This paper presents a novel metaheuristic binary crow search algorithm (CSA) designed for positive-unlabeled (PU) learning, a paradigm where only positive and unlabeled data are available, with applications in many diversified fields, such as medical diagnosis and fraud detection. The algorithm represent a useful adaptation of CSA, itself inspired by the food-hiding behavior of crows. The proposed BiCSA-PUL (binary crow search algorithm for positive-unlabeled learning) selects reliable negative samples from unlabeled data using binary vectors, and updates positions employing Hamming distance, guided by a modified F1-score, as fitness function. The algorithm was tested on 30 samples from 10 diverse datasets, outperforming seven state-of-the-art PU learning methods. The results reveal that BiCSA-PUL provides a robust and efficient approach for PU learning, significantly improving fitness and reliability. This work opens new avenues for applying metaheuristic optimization methods to challenging classification problems with limited labeled data. The main limitations are the potentially time-intensive process of parameters tuning and reliance on initial sampling.

This paper presents a novel metaheuristic binary crow search algorithm (CSA) designed for positive-unlabeled (PU) learning, a paradigm where only positive and unlabeled data are available, with applications in many diversified fields, such as medical diagnosis and fraud detection. The algorithm represent a useful adaptation of CSA, itself inspired by the food-hiding behavior of crows. The proposed BiCSA-PUL (binary crow search algorithm for positive-unlabeled learning) selects reliable negative samples from unlabeled data using binary vectors, and updates positions employing Hamming distance, guided by a modified F1-score, as fitness function. The algorithm was tested on 30 samples from 10 diverse datasets, outperforming seven state-of-the-art PU learning methods. The results reveal that BiCSA-PUL provides a robust and efficient approach for PU learning, significantly improving fitness and reliability. This work opens new avenues for applying metaheuristic optimization methods to challenging classification problems with limited labeled data. The main limitations are the potentially time-intensive process of parameters tuning and reliance on initial sampling.

This paper presents a novel metaheuristic binary crow search algorithm (CSA) designed for positive-unlabeled (PU) learning, a paradigm where only positive and unlabeled data are available, with applications in many diversified fields, such as medical diagnosis and fraud detection. The algorithm represent a useful adaptation of CSA, itself inspired by the food-hiding behavior of crows. The proposed BiCSA-PUL (binary crow search algorithm for positive-unlabeled learning) selects reliable negative samples from unlabeled data using binary vectors, and updates positions employing Hamming distance, guided by a modified F1-score, as fitness function. The algorithm was tested on 30 samples from 10 diverse datasets, outperforming seven state-of-the-art PU learning methods. The results reveal that BiCSA-PUL provides a robust and efficient approach for PU learning, significantly improving fitness and reliability. This work opens new avenues for applying metaheuristic optimization methods to challenging classification problems with limited labeled data. The main limitations are the potentially time-intensive process of parameters tuning and reliance on initial sampling.

The global wind energy industry achieved a significant milestone by reaching a total capacity of one terawatt (TW) by the end of 2023, underscoring the increasing importance of wind energy as a sustainable energy source (Global Wind Energy Outlook, 2022). This study focuses on the simulation and dynamic analysis of an H-Darrieus wind turbine rotor using 3D Finite Element Analysis (FEA). Key structural parameters, including natural frequencies, associated vibration modes, and mass participation rates, were determined to optimize the rotor performance. A novel blade design is proposed in this work, offering a lighter and more robust alternative to traditional rotor blades manufactured from composites, like fiberglass-polyester, fiberglass-epoxy, or combinations with wood and carbon. The lighter design enhances the startup performance at low wind speeds, while the improved strength and fixing mechanisms ensure resilience against the increasingly severe sandstorms reported in recent years. The vibration dynamics of the rotor under critical wind loads were analyzed using the SolidWorks Simulation software, yielding highly satisfactory results. The stability and reliability of the rotor were validated, as the dynamic performance indices, and the quality criteria meet the requirements for optimal operation.

The global wind energy industry achieved a significant milestone by reaching a total capacity of one terawatt (TW) by the end of 2023, underscoring the increasing importance of wind energy as a sustainable energy source (Global Wind Energy Outlook, 2022). This study focuses on the simulation and dynamic analysis of an H-Darrieus wind turbine rotor using 3D Finite Element Analysis (FEA). Key structural parameters, including natural frequencies, associated vibration modes, and mass participation rates, were determined to optimize the rotor performance. A novel blade design is proposed in this work, offering a lighter and more robust alternative to traditional rotor blades manufactured from composites, like fiberglass-polyester, fiberglass-epoxy, or combinations with wood and carbon. The lighter design enhances the startup performance at low wind speeds, while the improved strength and fixing mechanisms ensure resilience against the increasingly severe sandstorms reported in recent years. The vibration dynamics of the rotor under critical wind loads were analyzed using the SolidWorks Simulation software, yielding highly satisfactory results. The stability and reliability of the rotor were validated, as the dynamic performance indices, and the quality criteria meet the requirements for optimal operation.

The global wind energy industry achieved a significant milestone by reaching a total capacity of one terawatt (TW) by the end of 2023, underscoring the increasing importance of wind energy as a sustainable energy source (Global Wind Energy Outlook, 2022). This study focuses on the simulation and dynamic analysis of an H-Darrieus wind turbine rotor using 3D Finite Element Analysis (FEA). Key structural parameters, including natural frequencies, associated vibration modes, and mass participation rates, were determined to optimize the rotor performance. A novel blade design is proposed in this work, offering a lighter and more robust alternative to traditional rotor blades manufactured from composites, like fiberglass-polyester, fiberglass-epoxy, or combinations with wood and carbon. The lighter design enhances the startup performance at low wind speeds, while the improved strength and fixing mechanisms ensure resilience against the increasingly severe sandstorms reported in recent years. The vibration dynamics of the rotor under critical wind loads were analyzed using the SolidWorks Simulation software, yielding highly satisfactory results. The stability and reliability of the rotor were validated, as the dynamic performance indices, and the quality criteria meet the requirements for optimal operation.

Let (X,d,μ) be a space of homogeneous type and L be a nonnegative self-adjoint operator on L2(X) whose heat kernels satisfy Gaussian upper bounds. In this article, we introduce the weighted variable Besov space associated with the operator L and demonstrate that Peetre maximal functions can be used to characterize this space. Furthermore, we provide a detailed study of its atomic decompositions.

Let (X,d,μ) be a space of homogeneous type and L be a nonnegative self-adjoint operator on L2(X) whose heat kernels satisfy Gaussian upper bounds. In this article, we introduce the weighted variable Besov space associated with the operator L and demonstrate that Peetre maximal functions can be used to characterize this space. Furthermore, we provide a detailed study of its atomic decompositions.

Let (X,d,μ) be a space of homogeneous type and L be a nonnegative self-adjoint operator on L2(X) whose heat kernels satisfy Gaussian upper bounds. In this article, we introduce the weighted variable Besov space associated with the operator L and demonstrate that Peetre maximal functions can be used to characterize this space. Furthermore, we provide a detailed study of its atomic decompositions.

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).

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).

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).

Our study aims to analyse two communicative schemata: online interaction (IL) and radio interaction (IR). The objective is to understand the functioning of phatic expression and its characteristics in the opening and closing rituals in IL & IR. A descriptive analytical approach was adopted to conduct a qualitative analysis of a corpus consisting of IR on Alger Chaine 3 and IL in a Messenger group (Facebook). This analysis revealed the presence of phatic elements in the openings and closures of exchanges, both in IR and online interactions. It allowed contrasting these two types of interactions, highlighting the specificity of IL, especially as users shape their linguistic and interactive behaviour in the digital environment.

Our study aims to analyse two communicative schemata: online interaction (IL) and radio interaction (IR). The objective is to understand the functioning of phatic expression and its characteristics in the opening and closing rituals in IL & IR. A descriptive analytical approach was adopted to conduct a qualitative analysis of a corpus consisting of IR on Alger Chaine 3 and IL in a Messenger group (Facebook). This analysis revealed the presence of phatic elements in the openings and closures of exchanges, both in IR and online interactions. It allowed contrasting these two types of interactions, highlighting the specificity of IL, especially as users shape their linguistic and interactive behaviour in the digital environment.

L’écriture de Rachid Mimouni s’inscrit dans une dynamique contestataire qui s’oppose à la parole paternelle et se rebelle contre les régimes en place. Dans les années 1980, le roman Tombéza se distingue de l’écriture débridée de Boujedra par un discours corrosif maîtrisé et une représentation impitoyablement réaliste de l’horreur quotidienne d’une Algérie défigurée. Cet article propose de relire le texte en mobilisant la génétique textuelle, l’image littéraire et le concept de paratopie, en les conjuguant avec les philosophies du devenir et la notion de rhizome. L’objectif est d’analyser l’écartèlement du moi chez le personnage de Tombéza, érigé en paria, et de montrer comment la paratopie de l’écrivain sert à négocier l’intenable entre deux mondes, tout en exprimant la rupture par la démodélisation de l’œuvre en rhizome. Nous verrons comment cette « littérature-monde » se conçoit à travers l’exil de l’être déraciné Tombéza, qui devient le support du discours paratopique de Mimouni, se déplaçant tel un archipel pour se reconstruire en une identité multiculturelle. Ce processus s’opère par une répétition différentielle, incarnée par une écriture de l’urgence.

L’écriture de Rachid Mimouni s’inscrit dans une dynamique contestataire qui s’oppose à la parole paternelle et se rebelle contre les régimes en place. Dans les années 1980, le roman Tombéza se distingue de l’écriture débridée de Boujedra par un discours corrosif maîtrisé et une représentation impitoyablement réaliste de l’horreur quotidienne d’une Algérie défigurée. Cet article propose de relire le texte en mobilisant la génétique textuelle, l’image littéraire et le concept de paratopie, en les conjuguant avec les philosophies du devenir et la notion de rhizome. L’objectif est d’analyser l’écartèlement du moi chez le personnage de Tombéza, érigé en paria, et de montrer comment la paratopie de l’écrivain sert à négocier l’intenable entre deux mondes, tout en exprimant la rupture par la démodélisation de l’œuvre en rhizome. Nous verrons comment cette « littérature-monde » se conçoit à travers l’exil de l’être déraciné Tombéza, qui devient le support du discours paratopique de Mimouni, se déplaçant tel un archipel pour se reconstruire en une identité multiculturelle. Ce processus s’opère par une répétition différentielle, incarnée par une écriture de l’urgence.

Diesel engines (DEs) commonly power pumps used in agricultural and grassland irrigation. However, relying on unpredictable and costly fuel sources for DEs pose’s challenges related to availability, reliability, maintenance, and lifespan. Addressing these environmental concerns, this study introduces an emulation approach for photovoltaic (PV) water pumping (WP) systems. Emulation offers a promising alternative due to financial constraints, spatial limitations, and climate dependency in full-scale systems. The proposed setup includes three key elements: a PV system emulator employing back converter control to replicate PV panel characteristics, a boost converter with an MPPT algorithm for efficient power tracking across diverse conditions, and a motor pump (MP) emulator integrating an induction motor connected to a DC generator to simulate water pump behaviors. Precise induction motor control is achieved through a controlled inverter. This work innovatively combines PV and WP emulation while optimizing system dynamics, aiming to develop a comprehensive emulator and evaluate an enhanced control algorithm. An optimized scalar control strategy regulates the water MP, demonstrated through MATLAB/Simulink simulations that highlight superior performance and responsiveness to solar irradiation variations compared to conventional MPPT techniques. Experimental validation using the dSPACE control desk DS1104 confirms the emulator’s ability to faithfully reproduce genuine solar panel characteristics.

Diesel engines (DEs) commonly power pumps used in agricultural and grassland irrigation. However, relying on unpredictable and costly fuel sources for DEs pose’s challenges related to availability, reliability, maintenance, and lifespan. Addressing these environmental concerns, this study introduces an emulation approach for photovoltaic (PV) water pumping (WP) systems. Emulation offers a promising alternative due to financial constraints, spatial limitations, and climate dependency in full-scale systems. The proposed setup includes three key elements: a PV system emulator employing back converter control to replicate PV panel characteristics, a boost converter with an MPPT algorithm for efficient power tracking across diverse conditions, and a motor pump (MP) emulator integrating an induction motor connected to a DC generator to simulate water pump behaviors. Precise induction motor control is achieved through a controlled inverter. This work innovatively combines PV and WP emulation while optimizing system dynamics, aiming to develop a comprehensive emulator and evaluate an enhanced control algorithm. An optimized scalar control strategy regulates the water MP, demonstrated through MATLAB/Simulink simulations that highlight superior performance and responsiveness to solar irradiation variations compared to conventional MPPT techniques. Experimental validation using the dSPACE control desk DS1104 confirms the emulator’s ability to faithfully reproduce genuine solar panel characteristics.

Diesel engines (DEs) commonly power pumps used in agricultural and grassland irrigation. However, relying on unpredictable and costly fuel sources for DEs pose’s challenges related to availability, reliability, maintenance, and lifespan. Addressing these environmental concerns, this study introduces an emulation approach for photovoltaic (PV) water pumping (WP) systems. Emulation offers a promising alternative due to financial constraints, spatial limitations, and climate dependency in full-scale systems. The proposed setup includes three key elements: a PV system emulator employing back converter control to replicate PV panel characteristics, a boost converter with an MPPT algorithm for efficient power tracking across diverse conditions, and a motor pump (MP) emulator integrating an induction motor connected to a DC generator to simulate water pump behaviors. Precise induction motor control is achieved through a controlled inverter. This work innovatively combines PV and WP emulation while optimizing system dynamics, aiming to develop a comprehensive emulator and evaluate an enhanced control algorithm. An optimized scalar control strategy regulates the water MP, demonstrated through MATLAB/Simulink simulations that highlight superior performance and responsiveness to solar irradiation variations compared to conventional MPPT techniques. Experimental validation using the dSPACE control desk DS1104 confirms the emulator’s ability to faithfully reproduce genuine solar panel characteristics.

Diesel engines (DEs) commonly power pumps used in agricultural and grassland irrigation. However, relying on unpredictable and costly fuel sources for DEs pose’s challenges related to availability, reliability, maintenance, and lifespan. Addressing these environmental concerns, this study introduces an emulation approach for photovoltaic (PV) water pumping (WP) systems. Emulation offers a promising alternative due to financial constraints, spatial limitations, and climate dependency in full-scale systems. The proposed setup includes three key elements: a PV system emulator employing back converter control to replicate PV panel characteristics, a boost converter with an MPPT algorithm for efficient power tracking across diverse conditions, and a motor pump (MP) emulator integrating an induction motor connected to a DC generator to simulate water pump behaviors. Precise induction motor control is achieved through a controlled inverter. This work innovatively combines PV and WP emulation while optimizing system dynamics, aiming to develop a comprehensive emulator and evaluate an enhanced control algorithm. An optimized scalar control strategy regulates the water MP, demonstrated through MATLAB/Simulink simulations that highlight superior performance and responsiveness to solar irradiation variations compared to conventional MPPT techniques. Experimental validation using the dSPACE control desk DS1104 confirms the emulator’s ability to faithfully reproduce genuine solar panel characteristics.