screenings and cessation delivery, and integrating new interventions; (3) contradictory views on treating tobacco use that can inhibit implementation (e.g., wanting to quit yet anxious that quitting would cause SUD relapse); and (4) inadequate environmental supports—staff requested treating tobacco-use training, patients group cessation counseling; both requested nicotine replacement therapy. Conclusions: RQA identified key areas requiring capacity development through participants’ willingness to adopt the following adaptations: program content (e.g., trainings and tailored educational materials), delivery methods/systems (e.g., adopting additional tobacco care interventions) and implementation strategies (e.g., integrating tobacco cessation practices into routine care) critical to optimizing TFWP fit and implementation. The study findings can inform timely formative evaluation processes to design and tailor similar intervention efforts by addressing site-specific needs and implementation barriers to enhance program uptake. Full article