Particle bonding mechanism in CGDS-a three-dimensional approach

Abstract: Cold gas dynamics spray (CGDS) is a surface coating process using highly accelerated particles to form the surface coating by high speed impact of the particles. In the CGDS process, metal particles of generally 1-50 μm diameter is carried by a gas stream in high pressure (typically 20-30 atm) through a DE Laval type nozzle to achieve supersonic flying so as to impact on the substrate. Typically, the impact velocity ranges between 300 and 1200 m/s in the CGDS process. When the particle gains its critical velocity, the minimum in-flight speed at which it can deposit, adiabatic shear instabilities will occur. Herein, to ascertain the critical velocities of different particle sizes on the bonding efficiency in CGDS process, three-dimensional numerical simulations of single particle deposition process were performed. In the CGDS process, one of the most important parameters which determine the bonding strength with the substrate is particle impact temperature. Bonding will occur when the particle’s impacting velocity surpass the critical velocity, at which the interface can achieve 60 % of melting temperature of particle material (Ref 1). Therefore, critical velocity should be a main parameter on the coating quality. The particle critical velocity is determined not only by its size, but also by its material properties. This study numerically investigate the critical velocity for the particle deposition process in CGDS. In the present numerical analysis, copper (Cu) was chosen as particle material and aluminum (Al) as substrate material for this study. The impacting velocities were selected between 300 m/s and 800 m/s increasing in steps of 100 m/s. The simulation result reveals temporal and spatial interfacial temperature distribution and deformation between particle(s) and substrate. Finally, comparison is carried out between the computed results and experimental data

Soft-tissue Tumor Differentiation Using 3D Power Doppler Ultrasonography With Echo-contrast Medium Injection

BackgroundWe aimed to evaluate the ability of 3-dimensional power Doppler ultrasonography to differentiate soft-tissue masses from blood flow and vascularization with contrast medium.MethodsTwenty-five patients (mean age, 44.1 years; range, 12-77 years) with a palpable mass were enrolled in this study. Volume data were acquired using linear and convex 3-dimensional probes and contrast medium injected manually by bolus. Data were stored and traced slice by slice for 12 slices. All patients were scanned by the same senior sonologist. The vascular index (VI), flow index (FI), and vascular-flow index (VFI) were automatically calculated after the tumor was completely traced. All tumors were later confirmed by pathology.ResultsThe study included 8 benign (mean, 36.5 mL; range, 2.4-124 mL) and 17 malignant (mean, 319.4 mL; range, 9.9-1,179.6 mL) tumors. Before contrast medium injection, mean VI, FI and VFI were, respectively, 3.22, 32.26 and 1.07 in benign tumors, and 1.97, 29.33 and 0.67 in malignant tumors. After contrast medium injection, they were, respectively, 20.85, 37.33 and 8.52 in benign tumors, and 40.12, 41.21 and 17.77 in malignant tumors. The mean differences between with and without contrast injection for VI, FI and VFI were, respectively, 17.63, 5.07 and 7.45 in benign tumors, and 38.15, 11.88 and 16.55 in malignant tumors. Tumor volume, VI, FI and VFI were not significantly different between benign and malignant tumors before and after echo-contrast medium injection. However, VI, FI and VFI under self-differentiation (differences between with and without contrast injection) were significantly different between malignant and benign tumors.ConclusionThree-dimensional power Doppler ultrasound is a valuable tool for differential diagnosis of soft-tissue tumors, especially with the injection of an echo-contrast medium

Intraosseous Lipoma of the Proximal Radius with Extraosseous Extension: A Case Report

Examination of lipomatous tumors with ultrasound (US) is generally limited to the soft tissue component of the mass and cortical contours of the involved bone. We report a patient with an intraosseous lipoma of the proximal radius with extra-osseous extension. US showed a heterogeneous hyperechoic mass lesion (3.5 × 3.0 cm in size) at the radial aspect of the left elbow, with bony cortex interruption. The lesion was associated with increased marginal color flow signals on color Doppler US study. Atypical lipoma or low-grade liposarcoma was diagnosed. The pathologic examination of the lesion demonstrated an abnormal collection of mature adipose tissue consistent with lipoma

A Postverification Method for Solving Forced Duffing Oscillator Problems without Prescribed Periods

This paper proposes a postverification method (PVM) for solving forced Duffing oscillator problems without prescribed periods. Comprising a postverification procedure and small random perturbation, the proposed PVM improves the sensitivity of the convergence of Newton’s iteration. Numerical simulations revealed that the PVM is more accurate and robust than Kubíček’s approach. We applied the PVM to previous research on bifurcation problems

The spontaneous emergence of ordered phases in crumpled sheets

X-ray tomography is performed to acquire 3D images of crumpled aluminum foils. We develop an algorithm to trace out the labyrinthian paths in the three perpendicular cross sections of the data matrices. The tangent-tangent correlation function along each path is found to decay exponentially with an effective persistence length that shortens as the crumpled ball becomes more compact. In the mean time, we observed ordered domains near the crust, similar to the lamellae phase mixed by the amorphous portion in lyotropic liquid crystals. The size and density of these domains grow with further compaction, and their orientation favors either perpendicular or parallel to the radial direction. Ordering is also identified near the core with an arbitrary orientation, exemplary of the spontaneous symmetry breaking

GenEpi: gene-based epistasis discovery using machine learning.

BackgroundGenome-wide association studies (GWAS) provide a powerful means to identify associations between genetic variants and phenotypes. However, GWAS techniques for detecting epistasis, the interactions between genetic variants associated with phenotypes, are still limited. We believe that developing an efficient and effective GWAS method to detect epistasis will be a key for discovering sophisticated pathogenesis, which is especially important for complex diseases such as Alzheimer's disease (AD).ResultsIn this regard, this study presents GenEpi, a computational package to uncover epistasis associated with phenotypes by the proposed machine learning approach. GenEpi identifies both within-gene and cross-gene epistasis through a two-stage modeling workflow. In both stages, GenEpi adopts two-element combinatorial encoding when producing features and constructs the prediction models by L1-regularized regression with stability selection. The simulated data showed that GenEpi outperforms other widely-used methods on detecting the ground-truth epistasis. As real data is concerned, this study uses AD as an example to reveal the capability of GenEpi in finding disease-related variants and variant interactions that show both biological meanings and predictive power.ConclusionsThe results on simulation data and AD demonstrated that GenEpi has the ability to detect the epistasis associated with phenotypes effectively and efficiently. The released package can be generalized to largely facilitate the studies of many complex diseases in the near future

Event-based textual document retrieval by using semantic role labeling and coreference resolution

International audienceConventional keyword-based indexing and retrieval techniques for textual documents lack of precision when a long query string is employed in order to discover documents containing a specific “event”, such as “Einstein discovered relativity”. This paper proposes a framework to resolve such a problem. In our proposal, we apply semantic role labeling and coreference techniques in order to parse each sentence within textual documents into three elements: subject, object and predicates. These elements can subsequently be used for indexing and retrieval. Our primitive evaluation experiments have shown that this promising methodology raises the retrieval precision if we compared it to conventional literal termmatching techniques