Miracle-dz/UniFAR-FTUs huggingface dataset:
Susceptibility to Oxidative Stress is Greater in Korean Patients with Coronary Artery Disease than Healthy Subjects

There are some evidences that the increased oxidative stress and thus increased oxidizability of lipoproteins and DNA can contribute to the development of certain human diseases, such as cardiovascular disease. To confirm the association of DNA damage with cardiovascular disease, we investigated susceptibility of DNA to oxidation in lymphocytes and oxidative stress related parameters in blood of patients with coronary artery disease (CAD). Subjects were consisted of 42 patients (27 men, 15 women) with documented CAD and 49 apparently healthy subjects (33 men, 16 women) as controls. Cellular DNA damage induced by 100 µM H2O2 was measured using Comet assay and quantified by TL. There were no differences in age (61.4 ± 1.7 years vs 62.0 ± 2.2 years) between the two groups. All the findings were shown to be independent of either sex or smoking habit. The patients showed significantly higher TL (87.3 ± 1.6 µm) compared to the control (79.3 ± 1.7 µm, p<0.01). Plasma TRAP, vitamin C, γ-tocopherol, and α-carotene levels in patients group were lower than those of control groups, while erythrocytic catalase activity increased in patients group. In conclusion, we observed that reduced overall antioxidant status was closely connected to higher susceptibility of DNA damage in CAD patients.
Improved use of SNP information to detect the role of genes

A topical question in genetic association studies is the optimal use of the information provided by genotyped single‐nucleotide polymorphisms (SNPs) in order to detect the role of a candidate gene in a multifactorial disease. We propose a strategy called “combination test” that tests the association between a quantitative trait and all possible phased combinations of various numbers of SNPs. We compare this strategy to two alternative strategies: the association test that considers each SNP separately, and a multilocus genotype‐based test that considers the phased combination of all SNPs together. To compare these three tests, a quantitative trait was simulated under different models of correspondence between phenotype and genotype, including the extreme case when two SNPs interact with no marginal effects of each SNP. The genotypes were taken from a sample of 290 independent individuals genotyped for three genes with various number of SNPs (from 5–8 SNPs). The results show that the “combination test” is the only one able to detect the association when the two SNPs involved in disease susceptibility interact with no marginal effects. Interestingly, even in the case of a single etiological SNP, the “combination test” performed well. We apply the three tests to Genetic Analysis Workshop 12 (Almasy et al. [2001] Genet. Edpidemiol. 21:332–338) simulated data, and show that although there was no interactions between the etiological SNPs, the “combination test” was preferable to the two other compared methods to detect the role of the candidate gene. Genet Epidemiol 25:158–167, 2003. © 2003 Wiley‐Liss, Inc.
EXTRACTION OF SPATIAL PATTERNS IN TROPICAL RAINFOREST FROM POWER SPECTRUM ANALYSIS OF AIRBORNE SAR DATA

Power spectrum analysis is used for analysis of spatial forest structure from airborne X-band SAR data in the Brazilian Amazon. Spectral estimates are arrived at empirically by periodograms, from autoregressive moving-average models, and from a window-based autocorrelation function. The spectral estimates derived from SAR data are validated with those derived from ground data with exact locational match. The results gotten by ARMA modeling, and by the correlogram method do reveal particularly good correspondence between remote sensing and reference data, repeating patterns at the pixel level can be detected in the images. These patterns seem to arise from canopy structure, and thus allow for extraction of parameters of spatial forest structure, particularly of forest density.
A 107.4 dB SNR Multi-Bit Sigma Delta ADC With 1-PPM THD at $-$0.12 dB From Full Scale Input

A second order sigma delta modulator (SDM) with a 5-bit quantizer has been presented using several novel techniques: simplified DAC arrays for easy implementation, high-order truncation noise shaping for increased tolerance to analog imperfections, and an extended dynamic range for a maximum input signal swing of up to -0.12 dBFS (Full Scale). With truncation filters and a pseudo SDM in the DSP, the truncation and saturation errors are compensated through the DAC arrays and the DSP. The design, fabricated in a 0.18 mum dual gate oxide (DGO) process obtains a signal-to-noise-and-distortion ratio (SNDR) of 105.9 dB and a dynamic range (DR) of 107.4 dB with 31.25-KHz bandwidth at an 8-MHz sampling frequency and a power consumption of 14.7 mW.
Institutional change in the West African Economic and Monetary Union (WAEMU) since 1994: A fresh start after the devaluation shock?

Summary: Parallel to the Franc CFA devaluation in January 1994, the West African Economic and Monetary Union (WAEMU/UEMOA) was formed. It succeeded the monetary union within the Franc zone (NAMU/UMOA) and the economic community WAEC/CEAO. The WAEMU avoided some of the institutional errors and deficiencies of its predecessors, attempting to save the monetary union after the shock of devaluation. For this purpose, the economic policies of the member states have to be co-ordinated. The WAEMU treaty promotes the delegation of decisions to supranational authorities, which constitutes a novelty within West Africa. The WAEMU has autonomous sources of finance in connection with the existing Central Bank (BCEAO). The WAEMU is not only a preferential trading zone (as the WAEC/CEAO had been) but aims at the establishment of a common market. The realisation of its decisions, however, meets difficulties, arising from financial restrictions as well as from long-standing political practices of the WAEMU member states, such as insufficiencies regarding the rule of law. WAEMU does not yet address some important preconditions for a broadly-based regional integration process, such as the inclusion of the informal economic sector.
E-Assessment using Latent Semantic Analysis in the Computer Science Domain: A Pilot Study

Latent Semantic Analysis (LSA) is a statistical Natural Language Processing (NLP) technique for inferring meaning from a text. Existing LSA-based applications focus on formative assessment in general domains. The suitability of LSA for summative assessment in the domain of computer science is not well known. The results from the pilot study reported in this paper encourage us to pursue further research in the use of LSA in the narrow, technical domain of computer science. This paper explains the theory behind LSA, describes some existing LSA applications, and presents some results using LSA for automatic marking of short essays for a graduate class in architectures of computing systems.
Midline Body Actions and Leftward Spatial “Aiming” in Patients with Spatial Neglect

Spatial motor–intentional “Aiming” bias is a dysfunction in initiation/execution of motor–intentional behavior, resulting in hypokinetic and hypometric leftward movements. Aiming bias may contribute to posture, balance, and movement problems and uniquely account for disability in post-stroke spatial neglect. Body movement may modify and even worsen Aiming errors, but therapy techniques, such as visual scanning training, do not take this into account. Here, we evaluated (1) whether instructing neglect patients to move midline body parts improves their ability to explore left space and (2) whether this has a different impact on different patients. A 68-year-old woman with spatial neglect after a right basal ganglia infarct had difficulty orienting to and identifying left-sided objects. She was prompted with four instructions: “look to the left,” “point with your nose to the left,” “point with your [right] hand to the left,” and “stick out your tongue and point it to the left. ” She oriented leftward dramatically better when pointing with the tongue/nose, than she did when pointing with the hand. We then tested nine more consecutive patients with spatial neglect using the same instructions. Only four of them made any orienting errors. Only one patient made >50% errors when pointing with the hand, and she did not benefit from pointing with the tongue/nose. We observed that pointing with the tongue could facilitate left-sided orientation in a stroke survivor with spatial neglect. If midline structures are represented more bilaterally, they may be less affected by Aiming bias. Alternatively, moving the body midline may be more permissive for leftward orienting than moving right body parts. We were not able to replicate this effect in another patient; we suspect that the magnitude of this effect may depend upon the degree to which patients have directional akinesia, spatial Where deficits, or cerebellar/frontal cortical lesions. Future research could examine these hypotheses.
Quorum based geographically static data storage in ad-hoc networks

Large-scale wireless ad-hoc networks are formed automatically and allow nodes to communicate over greater distances. Every node acts as a router forming a complex network, which is simplified by the use of geodesic routing. However, a method to discover a node.s location is needed for geodesic routing. In this paper we propose two algorithms which could support location servers in ad-hoc networks and examine their performance.
Comparative analysis of automated classifiers applied to volcano event identification

The correct classification of several types of volcanic events can be used to determine the intrinsic behavior of a volcano. This information could be useful to provide an early alarm in the case of imminent volcanic activity. Therefore, finding an efficient algorithm capable of identifying seismic activity can be beneficial for this purpose. In such sense, this work evaluates several machine learning techniques, that have been previously applied to classify seismic events, taking into account quality and performance parameters. In order to test the algorithms, a seismic database from the Cotopaxi volcano in Ecuador was used. This database was collected by the Geophysical Institute at Escuela Politécnica Nacional between January and June of 2010. The analysis was focused in two major types of seismic events: long period and volcano tectonic. For each event, 79 key features in time and frequency domain were extracted. These features were used to train 3 well known classifiers: k-nearest neighbors, decision trees and neural networks. Finally, a feature selection technique was employed to find those features with greater impact improving the classifier performance. Our approach allow us to reach an accuracy of 98% by identifying 3 main features and using the k-NN classifier.
An Initial Evaluation of a Cognitive Model of UAV Reconnaissance

Training simulators have a specific need for accurate human behavior representation to best simulate conditions a trainee will encounter in the real world. This paper outlines a cognitive model of human pilots flying a Predator Unmanned Aerial Vehicle (UAV). The model was implemented to interact directly with a synthetic task environment (STE) built upon a validated flight dynamics model of the Predator RQ1A System 4 UAV. The model flies reconnaissance missions in the STE with the goal of maximizing the amount of surveillance footage that is obtained by maneuvering the Predator over a small hole in a layer of clouds. At the same time, the model must minimize the time spent in violation states (e.g., exceeding altitude restrictions or entering no-fly zones). Initial analysis shows that the model can complete simulated missions with performance characteristics similar to those observed in real pilots.
Aerosol optical properties of a haze episode in Wuhan based on ground-based and satellite observations

A severe haze episode that occurred in Wuhan, central China, from 6–14 June 2012 was investigated using ground-based and satellite-derived observations, from which the optical properties and vertical distribution of the aerosols were obtained. The mass concentrations of PM2.5 and black carbon (BC) were 9.9 (332.79 versus 33.66 μg∙m−3) and 3.2 times (9.67 versus 2.99 μg∙m−3) greater, respectively, on haze days than during normal weather. The large aerosol loading contributed to the high values of the scattering (2.32 km−1) and absorption coefficients (0.086 km−1). Particle size became larger, consistent with the reduced scattering Angstrom exponent. The high asymmetry parameter (0.65) and single scattering albedo (SSA) (0.97) observed in the haze, which coincided with the relatively low backscatter ratio (0.11) and up-scatter fraction (0.23), were related to the increased particle size, and could have had a heating effect on the atmosphere. Aerosols accumulated primarily below 3 km and according to CALIPSO, were regular in their shapes. At the surface, the aerosol extinction coefficient detected by satellite remained at ~1 km−1, very close to the ground-based observations. Aerosol optical properties measured at this downtown site could help further the understanding of the effects of aerosols on the air quality, city environment, and radiation balance.
Anthocyanin Characterization, Total Phenolic Quantification and Antioxidant Features of Some Chilean Edible Berry Extracts

The anthocyanin composition and HPLC fingerprints of six small berries endemic of the VIII region of Chile were investigated using high resolution mass analysis for the first time (HR-ToF-ESI-MS). The antioxidant features of the six endemic species were compared, including a variety of blueberries which is one of the most commercially significant berry crops in Chile. The anthocyanin fingerprints obtained for the fruits were compared and correlated with the antioxidant features measured by the bleaching of the DPPH radical, the ferric reducing antioxidant power (FRAP), the superoxide anion scavenging activity assay (SA), and total content of phenolics, flavonoids and anthocyanins measured by spectroscopic methods. Thirty one anthocyanins were identified, and the major ones were quantified by HPLC-DAD, mostly branched 3-O-glycosides of delphinidin, cyanidin, petunidin, peonidin and malvidin. Three phenolic acids (feruloylquinic acid, chlorogenic acid, and neochlorogenic acid) and five flavonols (hyperoside, isoquercitrin, quercetin, rutin, myricetin and isorhamnetin) were also identified. Calafate fruits showed the highest antioxidant activity (2.33 ± 0.21 μg/mL in the DPPH assay), followed by blueberry (3.32 ± 0.18 μg/mL), and arrayán (5.88 ± 0.21), respectively.
Side-channel attack mitigation using dual-spacer Dual-rail Delay-insensitive Logic (D3L)

Side-channel attacks have become a threat to secure electronic circuits, due to the strong correlation between data pattern and leaking power/timing information. By monitoring the power/timing behavior of a synchronous circuit, an attacker can easily obtain the secret data stored in the device. Although dual-rail asynchronous circuits have more stable power traces, they still show power fluctuation because of the imbalanced load between two rails. Moreover, asynchronous circuits are the most prone to timing attacks since delay is data dependent. Dual-spacer Dual-rail Delay-insensitive Logic (D3L), presented in this paper, is able to mitigate power and timing based side-channel attacks. Power fluctuation is decoupled from data pattern by the use of a dual-spacer protocol, while timing-data correlation is broken by insertion of random delays.
Determination of metabolite profiles in tropical wines by 1H NMR spectroscopy and chemometrics

Traditionally, wines are produced in temperate climate zones, with one harvest per year. Tropical wines are a new concept of vitiviniculture that is being developed, principally in Brazil. The new Brazilian frontier is located in the northeast region (São Francisco River Valley) in Pernambuco State, close to the equator, between 8 and 9°S. Compared with other Brazilian and worldwide vineyards, the grapes of this region possess peculiar characteristics. The aim of this work is a preliminary study of commercial São Francisco River Valley wines, analyzing their metabolite profiles by 1H NMR and chemometric methods. Copyright © 2009 John Wiley & Sons, Ltd.
A high-efficiency resonant solar micro-inverter

Transmission grids worldwide are presently facing challenges in integrating large scale renewable systems due to their limited power transmission capacity. This paper presents a novel circuit topology and control for grid connected micro-inverters suitable for solar AC modules. This topology is based on the single-stage DC to AC conversion approach. The circuit has an L-C series resonant converter, a high frequency transformer and a line frequency unfolder. Design and control considerations are presented along with the detailed design of resonant components. The circuit components and controls have been optimized to achieve very high efficiency at various load and input conditions. A controller has been designed and simulated using a Simulink® numeric package. An experimental prototype was designed to achieve a high California Energy Commission (CEC) efficiency rating
EXPERIMENTAL INVESTIGATING THE F-MEASURE AS SIMILARITY MEASURE FOR AUTOMATIC TEXT SUMMARIZATION

This paper evaluates the performance of different similarity measures in the context of document summarization. For this purpose in this paper a simple and effective sentence extractive technique is used. The proposed method is based on evaluation of relevance score of sentence. Many measures are available for the calculation of inter sentence relationships. To calculate a similarity between sentences we use cosine measure and classical IR F-measure. We present a comprehensive experimental evaluation two different document collection. Our experimental results show that F-measure lead to the best overall results than cosine measure.
Concept Types and Determination

The article offers a systematic account of four basic types of nouns, of four basic types of nominal determination and of the interaction of noun type and determination type. The four basic noun types are sortal, individual, relational and functional; they correspond to the four logical types 〈e,t〉, e, 〈e,〈e,t〉〉 and 〈e,e〉 on the one hand, and to four types of concepts on the other. The four basic types of nominal determination are singular definite, indefinite (a variety of determinations including simple indefinite), absolute and relative, where possessive determination is a combination of relative reference and possessor specification. Only inherently unique concepts are available for singular definite reference, only nonunique ones for indefinite use, only nonrelational concepts for absolute reference and only relational ones for relative use. However, determiners of each type can be combined with nouns of each lexical type: if the type restrictions are not met, the noun is shifted to an appropriate type. On this basis, congruent and incongruent determinations are distinguished. Statistical, typological and historical evidence is presented that corroborates the hypothesis that incongruent determination is a marked option and involves type shifts of the noun.
Robust non-fragile state feedback control of discrete time-delay systems

The problem of designing robust non-fragile state feedback controllers for linear discrete systems with uncertainties and constant delays is studied. The system uncertainties are assumed to be polytopic, and the state feedback gain uncertainties are norm-bounded. The H/sub /spl infin// norm is used to describe system performance. A method of designing robust non-fragile H/sub /spl infin// controllers is proposed in terms of linear matrix inequalities (LMIs). Numerical examples are given to illustrate the proposed results.
Cloud-based RDF data management

The W3C's Resource Description Framework (or RDF, in short) is set to deliver many of the original semi-structured data promises: flexible structure, optional schema, and rich, flexible URIs as a basis for information sharing. Moreover, RDF is uniquely positioned to benefit from the efforts of scientific communities studying databases, knowledge representation, and Web technologies. As a consequence, numerous collections of RDF data are published, going from scientific data to general-purpose ontologies to open government data, in particular published as part of the Linked Data movement. Managing such large volumes of RDF data is challenging, due to the sheer size, the heterogeneity, and the further complexity brought by RDF reasoning. To tackle the size challenge, distributed storage architectures are required. Cloud computing is an emerging distributed paradigm massively adopted in many applications for the scalability, fault-tolerance and elasticity features it provides. This tutorial presents the challenges faced in order to efficiently handle massive amounts of RDF data in a cloud environment. We provide the necessary background, analyze and classify existing solutions, and discuss open problems and perspectives.
Bounded Kernel-Based Online Learning

A common problem of kernel-based online algorithms, such as the kernel-based Perceptron algorithm, is the amount of memory required to store the online hypothesis, which may increase without bound as the algorithm progresses. Furthermore, the computational load of such algorithms grows linearly with the amount of memory used to store the hypothesis. To attack these problems, most previous work has focused on discarding some of the instances, in order to keep the memory bounded. In this paper we present a new algorithm, in which the instances are not discarded, but are instead projected onto the space spanned by the previous online hypothesis. We call this algorithm Projectron. While the memory size of the Projectron solution cannot be predicted before training, we prove that its solution is guaranteed to be bounded. We derive a relative mistake bound for the proposed algorithm, and deduce from it a slightly different algorithm which outperforms the Perceptron. We call this second algorithm Projectron++. We show that this algorithm can be extended to handle the multiclass and the structured output settings, resulting, as far as we know, in the first online bounded algorithm that can learn complex classification tasks. The method of bounding the hypothesis representation can be applied to any conservative online algorithm and to other online algorithms, as it is demonstrated for ALMA2. Experimental results on various data sets show the empirical advantage of our technique compared to various bounded online algorithms, both in terms of memory and accuracy.