La présente étude s’intéresse à la littérature scientifique qui s’est faite autour du penseur algérien Malek Bennabi (1905-1973) en ce début du 21e siècle. Son objectif est de vérifier l’authenticité du prétendu retour de la pensée bennabienne sur la scène académique et intellectuelle, ainsi que de mesurer le degré d’intérêt que les chercheurs lui portent à travers le monde, notamment en Algérie avec l’apparition de plusieurs inédits pendant cette même période. Pour cela, un état des lieux a été entrepris, en posant comme cadre chronologique la période qui va de l’an 2000 jusqu’à 2022. Le recensement des données bibliographiques, illustré par des tableaux et des représentations graphiques, s’est fait selon plusieurs plans : le nombre ainsi que les nationalités des chercheurs, les pays depuis lesquels les travaux ont été publiés, les types de documents (livres, thèses, conférences, etc.), les catégories de ces travaux (sociologie, économie, religion, etc.) ainsi que les langues dans lesquelles ils ont été exprimés. Les résultats de cette étude révèlent un phénomène de pluralité, voire de cosmopolitisme, et un taux de publication croissant au cours des années.

The targeted resorption of socio-economic deficits at the local (municipal) level requires the use of a cartography of development in the multidimensional sense of the term, combined with that of the causes structural factors of its possible delay. This article provides for this purpose a municipal cartography of the development of M’sila province, and its sources assimilated to education, standard of living, economic activity, housing and social services. To ensure a certain objectivity in our research, we have chosen an automatic technique following the essential steps (choice of variables, normalization, weighting and aggregation) in the hierarchical classification of municipalities. This mapping of multidimensional local development clearly shows the development deficits at the municipal level, due to the delays accumulated for years, despite the generalization of basic education and attempt the local authorities to improve the economic and social conditions of the population. The results obtained show that on the whole, the urban municipalities have a local development index higher than 0.7 and rank in the first places, this index goes from a minimum (0.310) observed in the rural municipalities Tamsa, Zerzour, Sidi M’hammed and the ones located south of the province where the climate is dry and hot, the maximum index (0.860) recorded in two urban municipalities at namely M’sila and Bousaada, The high variability of development deficits shows that any development strategy would benefit from being rethought in order to provide more effective to the different situations experienced by rural municipalities in particular.

The targeted resorption of socio-economic deficits at the local (municipal) level requires the use of a cartography of development in the multidimensional sense of the term, combined with that of the causes structural factors of its possible delay. This article provides for this purpose a municipal cartography of the development of M’sila province, and its sources assimilated to education, standard of living, economic activity, housing and social services. To ensure a certain objectivity in our research, we have chosen an automatic technique following the essential steps (choice of variables, normalization, weighting and aggregation) in the hierarchical classification of municipalities. This mapping of multidimensional local development clearly shows the development deficits at the municipal level, due to the delays accumulated for years, despite the generalization of basic education and attempt the local authorities to improve the economic and social conditions of the population. The results obtained show that on the whole, the urban municipalities have a local development index higher than 0.7 and rank in the first places, this index goes from a minimum (0.310) observed in the rural municipalities Tamsa, Zerzour, Sidi M’hammed and the ones located south of the province where the climate is dry and hot, the maximum index (0.860) recorded in two urban municipalities at namely M’sila and Bousaada, The high variability of development deficits shows that any development strategy would benefit from being rethought in order to provide more effective to the different situations experienced by rural municipalities in particular.

The targeted resorption of socio-economic deficits at the local (municipal) level requires the use of a cartography of development in the multidimensional sense of the term, combined with that of the causes structural factors of its possible delay. This article provides for this purpose a municipal cartography of the development of M’sila province, and its sources assimilated to education, standard of living, economic activity, housing and social services. To ensure a certain objectivity in our research, we have chosen an automatic technique following the essential steps (choice of variables, normalization, weighting and aggregation) in the hierarchical classification of municipalities. This mapping of multidimensional local development clearly shows the development deficits at the municipal level, due to the delays accumulated for years, despite the generalization of basic education and attempt the local authorities to improve the economic and social conditions of the population. The results obtained show that on the whole, the urban municipalities have a local development index higher than 0.7 and rank in the first places, this index goes from a minimum (0.310) observed in the rural municipalities Tamsa, Zerzour, Sidi M’hammed and the ones located south of the province where the climate is dry and hot, the maximum index (0.860) recorded in two urban municipalities at namely M’sila and Bousaada, The high variability of development deficits shows that any development strategy would benefit from being rethought in order to provide more effective to the different situations experienced by rural municipalities in particular.

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.

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.

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 article focuses on the generalization of Fuglede's theorem and the solvability of operator equations. Topics include extending Fuglede's theorem to non-normal operators, deriving criteria for solving operator equations such as AX − XB = C, and using inner inverses to establish necessary and sufficient conditions for operator equation solutions.

The article focuses on the generalization of Fuglede's theorem and the solvability of operator equations. Topics include extending Fuglede's theorem to non-normal operators, deriving criteria for solving operator equations such as AX − XB = C, and using inner inverses to establish necessary and sufficient conditions for operator equation solutions.

A Vertical Axis Wind Turbine (VAWT) comprises multiple parts constructed from different materials. This complexity presents challenges in designing the blade structure. In this study, we investigated a structural optimization of a small-scale blade for a VAWT, with Finite Element Analysis (FEA) model. The purpose is to minimize the blade mass while adhering to a suite of critical wind conditions according to the IEC 61400-2 Standard. The structure made from Aluminum material simulates structure’s global behavior to determine maximum stress and deflection levels. The same structure is modeled using Glass/Epoxy composite for optimizing its design. Twenty combinations of Glass/Epoxy layers, varying in ply thickness and orientation, are simulated to find the most suitable combination. Results demonstrated that the optimization case [45°/90°/0°/−45°] obtained the minimum values of stress and deflection, is 59% lighter than Aluminum blade (initial design). The designed Glass/Epoxy composite blade is acceptable and recommended for structural safety.

A Vertical Axis Wind Turbine (VAWT) comprises multiple parts constructed from different materials. This complexity presents challenges in designing the blade structure. In this study, we investigated a structural optimization of a small-scale blade for a VAWT, with Finite Element Analysis (FEA) model. The purpose is to minimize the blade mass while adhering to a suite of critical wind conditions according to the IEC 61400-2 Standard. The structure made from Aluminum material simulates structure’s global behavior to determine maximum stress and deflection levels. The same structure is modeled using Glass/Epoxy composite for optimizing its design. Twenty combinations of Glass/Epoxy layers, varying in ply thickness and orientation, are simulated to find the most suitable combination. Results demonstrated that the optimization case [45°/90°/0°/−45°] obtained the minimum values of stress and deflection, is 59% lighter than Aluminum blade (initial design). The designed Glass/Epoxy composite blade is acceptable and recommended for structural safety.

A Vertical Axis Wind Turbine (VAWT) comprises multiple parts constructed from different materials. This complexity presents challenges in designing the blade structure. In this study, we investigated a structural optimization of a small-scale blade for a VAWT, with Finite Element Analysis (FEA) model. The purpose is to minimize the blade mass while adhering to a suite of critical wind conditions according to the IEC 61400-2 Standard. The structure made from Aluminum material simulates structure’s global behavior to determine maximum stress and deflection levels. The same structure is modeled using Glass/Epoxy composite for optimizing its design. Twenty combinations of Glass/Epoxy layers, varying in ply thickness and orientation, are simulated to find the most suitable combination. Results demonstrated that the optimization case [45°/90°/0°/−45°] obtained the minimum values of stress and deflection, is 59% lighter than Aluminum blade (initial design). The designed Glass/Epoxy composite blade is acceptable and recommended for structural safety.

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.

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.

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.

Water resources are facing significant challenges in result of rapidly growing demand, deteriorating quality, and the effects of climate change. Today, water quantity and quality issues have become prevalent in various regions across the globe, affecting both northern and southern territories. Among the sectors reliant on this resource, irrigation stands out as the largest consumer of water. When surface water becomes inaccessible due to insufficient precipitation or other factors, the use of groundwater becomes the only viable alternative for irrigation. The Remila Plain (Khenchela) is located in an endorean watershed in northeastern Algeria and extends over 250 km2 in a synclinal basin filled with water from the Mio-Plio Quaternary - the main aquifer of the region, widely used for irrigation. The aim of this work is to study the hydrochemistry of these waters, as well as the evolution of mineralisation, the identification of the origin of the chemistry, and the suitability of these waters for irrigation. Initial results indicate an evolution of mineralisation in the direction of groundwater flow, with electrical conductivity values varying between 1000μS/cm in the recharge zones, and 2700μS/cm at the outlet. This mineralisation is mainly due to the dissolution of evaporitic minerals and the alteration of silicates. In addition, the various water quality indices used indicate that the water can be used for irrigation without major risk to plants and soils.

Water resources are facing significant challenges in result of rapidly growing demand, deteriorating quality, and the effects of climate change. Today, water quantity and quality issues have become prevalent in various regions across the globe, affecting both northern and southern territories. Among the sectors reliant on this resource, irrigation stands out as the largest consumer of water. When surface water becomes inaccessible due to insufficient precipitation or other factors, the use of groundwater becomes the only viable alternative for irrigation. The Remila Plain (Khenchela) is located in an endorean watershed in northeastern Algeria and extends over 250 km2 in a synclinal basin filled with water from the Mio-Plio Quaternary - the main aquifer of the region, widely used for irrigation. The aim of this work is to study the hydrochemistry of these waters, as well as the evolution of mineralisation, the identification of the origin of the chemistry, and the suitability of these waters for irrigation. Initial results indicate an evolution of mineralisation in the direction of groundwater flow, with electrical conductivity values varying between 1000μS/cm in the recharge zones, and 2700μS/cm at the outlet. This mineralisation is mainly due to the dissolution of evaporitic minerals and the alteration of silicates. In addition, the various water quality indices used indicate that the water can be used for irrigation without major risk to plants and soils.

Water resources are facing significant challenges in result of rapidly growing demand, deteriorating quality, and the effects of climate change. Today, water quantity and quality issues have become prevalent in various regions across the globe, affecting both northern and southern territories. Among the sectors reliant on this resource, irrigation stands out as the largest consumer of water. When surface water becomes inaccessible due to insufficient precipitation or other factors, the use of groundwater becomes the only viable alternative for irrigation. The Remila Plain (Khenchela) is located in an endorean watershed in northeastern Algeria and extends over 250 km2 in a synclinal basin filled with water from the Mio-Plio Quaternary - the main aquifer of the region, widely used for irrigation. The aim of this work is to study the hydrochemistry of these waters, as well as the evolution of mineralisation, the identification of the origin of the chemistry, and the suitability of these waters for irrigation. Initial results indicate an evolution of mineralisation in the direction of groundwater flow, with electrical conductivity values varying between 1000μS/cm in the recharge zones, and 2700μS/cm at the outlet. This mineralisation is mainly due to the dissolution of evaporitic minerals and the alteration of silicates. In addition, the various water quality indices used indicate that the water can be used for irrigation without major risk to plants and soils.

Water resources are facing significant challenges in result of rapidly growing demand, deteriorating quality, and the effects of climate change. Today, water quantity and quality issues have become prevalent in various regions across the globe, affecting both northern and southern territories. Among the sectors reliant on this resource, irrigation stands out as the largest consumer of water. When surface water becomes inaccessible due to insufficient precipitation or other factors, the use of groundwater becomes the only viable alternative for irrigation. The Remila Plain (Khenchela) is located in an endorean watershed in northeastern Algeria and extends over 250 km2 in a synclinal basin filled with water from the Mio-Plio Quaternary - the main aquifer of the region, widely used for irrigation. The aim of this work is to study the hydrochemistry of these waters, as well as the evolution of mineralisation, the identification of the origin of the chemistry, and the suitability of these waters for irrigation. Initial results indicate an evolution of mineralisation in the direction of groundwater flow, with electrical conductivity values varying between 1000μS/cm in the recharge zones, and 2700μS/cm at the outlet. This mineralisation is mainly due to the dissolution of evaporitic minerals and the alteration of silicates. In addition, the various water quality indices used indicate that the water can be used for irrigation without major risk to plants and soils.

Water resources are facing significant challenges in result of rapidly growing demand, deteriorating quality, and the effects of climate change. Today, water quantity and quality issues have become prevalent in various regions across the globe, affecting both northern and southern territories. Among the sectors reliant on this resource, irrigation stands out as the largest consumer of water. When surface water becomes inaccessible due to insufficient precipitation or other factors, the use of groundwater becomes the only viable alternative for irrigation. The Remila Plain (Khenchela) is located in an endorean watershed in northeastern Algeria and extends over 250 km2 in a synclinal basin filled with water from the Mio-Plio Quaternary - the main aquifer of the region, widely used for irrigation. The aim of this work is to study the hydrochemistry of these waters, as well as the evolution of mineralisation, the identification of the origin of the chemistry, and the suitability of these waters for irrigation. Initial results indicate an evolution of mineralisation in the direction of groundwater flow, with electrical conductivity values varying between 1000μS/cm in the recharge zones, and 2700μS/cm at the outlet. This mineralisation is mainly due to the dissolution of evaporitic minerals and the alteration of silicates. In addition, the various water quality indices used indicate that the water can be used for irrigation without major risk to plants and soils.