Protection efficiencies of surface-active inhibitors in zinc-air batteries

Zinc (Zn) particles in alkaline electrolyte of a Zn-air battery (ZAB) are unstable and prone to corrosion. Zinc oxide (ZnO) generated on the surface of Zn particles affects the electrochemical reactions and reduces the battery efficiency. Thus, inhibiting the self-corrosion rate of Zn particles has become acritical issue for the development of these batteries. In this study, a research endeavor has been attempted by employing three types and concentrations of organic inhibitors in ZABs to constrain Zn anode corrosion. Significant analyses like polarization curve, constant current discharge, AC impedance, and dendrite growth are executed for in-depth understanding of the influences of these inhibitors. The experimental results reveal that the inhibiting efficiency of 10 wt% Sodium dodecyl benzene sulfonate surpassed polyethylene glycol 600 (PEG 600) and polysorbate 20 (Tween 20), with a maximum current density of 476.20 mA/cm² and voltage output of 1.4 V along with discharge capacitance of 10.31 Ah for 2 hours and 8 minutes. Zn anode surface analysis exposes significant dendrite growth and elemental Zn required for passivation suppression. Nevertheless, the results are also justified by Nyquist and Bode plots. Thus, the selected inhibitor will proficiently guarantee the enhanced performance and stability of the ZABs obtained and provide enormous opportunities for its applications.     

ZnO energy transfer and enhanced photoluminescence in MEH-PPV/ZnO hybrid nanocomposite

Hybrid organic–inorganic nanocomposites are great candidates for display and illumination systems due to improved optoelectronic properties and photostability. This work endeavours towards the scientific study of the influence of defect-induced zinc oxide nanoparticles (ZnO) on the optical characteristics of poly[2-methoxy-5-(2′-ethylhexyloxy)-1,4-phenylenevinylene] (MEH-PPV). ZnO nanoparticles consist of many vacancies which facilitate light emission across the visible region. The green defective emission occurring due to the presence of oxygen vacancies in ZnO was used to re-excite MEH-PPV and hence, improve the luminescence quantum efficiency. The photostability of the nanocomposite was enhanced through charge transfer (prevents the formation of superoxides) and energy transfer (reduces the non-radiative decay) mechanisms.

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Effect of source tuning parameters on the plasma potential of heavy ions in the 18 GHz high temperature superconducting electron cyclotron resonance ion source

Plasma potentials for various heavy ions have been measured using the retarding field technique in the 18 GHz high temperature superconducting ECR ion source, PKDELIS [C. Bieth, S. Kantas, P. Sortais, D. Kanjilal, G. Rodrigues, S. Milward, S. Harrison, and R. McMahon, Nucl. Instrum. Methods B 235, 498 (2005); D. Kanjilal, G. Rodrigues, P. Kumar, A. Mandal, A. Roy, C. Bieth, S. Kantas, and P. Sortais, Rev. Sci. Instrum. 77, 03A317 (2006)]. The ion beam extracted from the source is decelerated close to the location of a mesh which is polarized to the source potential and beams having different plasma potentials are measured on a Faraday cup located downstream of the mesh. The influence of various source parameters, viz., RF power, gas pressure, magnetic field, negative dc bias, and gas mixing on the plasma potential is studied. The study helped to find an upper limit of the energy spread of the heavy ions, which can influence the design of the longitudinal optics of the high current injector being developed at the Inter University Accelerator Centre. It is observed that the plasma potentials are decreasing for increasing charge states and a mass effect is clearly observed for the ions with similar operating gas pressures. In the case of gas mixing, it is observed that the plasma potential minimizes at an optimum value of the gas pressure of the mixing gas and the mean charge state maximizes at this value. Details of the measurements carried out as a function of various source parameters and its impact on the longitudinal optics are presented.     

An innovative hybrid approach for extracting named entities from unstructured text data

Named entity recognition (NER) is the core part of information extraction that facilitates the automatic detection and classification of entities in natural language text into predefined categories, such as the names of persons, organizations, locations, and so on. The output of the NER task is crucial for many applications, including relation extraction, textual entailment, machine translation, information retrieval, etc. Literature shows that machine learning and deep learning approaches are the most widely used techniques for NER. However, for entity extraction, the abovementioned approaches demand the availability of a domain‐specific annotated data set. Our goal is to develop a hybrid NER system composed of rule‐based deep learning as well as clustering‐based approaches, which facilitates the extraction of generic entities (such as person, location, and organization) out of natural language texts of domains that lack generic named entities labeled domain data sets. The proposed approach takes the advantages of both deep learning and clustering approaches but separately, in combination with a knowledge‐based approach by using a postprocessing module. We evaluated the proposed methodology on court cases (judgments) as a use case since it contains generic named entities of different forms that are poorly or not present in open‐source NER data sets. We also evaluated our hybrid models on two benchmark data sets, namely, Computational Natural Language Learning (CoNLL) 2003 and Open Knowledge Extraction (OKE) 2016. The experimental results obtained from benchmark data sets show that our hybrid models achieved substantially better performance in terms of the F‐score in comparison to other competitive systems.     

A novel whispered speaker identification system based on extreme learning machine

Whispered speech speaker identification system is one of the most demanding efforts in automatic speaker recognition applications. Due to the profound variations between neutral and whispered speech in acoustic characteristics, the performance of conventional speaker identification systems applied on neutral speech degrades drastically when compared to whisper speech. This work presents a novel speaker identification system using whispered speech based on an innovative learning algorithm which is named as extreme learning machine (ELM). The features used in this proposed system are Instantaneous frequency with probability density models. Parametric and nonparametric probability density estimation with ELM was compared with the hybrid parametric and nonparametric probability density estimation with Extreme Learning Machine (HPNP-ELM) for instantaneous frequency modeling. The experimental result shows the significant performance improvement of the proposed whisper speech speaker identification system.     

Hand Gesture Recognition Based Omnidirectional Wheelchair Control Using IMU and EMG Sensors

This paper presents a hand gesture based control of an omnidirectional wheelchair using inertial measurement unit (IMU) and myoelectric units as wearable sensors. Seven common gestures are recognized and classified using shape based feature extraction and Dendogram Support Vector Machine (DSVM) classifier. The dynamic gestures are mapped to the omnidirectional motion commands to navigate the wheelchair. A single IMU is used to measure the wrist tilt angle and acceleration in three axis. EMG signals are extracted from two forearm muscles namely Extensor Carpi Radialis and Flexor Carpi Radialis and processed to provide Root Mean Square (RMS) signal. Initiation and termination of dynamic activities are based on autonomous identification of static to dynamic or dynamic to static transition by setting static thresholds on processed IMU and myoelectric sensor data. Classification involves recognizing the activity pattern based on periodic shape of trajectories of the triaxial wrist tilt angle and EMG-RMS from the two selected muscles. Second order Polynomial coefficients extracted from the sensor trajectory templates during specific dynamic activity cycles are used as features to classify dynamic activities. Classification algorithm and real time navigation of the wheelchair using the proposed algorithm has been tested by five healthy subjects. Classification accuracy of 94% was achieved by DSVM classifier on ‘k’ fold cross validation data of 5 users. Classification accuracy while operating the wheelchair was 90.5%.     

Diet-induced alterations in the discoid shape and phospholipid fatty acid compositions of rat erythrocytes

For eight weeks young male rats were fed diets rich in 18∶2 (stock diet, or 10% corn oil, CO) or those devoid of 18∶2 (fat free, FF, or 10% hydrogenated coconut oil, HCNO). The CO and HCNO diets were fed in the absence or presence of eicosa-5,8,11,14-tetraynoic acid (TYA). When 18∶2 was excluded, an increase in the level of 16∶1, 18∶1 and 20∶3 and a decrease in 18∶2 was observed in the fatty acids of red cells. On feeding TYA, an increase in 18∶2 and in the case of the HCNO+TYA diet, a decrease of 12∶0 and 14∶0 was also observed. In all cases the levels of 20∶4 in erythrocyte fatty acids were similar. Saturated fatty acids were predominant in phosphatidyl choline (PC), lysophosphatidylcholine, (LPC) and sphingomyelin whereas unsaturated acids were predominant in phosphatidyl ethanolamine (PE), (PS), and phosphatidyl inositol (PI). Acids containing three or more double bonds comprised about 90% of the total acids in PI. In all the phospholipids, the characteristic changes in the composition of fatty acids were observed due to the exclusion of 18∶2 from the diet. However, changes due to the feeding of TYA were found only in PC and LPC. In rats fed the 18∶2-rich diet, about 60% of the red cells were discocytes. In those fed the 18∶2-free diet, the level of discocytes decreased to about 23%, and the levels of echinocytes II and III increased. The exclusion of 18∶2 for even a few days decreased the proportion of discocytes. The loss of discoid shape was reversed in a few days by feeding an 18∶2-rich diet. Fatty acid analysis of erythrocytes of rats of the various dietary manipulations showed that the change in the proportion of discocytes followed the change in the level of 18∶2.