On the use of characteristic‐based split meshfree method for solving flow problems

This study presents characteristic‐based split (CBS) algorithm in the meshfree context. This algorithm is the extension of general CBS method which was initially introduced in finite element framework. In this work, the general equations of flow have been represented in the meshfree context. A new finite element and MFree code is developed for solving flow problems. This computational code is capable of solving both time‐dependent and steady‐state flow problems. Numerical simulation of some known benchmark flow problems has been studied. Computational results of MFree method have been compared to those of finite element method. The results obtained have been verified by known numerical, analytical and experimental data in the literature. A number of shape functions are used for field variable interpolation. The performance of each interpolation method is discussed. It is concluded that the MFree method is more accurate than FEM if the same numbers of nodes are used for each solver. Meshfree CBS algorithm is completely stable even at high Reynolds numbers. Copyright © 2007 John Wiley & Sons, Ltd.     

Automated Spleen Injury Detection Using 3D Active Contours and Machine Learning

The spleen is one of the most frequently injured organs in blunt abdominal trauma. Computed tomography (CT) is the imaging modality of choice to assess patients with blunt spleen trauma, which may include lacerations, subcapsular or parenchymal hematomas, active hemorrhage, and vascular injuries. While computer-assisted diagnosis systems exist for other conditions assessed using CT scans, the current method to detect spleen injuries involves the manual review of scans by radiologists, which is a time-consuming and repetitive process. In this study, we propose an automated spleen injury detection method using machine learning. CT scans from patients experiencing traumatic injuries were collected from Michigan Medicine and the Crash Injury Research Engineering Network (CIREN) dataset. Ninety-nine scans of healthy and lacerated spleens were split into disjoint training and test sets, with random forest (RF), naive Bayes, SVM, k-nearest neighbors (k-NN) ensemble, and subspace discriminant ensemble models trained via 5-fold cross validation. Of these models, random forest performed the best, achieving an Area Under the receiver operating characteristic Curve (AUC) of 0.91 and an F1 score of 0.80 on the test set. These results suggest that an automated, quantitative assessment of traumatic spleen injury has the potential to enable faster triage and improve patient outcomes.     

A hydrogen peroxide-responsive hyperpolarized 13C MRI contrast agent

We report a new reaction-based approach for the detection of hydrogen peroxide (H(2)O(2)) using hyperpolarized (13)C magnetic resonance imaging ((13)C MRI) and the H(2)O(2)-mediated oxidation of α-ketoacids to carboxylic acids. (13)C-Benzoylformic acid reacts selectively with H(2)O(2) over other reactive oxygen species to generate (13)C-benzoic acid and can be hyperpolarized using dynamic nuclear polarization, providing a method for dual-frequency detection of H(2)O(2). Phantom images collected using frequency-specific imaging sequences demonstrate the efficacy of this responsive contrast agent to monitor H(2)O(2) at pre-clinical field strengths. The combination of reaction-based detection chemistry and hyperpolarized (13)C MRI provides a potentially powerful new methodology for non-invasive multi-analyte imaging in living systems.     

Control releasing 5-aminosalicylic acid using pH-sensitive hydrogel with novel albumin cross-linker

Intelligent drug delivery systems are growing and changing too fast, these systems usually show a proper response at the proper time to one or several environmental factors. In the current research a biodegradable drug delivery system (pectin-g-PMA-co-PAAm) was designed and synthesized to release 5 aminosalicylic acid (5-ASA). The synthesized hydrogel is based on natural pectin and is in the form of simultaneous graft copolymerization of synthesized acryl-acid and acryl-amid. Using vinylized bovine serum albumin (VBSA) as cross linker agent is amongst important characteristics of this hydrogel. VBSA was synthesized through BSA modification with methylene-bis-acrylamide (MBA). In addition to having high water absorption, this hydrogel is pH-sensitive. In vitro tests under acid and base conditions of stomach show that this hydrogel is an appropriate option to release drugs through mouth. SEM analysis images show that synthesized hydrogel has a porous surface composed of nano and micro cavities.     

FIR Volterra kernel neural models and PAC learning

The probably approximately correct (PAC) learning theory creates a framework to assess the learning properties of static models for which the data are assumed to be independently and identically distributed (i.i.d.). The present article first extends the idea of PAC learning to cover the learning of modeling tasks with m‐dependent sequences of data. The data are assumed to be marginally distributed according to a fixed arbitrary probability. The resulting framework is then applied to evaluate learning of Volterra Kernel FIR models. © 2002 Wiley Periodicals, Inc.     

Sakiadis flow of an upper-convected Maxwell fluid

The flow of an upper-convected Maxwell (UCM) fluid is studied theoretically above a rigid plate moving steadily in an otherwise quiescent fluid. It is assumed that the Reynolds number of the flow is high enough for boundary layer approximation to be valid. Assuming a laminar, two-dimensional flow above the plate, the concept of stream function coupled with the concept of similarity solution is utilized to reduce the governing equations into a single third-order ODE. It is concluded that the fluid's elasticity destroys similarity between velocity profiles; thus an attempt was made to find local similarity solutions. Three different methods will be used to solve the governing equation: (i) the perturbation method, (ii) the fourth-order Runge-Kutta method, and (iii) the finite-difference method. The velocity profiles obtained using the latter two methods are shown to be virtually the same at corresponding Deborah number. The velocity profiles obtained using perturbation method, in addition to being different from those of the other two methods, are dubious in that they imply some degree of reverse flow. The wall skin friction coefficient is predicted to decrease with an increase in the Deborah number for Sakiadis flow of a UCM fluid. This prediction is in direct contradiction with that reported in the literature for a second-grade fluid.     

A new expertness index for assessment of secondary structure prediction engines

Improvement of prediction accuracy of the protein secondary structure is essential for further developments of the whole field of protein research. In this paper, the expertness of protein secondary structure prediction engines has been studied in three levels and a new criterion has been introduced in the third level. This criterion could be considered as an extension of the previous ones based on amino acid index. Using this new criterion, the expertness of some high score secondary structure prediction engines has been reanalyzed and some hidden facts have been discovered. The results of this new assessment demonstrated that a noticeable harmony has been existed among each amino acid prediction behavior in all engines. This harmony has also been seen between single global propensity and prediction accuracy of amino acid types in each secondary structure class. Moreover, it is shown that Proline and Glycine amino acids have been predicted with less accuracy in alpha helices and beta strands. In addition, regardless of different approaches used in prediction engines, beta strands have been predicted with less accuracy.     

Generating contrast in hyperpolarized 13C MRI using ligand-receptor interactions

We report the imaging of β-cyclodextrin-benzoic acid binding at 14T using hyperpolarized (13)C magnetic resonance (MR). Benzoic acid was polarized using a dynamic nuclear polarization (DNP) approach and combined with β-cyclodextrin in aqueous solution. As anticipated, decreases in the spin-lattice relaxation constant (T(1)) were observed with decreases in the ligand-receptor ratio. The calculated log K was approximately 1.7, similar to previously reported binding constants. Hyperpolarized [1-(13)C] benzoic acid was used to interrogate solutions of variable β-cyclodextrin concentrations, with the mixtures imaged at 14T using a 3D frequency-selective MR sequence. Differences in β-cyclodextrin concentration were easily visualized. These results suggest that hyperpolarized (13)C MR could be used in vivo to determine the presence and density of receptors for a given ligand-receptor pair.     

Preparation and properties of enhanced nanocomposites based on PLA/PC blends reinforced with silica nanoparticles

In order to lower brittleness of biobased polylactic acid (PLA), its blending with polycarbonate and nanosilica is aimed. In this line, to increase compatibility of the ingredients, dicumyl peroxide (DCP) and Cobalt (II) acetylacetonate (Co) were used as grafting and transesterification catalysts, respectively. The X‐ray diffraction (XRD) spectra demonstrated high compatibility of the ingredients by broadening of the PLA characteristic peaks and, also, good dispersion of nanosilica particles, especially in PLA/PC/Silica/Co sample. The EDX maps confirmed good nanosilica dispersion, too. The silica nanoparticle size was ranged from 20 to 100 nm in transmission electron microscopy (TEM) pictures. All nanocomposites showed improved thermal stability in thermogravimetric analysis (TGA). Differential scanning calorimetry (DSC) results demonstrated lower T_g, T_m, and crystallinity values for the fabricated nanocomposites. Notably, the dynamic mechanical thermal analysis (DMTA) curves confirmed the T_g, T_m, and T_cc trend obtained in DSC; moreover, much higher surface under tan δ peak for PLA/PC/Silica/Co sample was obtained, which implies its higher toughness. The precise tensile study of the samples confirmed significantly higher elongation at break of the nanocomposites, more considerably in PLA/PC/Silica/Co sample, with nearly negligible defect on tensile strength and modulus. In a concise, the obtained results confirmed the higher efficiency of Co catalyst, which leads to the sample with improved characteristics compared with DCP.