Towards the Development of Small‐Molecule MO25 Binders as Potential Indirect SPAK/OSR1 Kinase Inhibitors

The binding of the scaffolding protein MO25 to SPAK and OSR1 protein kinases, which regulate ion homeostasis, causes increases of up to 100‐fold in their catalytic activity. Various animal models have shown that the inhibition of SPAK and OSR1 lowers blood pressure, and so here we present a new indirect approach to inhibiting SPAK and OSR1 kinases by targeting their protein partner MO25. To explore this approach, we developed a fluorescent polarisation assay and used it in screening of a small in‐house library of ≈4000 compounds. This led to the identification of one compound—HK01—as the first small‐molecule inhibitor of the MO25‐dependent activation of SPAK and OSR1 in vitro. Our data confirm the feasibility of targeting this protein–protein interaction by small‐molecule compounds and highlights their potential to modulate ion co‐transporters and thus cellular electrolyte balance.     

Numerical and experimental study of dryer in forced convection

A numerical simulation model is developed to predict the forced convection performance of a dryer. This model takes into account the shrinkage phenomenon of the products during the drying process. The experimental results of the potato drying are obtained in climatic conditions similar to conditions found in natural open‐air drying when the dryer is fed by air heated by a solar air flat plate collector. After a study of the influence of parameters of the drying air on the product during the drying process, we expose the experimental results and compare them with those calculated by the theoretical model. Copyright © 2001 John Wiley & Sons, Ltd.     

Bond-slip law and short tie behavior without main cracks

The aim of this paper is to study the reinforced concrete short tie-rods behavior using the adhesion-slip curve shape between steel and concrete adopted by the European Concrete Committee. We are interested here in short tie-rods without main cracks for which we calculate and measure the maximum mobilization state of steel-concrete adhesion, and beyond the decrease mode of this bond. For this, tests of short tie-rods, with different high adhesion rebar diameters have been carried out. To characterize the first phase of the adhesion-slip behavior law (τ?g), pull out tests have been carried out with the same concrete, the same reinforcement and the same cross-section such as the tie-rod tests, with a proposed method to estimate the adhesion peak and the corresponding slip. For this adhesion peak value, slightly underestimated by the conventional curve of the European Concrete Committee, a new expression is suggested. A numerical model with theoretical relations of the behavior of such tie-rods is proposed. The comparison of this model with the obtained test curves of the short tie-rods shows a suitable approach. Also, we deduce that the steel (coated with concrete) fictitious module slope is even higher than the percentage of reinforcement is low. These results may help to understand the tie-rods behavior generally, in the phase of cracks stabilization, during which the tie-rod is composed of short tie-rods without main cracks.     

Simulation of a new concept of an indirect solar dryer equipped with offset rectangular plate fin absorber‐plate

A simulation code was developed to predict the indirect solar dryer performance of the thin beds of discs of potato, subjected to time‐varying air conditions. Two mathematical models are developed separately; the first allows the determination of the thermal performances of the solar collector with offset rectangular plate fin absorber‐plate and the second, allows to determine the kinetics of drying for the data input of the air at the exit of the collector. The latter takes into account calorific losses through the walls of the dryer and shrinkage of discs. Experimental results of the solar dryer thermal performances, using sunlight in Valenciennes (in the North of France), will be compared with the results obtained by the theoretical model suggested. Copyright © 2005 John Wiley & Sons, Ltd.     

Interference‐aware clustering approach improving QoS for linear WSNs using a token‐based MAC protocol

Wireless sensor networks (WSNs) have received a lot of attention from both academia and industry due to the increasing need for ubiquitous computing for monitoring applications, the continuous advances in miniaturization of electronic devices, and the ultra‐low‐power wireless technologies. These innovations in technology have driven the curiosity to use sensor networks in a new kind of applications such as road track or railway monitoring, border monitoring, oil and gas, or even water pipeline monitoring. Due to the underlying linear topology of these applications, a new type of network, called a linear sensor network (LSN), has emerged. Because of the specific characteristics of this application and the resource constraints of sensors, some of the major challenges faced in LSNs are to reduce end‐to‐end delays, to maximize the packet delivery ratio to a sink, and an even distribution of the load between nodes. To achieve these objectives, it is necessary to control node‐to‐node packet traffic conditions and to manage radio interference created by simultaneously active nodes. This paper addresses these challenges and proposes a new method of clustering LSNs that reduces or controls radio interference risks in order to satisfy these objectives, application needs, and the resource limitations of sensor nodes in the best possible way. This method is applied for LSNs using a token‐passing mechanism to access the medium. The performance evaluation is conducted by using a realistic propagation model in the analytical evaluation and also a NS‐2 simulation process.     

Mining of High-Utility Patterns in Big IoT-based Databases

When focusing on the general area of data mining, high-utility itemset mining (HUIM) can be defined as an offset of frequent itemset mining (FIM). It is known to emphasize more factors critically, which gives HUIM its intrinsic edge. Due to the flourishing development of the IoT technique, the uncertainty patterns mining is also attractive. Potential high-utility itemset mining (PHUIM) is introduced to reveal valuable patterns in an uncertainty database. Unfortunately, even though the previous methods are all very effective and powerful to mine, the potential high-utility itemsets quickly. These algorithms are not specifically designed for a database with an enormous number of records. In the previous methods, uncertainty transaction datasets would be load in the memory ultimately. Usually, several pre-defined operators would be applied to modify the original dataset to reduce the seeking time for scanning the data. However, it is impracticable to apply the same way in a big-data dataset. In this work, a dataset is assumed to be too big to be loaded directly into memory and be duplicated or modified; then, a MapReduce framework is proposed that can be used to handle these types of situations. One of our main objectives is to attempt to reduce the frequency of dataset scans while still maximizing the parallelization of all processes. Through in-depth experimental results, the proposed Hadoop algorithm is shown to perform strongly to mine all of the potential high-utility itemsets in a big-data dataset and shows excellent performance in a Hadoop computing cluster.

     

Fuzzy-PSO controller design for maximum power point tracking in photovoltaic system

Photovoltaic power generation system becomes increasingly important, highly attractive as a clean and renewable energy sources, widely used today in many applications. Recently, researchers have strongly promoted the use of solar energy as a viable source of energy due to its advantages and which it can be integrated into local and regional power supplies. The P–V curve of photovoltaic system exhibits multiple peaks under various conditions of functioning and changes in meteorological conditions which reduces the effectiveness of conventional maximum power point tracking (MPPT) methods and the Particle swarm optimization (PSO) algorithm is considered to be highly efficient for the solution of complicated problems.In this paper, the application of this approach based MPPT algorithm for Photovoltaic power generation system operating under variable conditions is proposed to optimize and to design an intelligent controller comparing to conventional one. PSO Approaches is considered to select and generate an optimal duty cycle which varies with photovoltaic parameters in order to extract the maximum Power. Simulation results show that the proposed approach can track the maximum power point faster and can improve the performance of the system compared to the conventional method.     

Robust diagnosis to measurement uncertainties using bond graph approach: Application to intelligent autonomous vehicle

This paper deals with robust bond graph model-based fault detection and isolation to improve the robustness of the diagnosis system in presence of measurements and parameters uncertainties. We develop a procedure of measurement uncertainties modeling directly on the graph. By using the structural and causal properties of the bond graph, the robust diagnosis is performed. The interest of the developed methodology consists in using the graphical tool not only for measurement uncertainties modeling, but also for designing robust fault detection and isolation algorithms. Moreover, this method can be easily automated. The developed approach is validated by an application to an electromechanical traction system of intelligent autonomous vehicle.