Phytochemical profile, total phenolic content and antioxidant activity of ethanolic extract of fumitory (Fumaria capreolata L.) from Algeria

Fumitory or Fumaria capreolata L. is a medicinal plant, spontaneous and widely distributed in North Africa, particularly in Algeria. It has been recognized for centuries for its therapeutic virtues, and it is used in traditional medicine in the treatment of hepatobiliary diseases, gastrointestinal disorders and in the treatment of skin diseases. The phytochemical screening carried out on the aerial part of the species F. capreolata L., revealed the richness of this plant in secondary metabolites, such as alkaloids, catechic tannins, sterols and terpenes. On the other hand, we noticed the absence of cardinolides, leuco-anthocyanins, quinones and starch in all parts of the plant. Quantitative spectrophotometric analysis allowed us to detect the levels of total polyphenols using the reagent of Folin-Ciocalteu, according to the results obtained we find that the species F. capreolata is rich in these compounds (14.27 ± 1.65 mg GAE/g). The evaluation of the antioxidant activity was carried out using the DPPH method, indicated that the ethanolic extract of F. capreolata L. showed significant antioxidant activity, with an IC50 = 0.27 mg/ml. And it also has a strong inhibitory activity of the coupled oxidation of linoleic acid and β-carotene, with a percentage of 88.46 ± 1.02% at a concentration of 0.5 mg/ml. In addition, the crude extract of F. capreolata L., also exhibits a good iron reduction capacity, with a maximum optical density of 0.349 at a concentration of 0.5 mg/ml. DOI: http://dx.doi.org/10.5281/zenodo.548449

Collaborative Foraging Using a new Pheromone and Behavioral Model

International audiencewe consider the problem of foraging with multiple agents, in which agents must collect disseminate resources in an unknown and complex environment. An efficient foraging should benefit from the presence of multiple agents, where cooperation between agents is a key issue for improvements. To do so, we propose a new distributed foraging mechanism. The aim is to adopt a new behavioral model regarding sources' affluence and pheromone's management. Simulations are done by considering agents as autonomous robots with goods transportation capacity, up to swarms that consist of 160 robots. Results demonstrate that the proposed model gives better results than c-marking agent model

Dérivation d’un spectre de réponse spécifique au site de la grande mosquée d’Alger (Algérie)

The estimation of the soil seismic response at the surface can be made by several experimental methods, approximate and numerical. This study consists in using numerical simulation to determine the surface response in terms of maximum acceleration and response spectrum of soil profiles located at the site of the Grand Mosque of Algiers, taking into account the soil’s non-linearity behavior, with an equivalent linear behavior (hysteresis degradation of the shear modulus G). The responses calculated on the surface that they are amplified or de-amplified compared to the excitation at the base (earthquake of May 21, 2003 in Boumerdès) indicate the presence of the site effects and which allows the derivation of a spectrum calculation to the studied site.L’estimation de la réponse sismique en surface du sol peut être faite par plusieurs méthodes expérimentales, approchées et numériques. Cette étude consiste à utiliser la simulation numérique pour déterminer la réponse en surface en termes d’accélération maximale et spectre de réponse des profils de sol localisé au niveau du site de la mosquée d’Alger en tenant compte de la non-linéarité du comportement du sol, avec un comportement linéaire équivalent (dégradation hystérésis du module de cisaillement G). Les réponses calculées en surface qu’elles soient amplifiées ou dés-amplifiées par rapport à l’excitation à la base (séisme du 21 Mai 2003 à Boumerdès) nous indiquent la présence des effets de site et ce qui permet la dérivation d’un spectre de calcul spécifique au site étudié

Comparative Histological Study on the Algerian Thymus Ciliatus at Different Phenological Stages

The aim of the current study was to compare the histological observations of stems, leaves, and different secretory structures of Thymus ciliatus at three phenological stages. The anatomical observations of stems, leaves, and glandular trichomes were carried out by light microscopy. The results showed that phenological stages do not affect significantly the anatomical, whereas there was a significant increase in secretory trichomes. The glandular trichomes are distributed on the surface of the stems and the leaves. There are only two distinct types of secretory trichomes, Peltate consisting of a basal cell, a stalk cell, and an 8-celled head type, which are distributed more diffusely on the leaf than on the stem, while capitate trichomes were present only on the surface stem samples. Accumulation of essential oils varies according to the seasons with high sizes of trichomes secretory at the flowering period

Cooperative c-Marking Agents for the Foraging Problem

International audienceWe consider the problem of foraging with multiple agents, in which agents must collect disseminate resources in an unknown and complex environment. So far, reactive multi-agent systems have been proposed, where agents can perform simultaneously exploration and path planning. In this work, we aim to decrease exploration and foraging time by increasing the level of cooperation between agents; to this end, we present in this paper a novel pheromone modeling in which pheromone's propagation and evaporation are managed by agents. As in c-marking agents, our agents are provided with very limited perceptions, and they can mark their environment. Simulation results demonstrate that the proposed model outperforms the c-marking agent-based systems in a foraging mission

Personalizing and Improving Resource Recommendation by Analyzing Users Preferences in Social Tagging Activities

Collaborative tagging which is the keystone of the social practices of web 2.0 has been highly developed in the last few years. In this paper, we propose a new method to analyze user profiles according to their tagging activity in order to improve resource recommendation. We base upon association rules which is a powerful method to discover interesting relationships among large datasets on the web. Focusing on association rules we can find correlations between tags in a social network. Our aim is to recommend resources annotated with tags suggested by association rules, in order to enrich user profiles. The effectiveness of the recommendation depends on the resolution of social tagging drawbacks. In our recommender process, we demonstrate how we can reduce tag ambiguity and spelling variations problems by taking into account social similarities calculated on folksonomies, in order to personalize resource recommendation. We surmount also the lack of semantic links between tags during the recommendation process. Experiments are carried out with two different scenarios: the first one is a proof of concept over two baseline datasets and the second one is a real world application for diabetes disease

Exploring unknown environments with multi-modal locomotion swarm

International audienceSwarm robotics is focused on creating intelligent systems from large number of simple robots. The majority of nowadays robots are bound to operations within mono-modal locomotion (i.e. land, air or water). However, some animals have the capacity to alter their locomotion modalities to suit various terrains, operating at high levels of competence in a range of substrates. One of the most significant challenges in bio-inspired robotics is to determine how to use multi-modal locomotion to help robots perform a variety of tasks. In this paper, we investigate the use of multi-modal locomotion on a swarm of robots through a multi-target search algorithm inspired from the behavior of flying ants. Features of swarm intelligence such as distributivity, robustness and scalability are ensured by the proposed algorithm. Although the simplicity of movement policies of each agent, complex and efficient exploration is achieved at the team level

Novel Approach for Detection and Removal of Moving Cast Shadows Based on RGB, HSV and YUV Color Spaces

Cast shadow affects computer vision tasks such as image segmentation, object detection and tracking since objects and shadows share the same visual motion characteristics. This unavoidable problem decreases video surveillance system performance. The basic idea of this paper is to exploit the evidence that shadows darken the surface which they are cast upon. For this reason, we propose a simple and accurate method for detection of moving cast shadows based on chromatic properties in RGB, HSV and YUV color spaces. The method requires no a priori assumptions regarding the scene or lighting source. Starting from a normalization step, we apply canny filter to detect the boundary between self-shadow and cast shadow. This treatment is devoted only for the first sequence. Then, we separate between background and moving objects using an improved version of Gaussian mixture model. In order to remove these unwanted shadows completely, we use three change estimators calculated according to the intensity ratio in HSV color space, chromaticity properties in RGB color space, and brightness ratio in YUV color space. Only pixels that satisfy threshold of the three estimators are labeled as shadow and will be removed. Experiments carried out on various video databases prove that the proposed system is robust and efficient and can precisely remove shadows for a wide class of environment and without any assumptions. Experimental results also show that our approach outperforms existing methods and can run in real-time systems

An Energy-Aware Algorithm for Large Scale Foraging Systems

International audienceThe foraging task is one of the canonical testbeds for cooperative robotics, in which a collection of coordinated robots have to find and transport one or more objects to one or more specific storage points. Swarm robotics has been widely considered in such situations, due to its strengths such as robustness, simplicity and scalability. Typical multi-robot foraging systems currently consider tens to hundreds of agents. This paper presents a new algorithm called Energy-aware Cooperative Switching Algorithm for Foraging (EC-SAF) that manages thousands of robots. We investigate therefore the scalability of EC-SAF algorithm and the parameters that can affect energy efficiency overtime. Results indicate that EC-SAF is scalable and effective in reducing swarm energy consumption compared to an energy-aware version of the reference well-known c-marking algorithm (Ec-marking)