Miracle-dz/UniFAR-FTUs huggingface dataset:
A method for predicting the success of a BCI training session based on the classification of the CSP filters itself

We present an offline analysis of a large set of BCI experiments, focusing on common spatial filters and patterns (CSP). First, we show that it is possible to infer from the CSP filters whether the cross-validation error of LDA-classified EEG data preprocessed by this CSP will be high or low and predict thus the future performance of the feedback sessions following the calibration. Our test is 7 to 10 times faster to compute than the cross-validation. Second, from the CSP patterns, we calculate the corresponding source localization of the activations on the cortex. We explore the possibility of applying our method towards the improvement of calibration procedure quality and thus reduce the phenomenon of BCI illiteracy.
Quantifying Parameter Errors Due to the Peculiar Velocities of Type Ia Supernovae

The fitting of the observed redshifts and magnitudes of Type Ia supernovae to what we would see in homogeneous cosmological models has led to constraints on cosmological parameters. However, in performing such fits it is assumed that the sampled supernovae are moving with the Hubble flow, or namely that their peculiar velocities are zero. In reality, peculiar velocities will modify supernova data in a way that can impact best-fit cosmological parameters. We theoretically quantify this effect in the nonlinear regime with a Monte Carlo analysis, using data from semianalytical galaxy catalogs built from the Millennium N-body simulation. We find scaling relations for the errors in best-fit parameters resulting solely from peculiar velocities, as a function of the total number of sources in a supernova survey N and its maximum redshift zmax. For low-redshift surveys, we find that these errors can be of the same order of magnitude as the errors due to an intrinsic magnitude scatter of 0.1 mag. For a survey with N = 2000 and zmax = 1.7, we estimate that the expected peculiar velocity-induced errors in the best-fit cosmological constant density and equation of state can be σΛ ≈ 0.009 and σw ≈ 0.01, respectively, which are subdominant to the errors due to the intrinsic scatter. We further find that throwing away supernova data below a redshift z ≈ 0.01-0.02 can reduce the combined error due to peculiar velocities and the intrinsic scatter, but by only about 10%.
SEQUENTIAL TIDAL HEIGHT PREDICTION USING ARTIFICIAL NEURAL NETWORK

Traditionally, tidal prediction was carried out using the harmonic method, which is based on the identification of the harmonic constituents existing in the tidal record. Unfortunately, however, unless long tidal records are available at the tide gauges, some important tidal constituents may not be identified. This, in turn, deteriorates the accuracy of the tidal prediction. Additionally, tidal prediction is affected by the accuracy of the estimated amplitudes and phases of tidal constituents. To overcome the limitations of the traditional method, a neural network-based model is developed for sequentially predicting the tidal heights using tidal data series collected at various tide gauges. A modular three-layer feedforward neural network trained using the back-propagation algorithm is used for this purpose. Tide data from three tide gauges are used to validate the model. A comparison is made between the developed neural network model and the sequential least squares method for tidal prediction. It is shown that the accuracy level of the tidal prediction has improved by a factor of 5 when using the neural network model.
Channel Capacity of MIMO Systems under Correlate Fading Environment

In this paper, the channel capacity of a Multiple Input Multiple Output (MIMO) system with correlated fading is investigated. The fading correlation model is established and the effects of the number of antennas and the scattering angle on the channel capacity are studied. Based on the random theory, the closed-form expression for the channel capacity of MIMO system is derived in detail. The simulation results show that the channel capacity is determined by the fading correlated matrix. And the channel capacity is saturated when the number of the antennas increases to some values。
Models of Political Economy

1. Introduction 2. What Are We Aiming At? 3. Homo Oeconomicus 4. Economic Man Under Attack 5. Games: Descriptions and Solutions 6. Bargaining and Coalitions 7. Decision-Making in Committees 8. Designing for Elections and Public Goods Provision 9. What Kind of Government? 10. Aspects of Policy Evaluation 11. Homo Oeconomicus: Should We Let Him Go?
In Vitro and In Vivo Characterization of MicroRNA-Targeted Alphavirus Replicon and Helper RNAs

ABSTRACT Alphavirus-based replicon vector systems (family Togaviridae) have been developed as expression vectors with demonstrated potential in vaccine development against both infectious diseases and cancer. The single-cycle nature of virus-like replicon particles (VRP), generated by supplying the structural proteins from separate replicable helper RNAs, is an attractive safety component of these systems. MicroRNAs (miRNAs) have emerged as important cellular RNA regulation elements. Recently, miRNAs have been employed as a mechanism to attenuate or restrict cellular tropism of replication-competent viruses, such as oncolytic adenoviruses, vesicular stomatitis virus, and picornaviruses as well as nonreplicating lentiviral and adenoviral vectors. Here, we describe the incorporation of miRNA-specific target sequences into replicable alphavirus helper RNAs that are used in trans to provide the structural proteins required for VRP production. VRP were found to be efficiently produced using miRNA-targeted helper RNAs if miRNA-specific inhibitors were introduced into cells during VRP production. In the absence of such inhibitors, cellular miRNAs were capable of downregulating helper RNA replication in vitro. When miRNA targets were incorporated into a replicon RNA, cellular miRNAs were capable of downregulating replicon RNA replication upon delivery of VRP into animals, demonstrating activity in vivo. These data provide the first example of miRNA-specific repression of alphavirus replicon and helper RNA replication and demonstrate the feasibility of miRNA targeting of expression vector helper functions that are provided in trans.
Partial reconfiguration and specialized circuitry for flexible FPGA-based packet processing

In order to process network packets at high rates, network functions like routing or firewalling require specialized hardware like TCAMs (Ternary Content Addressable Memories), ASICs (Application Specific Integrated Circuits), or GPUs (Graphics Processing Units). Such hardware must be fast enough to process packets at line rate, and furthermore, it must be programmable in order to update the packet processing policy (e. g., a forwarding table or firewall rule set). From a fundamental point of view, though, these goals are conflicting because a generic programmable circuit must provide sufficient resources to support a wide range of policies, which can lead to unused circuitry and low clock rates. In addition, it misses logic optimization opportunities with regard to the structure of the installed policy. In this work, we investigate the optimization potential of automatically generated network processing circuits that are tailor-made for a specific policy. Using the example of router forwarding information bases (FIBs), we demonstrate that circuits which are partially evaluated with respect to the implemented FIB need more than one order of magnitude less logic resources than an equivalent generic forwarding circuit. We combine this approach with the partial reconfiguration capability of FPGAs in order to obtain an efficient low-latency forwarding engine whose matching circuitry can be replaced on demand.
The Analysis of Resolution of the Discrete Fractional Fourier Transform

The fractional Fourier transform (FRFT) is a unified time-frequency transform that does not suffer from the cross terms and is suitable for processing the non stationary signal. It is required to define the corresponding analysis range and discrete resolution in the FRFT domain in order to apply the FRFT to digital signal processing field. In this paper the analysis range and resolution of the discrete FRFT are obtained according to the relationship between the Wigner distribution and the FRFT
Inhibition of mTOR Prevents ROS Production Initiated by Ethidium Bromide-Induced Mitochondrial DNA Depletion

The regulation of mitochondrial mass and DNA content involves a complex interaction between mitochondrial DNA replication machinery, functional components of the electron transport chain, selective clearance of mitochondria, and nuclear gene expression. In order to gain insight into cellular responses to mitochondrial stress, we treated human diploid fibroblasts with ethidium bromide at concentrations that induced loss of mitochondrial DNA over a period of 7 days. The decrease in mitochondrial DNA was accompanied by a reduction in steady state levels of the mitochondrial DNA binding protein, TFAM, a reduction in several electron transport chain protein levels, increased mitochondrial and total cellular ROS, and activation of p38 MAPK. However, there was an increase in mitochondrial mass and voltage dependent anion channel levels. In addition, mechanistic target of rapamycin (mTOR) activity, as judged by p70S6K targets, was decreased while steady state levels of p62/SQSTM1 and Parkin were increased. Treatment of cells with rapamycin created a situation in which cells were better able to adapt to the mitochondrial dysfunction, resulting in decreased ROS and increased cell viability but did not prevent the reduction in mitochondrial DNA. These effects may be due to a more efficient flux through the electron transport chain, increased autophagy, or enhanced AKT signaling, coupled with a reduced growth rate. Together, the results suggest that mTOR activity is affected by mitochondrial stress, which may be part of the retrograde signal system required for normal mitochondrial homeostasis.
Power-Aware Wireless Transmission for Computation Offloading in Mobile Cloud

In today's mobile devices, the battery reservoir remains severely limited in capacity, making power consumption a key concern in the design and implementation of mobile applications. In this paper, we closely examine one widely adopted approach to improve the energy efficiency of mobile applications-adaptively offloading the computation to the remote cloud. In particular, we measure the power consumption of computation offloading for two representative real-world mobile cloud applications under various wireless network conditions and identify the unique features of data transmission for computation offloading. We then formulate the power-aware scheduling problem for computation offloading and present a scheduling algorithm that makes adaptive offloading decisions according to the dynamic network conditions. Simulation results show that our proposed method can achieve better battery performance, which also reveal that computation-intensive and delay-tolerant tasks are more likely to benefit from offloading.
Neural correlates of absolute pitch differ between blind and sighted musicians

Several reports have indicated a higher incidence of absolute pitch in blind than in sighted musicians. Employing a pitch memory task, we examined whether a blind absolute pitch musician would rely on different neural correlates than a group of sighted absolute pitch musicians. The blind musician showed significantly more activation of bihemispheric visual association areas, lingual gyrus, parietal and frontal areas than the sighted musicians. Sighted musicians showed more activation of the right primary auditory cortex and the cerebellum when compared with the blind musician. These differences in the activation pattern suggest the use of a different neural network including visual association areas while performing pitch categorization and identification in this blind musician in comparison with sighted musicians.
Regional Policies and EU Enlargement

Taking both the enlargement process, as currently defined by the EU, and the structural funds as a given, this Paper examines what is the best way for candidate countries to fuel real convergence. The experience from earlier EU enlargements and current economic conditions within the CEEC10 suggest that placing too high expectations on enlargement per se would be misplaced. Further, regional transfers taking place under the structural and cohesion policies are unlikely to become the growth engines of the CEEC10. They may increase income in the receiving countries by an amount equal to the one transferred, but there is no evidence they will have an impact on long-run growth rates. To achieve long-run growth at rates higher than average an appropriate mix of European and national policies is needed. This includes further fostering of trade integration within the EU, restructuring public spending, creation of supply side incentives by proper reforms of fiscal and social insurance policies, free movement of capital and labour, together with a competitive level of labour income taxation. Based on historical experience two types of policies appear to be particularly relevant. First, public programs for long-term income support, corporate subsidies and other forms of income transfer have negative effect on economic growth. We believe they should be terminated as soon as possible. Second, labour and capital mobility are good for growth and economic convergence. In particular, the adoption or continuation of various transfer and/or regulation policies aimed at eliminating labour migration from the CEEC is wrong and damaging. The fear of migration has been magnified by skillful politicians: migrations in past enlargements have been small. There is no reason to expect it to be large in this case.
Magazine Subscription and Intertemporal Discounting: Some Further Evidence

The paper’s objective is to assess price discrimination in magazine subscriptions in the Brazilian market. Oster and Scott-Morton (2005) had advanced a price discrimination mechanism in which the ratio between subscription and newsstand prices would be positively associated to the extent that a magazine provides long-term benefits. The present conservative application, in a market where subscription is much less widespread, does not provide support for that form of price discrimination after controlling for different characteristics of the magazines in the econometric analysis. Nevertheless, an exploratory analysis based on principal components suggests that a multidimensional price discrimination mechanism that is composed of price and advertising discounts may be occurring.
Hyperammonemia Associated with Valproic Acid Concentrations

Valproic acid, a branched short-chain fatty acid, has numerous action mechanisms which turn it into a broad spectrum anticonvulsant drug and make its use possible in some other pathologies such as bipolar disorder. It is extensively metabolized in liver, representing β-oxidation in the mitochondria one of its main metabolic route (40%). Carnitine is responsible for its entry into the mitochondria as any other fatty acid. Long-term high-dose VPA therapy or acute VPA overdose induces carnitine depletion, resulting in high levels of ammonia in blood. As a high correlation between salivary valproic acid levels and plasma ultrafiltrate levels was found in humans, saliva becomes a promising monitoring fluid in order to study valproic acid pharmacokinetics and its toxic effect. Extended-release (twice daily) formulations of valproic acid or carnitine supplementation are the proposed two therapeutic strategies in order to reverse hyperammonemia.
Preprocessing and Quality Control Strategies for Illumina DASL Assay-Based Brain Gene Expression Studies with Semi-Degraded Samples

Available statistical preprocessing or quality control analysis tools for gene expression microarray datasets are known to greatly affect downstream data analysis, especially when degraded samples, unique tissue samples, or novel expression assays are used. It is therefore important to assess the validity and impact of the assumptions built in to preprocessing schemes for a dataset. We developed and assessed a data preprocessing strategy for use with the Illumina DASL-based gene expression assay with partially degraded postmortem prefrontal cortex samples. The samples were obtained from individuals with autism as part of an investigation of the pathogenic factors contributing to autism. Using statistical analysis methods and metrics such as those associated with multivariate distance matrix regression and mean inter-array correlation, we developed a DASL-based assay gene expression preprocessing pipeline to accommodate and detect problems with microarray-based gene expression values obtained with degraded brain samples. Key steps in the pipeline included outlier exclusion, data transformation and normalization, and batch effect and covariate corrections. Our goal was to produce a clean dataset for subsequent downstream differential expression analysis. We ultimately settled on available transformation and normalization algorithms in the R/Bioconductor package lumi based on an assessment of their use in various combinations. A log2-transformed, quantile-normalized, and batch and seizure-corrected procedure was likely the most appropriate for our data. We empirically tested different components of our proposed preprocessing strategy and believe that our results suggest that a preprocessing strategy that effectively identifies outliers, normalizes the data, and corrects for batch effects can be applied to all studies, even those pursued with degraded samples.
ANALYSIS OF THE WATERFALL MODEL FOR THE SOFTWARE DEVELOPMENT PROCESS AND POSSIBILITIES FOR ITS IMPROVEMENT

Waterfall model for software development is still widely used in the industry. In this paper, the brief definition of waterfall model is given, along with the statement of the four shortcomings of this particular model and what has been done over the years to correct these. The author proposes his own modifications to the model, which correct three out of four problems connected with the waterfall model.
CW 20-W AlGaN/GaN FET Power Amplifier for Quasi-Millimeter Wave Applications

This paper describes an AlGaN/GaN FET power amplifier module delivering a continuous wave (CW) output power of more than 20 W at 26 GHz. To achieve high breakdown characteristics with reduced current collapse and high gain, we have developed a 0.2 µm-long recessed-gate AlGaN/GaN FET with a field-modulating plate (FP), achieving high operation voltage of 25 V even at quasi-millimeter wave frequencies. A single-ended AlGaN/GaN FP-FET amplifier module for quasi- millimeter wave frequency has been fabricated for the first time. The amplifier module developed using a 6.3-mm-wide single chip recessed-gate AlGaN/GaN FP-FET exhibited an output power of 20.7 W, a linear gain of 5.4 dB and a power-aided efficiency of 21.3% at 26 GHz. This is the highest output power in solid state power amplifiers at over 20 GHz.
Improving Polish Mention Detection with Valency Dictionary

This paper presents results of an experiment integrating information from valency dictionary of Polish into a mention detection system. Two types of information is acquired: positions of syntactic schemata for nominal and verbal constructs and secondary prepositions present in schemata. The syntactic schemata are used to prevent (for verbal realizations) or encourage (for nominal groups) constructing mentions from phrases filling multiple schema positions, the secondary prepositions – to filter out artificial mentions created from their nominal components. Mention detection is evaluated against the manual annotation of the Polish Coreference Corpus in two settings: taking into account only mention heads or exact borders.
Modelling the Time on Unemployment Insurance Benefits

A duration model based on the time on Unemployment Insurance (UI) benefits instead of a model based on the time till re-employment is more relevant from a cost-benefit perspective. The contribution of this paper is to extend the standard (mixed) Proportional Hazard model to account for an upper bound on the duration. We use a modified mover-stayer model to this end and discuss the interpretation of the parameters. In an empirical application we compare the method with the standard analysis of unemployment duration. We also derive the expected UI-benefit costs implied by the model for some typical unemployed individuals.
Neural Network Adaptive Control for a Class of Nonlinear Uncertain Dynamical Systems With Asymptotic Stability Guarantees

In this paper, a neuroadaptive control framework for continuous- and discrete-time nonlinear uncertain dynamical systems with input-to-state stable internal dynamics is developed. The proposed framework is Lyapunov based and unlike standard neural network (NN) controllers guaranteeing ultimate boundedness, the framework guarantees partial asymptotic stability of the closed-loop system, that is, asymptotic stability with respect to part of the closed-loop system states associated with the system plant states. The neuroadaptive controllers are constructed without requiring explicit knowledge of the system dynamics other than the assumption that the plant dynamics are continuously differentiable and that the approximation error of uncertain system nonlinearities lie in a small gain-type norm bounded conic sector. This allows us to merge robust control synthesis tools with NN adaptive control tools to guarantee system stability. Finally, two illustrative numerical examples are provided to demonstrate the efficacy of the proposed approach.
Electromagnetic modeling of bianisotropic Debye materials

We study the periodic unfolding homogenization, in the time domain, of bianisotropic materials. We take into account the memory effects of the electromagnetic field by considering that our material obeys to the Debye polarization model. All the effective electromagnetic parameters, such as the permittivity, the permeability and the homogenized susceptibility kernel are computed.
Survivor Benefits and the Gender Tax Gap in Public Pension Schemes: Observations from Germany

Since its inception, the traditional form of providing survivor benefits within public pension schemes has lost much of its legitimacy. As a result of fundamental changes in marriage behaviour and the typical division of labour between married spouses, offering non-contributory benefits of this kind could be seen as inequitable. Since these benefits usually substitute for non-derived pension entitlements based on the surviving spouse’s own contributions, they can also lead to incentive effects, especially for married women with some degree of labour-force attachment, that appear to be far from optimal. The present paper highlights this problem referring to institutional details and empirical results related to Germany and shows how it could be resolved by jointly annuitizing a given couple’s pension entitlements.