Semi-Supervised Deep Learning for Multi-Tissue Segmentation from Multi-Contrast MRI

Journal of Signal Processing Systems - Segmentation of thigh tissues (muscle, fat, inter-muscular adipose tissue (IMAT), bone, and bone marrow) from magnetic resonance imaging (MRI) scans is useful...     

Prediction of deflection of reinforced concrete shear walls

Reinforced concrete shear walls are used in tall buildings for efficiently resisting lateral loads. Due to the low tensile strength of concrete, reinforced concrete shear walls tend to behave in a nonlinear manner with a significant reduction in stiffness, even under service loads. To accurately assess the lateral deflection of shear walls, the prediction of flexural and shear stiffness of these members after cracking becomes important. In the present study, an iterative analytical procedure which considers the cracking in the reinforced concrete shear walls has been presented. The effect of concrete cracking on the stiffness and deflection of shear walls have also been investigated by the developed computer program based on the iterative procedure. In the program, the variation of the flexural stiffness of a cracked member has been evaluated by ACI and probability-based effective stiffness model. In the analysis, shear deformation which can be large and significant after development of cracks is also taken into account and the variation of shear stiffness in the cracked regions of members has been considered by using effective shear stiffness model available in the literature. Verification of the proposed procedure has been confirmed from series of reinforced concrete shear wall tests available in the literature. Comparison between the analytical and experimental results shows that the proposed analytical procedure can provide an accurate and efficient prediction of both the deflection and flexural stiffness reduction of shear walls with different height to width ratio and vertical load. The results of the analytical procedure also indicate that the percentage of shear deflection in the total deflection increases with decreasing height to width ratio of the shear wall.     

Control of interface nanoscale structure created by plasma-enhanced chemical vapor deposition

Tailoring the structure of films deposited by plasma-enhanced chemical vapor deposition (PECVD) to specific applications requires a depth-resolved understanding of how the interface structures in such films are impacted by variations in deposition parameters such as feed position and plasma power. Analysis of complementary X-ray and neutron reflectivity (XR, NR) data provide a rich picture of changes in structure with feed position and plasma power, with those changes resolved on the nanoscale. For plasma-polymerized octafluorocyclobutane (PP-OFCB) films, a region of distinct chemical composition and lower cross-link density is found at the substrate interface for the range of processing conditions studied and a surface layer of lower cross-link density also appears when plasma power exceeds 40 W. Varying the distance of the feed from the plasma impacts the degree of cross-linking in the film center, thickness of the surface layer, and thickness of the transition region at the substrate. Deposition at the highest power, 65 W, both enhances cross-linking and creates loose fragments with fluorine content higher than the average. The thickness of the low cross-link density region at the air interface plays an important role in determining the width of the interface built with a layer subsequently deposited atop the first.     

A polyurethane‐based nanocomposite biocompatible bone adhesive

A novel polyurethane‐based foam‐like adhesive reinforced with nanosized hydroxyapatite (HA) particles was developed and investigated for bone‐to‐bone bonding applications in terms of mechanical adhesion and biocompatibility. The adhesive has a hierarchical structure with HA particles at the nanoscale level and pores at the micro‐scale level. This adhesive was tested mechanically in the three principal loading modes anticipated: shear, tension, and compression. Standard testing procedures were used when available. Tensile strength of primed adhesive showed a four‐fold increase in adhesion on unmodified bone and a nearly two‐fold increase in adhesion to primed bone as compared with the conventional bone cement. Biocompatibility was initially assessed in vitro using cell culture tests, which showed positive interaction with the adhesive. Then, a second biocompatibility test was performed using Xenopus laevis limbs to assess an in vivo response. The results indicated that the adhesive material produces a normal response consistent with control specimens. However, long‐term observations and tests with additional species are needed to demonstrate full biocompatibility. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2013     

An integrated decision aid extension to material selection problem

Choice of an adequate material in design process is one of the critical tasks for the relevant decision-makers. At this insight, the consistency of the decisions is extremely depending on the relevance of adapted techniques to the nature of different problem cases. This paper proposed an integrated decision aid (IDEA) to match the suitable techniques with different problem cases based on the following six dimensions: (i) the type of the decision problem, (ii) the size of the problem, (iii) selection of the preference techniques by decision-makers, (iv) decision-makers’ preference structure, (v) the necessity for the use of relative importance, (vi) the nature of performance values. Furthermore, the implementation procedure of the proposed IDEA for a material selection problem is demonstrated with the previously cited applications from material science literature. Hereafter, it is expected that the IDEA provides great advantages and encouragements to researchers/practitioners in order to prevent excessive time consuming, probable misapplications, and the other challenging issues in multiple criteria analysis of material selection problems.     

Surface roughness properties of polyester woven fabrics after abrasion

Effect of abrasion on surface roughness properties of textured polyester woven fabrics has been investigated. The effects of weft density, weft yarn filament number, fiber fineness, and weave pattern on surface roughness after abrasion were studied. Surface roughness values of control fabric (not abraded) and abraded fabrics after four different abrasion cycles were discussed according to different constructional parameters. Surface roughness values of fabrics changed according to abrasion cycles and the changes were related to yarn float lengths, yarn densities, yarn fiber fineness, and initial fabric surface roughness. A general overview of the results showed that abrasion eliminated the effect of texture especially at the fabric samples with initially high surface roughness. The surface roughness of fabrics with initially high surface roughness decreased at a greater extent than the ones with low surface roughness after abrasion. Fabrics with high surface roughness were affected more by abrasion and the effect of abrasion on rough surfaces depended on different manners regarding the compactness of woven structures.     

Glass Forming Ability and Magnetic Properties of Fe36Ni36B19.2Si4.8Nb4−x M x (M=Cu, Zr, Ti, Y, Pt) Bulk Glassy Alloys Fabricated by Suction Casting

In this study, the effects of Cu, Zr, Ti, Y, Pt substitution for Nb additions on the stability and magnetic properties of Fe-Ni-based bulk metallic glass (BMG) alloys fabricated by the suction casting method are investigated. The saturation magnetization (J _s) and coercivity (H _c) for as-cast Fe₃₆Ni₃₆B_19.2Si_4.8Nb_4?x M _x (M=Cu, Ti) BMG alloys were in the range of 0.51 T–0.55 T and 76–779 A/m, respectively. Differential scanning calorimetry curves show that the Fe₃₆Ni₃₆B_19.2Si_4.8Nb_4?x M _x (M=Cu, Ti) bulk metallic glasses have a supercooled liquid region for Cu at 44 K and for Ti at 39 K.     

Simultaneously learning actions and goals from demonstration

Our research aim is to develop interactions and algorithms for learning from naïve human teachers through demonstration. We introduce a novel approach to leverage the goal-oriented nature of human teachers by learning an action model and a goal model simultaneously from the same set of demonstrations. We use robot motion data to learn an action model for executing the skill. We use a generic set of perceptual features to learn a goal model and use it to monitor the executed action model. We evaluate our approach with data from 8 naïve teachers demonstrating two skills to the robot. We show that the goal models in the perceptual feature space are consistent across users and correctly recognize demonstrations in cross-validation tests. We additionally observe that a subset of users were not able to teach a successful action model whereas all of them were able to teach a mostly successful goal model. When the learned action models are executed on the robot, the success was on average 66.25 %. Whereas the goal models were on average 90 % correct at deciding on success/failure of the executed action, which we call monitoring.     

Synthesis and photopolymerization of novel,highly reactive phosphonated-urea-methacrylates for dental materials

An urea methacrylate (1) and two phosphonated methacrylates (2–3) were synthesized from 2-isocyanatoethyl methacrylate (IEM) and benzyl amine (1), diethyl aminomethylphosphonate (2) and diethyl amino(phenyl)methylphosphonate (3). Their photopolymerization rates are notably higher than commercial monomers, despite the presence of only one double bond. Their polymerization rates follow the order 1 ～ 2 > 3 ～ triethylene glycol dimethacrylate (TEGDMA) > 2-hydroxyethyl methacrylate (HEMA). A tendency toward high crosslinking density during thermal bulk polymerizations, low oxygen sensitivity and high conversions with benzophenone during photopolymerization indicated the importance of hydrogen abstraction/chain transfer reactions. It was found that the addition of the monomers to HEMA significantly increased its polymerization rate, proving their utility as replacements for TEGDMA as reactive diluents for 2,2-bis[4-(2-hydroxy-3-methacryloyloxy propyloxy) phenyl] propane (Bis-GMA). Copolymer systems containing 2 and 3 showed improved T_g values compared to Bis-GMA/TEGDMA systems.     

Template‐Based Synthesis of Aluminum Nitride Hollow Nanofibers Via Plasma‐Enhanced Atomic Layer Deposition

Aluminum nitride (AlN) hollow nanofibers were synthesized via plasma‐enhanced atomic layer deposition using sacrificial electrospun polymeric nanofiber templates having different average fiber diameters (~70, ~330, and ~740 nm). Depositions were carried out at 200°C using trimethylaluminum and ammonia precursors. AlN‐coated nanofibers were calcined subsequently at 500°C for 2 h to remove the sacrificial polymeric nanofiber template. SEM studies have shown that there is a critical wall thickness value depending on the template's average fiber diameter for AlN hollow nanofibers to preserve their shapes after the template has been removed by calcination. Best morphologies were observed for AlN hollow nanofibers prepared by depositing 800 cycles (corresponding to ~69 nm) on nanofiber templates having ~330 nm average fiber diameter. TEM images indicated uniform wall thicknesses of ~65 nm along the fiber axes for samples prepared using templates having ~70 and ~330 nm average fiber diameters. Synthesized AlN hollow nanofibers were polycrystalline with a hexagonal crystal structure as determined by high‐resolution TEM and selected area electron diffraction. Chemical compositions of coated and calcined samples were studied using X‐ray photoelectron spectroscopy (XPS). High‐resolution XPS spectra confirmed the presence of AlN.