Adaptive fuzzy control of DC motors using state and output feedback

Conventional PID of state feedback controllers for DC motors have poor performance when changes of the motor or load dynamics take place. To handle this shortcoming adaptive fuzzy control of DC motors is proposed. Neuro-fuzzy networks are used to approximate the unknown motor dynamics. The information needed to generate the control signal comes from feedback of the full state vector or from feedback of only the system’s output. In the latter case a state observer is used to estimate the parameters of the state vector. The stability of the closed-loop system is proved with the use of Lyapunov analysis. The performance of the proposed control approach is evaluated through simulation tests.     

Particle and Kalman filtering for state estimation and control of DC motors

State estimation is a major problem in industrial systems. To this end, Gaussian and nonparametric filters have been developed. In this paper the Kalman Filter, which assumes Gaussian measurement noise, is compared to the Particle Filter, which does not make any assumption on the measurement noise distribution. As a case study the estimation of the state vector of a DC motor is used. The reconstructed state vector is used in a feedback control loop to generate the control input of the DC motor. In simulation tests it was observed that for a large number of particles the Particle Filter could succeed in accurately estimating the motor’s state vector, but at the same time it required higher computational effort.     

Removal of phenolics in olive mill wastewaters using the white-rot fungus Pleurotus ostreatus

Olive mill wastewaters (OMW) present a major environmental problem. The large amounts generated, combined with the high phenols and chemical oxygen demand concentrations, are the main difficulties in finding a solution for the management of these wastewaters, which are dangerous for the environment. The phenols, which are contained in the OMW have a structure similar to lignin, which makes them difficult to biodegrade. Lignin can be degraded only by a few microorganisms, such as "white-rot" basidiomycete, which produce manganese (MnPs) and lignin peroxidases (LiPs) and laccases that are responsible for the oxidisation of lignin compounds. The capability of Pleurotus ostreatus to degrade phenols of OMW in different conditions such as in sterilized and thermally processed (at 100 degrees C) wastewater, with and without dilution, is investigated in this work. According to the experimental results P. ostreatus removed phenols from the culture medium, under all different conditions that were examined. The degradation of phenols reached up to 78.3% for the sterilized and 50% diluted OMW, 66.7% and 64.7% for the thermally processed OMW, with and without dilution, respectively. The effect of pre-treatment of OMW on the performance of anaerobic digestion is also assessed, as methanogenic bacteria are seriously affected by the presence of phenol compounds. The pre-treated wastewater was shown to be more amenable to a subsequent anaerobic digestion.     

The Role of Exosomal Non-Coding RNAs in Colorectal Cancer Drug Resistance

Background: Colorectal cancer (CRC) is one of the most common types of cancer diagnosed worldwide with high morbidity; drug resistance is often responsible for treatment failure in CRC. Non-coding RNAs (ncRNAs) play distinct regulatory roles in tumorigenesis, cancer progression and chemoresistance. Methods: A literature search was conducted in PubMed database in order to sum up and discuss the role of exosomal ncRNAs (ex-ncRNAs) in CRC drug resistance/response and their possible mechanisms. Results: Thirty-six (36) original research articles were identified; these included exosome or extracellular vesicle (EV)-containing microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs) and small-interfering (siRNAs). No studies were found for piwi-interacting RNAs. Conclusions: Exosomal transfer of ncRNAs has been documented as a new mechanism of CRC drug resistance. Despite being in its infancy, it has emerged as a promising field for research in order to (i) discover novel biomarkers for therapy monitoring and/or (ii) reverse drug desensitization.     

A Monte Carlo pore network for the simulation of porous characteristics of functionalized silica: pore size distribution, connectivity distribution and mean tortuosities

The simulation of the random porous network of five samples of functionalized SiO₂ took place using a dual-site-bond model (DSBM) and Monte Carlo techniques for achieving the proper arrangement of the pores into the system. The simulation took place in 7×7×7 lattice. As a starting point of simulation the adsorption branch of N₂ isotherm was considered from which the pore size distribution was estimated. Then as a benchmark of simulation the N₂ desorption branch was considered whose fitting was achieved using the Monte Carlo technique for selecting the proper place of each pore into the 7×7×7 lattice. From the obtained model, it was possible to estimate the distribution of pore connectivities of each system. The mean value of those connectivity distributions tallies with the corresponding mean values estimated using the standard methodology of Seaton. In addition, the mean tortuosity of the porous network was estimated and the results were favorably compared with values of tortuosity estimated recently via the so-called corrugated-pore-structure-model (CPSM) for the same solids. The degree of functionalization of the parent SiO₂ affects both connectivity and tortuosity in a linear way. Some discrepancies observed between the results obtained via this methodology and the ones obtained using the Seaton or the CPSM model are discussed.     

Matrix effect during the application of a rapid method using HS-SPME followed by GC–ECD for the analysis of 2,4,6-TCA in wine and cork soaks

An off-flavor in wine known as ‘cork taint’ is of concern in the wine and cork industry. Cork taint imparts a musty flavor to the wine and is primarily due to the presence of 2,4,6-trichloroanisole [2,4,6-TCA] in cork stoppers. During this study, an instrumental method for 2,4,6-TCA analysis was developed and evaluated using headspace solid-phase microextraction (HS-SPME) and gas chromatography coupled with an electron capture detector (GC–ECD). 2,3,6-Trichlorotoluene [2,3,6-TCT] was assayed as the internal standard. The method was developed in synthetic wine and was applied in commercial wine samples, as well as in cork soaks obtained by the extraction of TCA from cork stoppers and cork barks using synthetic wine. The method performance was evaluated through the estimation of its linearity (R² > 0.99), repeatability (RSD value = 5.72%) and sensitivity (recovery > 86%, LOD = 0.177–0.368 ng/L) in different types of samples. Due to the complexity of the samples used, the study has been especially focused on the matrix effects that were identified causing significant bias to the quantitative analysis of 2,4,6-TCA in cork soaks, where there is a lack of previous studies.