Given the significant importance of renewable or alternative energies today, extensive research is being conducted to enhance the efficiency and reduce the costs of utilizing these energy sources. Among these studies, solar energy forecasting plays a crucial role in achieving these objectives. Accurate forecasting can optimize energy yield, improve grid management, and facilitate the integration of solar power into existing energy systems, ultimately contributing to more reliable and cost-effective renewable energy solutions. This contribution investigates how data volume influences forecasting accuracy. In particular, the impacts on forecasting accuracy of varying forecast horizons and optimal data splitting for training and testing phases are examined. Additionally, the effects on forecasting Global Horizontal Irradiance (GHI) of clustering the data into 3, 5, or 7 groups using the K-means algorithm are investigated. Five different predictive models are employed— multi layer perceptron (MLP), support vector regression (SVR), random forest (RF), convolutional neural network (CNN), and long short-term memory (LSTM)— alongside the newly proposed kResCLSTM hybrid method. Using GHI observations at an arid site in southern Algeria, it is found that a 10-year time series is optimal, along with a 60%-40% split in it for the training vs. testing periods.
Olea europaea L. 1753, is one of the oldest and most distinctive trees in the Mediterranean region. Its nutritional, social, cultural, and economic value is very important for populations in arid regions, where it is widely distributed. A sign of a sustainable environment in many agricultural regions is the existence of a wide variety and abundance of arthropod groups. The main objective of the study is to evaluate the diversity of arthropods subservientin in olive agro-systems in the arid region by using several sampling techniques, namely classic sight hunting, visual inspection, Barber pots, and yellow traps. The inventory is carried out over a period of 5 months, from February to June 2023, in three stations in M’Sila (northeastern Algeria). Three classes of arthropods were found: Insecta, Arachnida, and Malacostraca. Captures were numerically dominated by Insecta, representing 96.88% of total captures. Arachnida and Malacostraca classes represented about 2.74 and 0.38%, respectively. During this research, a total of 1861 arthropod individuals were collected and identified into 83 species, 79 genera, 53 families, and 15 orders. The most abundant orders were: Diptera (42.56%), Hymenoptera (28.11%), and Coleoptera (7.32%). However, we found a significant difference in species composition according to habitat (P < 0.01). The species were determined, and the ecological indices were calculated (Shannon Value, Evenness values and Simpson reciprocal index). The dominant functional feeding groups were phytophages (41.91 %), predators (32.94%), and polyphages (22.14%). The arthropods included several olive pests such as Euphyllura olivina (Costa) (Hemiptera: Liviidae), Bactrocera oleae (Rossi) (Diptera: Tephritidae), Prays oleae (Bernard) (Lepidoptera: Praydidae), Liothrips oleae Costa (Thysanoptera: Phlaeothripidae), and Oxycenus maxwelli (Keifer) (Arachnida: Eriophyidae).
Soil reinforcement encompasses a set of techniques aimed at enhancing its mechanical or physical properties by introducing inclusions that work under tension, compression, or flexion. Some of these techniques include soil nailing, anchor tiebacks, micro-piles, bored piles, and ballasted columns. In this study, we analyze the behavior of a wall anchored by five anchor tiebacks (model of the Ain-Naadja Station 02) subjected to seismic excitations based on the Boumerdes 2003 response spectrum. The analysis is carried out using 2D and 3D finite element methods with the dynamic calculation software Plaxis version 20. The obtained results are presented in terms of horizontal stresses, shear stresses, horizontal displacements, and horizontal deformations over time along the wall (piles) at three different positions: the top, middle, and base of the wall. This is done to anticipate the effect of seismic loading on the stability of the structure.
Onion is an agricultural product widely used in daily life in fresh or dried state where microwave-drying method is one of the exploitable techniques. In such an operation, it would be important to control the effect of the output power in the device on the physicochemical quality of the food. In addition to the water content, the study of the physicochemical quality of onions concerns the color and the shrinkage rate. Monitoring and controlling these parameters is strongly recommended for microwave-dried onions. Onion slices of fixed dimensions (thickness of 10 mm and diameter of 67 mm) are microwave dried, at four different powers (90, 180, 270 and 360 W). The physicochemical quality of the samples is measured at each end of drying and all evaluations are based on minimum values. The results show that the increase of the drying power of the onions accelerates the degradation of their color and increases their shrinkage rate; nevertheless, a reduction in the drying time is quite remarkable. The browning index and shrinkage rate of onion slices are proportional to the microwave drying power. However, the drying time is inversely proportional. Finally, a drying power equal to 90 W and a thickness of the onion slices equal to 10 millimeters are recommended.
Introduction/purpose : This study investigates the seismic response of longspan continuous deck truss bridges under the effect of near-fault vertical ground motions. The primary objective is to assess how near-fault vertical seismic excitation affects the structural safety and performance of these bridges. By exploring the nuanced dynamics induced by near-fault vertical motions, the research aims to improve the understanding of the vulnerabilities and challenges faced by long-span continuous deck truss bridges during seismic events.
Methods : To achieve this objective, the truss bridge was subjected to a series of ground motions, representing natural seismic events. The seismic response of the bridge was investigated by applying the linear time history method to the 3D finite element model. This analysis focused specifically on the evaluation of base shear and displacement. The analysis was extended to include the seismic performance of truss structures. The comparison between the bridge responses with and without consideration of the vertical component of ground motion was made to clarify the effect of vertical excitation.
Results : The results show that there is a significant contribution of vertical excitation, particularly concerning the internal force in the truss elements, where it exceeded 60 % during a severe earthquake, and consequently increased the demand-to-capacity ratio in most elements of the truss bridge structure.
Conclusion : For structural engineers and designers, the results of this research suggest that neglecting to include the vertical ground motion component in the analytical assessments of this type of bridges can lead to a greater degree of uncertainty and risk, particularly in near-fault regions.
The present study aims to evaluate the effects of a cold brine (4 °C) pre-treatment on the quality of camel meat. The studied parameters are moisture content, macronutrient composition, color, pH, and shrinkage, before and after drying. Five groups of 108 camel meat slices with dimensions of 100 ×20 x 4 mm (length x width x thickness) were constituted. The control group (group 1) received no treatment. Groups 2 and 3 were immersed for 30 and 90 minutes respectively in a 19 % sodium chloride solution at 4 °C, then sun-dried. As for groups 4 and 5, they were treated in the same way for 30 and 90 minutes, but oven-dried at 65 °C. Results demonstrate that increasing the soaking time reduced the drying duration from 20 to 16 hours for oven drying and 14–12 hours for sun drying. Moisture content decreased from 73.94±0.31 % to 13.33±0.15 %, while protein levels decreased from 75.76±0.04 % to 74.465±0.02 % and 74.97±0.04 % for oven drying and 74.25±0.07 % to 74.51±0.01 % for sun drying after 30 and 90 minutes of soaking, respectively. A decrease in lipid content from 21.65±0.04 % to 19.10±0.06 % and 19.14±0.08 % was also observed during oven drying and 19.33±0.07 % to 19.12±0.09 % for sun drying. Sodium levels increased from 260.47±1.46 mg/100 g to 1690.36±1.94–1712.11±5.14 mg/100 g for oven drying and 1704.48±7.16 mg/100 g - 1714.89±4.18 mg/100 g for sun drying. Longer soaking times increased total color variation for both drying methods. By using cold brine, the nutrients in the muscle slices are preserved and the final product is lower in salinity.
This paper presents an application of a Region of Interest(ROI)-based compression technique designed to enhance the energy efficiency of visual sensor networks used in wildlife monitoring. By focusing on compressing only the most critical regions within each video frame, the proposed method significantly reduces data volume, leading to substantial energy savings during both compression and transmission stages. The integration of LoRaWAN technology further optimizes energy consumption by providing low-power, long-range communication capabilities. Experimental results demonstrate a compression ratio of 4:1, achieving overall energy savings of approximately 38% for short-range and 40% for long-range transmission compared to traditional non-ROI methods. Despite a slight reduction in image quality, the visual integrity remains acceptable for effective wildlife monitoring, and the method improves transmission success rates over varying distances. These findings highlight the potential of ROI-based compression to extend the operational lifespan of sensor nodes, offering a viable and sustainable solution for long-term environmental monitoring.
Reservoir dams in Algeria face reduced lifespans and diminished water resources due to sedimentation, which often leads to out-of-service states. To address this issue, topo-bathymetry has been identified as the preferred technique for predicting silting in dam basins. Consequently, the seek for optimal interpolation methods to conduct topo-bathymetric surveys has become increasingly important. This study compares two primary interpolation methods, deterministic and geostatistical, to determine the most effective approach for these surveys. Three specific techniques were examined in this research: inverse distance weighting, radial basis function (deterministic), and ordinary kriging (geostatistical). The study focused on five reservoir dams in Algeria, using cross-validation to assess the performance of each interpolation method. The results revealed that the geostatistical approach outperformed deterministic estimations across all five sites. The superiority of the geostatistical method was further supported by the performance metrics used in the study. Based on these findings, ordinary kriging emerged as the most suitable method for interpolating topo-bathymetric surveys for all sites, regardless of variations in morphology and spatial sampling density. This research contributes valuable insights for enhancing reservoir dam management in Algeria in order to optimize water resource allocation.
Recent climatic shifts and the growth of agricultural land have escalated the incidence of wheat field fires, presenting severe risks to both food security and local economies. This study aims to develop advanced predictive models to effectively forecast significant wheat fires in Barika, Algeria. We utilized a comprehensive dataset spanning from 2015 to 2023, which includes information on fire incidents and meteorological factors like temperature, humidity, precipitation, and wind speed. A sophisticated ensemble machine learning model was crafted, combining Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Random Forest (RF) in a stacked configuration to predict wheat fire events. Our analysis indicates that the ensemble model significantly outperforms traditional single-model approaches in terms of both accuracy and reliability. Employing these cutting-edge predictive techniques significantly bolsters firefighting measures, enhances resource management, and reduces the adverse effects of fires in agricultural zones. The employment of ensemble learning highlights its utility as a formidable tool in environmental management and crisis response. With more precise forecasts, this model facilitates improved emergency preparedness and strategic intervention plans, aiming to safeguard essential agricultural assets and support rural communities against the backdrop of mounting environmental pressures.
The significance of the Black female identity in the stratified predominantly White American society have been under scrutiny for the past half a century. Affiliated with two socially persecuted groups, African American women felt unavoidably compelled to fall under certain societal patterns and paradigms, which expectedly fail to represent their authentic sense of self. The conundrum encountered by Black females in “The Bluest Eye” is in fact aesthetically rooted; Toni Morrison vividly portrayed the destructive outcome of blindingly conforming to the standardized beauty concepts created by a dominant social group, and systematically masterminded for everyone to embrace and adapt to regardless of their cultural backgrounds and skin color. The novel exemplifies Morrison’s unswerving fight against the underestimation of Black women’s existence and the devaluation of their self-worth and identity.
Nowadays, the physiopathological and molecular mechanisms of multiple diseases have been identified, thus helping scientists to provide a clear answer, especially to those ambiguities related to chronic illnesses. This has been accomplished in part through the contribution of a key discipline known as bioinformatics. In this study, the bioinformatics approach was applied on four compounds identified in Centaurea tougourensis, using two axes of research: an in silico study to predict the molecular characteristics, medicinal chemistry attributes as well as the possible cardiotoxicity and adverse liability profile of these compounds. In this context, four compounds were selected and named, respectively, 2,5-monoformal-l-rhamnitol (compound 1), cholest-7-en-3.beta.,5.alpha.-diol-6.alpha.-benzoate (compound 2), 7,8-epoxylanostan-11-ol, 3-acetoxy- (compound 3), and 1H-pyrrole-2,5-dione, 3-ethyl-4-methyl- (compound 4). The second part looked into molecular docking, which objective was to evaluate the possible binding affinity between these compounds and the serotonin 5-hydroxytryptamine 2A (5-HT2A) receptor. Results indicated that compounds 1 and 4 were respecting Pfizer and giant Glaxo-SmithKline rules, while compounds 2 and 3 exhibited an optimal medicinal chemistry evolution 18 score. The structural and molecular features of almost all tested compounds could be considered optimal, indicating that these phyto-compounds may possess drug-likeness capacity. However, only compounds 1 and 4 could be considered non-cardiotoxic, but with a level of confidence more pronounced for compound 1 (80%). In addition, these four biocompounds could preferentially interact with G protein-coupled receptor, ion channel, transporters, and nuclear receptors. However, the heat map was less pronounced for compound 2. Data also indicated that these four compounds could possibly interact with serotonin 5-HT2A receptor, but in an antagonistic way. This research proved once again that plants could be crucial precursors of pharmaceutical substances, which could be helpful to enrich the international pharmacopoeia.
Soil erosion is the main cause of siltation in dams, on the one hand, and it is one of the main causes of degradation of the agro-pedological heritage, on the other hand. In this context, this work aims to quantify the eroded soils and their spatial distribution in the watershed of Wadi El-Hai (Aurès, Algeria), reaching the Fontaines des Gazelles dam located at the outlet of this basin. The work focuses on mapping and analyzing various thematic maps representing the key erosion factors, linking the Revised Universal Soil Loss Equation (RUSLE), with the goal of producing a synthesis map providing a quantitative spatial representation of the extent of the phenomenon in the watershed. From this map, we can confirm that the erosion phenomenon affects the entire watershed of Wad El Hai. The most severe erosion, affecting 11.60 % of the expansive territory at rates exceeding 33.6 tons per year per hectare, is predominantly concentrated in mountainous regions marked by exceptionally steep slopes. Conversely, the majority, accounting for 64.23% of the entire expanse, is situated in the plains, where erosion rates are comparatively lower at 6.7 tons per hectare per year. The assessment of potential water erosion yields disconcerting outcomes, projecting an average annual loss rate of 15.38 tons per hectare throughout the entire catchment area. The results presented in this study will serve as a vital resource and a decision-making tool, supporting the management and preservation of natural resources by policymakers and stakeholders.
