Electrical transport and crystallization studies of glassy semiconducting Si20Te80 alloy at high pressure

The effect of pressure on the electrical resistivity of bulk Si20Te80 glass is reported. Results of calorimetric, X-ray and transmission electron microscopy investigations at different stages of crystallization of bulk Si20Te80 glass are also presented. A pressure induced glass-to-crystal transition occurs at a pressure of 7 GPa. Pressure and temperature dependence of the electrical resistivity of Si20Te80 glass show the observed transition is a pressure induced glassy semiconductor to crystalline metal transition. The glass also exhibits a double Tg effect and double stage crystallization, under heating. The differences between the temperature induced crystallization (primary crystallization) and pressure induced congruent crystallization are discussed.

Electrical Transport Studies in as-se Glasses

The DC and AC conductivity studies of As---Se glasses over a wide range of compositions have been reported and discussed. The contribution to conductivity from transport among extended states has been delineated and the possible existence of a characteristic temperature is indicated. Two conductivity maxima have been observed as a function of composition in AC conductivities at lower temperatures.

Rotating Beams and Nonrotating Beams With Shared Eigenpair

In this paper, we look for rotating beams whose eigenpair (frequency and mode-shape) is the same as that of uniform nonrotating beams for a particular mode. It is found that, for any given mode, there exist flexural stiffness functions (FSFs) for which the jth mode eigenpair of a rotating beam, with uniform mass distribution, is identical to that of a corresponding nonrotating uniform beam with the same length and mass distribution. By putting the derived FSF in the finite element analysis of a rotating cantilever beam, the frequencies and mode-shapes of a nonrotating cantilever beam are obtained. For the first mode, a physically feasible equivalent rotating beam exists, but for higher modes, the flexural stiffness has internal singularities. Strategies for addressing the singularities in the FSF for finite element analysis are provided. The proposed functions can be used as test-functions for rotating beam codes and for targeted destiffening of rotating beams.

Bi-criteria single machine scheduling problem with a learning effect: Aneja-Nair method to obtain the set of optimal sequences

In this paper, we consider the bi-criteria single machine scheduling problem of n jobs with a learning effect. The two objectives considered are the total completion time (TC) and total absolute differences in completion times (TADC). The objective is to find a sequence that performs well with respect to both the objectives: the total completion time and the total absolute differences in completion times. In an earlier study, a method of solving bi-criteria transportation problem is presented. In this paper, we use the methodology of solvin bi-criteria transportation problem, to our bi-criteria single machine scheduling problem with a learning effect, and obtain the set of optimal sequences,. Numerical examples are presented for illustrating the applicability and ease of understanding.

Processing of Stimulus Repetition and Change in the Somatosensory System: Recordings of Electrical and Magnetic Brain Responses

In the present work, effects of stimulus repetition and change in a continuous stimulus stream on the processing of somatosensory information in the human brain were studied. Human scalp-recorded somatosensory event-related potentials (ERPs) and magnetoencephalographic (MEG) responses rapidly diminished with stimulus repetition when mechanical or electric stimuli were applied to fingers. On the contrary, when the ERPs and multi-unit a ctivity (MUA) were directly recorded from the primary (SI) and secondary (SII) somatosensory cortices in a monkey, there was no marked decrement in the somatosensory responses as a function of stimulus repetition. These results suggest that this rate effect is not due to the response diminution in the SI and SII cortices. Obviously the responses to the first stimulus after a long "silent" period are nhanced due to unspecific initial orientation, originating in more broadly distributed and/or deeper neural structures, perhaps in the prefrontal cortices. With fast repetition rates not only the late unspecific but also some early specific somatosensory ERPs were diminished in amplitude. The fast decrease of the ERPs as a function of stimulus repetition is mainly due to the disappearance of the orientation effect and with faster repetition rates additively due to stimulus specific refractoriness. A sudden infrequent change in the continuous stimulus stream also enhanced somatosensory MEG responses to electric stimuli applied to different fingers. These responses were quite similar to those elicited by the deviant stimuli alone when the frequent standard stimuli were omitted. This enhancement was obviously due to the release from refractoriness because the neural structures generating the responses to the infrequent deviants had more time to recover from the refractoriness than the respective structures for the standards. Infrequent deviant mechanical stimuli among frequent standard stimuli also enhanced somatosensory ERPs and, in addition, they elicited a new negative wave which did not occur in the deviants-alone condition. This extra negativity could be recorded to deviations in the stimulation site and in the frequency of the vibratory stimuli. This response is probably a somatosensory analogue of the auditory mismatch negativity (MMN) which has been suggested to reflect a neural mismatch process between the sensory input and the sensory memory trace.

Harnessing information from injury narrative in the 'big data' era: Understanding and applying machine learning for injury surveillance

Objective Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. Methods This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. Results The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semi-automatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and positive predictive value and reduced the need for human coding to less than one-third of cases in one large occupational injury database. Conclusion The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of ‘big injury narrative data’ opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice.

Flow between torsionally oscillating disks rotating about different axes at different speeds

The flow of an incompressible viscous fluid confined between two parallel infinite disks performing torsional oscillations with the same frequency, but rotating about different axes with different speeds has been studied. The solutions are presented for the symmetric and asymmetric first harmonic and steady streaming. The interesting features of the symmetric and asymmetric flow are discussed for the cases of small and large Womersley parameter at different ratios of the rotation speeds. The forces acting on one of the disks are also calculated.

Effects of increasing neuromuscular electrical stimulation current intensity on cortical sensorimotor network activation: A time domain fNIRS study

Neuroimaging studies have shown neuromuscular electrical stimulation (NMES)-evoked movements activate regions of the cortical sensorimotor network, including the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), and secondary somatosensory area (S2), as well as regions of the prefrontal cortex (PFC) known to be involved in pain processing. The aim of this study, on nine healthy subjects, was to compare the cortical network activation profile and pain ratings during NMES of the right forearm wrist extensor muscles at increasing current intensities up to and slightly over the individual maximal tolerated intensity (MTI), and with reference to voluntary (VOL) wrist extension movements. By exploiting the capability of the multi-channel time domain functional near-infrared spectroscopy technique to relate depth information to the photon time-of-flight, the cortical and superficial oxygenated (O₂Hb) and deoxygenated (HHb) hemoglobin concentrations were estimated. The O₂Hb and HHb maps obtained using the General Linear Model (NIRS-SPM) analysis method, showed that the VOL and NMES-evoked movements significantly increased activation (i.e., increase in O₂Hb and corresponding decrease in HHb) in the cortical layer of the contralateral sensorimotor network (SMC, PMC/SMA, and S2). However, the level and area of contralateral sensorimotor network (including PFC) activation was significantly greater for NMES than VOL. Furthermore, there was greater bilateral sensorimotor network activation with the high NMES current intensities which corresponded with increased pain ratings. In conclusion, our findings suggest that greater bilateral sensorimotor network activation profile with high NMES current intensities could be in part attributable to increased attentional/pain processing and to increased bilateral sensorimotor integration in these cortical regions.

Design and Development of an In-Vehicle Human Machine Interface to Improve Fuel Efficiency & Safety

Road transport plays a significant role in various industries and mobility services around the globe and has a vital impact on our daily lives. However it also has serious impacts on both public health and the environment. In-vehicle feedback systems are a relatively new approach to encouraging driver behaviour change for improving fuel efficiency and safety in automotive environments. While many studies claim that the adoption of eco-driving practices, such as eco-driving training programs and in-vehicle feedback to drivers, has the potential to improve fuel efficiency, limited research has integrated safety and eco-driving. Therefore, this research seeks to use human factors related theories and practices to inform the design and evaluation of an in-vehicle Human Machine Interface (HMI) providing real-time driver feedback with the aim of improving both fuel efficiency and safety.

Identifying safety beliefs among Australian electrical workers

The current study explored underlying beliefs regarding work safety among a sample of experienced Australian electrical workers. A qualitative research methodology using the theory of planned behavior as a framework was employed. A series of interviews and focus groups with licensed electrical workers (N = 46) were analyzed using thematic content analysis. Beliefs were classified as advantages (e.g. personal safety of self and co-workers), disadvantages (e.g., inconvenience to customer/clients and workload), referents (e.g., supervisors, work colleagues, customers), barriers (e.g., time and cost), and facilitators (e.g., training and knowledge, equipment availability) of safety adherence. The belief basis of the theory of planned behavior was a useful framework for exploring workers’ safety beliefs. The identified beliefs can inform future research about the important factors influencing safe work decisions and inform strategies to promote safer workplace decision making within the electrical safety context.

Single layer bismuth iodide: Computational exploration of structural, electrical, mechanical and optical properties

Layered graphitic materials exhibit new intriguing electronic structure and the search for new types of two-dimensional (2D) monolayer is of importance for the fabrication of next generation miniature electronic and optoelectronic devices. By means of density functional theory (DFT) computations, we investigated in detail the structural, electronic, mechanical and optical properties of the single-layer bismuth iodide (BiI3) nanosheet. Monolayer BiI3 is dynamically stable as confirmed by the computed phonon spectrum. The cleavage energy (Ecl) and interlayer coupling strength of bulk BiI3 are comparable to the experimental values of graphite, which indicates that the exfoliation of BiI3 is highly feasible. The obtained stress-strain curve shows that the BiI3 nanosheet is a brittle material with a breaking strain of 13%. The BiI3 monolayer has an indirect band gap of 1.57 eV with spin orbit coupling (SOC), indicating its potential application for solar cells. Furthermore, the band gap of BiI3 monolayer can be modulated by biaxial strain. Most interestingly, interfacing electrically active graphene with monolayer BiI3 nanosheet leads to enhanced light absorption compared to that in pure monolayer BiI3 nanosheet, highlighting its great potential applications in photonics and photovoltaic solar cells.

Low temperature electrical transport properties of carbon matrix containing iron nanoparticles

We present a comparative study of the low temperature electrical transport properties of the carbon matrix containing iron nanoparticles and the films. The conductivity of the nanoparticles located just below the metal-insulator transition exhibits metallic behavior with a logarithmic temperature dependence over a large temperature interval. The zero-field conductivity and the negative magnetoresistance, showing a characteristic upturn at liquid helium temperature, are consistently explained by incorporating the Kondo relation and the two dimensional electron-electron interaction. The films, in contrast, exhibit a crossover of the conductivity from power-law dependence at high temperatures to an activated hopping law dependence in the low temperature region. The transition is attributed to changes in the energy dependence of the density of states near the Fermi level. The observed magnetoresistance is discussed in terms of quantum interference effect on a three-dimensional variable range hopping mechanism.

Electrical properties of nickel-related deep levels in silicon

Electrically active deep levels related to nickel in silicon are studied under different diffusion conditions, quenching modes, and annealing conditions. The main nickel-related level is at Ev+0.32 eV. Levels at Ev+0.15 and Ev+0.54 eV are not related to nickel while those at Ev+0.50 and Ev+0.28 eV may be nickel related. Their concentrations depend on the quenching mode. There is no nickel-related level in the upper half of the band gap. The complicated annealing behavior of the main nickel-related level is explained on the basis of the formation and dissociation of a nickel-vacany complex. Journal of Applied Physics is copyrighted by The American Institute of Physics.

On the magnetohydrodynamic flow between eccentrically rotating disks

The steady flow of an incompressible, viscous, electrically conducting fluid between two parallel, infinite, insulated disks rotating with different angular velocities about two noncoincident axes has been investigated; under the application of a uniform magnetic field in the axial direction. The solutions for the symmetric and asymmetric velocities are presented. The interesting feature arising due to the magnetic field is that in the central region the flow attains a uniform rotation with mean angular velocity at all rotation speeds for sufficiently large Hartmann number. In this case the flow adjusts to the rotational velocities of the disks mainly in the boundary layers near the disks. The forces on the disks are found to increase due to the presence of the applied magnetic field.