An Incremental Tensor Train Decomposition Algorithm

We present a new algorithm for incrementally updating the tensor-train decomposition of a stream of tensor data. This new algorithm, called the tensor-train incremental core expansion (TT-ICE) improves upon the current state-of-the-art algorithms for compressing in tensor-train format by developing a new adaptive approach that incurs significantly slower rank growth and guarantees compression accuracy. This capability is achieved by limiting the number of new vectors appended to the TT-cores of an existing accumulation tensor after each data increment. These vectors represent directions orthogonal to the span of existing cores and are limited to those needed to represent a newly arrived tensor to a target accuracy. We provide two versions of the algorithm: TT-ICE and TT-ICE accelerated with heuristics (TT-ICE$^*$). We provide a proof of correctness for TT-ICE and empirically demonstrate the performance of the algorithms in compressing large-scale video and scientific simulation datasets. Compared to existing approaches that also use rank adaptation, TT-ICE$^*$ achieves 57$\times$ higher compression and up to 95% reduction in computational time.Comment: 22 pages, 7 figures, for the python code of TT-ICE and TT-ICE$^*$ algorithms see https://github.com/dorukaks/TT-IC

Human Perception-Inspired Grain Segmentation Refinement Using Conditional Random Fields

Accurate segmentation of interconnected line networks, such as grain boundaries in polycrystalline material microstructures, poses a significant challenge due to the fragmented masks produced by conventional computer vision algorithms, including convolutional neural networks. These algorithms struggle with thin masks, often necessitating intricate post-processing for effective contour closure and continuity. Addressing this issue, this paper introduces a fast, high-fidelity post-processing technique, leveraging domain knowledge about grain boundary connectivity and employing conditional random fields and perceptual grouping rules. This approach significantly enhances segmentation mask accuracy, achieving a 79% segment identification accuracy in validation with a U-Net model on electron microscopy images of a polycrystalline oxide. Additionally, a novel grain alignment metric is introduced, showing a 51% improvement in grain alignment, providing a more detailed assessment of segmentation performance for complex microstructures. This method not only enables rapid and accurate segmentation but also facilitates an unprecedented level of data analysis, significantly improving the statistical representation of grain boundary networks, making it suitable for a range of disciplines where precise segmentation of interconnected line networks is essential

Enhanced radiation damage tolerance of amorphous interphase and grain boundary complexions in Cu-Ta

Amorphous interfacial complexions are particularly resistant to radiation damage and have been primarily studied in alloys with good glass-forming ability, yet recent reports suggest that these features can form even in immiscible alloys such as Cu-Ta under irradiation. In this study, the mechanisms of damage production and annihilation due to primary knock-on atom collisions are investigated for amorphous interphase and grain boundaries in a Cu-Ta alloy using atomistic simulations. Amorphous complexions, in particular amorphous interphase complexions that separate Cu and Ta grains, result in less residual defect damage than their ordered counterparts. Stemming from the nanophase chemical separation in this alloy, the amorphous complexions exhibit a highly heterogeneous distribution of atomic excess volume, as compared to a good glass former like Cu-Zr. Complexion thickness, a tunable structural descriptor, plays a vital role in damage resistance. Thicker interfacial films are more damage-tolerant because they alter the defect production rate due to differences in intrinsic displacement threshold energies during the collision cascade. Overall, the findings of this work highlight the importance of interfacial engineering in enhancing the properties of materials operating in radiation-prone environments and the promise of amorphous complexions as particularly radiation damage-tolerant microstructural features

Chemical order transitions within extended interfacial segregation zones in NbMoTaW

Interfacial segregation and chemical short-range ordering influence the behavior of grain boundaries in complex concentrated alloys. In this study, we use atomistic modeling of a NbMoTaW refractory complex concentrated alloy to provide insight into the interplay between these two phenomena. Hybrid Monte Carlo and molecular dynamics simulations are performed on columnar grain models to identify equilibrium grain boundary structures. Our results reveal extended near-boundary segregation zones that are much larger than traditional segregation regions, which also exhibit chemical patterning that bridges the interfacial and grain interior regions. Furthermore, structural transitions pertaining to an A2-to-B2 transformation are observed within these extended segregation zones. Both grain size and temperature are found to significantly alter the widths of these regions. Analysis of chemical short-range order indicates that not all pairwise elemental interactions are affected by the presence of a grain boundary equally, as only a subset of elemental clustering types are more likely to reside near certain boundaries. The results emphasize the increased chemical complexity that is associated with near-boundary segregation zones and demonstrate the unique nature of interfacial segregation in complex concentrated alloys

Manajans ve Türk reklamcılığına katkısı

Ankara : İhsan Doğramacı Bilkent Üniversitesi İktisadi, İdari ve Sosyal Bilimler Fakültesi, Tarih Bölümü, 2015.This work is a student project of the The Department of History, Faculty of Economics, Administrative and Social Sciences, İhsan Doğramacı Bilkent University.by Öztürk, İbrahim Mert

Evaluation of Perimandibular Neurovascularization With Accessory Mental Foramina Using Cone-Beam Computed Tomography in Children

Orhan, Kaan/0000-0001-6768-0176WOS: 000330129000019PubMed: 23851871Objectives: The purpose of this study was to clarify the perimandibular neurovascularization with mandibular accessory mental foramina in a children population using cone-beam computed tomography (CBCT) to avoid complications during anesthetic and surgical procedures. Methods: This retrospective study evaluated cone-beam CT images for bifid mandibular canals in the mandibles of 63 children (35 girls, 28 boys; age range, 7-16 years; mean age, 12.3 years). Both right and left sides were examined from CT images (n = 126), including axial, sagittal, cross-sectional, and panoramic views as well as reconstructed three-dimensional images, as necessary. The course, length, and superior and inferior angles between canals were classified and measured. Results: Bifid mandibular canals were observed in 34 (27%) of the 126 sides examined. The most frequently encountered type of bifid canal was the retromolar canal (11.1%), followed by the forward (7.14%), buccolingual (6.35%), and dental canal (2.4%). Mean lengths of bifid canals were 10.2 mm on the right side and 10.6 mm on the left side. Mean superior angles were 131 degrees on the right side and 147 degrees on the left side, whereas mean inferior angles were 47 degrees on the right side and 34 degrees on the left side. No statistically significant differences were found in the lengths or angles between the right and left sides or between boys and girls (P < 0.05). The most common position for the mental foramen was between the first and second premolars, and an accessory mental foramen was observed in 4 children (6.34%). Conclusions: This study utilized CBCT images to identify bifid mandibular canals and accessory mental foramina in children. Cone-beam CT was found to be a useful technique for detecting secondary canals. However, despite the fact that CBCT uses less ionizing radiation than other types of three-dimensional imaging, unless the diagnostic information provided through CBCT improves treatment results, CBCT should not be recommended for use in children or adolescents