Study of Band Structure Properties of Pnictide LaO1−xF x FeAs (x = 0, 0.2) Superconducting Compound

This paper reports on the band structure properties and changes in band structure of fluorine-doped LaO_1?x F _x FeAs (x = 0, 0.2) compound, measured using X-ray photoemission spectroscopy (XPS). The band structure of the superconducting compound is compared with nonsuperconducting parent compound LaOFeAs. With fluorine doping, a shift of the shallow core level is observed in XPS spectra, which may be a response of the band structure due to fluorine doping in the system. The balance of the chemical potential shift with the screening effect of conduction electrons near the Fe and As ions is discussed using nearly unchanged Fe 2p and As 3d core-level spectra. The La 3d core-level spectra shift towards the high energy, ～0.36 eV, may be due to the chemical potential shift caused by fluorine doping. In our valence band spectra, a small peak at around 0.2 eV is observed, which disappeared with the fluorine doping in the system, indicating a change of Fe 3d state from low spin to high spin states and also confirming the nature of Fe 3d electrons as itinerant, which is responsible for superconductivity in these compounds.     

Activity and Growth of Organic Chemistry Research in India During 1971–1989

The paper investigates Indian organic chemistry research activity during 1971–1989 using Chemical Abstracts. It attempts at quantification of national contribution to world efforts, and identify areas of relative strengths and weaknesses. Also models the growth of Indian organic chemistry output to world organic chemistry output as a whole and in sub-fields where the activity index for the world and India are similar.     

Scientometrics of the international journal Scientometrics

An analysis of 1317 papers published in first fifty volumes during 1978 to 2001 of the international journal Scientometrics indicates the heterogeneity of the field with emphasis on scientometric assessment. The study indicates that the US share of papers is constantly on the decline while that of the Netherlands, India, France and Japan is on the rise. The research output is highly scattered as indicated by the average number of papers per institution. The scientometric output is dominated by the single authored papers, however, multi-authored papers are gaining momentum. Similar pattern has been observed for domestic and international collaboration.     

Boron-doped activated carbon from the stems of Prosopis juliflora as an effective electrode material in symmetric supercapacitors

For a supercapacitor electrode, carbon-based materials have received great attention for their high surface area and stability. In this work, sustainable and cost-effective synthesis of boron-doped activated biomass-derived carbon from the stems of Prosopis juliflora has been reported for supercapacitor applications. The activation by KOH creates pores and boron induces p-type doping in the carbon matrix. The material gave a higher specific capacitance of 307.14 F/g at a current density of 0.5 A/g. The symmetric supercapacitor device delivered 156.29 F/g of specific capacitance with 98.1% of energy efficiency. The observed energy and power densities were 7.81 Wh/Kg and 150 W/Kg, respectively. The device was further studied with stability test for 1000 charge/discharge cycles and showed 98.6% of capacitance retention and 97.9% of coulombic efficiency.

     

Machine learning model for mapping of music mood and human emotion based on physiological signals

Emotion is considered a physiological state that appears whenever a transformation is observed by an individual in their environment or body. While studying the literature, it has been observed that combining the electrical activity of the brain, along with other physiological signals for the accurate analysis of human emotions is yet to be explored in greater depth. On the basis of physiological signals, this work has proposed a model using machine learning approaches for the calibration of music mood and human emotion. The proposed model consists of three phases (a) prediction of the mood of the song based on audio signals, (b) prediction of the emotion of the human-based on physiological signals using EEG, GSR, ECG, Pulse Detector, and finally, (c) the mapping has been done between the music mood and the human emotion and classifies them in real-time. Extensive experimentations have been conducted on the different music mood datasets and human emotion for influential feature extraction, training, testing and performance evaluation. An effort has been made to observe and measure the human emotions up to a certain degree of accuracy and efficiency by recording a person’s bio- signals in response to music. Further, to test the applicability of the proposed work, playlists are generated based on the user’s real-time emotion determined using features generated from different physiological sensors and mood depicted by musical excerpts. This work could prove to be helpful for improving mental and physical health by scientifically analyzing the physiological signals.

     

A biomechanical and ergonomic evaluation of patient transferring tasks: wheelchair to shower chair and shower chair to wheelchair.

A laboratory study was conducted to evaluate five different manual techniques (two-person manual lifting; rocking and pulling the patient using a gait belt with two persons; walking belt with one and two persons) and three different mechanical hoists (Hoyer lift, Trans-Aid and Ambulift) for transferring patients from wheelchair to shower chair and shower chair to wheelchair. Six female nursing students with prior patient transfer experience served both as nurses and as passive patients. Static biomechanical evaluation showed that the mean trunk flexion moments, erector spinae muscle forces and compressive and shear forces at the L5S1 disc for the four pulling methods ranged from 92 to 125 Nm, 1845 to 2507 N, 1973 to 2641 N and 442 to 580 N, respectively, as compared to about 213 Nm, 4260 N, 5050 N and 926 N for two-person manual lifting. Perceived stress ratings for the shoulder, upper back, lower back and whole body were significantly lower for pulling methods than those for lifting the patient (p less than or equal to 0.01). Patients found pulling techniques, except the gait belt, to be more comfortable and secure than the lifting method (p less than or equal to 0.01). However, most of the nurses believed that Medesign and the one-person walking belt would not work on those patients who cannot bear weight and those who are heavy, contracted or combative. A two-person walking belt was the most preferred method. Two out of three hoists (Hoyer lift and Trans-Aid) were perceived by the nurses to be more stressful than one- and two-person walking belts. The patients found these two hoists to be more uncomfortable and less secure than with three of the five manual methods (one- and two-person walking belts and Medesign). Pulling techniques and hoists took significantly longer amounts of time to make the transfer than manually lifting the patient (p less than or equal to 0.01). The two-person walking belt, using a gentle rocking motion to utilize momentum and a pulling technique, and Ambulift are recommended for transferring patients from wheelchair to shower chair and shower chair to wheelchair.     

Survey of denoising,segmentation and classification of magnetic resonance imaging for prostate cancer

Multimedia Tools and Applications - Prostate cancer (PCa) has become the second most dreadful cancer in men after lung cancer. Traditional approaches used for treatment of PCa were manual, time...     

Evaluation of reservoir sedimentation using data driven techniques

The sedimentation is a pervasive complex hydrological process subjected to each and every reservoir in world at different extent. Hydrographic surveys are considered as most accurate method to determine the total volume occupied by sediment and its distribution pattern in a reservoir. But, these surveys are very cumbersome, time consuming and expensive. This complex sedimentation process can also be simulated through the well calibrated numerical models. However, these models generally are data extensive and require large computational time. Generally, the availability of such data is very scarce. Due to large constraints of these methods and models, in the present study, data driven approaches such as artificial neural networks (ANN), model trees (MT) and genetic programming (GP) have been investigated for the estimation of volume of sediment deposition incorporating the parameters influenced it along with conventional multiple linear regression data driven model. The aforementioned data driven models for the estimation of reservoir sediment deposition were initially developed and applied on Gobindsagar Reservoir. In order to generalise the developed methodology, the developed data driven models were also validated for unseen data of Pong Reservoir. The study depicted that the highly nonlinear models ANN and GP captured the trend of sediment deposition better than piecewise linear MT model, even for smaller length datasets.     

Double auction-inspired meta-scheduling of parallel applications on global grids

Meta-schedulers map jobs to computational resources that are part of a Grid, such as clusters, that in turn have their own local job schedulers. Existing Grid meta-schedulers either target system-centric metrics, such as utilisation and throughput, or prioritise jobs based on utility metrics provided by the users. The system-centric approach gives less importance to users’ individual utility, while the user-centric approach may have adverse effects such as poor system performance and unfair treatment of users. Therefore, this paper proposes a novel meta-scheduler, based on the well-known double auction mechanism that aims to satisfy users’ service requirements as well as ensuring balanced utilisation of resources across a Grid. We have designed valuation metrics that commodify both the complex resource requirements of users and the capabilities of available computational resources. Through simulation using real traces, we compare our scheduling mechanism with other common mechanisms widely used by both existing market-based and traditional meta-schedulers. The results show that our meta-scheduling mechanism not only satisfies up to 15% more user requirements than others, but also improves system utilisation through load balancing.