162 research outputs found
Neurophysiological correlates of semantic processing in perception of atypical objects
Препознавање објеката и визуелна категоризација се у оквиру свакодневног искуства доживљавају као наизглед врло лаки задаци који се обављају изузетно брзо и без пуно промишљања. Претходна истраживања указују да ефекат типичности у знатној мери утиче на процес категоризације, при чему се типични представници неког концепта лакше и брже категоризују од атипичних. Предмет ове студије представља испитивање процеса класификације визуелно приказаних атипичних објеката, са циљем детаљнијег увида у утицај семантичке обраде. У те сврхе спроведена су три експеримента током којих су испитаницима снимани потенцијали у вези са догађајем (ERP). Користећи задатак именовања слика, истражено је на који начин се обрађују и класификују атипични објекти, док су на основу задатака диференцијације и верификације формирани P300 и N400 профили који су упоређени са профилом задатка именовања. Добијени резултати указују да, за разлику од претходних ERP истраживања атипичних објеката, у задатку именовања нису идентификоване P300 и N400 компоненте у временском опсегу и на локацијама обично навођеним у литератури. Међутим, значајне разлике између типичних и атипичних објеката су пронађене у оквиру неколико раних и средњих временских прозора који одговарају постериорном N1, централнoм P2, антериорном и постериорном N2 таласу. Такође, разлике су биле присутне и латерално у средњем временском опсегу, уз међусобно супротан образац разлика у зависности од хемисфере. ERP подаци сугеришу да диференцијација између типичних и атипичних објеката започиње врло рано, око 120 милисекунди након излагања стимулуса и завршава се оквирно око 500 милисекунди након излагања стимулуса. Анализа ERP компоненти указује да се процес класификације ослања на неки вид имплицитног додељивања ознака мете и стандардног стимулуса/дистрактора, при чему је удео процеса одозго на доле, односно семантичке обраде, сведен на најмању могућу меру довољну за успешно извршење задатка.Object recognition and visual categorization are perceived as seemingly effortless tasks in everyday experience that are performed extremely quickly and without much thought. Previous research indicates that the typicality effect significantly affects the process of categorization, whereby typical members of a concept are easier and faster categorized than atypical ones. The subject of this study is an examination of the classification process of visually presented atypical objects, with the aim of a more detailed insight into semantic processing influence. For these purposes, three experiments were conducted during which event-related potentials (ERPs) were recorded. Atypical objects processing and classification was investigated using the picture naming task, while the differentiation and verification tasks were used to form P300 and N400 profiles that were compared with the naming task profile. In contrast to previous ERP studies of atypical objects, the picture naming task did not produce P300 and N400 components in the time range and locations usually reported in the literature. However, significant differences between typical and atypical objects were found within several early and mid-latency time windows corresponding to the posterior N1, central P2, anterior and posterior N2 waves. Differences were also present laterally in the mid-latency time range, consisting of opposite patterns of differences depending on the hemisphere. ERP data suggest that the differentiation between typical and atypical objects begins very early, about 120 milliseconds after stimulus presentation, and ends approximately 500 milliseconds after stimulus presentation. The analysis of ERP components indicates that the classification process relies on some kind of implicit label assignment of target and standard stimulus/distractor, whereby the amount of the top-down processes, ie semantic processing, is reduced to the smallest possible extent sufficient for the successful completion of the task
Franck-Condon factors and observed band strength distribution in the vibrational structure of the Ag_2 D-X band system
Potential curves for the X_1Σ_g^+ and D_1Σ_u^+ states of three diatomic silver isotopomers, ^(107)Ag_2, ^(107)Ag^(109)Ag and ^(109)Ag_2, were determined from the best available molecular constants by the Rydberg-Klein-Rees method. From these potentials, Franck-Condon factors and band-origin wave numbers were computed, and the reliability of the obtained values was verified by comparison with the observed band strength distribution and the measured band origin positions in a previously recorded D-X spectrum. The ratios of the Franck-Condon factors to those of corresponding isotopic bands were found to be very close to unity, revealing only a very small isotopic effect on the Franck Condon factors of Ag_2 D-X bands. The isotopic shifts of the calculated band origins agree well with previously measured displacements of band heads
Uloga različitih preparata gvožđa u sprečavanju trkačke anemije konja
The hypothesis that a high hematocrit value and high hemoglobin concentration are the most important conditions which have to be fulfilled in order to achieve top racing results has resulted in a massive use of iron preparations in healthy horses. This specially implies in racing horses during intensive training aiming at the prevention of the so-called racing anemia. By studying the effects of the most commonly used iron preparations in Serbia and Montenegro (Fedex®, as the representative of dextrane iron preparations; Hippirion® as a well known representative of iron complexed to saccharate and Hemo® 15 which is a representative of complex iron preparations which contain other hemantics) the expected changes in erythrocyte count, hemoglobin concentration and hematocrit value were recorded. However, the recorded changes in hematological values did differ between used iron preparations. The best effects were exhibited by Hemo®15, the application of which resulted in a prompt and significant increase in erythrocyte count, MCH, MCHC and hemoglobin concentration.Hipoteza da je za postizanje vrhunskih rezultata na trkama najvažniji preduslov visoka koncentracija hemoglobina i vrednost hematokrita, dovela je do masovne primene različitih preparata za podsticanje hematopoeze kod zdravih konja. Ovo se pre svega odnosi na konje u treningu, u cilju preveniranja takozvanih trkačkih anemija. U ovom radu su spitivanjem uticaja tri najčešće korišćena preparata gvožđa kod trkačkih konja u našoj zemlji (Fedex kao predstavnik dekstranskih preparata gvožđa, Hippiron kao najpoznatiji predstavnik gvožđa u kompleksu sa saharatom i Hemo 15 koji je predstavnik kompleksnih preparata koji uz gvožđe sadrže i druge hematinike) utvrđene očekivane promene u broju eritrocita, koncentraciji hemoglobina i hematokritskoj vrednosti. Primena sva tri preparata gvožđa dovela je do povećanja vrednosti svih ispitivanih hematoloških parametara kod trkačkih konja. Najbolji efekat ispoljio je preparat Hemo 15 čija je primena dovela do najvećeg povećanja broja eritrocita, MCH, MCHC i koncentracije hemoglobina, a i sam efekat je nastajao najbrže
The influence of carbon black on curing kinetics and thermal aging of acrylonitrile–butadiene rubber
Elastomers based on a copolymer of butadiene and acrylonitrile (NBR) have excellent oil resistance but are very sensitive for degradation at very high temperatures. The aim of this applicative contribution was to determine the effect of high abrasion furnace carbon black with primary particle size 46 nm on aging properties of elastomeric materials based on NBR as network precursor. The curing kinetics was determined using the rheometer with an oscillating disk, in which the network formation process is registered by the torque variation during time. The vulcanizates were obtained in a hydraulic press at 150 °C. The mechanical properties of elastomeric composites were determined before and after thermal aging in an air circulating oven. The reinforcing effect of the filler particles was assessed according to mechanical properties before and after aging
General procedures in diagnosis of malignant diseases in dogs and cats
Tumors occur in all domestic and wild animals. They are most often diagnosed
in dogs and cats, and their numbers increase from year to year. In the recent
years, cancer is believed to be the most frequent cause of pet deaths. A
speedy and reliable diagnosis is of paramount importance because it enables
the veterinarian to begin therapy and make a prognosis. The objective of an
early diagnosis is to enable the detection of neoplastic diseases before the
tumor spreads throughout the organism, consequently enabling the timely
administration of therapy and providing greater chances for curing the
animal. A tumor is diagnosed on the grounds of the anamnesis, clinical
picture, and special diagnostic procedures. The most frequently applied
diagnostic procedures are laboratory diagnostics, cytology, biopsy and
pathohistology, imaging diagnostics (roentgenography and roentgenoscopy,
ultrasound diagnostics, endoscopy, computer tomography, magnetic resonance,
and scintigraphy) and molecular diagnostics. Each of these methods has its
advantages and faults in connection with costs, availability, sensitivity,
specificity and quality of anatomic vs functional pictures. Every one of
these techniques has its own field of implementation and each one provides
different and additional information in connection with the nature and
position of the primary lesion and the presence of metastases
The effect of y-irradiation on thermal stability urea-formaldenyde resin with TiO2 and furfuryl alcohole
The thermal stability of organic-inorganic nano-composites prepared by a twostage polymerization of urea-formaldehyde resin (UF) with furfuryl alcohol (FA)
and TiO2 before and after irradiation has been investigated. The two resins of ureaformaldehyde–TiO2 composites, namely: Resin 1 (UF+TiO2) and Resin 2 (UF +
TiO2 + FA), were synthesized. The thermal stability of obtained materials was
studied by non-isothermal thermo-gravimetric analysis (TG), differential thermal
gravimetry (DTG) and differential thermal analysis (DTA). UF hybrid composites
have been irradiated (50 kGy) and after that their radiation stability was evaluated
on the basis of thermal behavior. The free formaldehyde percentage in all prepared
samples was determined. DTG peaks of both UF resin are shifted to a higher
temperature after irradiation. The minimum percentage values of free
formaldehyde (4% and 3%) for Resin 1 and Resin 2, respectively, after irradiation
dose of 50 kGy are detected.Physical chemistry 2012 : 11th international conference on fundamental and applied aspects of physical chemistry; Belgrade (Serbia); 24-28 September 201
A Matlab/Simulink 3D Model of Metal Rings and Discs for Ultrasonic Sandwich Transducer Design
Metal-endings are integral part of different ultrasonic sandwich transducers. In this paper a new Matlab/Simulink 3D model of of the finite metal rings and discs of various dimensions is realized. With this model, which describes both the thickness and the radial resonant modes, and the coupling between them, mechanical impedance of the sample can be easily computed. Resonance frequency-length curves for rings and disks with various materials and for different selected dimensions are given. Also, comparisons of the different approaches in determining of their resonant frequencies are shown. The proposed Matlab/Simulink model requires simpler implementation than other analytical models. That enabled modifying of 1D theory and simplified modelling and projecting of the ultrasonic sandwich transducers with short-endings. Finally, the computed and experimental results are compared
The High-Energy Irradiation Ageing of Reinforced Elastomers Based on Rubber Blends
Elastomers are very often used in severe environments, for instance, in nuclear power plants, where they may be degraded by high-energy radiation and heat. The ageing behaviour of materials used in different equipments is very important. Elastomers based on chlorosulfonated polyethylene (CSM) are used for cable jacketing materials and have excellent radiation resistance needed in nuclear power stations. In the current work, the influence of gamma-irradiation dose (100, 200 and 400 kGy) on the ageing of reinforced blends based on CSM, styrene butadiene rubber (SBR) and natural rubber (NR) has been evaluated. The content of silica in CSM/SBR and CSM/NR rubber blends was varied. The curing behavior of compounds was estimated using the oscillating disk reometer. The irradiation of nano composites has been performed in air in the Co 60 radiation sterilization unit with the dose rate of 10 kGy h(-1). The thermal properties were studied by thermogravimetric test. The mechanical properties (hardness, modulus at 100% elongation, tensile strength and elongation at break) were determined before and after irradiation. A decrease in the elastic modulus and in the strain at break has been observed with increasing irradiation. At higher doses, the network chain scissions become the main degradation process, the cross-linked topology becomes irregular, and material contains more and more weak zones, which deteriorate the ultimate properties.4th International Conference on Radiation and Applications in Various Fields of Research (RAD), Proceedings, May 23-27, 2016, Nis, Serbi
Support vector machine for the prediction of heating energy use
Prediction of a building energy use for heating is very important for adequate energy planning. In this paper the daily district heating use of one university campus was predicted using the support vector machine model. Support vector machine is the artificial intelligence method that has recently proved that it can achieve comparable, or even better prediction results than the much more used artificial neural networks. The proposed model was trained and tested on the real, measured data. The model accuracy was compared with the results of the previously published models (various neural networks and their ensembles) on the same database. The results showed that the support vector machine model can achieve better results than the individual neural networks, but also better than the conventional and multistage ensembles. It is expected that this theoretically well-known methodology finds wider application, especially in prediction tasks
Hybrid artificial intelligence model for prediction of heating energy use
Currently, in the building sector there is an increase in energy use due to the increased demand for indoor thermal comfort. Proper energy planning based on a real measurement data is a necessity. In this study we developed and evaluated hybrid artificial intelligence models for the prediction of the daily heating energy use. Building energy use is defined by significant number of influencing factors, while many of them are difficult to adequately quantify. For heating energy use modelling, the complex relationship between the input and output variables is hard to define. The main idea of this paper was to divide the heat demand prediction problem into the linear and the non-linear part (residuals) by using (Afferent statistical methods for the prediction. The expectations were that the joint hybrid model, could outperform the individual predictors. Multiple linear regression was selected for the linear modelling, while the non-linear part was predicted using feedforward and radial basis neural networks. The hybrid model prediction consisted of the sum of the outputs of the linear and the non-linear model. The results showed that both hybrid models achieved better results than each of the individual feedforward and radial basis neural networks and multiple linear regression on the same dataset. It was shown that this hybrid approach improved the accuracy of artificial intelligence models
- …