1. Background purification framework with extended morphological attribute profile for hyperspectral anomaly detectionJu Huang, Kang Liu, Mingliang Xu, Matjaž Perc, Xuelong Li, 2021, original scientific article Abstract: Hyperspectral anomaly detection has attracted extensive interests for its wide use in military and civilian fields, and three main categories of detection methods have been developed successively over past few decades, including statistical model-based, representation-based, and deep-learning-based methods. Most of these algorithms are essentially trying to construct proper background profiles, which describe the characteristics of background and then identify the pixels that do not conform to the profiles as anomalies. Apparently, the crucial issue is how to build an accurate background profile; however, the background profiles constructed by existing methods are not accurate enough. In this article, a novel and universal background purification framework with extended morphological attribute profiles is proposed. It explores the spatial characteristic of image and removes suspect anomaly pixels from the image to obtain a purified background. Moreover, three detectors with this framework covering different categories are also developed. The experiments implemented on four real hyperspectral images demonstrate that the background purification framework is effective, universal, and suitable. Furthermore, compared with other popular algorithms, the detectors with the framework perform well in terms of accuracy and efficiency.
Keywords: detectors, anomaly detection, image reconstruction, hyperspectral imaging, training, optics, dictionaries, background purification, extended attribute profile, sparse representation, stacked autoencoder
Published in DKUM: 19.08.2024; Views: 92; Downloads: 9
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2. Design of Tetra-Peptide Ligands of Antibody Fc Regions Using In Silico Combinatorial Library ScreeningMarko Jukič, Sebastjan Kralj, Anja Kolarič, Urban Bren, 2023, original scientific article Abstract: Abstract
Peptides, or short chains of amino-acid residues, are becoming increasingly important as active ingredients of drugs and as crucial probes and/or tools in medical, biotechnological, and pharmaceutical research. Situated at the interface between small molecules and larger macromolecular systems, they pose a difficult challenge for computational methods. We report an in silico peptide library generation and prioritization workflow using CmDock for identifying tetrapeptide ligands that bind to Fc regions of antibodies that is analogous to known in vitro recombinant peptide libraries’ display and expression systems. The results of our in silico study are in accordance with existing scientific literature on in vitro peptides that bind to antibody Fc regions. In addition, we postulate an evolving in silico library design workflow that will help circumvent the combinatorial problem of in vitro comprehensive peptide libraries by focusing on peptide subunits that exhibit favorable interaction profiles in initial in silico peptide generation and testing.
Keywords: peptide design, in silico combinatorial library, peptide combinatorial library, peptide library design, high-throughput virtual screening, peptide molecular docking, antibody purification, peptide drug design, recombinant peptide libraries
Published in DKUM: 01.12.2023; Views: 353; Downloads: 88
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3. Residual dyebath purification using a system of constructed wetlandAlenka Ojstršek, Darinka Fakin, Danijel Vrhovšek, 2007, original scientific article Abstract: A constructed wetland model, comprising two different substrate mixtures, was used to purify textile dyebath wastewater. Three laboratory prepared wastewaters containing three commercial dyes of different classes and chemicalconstitution (one vat and two reactive dyes), different chemicals (NaOH, NaCl) and auxiliaries (migration inhibitor, sequestering, defoaming andwetting agents) were employed. Purifying efficiency was verified by measuring pollution parameters, such as absorbance, pH, total organic carbon (TOC), chemical oxygen demand (COD) and electrical conductivity (EC). It was found that the constructed wetland model reduced dye concentration by up to 70%, lowered the TOC and COD values up to 88%, electrical conductivity up to 60% and pH from 12 to 7.6.
Keywords: textile dyeing, reactive dyes, vat dyes, wastewater treatment, constructed wetland model, biological treatment, purification
Published in DKUM: 01.06.2012; Views: 2315; Downloads: 100
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