Inhibition of nicotine-induced seizures in rats by combining vaccination against nicotine with chronic nicotine infusion.

The ability of a nicotine vaccine to protect against nicotine-induced seizures was studied in rats. Groups of 10 rats were vaccinated with 3 doses of either a nicotine conjugate vaccine over 6 weeks to elicit high titters of nicotine-specific antibodies or with a control vaccine. Rats were then pretreated with a 1-weekk subcutaneous infusion of either nicotine 1 mg/kg/day or saline and then received a single 2 mg/kg ip dose of nicotine to provoke seizures. Vaccination reduced the incidence of seizures. The combination of vaccination and pretreatment with nicotine infusion was more effective than either treatment alone. These data suggest that vaccination is protective against this toxic effect of nicotine and that combining vaccination and chronic nicotine administration may provide a novel strategy for blocking some effects of nicotine. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Role of microstructure in sucker rod string failures in oil well production

Sucker-rod pumps are operating in very aggressive environments in oil well production. The combined effect of a corrosive environment and significant mechanical loads contribute to frequent cases of failure of the rod string during operation. Standards and recommendations have been developed to control and avoid those failures. This study presents various failure cases of sucker rods in different applications. The heat treatment of the steel material and the resulting microstructure are an important factor in the behavior of the sucker rod. A spheroidized microstructure presents a weaker resistance to corrosion affecting the rod life. Non-metallic inclusions are a pitting preferential site leading to fatigue crack initiation. Heterogenous microstructure as banded martensite and ferrite/pearlite decreases the ductility of the material affecting the fatigue propagation resistance.     

Corrosion behavior on the different zones of AA2014 welded aluminum alloy by AA5554 filler aluminum alloy with TIG process: Before and after solution heat treatments followed by ageing

In this work, we have studied the effects of solution heat treatment followed by ageing on the corrosion behavior of AA2014 aluminum alloy welded by AA5554 aluminum alloy. Two samples are then analyzed, in the first case the solution heat treatment is followed by quenching and natural ageing of 90 days (sample 1), and in the second one, the solution heat treatment is followed by quenching and artificial ageing of twelve hours at 190°C (sample 2). The principal observations can be summarized as: evaporation of magnesium in fusion zone, and diffusion of magnesium and copper from the heat affected zone to the fusion zone were identified. Solution heat treatment, quenching and 90 days of natural ageing leads to a uniform corrosion in the heat affected zone and in the fusion one, when the material is immersed for ten seconds in Keller reagent solution. After immersion in 0.3% NaCl chloride solution, and after solution treatment and quenching, we observed that applied artificial ageing at 190°C causes localized corrosion surrounding precipitates and then develops uniform corrosion in all zones, particularly in the fusion one. Finally, it is noted that the surface of different zones became nobler after applying solution heat treatment followed by natural ageing.     

Setting time determination of cementitious materials based on measurements of the hydraulic pressure variations

An experimental investigation was carried out to determine the setting time of cement based materials (cement paste, mortar, concrete, etc.). An original method based on measurements of both total lateral pressure and hydraulic pressure has been investigated. An original device has been engineered to measure the pressure kinetics. Just after mixing and filling of the device, a simultaneous drop and an equal value of the both hydraulic and total lateral pressures has been recorded. A definitive cessation of total lateral pressure and negative hydraulic pressures are then observed. The proposed setting time was defined as the elapsed time between the end of mixing and the time at which the hydraulic pressure becomes zero. In addition to the usual W / C parameter, the influence of the vibration and the height of the material tested on the pressure based method were studied. Comparing to other classical methods (Vicat, calorimetry, ultrasonic pulse-echo …), the presented device is efficient with major types of cement based materials (concrete, SCC …) and was able to give a simple and direct information about the mechanical state of the material.     

Preparation and electrochemical properties of nano-sized SnF2 as negative electrode for lithium-ion batteries

Nanocrystalline SnF₂ was prepared via recrystallization of commercially available tin (II) fluoride. The electrochemical performance of tin fluoride as anode material for Li-ion batteries was investigated. The cyclic voltammetry of the obtained material showed occurrence of SnF₂ decomposition at first and a typical reversible alloying/de-alloying process at low potentials. Furthermore, it was found that the synthesized material delivered a high reversible capacity of 1016 mAh g^− 1 and a capacity retention of 54.8% after 30 cycles when the electrode was cycled at a current of 100 mA g^− 1.     

Combination of canonical correlation analysis and empirical mode decomposition applied to denoising the labor electrohysterogram

The electrohysterogram (EHG) is often corrupted by electronic and electromagnetic noise as well as movement artifacts, skeletal electromyogram, and ECGs from both mother and fetus. The interfering signals are sporadic and/or have spectra overlapping the spectra of the signals of interest rendering classical filtering ineffective. In the absence of efficient methods for denoising the monopolar EHG signal, bipolar methods are usually used. In this paper, we propose a novel combination of blind source separation using canonical correlation analysis (BSS_CCA) and empirical mode decomposition (EMD) methods to denoise monopolar EHG. We first extract the uterine bursts by using BSS_CCA then the biggest part of any residual noise is removed from the bursts by EMD. Our algorithm, called CCA_EMD, was compared with wavelet filtering and independent component analysis. We also compared CCA_EMD with the corresponding bipolar signals to demonstrate that the new method gives signals that have not been degraded by the new method. The proposed method successfully removed artifacts from the signal without altering the underlying uterine activity as observed by bipolar methods. The CCA_EMD algorithm performed considerably better than the comparison methods.     

Numerical modelling of rotating packed beds used for CO2 capture processes: A review

Over the last decades, renewable and clean energy sources are being rigorously adopted along with carbon capture technologies to tackle the increasing carbon dioxide (CO₂) concentration level in the environment. CO₂ capture is a quintessential option for tackling global warming issues. In this context, the present paper has reviewed the process intensification equipment called a rotating packed bed (RPB), which is highly industry applicable due to high gravity (HiGee) force. This facilitates strong mass transfer characteristics, a compact design, and low energy consumption. In this review, the current research scenario of RPBs using numerical, computational fluid dynamics (CFD), and mathematical modelling, along with different machine learning approaches in the CO₂ capture process, has been reviewed. The different geometry designs, hydrodynamic characteristics, performance parameters, research methods, and their effects on CO₂ removal efficiency have been discussed. Furthermore, the latest experimental studies are also summarized, especially in the absorption and adsorption domain. Finally, recommendations have been given to support the RPBs in different industrial and commercial applications of CO₂ removal.     

Machine learning-based clustering protocols for Internet of Things networks: An overview

The Internet of Things (IoT) continues to expand the current Internet, opening the door to a wide range of novel applications. The increasing volume of the IoT requires effective strategies to overcome its challenges. Machine Learning (ML) has led to a growing technology that enables computers to solve problems without the need for knowledge of their intricate details. Over the past years, various ML techniques have been used to efficiently manage IoT networks. Clustering is a technique that has proven its performance in the networking domain. Many works in the literature have studied ML-based clustering methods for IoT networks, including their main properties, characteristics, underlying technologies, and open issues. In this paper, we focus on topology-centered ML-based clustering protocols for IoT networks. Specifically, we investigate the potential benefits of adopting the clustering approach to address several IoT challenges. Moreover, we provide a comprehensive taxonomy of ML-based clustering algorithms for IoT networks. Finally, we statistically analyze the incorporation of ML techniques for clustering in various IoT systems and highlight the related open issues.