Related papers: Examples for the improvements in AES Depth Profili…
Gildings, patinas and alteration crusts are common features of many heritage artefacts, especially for metals. Their size depends on many factors, like the manufacturing method for gildings or the conservation state for alteration crusts:…
Protein quantification and analysis are well-accepted approaches for biomarker discovery but are limited to identification without structural information. High-throughput omics data (i.e., genomics, transcriptomics, and proteomics) have…
Multiresolution analysis and matrix factorization are foundational tools in computer vision. In this work, we study the interface between these two distinct topics and obtain techniques to uncover hierarchical block structure in symmetric…
Integrating various data modalities brings valuable insights into underlying phenomena. Multimodal factor analysis (FA) uncovers shared axes of variation underlying different simple data modalities, where each sample is represented by a…
Personalized treatment of patients based on tissue-specific cancer subtypes has strongly increased the efficacy of the chosen therapies. Even though the amount of data measured for cancer patients has increased over the last years, most…
Identifying altered pathways that are associated with specific cancer types can potentially bring a significant impact on cancer patient treatment. Accurate identification of such key altered pathways information can be used to develop…
Anomaly detection aims to identify observations that deviate from the typical pattern of data. Anomalous observations may correspond to financial fraud, health risks, or incorrectly measured data in practice. We show detecting anomalies in…
We report an interpretation method for deep learning models that allows us to handle high-dimensional spectral data in materials science. The proposed method uses feature extraction and clustering analysis to categorize materials into…
Materials characterization remains a labor-intensive process, with a large amount of expert time required to post-process and analyze micrographs. As a result, machine learning has become an essential tool in materials science, including…
In previous work a different and powerful, analytical, technique was used to get data, such as the absolute atom concentration (AAC), specimen thickness etc., from public domain boron nitride EELS spectrum collected under a collection…
Growing materials data and data-driven informatics drastically promote the discovery and design of materials. While there are significant advancements in data-driven models, the quality of data resources is less studied despite its huge…
It is shown that for thin metal films, thickness of which does not exceed a thickness of a skin-layer, the problem allows analytical solution for any boundary conditions. The analysis of transmission, reflection and absorption of an…
A simple model is explored mainly analytically to calculate and understand the PHS of single and multi-layer thermal neutron detectors and to help optimize the design in different circumstances. Several theorems are deduced that can help…
By adjusting the incidence angle of incoming X-ray near the critical angle of X-ray total reflection, the photoelectron intensity is strongly modulated due to the variation of X-ray penetration depth. Photoelectron spectroscopy (PES)…
The emergence of deep learning has brought the long-standing goal of comprehensively understanding and exploring crystalline materials closer to reality. Yet, universal exploration across all elements remains hindered by the combinatorial…
The authors report in situ Auger electron spectroscopy (AES) of the surfaces of complex oxides thin films grown by pulsed laser deposition (PLD). The authors demonstrate the utility of the technique in studying chemical composition by…
Amino acids are essential to all life. However, our understanding of some aspects of their intrinsic structure, molecular chemistry, and electronic structure is still limited. In particular the nature of amino acids in their crystalline…
Improvement of electrochemical technologies is one of the most popular topics in the field of renewable energy. However, this process requires a deep understanding of the electrode electrolyte interface behavior under operando conditions.…
In this letter, we explore electron filtering as a technique to increase Seebeck coefficient and the thermoelectric power factor of heterostructured materials over that of the bulk. We present a theoretical model in which Seebeck…
Factor Analysis based on multivariate $t$ distribution ($t$fa) is a useful robust tool for extracting common factors on heavy-tailed or contaminated data. However, $t$fa is only applicable to vector data. When $t$fa is applied to matrix…