Miracle-dz/UniFAR-FTUs huggingface dataset:
Testing the Weak Form of Efficiency on Czech and Slovak Stock Market

The article deals with the testing of the weak form of efficiency on Czech and Slovak stock market during the period 2000–2004 based on daily returns representing index PX50 and SAX30 in the form of martingale as well as in the form of random walk. Concerning functional model forms of conditional variance, the linear and nonlinear volatility models have been estimated and half-life of the variance on the markets, presence of leverage effect or risk aversion have been evaluated.
Aspects of Control for the Normal Markov Processes

The choice of optimal control policy for sequentially observed data studied in a Bayesian context is usually a dynamic programming problem that involves a backward iterative solution. In general, as in most sequential Bayes problems, optimal solutions are difficult to derive analytically in simple forms. The system of linear models examined here is, however, amongst the few cases with known explicit optimal solutions. This would allow analytical comparisons with the performance of sub-optimal control procedures. Certain sequence of myopic rules are introduced and applied to the control system. These rules, in general, will provide the user with good near- optimal control policies whenever optimal solutions are analytically difficult to determine. As the myopic rules do not involve backward iteration procedures, they are often convenient to apply, and in addition, the user has the option of improving the accuracy of any particular approximating solution by taking additional future costs into consideration. This approximation is, naturally, at its best when the complete future cost is considered and, for the Aoki (1967) linear control system, solutions are then proved to be optimal.
Credit Market Shocks, Monetary Policy, and Economic Fluctuations

This paper uses a dynamic stochastic general equilibrium model with credit market imperfections to estimate the role of credit market shocks and monetary policy in US business cycles. The estimated model captures much of the historical narrative regarding the conduct of monetary policy and developments in financial markets that led to episodes of financial excess and distress over the last two decades. The estimation suggests that credit market shocks are an important factor behind economic fluctuations accounting for 15% of the variance in real output since 1985. In addition, we find that once credit market imperfections are considered, monetary policy is also an important force behind real output fluctuations explaining 12.5% of its variance.
A Novel Protein Secondary Structure Prediction System Based on Compound Pyramid Model

Protein Secondary structure prediction is essential for the tertiary structure modeling, and it is the one of the major challenge of bioinformatics. In this article, we proposed a gradually enhanced, multi-layered prediction systematic model, Compound Pyramid Model (CPM). This model is composed of four independent coordination's layers by intelligent interfaces, synthesizes several methods, such as SVM, KDD* process model and so on. The model penetrates the whole domain knowledge, and the effective attributes are chosen by Causal Cellular Automata, and the high pure structure database is constructed for training. On the RS126 data set, state overall per-residue accuracy, Q3, reached 83.99%. On the CB513 data set, Q3 reached 85.58%. Meanwhile, on the CASP8's sequences, the results are found to be superior to those produced by other methods, such as SAM, PSI-Blast, Prospect, JUFO, and so on. The result shows that our method has strong generalization ability.
Clathrin Is Spindle-Associated but Not Essential for Mitosis

Background Clathrin is a multimeric protein involved in vesicle coat assembly. Recently clathrin distribution was reported to change during the cell cycle and was found to associate with the mitotic spindle. Here we test whether the recruitment of clathrin to the spindle is indicative of a critical functional contribution to mitosis. Methodology/Principal Findings Previously a chicken pre-B lymphoma cell line (DKO-R) was developed in which the endogenous clathrin heavy chain alleles were replaced with the human clathrin heavy chain under the control of a tetracycline-regulatable promoter. Receptor-mediated and fluid-phase endocytosis were significantly inhibited in this line following clathrin knockout, and we used this to explore the significance of clathrin heavy chain expression for cell cycle progression. We confirmed using confocal microscopy that clathrin colocalised with tubulin at mitotic spindles. Using a propidium iodide flow cytometric assay we found no statistical difference in the cell cycle distribution of the knockout cells versus the wild-type. Additionally, we showed that the ploidy and the recovery kinetics following cell cycle arrest with nocodazole were unchanged by repressing clathrin heavy chain expression. Conclusions/Significance We conclude that the association of clathrin with the mitotic spindle and the contribution of clathrin to endocytosis are evolutionarily conserved. However we find that the contribution of clathrin to mitosis is less robust and dependent on cellular context. In other cell-lines silencing RNA has been used by others to knockdown clathrin expression resulting in an increase in the mitotic index of the cells. We show an effect on the G2/M phase population of clathrin knockdown in HEK293 cells but show that repressing clathrin expression in the DKO-R cell-line has no effect on the size of this population. Consequently this work highlights the need for a more detailed molecular understanding of the recruitment and function of clathrin at the spindle, since the localisation but not the impact of clathrin on mitosis appears to be robust in plants, mammalian and chicken B-cells.
Metabolic Syndrome and Inflammation: A Critical Review of In Vitro and Clinical Approaches for Benefit Assessment of Plant Food Supplements

Metabolic syndrome is defined as the clustering in an individual of several metabolic abnormalities associated with insulin resistance, type 2 diabetes, and obesity, in which low-grade chronic inflammatory activity is commonly observed. Part of the European Project PlantLIBRA is concerned with methods to assess the benefits of plant food supplements (PFSs) in countering inflammatory activity and metabolic syndrome. This paper summarizes the current methods used for benefit assessment of PFS, taking into consideration only in vitro, in silico, and clinical methodologies used to investigate the anti-inflammatory properties of plants. No in silico studies (using computer simulation) related to metabolic syndrome were found; these methods appear to be used exclusively for identifying or testing potentially effective compounds in drug development. Most in vitro methods for the assessment of beneficial effects of botanicals or plant food supplements in diabetes were based on a quantitative polymerase chain reaction (PCR), whereas the preferred kind of clinical study was the double-blind randomized controlled clinical trial. Only two parameters were observed to change after treatment with botanicals in both in vitro and in vivo studies: interleukin-6 and tumour necrosis factor-α, and these biomarkers should be carefully considered in future studies for PFS benefit assessment.
Query Optimization on Compressed and Decompressed Object-Oriented Database Using Operators

-In this paper, we present an approach using various database operators that permits to enrich technique of query optimization existing in the object-oriented databases and the comparative analysis of query optimization of compressed and uncompressed object oriented database based on cost, cardinality and no of bytes. Focus is on query optimization using relational operator, logical operator and special operators. Our experimental study shows that the improvement in the quality of plans is significant only with decrease in cost, cardinality and no of bytes after database compression. Looking at the success of query optimization in the relational model, our approach inspires itself of these optimization techniques and enriched it so that they can support the new concepts introduced by the object oriented databases.
0 21 10 51 v 5 4 N ov 2 00 4 Infrared Catastrophe for Nelson ’ s Model

We mathematically study the infrared catastrophe for the Hamiltonian of Nelson’s model when it has the external potential in a general class. For the model, we prove the pull-through formula on ground states in operator theory first. Based on this formula, we show both, non-existence of any ground state and divergence of the total number of soft bosons.
Data selection and pilot run on simplified genomic MACE (S-GMACE)

As a first step to international evaluation of genomically enhanced breeding values (GEBV) a pilot run on Simplified Genomic Multiple Across Country Evaluation (S-GMACE) was performed. This implies that only one GEBV per bull is considered in the analysis. GEBV data for Holstein bulls corresponding to the December 2010 routine MACE run from 3 to 7 countries for the traits protein yield, somatic cell score, stature, direct longevity and cow conception 1 (measures as conception rate) were available. For bulls with several GEBVs only one was chosen based on the following hierarchical selection criteria: largest number of daughters, country of first registration, highest correlation to country of first registration, and highest genomic reliability. The GEBV data were merged with the corresponding pre-edited conventional EBVs. In cases where both a GEBV and an EBV for the same bull existed within a country the EBV was discarded. The final dataset ranged from 68,481 (cow conception 1) to 151,904 records (protein yield) with a GEBV proportion from 40% (protein yield) to 52% (cow conception 1). The data were analyzed with MACE methodology using sire-dam relationships. Genetic trends of conventional and genomic runs coincided. Young bulls were among the top 100. In the case of protein yield they ranged from 26 to 64 according to the country scale. Due to the inclusion of genomic information there was an overall increase in international reliability on all country scales. Harmonization of input data is important in order to fairly select among GEBVs from different sources.
Influence of the Wavelet Family in the Compression-Denoising Technique on Synthetic and Natural Images

A denoising procedure based on a thresholding function has been integrated into the JPEG2000 part II standard which is designed to support a wide variety of applications, including the compression and transmission of medical images. This standard is based on the discrete wavelet transform using the Daubechies(9,7) biorthogonal wavelet, also named the Cohen-Daubechies-Feauveau 9/7 wavelet. However, is this the best choice concerning quality at any time? In this work we compared the results from 36 different variations of wavelets compression schemes to explore their difference related to image content and quality. Two groups of well known images of different levels of complexities and content are used to evaluate the relation among fidelity, image content and noise level. The first group is formed by natural images and the second group is formed by synthetic images. They are considered on two different resolutions (128 × 128 and 256 × 256) and with high level of Additive White Gaussian Noise. The performance of each approach is evaluated by means of fidelity, comparing the originals without noise versus the same images after compression/denoising and decompression. The goal is to define which combination present the best and the worst results considering the final visual quality.
EXTRACTION OF 3 D FEATURE FROM LIDAR DATA FUSED WITH AERIAL IMAGES USING IMPROVED MEAN-SHIFT ALGORITHM

An innovative approach is proposed for the extraction of the complex urban three dimensional feature efficiently and accurately. In this method, firstly, both the LiDAR data and the aerial images are respectively pre-processed and matched using an affine transformation technique. Then, an improved mean-shift algorithm is employed to classify the LiDAR data fused with reflected intensity and spectrum attribute into groups by kinds of feature, such as buildings, vegetation, water etc. The spectral information are extracted from aerial-image to extend the attribute of the LiDAR data. The classification accuracy is evaluated by a confusion matrix. Finally, the 3D model of interested region is quickly constructed based on the classified points and the aerial-image in software SketchUp. During the experiment, the key issue is how to control the results of classification through parameters setting.
Development of a high-speed, high-accuracy robot hand for micromanipulation

This study reports the development of a high-speed, high-accuracy robotic hand with the aim of implementing flexible and fast micromanipulation. The robotic hand, which has two fingers, each with three degrees of freedom, was tested for rapidity and accuracy to determine whether it was capable of micromanipulation. Our end goal was to enable it to handle smaller objects than humans can, more dexterously and quickly than them, by incorporating accuracy into the design of prevalent high-speed robotic hands. The size of the target objects to be manipulated was of the order of submillimeter. With regard to rapidity, we showed that each joint of the hand exhibited the same speed of movement as conventional high-speed robotic hands. In order to verify accuracy, we showed that the positioning accuracy of the fingertip was 10 [μm] at 0.20 [s] when all joints were actuated π/2 [rad], which was sufficient to manipulate objects of submillimeter size. Hence, the proposed robotic hand has the potential to manipulate micrometer-sized objects if combined with high-resolution visual feedback systems.
Diffuse, Nonthermal X-Ray Emission from the Galactic Star Cluster Westerlund 1

We present the diffuse X-ray emission identified in Chandra observations of the young, massive Galactic star cluster Westerlund 1. After removing pointlike X-ray sources down to a completeness limit of ≈2 × 1031 ergs s-1, we identify (3 ± 1) × 1034 ergs s-1 (2-8 keV) of diffuse emission. The spatial distribution of the emission can be described as a slightly elliptical Lorentzian core with a half-width at half-maximum along the major axis of 25′′ ± 1′′, similar to the distribution of point sources in the cluster, plus a 5' halo of extended emission. The spectrum of the diffuse emission is dominated by a hard continuum component that can be described as a kT ≳ 3 keV thermal plasma that has a low iron abundance (≲0.3 solar) or as nonthermal emission that could be stellar light that is inverse Compton scattered by MeV electrons. Only 5% of the flux is produced by a kT ≈ 0.7 keV plasma. The low luminosity of the thermal emission and the lack of a 6.7 keV iron line suggest that ≲40,000 unresolved stars with masses between 0.3 and 2 M☉ are present in the cluster, fewer than previously estimated. Moreover, the flux in the diffuse emission is a factor of several lower than would be expected from a supersonically expanding cluster wind, and there is no evidence for thermal remnants produced by supernovae. Less than 10-5 of the mechanical luminosity of the cluster is dissipated as 2-8 keV X-rays, leaving a large amount of energy that either is radiated at other wavelengths, is dissipated beyond the bounds of our image, or escapes into the intergalactic medium.
Robust denoising of point-sampled surfaces

Based on sampling likelihood and feature intensity, in this paper, a feature-preserving denoising algorithm for point-sampled surfaces is proposed. In terms of moving least squares surface, the sampling likelihood for each point on point-sampled surfaces is computed, which measures the probability that a 3D point is located on the sampled surface. Based on the normal tensor voting, the feature intensity of sample point is evaluated. By applying the modified bilateral filtering to each normal, and in combination with sampling likelihood and feature intensity, the filtered point-sampled surfaces are obtained. Experimental results demonstrate that the algorithm is robust, and can denoise the noise efficiently while preserving the surface features.
A cosine theorem based algorithm for similarity aggregation of ontologies

Ontology matching is a basic method for resolving ontology heterogeneity. In order to achieve the finest matching result through aggregation, a couple of measuring methods are often applied to the process of ontology matching and then the results of all methods produced are aggregated. This paper proposes a new method in aggregating the similarity through analysis of existing methods. Our proposal considers two similarities to be aggregated as two vectors with a specific angle and their values as the modulus of the vectors. The result of aggregation equals to the modulus of the vector determined by the subtraction of the two previous vectors. The process of calculation is involved in the application of cosine theorem and therefore that is the reason why this method is called a Cosine Theorem Based Algorithm (CTBA) for similarities aggregation of ontologies in this paper. The results of experiments and analysis conducted with the known data suggest that CTBA presented in this paper has a comparatively good performance in aggregating similarities of ontologies.
Reaction Time to 1- and 4-kHz Tones as a Function of Sensation Level in Listeners with Normal Hearing

Objective: Measures of reaction time (RT) near threshold have been used to indicate whether listeners with hearing losses of primarily cochlear origin experience greater loudness at elevated thresholds than at normal thresholds. These measurements have been based on the assumption that RTs near threshold are not affected by stimulus frequency in the 1- to 4-kHz range. The present study tests this hypothesis. Design: To gain an understanding of how RT is affected by frequency, RTs to 1- and 4-kHz tones were measured in 16 listeners with normal hearing across a wide range of sensation levels (SLs). Results: Statistical analyses indicate that RTs are affected by frequency in some listeners. This effect is most common at low SLs but is also present at higher SLs. Learning effects could not account for the observed differences between RTs at the two frequencies. Conclusions: Although reaction time—especially at low levels—is affected by stimulus frequency in some listeners, the effect is not large enough to account for the differences in RTs measured in all listeners with impaired hearing in other studies.
Network Vertical Intrusion Model (NetVIM)

The Network Vertical Intrusion Model (NetVIM) is proposed in this paper. The NetVIM is a vertical four layer model that provides for the identification, detection and profiling of network based attacks. The NetVIM models attack profiles consisting of the components involved in the physical delivery, the involved computation and communication processes and the states and state transitions inherent in an attack. This paper describes the NetVIM together with an example application to a TCP port scan attack.
Identification and Characterization of FAM124B as a Novel Component of a CHD7 and CHD8 Containing Complex

Background Mutations in the chromodomain helicase DNA binding protein 7 gene (CHD7) lead to CHARGE syndrome, an autosomal dominant multiple malformation disorder. Proteins involved in chromatin remodeling typically act in multiprotein complexes. We previously demonstrated that a part of human CHD7 interacts with a part of human CHD8, another chromodomain helicase DNA binding protein presumably being involved in the pathogenesis of neurodevelopmental (NDD) and autism spectrum disorders (ASD). Because identification of novel CHD7 and CHD8 interacting partners will provide further insights into the pathogenesis of CHARGE syndrome and ASD/NDD, we searched for additional associated polypeptides using the method of stable isotope labeling by amino acids in cell culture (SILAC) in combination with mass spectrometry. Principle findings The hitherto uncharacterized FAM124B (Family with sequence similarity 124B) was identified as a potential interaction partner of both CHD7 and CHD8. We confirmed the result by co-immunoprecipitation studies and showed a direct binding to the CHD8 part by direct yeast two hybrid experiments. Furthermore, we characterized FAM124B as a mainly nuclear localized protein with a widespread expression in embryonic and adult mouse tissues. Conclusion Our results demonstrate that FAM124B is a potential interacting partner of a CHD7 and CHD8 containing complex. From the overlapping expression pattern between Chd7 and Fam124B at murine embryonic day E12.5 and the high expression of Fam124B in the developing mouse brain, we conclude that Fam124B is a novel protein possibly involved in the pathogenesis of CHARGE syndrome and neurodevelopmental disorders.
Robust online multiple object tracking based on the confidence-based relative motion network and correlation filter

When tracking multiple objects in an image sequence, various difficulties such as occlusion, mis-detection, false detection, and abrupt camera motion often occur together. Nevertheless, previous methods on multi-object tracking generally focus on only one or two of them. For that reason, the previous methods could not handle various problematic situations, where multiple difficulties occur simultaneously. To overcome this limitation, we propose a unified framework that can handle such difficulties concurrently, where we effectively combine the confidence-based two-step data association and relative motion network with correlation filtering. We show that the proposed unified framework yields noticeable performance enhancement under various difficulties.
Merit Pay for Florida Teachers Design and Implementation Issues

This product is part of the RAND Education working paper series. RAND working papers are intended to share researchers' latest findings and to solicit additional peer review. This paper has been peer reviewed but not edited. Unless otherwise indicated, working papers can be quoted and cited without permission of the author, provided the source is clearly referred to as a working paper. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors. is a registered trademark. Abstract Florida has enacted a plan to reward teachers based on their classroom performance, as measured on standardized student achievement tests and principal evaluations. This merit pay initiative is designed to provide a financial incentive for teachers to improve student outcomes, to encourage the retention of proficient teachers, and to attract high‐ skilled individuals to the teaching profession. The design and implementation of merit pay faces several key challenges. First, student outcomes are difficult to define and measure. Second, the contributions of individual teachers to student outcomes are difficult to disentangle from student background and prior achievement. The analysis shows serious deficiencies in several measures of teacher performance. Policy makers should be wary of adapting any measure without careful analysis of its properties and a plan to monitor how it is performing. The key issue is whether the incentive and sorting effects of an admittedly imperfect merit pay system can improve the quality of the teacher workforce.