EFFECT OF DIFFRENT LOADS ON THE WEAR BEHAVIORS OF 5Cr5Mo2V STEEL AT 700 °C

The effect of different loads on the high-temperature wear behavior of 5Cr5Mo2V steel at 700 °C was investigated. Wear morphologies, oxide compositions and matrix evolution were studied. The results showed that the wear rate increased with an increased test load, and the wear mechanism transformed from abrasive-oxidative wear to adhesive-oxidative wear. The relation between a delaminated oxide layer and cracks in the matrix were investigated. The exfoliation of carbides and displacement difference between the matrix and carbides caused a crack initiation. The wear rate strongly related to carbides, and coarse M6C carbides with poor holding power led to a high wear rate. Besides, a diagram of wear characteristics under different loads was suggested in this work.

Low-rank density-matrix evolution for noisy quantum circuits

In this work, we present an efficient rank-compression approach for the classical simulation of Kraus decoherence channels in noisy quantum circuits. The approximation is achieved through iterative compression of the density matrix based on its leading eigenbasis during each simulation step without the need to store, manipulate, or diagonalize the full matrix. We implement this algorithm using an in-house simulator and show that the low-rank algorithm speeds up simulations by more than two orders of magnitude over existing implementations of full-rank simulators, and with negligible error in the noise effect and final observables. Finally, we demonstrate the utility of the low-rank method as applied to representative problems of interest by using the algorithm to speed up noisy simulations of Grover’s search algorithm and quantum chemistry solvers.

Monitoring stem cell differentiation using Raman microspectroscopy: chondrogenic differentiation, towards cartilage formation

Raman microspectroscopy is employed to monitor the differentiation of mesenchymal stem cells to chondrocytes, from subcellular to extracellular matrix evolution.

Path Integrals, Spontaneous Localisation, and the Classical Limit

The measurement problem and the absence of macroscopic superposition are two foundational problems of quantum mechanics today. One possible solution is to consider the Ghirardi–Rimini–Weber (GRW) model of spontaneous localisation. Here, we describe how spontaneous localisation modifies the path integral formulation of density matrix evolution in quantum mechanics. We provide two new pedagogical derivations of the GRW propagator. We then show how the von Neumann equation and the Liouville equation for the density matrix arise in the quantum and classical limit, respectively, from the GRW path integral.

Application of Fractal and Gray-Level Co-Occurrence Matrix Indices to Assess the Forest Dynamics in the Curvature Carpathians—Romania

The mountain ecosystems face significant damage from deforestation and environmental forest changes. We investigated the evolution of tree types of cover areas, deforested areas and total deforested areas from Curvature Carpathians using Gray-Level Co-occurrence Matrix and fractal analysis. The forest dynamics mapping was one of the main objectives of this study and it was carried out using multiple fractal and GLCM indices. We approached the analysis of satellite forest images by calculation of four fractal indices such as Pyramid dimension, Cube Counting Dimension, Fractal Fragmentation-Compaction Index and Tug-of-War lacunarity. We also calculated fractal dimension because it is an index of complexity comparing how the detail in a pattern changes with the scale at which it is measured. Fractal dimension is useful for estimation of irregularity or roughness of fractal and natural objects that do not conform to Euclidian geometry. While the fractal dimension quantifies how much space is occupied, the Tug-of-War lacunarity complements fractal dimension with its ability to quantify how space is occupied. Analysis was further supplemented by the Gray-Level Co-occurrence Matrix analysis because it quantifies spatial probability distributions of gray level values between pixel pairs within an image. The calculated Gray-Level Co-occurrence Matrix features included Angular Second Moment, Contrast, Correlation, Inverse Difference Moment and Entropy. Such comprehensive analysis has the advantage of combining fractal analysis that extracts quantitative information about the morphological complexity of the image with the spatial distribution of the gray pixel intensities as calculated by the co-occurrence features provided by Gray-Level Co-occurrence Matrix. Evolution of deforested areas, expansion of agricultural land and the increased demand for quality timber have affected the forests ecosystems and, the regional sustainable development of local communities.