Functional activation during the Rapid Visual Information Processing task in a middle aged cohort: An fMRI study

The Rapid Visual Information Processing (RVIP) task, a serial discrimination task where task performance believed to reflect sustained attention capabilities, is widely used in behavioural research and increasingly in neuroimaging studies. To date, functional neuroimaging research into the RVIP has been undertaken using block analyses, reflecting the sustained processing involved in the task, but not necessarily the transient processes associated with individual trial performance. Furthermore, this research has been limited to young cohorts. This study assessed the behavioural and functional magnetic resonance imaging (fMRI) outcomes of the RVIP task using both block and event-related analyses in a healthy middle aged cohort (mean age = 53.56 years, n = 16). The results show that the version of the RVIP used here is sensitive to changes in attentional demand processes with participants achieving a 43% accuracy hit rate in the experimental task compared with 96% accuracy in the control task. As shown by previous research, the block analysis revealed an increase in activation in a network of frontal, parietal, occipital and cerebellar regions. The event related analysis showed a similar network of activation, seemingly omitting regions involved in the processing of the task (as shown in the block analysis), such as occipital areas and the thalamus, providing an indication of a network of regions involved in correct trial performance. Frontal (superior and inferior frontal gryi), parietal (precuenus, inferior parietal lobe) and cerebellar regions were shown to be active in both the block and event-related analyses, suggesting their importance in sustained attention/vigilance. These networks and the differences between them are discussed in detail, as well as implications for future research in middle aged cohorts.

Dynamic analysis and simulation of a VSC based Back-to-Back HVDC link

This paper presents the modeling and analysis of a voltage source converter (VSC) based back-to-back (BTB) HVDC link. The case study considers the response to changes in the active and reactive power and disturbance caused by single line to ground (SLG) fault. The controllers at each terminal are designed to inject a variable (magnitude and phase angle) sinusoidal, balanced set of voltages to regulate/control the active and reactive power. It is also possible to regulate the converter bus (AC) voltage by controlling the injected reactive power. The analysis is carried out using both d-q model (neglecting the harmonics in the output voltages of VSC) and three phase detailed model of VSC. While the eigenvalue analysis and controller design is based on the d-q model, the transient simulation considers both models.

Analysis Of The Energy Quantization Effects On Single Electron Inverter Performance Through Noise Margin Modeling

Possible integration of Single Electron Transistor (SET) with CMOS technology is making the study of semiconductor SET more important than the metallic SET and consequently, the study of energy quantization effects on semiconductor SET devices and circuits is gaining significance. In this paper, for the first time, the effects of energy quantization on SET inverter performance are examined through analytical modeling and Monte Carlo simulations. It is observed that the primary effect of energy quantization is to change the Coulomb Blockade region and drain current of SET devices and as a result affects the noise margin, power dissipation, and the propagation delay of SET inverter. A new model for the noise margin of SET inverter is proposed which includes the energy quantization effects. Using the noise margin as a metric, the robustness of SET inverter is studied against the effects of energy quantization. It is shown that SET inverter designed with CT : CG = 1/3 (where CT and CG are tunnel junction and gate capacitances respectively) offers maximum robustness against energy quantization.

A Proposal for Concurrent Estimation of Static and Dynamic Nonlinearity of ADC

Despite great advances in very large scale integrated-circuit design and manufacturing, performance of even the best available high-speed, high-resolution analog-to-digital converter (ADC) is known to deteriorate while acquiring fast-rising, high-frequency, and nonrepetitive waveforms. Waveform digitizers (ADCs) used in high-voltage impulse recordings and measurements are invariably subjected to such waveforms. Errors resulting from a lowered ADC performance can be unacceptably high, especially when higher accuracies have to be achieved (e.g., when part of a reference measuring system). Static and dynamic nonlinearities (estimated independently) are vital indices for evaluating performance and suitability of ADCs to be used in such environments. Typically, the estimation of static nonlinearity involves 10-12 h of time or more (for a 12-b ADC) and the acquisition of millions of samples at high input frequencies for dynamic characterization. ADCs with even higher resolution and faster sampling speeds will soon become available. So, there is a need to reduce testing time for evaluating these parameters. This paper proposes a novel and time-efficient method for the simultaneous estimation of static and dynamic nonlinearity from a single test. This is achieved by conceiving a test signal, comprised of a high-frequency sinusoid (which addresses dynamic assessment) modulated by a low-frequency ramp (relevant to the static part). Details of implementation and results on two digitizers are presented and compared with nonlinearities determined by the existing standardized approaches. Good agreement in results and time savings achievable indicates its suitability.

Resistance Noise in Electrically Biased Bilayer Graphene

We demonstrate that the low-frequency resistance fluctuations, or noise, in bilayer graphene are strongly connected to its band structure and display a minimum when the gap between the conduction and valence band is zero. Using double-gated bilayer graphene devices we have tuned the zero gap and charge neutrality points independently, which offers a versatile mechanism to investigate the low-energy band structure, charge localization, and screening properties of bilayer graphene.

On Visual Detection of Highly-occluded Objects for Harvesting Automation in Horticulture

Developing accurate and reliable crop detection algorithms is an important step for harvesting automation in horticulture. This paper presents a novel approach to visual detection of highly-occluded fruits. We use a conditional random field (CRF) on multi-spectral image data (colour and Near-Infrared Reflectance, NIR) to model two classes: crop and background. To describe these two classes, we explore a range of visual-texture features including local binary pattern, histogram of oriented gradients, and learn auto-encoder features. The pro-posed methods are evaluated using hand-labelled images from a dataset captured on a commercial capsicum farm. Experimental results are presented, and performance is evaluated in terms of the Area Under the Curve (AUC) of the precision-recall curves.Our current results achieve a maximum performance of 0.81AUC when combining all of the texture features in conjunction with colour information.

On the shear deformation theory for dynamic analysis of beams

Timoshenko's shear deformation theory is widely used for the dynamical analysis of shear-flexible beams. This paper presents a comparative study of the shear deformation theory with a higher order model, of which Timoshenko's shear deformation model is a special case. Results indicate that while Timoshenko's shear deformation theory gives reasonably accurate information regarding the set of bending natural frequencies, there are considerable discrepancies in the information it gives regarding the mode shapes and dynamic response, and so there is a need to consider higher order models for the dynamical analysis of flexure of beams.

A Proposal for Concurrent Estimation of Static and Dynamic Nonlinearity of ADC

Despite great advances in very large scale integrated-circuit design and manufacturing, performance of even the best available high-speed, high-resolution analog-to-digital converter (ADC) is known to deteriorate while acquiring fast-rising, high-frequency, and nonrepetitive waveforms. Waveform digitizers (ADCs) used in high-voltage impulse recordings and measurements are invariably subjected to such waveforms. Errors resulting from a lowered ADC performance can be unacceptably high, especially when higher accuracies have to be achieved (e.g., when part of a reference measuring system). Static and dynamic nonlinearities (estimated independently) are vital indices for evaluating performance and suitability of ADCs to be used in such environments. Typically, the estimation of static nonlinearity involves 10-12 h of time or more (for a 12-b ADC) and the acquisition of millions of samples at high input frequencies for dynamic characterization. ADCs with even higher resolution and faster sampling speeds will soon become available. So, there is a need to reduce testing time for evaluating these parameters. This paper proposes a novel and time-efficient method for the simultaneous estimation of static and dynamic nonlinearity from a single test. This is achieved by conceiving a test signal, comprised of a high-frequency sinusoid (which addresses dynamic assessment) modulated by a low-frequency ramp (relevant to the static part). Details of implementation and results on two digitizers are presented and compared with nonlinearities determined by the existing standardized approaches. Good agreement in results and time savings achievable indicates its suitability.

The Learning Component of Dynamic Allocation Indices

For a multiarmed bandit problem with exponential discounting the optimal allocation rule is defined by a dynamic allocation index defined for each arm on its space. The index for an arm is equal to the expected immediate reward from the arm, with an upward adjustment reflecting any uncertainty about the prospects of obtaining rewards from the arm, and the possibilities of resolving those uncertainties by selecting that arm. Thus the learning component of the index is defined to be the difference between the index and the expected immediate reward. For two arms with the same expected immediate reward the learning component should be larger for the arm for which the reward rate is more uncertain. This is shown to be true for arms based on independent samples from a fixed distribution with an unknown parameter in the cases of Bernoulli and normal distributions, and similar results are obtained in other cases.

A robust approach to design a single facility layout plan in dynamic manufacturing environments using a permutation-based genetic algorithm

During the past few decades, developing efficient methods to solve dynamic facility layout problems has been focused on significantly by practitioners and researchers. More specifically meta-heuristic algorithms, especially genetic algorithm, have been proven to be increasingly helpful to generate sub-optimal solutions for large-scale dynamic facility layout problems. Nevertheless, the uncertainty of the manufacturing factors in addition to the scale of the layout problem calls for a mixed genetic algorithm–robust approach that could provide a single unlimited layout design. The present research aims to devise a customized permutation-based robust genetic algorithm in dynamic manufacturing environments that is expected to be generating a unique robust layout for all the manufacturing periods. The numerical outcomes of the proposed robust genetic algorithm indicate significant cost improvements compared to the conventional genetic algorithm methods and a selective number of other heuristic and meta-heuristic techniques.

Modeling of dynamic material behavior in hot deformation: Forging of Ti-6242

A new method of modeling material behavior which accounts for the dynamic metallurgical processes occurring during hot deformation is presented. The approach in this method is to consider the workpiece as a dissipator of power in the total processing system and to evaluate the dissipated power co-contentJ = ∫o σ ε ⋅dσ from the constitutive equation relating the strain rate (ε) to the flow stress (σ). The optimum processing conditions of temperature and strain rate are those corresponding to the maximum or peak inJ. It is shown thatJ is related to the strain-rate sensitivity (m) of the material and reaches a maximum value(J max) whenm = 1. The efficiency of the power dissipation(J/J max) through metallurgical processes is shown to be an index of the dynamic behavior of the material and is useful in obtaining a unique combination of temperature and strain rate for processing and also in delineating the regions of internal fracture. In this method of modeling, noa priori knowledge or evaluation of the atomistic mechanisms is required, and the method is effective even when more than one dissipation process occurs, which is particularly advantageous in the hot processing of commercial alloys having complex microstructures. This method has been applied to modeling of the behavior of Ti-6242 during hot forging. The behavior of α+ β andβ preform microstructures has been exam-ined, and the results show that the optimum condition for hot forging of these preforms is obtained at 927 °C (1200 K) and a strain rate of 1CT•3 s•1. Variations in the efficiency of dissipation with temperature and strain rate are correlated with the dynamic microstructural changes occurring in the material.

Atmospheric Noise on the Bispectrum in Optical Speckle Interferometry

Based on a simple picture of speckle phenomena in optical interferometry it is shown that the recent signal-to-noise ratio estimate for the so called bispectrum, due to Wirnitzer (1985), does not possess the right limit when photon statistics is unimportant. In this wave-limit, which is true for bright sources, his calculations over-estimate the signal-to-noise ratio for the bispectrum by a factor of the order of the square root of the number of speckles.

Changes in Beer Labels and their Meaning : A Holistic Approach to the Semiosic Process

The purpose of this study is to find a framework for a holistic approach to, and form a conceptual toolbox for, investigating changes in signs and in their interpretation. Charles S. Peirce s theory of signs in a communicative perspective is taken as a basis for the framework. The concern directing the study is the problem of a missing framework in analysing signs of visual artefacts from a holistic perspective as well as that of the missing conceptual tools. To discover the possibility of such a holistic approach to semiosic processes and to form a conceptual toolbox the following issues are discussed: i) how the many Objects with two aspects involved in Peirce s definition of sign-action, promote multiple semiosis arising from the same sign by the same Interpretant depending on the domination of the Objects; ii) in which way can the relation of the individual and society or group be made more apparent in the construction of the self since this construction is intertwined with the process of meaning-creation and interpretation; iii) how to account for the fundamental role of emotions in semiosis, and the relation of emotions with the often neglected topic of embodiment; iv) how to take into account the dynamic, mediating and processual nature of sign-action in analysing and understanding the changes in signs and in the interpretation of signs. An interdisciplinary approach is chosen for this dissertation. Concepts that developed within social psychology, developmental psychology, neurosciences and semiotics, are discussed. The common aspect of the approaches is that they in one way or another concentrate on mediation provided by signs in explaining human activity and cognition. The holistic approach and conceptual toolbox found are employed in a case study. This consists of an analysis of beer brands including a comparison of brands from two different cultures. It becomes clear that different theories and approaches have mutual affinities and do complement each other. In addition, the affinities in different disciplines somewhat provide credence to the various views. From the combined approach described, it becomes apparent that by the semiosic process, the emerging semiotic self intertwined with the Umwelt, including emotions, can be described. Seeing the interpretation and meaning-making through semiosis allows for the analysis of groups, taking into account the embodied and emotional component. It is concluded that emotions have a crucial role in all human activity, including so-called reflective thinking, and that emotions and embodiment should be consciously taken into account in analysing signs, the interpretation, and in changes of signs and interpretations from both the social and individual level. The analysis of the beer labels expresses well the intertwined nature of the relationship between signs, individual consumers and society. Many direct influences from society on the label design are found, and also some indirect attitude changes that become apparent from magazines, company reports, etc. In addition, the analysis brings up the issues of the unifying tendency of the visual artefacts of different cultures, but also demonstrates that the visual artefacts are able to hold the local signs and meanings, and sometimes are able to represent the local meanings although the signs have changed in the unifying process.

Pattern visual evoked potentials in dyslexic versus normal children

Purpose: Presence of neurophysiological abnormalities in dyslexia has been a conflicting issue. This study was performed to evaluate the role of sensory visual deficits in the pathogenesis of dyslexia. Methods: Pattern visual evoked potentials (PVEP) were recorded in 72 children including 36 children with dyslexia and 36 children without dyslexia (controls) who were matched for age, sex and intelligence. Two check sizes of 15 and 60 min of arc were used with temporal frequencies of 1.5 Hz for transient and 6 Hz for steady‑state methods. Results: Mean latency and amplitude values for 15 min arc and 60 min arc check sizes using steady state and transient methods showed no significant difference between the two study groups (P values: 0.139/0.481/0.356/0.062).Furthermore, no significant difference was observed between two methods of PVEPs in dyslexic and normal children using 60min arc with high contrast(Pvalues: 0.116, 0.402, 0.343 and 0.106). Conclusion: The sensitivity of PVEP has high validity to detect visual deficits in children with dyslexic problem. However, no significant difference was found between dyslexia and normal children using high contrast stimuli.