Search Results (4,459)

Precise modeling and state of charge (SoC) estimation of a lithium-ion battery (LIB) are crucial for the safety and longevity of battery systems in electric vehicles. Traditional methods often fail to adapt to the dynamic, nonlinear, and time-varying behavior of LIBs under different operating conditions. In this paper, an advanced joint estimation approach of the model parameters and SoC is proposed utilizing an enhanced Sigma Point Kalman Filter (SPKF). Based on the second-order equivalent circuit model (2RC-ECM), the proposed approach was compared to the two most widely used methods for simultaneously estimating the model parameters and SoC, including a hybrid recursive least square (RLS)-extended Kalman filter (EKF) method, and simple joint SPKF. The proposed adaptive joint SPKF (ASPKF) method addresses the limitations of both the RLS+EKF and simple joint SPKF, especially under dynamic operating conditions. By dynamically adjusting to changes in the battery’s characteristics, the method significantly enhances model accuracy and performance. The results demonstrate the robustness, computational efficiency, and reliability of the proposed ASPKF approach compared to traditional methods, making it an ideal solution for battery management systems (BMS) in modern EVs. Full article

Background/Objectives: The use of dietary supplements (DSs) has become common among fitness enthusiasts, aiming to enhance performance, recovery, and overall well-being. Methods: A cross-sectional study was conducted in the city of Beni Mellal from April to July 2024, assessed dietary practices, motivations for supplement use, and associated adverse effects among 420 survey participants. Results: The majority of dietary supplement users were aged 25–64 and had higher education levels. Colopathy (67.38%) was the most common eating disorder, followed by digestive (59.46%), inflammatory, and rheumatic diseases (53.50%). Dietary supplementation prevalence was 88.1%, with proteins (60.81%), medicinal plants (45.13%), and vitamins (42.70%) being the most consumed. Key motivations included supporting muscle, bone, and joint strength (musculoskeletal) (83.78%) and enhancing heart and lung function for cardiorespiratory health (82.43%). However, 28% of protein users experienced adverse effects, such as myalgia, gastralgia, palpitations, and insomnia. Multivariate linear regression indicated a significant negative association of creatine with effectiveness (β = −0.485, p = 0.001). Conclusions: Overall, while the benefits of dietary and sports practices are evident, the adverse effects associated with protein supplements highlight the necessity for enhanced nutrivigilance and nutritional education to ensure safe supplements. Full article

Catalytic activity, mechanisms, and active sites were determined for methane steam reforming (MSR) over gadolinium-doped ceria (GDC) supported iridium (0.1 wt%) prepared by impregnation of GDC with iridium acetylacetonate. Isothermal steady-state rate measurements followed by micro-gas chromatography analysis were performed at 660 and 760 °C over Ir/GDC samples pretreated in N₂ or H₂ at 900 °C. Transient responses to CH₄ or H₂O step changes in isothermal conditions were carried out at 750 °C over Ir/GDC pretreated in He or H₂ using online quadrupole mass spectrometry. In the proposed mechanism, Ir/GDC proceeds through a dual-type active site associating, as follows: (i) Ir metallic particles surface as active sites for the cracking of CH₄ into reactive C species, and (ii) reducible (Ce⁴⁺) sites at GDC surface responsible for a redox mechanism involving Ce⁴⁺/Ce³⁺ sites, being reduced by reaction with reactive C into CO (or CO₂) depending on the oxidation state of GDC and re-oxidized by H₂O. Full reduction of reducible oxygen species is possible with CH₄ after He treatment, whereas only 80% is reached in CH₄ after H₂ treatment. Full article

Effective health management and accurate state of charge (SOC) estimation are crucial for the safety and longevity of lithium-ion batteries (LIBs), particularly in electric vehicles. This paper presents a health management system (HMS) that continuously monitors a 4s2p LIB pack’s parameters—current, voltage, and temperature—to mitigate risks such as overcurrent and thermal runaway while ensuring balanced charge distribution between cells. An improved online battery model (IOBM) is developed to enhance SOC estimation accuracy. The system utilises forgetting factor recursive least squares (FFRLS) for real-time parameter updates, an adaptive nonlinear sliding mode observer (ANSMO) for SOC estimation, and a long short-term memory (LSTM) network to dynamically adjust capacity based on operating conditions. Validation using the urban dynamometer driving schedule (UDDS) test demonstrated high accuracy, with the proposed battery model achieving a root mean square error (RMSE) of 12.13 mV and the LSTM achieving an RMSE of 0.0118 Ah. Regular updates to the battery’s current capacity, along with the proposed IOBM, significantly improved SOC estimation performance, maintaining estimation errors within 1.08%. Full article

Eucalyptus essential oil is widely valued for its therapeutic properties and extensive commercial applications, with its chemical composition significantly influenced by species variety, geographical origin, and environmental conditions. This study aims to develop a reliable method for identifying the geographical origin and variety of eucalyptus oil samples through the application of advanced analytical techniques combined with chemometric methods. Essential oils from Eucalyptus globulus and Eucalyptus camaldulensis were analyzed using Gas Chromatography–Flame Ionization Detection (GC–FID) and Fourier Transform Infrared (FTIR) Spectroscopy. Chemometric analyses, including Orthogonal Partial Least Squares-Discriminant Analysis (O2PLS-DA) and Hierarchical Cluster Analysis (HCA), were utilized to classify the oils based on their volatile compound profiles. Notably, O2PLS-DA was applied directly to the raw FTIR data without additional spectral processing, showcasing its robustness in handling unprocessed data. For geographical origin determination, the GC–FID model achieved a Correct Classification Rate (CCR) of 100%, with 100% specificity and 100% sensitivity for both calibration and validation sets. FTIR spectroscopy achieved a CCR of 100%, specificity of 100%, and sensitivity of 100% for the calibration set, while the validation set yielded a CCR of 95.83%, specificity of 99.02%, and sensitivity of 94.44%. In contrast, the analysis based on species variety demonstrated 100% accuracy across all metrics CCR, specificity, and sensitivity—for both calibration and validation using both techniques. These findings underscore the effectiveness of volatile and infrared spectroscopy profiling for quality control and authentication, providing robust tools for ensuring the consistency and reliability of eucalyptus essential oils in various industrial and therapeutic applications. Full article

Lichens are symbiotic organisms with unique secondary metabolism. Various metabolites from lichens have shown antimicrobial activity. Nevertheless, very few studies have investigated the antimicrobial potential of the volatile compounds they produce. This study investigates the chemical composition and antimicrobial properties of volatile compounds from Pseudevernia furfuracea collected in two regions of Morocco. Hydrodistillation was used to obtain volatile compounds from samples collected in the High Atlas and Middle Atlas. Gas chromatography–mass spectrometry (GC-MS) analysis identified phenolic cyclic compounds as the primary constituents, with atraric acid and chloroatranol being the most abundant. Additionally, eight compounds were detected in lichens for the first time. The antimicrobial activity of these compounds was assessed using disc diffusion and broth microdilution methods. Both samples demonstrated significant antimicrobial effects against multidrug-resistant human bacteria, reference microorganisms, fish pathogens, and Candida albicans, with minimum inhibitory concentrations (MICs) ranging from 1000 µg/mL to 31.25 µg/mL. This study provides the first report on the volatile compounds from Pseudevernia furfuracea and their antimicrobial effects, particularly against fish pathogens, suggesting their potential as novel antimicrobial agents for human and veterinary use. Further research is warranted to explore these findings in more detail. Full article

For biodiversity conservation and the development of protected areas, it is essential to create strategic plans that ensure the preservation and sustainable use of natural resources. Biogeography plays a crucial role in supporting these efforts by identifying and categorizing geographic areas (regionalization) that represent different biotas, as well as recognizing patterns in biodiversity distribution. Another application of regionalization is in planning species sampling and inventories. Developing a species list is vital for monitoring and understanding diversity patterns. This study focuses on the Palearctic region, specifically the areas between Morocco, the Iberian Peninsula, and France. Its aim is to compare different clustering algorithms—such as K-means++, DBSCAN, PD-clustering, Infomap, and federated heuristic optimization based on fuzzy clustering—with a reference regionalization, using environmental and soil data. Various spatial contiguity approaches were applied, including the third-degree polynomial model and principal coordinates. The results demonstrated that the hybrid approach offers a robust solution in the construction of the regions and that K-means++ and PDC produced regions with strong spatial similarity to the reference regionalization, closely aligning with the expected number of regions, especially at the biome level. Our study shows that a purely statistical regionalization can approximate a global reference regionalization, making it reproducible. Full article

Particle Swarm Optimization (PSO) is a widespread evolutionary technique that has successfully solved diverse optimization problems across various application fields. However, when dealing with more complex optimization problems, PSO can suffer from premature convergence and may become stuck in local optima. The primary goal is accelerating convergence and preventing solutions from falling into these local optima. This paper introduces a new approach to address these shortcomings and improve overall performance: utilizing a reinforcement deep learning method to carry out online adjustments of parameters in a homogeneous Particle Swarm Optimization, where all particles exhibit identical search behaviors inspired by models of social influence among uniform individuals. The present method utilizes an online parameter control to analyze and adjust each primary PSO parameter, particularly the acceleration factors and the inertia weight. Initially, a partially observed Markov decision process model at the PSO level is used to model the online parameter adaptation. Subsequently, a Hidden Markov Model classification, combined with a Deep Q-Network, is implemented to create a novel Particle Swarm Optimization named DPQ-PSO, and its parameters are adjusted according to deep reinforcement learning. Experiments on different benchmark unimodal and multimodal functions demonstrate superior results over most state-of-the-art methods regarding solution accuracy and convergence speed. Full article

Grass pea (Lathyrus sativus L.) is a nutritious legume crop well-adapted to fragile agro-ecosystems that can survive under challenging climatic conditions. The cultivation of grass pea faces stigma primarily due to the presence of β-N-Oxalyl-L-α, β-diaminopropionic acid (β-ODAP), which is associated with a risk of inducing neurolathyrism upon prolonged consumption of its grains as a staple diet. The grass pea improvement program of the International Center for Agricultural Research in the Dry Areas (ICARDA) aims to reduce β-ODAP content to a safe level along with improving yield potential and nutritional quality of grass pea. In this study, 183 germplasm accessions representing 13 different Lathyrus species and 11 L. sativus breeding lines were evaluated for β-ODAP content based on Rao protocol and mineral concentration using ICP-OES. Significant variability was observed among the accessions for the studied traits. The results showed low β-ODAP content and high mineral concentration in 25 accessions of crop wild relatives, which included L. cicera, L. ochrus, and L. cassius, with one accession IG65277 of L. cassius, in addition to two lines, IG117034 and ACC1335, of L. sativus having very low β-ODAP content. Furthermore, some accessions of L. pseudocicera, L. aphaca, L. cicera, L. marmoratus, L. gorgoni, and L. tingitanus also showed low β-ODAP content. The results showed significant positive correlations among different trait combinations, viz., K and P (r = 0.193 ***), K and Fe (r = 0.177 ***), Mn and Fe (r = 0.210 ***), Mn and Se (r = 0.137 ***), β-ODAP and Mg (r = 0.158 **), and β-ODAP and Ca (r = 0.140 **). L. cicera, L. ochrus, and L. cassius were identified as a great source for improving the mineral concentration and reducing β-ODAP content in the cultivated grass pea. Full article

The rapid expansion of the Internet of Things (IoT) has steered in a new generation of connectivity and data-driven decision-making across diverse industrial sectors. As IoT deployments continue to expand, the need for robust and reliable data management systems at the network’s edge becomes increasingly critical, especially for time-sensitive IoT applications requiring real-time responses. This study delves into the emerging research area known as the Internet of Transactional Things (Io2T) at the edge architecture, where the integration of transactional ACID properties into IoT devices and objects promises to enhance data reliability and consistency in distributed, resource-constrained environments. This paper investigates the reliability issues regarding Io2T applications at the edge and tackles more specifically the service placement problem. A formalized problem is proposed that aims to minimize the global response time of the Io2T services in edge infrastructure. The concept of an allele is introduced to address service placement using a hybrid approach for ordering transactional components. Furthermore, a demonstration is featured using a smart transportation system as a proof-of-concept. Full article

The solar drying of sewage sludge in greenhouses is one of the most used solutions in wastewater treatment plants (WWTPs). However, it presents challenges, particularly in terms of efficiency and drying time. In this context, the present study explores the drying performances of an innovative Combined Solar Greenhouse Dryer (CSGD) for sewage sludge. The system integrates rock bed storage (RBS), a solar air collector (SAC), and a solar greenhouse dryer (SGD). A numerical model, developed using TRNSYS software, predicts the drying kinetics of sewage sludge through hourly dynamic simulations based on the climatic conditions of Marrakesh, Morocco. Experimental validation confirmed the accuracy of the model. The results reveal that integrating the SAC with the SGD during the day and the RBS with the SGD at night significantly enhances the drying efficiency of the sewage sludge. During daylight hours, the SAC generates hot air, reaching maximum temperatures of 64 °C in January and 109 °C in July. Concurrently, the outlet air temperature of the RBS rises notably during the day, corresponding to the charging phase of the storage unit. Moreover, during the night, the RBS air temperature exceeds ambient temperatures by approximately 7–16 °C in January and 11–37 °C in July. This integration leads to a substantial reduction in drying time. The reduction in sewage sludge water content from 4 kg/kg of dry solid (20% dry solid content) to 0.24 kg/kg of dry solid (80% dry solid content) is related to a decrease in the drying time from 121 h to 79 h in cold periods and from 47 h to 27 h in warm periods. The drying process is significantly enhanced within the greenhouse, both during daylight and nocturnal periods. The CSGD system proves to be energy-efficient, offering an effective, high-performance solution for sewage sludge management, while also lowering operational costs for WWTPs. This innovative solar drying system combines a thermal storage bed and a solar collector to enhance drying efficiency, even in the absence of sunlight. Full article

Background: Angiogenesis is a crucial process in the growth and proliferation of cancer, enabling tumor growth through the formation of new vasculature and the supply of nutrients and oxygen to growing malignant cells. This disease-promoting process can be targeted through the inhibition of tyrosine kinase enzymes. Objectives: The objective of this study is to evaluate the anticancer potential of various Moroccan plants from different regions. While these plants have a rich history of traditional medicinal use, they have not been extensively investigated as anticancer therapies. Methods: This study employed a multifaceted approach to evaluate the anticancer potential of various Moroccan plants. Receptor–ligand docking and virtual screening were used to assess the binding affinity of phytocompounds to the EGFR and VEGFR2 receptors. Additionally, predictive pharmacokinetic analyses were conducted to evaluate the ADMET properties of the selected compounds, followed by molecular dynamics simulations to analyze the stability of the receptor–ligand complexes. Results: In our research, we identified three notable active compounds—catechin, 4-O-glucoside ferulic acid, and 3-glucoside resveratrol—in the Moroccan plant Ajuga iva L. These findings suggest that Ajuga iva L. may possess significant potential for cancer inhibition. Conclusions: This research highlights the potential of the Moroccan plant Ajuga iva L. as a source of active compounds with significant anticancer properties. Further investigation is essential to validate these findings and explore new therapeutic avenues based on these traditional resources. Full article

A quantitative risk assessment (QRA) model was developed to evaluate the risk of invasive listeriosis from the consumption of non-ready-to-eat (non-RTE) frozen vegetables. On a lot basis, the QRA model simulates Listeria monocytogenes concentration and prevalence in a “Processing module” that comprises blanching, potential recontamination and packaging, any post-packaging inactivation treatment, and within-lot end-product testing and in a subsequent “Consumer’s handling module” that encompasses portioning of frozen vegetables, defrosting, and cooking. Based on available published data, the model was coded in nine sequential R functions designed to assess the effectiveness of blanching, the improvement in processing environment hygiene, the implementation of sampling schemes at the end of processing, and improved consumer instructions on the product’s package. In a reference scenario, the model estimated that 9.4% of 500 g packages of frozen vegetables would be contaminated, although at mean levels lower than 10 CFU/g, and assuming that 20% of the portions of frozen vegetables would be left to thaw at room temperature for 2 h, the lot-level mean risk of listeriosis in the susceptible population would be 2.935 × 10⁻¹⁴ (median 5.446 × 10⁻¹⁵) for uncooked 50 g servings and 2.765 × 10⁻¹⁷ (median 5.184 × 10⁻¹⁸) for cooked 50 g servings. Analysis of selected scenarios suggested that not cooking the non-RTE product contributes to the risk to a greater extent than the level of contamination in the incoming raw vegetables, the latter in turn being more influential than the level of contamination in the processing environment. The QRA model is freely available as an R package with full documentation and can be used as a tool to inform the consideration of strengthened risk management measures in view of the current changes in consumer behavior and new diet trends. Full article

The hydrogeochemical properties and evolution of groundwater in the Essaouira syncline basin in northwestern Morocco were investigated in this study, with a total of 447 samples during different campaigns (April 2017, May 2018, March 2019, and July 2020). These samples were analyzed for major ions and stable and radioactive water isotopes (δ²H, δ¹⁸O, and ³H). With decreasing rainfall from climate change in Morocco, it is crucial to assess the sustainability of groundwater reserves. This shortage leads to the degradation of water and soil quality. To ensure sustainable water management and preserve the environment in the study area, it is necessary to assess groundwater quality for drinking and irrigation, take precautions, and establish management plans. This study assessed groundwater quality using two water quality index methods (WQI and IWQI). Several natural processes control groundwater mineralization, including the dissolution of evaporite and carbonate minerals, cation exchange phenomena, evaporation, and seawater intrusion. According to the results obtained using the WQI method, all groundwater samples in the study area are generally of poor quality and must be treated before being used for domestic purposes. Based on the results obtained by the IWQI method, the samples are suitable for use as irrigation water, especially for plants resistant to high salinity concentrations. Stable isotope measurements (δ²H and δ¹⁸O) indicate that Atlantic precipitation continuously recharges the recharge areas of the Essaouira Basin. Thus, the low values of tritium (³H) in groundwater mean that the freshwater in the Essaouira Basin is ancient. Full article