Experimental investigation of solar tower with chimney effect installed in CRTEn,Tunisia

This paper studies the performance of a solar tower power plant (STPP) with chimney effect based on renewable energy proposed for electricity production. That's way, a solar tower prototype was constructed and tested in the Research and Technology Centre of Energy (CRTEn), Borj Cédria, northern Tunisia.The design involves heating air using solar energy and the chimney effect to raise the hot air up the chimney stack. The hot air velocity increases by the use of a convergent nozzle to reach a suitable velocity which can run the wind turbine. The kinetic energy of the hot air is then converted to electricity by the wind turbine.During this study, the influence of the climatic conditions of Borj Cédria site (insulation, ambient temperature) as well as the chimney height and the collector diameter on the amount of electricity production were investigated.The distribution and the evolution of the temperature at different positions of the prototype as well as the electrical energy produced were determined.The results reveal that when the temperatures reach 45 °C, the electric power reaches an average value of about 0.3 W/m² for a solar tower prototype with 8 m of diameter and 2 m of height chimney.     

Combination of PDMS microfilters and micromixers based on flexible thermoplastic films for size sorting and mixing of microparticles

We present a study for the development of flexible microfilters based on sealing microstructured poly(dimethylsiloxane) (PDMS) to different functionalized thermoplastic films [polyimide (PI), polyethylene naphthalate (PEN), and polyethylene terephthalate (PET)]. The microfilter was manufactured by soft‐lithography and replica molding and then combined with plasma activation and chemical treatment using 3‐(aminopropyl)triethoxysilane (APTES). To demonstrate the functionality of the PDMS microfilters, poly(lactic‐co‐glycolic acid) (PLGA) microparticles (MPS) were filtered through the microfluidic device based on the three thermoplastic films. Subsequently, the mixing capabilities of a passive PDMS micromixer was observed with the injection of polymeric MPS (fluorescent and nonfluorescent) as fluidic mixers are not generally effective at mixing particles. On mixing nonfluorescent MPS (～<10–30 µm in diameter) a mixing performance of 13.3% at 5 mm was observed. Therefore, a PDMS microfiltering device was integrated with a PDMS micromixer using a simple and cost effective home‐made polymeric connector for filtration at a size sorting of 11 µm. The results exhibit that the combination of the two microfluidic devices can be achieved with size sorting and mixing of MPS with an improved mixing performance of 62.5% at 3 mm. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42088.     

Influence of regeneration conditions on the cyclic performance of amine-grafted mesoporous silica for CO2 capture: An experimental and statistical study

This work deals with the behavior of amine-grafted mesoporous silica (referred to as TRI-PE-MCM-41) throughout adsorption–desorption cycles in the presence of 5% CO₂/N₂ using various regeneration conditions in batch experiments. The criteria proposed to determine the optimum regeneration conditions are the working adsorption capacity, the rate of desorption and the change of adsorption capacity between consecutive cycles. Using a 2³ factorial design of experiments, the impact on the performance of the adsorbent of different levels of temperature, pressure, and flow rate of purge gas during desorption was determined. It was found that all the parameters under study have a statistically significant influence on the working adsorption capacity, but only temperature is influential with respect to desorption rate. Regeneration using temperature swing was found to be attractive, as the highest CO₂ adsorption capacity (1.95 mmol g^?1) and the fastest desorption rate (9.82×10^?4 mmol g^?1 s^?1) occurred when desorption was carried out at 150 °C. However, if vacuum is applied, regeneration can be achieved at a temperature as low as 70 °C with only a 13% penalty in terms of working adsorption capacity. It was also demonstrated that under the proper regeneration conditions, TRI-PE-MCM-41 is stable over 100 adsorption–desorption cycles.     

Cancer prognostics by direct detection of p53-antibodies on gold surfaces by impedance measurements

The identification and measurement of biomarkers is critical to a broad range of methods that diagnose and monitor many diseases. Serum auto-antibodies are rapidly becoming interesting targets because of their biological and medical relevance. This paper describes a highly sensitive, label-free approach for the detection of p53-antibodies, a prognostic indicator in ovarian cancer as well as a biomarker in the early stages of other cancers. This approach uses impedance measurements on gold microelectrodes to measure antibody concentrations at the picomolar level in undiluted serum samples. The biosensor shows high selectivity as a result of the optimization of the epitopes responsible for the detection of p53-antibodies and was validated by several techniques including microcontact printing, self-assembled-monolayer desorption ionization (SAMDI) mass spectrometry, and adhesion pull-off force by atomic force microscopy (AFM). This transduction method will lead to fast and accurate diagnostic tools for the early detection of cancer and other diseases.     

Preparation and characterization of CeO2–TiO2 support for Ru catalysts: Application in CWAO of p-hydroxybenzoic acid

The catalytic wet air oxidation of aqueous solutions of p-hydroxybenzoic acid has been carried out over CeO₂–TiO₂ supported ruthenium catalysts (Ru/Ce–Ti) at 140 °C and 50 bar of air. High activity of ruthenium supported catalysts was observed. It was found that the decrease of the molar ratio Ce/Ti from 3 to 1/3, improves the activity of Ru catalysts. The activity of the samples decreases in the following order: Ru/Ce–Ti (1/3) > Ru/CeO₂ ≈ Ru/TiO₂ > Ru/TiO₂DT51. Characterization of samples was performed by means of N₂ adsorption–desorption, XRD, UV–visible, TPR, SEM and TEM.     

Effects of frying on the fatty acid composition in farmed and wild gilthead sea bream (Sparus aurata)

The effects of frying in soybean (FWSO) and olive oils (FWOO) on the fatty acid composition of farmed and wild gilthead sea bream Sparus aurata were evaluated. The fat content increased with both frying treatments. However, after FWOO the moisture content of the fish was reduced to a greater extent than that in fish FWSO. The concentration of saturated fatty acids (SFA) decreased significantly during both frying processes ( P  < 0.01). However, the concentration of monounsaturated fatty acids (MUFA) increased significantly in fish fried in olive oil ( P  < 0.01). The fried fish contained a higher level of n-6 polyunsaturated fatty acids (PUFA) and a lower level of n-3 PUFA compared to raw fish. The n-3/n-6 ratio decreased in wild fish FWSO and FWOO from 0.94 ± 0.08 to 0.15 ± 0.01 and 0.15 ± 0.02, respectively. In farmed bream, the ratios decreased from 2.51 ± 0.03 to 0.18 ± 0.03 and 0.36 ± 0.01, respectively. The concentration of trans fatty acids decreased significantly in both fish types after frying ( P  < 0.05). The frying process widely affected the EPA and DHA content, limiting the positive effects of n-3 PUFA.     

Experimental and numerical investigation of using waste glass aggregates in asphalt pavement to mitigate urban heat islands

Clean Technologies and Environmental Policy - In this study, the experimental and numerical effects of using waste glass as aggregates of asphalt pavement are evaluated. The main reason for using...     

Metaheuristic Optimization of Time Series Models for Predicting NetworksTraffic

Traffic prediction of wireless networks attracted many researchers and practitioners during the past decades. However, wireless traffic frequently exhibits strong nonlinearities and complicated patterns, which makes it challenging to be predicted accurately. Many of the existing approaches for predicting wireless network traffic are unable to produce accurate predictions because they lack the ability to describe the dynamic spatial-temporal correlations of wireless network traffic data. In this paper, we proposed a novel meta-heuristic optimization approach based on fitness grey wolf and dipper throated optimization algorithms for boosting the prediction accuracy of traffic volume. The proposed algorithm is employed to optimize the hyper-parameters of long short-term memory (LSTM) network as an efficient time series modeling approach which is widely used in sequence prediction tasks. To prove the superiority of the proposed algorithm, four other optimization algorithms were employed to optimize LSTM, and the results were compared. The evaluation results confirmed the effectiveness of the proposed approach in predicting the traffic of wireless networks accurately. On the other hand, a statistical analysis is performed to emphasize the stability of the proposed approach.     

Network Intrusion Detection Based on Feature Selection and Hybrid Metaheuristic Optimization

Applications of internet-of-things (IoT) are increasingly being used in many facets of our daily life, which results in an enormous volume of data. Cloud computing and fog computing, two of the most common technologies used in IoT applications, have led to major security concerns. Cyberattacks are on the rise as a result of the usage of these technologies since present security measures are insufficient. Several artificial intelligence (AI) based security solutions, such as intrusion detection systems (IDS), have been proposed in recent years. Intelligent technologies that require data preprocessing and machine learning algorithm-performance augmentation require the use of feature selection (FS) techniques to increase classification accuracy by minimizing the number of features selected. On the other hand, metaheuristic optimization algorithms have been widely used in feature selection in recent decades. In this paper, we proposed a hybrid optimization algorithm for feature selection in IDS. The proposed algorithm is based on grey wolf (GW), and dipper throated optimization (DTO) algorithms and is referred to as GWDTO. The proposed algorithm has a better balance between the exploration and exploitation steps of the optimization process and thus could achieve better performance. On the employed IoT-IDS dataset, the performance of the proposed GWDTO algorithm was assessed using a set of evaluation metrics and compared to other optimization approaches in the literature to validate its superiority. In addition, a statistical analysis is performed to assess the stability and effectiveness of the proposed approach. Experimental results confirmed the superiority of the proposed approach in boosting the classification accuracy of the intrusion in IoT-based networks.     

Optimization of Electrocardiogram Classification Using Dipper Throated Algorithm and Differential Evolution

Electrocardiogram (ECG) signal is a measure of the heart’s electrical activity. Recently, ECG detection and classification have benefited from the use of computer-aided systems by cardiologists. The goal of this paper is to improve the accuracy of ECG classification by combining the Dipper Throated Optimization (DTO) and Differential Evolution Algorithm (DEA) into a unified algorithm to optimize the hyperparameters of neural network (NN) for boosting the ECG classification accuracy. In addition, we proposed a new feature selection method for selecting the significant feature that can improve the overall performance. To prove the superiority of the proposed approach, several experiments were conducted to compare the results achieved by the proposed approach and other competing approaches. Moreover, statistical analysis is performed to study the significance and stability of the proposed approach using Wilcoxon and ANOVA tests. Experimental results confirmed the superiority and effectiveness of the proposed approach. The classification accuracy achieved by the proposed approach is (99.98%).