In vitro antioxidant capacity of honeybee-collected pollen of selected floral origin harvested from Romania

Total phenolic phytochemical concentration was measured in 12 honeybee-collected pollens of selected floral species as well as their antioxidant capacity. The content of total polyphenols was measured spectrophotometrically using the Folin–Ciocalteu reagent with gallic acid as standard. The antioxidant properties were evaluated by 2,2-diphenyl-picrylhydrazyl radical scavenging capacity (DPPH) assay, Trolox equivalent antioxidant Capacity procedure and Ferric ion reducing antioxidant power assay. A great variability regarding the correspondence between the antioxidant activity and the content of total polyphenols of honeybee-collected pollens with different botanical origin was found. Antioxidant activities were different for each floral species and were not clearly associated to their total phenolic content.     

Forward electric field calculation using BEM for time-varying magnetic field gradients and motion in strong static fields

A boundary element method for evaluating the electric fields induced in conducting bodies exposed to magnetic fields varying at low frequency has been developed and applied to sources of magnetic field variation that are of relevance in magnetic resonance imaging. An integral formulation based on constant boundary elements which can be used to study the effects of both temporally varying magnetic field gradients and rigid body movement in a static magnetic field is presented. The validity of this approach has been demonstrated for simple geometries with known analytical solutions and it has also been applied to the evaluation of the induced fields in more realistic models of the human head.     

Assessment of the cleaning effect of HF cold plasma by statistical processing of photographic image

The assessment of cultural heritage objects cleaning by HF cold plasma treatment is hard to quantify. One method is based on direct comparison of photographic images acquired before and after treatment, a subjective evaluation, depending on the rigor and visual accuracy of the observer.     

Metals migration between product and metallic package in canned meat

The aim of this study is to investigate the migration of heavy metals in meat can under different parameters (varnish, storage time, storage temperature, storage humidity and varnish width and porosity). The physicochemical and organoleptic properties of the meat can have been analyzed. The metal content (Cd, Pb, Cu, Fe, Zn and Sn) were determined by flame and graphite furnace atomic absorption spectrometry after microwave digestion. The organoleptic and physicochemical properties of the samples have not modified significantly during the experiments. The metals migration is not influenced significantly by the varnish type. The highest level of metals in food products was observed at 4 and 50 °C. The porosity influenced significantly (p < 0.05) the migration of metals while the varnish width influence is not a significant one. The migration modeling using 3rd grade polynomial model achieved models with high coefficients of regression (greater than 0.9858).     

Stable Boundary and Internal Data Reconstruction in Two-Dimensional Anisotropic Heat Conduction Cauchy Problems Using Relaxation Procedures for an Iterative MFS Algorithm

We investigate two algorithms involving the relaxation of either the given boundary temperatures (Dirichlet data) or the prescribed normal heat fluxes (Neumann data) on the over-specified boundary in the case of the iterative algorithm of Kozlov91 applied to Cauchy problems for two-dimensional steady-state anisotropic heat conduction (the Laplace-Beltrami equation). The two mixed, well-posed and direct problems corresponding to every iteration of the numerical procedure are solved using the method of fundamental solutions (MFS), in conjunction with the Tikhonov regularization method. For each direct problem considered, the optimal value of the regularization parameter is chosen according to the generalized cross-validation (GCV) criterion. The iterative MFS algorithms with relaxation are tested for over-, equally and under-determined Cauchy problems associated with the steady-state anisotropic heat conduction in various two-dimensional geometries to confirm the numerical convergence, stability, accuracy and computational efficiency of the method.     

Boundary reconstruction in two-dimensional steady state anisotropic heat conduction using a regularized meshless method

We study the stable numerical identification of an unknown portion of the boundary on which either a Dirichlet or a Robin boundary condition is provided, while additional Cauchy data are given on the remaining known part of the boundary of a two-dimensional domain, in the case of steady state anisotropic heat conduction problems. This inverse geometric problem is solved using the method of fundamental solutions (MFS) in conjunction with the Tikhonov regularization method [53]. The optimal value for the regularization parameter is chosen according to Hansen’s L-curve criterion [17]. The stability, convergence, accuracy and efficiency of the proposed method are investigated by considering several examples in both smooth and piecewise smooth geometries.     

The Supervised Network Self-Organizing Map for Classification of Large Data Sets

Complex application domains involve difficult pattern classification problems. The state space of these problems consists of regions that lie near class separation boundaries and require the construction of complex discriminants while for the rest regions the classification task is significantly simpler. The motivation for developing the Supervised Network Self-Organizing Map (SNet-SOM) model is to exploit this fact for designing computationally effective solutions. Specifically, the SNet-SOM utilizes unsupervised learning for classifying at the simple regions and supervised learning for the difficult ones in a two stage learning process. The unsupervised learning approach is based on the Self-Organizing Map (SOM) of Kohonen. The basic SOM is modified with a dynamic node insertion/deletion process controlled with an entropy based criterion that allows an adaptive extension of the SOM. This extension proceeds until the total number of training patterns that are mapped to neurons with high entropy (and therefore with ambiguous classification) reduces to a size manageable numerically with a capable supervised model. The second learning phase (the supervised training) has the objective of constructing better decision boundaries at the ambiguous regions. At this phase, a special supervised network is trained for the computationally reduced task of performing the classification at the ambiguous regions only. The performance of the SNet-SOM has been evaluated on both synthetic data and on an ischemia detection application with data extracted from the European ST-T database. In all cases, the utilization of SNet-SOM with supervised learning based on both Radial Basis Functions and Support Vector Machines has improved the results significantly related to those obtained with the unsupervised SOM and has enhanced the scalability of the supervised learning schemes. The highly disciplined design of the generalization performance of the Support Vector Machine allows to design the proper model for the particular training set.     

Relaxation of Alternating Iterative Algorithms for the Cauchy Problem Associated with the Modified Helmholtz Equation

We propose two algorithms involving the relaxation of either the given Dirichlet data or the prescribed Neumann data on the over-specified boundary, in the case of the alternating iterative algorithm of Kozlov, Maz'ya and Fomin(1991) applied to Cauchy problems for the modified Helmholtz equation. A convergence proof of these relaxation methods is given, along with a stopping criterion. The numerical results obtained using these procedures, in conjunction with the boundary element method (BEM), show the numerical stability, convergence, consistency and computational efficiency of the proposed methods.     

Regularized MFS-Based Boundary Identification in Two-Dimensional Helmholtz-Type Equations

We study the stable numerical identification of an unknown portion of the boundary on which a given boundary condition is provided and additional Cauchy data are given on the remaining known portion of the boundary of a two-dimensional domain for problems governed by either the Helmholtz or the modified Helmholtz equation. This inverse geometric problem is solved using the method of fundamental solutions (MFS) in conjunction with the Tikhonov regularization method. The optimal value for the regularization parameter is chosen according to Hansen's L-curve criterion. The stability, convergence, accuracy and efficiency of the proposed method are investigated by considering several examples.     

Circulating RNA Molecules as Biomarkers in Liver Disease

Liver disease is a major cause of morbidity and mortality worldwide. As in other fields of medicine, there is a stringent need for non-invasive markers to improve patient diagnostics, monitoring and prognostic ability in liver pathology. Cell-free circulating RNA molecules have been recently acknowledged as an important source of potential medical biomarkers. However, many aspects related to the biology of these molecules remain to be elucidated. In this review, we summarize current concepts related to the origin, transportation and possible functions of cell-free RNA. We outline current development of extracellular RNA-based biomarkers in the main forms of non-inherited liver disease: chronic viral hepatitis, hepatocellular carcinoma, non-alcoholic fatty liver, hepato-toxicity, and liver transplantation. Despite recent technological advances, the lack of standardization in the assessment of these markers makes their adoption into clinical practice difficult. We thus finally review the main factors influencing quantification of circulating RNA. These factors should be considered in the reporting and interpretation of current findings, as well as in the proper planning of future studies, to improve reliability and reproducibility of results.