Characterization,in vitro bioactivity and biological studies of sol-gel-derived TiO2 substituted 58S bioactive glass

Bioactive glasses (BGs) have been used for bone formation and bone repair processes in recent years. This study investigated the titanium substitution effect on 58S BGs (Ti-BGs) 60SiO₂-(36 − X)CaO-4P₂O₅-XTiO₂ (X = 0, 3, and 5 mol.%) prepared by the sol-gel technique, and the main goal was to find the optimum amount of titanium in Ti-BGs. Synthesized BGs, which were investigated after immersion in simulated body fluid (SBF), were tested by X-ray diffraction (XRD) analysis, Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy. Moreover alkaline phosphate (ALP) activity, 3-(4,5dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, and antibacterial studies were employed to investigate the biological properties of Ti-BGs. According to the FTIR and XRD test results, hydroxyapatite (HA) formation on Ti-BGs surfaces was confirmed. Meanwhile, the presence of 5 mol.% compared to 3 mol.% increased the HA grain distribution and their size on the Ti-BGs surface. Additionally, MTT and ALP results confirmed that the optimal amount of titanium substitution in BG was 5 mol.%. Since 5 mol.% Ti incorporated BG (BG-5) had the highest biocompatibility level, antibacterial properties, maximum cell proliferation, and ALP activity among the synthesized Ti-BGs, it is presented as the best candidate for further in vivo investigations.     

Modified Mechanical Coating Technique for the Preparation of Nanohydroxyapatite Coated Ti–6Al–4V Dental Implants

Protection of Metals and Physical Chemistry of Surfaces - To improve the mechanical and biological properties and also to increase the lifetime and performance of Ti–6Al–4V dental...     

Berechnung der Wirbelstromdichten und-kräfte in der Umgebung großer supraleitender Spulen für den magnetischen Einschluß bei der Kernfusion

Übersicht Um die Betriebssicherheit großer supraleitender Magnetsysteme für die Kernfusionsforschung zu gewährleisten, muß die im Magnetsystem gespeicherte Energie schnell entladen werden können. Durch die veränderlichen großvolumigen Magnetfelder werden in benachbarten leitfähigen Strukturen durch Induktion hohe Wirbelströme hervorgerufen. Durch sie treten dort elektromagnetische Kräfte. auf, die einzelne Komponenten mechanisch überlasten können. Zur Berechnung dieser Kräfte wurde eine einfache numerischanalytische Methode entwickelt, die im folgenden vorgestellt und mit Finite-Elemente-Verfahren verglichen wird.

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Calculation of eddy current densities and forces around large superconducting coils for nuclear fusion

Contents The reliable operation of the superconducting magnet systems used for the magnetic confinement in nuclear fusion research requires the ability of a fast discharge of the stored magnetic energy. The corresponding magnetic field variation gives rise to high eddy currents by inductive coupling with surrounding conductive components. The eddy current forces can lead to a mechanical overload of some of these components. A simple numerical-analytical method was developed in order to calculate these forces. This method is presented and compared with the Finite Element Method.

     

A note on the Consecutive Ones Submatrix problem

A binary matrix has the Consecutive Ones Property (C1P) for columns if there exists a permutation of its rows that leaves the 1's consecutive in every column. The problem of Consecutive Ones Property for a matrix is a special variant of Consecutive Ones Submatrix problem in which a positive integer K is given and we want to know if there exists a submatrix B of A consisting of K columns of A with C1P property. This paper presents an error in the proof of NP-completeness for this problem in the reference cited in text by Garey and Johnson [Computers and Intractability, A Guide to the Theory of NP-Completeness, 1979].     

Water-soluble Copolymers of N-vinylpyrrolidone and Vinyl Acetate: Synthesis, Characterization, and Monomer Reactivity at High Conversions

Homogeneous copolymers of N-vinylpyrrolidone (VP) and vinyl acetate (VA) which form clear aqueous solutions were prepared by free radical polymerization in a solution of isopropanol alcohol, using 2,2-azobisisobutyronitrile as an initiator. They were characterized by FTIR, ¹H-NMR, and element analysis studies. The reactivity ratios of the monomer were computed by the Extended Kelen–Tüdós method at high conversions, using data from both ¹H-NMR and elemental analysis studies. The reactivity ratios of VP and VA in a homogenous copolymer were observed to be very different from that of a heterogeneous copolymer. Additional information was obtained by finding out the sequence length distribution for copolymers.     

A comparative study of iterative and non-iterative feature selection techniques for software defect prediction

Two important problems which can affect the performance of classification models are high-dimensionality (an overabundance of independent features in the dataset) and imbalanced data (a skewed class distribution which creates at least one class with many fewer instances than other classes). To resolve these problems concurrently, we propose an iterative feature selection approach, which repeated applies data sampling (in order to address class imbalance) followed by feature selection (in order to address high-dimensionality), and finally we perform an aggregation step which combines the ranked feature lists from the separate iterations of sampling. This approach is designed to find a ranked feature list which is particularly effective on the more balanced dataset resulting from sampling while minimizing the risk of losing data through the sampling step and missing important features. To demonstrate this technique, we employ 18 different feature selection algorithms and Random Undersampling with two post-sampling class distributions. We also investigate the use of sampling and feature selection without the iterative step (e.g., using the ranked list from a single iteration, rather than combining the lists from multiple iterations), and compare these results from the version which uses iteration. Our study is carried out using three groups of datasets with different levels of class balance, all of which were collected from a real-world software system. All of our experiments use four different learners and one feature subset size. We find that our proposed iterative feature selection approach outperforms the non-iterative approach.     

Deep Neural Networks Regularization Using a Combination of Sparsity Inducing Feature Selection Methods

Neural Processing Letters - Deep learning is an important subcategory of machine learning approaches in which there is a hope of replacing man-made features with fully automatic extracted features....     

Imputation techniques for multivariate missingness in software measurement data

The problem of missing values in software measurement data used in empirical analysis has led to the proposal of numerous potential solutions. Imputation procedures, for example, have been proposed to ‘fill-in’ the missing values with plausible alternatives. We present a comprehensive study of imputation techniques using real-world software measurement datasets. Two different datasets with dramatically different properties were utilized in this study, with the injection of missing values according to three different missingness mechanisms (MCAR, MAR, and NI). We consider the occurrence of missing values in multiple attributes, and compare three procedures, Bayesian multiple imputation, k Nearest Neighbor imputation, and Mean imputation. We also examine the relationship between noise in the dataset and the performance of the imputation techniques, which has not been addressed previously. Our comprehensive experiments demonstrate conclusively that Bayesian multiple imputation is an extremely effective imputation technique.