Pt-based bimetallic nanoparticles have attracted significant attention as a promising replacement for expensive Pt nanoparticles. In the systematic design of bimetallic nanoparticles, it is important to understand their preferred atomic structures. However, compared with unary systems, alloy nanoparticles present more structural complexity with various compositional configurations, such as mixed-alloy, core-shell, and multishell structures. In this paper, we developed a unified empirical potential model for various Pt-based binary alloys, such as Pd-Pt, Cu-Pt, Au-Pt, and Ag-Pt. Within this framework, we performed a series of Monte Carlo (MC) simulations that quantify the energetically favorable atomic arrangements of Pt-based alloy nanoparticles: an intermetallic compound structure for the Pd-Pt alloy, an onion-like multi-shell structure for the Cu-Pt alloy, and core-shell structures (Au@Pt and Ag@Pt) for the Au-Pt and Ag-Pt alloys. The equilibrium nanoparticle structures for the four alloy types were compared with each other, and the structural features can be interpreted by the interplay of their material properties, such as the surface energy and heat of formation. PACS numbers: 61.46.+w, 36.40.Ei, 64.70.Nd I. II. INTERATOMIC POTENTIAL MODEL A. Embedded atom method potentials for Pt, Pd, and novel metals (Ag, Au, Cu)

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Pre-operative diagnosis of chest-wall deformity is important for successful surgical correction and post-operative evaluation of funnel chest patients. However, conventional indices that define the severity of deformity have several limitations; manually calculated and cannot supply information about asymmetry. We developed four indices that can represent both the depression and the asymmetry of the chest-wall, and can automatically be extracted by computerized image processing technique. Three indices, including eccentricity index (EI), flatness index (FI), and circularity index (CI), were suggested to represent the depression of the chest-wall, and one index, rotation index (RI), to represent the asymmetry of the chest-wall. To verify the feasibility of new indices, several synthetic images and real CT images were used to analyze the performance of new indices and the statistical relationship with conventional Haller index. The experimental results showed possible application of suggested indices to the diagnosis of funnel chest patient. Suggested indices showed clear trends of change with the severity of chest-wall deformation in regards to both the depression and the asymmetry. Results of statistical analysis showed high correlation between new indices and HI, showing possibility of replacing HI.

The present study aimed to map the location and frequency of fracture lines on the coronal articular and sagittal planes in multifragmentary patellar fractures. 66 multifragmentary patellar fractures were digitally reconstructed using the 3D CT mapping technique. The coronal articular surface and midsagittal fracture maps were produced by superimposing each case over a single template. Each fracture line was classified based on the initial displacement and orientation. We evaluated the frequency and direction of the fracture line, coronal split fragment area, and satellite and inferior pole fragment presence. Coronal articular surface fracture mapping identified primary horizontal fracture lines between the middle and inferior one-third of the articular surface in 63 patients (95.4%). Secondary horizontal fracture lines running on the inferior border of the articular facet were confirmed (83.3%). Secondary vertical fracture lines creating satellite fragments were mostly located on the periphery of the bilateral facet. Midsagittal fracture mapping of primary and secondary horizontal fracture lines with the main coronal fracture line revealed a predominantly X-shaped fracture map. The consequent coronal split fragment and inferior pole fracture were combined in most cases. In conclusion, the multifragmentary patellar fracture has a distinct pattern which makes coronal split, inferior pole, or satellite fragments.

The search for efficient and predictive methods to describe the protein folding process at the all-atom level remains an important grand-computational challenge. The development of multi-teraflop architectures, such as the IBM BlueGene used in this study, has been motivated in part by the large computational requirements of such studies. Here we report the predictive all-atom folding of the forty-amino acid HIV accessory protein using an evolutionary stochastic optimization technique. We implemented the optimization method as a master-client model on an IBM BlueGene, where the algorithm scales near perfectly from 64 to 4096 processors in virtual processor mode. Starting from a completely extended conformation, we optimize a population of 64 conformations of the protein in our all-atom free-energy model PFF01. Using 2048 processors the algorithm predictively folds the protein to a near-native conformation with an RMS deviation of 3.43 A in < 24 h.