Role of Macrophages and RhoA Pathway in Atherosclerosis

The development, progression, or stabilization of the atherosclerotic plaque depends on the pro-inflammatory and anti-inflammatory macrophages. The influx of the macrophages and the regulation of macrophage phenotype, inflammatory or anti-inflammatory, are controlled by the small GTPase RhoA and its downstream effectors. Therefore, macrophages and the components of the RhoA pathway are attractive targets for anti-atherosclerotic therapies, which would inhibit macrophage influx and inflammatory phenotype, maintain an anti-inflammatory environment, and promote tissue remodeling and repair. Here, we discuss the recent findings on the role of macrophages and RhoA pathway in the atherosclerotic plaque formation and resolution and the novel therapeutic approaches.     

Genetic algorithm for the design of a class of fuzzy controllers:an alternative approach

A simple, easy to implement alternative method for designing fuzzy logic controllers (FLCs) with symmetrically distributed fuzzy sets in a universe of discourse is introduced. The design parameters include the parameters of the membership functions of the inputs and outputs and the rule base. The method is based on a network implementation of the FLC with real and binary weights with constraints. Due to the presence of the binary weights the backpropagation technique cannot be used. The learning problem is cast as a mixed integer constrained dynamic optimization problem and solved using the genetic algorithm (GA). The crossover and mutation are slightly disrupted in order to cope with the constraints on the binary weights. Training of the controller is carried out in a closed-loop simulation with the controller in the loop     

Coupled heat and moisture transfer in multi-layer building materials

A dynamic mathematical model for simulating the coupled heat and moisture migration through multi-layer porous building materials was proposed. Vapor content and temperature were chosen as the principal driving potentials. The discretization of the governing equations was done by the finite difference approach. A new experimental set-up was also developed in this study. The evolution of transient temperature and moisture distributions inside specimens were measured. The method for determining the temperature gradient coefficient was also presented. The moisture diffusion coefficient, temperature gradient coefficient, sorption–desorption isotherms were experimentally evaluated for some building materials (sandstone and lime-cement mortar). The model was validated by comparing with the experimental data with good agreement. Another advantage of the method lies in the fact that the required transport properties for predicting the non-isothermal moisture flow only contain the vapor diffusion coefficient and temperature gradient coefficient. They are relatively simple, and can be easily determined.     

A Stable Model-Based Fuzzy Predictive Control Based on Fuzzy Dynamic Programming

A stable model based fuzzy predictive controller based on fuzzy dynamic programming is introduced. The objective of the fuzzy predictive controller is to drive the state of the system to a terminal region where a local stabilizing controller is invoked, leading to a dual mode strategy. The prediction horizon is fixed and specified. The stability of the controlled system is studied using the value function as a Lyapunov function. Guaranteed stability is obtained under conditions on the terminal region, the local control law and the membership functions of fuzzy goal and constraints therein. The solution procedure is based on dynamic programming with branch and bound.     

Direct adaptive neural network controller for a class of nonlinear systems based on fuzzy estimator of the control error

A new approach of direct adaptive control of single input single output nonlinear systems in affine form using single-hidden layer neural network (NN) is introduced. In contrast to the algorithms in the literature, the weights adaptation laws are based on the control error and not on the tracking error or its filtered version. Since the control error is being expressed in terms of the NN controller, hence its weights updating laws are obtained via back-propagation concept. A fuzzy inference system (FIS) with heuristically defined rules is introduced to provide an estimate of this error based on the past history of the system behaviour. The stability of the closed loop is studied using Lyapunov theory. A fixed structure is then proposed for the FIS and the design parameters reduce to the parameters of the NN. The method is reproducible and does not require any pre-training of the network weights.     

Bacterial-based additives for the production of artificial snow: What are the risks to human health?

For around two decades, artificial snow has been used by numerous winter sports resorts to ensure good snow cover at low altitude areas or more generally, to lengthen the skiing season. Biological additives derived from certain bacteria are regularly used to make artificial snow. However, the use of these additives has raised doubts concerning the potential impact on human health and the environment. In this context, the French health authorities have requested the French Agency for Environmental and Occupational Health Safety (Afsset) to assess the health risks resulting from the use of such additives. The health risk assessment was based on a review of the scientific literature, supplemented by professional consultations and expertise. Biological or chemical hazards from additives derived from the ice nucleation active bacterium Pseudomonas syringae were characterised. Potential health hazards to humans were considered in terms of infectious, toxic and allergenic capacities with respect to human populations liable to be exposed and the means of possible exposure. Taking into account these data, a qualitative risk assessment was carried out, according to four exposure scenarios, involving the different populations exposed, and the conditions and routes of exposure. It was concluded that certain health risks can exist for specific categories of professional workers (mainly snowmakers during additive mixing and dilution tank cleaning steps, with risks estimated to be negligible to low if workers comply with safety precautions). P. syringae does not present any pathogenic capacity to humans and that the level of its endotoxins found in artificial snow do not represent a danger beyond that of exposure to P. syringae endotoxins naturally present in snow. However, the risk of possible allergy in some particularly sensitive individuals cannot be excluded. Another important conclusion of this study concerns use of poor microbiological water quality to make artificial snow.     

Effect of extraction methods on kinetic,chemical composition and antibacterial activities of Tunisian Thymus vulgaris. L. essential oil

The present study aims to compare two innovative extraction techniques: microwave-assisted hydrodistillation (MAHD) and solvent-free microwave extraction (SFME) through traditional extraction techniques: hydrodistillation (HD) and steam distillation (SD) for their efficiency in the extraction of the volatile compounds from Tunisian Thymus vulgaris leaves; the kinetic, yield, composition and antibacterial activities of the essential oil were assessed in vitro. Results show that the essential oils extracted by microwaves were quantitatively (yield) similar to those obtained through the conventional methods, but qualitatively, essential oils analysed by gas chromatography–mass spectrometry (GC–MS) presented 17, 11, 11 and 8 compounds obtained through SFME, MAHD, SD and HD, respectively, mostly consisting of carvacrol (89.24–41.17%), followed by γ-terpinene (11.37–1.37%) and para-cymene (27.95–2.05%). The essential oils were screened for antibacterial activity against 5 microorganisms. All essential oils obtained by studied extraction methods showed the same resistance against Gram (?) and Gram (+) bacteria. The SFME method gave the best results: rapid kinetic of extraction (30 min vs. 35 min for MAHD, 120 min for SD, and 180 min for HD), less energy saving and cleanest process.     

Generating a Condensed Representation for Association Rules

Association rule extraction from operational datasets often produces several tens of thousands, and even millions, of association rules. Moreover, many of these rules are redundant and thus useless. Using a semantic based on the closure of the Galois connection, we define a condensed representation for association rules. This representation is characterized by frequent closed itemsets and their generators. It contains the non-redundant association rules having minimal antecedent and maximal consequent, called min-max association rules. We think that these rules are the most relevant since they are the most general non-redundant association rules. Furthermore, this representation is a basis, i.e., a generating set for all association rules, their supports and their confidences, and all of them can be retrieved needless accessing the data. We introduce algorithms for extracting this basis and for reconstructing all association rules. Results of experiments carried out on real datasets show the usefulness of this approach. In order to generate this basis when an algorithm for extracting frequent itemsets—such as Apriori for instance—is used, we also present an algorithm for deriving frequent closed itemsets and their generators from frequent itemsets without using the dataset.     

A Strategy for Controlling Groundwater Depletion in the Sa'dah Plain,Yemen

Over-exploitation of the groundwater resources is the major problem leading to groundwater depletion in the Sa'dah Plain, one of the major semi-arid highland basins of Yemen. Groundwater-irrigated agriculture is the chief economic activity in the Plain. Consequently, depletion places socioeconomic development in jeopardy. Owing to the lack of institutional arrangements and management instruments, government intervention is not likely to alleviate the crisis. One non-governmental approach that takes advantage of the existing local sociopolitical structure and customary law would be to adopt an annual abstraction quota. Approaching the crisis at a grass-roots level and relying on the conformity of the local citizens with customary law are the main characteristics of this strategy, the optimum objective of which is sustainable utilization of water resources.     

Enhancing Emergency Messages Dissemination in Vehicular Networks Using Network Coding

Vehicular ad-hoc networks play an important role in providing safety on the road. Vehicles generate and exchange emergency and control messages to avoid dangerous situations. According to IEEE 1609.4 standard, all these messages share the same control channel interval even if the emergency messages are with a highest priority. Besides that, network’s characteristics, such as vehicle density and high mobility, would make the diffusion of emergency messages a challenging task. Especially with the absence of acknowledgements and retransmission. Network coding could be seen as a solution where a block of data packets could be sent on the same transmission process. Firstly, we analyze the messages’ dissemination, and we propose a thoroughly model for success probability according to the emergency messages’ generation probabilities. Further, we propose a new network coding access scheme. The emergency messages take the priority in the channel access and it could be retransmitted several times. Thus, the scheme deals with the emergency messages’ loss and latency. NS-3 simulations show that our model increases emergency messages’ reliability.