A comparative study of phenols composition,antioxidant, and antifungal potency of leaves extract from five Moroccan Vitis vinifera L. varieties

Vitis vinifera (L) crops, covers an area of about 54,000 ha corresponding to a production of 230,000 t of grapes, representing 5.5% of the national perennial corps. However, this plant is sensitive to various ravages and diseases, among others, the cryptogrammic by fungi. The degrading enzymes of the cell wall are among the factors of pathogenicity the more important than fungi use to colonize their host plants. In this study, the first step was devoted to the antioxidant activity and phenols composition (phenylalanine-ammonia-lyase [PAL], tyrosine-ammonia-lyase [TAL], flavonoids, and tannins) as well as high-performance liquid chromatography analysis in five vineyard leaves extract, which are “Superior, Early sweet and Flame” (Allochthonous), “Abbou and Adari” (endemic). In the second step, the lytic activities “pectinase, polygalacturonase, xylanase, mannanase, glucanase, and cellulase” were investigated among six epiphytic fungus to compare their hydrolytic aggressiveness. Subsequently, as a third part, phenols antifungal potency and Trichoderma biocontrol were displayed in the study. The phenolic compounds observed in the attributes leaves were different among varieties (p < .05), and show that the endemic variety “Abbou” leads the phytochemical amount, which has the highest quantities of PAL, and TAL, as well as the DPPH and FRAP antioxidant activity, while the introduced variety show a higher amount in total phenol and flavonoids. The polygalacturonase, mannanase, and pectinase activities are probably the main factors responsible for the aggressiveness of the studied fungus. Phenols potency showed a good mycelial inhibition with 82.09% as compared to the biocontrol (64.45%). Given the efficacy of the phytochemical control in this study, the phenols could be a part of integrated management strategies for sustainable control of vineyard disease.     

A passivity‐based simple adaptive synergetic control for a class of nonlinear systems

For a class of nonlinear systems with the representation {A(x), B(x), C} and where the system parameters and dynamics are unknown, a simple adaptive synergetic controller ensuring the asymptotic convergence of the system to a desired manifold is proposed based on the technique of simple adaptive control (SAC). It is well known that the design of the synergetic control (SC) law requires a thorough knowledge of the system parameters and dynamics. Such problem obstructs the synthesis of the SC law and the designer is prompted to pass through the estimation methods, which, in turn, poses a problem of increasing the computation time of the control algorithm. To cope with this problem, a solution is proposed by modifying the original SC law to develop an SAC‐like adaptive SC law without the need of prior knowledge of the system. The stability of the proposed adaptive controller is formally proven via the Lyapunov approach. Experimental application to a quadrotor system is given to validate the theoretical results.     

Influence of Inoculant Type on the Microstructure Characteristics and Mechanical Properties of Ductile Iron

Transactions of the Indian Institute of Metals - The inoculation process of molten cast iron defines the final microstructure of the produced castings. The current study is concerned with the...     

Human gait recognition using GEI-based local multi-scale feature descriptors

Multimedia Tools and Applications - Human gait recognition is a biometric technique for persons identification based on their walking manner. This paper proposes a novel gait recognition approach...     

Effect of Thickness Size on Magnetic Behavior of Layered Ising Nanocube Fe/Co/Fe: a Monte Carlo Simulation

Journal of Superconductivity and Novel Magnetism - The Monte Carlo simulation method is used to investigate the magnetic and thermodynamic properties of a single Ising nanocube Fe/Co/Fe system...     

Theoretical Investigation of Magnetoelectric Coupling in MFe2O4/PbZ0.5T0.5O3/MFe2O4 (M = Ni,Co) Heterostructure

Journal of Superconductivity and Novel Magnetism - Magnetoelectric materials that allow magnetic-field control of electric polarization are promising candidates for high-density data storage and...     

Magnetocaloric Properties of the Perovskite GdCuO3: Monte Carlo Simulation

Journal of Superconductivity and Novel Magnetism - This work aims to examine the magnetocaloric properties of the Perovskite GdCuO3, such as the total magnetization, the susceptibility, and the...     

COACT: a query interface language for collaborative databases

Data curation activities in collaborative databases mandate that collaborators interact until they converge and agree on the content of their data. In a previous work, we presented a cloud-based collaborative database system that promotes and enables collaboration and data curation scenarios. Our system classifies different versions of a data item to either pending, approved, or rejected. The approval or rejection of a certain version is done by the database Principle Investigators (or PIs) based on its value. Our system also allows collaborators to view the status of each version and help PIs take decisions by providing feedback based on their experiments and/or opinions. Most importantly, our system provided mechanisms for history tracking of different versions to trace the modifications and approval/rejection done by both collaborators and PIs on different versions of a data item. We labeled our system as Update-Pending-Approval model (or UPA). In this paper, we describe a high level SQL query interface language for PIs and collaborators to interact with the UPA framework. We define a set of UPA keywords that are used as a part of the history tracking mechanism to select specific versions of a data item, and a set of UPA options that select specific versions based on possible future decisions of PIs. We implemented our query interface mechanism on top of Apache Phoenix, taking into consideration that the UPA system was implemented on top of Apache HBase. We test the performance of the UPA query language by executing several queries that contain different complexity levels and discuss their results.     

Partial syndrome-based system-level fault diagnosis using game theory

This paper introduces a novel diagnosis approach, using game theory, to solve the comparison-based system-level fault identification problem in distributed and parallel systems based on the asymmetric comparison model. Under this diagnosis model tasks are assigned to pairs of nodes and the results of executing these tasks are compared. Using the agreements and disagreements among the nodes’ outputs, i.e. the input syndrome, the fault diagnosis algorithm identifies the fault status of the system’s nodes, under the assumption that at most t of these nodes can permanently fail simultaneously. Since the introduction of the comparison model, significant progress has been made in both theory and practice associated with the original model and its offshoots. Nevertheless, the problem of efficiently identifying the set of faulty nodes when not all the comparison outcomes are available to the fault identification algorithm prior to initiating the diagnosis phase, i.e. partial syndromes, remains an outstanding research issue. In this paper, we first show how game theory can be adapted to solve the fault diagnosis problem by maximising the payoffs of all players (nodes). We then demonstrate, using results from a thorough simulation, the effectiveness of this approach in solving the fault identification problem using partial syndromes from randomly generated diagnosable systems of different sizes and under various fault scenarios. We have considered large diagnosable systems, and we have experimented extreme faulty situations by simulating all possible fault sets even those that are less likely to occur in practice. Over all the extensive simulations we have conducted, the new game-theory-based diagnosis algorithm performed very well and provided good diagnosis results, in terms of correctness, latency, and scalability, making it a viable addition or alternative to existing diagnosis algorithms.