Laboratory experiments and field observations indicate that tlie Q of many non ferromagnetic inorganic solids is almost frequency independent in the range 10' to 10~2 cps; although no single substance has been investigated over the entire frequency spectrum. One of the purposes of this investigation is to find the analytic expression of a linear dissipative mechanism whose Q is almost frequency independent over large frequency ranges. This will be obtained by introducing fractional derivatives in the stress strain relation. Since the aim of this research is to also contribute to elucidating the dissipating mechanism in the earth free modes, we shall treat the cases of dissipation in the free purely torsional modes of a shell and the purely radial vibration of a solid sphere. The theory is checked with the new values determined for the Q of the spheroidal free modes of the earth in the range between 10 and 5 minutes integrated with the Q of the Railegh waves in the range between 5 and 0.6 minutes. Another check of the theory is made with the experimental values of the Q of the longitudinal waves in an alluminimi rod, in the range between 10-5 and 10-3 seconds. In both clicks the theory represents the observed phenomena very satisfactory.
Rat brain cannabinoid receptor (CB-1) was stably transfected into the murine tumor line AtT-20 to study its coupling to inwardly rectifying potassium currents (Kir) and high voltage-activated calcium currents (ICa). In cells expressing CB-1 (“A-2” cells), cannabinoid agonist potently and stereospecifically activated Kir via a pertussis toxin- sensitive G protein. ICa in A-2 cells was sensitive to dihydropyridines and omega CTX MVIIC, less so to omega CgTX GVIA and insensitive to omega Aga IVa. In CB-1 expressing cells, cannabinoid agonist inhibited only the omega CTX MVIIC-sensitive component of ICa. Inhibition of Q- type ICa was voltage dependent and PTX sensitive, thus similar in character to the well-studied modulation of N-type ICa. An endogenous cannabinoid, anandamide, activated Kir and inhibited ICa as efficaciously as potent cannabinoid agonist. Immunocytochemical studies with antibodies specific for class A, B, C, D, and E voltage-dependent calcium channel alpha 1 subunits revealed that AtT-20 cells express each of these major classes of alpha 1 subunit.
Patricia Silva de Camargo, Paulo Roberto Cabral-Passos, André Frazão Helene
Motor imagery corresponds to the mental practice of simulating visual and kinesthetic aspects of a given motor task. This practice shares a similar neural substrate and correlated temporal scale with motor execution. Besides that, it can lead to performance improvements in the actual execution of the imagined task. Therefore it is important to understand functional differences and equivalences between motor imagery and motor execution. To tackle that we employed a finger-tapping serial reaction time task in two groups of participants, a Motor Execution (n=10) and a Motor imagery (n=10). The sequence of stimuli defining the task had 750 items composed of three distinct auditory stimuli. Also, this sequence had some intrinsic variability making some of the next items unpredictable. Each auditory stimulus was mapped to a single right hand finger in the Motor Imagery group. The Motor imagery group indicated the end of the imagination with a single response using the left hand. The results show improvement in performance of the Motor Imagery group throughout the task and that the duration of the motor imagery, indirectly measured by reaction times, are influenced by distinct factors than those of Motor Execution.
In recent years, there has been increasing interest in developing models and tools to address the complex patterns of connectivity found in brain tissue. Specifically, this is due to a need to understand how emergent properties emerge from these network structures at multiple spatiotemporal scales. We argue that computational models are key tools for elucidating the possible functionalities that can emerge from interactions of heterogeneous neurons connected by complex networks on multi-scale temporal and spatial domains. Here we review several classes of models including spiking neurons, integrate and fire neurons with short term plasticity (STP), conductance based integrate-and-fire models with STP, and population density neural field (PDNF) models using simple examples with emphasis on neuroscience applications while also providing some potential future research directions for AI. These computational approaches allow us to explore the impact of changing underlying mechanisms on resulting network function both experimentally as well as theoretically. Thus we hope these studies will inform future developments in artificial intelligence algorithms as well as help validate our understanding of brain processes based on experiments in animals or humans.
Alzheimer's disease (AD) is a neurodegenerative disease known to affect brain functional connectivity (FC). Linear FC measures have been applied to study the differences in AD by splitting neurophysiological signals such as electroencephalography (EEG) recordings into discrete frequency bands and analysing them in isolation. We address this limitation by quantifying cross-frequency FC in addition to the traditional within-band approach. Cross-bispectrum, a higher-order spectral analysis, is used to measure the nonlinear FC and is compared with the cross-spectrum, which only measures the linear FC within bands. Each frequency coupling is then used to construct an FC network, which is in turn vectorised and used to train a classifier. We show that fusing features from networks improves classification accuracy. Although both within-frequency and cross-frequency networks can be used to predict AD with high accuracy, our results show that bispectrum-based FC outperforms cross-spectrum suggesting an important role of cross-frequency FC.
Identity theft has impaired e-commerce. To combat the crime, many identity theft countermeasures (ITC) have been proposed. As investments in ITC are substantial and the benefits of such investments are intangible, companies are often hesitant to adopt such measures. This was the motivation for this study of the impact of 526 ITC adoption announcements on short- and long-term market value. The event study shows that such announcements result in positive market return of about U.S. $583 million around the date of announcement. Calendar-time portfolio analysis (CPA) is used for the long-term impact analysis and shows that the adoption of ITC generates positive and significant average monthly return up to 1.5% with control of market risk factors in a year. Subsampling analysis and interaction analysis show that U.S. listing, early ITC adoption, and two- factor authentication may moderate the market value of ITC adopters differently. A number of robustness checks (e.g., Heckman model, cross-sectional regression on Tobin’s Q, firm-specific risk factor analysis, subsampling analysis by ICT development, and analysis of security statements in annual reports) are performed. The research provides quantitative evidence of financial gain resulting from adoption of ITC and aspires to raise ITC awareness among industrial practitioners.
Jonathan S. Tsay, Alan Lee, Richard B. Ivry
et al.
Collecting data online via crowdsourcing platforms has proven to be a very efficient way to recruit a large and diverse sample. Studies of motor learning, however, have been largely confined to the lab due to the need for special equipment to record movement kinematics and, as such, are typically only accessible to specific participants (e.g., college students). As a first foray to make motor learning studies accessible to a larger and more diverse audience, we developed an online, web-based platform (OnPoint) to collect kinematic data, serving as a template for researchers to create their own online sensorimotor control and learning experiments. As a proof-of-concept, we asked if fundamental motor learning phenomena discovered in the lab could be replicated online. In a series of three experiments, we observed a close correspondence between the results obtained online with those previously reported from research conducted in the laboratory. This web-based platform paired with online crowdsourcing can serve as a powerful new method for the study of motor control and learning.
In this paper, we have given a corrigendum to our paper "Some Approximation Results by $(p,q)$-analogue of Bernstein-Stancu Operators" published in Applied Mathematics and Computation $264 (2015) 392-402.$ We introduce a new analogue of Bernstein-Stancu operators and we call it as $(p,q)$-Bernstein-Stancu operators. We study approximation properties based on Korovkin's type approximation theorem of $(p,q)$-Bernstein-Stancu operators. We also establish some direct theorems.