Differences of behaviour in electrooxidation of 3,3′-dimethoxybenzidine and its N,N,N′,N′-tetraalkylated derivatives: a further example of potential inversion

The anodic oxidation of 3,3′-dimethoxybenzidine and its derivatives were studied by cyclic voltammetry, voltammetry at a rotating platinum electrode, chronopotentiometry and constant potential coulometry. The exhaustive oxidation of 3,3′-dimethoxybenzidine led at the potential of the first oxidation peak and second oxidation peak, respectively, to a stable cation radical salt (characterized by ESR spectroscopy) and to a quinone-diimine. Whereas, 3,3′-dimethoxy-N,N,N′,N′-tetramethylbenzidine afforded directly a dication salt owing to potential inversion 3,3′-dimethoxy-N,N,N′,N′-tetraethylbenzidine gave the corresponding soluble cation radical salt.     

Analysis of information exchange activities to actualize and validate situation awareness during shift changeovers in nuclear power plants

Shift work situations occur in almost all safety‐critical organizations, and the investigations of some catastrophes like Chernobyl, Exxon Valdez, and the Gol/Legacy mid‐air collision indicated that shift work information exchange played an important role during the evolution of the situation before the accidents. Inadequate communications during shift changeovers challenged operators' work in the moments that preceded these accidents, because they got inadequate information about the current situation. Our research focuses on the information exchange activities (verbal, written, and nonverbal) of nuclear power plant control operators during shift changeovers. Our aim is to investigate how verbal exchanges and other representations enable operator crews to share information regarding the events that occurred in the previous shift to achieve adequate situation awareness. Our findings indicated the importance and richness of the information exchange during the shift changeover process to update and validate individual and collective situation awareness, showing that information adequately shared enables the ad hoc configurations of regulation loops and a safer use of simplified strategies that can be understood and be validated by other operators, reducing the occurrence of cognitive overloads and contributing to the construction of a common cognitive ground that enhances system resilience. © 2010 Wiley Periodicals, Inc.     

An Efficient Mobile Data Gathering Method with Tree Clustering Algorithm in Wireless Sensor Networks Balanced and Unbalanced Topologies

Wireless Personal Communications - Electroencephalography (EEG) is a technique of Electrophysiology used in a wide variety of scientific studies and applications. Inadequately, many commercial...     

Schedule-Based Cooperative Multi-agent Reinforcement Learning for Multi-channel Communication in Wireless Sensor Networks

Wireless sensor networks (WSNs) have become an important component in the Internet of things (IoT) field. In WSNs, multi-channel protocols have been developed to overcome some limitations related to the throughput and delivery rate which have become necessary for many IoT applications that require sufficient bandwidth to transmit a large amount of data. However, the requirement of frequent negotiation for channel assignment in distributed multi-channel protocols incurs an extra-large communication overhead which results in a reduction of the network lifetime. To deal with this requirement in an energy-efficient way is a challenging task. Hence, the Reinforcement Learning (RL) approach for channel assignment is used to overcome this problem. Nevertheless, the use of the RL approach requires a number of iterations to obtain the best solution which in turn creates a communication overhead and time-wasting. In this paper, a Self-schedule based Cooperative multi-agent Reinforcement Learning for Channel Assignment (SCRL CA) approach is proposed to improve the network lifetime and performance. The proposal addresses both regular traffic scheduling and assignment of the available orthogonal channels in an energy-efficient way. We solve the cooperation between the RL agents problem by using the self-schedule method to accelerate the RL iterations, reduce the communication overhead and balance the energy consumption in the route selection process. Therefore, two algorithms are proposed, the first one is for the Static channel assignment (SSCRL CA) while the second one is for the Dynamic channel assignment (DSCRL CA). The results of extensive simulation experiments show the effectiveness of our approach in improving the network lifetime and performance through the two algorithms.

     

Photothermoelectric (PTE) Versus Photopyroelectric (PPE) Detection of Phase Transitions

The photopyroelectric (PPE) technique is one of the photothermal (PT) methods mostly used for phase transitions investigations. In this paper, we want to compare the PPE results with those obtained using another, recently developed PT method [the photothermoelectric (PTE) calorimetry] for the same purpose of detecting phase transitions. The well-known ferro-paraelectric phase transition of TGS, taking place at a convenient temperature (about \(49\, {}^{\circ }\hbox {C}\)), has been selected for demonstration. A comparison of the two PPE and PTE methods, both in the back detection configuration (in the special case of optically opaque sample and thermally thick regime for both sensors and sample) shows that they are equally suitable for phase transitions detection. Performing a proper calibration, the amplitude and phase of the signals can be used in order to obtain the critical behaviour of all sample’s static and dynamic thermal parameters.     

On the accurate determination of thermal diffusivity of liquids by using the photopyroelectric thickness scanning method

An enhanced accurate method of measuring the thermal diffusivity of liquids by the sample's thickness scan of the phase of the photopyroelectric signal is presented. The method, making use of the absolute values of the phase and sample thickness, leads to very accurate results for the room temperature values of thermal diffusivity (about +/-0.3%). The high accuracy of the method is due to a very precise control of the sample's thickness variation (0.1 microm step), to a proper localization of the thickness scan range, and to a new procedure of data analysis. The high accuracy of the method recommends it for the study of processes associated with small changes of the thermal parameters.     

Plasma lipids are affected similarly by dietary lauric or palmitic acid in gerbils and monkeys

To compare the relative impact of dietary lauric acid (12∶0) and palmitic acid (16∶0) on plasma lipids, two fat-sensitive species, Mongolian gerbils and cebus monkeys, were fed cholesterol-free, purified diets enriched with either 12∶0-rich or 16∶0-rich fats, while all other fatty acids were held constant by selective blending of up to five natural fats or oils. The two gerbil diets (40 en% from fat) allowed for an 8 en% exchange between 12∶0 and 16∶0, and the monkey diets (31 en% from fat) allowed for 6 en% exchange beteen these two fatty acids. Eight gerbils received the diets for eight weeks, and 12 cebus monkeys were fed each diet in a cross-over design for up to 22 wk. Both diets resulted in similar plasma cholesterol, triglyceride, and high density lipoprotein cholesterol concentrations within each species. Additionally, separation of cebus lipoproteins by discontinuous density-gradient ultracentrifugation failed to show any dietary differences in concentration or composition of the three major lipoprotein classes (d<1.019, 1.019–1.055, and 1.055–1.168 g/mL). Thus, in two species sensitive to manipulations in dietary fat while consuming cholesterol-free diets, 16∶0 was not hypercholesterolemic relative to 12∶0. Based on a paper presented at the PORIM International Palm Oil Congress (PIPOC) held in Kuala Lumpur, Malaysia, September 1993.     

Development of a simulation model for a three-dimensional wind velocity field using Ténès Algeria as a case study

A mathematical simulation model was developed that can determine the three-dimensional wind velocity field over a complex terrain. The Ténès area in the Valley of Cheliff in Algeria was used as a case study. This region is exposed to south-west circulation that makes it favorable to the use of wind energy. Knowledge of wind fields is crucial for predicting the dispersion of pollutants, for forecasting meteorological weather, for fire spread prediction and in the design and implementation of wind turbines. By means of a mass consistent model, an in-house program was developed to calculate the three-dimensional wind velocity field in the study region. The model was supported by a numerical box in which flow through is allowed for in the upper and lateral boundaries. The bottom boundary through which no flow through occurs was determined by the topographic relief at the surface. From measured wind velocities, observed values were calculated by interpolation-extrapolation. Using an optimization method, the adjusted velocities were obtained from constraints, observed velocities and the continuity equation. The model was verified with wind point data, the relative error did not exceed 6%.     

Co1−xZnxFe2O4 (0 ≤ x ≤ 1) nanocrystalline solid solution prepared by the polyol method: Characterization and magnetic properties

Highly crystalline stoichiometric Co_1?xZn_xFe₂O₄ (0 ≤ x ≤ 1) nanoparticles were successfully synthesized by the polyol process. X-ray diffraction (XRD), X-ray fluorescence spectroscopy (XRF), transmission electron microscopy (TEM), infrared spectroscopy (IR), zero-field ⁵⁷Fe Mössbauer spectrometry and magnetic measurements using a SQUID magnetometer were employed to investigate the effect of the substitution of Zn²⁺ ions for Co²⁺ ones on the structure, and the magnetic properties of the cobalt ferrite, CoFe₂O₄. The unit cell parameter almost increases linearly with increasing Zn concentration, x, following Vegard's law. The red and blue shifts observed for the metal-oxygen ν₁ and ν₂ IR vibration bands, respectively, were consistent with the preferential entrance of Zn²⁺ ions in tetrahedral sites. Besides, detailed magnetic investigation in correlation with the cation distribution has been reported. All the particles exhibit superparamagnetic behaviour at room temperature. In addition, the magnetic characteristics (blocking temperature, saturation magnetization, coercivity, Curie temperature) clearly depend on the chemical composition and cation distribution. Both the blocking temperature and Curie temperature decrease drastically with Zn composition, x, increase. Further, the saturation magnetization follows an almost bulk-like behaviour with values notably larger than that of the bulk, mainly attributed to cation distribution deviation.     

An effective hybrid learning system for telecommunication churn prediction

Customer churn has emerged as a critical issue for Customer Relationship Management and customer retention in the telecommunications industry, thus churn prediction is necessary and valuable to retain the customers and reduce the losses. Moreover, high predictive accuracy and good interpretability of the results are two key measures of a classification model. More studies have shown that single model-based classification methods may not be good enough to achieve a satisfactory result. To obtain more accurate predictive results, we present a novel hybrid model-based learning system, which integrates the supervised and unsupervised techniques for predicting customer behaviour. The system combines a modified k-means clustering algorithm and a classic rule inductive technique (FOIL).Three sets of experiments were carried out on telecom datasets. One set of the experiments is for verifying that the weighted k-means clustering can lead to a better data partitioning results; the second set of experiments is for evaluating the classification results, and comparing it to other well-known modelling techniques; the last set of experiment compares the proposed hybrid-model system with several other recently proposed hybrid classification approaches. We also performed a comparative study on a set of benchmarks obtained from the UCI repository. All the results show that the hybrid model-based learning system is very promising and outperform the existing models.