The present work was designed to investigate the effects of different extraction processes, namely ultrasonic-assisted, supercritical fluid, microwave-assisted and Soxhlet applied to carob pods. The total phenolic quantification and the antioxidant activity were assessed by the means of rapid in vitro spectrophotometric assays; the phenolic profile was identified using ultra-high performance liquid chromatography coupled to mass spectrometry. The results revealed that the phenolic compounds and the antioxidant capacity varied significantly with the nature of the extraction process. The content of total phenolic compounds ranged from 11.55 to 34.38 mg GAE/g DW; the content of total flavonoids varied from 3.50 to 10.53 mg QE/g DW, and the content of condensed tannins fluctuated from 3.30 to 6.55 mg CE/ g DW. All extracts performed differently on antioxidant activity when determined by the DPPH assay producing a dose-dependent response, with IC₅₀ extended from 11.33 to 6.07 µg/mL. HPLC analysis enabled the identification of nine compounds. As a function of the studied extraction methods, the phenolic compound contents were positively correlated with antioxidant activity.

In the present work, the adsorption behavior of Eriochrome Black T (EBT) on waste hemp activated carbon (WHAC) was examined. The surface of the WHAC was modified by H₃PO₄ acid treatment. The surface and structural characterization of the adsorbents was carried out using Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM) analysis. The effect of influential adsorption parameters (pH, contact time, dosage, and initial concentration) on the adsorption of EBT onto WHAC was examined in batch experiments; some adsorption parameters such as pH, concentration and dose were improved by new mathematical models. The adsorption behavior of EBT on the surfaces of WHAC was evaluated by applying different isotherm models (Langmuir, Freundlich, Temkin and Dubinin–Radushkevich) to equilibrium data. The adsorption kinetics was studied by using pseudo-first-order, pseudo-second-order, Elovich and intraparticle models on the model. Adsorption followed the pseudo-second-order rate kinetics. The maximum removal of EBT was found to be 44–62.08% by WHAC at pH = 7, adsorbent dose of 10–70 mg, contact time of 3 h and initial dye concentration of 10 mg.L⁻¹. The maximum adsorption capacities were 14.025 mg.g⁻¹ obtained by calculating according to the Langmuir model, while the maximum removal efficiency was obtained at 70 mg equal to 62.08% for the WHAC. The adsorption process is physical in the monolayer and multilayer.

The current paper introduced two approximation operators of large scattered datasets for spherical interpolation. The suggested solution method is an extension of Shepard's well-known method of spherical interpolating, which uses the inverted distances of scattered points as weight functions. With regard to this, the first proposed operator is a linear combination of basis functions with coefficients that are the values of the function. As for the second operator, we consider a spherical triangulation of the scattered points and substitute function values with a local interpolant, which locally interpolates the given data at the vertices of each triangle. Moreover, numerical tests have been carried out to show the interpolation performance, where several numerical results reveal the signified approximation accuracy of the proposed operators.

In this work, we present a self-adaptive algorithm based on the techniques of the a posteriori estimates for the transport equation modeling the dispersion of pollutants in the atmospheric boundary layer at the local scale (industrial accident, urban air quality). The goal is to provide a powerful model for forecasting pollutants concentrations with better manipulation of available computing resources. This analysis is based on a vertex-centered Finite Volume Method in space and an implicit Euler scheme in time. We apply and validate our model, using a self-adaptive algorithm, with real atmospheric data of the Grand Casablanca area (Morocco).

This work gives a posteriori error estimates for a finite volume implicit scheme, applied to a two-time nonlinear reaction-diffusion problem in population dynamics, whose evolution processes occur at two different time scales, represented by a parameter $ \varepsilon>0 $ small enough. This work consists of building error indicators concerning time and space approximations and using them as a tool of adaptive mesh refinement in order to find approximate solutions to such models, in population dynamics, that are often hard to be handled analytically and also to be approximated numerically using the classical approach. An application of the theoretical results is provided to emphasize the efficiency of our approach compared to the classical one for a spatial inter-specific model with constant diffusivity and population growth given by a logistic law in population dynamics.

Assessing tourism sustainability has become of paramount importance to researchers and policymakers in regard to better protecting tourism destinations, particularly with the continued increase in the number of tourists and visitors who alter the natural components of the environment and degrade ecosystems. The use of geographic data is of great importance, as it can serve as a dashboard for monitoring and controlling the sustainability of tourist areas. Due to their diversity and abundance in the city of Tangier, these tools are available and easy to use. The medina of Tangier is used as a calculation example, a method that will also be applicable to other areas of the metropolitan city and to other cities as well. Based on the annual meeting of the different component of society involved in the Medina of Tangier, the data are extracted and integrated into the proposed model through a plugin interface. Therefore, the use of geographic data is of great importance, especially in environmental monitoring and land management, due to its ease of use and availability. However, calculating composite sustainability indices involves several steps and requires a basic understanding of existing models. This article describes the development and design of a plugin package in QGIS that serves as an easy-to-use tool to automatically process and calculate economic, environmental and social indices and the overall tourism sustainability index. These plugins were built in Python and designed as plugins for the QGIS software version 3.22.