Xi'an Jiaotong University

About: Xi'an Jiaotong University is a education organization based out in Xi'an, China. It is known for research contribution in the topics: Heat transfer & Dielectric. The organization has 85440 authors who have published 99682 publications receiving 1579683 citations. The organization is also known as: '''Xi'an Jiaotong University''' & Xi'an Jiao Tong University.

Anisotropic Swelling and Fracture of Silicon Nanowires during Lithiation

Abstract: We report direct observation of an unexpected anisotropic swelling of Si nanowires during lithiation against either a solid electrolyte with a lithium counter-electrode or a liquid electrolyte with a LiCoO2 counter-electrode. Such anisotropic expansion is attributed to the interfacial processes of accommodating large volumetric strains at the lithiation reaction front that depend sensitively on the crystallographic orientation. This anisotropic swelling results in lithiated Si nanowires with a remarkable dumbbell-shaped cross section, which develops due to plastic flow and an ensuing necking instability that is induced by the tensile hoop stress buildup in the lithiated shell. The plasticity-driven morphological instabilities often lead to fracture in lithiated nanowires, now captured in video. These results provide important insight into the battery degradation mechanisms.

Simulation Budget Allocation for Further Enhancing theEfficiency of Ordinal Optimization

Abstract: Ordinal Optimization has emerged as an efficient technique for simulation and optimization. Exponential convergence rates can be achieved in many cases. In this paper, we present a new approach that can further enhance the efficiency of ordinal optimization. Our approach determines a highly efficient number of simulation replications or samples and significantly reduces the total simulation cost. We also compare several different allocation procedures, including a popular two-stage procedure in simulation literature. Numerical testing shows that our approach is much more efficient than all compared methods. The results further indicate that our approach can obtain a speedup factor of higher than 20 above and beyond the speedup achieved by the use of ordinal optimization for a 210-design example.

Interface and performance of 3D printed continuous carbon fiber reinforced PLA composites

Abstract: A novel 3D printing based fabrication process of Continuous Fiber Reinforced Thermoplastic Composites (CFRTPCs) was proposed. Continuous carbon fiber and PLA filament were utilized as reinforcing phase and matrix, respectively, and simultaneously fed into the fused deposition modeling (FDM) 3D printing process realizing the integrated preparation and forming of CFRTPCs. Interfaces and performance of printed composites were systematically studied by analyzing the influencing of process parameters on the temperature and pressure in the process. Forming mechanism of multiple interfaces was proposed and utilized to explain the correlations between process and performance. Fiber content of the printed specimens can be easily controlled by changing the process parameters. When the fiber content reached 27%, flexural strength of 335 MPa and modulus of 30 GPa were obtained for the printed composite specimens. Composite components were fabricated to demonstrate the process feasibility. Potential applications could be found in the field of aviation and aerospace.

Cancer classification using the Immunoscore: a worldwide task force

Abstract: Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J Transl Med. editorial from January 2012. Immunophenotyping of tumors may provide crucial novel prognostic information. The results of this international validation may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).

Computer vision and pattern recognition

Abstract: This Special Issue of International Journal of Computer Mathematics (IJCM) offers a venue to present innovative approaches in computer vision and pattern recognition, which have been changing our e...