Physicochemical and Functional Properties of Freeze-Dried and Oven Dried Corn Gluten Meals

The physicochemical and functional properties of convection oven- and freeze-dried gluten meals of two corn varieties were evaluated. The physicochemical properties (water solubility index, water absorption index, Hunter color parameters, and bulk density) and functional properties (water absorption, oil absorption, least gelation concentration, protein solubility, and emulsification properties) of convection-oven and freeze-dried corn gluten meals were compared with each other and soy flour. Freeze-dried corn gluten meals was observed to have lower bulk density (0.244-0.263 kg/m³) and was lighter in color (high L and ΔE) compared to their counterpart convection oven-dried gluten meals. Freeze-dried gluten meals from both corn varieties showed significantly higher oil absorption, water absorption, pH, emulsification, and protein solubility compared to oven-dried corn gluten meals. The gluten meals from both corn varieties had lower water absorption and bulk density but higher oil absorption than soy flour, suggesting the hydrophobic nature of corn proteins. Corn gluten meals formed thin (pourable) emulsions compared to soy flour emulsions, which were thick salad dressing type. Freeze- and convection oven-dried corn gluten meals showed significantly lower protein solubility measured at different pH than soy flour.     

Smart computational fracture of materials and structures

The use of the finite element method for complex engineering problems is now common. To ease the burden on the engineer the development of smart or adaptive computational methods is now required to model complex problems. In this paper we investigate the development of an adaptive finite element method for fracture-related problems. The adaptive method involves various stages which include the finite element analysis, error estimation/indication, mesh refinement and fracture/failure analysis in a loop. Some simple error estimators, based on stress projection, are used to investigate the adaptive finite element process. Element refinement is based on three schemes; the first and second are a simple and hierarchical refinement scheme with transitioning which avoids the need for constraint equations between element boundaries. Another scheme based on constraint equations between elements is also examined. The energy norm is used to estimate the element error. The software has the ability to introduce a discrete fracture in the structure according to standard fracture analysis practice. Crack tip parameters are calculated using a least-squares fit of the displacements into the asymptotic crack tip displacement field. Some simple examples are used to investigate the adaptive process, its behavior and some of the practical problems encountered. The convergence and equilibrium of the adaptive process, in terms of global error in the energy norm, are investigated. In the example the same problem is analyzed using both a fine computational grid and a coarse one. The coarse mesh is then adapted using the three different procedures available. The estimated error in the solution and the stress intensity are shown against the number of elements and number of iterations. Some further areas of research in adaptive finite element analysis are discussed.     

Evaluation of NR-LU-10 with the Neoprobe gamma detector in a mouse model

1. The effects of diethyl maleate (DEM) on the cytotoxicity of phenyl-hydroquinone (PHQ) and other hydroquinones were studied in freshly isolated rat hepatocytes. 2. Addition of PHQ (0.5 or 0.75 mM) to hepatocytes resulted in dose-dependent cell death accompanied by the abrupt depletion of both GSH and protein thiols and the accumulation of phenyl-benzoquinone (PBQ). 3. Pretreatment with DEM (1.25 mM), which causes an abrupt depletion of cellular GSH in hepatocytes, delayed the onset of PHQ-induced cytotoxicity. The delay correlated with inhibition of PBQ formation. 4. Although the pH of the cell suspension was increased slightly (mean pH 0.18) by incubation under carbogen flow, the addition of DEM to the cell suspension inhibited both the increase in pH and the formation of PBQ from PHQ. 5. In hepatocyte suspensions without DEM, PHQ cytotoxicity was dependent on pH, and toxicity was associated with oxidation of PHQ and accumulation of PBQ. 6. Among other hydroquinones (0.5 mM), tert-butyl-hydroquinone-induced cytotoxicity was decreased by DEM (1.25 mM), but DEM did not affect the cytotoxicity of 2,5-di(tert-butyl)-1,4-benzohydroquinone. 7. PHQ-induced cytotoxicity correlated with the accumulation of PBQ in the cell, and the inhibition of PHQ-induced cytotoxicity by DEM correlated with pH-dependent changes in PBQ formation.     

All Ag Nanoparticles Are Not the Same: Covalent Interactions between Ag Nanoparticles and Nitrile Groups Help Combat Drug- and Ag-Resistant Bacteria

Antimicrobial resistance has long been viewed as a lethal threat to global health. Despite the availability of a wide range of antibacterial medicines all around the world, organisms have evolved a resistance mechanism to these therapies. As a result, a scenario has emerged requiring the development of effective antibacterial drugs/agents. In this article, we exclusively highlight a significant finding reported by Zbořil and associates (Adv. Sci. 2021, 2003090). The authors construct a covalently bounded silver-cyanographene (GCN/Ag) with the antibacterial activity of 30 fold higher than that of free Ag ions or typical Ag nanoparticles (AgNPs). Ascribed to the strong covalent bond between nitrile and Ag, an immense cytocompatibility is shown by the GCN/Ag towards healthy human cells with a minute leaching of Ag ions. Firm interactions between the microbial membrane and the GCN/Ag are confirmed by molecular dynamics simulations, which rule out the dependence of antibacterial activity upon the Ag ions alone. Thus, this study furnishes ample scope to unfold next-generation hybrid antimicrobial drugs to confront infections arising from drug and Ag-resistant bacterial strains.     

Particle filters and occlusion handling for rigid 2D–3D pose tracking

In this paper, we address the problem of 2D–3D pose estimation. Specifically, we propose an approach to jointly track a rigid object in a 2D image sequence and to estimate its pose (position and orientation) in 3D space. We revisit a joint 2D segmentation/3D pose estimation technique, and then extend the framework by incorporating a particle filter to robustly track the object in a challenging environment, and by developing an occlusion detection and handling scheme to continuously track the object in the presence of occlusions. In particular, we focus on partial occlusions that prevent the tracker from extracting an exact region properties of the object, which plays a pivotal role for region-based tracking methods in maintaining the track. To this end, a dynamical choice of how to invoke the objective functional is performed online based on the degree of dependencies between predictions and measurements of the system in accordance with the degree of occlusion and the variation of the object’s pose. This scheme provides the robustness to deal with occlusions of an obstacle with different statistical properties from that of the object of interest. Experimental results demonstrate the practical applicability and robustness of the proposed method in several challenging scenarios.     

Performing Efficient NURBS Modeling Operations on the GPU

We present algorithms for evaluating and performing modeling operations on NURBS surfaces using the programmable fragment processor on the Graphics Processing Unit (GPU). We extend our GPU-based NURBS evaluator that evaluates NURBS surfaces to compute exact normals for either standard or rational B-spline surfaces for use in rendering and geometric modeling. We build on these calculations in our new GPU algorithms to perform standard modeling operations such as inverse evaluations, ray intersections, and surface-surface intersections on the GPU. Our modeling algorithms run in real time, enabling the user to sketch on the actual surface to create new features. In addition, the designer can edit the surface by interactively trimming it without the need for retessellation. Our GPU-accelerated algorithm to perform surface-surface intersection operations with NURBS surfaces can output intersection curves in the model space as well as in the parametric spaces of both the intersecting surfaces at interactive rates. We also extend our surface-surface intersection algorithm to evaluate self-intersections in NURBS surfaces.     

GPU-accelerated minimum distance and clearance queries

We present practical algorithms for accelerating distance queries on models made of trimmed NURBS surfaces using programmable Graphics Processing Units (GPUs). We provide a generalized framework for using GPUs as coprocessors in accelerating CAD operations. By supplementing surface data with a surface bounding-box hierarchy on the GPU, we answer distance queries such as finding the closest point on a curved NURBS surface given any point in space and evaluating the clearance between two solid models constructed using multiple NURBS surfaces. We simultaneously output the parameter values corresponding to the solution of these queries along with the model space values. Though our algorithms make use of the programmable fragment processor, the accuracy is based on the model space precision, unlike earlier graphics algorithms that were based only on image space precision. In addition, we provide theoretical bounds for both the computed minimum distance values as well as the location of the closest point. Our algorithms are at least an order of magnitude faster and about two orders of magnitude more accurate than the commercial solid modeling kernel ACIS.