Effect of data scaling on color device model fitting

Output devices in print production can be characterized by different characterization methods. One commonly used method of color device characterization is least squares fitting. In essence, the least squares fitting is used to determine the coefficients of a predetermined polynomial, such that the sum of squared differences between the values predicted by the model and the empirical data is minimal. The choice of the polynomial order and the cross product terms which best describe the behavior of a certain device is not obvious. This paper is a part of a larger study which investigates the criteria in the measurement data which can be used for optimal model selection. The part of the study covered in this paper addresses the data over fitting problem. It is investigated by comparing the performance of models of different polynomial orders on two different domains.Peer Reviewe

Through the labyrinth of yesteryears

Background Allergy to dog (Canis familiaris) is a worldwide common cause of asthma and allergic rhinitis. However, dander extract in routine diagnostics is not an optimal predictor of IgE-mediated dog allergy. Our objective was to evaluate saliva as an allergen source for improved diagnostics of allergy to dog. Methods IgE-binding proteins in dog saliva and dander extract were analysed by immunoblot and mass spectrometry (LC-MS/MS) using pooled or individual sera from dog-allergic patients (n=13). Sera from 59 patients IgE positive to dander and 55 patients IgE negative to dander but with symptoms to dog were analysed for IgE against saliva and dander by ELISA. Basophil stimulation with dog saliva and dander extract was measured by flow cytometry among three dog-allergic patients. Additionally, IgE-binding protein profiles of saliva from different breeds were investigated by immunoblot. Results Greater number and diversity of IgE-binding proteins was found in saliva compared to dander extract and varied among dog breeds. In saliva, Can f 1, 2, 3 and 6 were identified but also four new saliva allergen candidates. The majority of the 59 dog danderpositive sera (n=44) were IgE positive to dog saliva. Among patients IgE negative to dander, but with symptoms to dog, 20% were IgE positive to saliva. The biological activity of saliva was confirmed by basophil degranulation. Conclusions Dog saliva is an allergen source for improved diagnostics of dog allergy. The IgE-binding protein profile of saliva from different dogs varies.Supplementary material: [http://cherry.chem.bg.ac.rs/handle/123456789/3488

Factors influencing gastrointestinal tract and microbiota immune interaction in preterm infants

The role of microbial colonization is indispensable for keeping a balanced immune response in life. However, the events that regulate the establishment of the microbiota, their timing, and the way in which they interact with the host are not yet fully understood. Factors such as gestational age, mode of delivery, environment, hygienic measures, and diet influence the establishment of microbiota in the perinatal period. Environmental microbes constitute the most important group of exogenous stimuli in this critical time frame. However, the settlement of a stable gut microbiota in preterm infants is delayed compared to term infants. Preterm infants have an immature gastrointestinal tract and immune system which predisposes to infectious morbidity. Neonatal microbial dynamics and alterations in early gut microbiota may precede and/or predispose to diseases such as necrotizing enterocolitis (NEC), late-onset sepsis or others. During this critical period, nutrition is the principal contributor for immunological and metabolic development, and microbiological programming. Breast milk is a known source of molecules that act synergistically to protect the gut barrier and enhance the maturation of the gut-related immune response. Host-microbe interactions in preterm infants and the protective role of diet focused on breast milk impact are beginning to be unveiled.M.C. acknowledges a “Rio Hortega” Research Fellowship Grant (CM13/0017) and M.V. acknowledges grants PI11/0313 and RD12/0026/0012 (Red SAMID) from the Instituto Carlos III (Spanish Ministry of Economy and Competitivity). M.C.C. and G.P-M. were supported by the grant AGL2013-47420-R from the Spanish Ministry of Science and Innovation.Peer reviewe

Numerical simulation of friction stir welding

Friction stir welding is a solid-state welding technique that utilizes thermo-mechanical influence of the rotating welding tool on parent material resulting with monolith joint-weld. On the contact of welding tool and parent material, significant stirring and deformation of parent material appears, and during this process mechanical energy is partially transformed into heat. The paper describes the software for the numerical simulation of friction stir welding developed at Mechanical Engineering Faculty, University of Nis. Numerical solution for estimation of welding plates temperature is estimated using finite difference method-explicit scheme with adaptive grid, considering influence of temperature on material's conductivity, contact conditions between welding tool and parent material, material flow around welding tool etc. The calculated results are in good agreement with the experimental results. [Projekat Ministarstva nauke Republike Srbije, br. TR35034: The research of modern non-conventional technologies application in manufacturing companies with the aim of increase efficiency of use, product quality, reduce of costs and save energy and materials

Effect of data scaling on color device model fitting

Output devices in print production can be characterized by different characterization methods. One commonly used method of color device characterization is least squares fitting. In essence, the least squares fitting is used to determine the coefficients of a predetermined polynomial, such that the sum of squared differences between the values predicted by the model and the empirical data is minimal. The choice of the polynomial order and the cross product terms which best describe the behavior of a certain device is not obvious. This paper is a part of a larger study which investigates the criteria in the measurement data which can be used for optimal model selection. The part of the study covered in this paper addresses the data over fitting problem. It is investigated by comparing the performance of models of different polynomial orders on two different domains.Peer Reviewe

Effect of data scaling on color device model fitting

Output devices in print production can be characterized by different characterization methods. One commonly used method of color device characterization is least squares fitting. In essence, the least squares fitting is used to determine the coefficients of a predetermined polynomial, such that the sum of squared differences between the values predicted by the model and the empirical data is minimal. The choice of the polynomial order and the cross product terms which best describe the behavior of a certain device is not obvious. This paper is a part of a larger study which investigates the criteria in the measurement data which can be used for optimal model selection. The part of the study covered in this paper addresses the data over fitting problem. It is investigated by comparing the performance of models of different polynomial orders on two different domains