Pharmacological, biological and phytochemical aspects of Thymus munbyanus Boiss. & Reut.: A review

Thymus munbyanus Boiss. & Reut., is a small shrub endemic to Morocco and Algeria, and it is commonly used to treat several diseases, including digestive, circulatory, genital, skin, urinary, nervous and respiratory diseases. The extracts of this thyme are rich in a wide variety of phenolic compounds such as polyphenols and volatile phenols and exhibit numerous biological activities. The present review summarizes the literature investigations reported on Thymus munbyanus concerning various pharmacological and biological properties as well as phytochemical aspects. This species revealed a richness in phenolic compounds in its volatile oils, including thymol and carvacrol, as well as in its non-volatile extracts including phenolic acids phenolic acids (rosmarinic acid, caffeic acid, salvianolic acid, ferulic acid, etc.), flavonoids (luteolin, gallocatechin, quercetin, isorhamnetin, etc.). Moreover, powerful antioxidant and antimicrobial properties were reported for this Thymus species, which are attributed to its richness in bioactive antioxidants. Furthermore, this thyme was found to possess important nephroprotective, hepatoprotective, and tumor cytotoxic properties. In conclusion, Thymus munbyanus is an important natural source of bioactive phenolic compounds that can be used for developing alternative natural drugs for the treatment and prevention of several pathologies

The capability of recurrent neural networks to predict turbulence flow via spatiotemporal features

This study presents a deep learning (DL) neural network hybrid data-driven method that is able to predict turbulence flow velocity field. Recently many studies have reported the application of recurrent neural network (RNN) methods, particularly the Long short-term memory (LSTM) for sequential data. The airflow around the objects and wind speed are the most presented with different hybrid architecture. In some of them, the data series is used with the known equation, and the data is firstly generated. Data series extracted from Computational Fluid Dynamics (CFD) have been used in many cases. This work aimed to determine a method with raw data that could be measured with devices in the airflow, wind tunnel, water flow in the river, wind speed and industry application to process in the DL model and predict the next time steps. This method suggests spatialtemporal data in time series, which matches the Lagrangian framework in fluid dynamics. Gated Recurrent Unit (GRU), the next generation of LSTM, has been employed to create a DL model and forecasting. Time series data source is from turbulence flow has been generated in a laboratory and extracted via 2D Lagrangian Particle Tracking (LPT). This data has been used for the training model and to validate the prediction in the suggested approach. The achievement via this method dictates a significant result and could be developed.This work was performed in the Center of Excellence (CoE) Research on AI and Simulation Based Engineering at Exascale (RAISE) and the EuroCC projects receiving funding from EU’s Horizon 2020 Research and Innovation Framework Programme under the grant agreement no.951733 and no. 951740 respectively.Peer Reviewe

BIOACTIVITY OF Anvillea radiata COSS & DUR. COLLECTED FROM THE SOUTHEAST OF MOROCCO

The in vitro antimicrobial and antioxidant activities of aqueous, methanolic and ethyl acetate extracts of Anvillea radiata (Asteraceae) were investigated. Antibacterial activity was tested against six pathogenic strains viz. Staphylococcus aureus (ATCC 29213), Staphylococcus aureus (ATCC 6538), Bacillus subtilis (ATCC 6633), Salmonella abony (NCTC 6017), Escherichia coli (ATCC 25922), Escherichia coli (ATCC 8739) and by using Disc diffusion method and Minimum Inhibitory Concentrations (MIC). Total antioxidant capacities were assessed by DPPH (1.1 diphenyl-2- picrylhydrazyl) radical scavenging activity, ferric reducing power (FRAP) and ABTS (2.2’-Azinobis-(3-ethylbenzothiazoline-6-sulfonic acid)) radical cation scavenging activity. Total phenolic contents were measured by Folin- Ciocalteu assay. Among the extracts tested, methanolic extract showed promising antibacterial activity against bacteria and reasonable antioxidant properties, and they can therefore be potentially used as a natural additive in food, cosmetic and pharmaceutical industries

Lagrangian Particle Tracking Data of a Straining Turbulent Flow Assessed Using Machine Learning and Parallel Computing

This study aimed to employ artificial intelligence capability and computing scalability to predict the velocity field of the straining turbulence flow. Rotating impellers in a box have generated the turbulence, subsequently subjected to an axisymmetric straining motion, with mean nominal strain rates of 4s^-1. Tracer particles are seeded in the flow, and their dynamics are investigated using high-speed Lagrangian Particle Tracking at 10,000 frames per second. The particle displacement, time, and velocities can be extracted using this technique. Particle displacement and time are used as input observables, and the velocity is employed as a response output. The experiment extracted data have been divided into training and test data to validate the models. Support vector polynomial regression (SVR) and Linear regression were employed to see how extrapolation for the velocity field can be extracted. These models can be done with low computing time. On the other hand, to create a dynamic prediction, Gated Recurrent Unit (GRU) is applied with a high-performance computing application. The results show that GRU presents satisfactory forecasting for the turbulence velocity field and the computing scale performed on the JUWELS and DEEP-EST and reported. GPUs have a significant effect on computing time. This work presents the capability of the GRU model for time series data related to turbulence flow prediction.This work was performed in the Center of Excellence (CoE) Research on AI and Simulation Based Engineering at Exascale (RAISE) and the EuroCC projects receiving funding from EU’s Horizon 2020 Research and Innovation Framework Programme under the grant agreement no.951733 and no. 951740 respectivelyPeer Reviewe

Systematic review of Ethiopian medicinal plants used for their anti-inflammatory and wound healing activities

Ethnopharmacological relevance: Plant materials are used worldwide as complementary and alternative therapeutics for the treatment of various illnesses. In Ethiopia, folk medicines are utilized across a wide range of cultures and settings. Ethiopia has numerous plant species of which around 12% are endemic, making it a rich source of medicinal plants that are potentially important for human wellbeing. Aim of the study: The aim of this study was to assess Ethiopian medicinal plants with anti-inflammatory or wound healing activities, in an attempt to compile the information required for further investigation of their potential role in the management of lymphoedema. Methods: A systematic review protocol was developed according to the preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) statement. The protocol for this review was registered on PROSPERO with registration number CRD42019127471. This review considers all controlled in vivo and in vitro anti-inflammatory and wound healing studies evaluating the efficacy and safety of Ethiopian medicinal plants. The search strategy included all articles containing descriptors such as Ethiopia, medicinal plants, herbal products, care, management, lymphoedema, lymphedema, swelling, podoconiosis, elephantiasis, wound, wound healing, inflammation, and anti-inflammatory that were published up to June 28, 2019. Outcomes were measured as the percentage of inflammatory and pro-inflammatory cell inhibition, as the percentage of carrageenan-induced oedema (anti-inflammation) inhibition, and the percentage of cell migration and proliferation (wound healing). For quality assessment of individual animal studies, the Risk of Bias tool for animal intervention studies (SYRCLE’s RoB tool) criteria was used. For quality assessment of individual in vitro studies, the OECD guidelines and the WHO Good Laboratory Practice (GLP) handbook were used. Results: A total of 46 articles on anti-inflammatory and 17 articles on wound healing properties were reviewed. For the in vivo studies, Swiss albino mice and Wistar rats were used, and the concentration of plant extracts or fractions administered to the lab animals varied considerably. Acetone extract of Vernonia amygdalina showed the fastest anti-inflammatory activity at lower concentrations in carrageenan-induced paw oedema. Conclusion: Lawsonia inermis, Azadirachta indica, Achyranthes aspera, and Cuminum cyminum are the most studied plant species in terms of anti-inflammatory activity, while Lawsonia inermis and Azadirachta indica are the most studied for wound healing. The most common in vivo techniques used for the anti-inflammatory and the wound healing assays were carrageenan-induced paw oedema, and excision and incision wound models, respectively

On the effects of buoyancy on passive particle motions in the convective boundary layer from the Lagrangian viewpoint

Mechanical turbulence and convection are combined together in this project to make it a real scientific and engineering challenge. Thees two natural phenomenon are put together under experimental investigations inside the flow facility at the Laboratory for Fundamental Turbulence Research (LFTR) at Reykjavik University. The aim of this research is to study the effects of the buoyancy on passive particle motions in the convective boundary layer, and on the intermittent nature of the small scale structures present in such region. The region of interest is located at 15\,mm above the heated wall. Particle image velocimetry (Eulerian frame of reference) and Particle tracking velocimetry (Lagrangian frame of reference) are the measurements techniques used in this present work. Our flow is found to be approximatively homogeneous with a slight variation in the direction of the heat flow and anisotropic, with a Taylor Reynolds number, R_\lambda = 200, local Rayleigh number based on the thickness of the boundary layer, Ra_delta = 3x10^5$and local Prandtl number, Pr = 6.77. Our focus is on small structures of homogeneous and anisotropic turbulence, ranging from the smallest scale present in the dissipative range,$\eta $ (Kolmogorov scale) to the to energy containing scales in the inertial subrange \eta << r << L . Eulerian and Lagrangian experiments were conducted at the region of interest with an imposed mean thermal gradient of various intensities. The production and generation of stable mean thermal gradient in the box-turbulence was done by a developed mathematical model which had predicted the shape of the mean temperature profile of our flow. New heating/cooling system was designed and implemented to generate the convective turbulence. We found that, in the presence of the buoyancy force, a new dynamic regime arises and the intermittency becomes very high which will increase the particle-particle interaction and therefore will increase their coalescence and rate of collisions

La mise à l’agenda de la question religieuse dans l’enseignement francophone belge : étude de cas appliquée au projet de réforme de la Ministre Marie-Dominique Simonet datant de 2012 : à savoir l’introduction d’un tronc commun pour tous les cours philosophiques

Master [60] en sciences politiques, orientation générale (horaire décalé), Université catholique de Louvain, 201

Urgences chez le patient cirrhotique (évaluation des mesures thérapeutiques initiales à l'usage du médecin urgentiste)

AIX-MARSEILLE2-BU Méd/Odontol. (130552103) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Antifungal Potential of Phytochemicals against Mauginiella scaettae, the Plant Pathogen Causing Inflorescence Rot of Date Palm

Date palm (Phoenix dactylifera L.) inflorescence rot caused by Mauginiella scaettae poses a serious threat to date palm in Morocco. The present study aims to determine the antifungal activity of five plant extracts against M. scaettae, including Acacia cyanophylla, Cupressus atlantica, Eucalyptus torquata, Nerium oleander, and Schinus molle and link this effect to their content in phenolics and flavonoids, as well as their antioxidant properties. Plant extracts exhibited significant discrepancies regarding their antifungal activity (p<0.05). The extracts of E. torquata and C. atlantica had the strongest and dose-dependent manner inhibitory effect against mycelial growth and spore germination. E. torquata and S. molle caused the greatest sporulation reductions of about 88.05% and 36.11%, respectively. In addition, there were significant differences among the examined plant extracts with respect to their total polyphenols (14.52–76.68 mg GAE/g DW), flavonoids (8.75–57.78 g RE/100 g DW), and antioxidant properties as measured by TEAC (74.77–391.23 mmol TE/g DW) and FRAP assays (87.18–474.04 mmol TE/g DW). Strong correlations were found between phenolic compounds and antioxidant activity suggesting that polyphenols play a key role in the observed antioxidant and antifungal activities