Pharmacologically induced and stimulus evoked rhythmic neuronal oscillatory activity in the primary motor cortex in vitro

Parkinson's disease (PD) is associated with enhanced synchronization of neuronal network activity in the beta (15-30 Hz) frequency band across several nuclei of the basal ganglia (BG). Deep brain stimulation of the subthalamic nucleus (STN) appears to reduce this pathological oscillation, thereby alleviating PD symptoms. However, direct stimulation of primary motor cortex (M1) has recently been shown to be effective in reducing symptoms in PD, suggesting a role for cortex in patterning pathological rhythms. Here, we examine the properties of M1 network oscillations in coronal slices taken from rat brain. Oscillations in the high beta frequency range (layer 5, 27.8 +/- 1.1 Hz, n=6) were elicited by co-application of the glutamate receptor agonist kainic acid (400 nM) and muscarinic receptor agonist carbachol (50 mu M). Dual extracellular recordings, local application of tetrodotoxin and recordings in M1 micro-sections indicate that the activity originates within deep layers V/VI. Beta oscillations were unaffected by specific AMPA receptor blockade, abolished by the GABA type A receptor (GABAAR) antagonist picrotoxin and the gap-junction blocker carbenoxolone, and modulated by pentobarbital and zolpidem indicating dependence on networks of GABAergic interneurons and electrical coupling. High frequency stimulation (HFS) at 125 Hz in superficial layers, designed to mimic transdural/transcranial stimulation, generated gamma oscillations in layers 11 and V (incidence 95%, 69.2 +/- 7.3 Hz, n=17) with very fast oscillatory components (VFO; 100-250 Hz). Stimulation at 4 Hz, however, preferentially promoted theta activity (incidence 62.5%, 5.1 +/- 0.6 Hz, n=15) that effected strong amplitude modulation of ongoing beta activity. Stimulation at 20 Hz evoked mixed theta and gamma responses. These data suggest that within M1, evoked theta, gamma and fast oscillations may coexist with and in some cases modulate pharmacologically induced beta oscillations.

Estimation of functional connectivity from electromagnetic signals and the amount of empirical data required

An increasing number of neuroimaging studies are concerned with the identification of interactions or statistical dependencies between brain areas. Dependencies between the activities of different brain regions can be quantified with functional connectivity measures such as the cross-correlation coefficient. An important factor limiting the accuracy of such measures is the amount of empirical data available. For event-related protocols, the amount of data also affects the temporal resolution of the analysis. We use analytical expressions to calculate the amount of empirical data needed to establish whether a certain level of dependency is significant when the time series are autocorrelated, as is the case for biological signals. These analytical results are then contrasted with estimates from simulations based on real data recorded with magnetoencephalography during a resting-state paradigm and during the presentation of visual stimuli. Results indicate that, for broadband signals, 50-100 s of data is required to detect a true underlying cross-correlations coefficient of 0.05. This corresponds to a resolution of a few hundred milliseconds for typical event-related recordings. The required time window increases for narrow band signals as frequency decreases. For instance, approximately 3 times as much data is necessary for signals in the alpha band. Important implications can be derived for the design and interpretation of experiments to characterize weak interactions, which are potentially important for brain processing.

High frequency sensing interrogation system using fiber Bragg grating based microwave photonic filtering

A high frequency sensing interrogation system by using fiber Bragg grating based microwave photonic filtering is proposed, in which the wavelength measurement sensitivity is proportional to the RF modulation frequency applied to the optical signal.

High-frequency fiber Bragg grating sensing interrogation system using Sagnac-loop-based microwave photonic filtering

A novel high-frequency fiber Bragg grating (FBG) sensing interrogation system by using fiber Sagnac-loop-based microwave photonic filtering is proposed and experimentally demonstrated. By adopting the microwave photonic filtering, the wavelength shift of sensing FBG can be converted into amplitude variation of the modulated electronic radio-frequency (RF) signal. In the experiment, the strain applied onto the sensing FBG has been demodulated by measuring the intensity of the recovered RF signal, and by modulating the RF signal with different frequencies, different interrogation sensitivities can be achieved.

The use of ERS-1 crossovers and TOPEX/Poseidon repeat pass data for global sea surface variability studies

In previous sea-surface variability studies, researchers have failed to utilise the full ERS-1 mission due to the varying orbital characteristics in each mission phase, and most have simply ignored the Ice and Geodetic phases. This project aims to introduce a technique which will allow the straightforward use of all orbital phases, regardless of orbit type. This technique is based upon single satellite crossovers. Unfortunately the ERS-1 orbital height is still poorly resolved (due to higher air drag and stronger gravitational effects) when compared with that of TOPEX/Poseidon (T/P), so to make best use of the ERS-1 crossover data corrections to the ERS-1 orbital heights are calculated by fitting a cubic-spline to dual-crossover residuals with T/P. This correction is validated by comparison of dual satellite crossovers with tide gauge data. The crossover processing technique is validated by comparing the extracted sea-surface variability information with that from T/P repeat pass data. The two data sets are then combined into a single consistent data set for analysis of sea-surface variability patterns. These patterns are simplified by the use of an empirical orthogonal function decomposition which breaks the signals into spatial modes which are then discussed separately. Further studies carried out on these data include an analysis of the characteristics of the annual signal, discussion of evidence for Rossby wave propagation on a global basis, and finally analysis of the evidence for global mean sea level rise.

Selectivity and timing performance of UK investment trusts

This study examines the selectivity and timing performance of 218 UK investment trusts over the period July 1981 to June 2009. We estimate the Treynor and Mazuy (1966) and Henriksson and Merton (1981) models augmented with the size, value, and momentum factors, either under the OLS method adjusted with the Newey-West procedure or under the GARCH(1,1)-in-mean method following the specification of Glosten et al. (1993; hereafter GJR-GARCH-M). We find that the OLS method provides little evidence in favour of the selectivity and timing ability, consistent with previous studies. Interestingly, the GJR-GARCH-M method reverses this result, showing some relatively strong evidence on favourable selectivity ability, particularly for international funds, as well as favourable timing ability, particularly for domestic funds. We conclude that the GJR-GARCH-M method performs better in evaluating fund performance compared with the OLS method and the non-parametric approach, as it essentially accounts for the time-varying characteristics of factor loadings and hence obtains more reliable results, in particular, when the high frequency data, such as the daily returns, are used in the analysis. Our results are robust to various in-sample and out-of-sample tests and have valuable implications for practitioners in making their asset allocation decisions across different fund styles. © 2012 Elsevier B.V.

Dynamical embedding and feature extraction of electroencephalographic data

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High frequency sensing interrogation system using fiber Bragg grating based microwave photonic filtering

A high frequency sensing interrogation system by using fiber Bragg grating based microwave photonic filtering is proposed, in which the wavelength measurement sensitivity is proportional to the RF modulation frequency applied to the optical signal.

Board composition, ownership structure and dividend policies in an emerging market: further evidence from CASE 50

Purpose – The purpose of this study is to examine dividend policies in an emerging capital market, in a country undergoing a transitional period. Design/methodology/approach – Using pooled cross-sectional observations from the top 50 listed Egyptian firms between 2003 and 2005, this study examines the effect of board of directors’ composition and ownership structure on dividend policies in Egypt. Findings – It is found that there is a significant positive association between institutional ownership and firm performance, and both dividend decision and payout ratio. The results confirm that firms with a higher return on equity and a higher institutional ownership distribute higher levels of dividend. No significant association was found between board composition and dividend decisions or ratios. Originality/value – This study provides additional evidence of the applicability of the signalling model in the emerging market of Egypt. It was found that despite the high institutional ownership and the closely held nature of the firms, which imply lower agency costs, the payment of higher dividend was considered necessary to attract capital during this transitional period.

High-frequency conductivity of optically excited charge carriers in hydrogenated nanocrystalline silicon investigated by spectroscopic femtosecond pump-probe reflectivity measurements

We report an investigation into the high-frequency conductivity of optically excited charge carriers far from equilibrium with the lattice. The investigated samples consist of hydrogenated nanocrystalline silicon films grown on a thin film of silicon oxide on top of a silicon substrate. For the investigation, we used an optical femtosecond pump-probe setup to measure the reflectance change of a probe beam. The pump beam ranged between 580 and 820nm, whereas the probe wavelength spanned 770 to 810nm. The pump fluence was fixed at 0.6mJ/cm2. We show that at a fixed delay time of 300fs, the conductivity of the excited electron-hole plasma is described well by a classical conductivity model of a hot charge carrier gas found at Maxwell-Boltzmann distribution, while Fermi-Dirac statics is not suitable. This is corroborated by values retrieved from pump-probe reflectance measurements of the conductivity and its dependence on the excitation wavelength and carrier temperature. The conductivity decreases monotonically as a function of the excitation wavelength, as expected for a nondegenerate charge carrier gas.

A high-power-factor, three-phase isolated AC-DC converter using high-frequency current injection

A single-stage, three-phase AC-to-DC converter topology is proposed for high-frequency power supply applications. The principal features of the circuit include continuous current operation of the three AC input inductors, inherent shaping of the input currents, resulting in high power factor, a transformer isolated output, and only two active devices are required, both soft-switched. Resonant conversion techniques are used, and a high power factor is achieved by injecting high-frequency currents into the three-phase rectifier, producing a high frequency modulation of the rectifier input voltages. The current injection principle is explained and the system operation is confirmed by a combination of simulation and experimental results.

Practical and cost-effective high-fidelity optical carrier dissemination using coherent communication techniques

We report a unidirectional frequency dissemination scheme for high-fidelity optical carriers deployable over telecommunication networks. For the first time, a 10 Gb/s Binary Phase Shift Keying (BPSK) signal from an ultra-narrow linewidth laser was transmitted through a field-installed optical fibre with round-trip length of 124 km between Cork City and town of Clonakilty, without inline optical amplification. At the receiver, using coherent communication techniques and optical injection-locking the carrier was recovered with noise suppression. The beat signal between the original carrier at the transmitter and recovered carrier at the receiver shows a linewidth of 2.8 kHz. Long term stability measurements revealed fractional instabilities (True Allan deviation) of 3.3 × 10-14 for 1 s averaging time, prior to phase noise cancellation.

High frequency inverter topologies integrated with the coupled inductor bridge arm

A new topology of the high frequency alternating current (HFAC) inverter bridge arm is proposed which comprises a coupled inductor, a switching device and an active clamp circuit. Based on it, new single-phase and threephase inverters are proposed and their operating states are analysed along with the traditional H-bridge inverter. Multiphase and multi-level isolated inverters are also developed using the HFAC bridge arm. Furthermore, based on the proposed HFAC, a front-end DC-DC converter is also developed for photovoltaic systems to demonstrate the application of the proposed HFAC converter. Simulation and experimental results from prototype converters are carried out to validate the proposed topologies which can be utilised widely in high frequency power conversion applications such as induction heating and wireless power transfer.

Education, earnings, and rates of return: The case of Taiwan

Educational planners and economists have long recognized the importance of education as a form of productive investment in both advanced countries and developing countries. In the case of Taiwan, along with impressive economic growth, there was an even faster rate of growth of the government's investment in education. This leads some to question whether education has any role in economic development. ^ The purpose of this study is to provide a broad overview of the role of education, in terms of private rates of return to education, in Taiwan. In the process, a variety of hypotheses about human capital theory are examined and an empirical study of Taiwan's earnings functions are tested to show that education can be an important instrument to increase private rate of return, even under conditions of scarcity of natural and physical resources. Data was collected using the Manpower Survey and Manpower Utilization Survey, conducted by the government. Research questions were analyzed using descriptive statistics, frequencies, and regression analysis. ^ Results indicated that the Manpower Development Plans have been the decisive influence in allowing Taiwan to develop its human resources and achieve success in meeting the needs of Taiwan's economy. The structure of age-earnings profiles showed a strong relationship between earnings and education, and the profiles that successively shift upward are associated with higher levels of education. In the cross-sectional results of the rate of return in 1997, each additional year of schooling leads to a 6.2% increase in income. As to the private rates of return to different levels of education, the results found that the private rates of return are 2.88%, 4.85% and 10.05% for primary, secondary and higher education respectively. In an intertemporal comparison for 1980, 1985, 1990 and 1997, the results showed no significant trend except the private rates of return for primary education have been falling from 3.9% to 2.88%. ^ On the basis of this study, for individual student or family in Taiwan, there is likely to be a strong demand for education, particularly at the higher level. Therefore, a well-developed higher educational level becomes essential and the content of curriculum in higher education becomes another crucial question facing planners in Taiwan if they are going to use education as a means to foster economic development. ^

Statistical analysis and meta-analysis of microarray data

The microarray technology provides a high-throughput technique to study gene expression. Microarrays can help us diagnose different types of cancers, understand biological processes, assess host responses to drugs and pathogens, find markers for specific diseases, and much more. Microarray experiments generate large amounts of data. Thus, effective data processing and analysis are critical for making reliable inferences from the data. ^ The first part of dissertation addresses the problem of finding an optimal set of genes (biomarkers) to classify a set of samples as diseased or normal. Three statistical gene selection methods (GS, GS-NR, and GS-PCA) were developed to identify a set of genes that best differentiate between samples. A comparative study on different classification tools was performed and the best combinations of gene selection and classifiers for multi-class cancer classification were identified. For most of the benchmarking cancer data sets, the gene selection method proposed in this dissertation, GS, outperformed other gene selection methods. The classifiers based on Random Forests, neural network ensembles, and K-nearest neighbor (KNN) showed consistently god performance. A striking commonality among these classifiers is that they all use a committee-based approach, suggesting that ensemble classification methods are superior. ^ The same biological problem may be studied at different research labs and/or performed using different lab protocols or samples. In such situations, it is important to combine results from these efforts. The second part of the dissertation addresses the problem of pooling the results from different independent experiments to obtain improved results. Four statistical pooling techniques (Fisher inverse chi-square method, Logit method. Stouffer's Z transform method, and Liptak-Stouffer weighted Z-method) were investigated in this dissertation. These pooling techniques were applied to the problem of identifying cell cycle-regulated genes in two different yeast species. As a result, improved sets of cell cycle-regulated genes were identified. The last part of dissertation explores the effectiveness of wavelet data transforms for the task of clustering. Discrete wavelet transforms, with an appropriate choice of wavelet bases, were shown to be effective in producing clusters that were biologically more meaningful. ^