The genetic diversity of local coffee populations is crucial to breed new varieties better adapted to the increasingly stressful environment due to climate change and evolving consumer preferences. Unfortunately, local coffee germplasm conservation and genetic assessment have not received much attention. Molecular tools offer substantial benefits in identifying and selecting new cultivars or clones suitable for sustainable commercial utilization. New annotation methods, such as chloroplast barcoding, are necessary to produce accurate and high-quality phylogenetic analyses. This study used DNA barcoding techniques to examine the genetic relationships among fifty-six accessions collected from the southwestern part of Saudi Arabia. PCR amplification and sequence characterization were used to investigate the effectiveness of four barcoding loci: atpB-rbcl, trnL-trnF, trnT-trnL, and trnL. The maximum nucleotide sites, nucleotide diversity, and an average number of nucleotide differences were recorded for atpB-rbcl, while trnT-trnL had the highest variable polymorphic sites, segregating sites, and haploid diversity. Among the four barcode loci, trnT-trnL recorded the highest singleton variable sites, while trnL recorded the highest parsimony information sites. Furthermore, the phylogenetic analysis clustered the Coffea arabica genotypes into four different groups, with three genotypes (KSA31, KSA38, and KSA46) found to be the most divergent genotypes standing alone in the cluster and remained apart during the analysis. The study demonstrates the presence of considerable diversity among coffee populations in Saudi Arabia. Furthermore, it also shows that DNA barcoding is an effective technique for identifying local coffee genotypes, with potential applications in coffee conservation and breeding efforts.
Image denoising attempts to restore images that have been degraded. Historical document denoising is specially challenging because there is considerable background noise or variation in contrast and illumination in handwritten literature and the first times of the printing press. The main objective of this work is to propose a new method for historical document denoising based on an Attentive Generative Adversarial Network (Attentive-GAN). Our proposed model for historical document denoising is named Doc-Attentive GAN , and it employs an attention map generated by a deep network to help the generator to learn and focus on the modification between the target image and its noisy version. It has been trained and tested with different historical document collections such as well-known DIBCO datasets, Arabic Historical Documents from the Tunisian National Library, and Incunabula books. The experiments demonstrate a clear improvement in the visual quality of the images obtained by Doc-Attentive-GAN with respect to the state-of-the-art.
Intercropping is known to improve the available resource usage and increase yield compared to sole cropping. Field experiments were carried out in 2020-2021 (EXP-A) and 2021-2022 (EXP-B) in Medenine, Tunisia, to compare at the flowering stage of plant growth, the agronomic performance of cereals (durum wheat) intercropped with a legume (chickpea) to their monoculture and to the soil bulk such as microbial mass C and N, nitrogen nutrition, and carbon availability. In this study, we found no significant differences between the proportions of Ntot for sole or intercropped Chickpea, with a difference of 4 and 6% for two seasons of culture (2020-2021 and 2021-2022). On the other hand, durum wheat grown in intercrops (DuWh-IR) significantly (p<0.05) acquired more Ntot than durum wheat grown in mono-crops (DuWh-MC) with an augmentation of 20% in 2020-2021 and 18% in 2021-2022. At the same time, the N concentration of durum wheat roots increases significantly under the effect of intercropping with 20% in 2020-2021 and 28% in 2021-2022. However, it is noted that the N content for chickpeas was comparatively lower for the intercrops as compared to sales crops i.e., eight percent in the years 2020 to 2021 and seven percent in the year 2021 to 2022, for both the shoots. In semi-arid regions of Southern Tunisia, cereals-legumes (Chickpea-Durum wheat) intercropping can influence the N and C soil fertility, which improves crop production while respecting the environment by reducing the use of nitrogen fertilizers.
The purpose of the study is to evaluate the effectiveness of intercropping systems cereals (Durum/hard Wheat)-legume (Cicer arietinum) on phosphorus (P) acquisition, pH soil variation, and the variation in enzymatic activity, through root-induced processes in semi-arid soil of South Tunisia. Split plot experiments with triplicate repetitions were carried out in southern Tunisia during two years of field (2020–2021 and 2021–2022). These comprise mono-crop chickpea (CK) and mono-crop durum wheat/ wheat durum (DW/WD), durum wheat intercropping (DW-C), and chickpea intercropping (CK-C). At the complete vegetation stage of durum wheat and chickpea, three soil samples were carried in layer surface for each experimental plot. For the analyses of soil, the P total, Olsen-P, phytase, acid phosphatases, and pH were carried out in the experiment. The obtained findings show a significant amelioration in P total contents in DW-C by 28% and 26% to DW, and 94% and 93% than BS during the two years of field experiment (2020–2021 and 2021–2022) respectively. Furthermore, the Study reported an increase of Olsen-P in the rhizosphere of DW-C by around 5%, 42% than DW, and 36%, 65% to bulk soil (BS) during the two-year experiment. Likewise, these results revealed an increase in A-Phase rates in the DW-C rhizosphere during the two agricultural seasons (2020–2021 and 2021–2021), of approximately 26%, 8% than DW and 33%, 67% than BS respectively. As well as the phytase activity indicated an increase in the DW-C rhizosphere by 67% and 69% than in BS and only by 8% and 7% than in DW for the two seasons (2020–2021 and 2021–2021). Indeed, the rhizosphere acidification of rhizosphere was found very much high in CK-C (0.63 pH units and 0.55 units lower than in the BS).
Solar energy is widely utilized for water pumping systems, particularly in remote areas. However, such systems have different configurations and strategies, each with its own advantages and drawbacks. To design a suitable system, this paper proposes a method that utilizes a single-stage conversion system with hydraulic storage. In this method, the predictive torque controller (PTC) adjusts the inverter switching while the electrical storage in batteries is replaced by the potential energy of water in tanks. The PTC works side-by-side with a maximum power point tracking (MPPT) technique to supply the optimal power to the water-pumping Induction Motor (IM). This maximum power tracking is maintained during the day hours to provide and store water, whereas the water supply is guaranteed due to the gravity at night. The effectiveness of the proposed system is evaluated through MATLAB/Simulink-based results, demonstrating that the single-stage configuration outperforms the double-stage configuration in terms of power optimization, torque ripples, and power loss reduction. Furthermore, the suggested system offers the advantage of cost-effective installation due to its simple structure.
In this paper, an interval multiobserver is designed for nonlinear systems subject to unknown but bounded disturbances and measurement noises. The behavior of discrete nonlinear systems is described by an uncoupled multimodel. Linear Matrix Inequalities (LMIs) are formulated to study the stability of the proposed systems and to ensure the cooperativity dynamic of the observation errors. An augmented system is introduced to apply a tracking control where the control gains are obtained by pole placement. Finally, a numerical example is proposed to verify the efficiency of the interval multiobserver in state estimation and to prove the performance of the control strategy to follow the desired trajectory.
Oral medications are prone to gastric degradation and enzymatic inactivation, diminishing their efficacy. This study investigates a solution by developing intelligent polymeric networks, incorporating chitosan, methacrylic acid, N, N, methylene bisacrylamide, and montmorillonite clay, to enable the controlled release of Diloxanide Furoate (DF), an anti-protozoal drug. Employing a swelling-assisted diffusion technique, drug loading percentages varied from 63.96% to 76.82% among different formulations. Increased chitosan and methacrylic acid content enhanced drug loading, while N, N, methylene bisacrylamide and montmorillonite clay demonstrated an inverse relationship affecting diffusion and swelling. Equilibrium swelling studies unveiled formulation-dependent behaviors, with chitosan reducing swelling and methacrylic acid promoting it. Higher N, N, methylene bisacrylamide concentrations decreased swelling, indicating a denser cross-linked structure, while montmorillonite clay reduced hydrophilicity and swelling capacity. Further analyses confirmed successful gel formation, particularly in formulations with higher chitosan, methacrylic acid, and N, N, methylene bisacrylamide content, while montmorillonite clay limited gel fraction due to restricted polymer chain mobility. Techniques such as Fourier transform infrared spectroscopy, Differential scanning calorimetry, and thermal gravimetric analyses supported network development, enhancing thermal stability and cross-linking density. This research underscores the flexibility of polymeric networks for precise drug delivery, offering potential advancements in targeted therapies for various medical conditions.
The new spinel ferrite has garnered significant attention and has piqued the broadest interest among scientists due to its versatile and promising features, as well as its wide range of applications. In this study, we outline the process of synthesizing nano-sized Li-Cr ferrite powder, which exhibits remarkable dielectric relaxor activity when exposed to elevated temperatures. The study primarily focuses on investigating the structural, electrical, and optical properties of these Li-Cr ferrite particles. X-ray diffraction measurements confirmed the well-arranged inverse-cubic spinel structure of the material. The sample's nanostructural properties were examined using scanning electron microscopy. The sample's well-organized inverse-cubic spinel structure was confirmed using Fourier transform infrared spec-troscopy examinations. The optical properties of our sample, as measured by UV-Visible spectroscopy, revealed a bandgap value of 2.6 eV makes it interesting for optoelectronic applications. The investigation focused on dielectric relaxation and electrical characteristics using impedance spectroscopy. It was shown that the AC conductivity follows Jonscher's law, and the Non-overlapping Small-Polaron Tun-neling model was developed to elucidate the conduction mechanism. The impedance spectra's Nyquist plot confirmed the presence of grain boundary relaxation in the temperature ranges of 300-370 K and 560-660 K. Additionally, the interface, consisting of both the grain boundary and electrode effect, had a substantial influence between 380 and 550 K. An appreciable value for the temperature coefficient of resistance is observed. The results obtained demonstrate that the synthesized powder is well-suited for utilization in high-energy storage, low-temperature co-fired ceramics technology and bolometer applications.
Water erosion is a critical factor contributing to soil loss in southern Tunisia and poses a substantial risk to both ecosystems and water/soil conservation. This study employs an analytic hierarchy process (AHP) model integrated with geographic information systems (GIS) to evaluate the potential soil erosion risk and the relative significance of erosion factors within the Oum el Ghram and Bou Said watersheds. Ten factors, including rainfall, land cover/use, slope, elevation, runoff, drainage density, lineament density, lithology, soil type, and support practices, are analyzed. The results highlight land cover/use (27%), elevation (18%), and slope (14%) as the most influential factors. High to very high erosion classes predominantly occur in mountainous areas, covering 5.22% of the study area. Validation using the ROC curve demonstrates a satisfactory accuracy level for the AHP method (AUC = 0.85). To mitigate soil degradation and erosion risks, the findings advocate for implementing sustainable management strategies. Furthermore, this research offers insights for establishing effective soil management strategies under similar conditions in various studies. This work addresses the pressing issue of erosion in southern Tunisia, emphasizing practical solutions and valuable applications for soil conservation efforts.
One of the crucial problems in in the fields of machine learning and data mining is data reduction by feature selection (FS). In this context, this paper proposes an FS method based on a hybrid of type 2 fuzzy rough k-nearest neighbors (T2FRKNN) and a weighted mean vector optimization method called FKNINFO. Thus, the significance of the features can be determined by the creation of the lower and upper fuzzy similarity partition matrices. The introduction of INFO is intended to enhance the T2FRKNN with the best parameters and feature subsets. The proposed method is a dynamic framework originally aimed at solving problems through continuous optimization. In this regard, we propose a binary version of FKNINFO (BFKNINFO), which uses the X-shaped function to improve the efficiency of FS. The BFKNINFO is tested using medical datasets and compared to the other optimization methods in terms of fitness, accuracy, precision, recall, ROC curves,Wilcoxon statistical test (P-value), running time, and number of features. BFKNINFO is used to detect the coronavirus disease (COVID-19) datasets. The results of the experiments demonstrate the effectiveness of BFKNINFO in navigating the problem space and identifying the most effective parameter and features by reducing the number of features.
This study aims to explore for the first time the thermoelastic buckling behavior of functionally graded porous plates and shells using an efficient finite element model based on the first-order shear deformation theory (FSDT) with the improvement of the shear strains via the introduction of a quadratic function that able to take into account the parabolic distribution of transverse shear stresses without any need of shear correction factors as standard (FSDT) theory. In this research, different sets of functionally graded metal/ceramic combinations, as well as porosity distributions, namely uniform (or even) and random (or uneven) porosity patterns, are also considered, and the effective material properties of the graded porous structure are determined via a modified power-law function. Two types of applied thermal loads are considered, namely Uniform and nonuniform thermal load (UT, NUT) with temperature-dependent (TD) and independent (TID) mechanical properties. The Green-Lagrange formulation, variational method, and a numerical iterative algorithm are applied to solve the governing equations with porosity and thermal dependent coefficients. To verify our results, various numerical comparisons are conducted on critical temperature buckling of plates and spherical shells, and they are compared with available results where a close correlation is observed. The influence of thermal loads, porosity volume fraction, types of porosity patterns, temperature dependency, and geometrical aspects on the thermal buckling behavior of FG porous plates and shells are scrutinized through different parametric studies.
The identification of robot dynamic parameters is usually based on the use of the reverse model which is linear in relation to the dynamic parameters to be identified. To get an over determined system, this model is sampled while the robot is trained with fascinating movements. The optimum solution is obtained with linear least squares (LCL). The efficacy of this approach has been demonstrated through the experimental identification of numerous industrial prototypes and robots. It has been expanded to other systems including compactors, cars, engines, and haptic interfaces. Though, this method requires accurate measurement at a high rate of torque and position image. It also requires estimating speeds and accelerations by band-pass filtering positions. This results in a noisy observation matrix. Furthermore, the identification is done in a closed loop due to the unstable nature of the robots’ dual integrator. The observation matrix being noisy, and the identification being carried out in a closed loop, we have adapted the method of the instrumental variable (IV) to remedy the problem of the noisy observation matrix. This article highlights this technique and proposes an extension of this method which is applied to a flat robot of 2 degrees of freedom (DOF).
This work discusses the analysis of uncertain neutral time-delay systems, These systems include delays in both the state and derivatives. In actuality, the study of stability and observability in an open-loop is proposed using the Lyapunov-Krasovskii functional. Then, by resolving linear matrix inequalities (LMI) and taking into account optimization theory, new requirements of stability and observability are obtained, In order to support theory development, simulation results will be provided.
This chapter studies the problem of state estimation for a class of discrete-time switched systems. The considered system is subject to disturbances and measurement noise which are supposed to be unknown but bounded in predefined zonotopes. The proposed method consists of two steps. First, a switched \(L_\infty \)-based observer attenuating the effect of uncertainties is designed to obtain point estimate of the system state. The robust observer is designed using firstly the Luenberger structure and secondly the T-N-L structure. Then, interval state estimation is achieved by integrating robust point estimation with zonotopic analysis techniques. The observers gains are calculated by solving Linear Matrix Inequality (LMI) derived using a Multiple Lyapunov functions (MLF) under an Average Dwell Dime (ADT) switching signal. A numerical example is performed to illustrate the effectiveness of the obtained results.
In many studies cases, generating a control laws using the state and/or output variables in Reciprocal State Space (RSS) form can be more easy than in Standard State Space (SSS) one. The formulation of a new stabilization control problem using feedback principle for linear discrete-time systems in RSS is presented in this brief. In contrast to the existing approaches, the considered model is described in RSS framework with an extension to Lipschitz nonlinear discrete-time systems. The asymptotic stability based on Lyapunov functions of the closed-loop system is guaranteed. The control design resolution problem is ensured through the Linear Matrix Inequalities (LMI) technique, the lemmas and the use of slack-variables and Differential Mean Value Theorem (DMVT). The performance of the proposed approach are shown through the experimental results using Real Time Implementation (RTI) with an Arduino MEGA 2560 board.
Limonium. Mill is a genus of flowering plants belonging to the Plumbaginaceae family. The present study aimed to compare two Limonium species (L. pruinosum Kuntze and L. tunetanum (Barratte & Bonnet) Maire) in terms of their chemical composition and bioactivity. Chemical profiling showed that the methanolic (MeOH) extracts of both species were the most enriched with total phenolic (TP) and total flavonoid (TF) contents. The TFC were higher in L. tunetanum compared to L. pruinosum. HPLC‐DAD analysis showed that distinctly the gallic acid and L‐tyrosine 7‐amido‐4‐methylcoumarin were the main compounds for L. pruinosum and L. tunetanum, respectively. For both Limonium. Mil species, the MeOH extracts displayed the highest antioxidant with IC50 of 7.7 and 8.4 µg/mL for L. pruinosum and L. tunetanum, respectively. The highest anti‐15‐lipoxygnase activity was recorded in the ethyl acetate (IC50 = 14.2 µg/mL) and Methanol (IC50 = 15.6 µg/mL) extracts for L. pruinosum. However, for L. tunetanum the best activity was recorded for dichloromethane extract (IC50 = 10.4 µg/mL). L. pruinosum extracts displayed the highest cytotoxic activity against MCF‐7 and HCT‐116 cell lines compared to L. tunetanum ones. The obtained bioactivity discrepancy between Limonium. Mill species was discussed in relation to the organic extract chemical richness.
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