Université de Tébessa

The age-structured approach plays a crucial role in epidemiological modelling as it accounts for age-specific variations in susceptibility, transmission and disease progressions, providing a more accurate description of disease dynamics. In this paper, we create an age-structured epidemic model that incorporates age-dependent susceptibility and latency, as well as a relapse phase, with the objective of investigating the global dynamics of this model under the impact of that combination. The very important threshold parameter $\mathcal{R}_{0}$ was introduced, and it has shown that it completely controls the stability of each equilibrium of the model. Based on the Lyapunov functional approach, we show that the disease-free equilibrium is globally asymptotically stable when $\mathcal{R}_{0}<1$, while the positive endemic equilibrium is globally asymptotically stable whenever $\mathcal{R}_{0}>1$. Our results suggest that early diagnostic of latency individuals, reduction in transmission rate and improvements in treatment and heath-care of infected individuals may effectively control the spread of the disease.

Enhancing the fire resilience of concrete structures is a critical challenge in construction engineering, prompting the investigation of innovative additives to improve the performance of reactive powder concrete (RPC) under high-temperature conditions. This study explores the effects of incorporating waste marble powder (WMP) and metal fibers (MF) on RPC’s physical and mechanical properties exposed to elevated temperatures. Two RPC formulations were prepared: a reference RPC (C1-RPC) without additives and an experimental RPC (C2-RPC) with 10% WMP and 2% MF, maintaining a consistent water-to-binder ratio of 0.25. The samples were subjected to temperature levels of 20 °C, 200 °C, 500 °C, and 800 °C. Key parameters, including mass loss, water porosity, compressive strength, and flexural tensile strength, were measured at 28 and 206 days. In addition, Scanning Electron Microscopy (SEM) was used to analyze the microstructural changes of C2-RPC after high-temperature exposure. The experimental results revealed that C2-RPC exhibited enhanced physical and mechanical properties compared to C1-RPC, particularly regarding fire resistance. Incorporating 10% WMP and 2% MF significantly improved RPC’s durability and structural integrity at elevated temperatures. These findings suggest that using WMP and MF in RPC formulations offers a sustainable and practical approach to improving the fire performance of concrete, contributing to more resilient construction materials.

Subject and purpose of work This article aims to analyze the relationship between inflation rates (INF) and unemployment rates (UR) in the Algerian economy during the period 1970-2021 by studying the extent to which the unemployment rate responds to shocks and structural changes that occur at the level of the inflation rate. Materials and methods Use the structural VAR (SVAR) approach, based on RStudio output. Results The estimation results provide strong evidence in favor of the VAR (SVAR) approach. Conclusions The application of Impulse–Response Functions (IRFs) and analysis of variance (ANOVA) reveals that the occurrence of a structural shock in the inflation rate (INF) by one standard deviation leads to a positive effect on the unemployment rate (UNEM) at the beginning of the first period, and then it gradually decreases to become almost nonexistent. Therefore, the improvement in Consumer Price Index (CPI) leads to the absorption and reduction of unemployment rates (UR) to achieve stability and confirm the existence of the Phillips curve.

The introduction of fractional derivatives into the cancer treatment model continues to be improved with current cancer treatment. In this work, we define a new time-fractional nonlinear Burgess equation in order to model the brain tumor growth under treatment. The new mathematical model is in agreement with the clinical data proposed by Stupp et al. (2005). The numerical processing of this model is based on the splitting method which makes it possible to avoid and relax several numerical problems. The numerical results obtained are very satisfactory and excellent.

Arid steppe rangelands in North Africa are highly significant ecosystems that are exceedingly sensitive to global warming and are also influenced by severe grazing and heavy utilization practices. Consequently, it is imperative to conduct extensive investigations regarding the impact of overgrazing due to increased sheep populations on plant diversity in these regions. The objective of this study is to examine the effect of two grazing managements (grazing-excluded vs. free-grazing) on floristic diversity in the arid steppe rangelands of North Africa. Sampling encompassed 10 sites, with 5 freely accessible to livestock and 5 protected from grazing. Within each site, three 200-meter transects were established to survey and quantify plant species abundance. Alpha (species richness and diversity) and beta (qualitative and quantitative similarity analysis) biodiversity parameters were evaluated at both small and large spatial scales. The findings demonstrated a substantial disparity in plant diversity between grazing-excluded rangelands and free-grazed rangelands. Plant community diversity and stability parameters were notably higher in grazing-excluded areas. The taxonomic structure of plant communities also exhibited greater stability in grazing-excluded steppe areas. Specifically, the grazing-excluded sites displayed superior diversity metrics, including species richness (93), Shannon index (3.2), and Simpson reciprocal index (5.5), in comparison to severely grazed sites (61, 2.6, and 4.4), respectively). The influence of severe grazing had a more pronounced effect on ephemeral species rather than perennials, emphasizing the heightened vulnerability of these plants to overgrazing effect or inadequate grassland management practices. This effect coincided with heterogeneity in floristic composition between sites with free continuous livestock access and those protected from grazing. Furthermore, analysis of similarity at different spatial scales revealed an increase in diversity at small scales contrasted with a decrease at larger scales. Grazing exerted discernible effects on floristic composition, particularly affecting ephemeral species, albeit primarily at small scales. At larger scales, the impact of grazing was not detected. These findings underscore the complex relationship between grazing practices and plant diversity dynamics in arid steppe ecosystems, emphasizing the importance of sustainable management strategies to preserve biodiversity in these vulnerable habitats.

We prove the nonexistence of global solutions for the following wave equations with structural damping and nonlinear memory source term {u}_{tt}+{\left(-\Delta )}^{\tfrac{\alpha }{2}}u+{\left(-\Delta )}^{\tfrac{\beta }{2}}{u}_{t}=\underset{0}{\overset{t}{\int }}{\left(t-s)}^{\delta -1}{| u\left(s)| }^{p}{\rm{d}}s and {u}_{tt}+{\left(-\Delta )}^{\tfrac{\alpha }{2}}u+{\left(-\Delta )}^{\tfrac{\beta }{2}}{u}_{t}=\underset{0}{\overset{t}{\int }}{\left(t-s)}^{\delta -1}{| {u}_{s}\left(s)| }^{p}{\rm{d}}s, posed in \left(x,t)\in {{\mathbb{R}}}^{N}\times \left[0,\infty ) , where u=u\left(x,t) is the real-valued unknown function, p\gt 1 , \alpha ,\beta \in \left(0,2) , \delta \in \left(0,1) , by using the test function method under suitable sign assumptions on the initial data. Furthermore, we give an upper bound estimate of the life span of solutions.

Biochar has been recognized for its potential to improve the fertility soils by reducing the reliance on chemical fertilizers, mitigating carbon emissions, and fostering soil microbial growth. This study aimed to evaluate the impact of biochar addition on the physicochemical properties of arid and semi-arid soils containing microplastics, while also assessing its effect on Barley (Hordeum vulgare) yield under drought stress. The experiment was conducted in a glass greenhouse. Plastic pots containing 3 kg of soil were each planted with 6 barley grains. Biochar was applied at three doses (B0 = 0 g biochar/kg soil, B1 = 6 g biochar/kg soil, B2 = 10 g biochar/kg soil), while microplastics were added at three levels (M0 = Control without microplastics, M1 = 0.5 g/kg soil, and M2 = 1 g/kg soil) on the same sowing date. Water stress was induced when the plants reached the four-leaf stage. ANOVAs and Tukey post-hoc tests were employed for multiple mean comparisons of soil and plant parameters. Drought stress and microplastics negatively influenced soil parameters namely soil moisture, organic carbon, and nitrates, while also affecting electrical conductivity and pH. Biochar exhibited minimal effect on soil properties but significantly altered pH, nitrates, and total CaCO3. Plant chlorophyll levels decreased under stress, particularly with microplastic dose M1. However, biochar and microplastics enhanced chlorophyll a content, except for dose B1 of biochar, which leads to a decrease in chlorophyll b (0.91 ± 0.138 μg/g FM). Microplastics, at dose M2, improved chlorophyll b content (1.11 ± 0.090 μg/g FM). Aboveground biomass, leaf area, and yield were generally unaffected by tested stresses. Nonetheless, barley grain yield decreased in biochar and microplastic dose M1 (0.47 ± 0.108 g/plant), while it improved with microplastic dose M2 (0.65 ± 0.168 g/plant). Leaf relative water content increased under water stress and microplastics but not with biochar alone. Interaction between microplastics and biochar enhanced plant water content. Drought stress and microplastics diminished soil parameters, whereas biochar lowered nitrates and pH without significantly affecting soil organic carbon. Plant productivity parameters generally exhibited no significant change under water stress, microplastics, or biochar, except for yield and chlorophyll pigments.

To understand the distribution of Atlas pistachio (Pistacia atlantica Desf.) in Algeria, we analyzed the environmental factors influencing its habitat. This study employs an ensemble modelling (EM) approach, a robust predictive technique in ecological niche modelling that enables us to identify critical environmental drivers affecting plant distributions across different ecosystems’ focal species. The EM incorporated four prediction algorithms (generalized linear model, boosted regression trees, random forest, and maximum entropy algorithms); we modelled Atlas pistachio’s niche with 2810 occurrence points and 32 environmental variables, including climatic, edaphic, topographic, and anthropogenic factors. The model demonstrated high accuracy, with an AUC of 0.97 and TSS of 0.88. Key factors influencing distribution were precipitation in the driest month (Bio14), soil bulk density (BD), cation exchange capacity (CEC), human modification, and average diurnal amplitude (Bio2), with a relative importance of 20.1%, 12.7%, 6.7%, 4.9%, and 3.1%, respectively. These findings underscore the utility of ensemble modelling to pinpoint specific environmental variables critical to the species’ presence and ecological adaptability, which has broader implications for other plant species in arid landscapes. Notably, the probability of Atlas pistachio occurrence increased with BD and decreased with CEC and human influence. Our results emphasize the EM approach as a versatile tool in ecological modelling, facilitating species-specific analyses that contribute to broader ecological restoration efforts, especially in degraded arid and semi-arid regions. This study advances our understanding of Atlas pistachio’s environmental requirements and highlights the importance of EM in developing targeted programs to restore degraded ecosystems. Graphical abstract

Background: Ticks are ectoparasites and can be vectors of a wide range of pathogens, posing significant health risks to livestock. In the Sahara Desert of Algeria, particularly among one-humped camels (Camelus dromedarius), there is a need to better understand the factors influencing tick infestation patterns to improve livestock management and health outcomes. Objectives: This study aimed to investigate the prevalence, intensity, and abundance of hard-bodied ticks (Acari: Ixodidae) among dromedaries, examining both intrinsic factors (sex, age, coat color) and extrinsic variables (farming systems, vegetation types, climate zones, and elevation) that might influence tick infestation in this region. Methods: Ticks were collected from 286 dromedaries across nine sites in the pre-Saharan regions of Algeria, with elevations ranging from 736 m to 980 m. The sampled camels, which ranged in age from 6 days to 21 years, were examined for tick infestations. The ticks were identified through macroscopic and microscopic methods, and their abundance was analyzed in relation to the camels' characteristics and environmental factors. Three breeding systems were recognized: extensive, intensive, and mixed. Results: A total of 980 ticks were collected, with Hyalomma dromedarii Koch, 1844 being the most abundant species (553 specimens), followed by Hyalomma impeltatum Schulze & Schlottke, 1930 (393 specimens), and Hyalomma excavatum Koch, 1844 (34 specimens). H. dromedarii showed a preference for parasitizing brown-coated dromedaries and exhibited significantly higher infestation levels during spring (p < 0.001). No significant association was observed between tick infestation and the camels' age or sex (p > 0.05). However, the farming system had a significant impact on tick abundance, with extensive and mixed systems showing higher tick burdens compared to intensive systems (p < 0.01). Additionally, the vegetation type, climate zone, and foraging habitat elevation were found to significantly influence tick densities and prevalence. Conclusion: This study provides essential insights into the tick infestation dynamics in dromedaries in drylands of Algeria. It highlights the influence of coat color, seasonality, and farming practices on tick burden, with brown-coated camels being more susceptible during the spring. The findings underline the importance of considering both intrinsic and extrinsic factors when developing effective tick control strategies, especially for camels raised in extensive or mixed farming systems in diverse arid rangelands. Future research should expand the scope to cover other arid regions in North Africa for a comprehensive understanding of tick-host dynamics.

In this study, we investigate the thermal properties of the relativistic Klein-Gordon oscillator with non-minimal coupling in one, two, and three dimensions within the framework of superstatistics theory. We focus on three distinct distributions: Gamma, Log-Normal, and F-distributions, each described by a specific probability density function f(β)$f(\beta )$. To compute the partition function, we apply the Euler-MacLaurin formula, incorporating the low-energy asymptotics approximation of superstatistics and accounting for the remainder term Ri$R_{i}$. Our study involves a detailed analysis of how entropy SS and specific heat Cv$C_{v}$ vary with temperature 1/β$1/\beta$ and the universal parameter qq, based on the derived partition functions. The variations in these thermodynamic quantities are explored across different dimensionalities and statistical frameworks, providing insights into the interplay between statistical distributions and the thermal dynamics of the system. This approach allows us to understand the influence of non-equilibrium conditions and fluctuating temperature fields on the behavior of relativistic quantum systems. By extending the analysis to multiple dimensions and distribution types, we aim to offer a comprehensive view of how superstatistical distributions affect the thermodynamic properties of the Klein-Gordon oscillator, thus contributing to the broader understanding of thermal dynamics in relativistic systems.

In this study, a comprehensive approach is presented for the sizing and management of hybrid renewable energy systems (HRESs) that incorporate a variety of energy sources, while emphasizing the role of artificial neural networks (ANNs) in system management. For optimal sizing of an HRES, the monthly average method wherein historical weather data are used to calculate the monthly averages of solar irradiance and wind speed, offering a well-balanced strategy for system sizing. This ensures that the HRES is appropriately scaled to meet the actual energy requirements of the specified location, avoiding the pitfalls of over- and under-sizing, and thereby enhancing the operational efficiency. Furthermore, the study details a cutting-edge strategy that employs ANNs for managing the inherent complexities of HRESs. It elaborates on the design, modeling, and control strategies for the HRES components by utilizing Matlab/Simulink for implementation. The findings demonstrate the proficiency of the ANN -based power manager in determining the operational modes guided by a specifically designed flowchart. By integrating ANN-driven energy management strategies into an HRES, the proposed approach marks a significant advancement in system adaptability, precision control, and efficiency, thereby maximizing the effective utilization of renewable resources.

Spin coating is a key method for thin film preparation due to its simplicity and cost-effectiveness, relying on the number of layers deposited. This study investigates the impact of sample thickness on polyvinyl chloride (PVC) nanocomposites doped with zinc oxide (ZnO) nanoparticles, focusing on structural, optical properties, and photocatalytic activity. Different numbers of layers (15, 20, 25, and 30) were synthesized via sol-gel spin coating using tetrahydrofuran as a solvent. X-ray diffraction revealed ZnO crystallites in 30-layer films, with a wurtzite structure and 32 nm crystallite size. Raman and infrared spectra confirmed ZnO incorporation. Optical transmittance ranged from 75% to 86%, with band gap energies between 3.45 and 3.94 eV. Photoluminescence spectra indicated ultraviolet and green luminescence attributed to ZnO defects. Photocatalytic efficiency, tested with methylene blue under UV irradiation, showed the 30-layer sample achieving 79% removal efficiency at 60 minutes, outperforming others.

Today, the classification of hate speech in Arabic tweets has garnered significant attention from scholars worldwide. Although numerous classification approaches proposed in response to this interest, two primary challenges persist are reliance on handcrafted features and limited performance rates. This paper addresses the task of identifying Arabic hate speech on Twitter, aiming to deepen insights into the efficacy of novel machine-learning techniques. Specifically, we compare the performance of traditional machine learning-based approaches with state-of-the-art pretrained language models based on Transfer Learning, as well as deep learning models. Our experiments, conducted on a benchmark dataset using a standard evaluation scenario, reveal several key findings. Firstly, multidialectal pre-trained language models demonstrate superior performance compared to monolingual and multilingual variants. Secondly, fine-tuning the pretrained large language models significantly enhances the accuracy of hate speech classification in Arabic tweets. Our primary contribution lies in achieving promising results for the corresponding task through the application of multidialectal pre-trained language models trained on Twitter data

The objective of this research is to explore the photocatalytic properties of poly(vinyl chloride) (PVC) films, both pure and doped with varying concentrations of nanoscale nickel oxide (NiO), fabricated using the spin-coating technique. The concentrations of NiO used were 8%, 10%, and 20%. Various analytical methods were employed to characterize the samples. The presence of NiO nanocrystals within the PVC films was confirmed through X-ray diffraction, Raman spectroscopy, and infrared spectroscopy. X-ray diffraction analysis revealed an average particle size of 12 nm for the NiO. Raman spectroscopy of the nanocomposites showed additional low-intensity lines characteristic of the NaCl phase of NiO cubic (NaCl type) within the PVC host matrix, indicating excellent crystalline quality with low defect density. FTIR infrared spectroscopy confirmed the presence of peaks corresponding to the Ni–O bond vibration, with increased visibility of the absorption band of NiO as doping percentages increased. Optical analysis revealed distinct differences between the spectra of pure and doped matrices. Doping led to increased absorption, characterized by the emergence of absorption bands and a redshifted absorption edge compared to the bulk semiconductor. The optical band gap of the nanocomposites decreased with increasing NiO concentration, ranging from 3.71 to 3.90 eV. PVC/NiO nanocomposites exhibited broad luminescence across the visible to near-UV range, suggesting potential applications in optical systems operating within this spectral range. Photocatalytic activity assessments demonstrated that the inclusion of NiO nanoparticles enhanced the efficiency of the composites under UV light. The (PVC/20% NiO) sample exhibited a 65% efficiency in removing MR within 100 min, comparable to other samples with lower efficiency. The photodecomposition reaction of MR followed first-order kinetics, characterized by a rate constant (k) of 0.0098 min⁻¹.

Mathematical models play a crucial role in controlling and preventing the spread of diseases. Based on the communication characteristics of diseases, it is necessary to take into account some essential epidemiological factors such as the time delay that takes an individual to progress from being latent to become infectious, the infectious age which refers to the duration since the initial infection and the occurrence of reinfection after a period of improvement known as relapse, etc. Moreover, age-structured models serve as a powerful tool that allows us to incorporate age variables into the modeling process to better understand the effect of these factors on the transmission mechanism of diseases. In this paper, motivated by the above fact, we reformulate an SEIR model with relapse and age structure in both latent and infected classes. Then, we investigate the asymptotic behavior of the model by using the stability theory of differential equations. For this purpose, we introduce the basic reproduction number R0$\mathcal {R}_0$ of the model and show that this threshold parameter completely governs the stability of each equilibrium of the model. Our approach to show global attractivity is based on the fluctuation lemma and Lyapunov functionals method with some results on the persistence theory. The conclusion is that the system has a disease-free equilibrium which is globally asymptotically stable if R0<1$\mathcal {R}_0<1$, while it has only a unique positive endemic equilibrium which is globally asymptotically stable whenever R0>1$\mathcal {R}_0>1$. Our results imply that early diagnosis of latent infection with decrease in both transmission and relapse rates may lead to control and restrict the spread of disease. The theoretical results are illustrated with numerical simulations, which indicate that the age variable is an essential factor affecting the spread of the epidemic.

This study explores the synthesis and diverse properties of newly synthesised water‐soluble cobalt (II) complexes (1–3). Analysis of the complexes through various methods, including Hirshfeld surface analysis, reveals distinctive intermolecular interactions, particularly robust H‐bonding contributions to crystal packing. 2D fingerprint plots provide quantitative insights into supramolecular interactions, while TGA‐DSC analysis elucidates multi‐step decomposition processes, mainly involving organic moieties. FT‐IR and SCXRD confirm the structures of the complexes. Magnetic susceptibility measurements show paramagnetic behaviour in all complexes. FMO calculations expose HOMO‐LUMO gaps and charge transfer processes, with NBO analysis emphasizing the significance of chloride, nitrogen, and oxygen atoms in coordination. In addition, pkCSM profile was carried out. The biological properties of the complexes reveal potent antibacterial activity for 2 and 3 against Gram‐positive and Gram‐negative bacteria. Despite lower antibacterial efficacy compared to standard antibiotics, their water solubility suggests potential human pharmacological applications. In terms of anti‐inflammatory activity, all three complexes exhibit concentration‐dependent prevention of ovalbumin denaturation, with 2 being the most effective. Compound 3, despite having seven carboxyl groups, exhibits the weakest anti‐inflammatory effect, potentially attributed to complex formation obscuring these groups. Furthermore, all complexes display antioxidant activities; 1 and 2 are greater than BHT in the ferric thiocyanate assay.