bluuebunny/crossref_metadata_2025_split huggingface dataset:
Younger age at onset of sporadic Parkinson’s disease among subjects occupationally exposed to metals and pesticides
Authors: Ratner Marcia H. , Farb David H. , Ozer Josef , Feldman Robert G. , Durso Raymon 
Published: January 2015

ABSTRACT
An earlier age at onset of Parkinson’s disease (PD) has been reported to be associated with occupational exposures to manganese and hydrocarbon solvents suggesting that exposure to neurotoxic chemicals may hasten the progression of idiopathic PD. In this study the role of occupational exposure to metals and pesticides in the progression of idiopathic PD was assessed by looking at age at disease onset. The effects of heritable genetic risk factors, which may also influence age at onset, was minimized by including only sporadic cases of PD with no family history of the disease (n=58). Independent samples Student t-test revealed that subjects with occupational exposure to metals and/or pesticides (n=36) were significantly (p=0.013) younger than unexposed controls (n=22). These subjects were then divided into three groups [high (n=18), low (n=18), and unexposed (n=22)] to ascertain if duration of exposure further influenced age at onset of PD. One-way ANOVA revealed that subjects in the high exposure group were significantly (p=0.0121) younger (mean age: 50.33 years) than unexposed subjects (mean age: 60.45 years). Subjects were also stratified by exposure type (metals vs. pesticides). These results suggest that chronic exposure to metals and pesticides is associated with a younger age at onset of PD among patients with no family history of the disease and that duration of exposure is a factor in the magnitude of this effect.
Postponed effect of neostigmine on oxidative homeostasis
Authors: Pohanka Miroslav 
Published: January 2015

ABSTRACT
Cholinesterases are enzymes able to hydrolyze the neurotransmitter acetylcholine and thus to terminate transmission. Once the enzymes are inhibited, excitotoxicity can appear in the adjacent cells. It is well known that oxidative stress is involved in the toxicity of cholinesterase inhibitors. Commonly, stress follows inhibition of cholinesterases and disappears shortly afterwards. In the present experiment, it was decided to test the impact of an inhibitor, neostigmine, on oxidative stress in BALB/c mice after a longer interval. The animals were sacrificed three days after onset of the experiment and spleens and livers were collected. Reduced glutathione (GSH), glutathione reductase (GR), glutathione S-transferase (GST), thiobarbituric acid reactive substances (TBARS), ferric reducing antioxidant power (FRAP), caspase-3 and activity of acetylcholinesterase (AChE) were assayed. The tested markers were not altered with exceptions of FRAP. The FRAP values indicate accumulation of low molecular weight antioxidants in the examined organs. The role of low molecular weight antioxidants in the toxicity of AChE inhibitors is discussed.
Iron induced genotoxicity: attenuation by vitamin C and its optimization
Authors: Parveen Nuzhat , Ahmad Shoeb , Shadab G.G. Hammad A. 
Published: January 2015

ABSTRACT
Vitamin C (VC) is a well-known antioxidant and strong free radical scavenger. Its antioxidant activity is useful for protection of cellular macromolecules, particularly DNA, from oxidative damage induced by different agents. This study was undertaken to evaluate the optimum level of VC in attenuating the chromosome aberrations (CAs) and DNA damage after iron sulfate (FeSO4) acute administration in Wistar rats. The results exhibited that the increase of CAs and DNA damage induced by FeSO4, 200 mg Fe/kg, could be reduced significantly by VC pretreatment at the dose of 500 mg/kg (p<0.001), but not in the 100 mg/kg group. The findings provide evidence that VC at the dose of 500 mg/kg exerted a possible protective effect against FeSO4 induced CAs and DNA damage. The possible mechanisms of VC may be attributed to its property as a free radical scavenger or to its indirect action in reducing the level of reactive oxygen species (ROS).
Cardiovascular effects of high-fructose intake in rats with nitric oxide deficiency
Authors: Zemančíková Anna , Török Jozef 
Published: January 2015

ABSTRACT
The aim of this study was to evaluate the involvement of nitric oxide (NO) system damage in the deleterious effects of high-fructose intake in rats. Fructose was administered as 10% solution in drinking water to twelve-week-old male Wistar rats for the period of 8 weeks. Blood pressure was measured by tail-cuff plethysmography. After sacrificing the rats at the end of the treatment, relative weights of heart and liver and biochemical parameters in blood plasma were determined. Reactivity of isolated conduit arteries was measured using a force-displacement transducer for recording isometric tension. Fructose drinking rats had increased blood pressure and impaired acetylcholine-induced relaxation of the thoracic aorta in comparison with control rats drinking just tap water. Relative liver weight and plasma concentrations of glucose and triglycerides were also elevated after fructose administration. In a further group of Wistar rats, inhibition of NO production by administration of NG-nitro-L-arginine methyl ester (L-NAME; 40 mg/kg/day) was performed throughout fructose intake. L-NAME treatment itself induces increase in blood pressure and relative heart weight as well as impairment in arterial relaxation and contractility. However, in these rats, fructose administration did not cause further elevation of blood pressure and other abnormalities observed in rats receiving fructose without L-NAME. Our results showed that in the state of NO deficiency (induced by L-NAME administration) fructose does not induce cardiovascular and metabolic alterations which develop in rats with a functional NO system. This indicates that impairment of the NO system may participate in many of the adverse effects induced by high-fructose intake.
A Linear Approach for Parameters Estimation of Multivariable Models in a Parameter Matrix Form
Authors: Efremov A. 
Published: January 2015

Abstract
When a model output is a linear function of the model parameters, the estimation process is significantly simplified, since the optimal estimates can be determined without the usage of a numerical optimization method. Moreover, some types of nonlinear models w.r.t. their parameters can be interpreted as linear (obviously introducing a discrepancy). This is the main premise behind the linear approach for parameter estimation, where the Least Squares (LS) method is used for parameters estimation. As this assumption contradicts with the non-linear parameterized model structure, the estimation process becomes iterative. In spite of this, the linear approach is frequently preferable due to the reduced number of computations, compared with the non-linear approach, where the model is correctly considered as non-linear. Moreover, some issues with the starting point selection, stuck at a local minima, etc., natural for the non-linear approach, are avoided. In this paper estimators are presented, based on the linear approach, for both MIMO linear and non-linear parameterized models in a parameter matrix form. The representatives of the first group are LS and Weighted LS (WLS). For non-linear models, this approach is presented in terms of Extended LS (ELS). The topic regarding the efficient realizations of the estimators is also discussed
Biologically Inspired Feature Detection Using Cascaded Correlations of off and on Channels
Authors: Wiederman Steven D. , O’Carroll David C. 
Published: January 2015

Abstract
Flying insects are valuable animal models for elucidating computational processes underlying visual motion detection. For example, optical flow analysis by wide-field motion processing neurons in the insect visual system has been investigated from both behavioral and physiological perspectives [1]. This has resulted in useful computational models with diverse applications [2,3]. In addition, some insects must also extract the movement of their prey or conspecifics from their environment. Such insects have the ability to detect and interact with small moving targets, even amidst a swarm of others [4,5]. We use electrophysiological techniques to record from small target motion detector (STMD) neurons in the insect brain that are likely to subserve these behaviors. Inspired by such recordings, we previously proposed an ‘elementary’ small target motion detector (ESTMD) model that accounts for the spatial and temporal tuning of such neurons and even their ability to discriminate targets against cluttered surrounds [6-8]. However, other properties such as direction selectivity [9] and response facilitation for objects moving on extended trajectories [10] are not accounted for by this model. We therefore propose here two model variants that cascade an ESTMD model with a traditional motion detection model algorithm, the Hassenstein Reichardt ‘elementary motion detector’ (EMD) [11]. We show that these elaborations maintain the principal attributes of ESTMDs (i.e. spatiotemporal tuning and background clutter rejection) while also capturing the direction selectivity observed in some STMD neurons. By encapsulating the properties of biological STMD neurons we aim to develop computational models that can simulate the remarkable capabilities of insects in target discrimination and pursuit for applications in robotics and artificial vision systems.
Fast FCM with Spatial Neighborhood Information for Brain Mr Image Segmentation
Authors: Biniaz Abbas , Abbasi Ataollah 
Published: January 2015

Abstract
Among different segmentation approaches Fuzzy c-Means clustering (FCM) is a welldeveloped algorithm for medical image segmentation. In emergency medical applications quick convergence of FCM is necessary. On the other hand spatial information is seldom exploited in standard FCM; therefore nuisance factors can simply affect it and cause misclassification. This paper aims to introduce a Fast FCM (FFCM) technique by incorporation of spatial neighborhood information which is exploited by a linear function on fuzzy membership. Applying proposed spatial Fast FCM (sFFCM), elapsed time is decreased and neighborhood spatial information is exploited in FFCM. Moreover, iteration numbers by proposed FFCM/sFFCM techniques are decreased efficiently. The FCM/FFCM techniques are examined on both simulated and real MR images. Furthermore, to considerably decrease of convergence time and iterations number, cluster centroids are initialized by an algorithm. Accuracy of the new approach is same as standard FCM. The quantitative assessments of presented FCM/FFCM techniques are evaluated by conventional validity functions. Experimental results demonstrate that sFFCM techniques efficiently handle noise interference and significantly decrease elapsed time.
Profiling Bell’s Palsy based on House-Brackmann Score
Authors: Song Insu , Vong John , Yen Nguwi Yok , Diederich Joahchim , Yellowlees Peter 
Published: January 2015

Abstract
In this study, we propose to diagnose facial nerve palsy using Support Vector Machines (SVMs) and Emergent Self-Organizing Map (ESOM). This research seeks to analyze facial palsy domain using facial features and grade the degree of nerve damage based on the House-Brackmann score. Traditional diagnostic approaches involve a medical doctor recording a thorough history of a patient and determining the onset of paralysis, rate of progression and so on. The most important step is to assess the degree of voluntary movement of the facial nerves and document the grade of facial paralysis using House- Brackmann score. The significance of the work is the attempt to understand the diagnosis and grading processes using semi-supervised learning with the aim of automating the process. The value of the research is in identifying and documenting the limited literature seen in this area. The use of automated diagnosis and grading greatly reduces the duration of medical examination and increases the consistency, because many palsy images are stored to provide benchmark references for comparative purposes. The proposed automated diagnosis and grading are computationally efficient. This automated process makes it ideal for remote diagnosis and examination of facial palsy. The profiling of a large number of facial images are captured using mobile phones and digital cameras.
Segmentation and Edge Detection Based on Modified ant Colony Optimization for Iris Image Processing
Authors: Biniaz Abbas , Abbasi Ataollah 
Published: January 2015

Abstract
Ant colony optimization (stocktickerACO) is a meta-heuristic algorithm inspired by food searching behavior of real ants. Recently stocktickerACO has been widely used in digital image processing. When artificial ants move in a discrete habitat like an image, they deposit pheromone in their prior position. Simultaneously, vaporizing of pheromone in each iteration step avoids from falling in the local minima trap. Iris recognition because of its great dependability and non-invasion has various applications. simulation results demonstrate stocktickerACO algorithm can effectively extract the iris texture. Also it is not sensitive to nuisance factors. Moreover, stocktickerACO in this research preserves details of the various synthetic and real images. Performance of ACO in iris segmentation is compared with operation of traditional approaches such as canny, robert, and sobel edge detections. Experimental results reveal high quality and quite promising of stocktickerACO to segment images with irregular and complex structures.
Parallel Pbil Applied to Power System Controller Design
Authors: Folly Komla 
Published: January 2015

Abstract
Population-Based Incremental Learning (PBIL) algorithm is a combination of evolutionary optimization and competitive learning derived from artificial neural networks. PBIL has recently received increasing attention in various engineering fields due to its effectiveness, easy implementation and robustness. Despite these strengths, it was reported in the last few years that PBIL suffers from issues of loss of diversity in the population. To deal with this shortcoming, this paper uses parallel PBIL based on multi-population. In parallel PBIL, two populations are used where both probability vectors (PVs) are initialized to 0.5. It is believed that by introducing two populations, the diversity in the population can be increased and better results can be obtained. The approach is applied to power system controller design. Simulations results show that the parallel PBIL approach performs better than the standard PBIL and is as effective as another diversity increasing PBIL called adaptive PBIL
A Survey of old and New Results for the Test Error Estimation of a Classifier
Authors: Anguita Davide , Ghelardoni Luca , Ghio Alessandro , Ridella Sandro 
Published: January 2015

Abstract
The estimation of the generalization error of a trained classifier by means of a test set is one of the oldest problems in pattern recognition and machine learning. Despite this problem has been addressed for several decades, it seems that the last word has not been written yet, because new proposals continue to appear in the literature. Our objective is to survey and compare old and new techniques, in terms of quality of the estimation, easiness of use, and rigorousness of the approach, so to understand if the new proposals represent an effective improvement on old ones.
B-Tree Algorithm Complexity Analysis to Evaluate the Feasibility of its Application in the University Course Timetabling Problem
Authors: Cruz Chvez Marco Antonio , Martnez Oropeza Alina 
Published: January 2015

Abstract
This paper presents a comparative analysis of complexity between the B-TREE and the Binary Search Algorithms, both theoretically and experimentally, to evaluate their efficiency in finding overlap of classes for students and teachers in the University Course Timetabling Problem (UCTP). According to the theory, B-TREE Search complexity is lower than Binary Search. The performed experimental tests showed the B-TREE Search Algorithm is more efficient than Binary Search, but only using a dataset larger than 75 students per classroom.
Dimensionality Reduction of Dynamic Mesh Animations Using HO-SVD
Authors: Romaszewski Michał , Gawron Piotr , Opozda Sebastian 
Published: January 2015

Abstract
This work presents an analysis of Higher Order Singular Value Decomposition (HOSVD) applied to reduction of dimensionality of 3D mesh animations. Compression error is measured using three metrics (MSE, Hausdorff, MSDM). Results are compared with a method based on Principal Component Analysis (PCA) and presented on a set of animations with typical mesh deformations.
Estimation of Engine Intake Air Mass Flow using a generic Speed-Density method
Authors: Vojtíšek Michal , Kotek Martin 
Published: January 2015

SHRNUTÍ
Měření výfukových emisí spalovacích motorů během reálného provozu přenosnými zařízeními umístěnými na palubě vozidla (PEMS) je důležitou součástí hodnocení dopadu nových paliv a technologií na životní prostředí a lidské zdraví. Znalost aktuálního toku výfukových plynů je jedním z nezbytných předpokladů pro takové provozní měření. Jedním z nejjednodušších způsobů je výpočet z toku nasáveného vzduchu, který je vypočten z měřených otáček motoru a tlaku a teploty náplně v sacím potrubí. V této práci byl obecný algoritmus využívající odhad dopravní účinnosti libovolného běžného čtyřdobého motoru aplikován na tři produkční evropské motory běžně využívané v ČR: těžký a automobilový přeplňovaný vznětový motor, a atmosférický zážehový motor. Vypočtené průtoky nasávaného vzduchu byly porovnány s různými referenčními metodami. Výsledky ukazují, že nejistota stanovení toku nasáveného vzduchu obecným algoritmem je v řádu 10% pro většinu provozních režimů motoru, kromě případů recirkulace velké části výfukových plynů, kdy nejistota vzrůstá na desítky procent. Desetiprocentní nejistota pro motory bez vysoké míry recirkulace výfukových plynů je přijatelná pro mnohá, zvláště průzkumná a orientační, měření emisí za provozu, a může být snížena kalibrací algoritmu pro daný motor.
Creating a common symbol classification for a new historical geoportal of Poland
Authors: Panecki Tomasz 
Published: January 2015

Abstract
The crowd-sourcing approach should be implemented into a new historical geoportal of Poland due to its increasing potential in WebGIS. Registered users will be able to acquire spatial data from various map series. As it requires feature class harmonization, a common symbol classification should be proposed. It will be based on chosen topographic maps of Polish land from the 19th and 20th centuries. Feature classes derived from archival maps will be standardized and reclassified, but with no information lost. This will be done in four steps which require: data acquisition, map content harmonization, feature class typification and attribute table elaboration. In addition, four methods of data harmonization can be distinguished: symbol sequence, semantic analogies, spatial relations and a combined method. The paper covers the elaboration of two thematic layers - roads and railways based on three topographic maps (Austrian 1:75 000, German 1:100 000, Russian 1: 126 000).
The Warsaw soundscape - structure and specifics
Authors: Romanowska Małgorzata 
Published: January 2015

Abstract
The Warsaw soundscape has been examined according to the principles of acoustic ecology. The soundscape is the acoustic environment tested primarily by qualitative research. Warsaw residents were asked in a survey about their sound impressions and requirements for the Warsaw soundscape. The aim of this research was to learn both the conditions of acoustic environment and the needs of space users in accordance with the space category. The present and expected sound structures of five different categories of space were examined (residential areas, streets, city centre, tourist areas and green areas). Information on both the specific Warsaw sounds and the ideas for new sounds (which could be introduced into the city) was collected.
Thermal seasons in Warsaw during the period 1961-2013
Authors: Majewski Grzegorz , Przewoźniczuk Wiesława 
Published: January 2015

Abstract
This study determines the approximate duration of the thermal seasons in Warsaw, and investigates their long-term variability. The measurement data come from the Ursynów meteorological station at the Warsaw University of Life Sciences (WULS) (λE 21°02’52’’, φN 52°09’38’’, 102.5 m a.s.l.), situated in the south of Warsaw, and comprise mean diurnal air temperatures for the years 1961-2013. In order to identify thermal seasons, the method of five-day rolling averages was applied, which revealed a substantial year-by-year variability. The achieved results were close to those found by other methods for stations situated within the same climatic region. Over the analysed period, winters and springs have become shorter, whereas the other two seasons have become longer. Nevertheless, the positive trend was only statistically significant for thermal summers. The increasing length of the thermal summer in Warsaw Ursynów may be due to the influence of urban heat islands in built-up areas.
Measurement Uncertainty Evaluation Method Considering Correlation and its Application to Precision Centrifuge
Authors: Ling Mingxiang , Li Huimin , Li Qisheng 
Published: January 2015

Abstract
Measurement uncertainty evaluation based on the Monte Carlo method (MCM) with the assumption that all uncertainty sources are independent is common. For some measure problems, however, the correlation between input quantities is of great importance and even essential. The purpose of this paper is to provide an uncertainty evaluation method based on MCM that can handle correlated cases, especially for measurement in which uncertainty sources are correlated and submit to non-Gaussian distribution. In this method, a linear-nonlinear transformation technique was developed to generate correlated random variables sampling sequences with target prescribed marginal probability distribution and correlation coefficients. Measurement of the arm stretch of a precision centrifuge of 10-6 order was implemented by a high precision approach and associated uncertainty evaluation was carried out using the mentioned method and the method proposed in the Guide to the Expression of Uncertainty in Measurement (GUM). The obtained results were compared and discussed at last.
On the Implications of Knowledge Bases for Regional Innovation Policies in Germany
Authors: Hassink Robert , Plum Oliver , Rickmers Arne 
Published: January 2015

Abstract
Regional innovation policies have been criticised for being too standardised, one-size-fits-all and place-neutral in character. Embedded in these debates, this paper has two aims: first, to analyse whether industries with different knowledge bases in regions in Germany have different needs for regional innovation policies, and secondly, to investigate whether knowledge bases can contribute to the fine-tuning of regional innovation policies in particular and to a modern, tailor-made, place-based regional innovation policy in general. It concludes that although needs differ due to differences in knowledge bases, those bases are useful only to a limited extent in fine-tuning regional innovation policies