Neuro-Fuzzy Combination for Reactive Mobile Robot Navigation: A Survey

Autonomous navigation of mobile robots is a fruitful research area because of the diversity of methods adopted by artificial intelligence. Recently, several works have generally surveyed the methods adopted to solve the path-planning problem of mobile robots. But in this paper, we focus on methods that combine neuro-fuzzy techniques to solve the reactive navigation problem of mobile robots in a previously unknown environment. Based on information sensed locally by an onboard system, these methods aim to design controllers capable of leading a robot to a target and avoiding obstacles encountered in a workspace. Thus, this study explores the neuro-fuzzy methods that have shown their effectiveness in reactive mobile robot navigation to analyze their architectures and discuss the algorithms and metaheuristics adopted in the learning phase

Evaluation of adherence to gluten-free diets in Moroccan celiac patients and factors of adherence failure

The prevalence of celiac disease (CD) is increasing in the world. In Morocco, its incidence is also increasing considerably. The gluten-free diet (GFD) remains the only effective treatment so far. Its effectiveness depends essentially on good adherence to this diet. However, several factors hinder adherence by contributing to diet failure. Within this framework, this study aims to evaluate adherence to this diet in celiac children and adolescents continuing in a tertiary health center. The article also looks to identify the different factors influencing adherence to GFD in Morocco. The results show from serological and/or biopsy tests on 238 celiac patients that half had good adherence and 13% had poor adherence. The questionnaire aimed at 127 parents or proxies of celiac children and adolescents shows that several factors are responsible for the failure to adhere to the diet such as the role of the mass media, cultural and psychological factors. The exorbitant price, nutritional quality, and low availability of gluten-free products play a major role in GFD failure. Low socio-economic factors have a negative influence on the adherence to the GFD

Furfural Analogs as Sustainable Corrosion Inhibitors—Predictive Efficiency Using DFT and Monte Carlo Simulations on the Cu(111), Fe(110), Al(111) and Sn(111) Surfaces in Acid Media

Nowadays, theoretical calculation tools have become powerful in predicting the behavior of corrosion inhibitors on the surface of metals and, therefore, avoiding energy consumption and the cost of experimental tests. This work aims to predict the inhibitory power of some furan derivatives on Cu (111), Fe (110), Al (111) and Sn (111) surfaces in acidic media. For this purpose, three furan derivatives—furan-2-carbaldehyde (FF1), 5-(hydroxymethyl)furfural (FF2) and 5-(hydroxymethyl)furoic acid (FF3)—have been selected to compare their intrinsic properties against corrosion as well as their behavior on iron (Fe), copper (Cu), aluminum (Al) and tin (Sn) surfaces in acid medium. Typically, the anti-corrosive properties of FF1, FF2 and FF3 were studied by using quantum chemical calculations and Monte Carlo simulations. Density Functional Theory (DFT), lowest unoccupied (ELUMO) and highest occupied (EHOMO) molecular orbital energies, energy gap (∆E), chemical hardness (η), softness (σ), electronegativity (χ), electrophilicity (ω) and nucleophilicity (ε) have been calculated and discussed. Theoretical vibrational spectra were also calculated to exhibit the functional groups in the selected chemicals. On the other hand, the adsorption behaviors of FF1, FF2 and FF3 were studied on the Fe(110), Cu(111), Al(111) and Sn(111) surfaces. As a result, the adsorption energies of all molecules are ordered as Fe(110) < Cu(111) < Al(111) < Sn(111) and FF3 seems to be more effective as a corrosion inhibitor due to the existence of both carboxylic acid and hydroxyl groups, which consist of favorable sites of adsorption into the metal surface