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Catalog Publications
Year 2010
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Decomposition of xenobiotics in wastewater treatment
PublicationCiecze jonowe ze względu na rozpuszczalność w wodzie mogą przyczynić się do jej zanieczyszczenia. Możliwość ich biodegradacji nie jest dokładnie zbadana. W niniejszej pracy podjęto próbę sprawdzenie, jak na proces biodegradacji cieczy jonowych wpłynie obecność innych, łatwiej dostępnych dla osadu czynnego, źródeł węgla i azotu. Ponadto podjęto próbę ustalenia górnej granicy stężeń dla biodegradowalności chlorku 1-metylo-3-oktyloimidazolu
Year 2019
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Decontaminating Arbitrary Graphs by Mobile Agents: a Survey
PublicationA team of mobile agents starting from homebases need to visit and clean all nodes of the network. The goal is to find a strategy, which would be optimal in the sense of the number of needed entities, the number of moves performed by them or the completion time of the strategy. Currently, the field of distributed graph searching by a team of mobile agents is rapidly expanding and many new approaches and models are being presented...
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Decreased integrity of exercise-induced plasma cell free nuclear DNA – negative association with the increased oxidants production by circulating phagocytes
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Decreased integrity of exercise-induced plasma cell free nuclear DNA – negative association with the increased oxidants production by circulating phagocytes
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Decreasing Vaccination Coverage Against Hepatitis B and Tuberculosis in Newborns
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Decyzje przedsiębiorstwa na rynku finansowym
PublicationProwadzenie działalności gospodarczej, w tym realizowanie zamierzeń rozwojowych oraz bieżących, wiąże się z ryzykiem niezrealizowania wytyczonego celu. Oznacza to, że firma działa w warunkach ryzyka, a niekiedy niepewności. Główne ryzyka dotyczą utrudnień w pozyskaniu niezbędnych środków finansowych, wahań kursów walut, zmian stóp procentowych itp. Przedsiębiorstwo musi więc znaleźć miejsce, w którym firma pozyska niezbędne kapitały...
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DEDUKCJA ZACHOWAŃ WĘZŁÓW TRANZYTOWYCH W WIELOSKOKOWEJ SIECI BEZPRZEWODOWEJ W OBECNOŚCI ZAKŁÓCEŃ
PublicationPrzedstawiono nowy algorytm dedukcji zachowań (metryki reputacji) węzłów tranzytowych w wieloskokowej sieci bezprzewodowej na podstawie potwierdzeń końcowych. Algorytm stosuje znane metody matematyczne i jest odporny na zakłócenia naturalnie występujące w sieciach bezprzewodowych oraz intencjonalne zmiany zachowania węzłów. Informacja zwracana przez algorytm, poza wydedukowanym zachowaniem węzłów, zawiera dane o możliwym błędzie...
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Deep brain stimulation in obsessive-compulsive disorder – case report of two patients
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Deep brain stimulation: new possibilities for the treatment of mental disorders
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Deep eutectic solvents based highly efficient extractive desulfurization of fuels – Eco-friendly approach
PublicationThe developed process is based on alternative, green and cheap solvents for efficient desulfurization of fuels. Several deep eutectic solvents (DESs) were successfully synthesized and studied as extraction solvents for desulfurization of model fuel containing thiophene (T), benzothiophene (BT) and dibenzothiophene (DBT). The most important extraction parameters (i.e. kind of DES, DES: fuel volume ratio, hydrogen bond acceptor:...
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Deep learning in the fog
PublicationIn the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...
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Deep learning model for automated assessment of lexical stress of non-native english speakers
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublicationThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Deep neural network architecture search using network morphism
PublicationThe paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...
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Deep neural networks for human pose estimation from a very low resolution depth image
PublicationThe work presented in the paper is dedicated to determining and evaluating the most efficient neural network architecture applied as a multiple regression network localizing human body joints in 3D space based on a single low resolution depth image. The main challenge was to deal with a noisy and coarse representation of the human body, as observed by a depth sensor from a large distance, and to achieve high localization precision....
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Definicja kognitywna w diagnozie logopedycznej dzieci w normie oraz osób niepełnosprawnych intelektualnie
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Definicje kognitywne osoby niepełnosprawnej intelektualnie – na wybranych przykładach
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Year 2021
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Decoupled Kalman filter based identification of time-varying FIR systems
PublicationWhen system parameters vary at a fast rate, identification schemes based on model-free local estimation approaches do not yield satisfactory results. In cases like this, more sophisticated parameter tracking procedures must be used, based on explicit models of parameter variation (often referred to as hypermodels), either deterministic or stochastic. Kalman filter trackers, which belong to the second category, are seldom used in...
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Deep convolutional neural network for predicting kidney tumour malignancy
PublicationPurpose: According to the statistics, up to 15-20% of removed solid kidney tumors turn out to be benign in postoperative histopathological examination, despite having been identified as malignant by a radiologist. The aim of the research was to limit the number of unnecessary nephrectomies of benign tumors. Methods or Background: We propose a machine-aided diagnostic system for kidney...
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Deep eutectic solvent based method for analysis of Niclosamide in pharmaceutical and wastewater samples – A green analytical chemistry approach
PublicationThe paper presents a simple, but very effective and sensitive spectrophotometric method for trace analysis of Niclosamide based on liquid–liquid microextraction using deep eutectic solvents (DESs) prior to its quantification. Here, different DES systems, such as Choline chloride (ChCl) + Urea, ChCl + Citric acid, ChCl + Ethylene glycol and ChCl + Phenol, were synthesized and evaluated at different molar ratios, selecting ChCl + Phenol...
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Deep eutectic solvents – based green absorbents for effective volatile organochlorine compounds removal from biogas
PublicationVolatile organochlorine compounds (VOXs) presented in biogas can cause many technological and environmental problems. During the combustion of biogas containing VOXs, the corrosion of installation, as well as the formation of toxic by-products (polyhalogenated dioxins and furans) and further emission to the atmosphere, may occur. Therefore, in this study, a new procedure based on physical absorption was developed. In order to meet...
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Deep eutectic solvents based assay for extraction and determination of zinc in fish and eel samples using FAAS
PublicationA new assay based on effective (high recovery) extraction by means of deep eutectic solvents (DESs) was developed for ppb level determination of zinc in fishes and eel samples. Choline chloride and Phenol in a 1:2 M ratio was selected as optimal DES-based extraction solvent. 8-Hydroxy quinoline was used as a chelating agent for zinc ions. The optimized conditions were found at pH value of 8, ligand concentration of 10 mg/L, THF...
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Deep Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Deep learning for ultra-fast and high precision screening of energy materials
PublicationSemiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...
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Deep Learning-based Recalibration of the CUETO and EORTC Prediction Tools for Recurrence and Progression of Non–muscle-invasive Bladder Cancer
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Defense mechanisms and borderline personality organization among COVID-19 believers and non-believers during complete lock-down
PublicationThe aim of the current study was to investigate whether a specific social perception of the pandemic—believing or not in COVID-19—predicts borderline personality organizations and whether this relationship is mediated by more primitive maladaptive mechanisms—splitting, denial, and dissociation. The online study included 720 organization aged 25–45. Participants were diverse in terms of place of residence, being in a relationship,...
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Defining a novel domain that provides an essential contribution to site-specific interaction of Rep protein with DNA
PublicationAn essential feature of replication initiation proteins is their ability to bind to DNA. In this work, we describe a new domain that contributes to a replication initiator sequence-specific interaction with DNA. Applying biochemical assays and structure prediction methods coupled with DNA–protein crosslinking, mass spectrometry, and construction and analysis of mutant proteins, we identified that the replication initiator of the...
Year 2020
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Decrease in Photovoltaic Module Efficiency Due to Deposition of Pollutants
PublicationThe deposition of pollutants on the surface of photovoltaic (PV) modules reduce the efficiency that can be achieved in given climatic conditions. This results in the loss of energy yield obtained from the solar installation. A number of factors determine the scale of this problem. The first of these is the amount of impurities deposited, the associated amount of precipitation, and the speed and direction of the wind. A second aspect...
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Decyzje optymalne z Solverem
PublicationNa rynku można odnaleźć wiele podręczników pomocnych w rozwijaniu kompetencji związanych z posługiwaniem się arkuszem kalkulacyjnym w praktyce menedżerskiej. Niewiele jest natomiast pozycji literaturowych pokazujących możliwości wykorzystania MS Solver do wspomagania decyzji. Niniejsza książka ma za zadanie wypełnić tę lukę. Jej celem jest przedstawienie możliwości dodatku Solver w procesie podejmowania decyzji optymalnych. Intencją...
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Deep eutectic solvents vs ionic liquids: Similarities and differences
PublicationDeep eutectic solvents (DES) were introduced as an alternative to ionic liquids (IL) to overcome the drawbacks of IL solvents. However, some authors consider them to be a subclass of ILs. In contrast, other authors emphasize that these are by their nature independent, different groups of substances. Thus, the question arises: Which solvent group should DESs belong to? Maybe a new class should be added to the existing ones. The...
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Deep insight into the pore size distribution of N-doped porous carbon materials on electrochemical energy storage and CO2 sorption
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Deep Instance Segmentation of Laboratory Animals in Thermal Images
PublicationIn this paper we focus on the role of deep instance segmentation of laboratory rodents in thermal images. Thermal imaging is very suitable to observe the behaviour of laboratory animals, especially in low light conditions. It is an non-intrusive method allowing to monitor the activity of animals and potentially observe some physiological changes expressed in dynamic thermal patterns. The analysis of the recorded sequence of thermal...
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Deep learning based thermal image segmentation for laboratory animals tracking
PublicationAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Deep learning for recommending subscription-limited documents
PublicationDocuments recommendation for a commercial, subscription-based online platform is important due to the difficulty in navigation through a large volume and diversity of content available to clients. However, this is also a challenging task due to the number of new documents added every day and decreasing relevance of older contents. To solve this problem, we propose deep neural network architecture that combines autoencoder with...
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublicationThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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Defect engineering, microstructural examination and improvement of ultrafast third harmonic generation in GaZnO nanostructures: a study of e-beam irradiation
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Defect in Mitochondrial NADH-Dehydrogenase Genes in Canine Mast Cell Tumours
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Defective TiO2 Core-Shell Magnetic Photocatalyst Modified with Plasmonic Nanoparticles for Visible Light-Induced Photocatalytic Activity
PublicationIn the presented work, for the first time, the metal-modified defective titanium(IV) oxide nanoparticles with well-defined titanium vacancies, was successfully obtained. Introducing platinum and copper nanoparticles (NPs) as surface modifiers of defective d-TiO2 significantly increased the photocatalytic activity in both UV-Vis and Vis light ranges. Moreover, metal NPs deposition on the magnetic core allowed for the effective separation...
Year 1998
Year 2018
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Decreasing CO2 Emissions By Reducing Tire Rolling Resistance
PublicationThe first motor vehicle was built by Nicolas Cugnot almost 250 years ago and since then there has been a continuous process of motor vehicles’ improvements, as well as development of new road pavements. The fuel crisis of the 70s of the 20th century made it clear to vehicle builders that measures should be taken to reduce vehicle fuel consumption and it contributed to an increased interest in electric vehicles. Although significant...
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Deep analysis of Loop L1 HVRs1-4 region of the hexon gene of adenovirus field strains isolated in Poland
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublicationThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Deep sea habitats in the chemical warfare dumping areas of the Baltic Sea
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Deep submarine groundwater discharge indicated by pore water chloride anomalies in the Gulf of Gdańsk, southern Baltic Sea
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Year 2002
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DECT: nadzieja na integrację komunikacji
PublicationW artykule przedstawiono strukturę systemu DECT ze szczególnym uwzględnieniem sposobu realizacji transmisji danych. Przedstawiono koncepcję integracji systemu DECT z systemami telefonii komórkowej II i III generacji.
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Dedicated scheduling of tasks to minimize mean flow time
PublicationThis paper investigates the complexity of scheduling biprocessor tasks on dedicated processors to minimize mean flow time. Since the general problem is strongly NP-hard, we assume some restrictions on task lengths and the structure of associated scheduling graphs. Of particular interest are acyclic graphs. In this way we identify a borderline between NP-hard and polynomially solvable special cases.
Year 2003
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Decymator do przetwornika A/C typu ä(delta)
PublicationArtykuł opisuje projekt decymatora wykorzystywanego w przetworniku analogowo-cyfrowym typu ä(trójkt). Zaprojektowana struktura została zasymulowana zza pomocą programu MATLAB. Rozwijając architekturę decymatora szczególny nacisk został położony na minimalizację pobieranej mocy.
Year 2008
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Dedicated Geographical Information System in the context of Critical Infrastructure Protection
PublicationNowe zaawansowane narzędzia Technologii Informacyjnych i Komunikacyjnych mogą stanowić bardzo użyteczną pomoc podczas przewidywania różnego rodzaju zagrożeń jak również minimalizacji związanego z nimi ryzyka. Artykuł prezentuje Sieciowy System Informacji Przestrzennej dla Szacowania i Wizualizacji Infrastruktur Krytycznych i ich Zagrożeń, stworzony dla Urzędu Miejskiego w Gdańsku przez Politechnikę Gdańską. System ten jest przeznaczony...
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Dedykowane sieciowe technologie SIP dla prezentacji pseudodynamicznych danych geoprzestrzennych
PublicationSieciowe technologie prezentacji danych przestrzennych przeżywają aktualnie rozkwit spowodowany między innymi spadającymi cenami sprzętu komputerowego. Wynikający z tego wzrost wydajności domowych i biurowych stacji roboczych pozwala na praktyczne zastosowanie czasochłonnych algorytmów wizualizacji i przetwarzania skomplikowanych danych rastrowych i wektorowych. Niniejszy artykuł omawia wybrane technologie sieciowej prezentacji...
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Dedykowany System Informacji Przestrzennej w kontekście ochrony infrastruktur krytycznych
PublicationNowe zaawansowane narzędzia Technologii Informacyjnych i Komunikacyjnych mogą stanowić bardzo użyteczną pomoc podczas przewidywania różnego rodzaju zagrożeń jak również minimalizacji związanego z nimi ryzyka. Artykuł prezentuje Sieciowy System Informacji Przestrzennej dla Szacowania i Wizualizacji Infrastruktur Krytycznych i ich Zagrożeń, stworzony dla Urzędu Miejskiego w Gdańsku przez Politechnikę Gdańską. System ten jest przeznaczony...
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Definicja zadań inteligentnych agentów do oceny technologii informatycznych
PublicationCelem pracy jest prezentacja definicji zadań agentów dla potrzeb systemu agentowego do oceny technologii informatycznych.
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Definicje ontologii w wieloagentowym systemie do oceny technologii informatycznych
PublicationCelem artykułu jest zdefiniowanie ontologii dla potrzeb systemu wieloagentowego do oceny technologii informatycznych. Definicje ontologii stanowią podstawę do przygotowania ich specyfikacji dla potrzeb JADE (Java Agent Development Framework). W założeniu ma to być rozwiązanie wieloagentowe korzystające z takich elementów jak bazy wiedzy oraz ontologie traktowane z punktu widzenia JADE jako dołączane biblioteki. W artykule zaprezentowano...
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Definicje schematów danych jako specjalizowane dialekty językowe na przykładzie XML Schema dla sektora energetycznego
PublicationRozdział przedstawia zagadnienie opracowania zbioru reguł (schematu) dla dokumentów XML i omawia celowość tworzenia takich schematów na przykładzie XML Schema dla sieci elektroenergetycznej.
Year 2013
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Dedicated power supply subsystem for ultra-low noise preamplifiers
PublicationIn field of electronics there is need for low-noise amplifiers. Noise have the most important influence on analog circuits. Therefore exist necessity to develop new ultra-low noise power supplies, which can cooperate with specified amplifiers and preamplifiers. It is very common that professional power supplies are very expensive and still have disadvantages. This paper proposes simple and inexpensive solution, which fulfill specific...
Year 2007
Year 2016
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Dedukcja zachowań węzłów sieci ad hoc na podstawie potwierdzeń końcowych: ocena dokładności
PublicationPrzebadano precyzję algorytmu dedukcji rzeczywistych spolegliwości węzłów sieci MANET w oparciu o potwierdzenia end-to-end i bez użycia mechanizmu watchdog. W przeprowadzonych eksperymentach numerycznych wskazano charakterystyki topologiczne wpływające na tę precyzję.
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DEDYKOWANY SYSTEM MONITORINGU WARUNKÓW KLIMATYCZNYCH W CENTRUM DANYCH
PublicationKoszty utrzymania centrum danych istotnie zależą od kosztów zużycia energii elektrycznej. Zapotrzebowanie na energię elektryczną w tego typu obiektach można optymalizować poprzez monitoring warunków klimatycznych oraz odpowiednie sterowanie czasem pracy urządzeń je utrzymujących. W pracy przedstawiono analizę czynników wpływających na zużycie energii elektrycznej w centrach danych oraz ich wpływ na koszty zużycia energii. Przedstawiono...
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Deep Data Analysis of a Large Microarray Collection for Leukemia Biomarker Identification
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Deep slot effect in the squirrel-cage induction motors with scalar (V/F) control
PublicationQualitative characteristics of the electrical drive considerably depend on identification accuracy of math model parameters. In particular, it is depend on detection accuracy of stator active resistance r1 that is used in calculation of flux linkages, rotary speed in sensorless control systems. Paper provides analysis of influence of stator deep slot effect to stator active resistance value
Year 2015
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Deduplication of Position Data and Global Identification of Objects Tracked in Distributed Vessel Monitoring System
PublicationVessel monitoring systems (VMS) play a very important role in safety navigation. In most cases, their structure is distributed and they are based on two data sources, namely Automatic Identification System (AIS) and Automatic Radar Plotting Aids (ARPA). Such approach results in several objects identification and position data duplication problems, which need to be solved in order to ensure the correct performance of a given VMS....
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Deduplication of Tracked Objects Position Data at Single Observation Point of a Vessel Monitoring System
PublicationVessel Monitoring System (VMS) play a major role in safety navigation. In most cases they are based on two data sources, namely Automatic Identification System (AIS) and Automatic Radar Plotting Aids (ARPA). Integration of data obtained from these sources is an important problem, which needs to be solved in order to ensure the correct performance of a given VMS. In this paper basic functions which should be implemented in a tracked...
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Defects in RNA polyadenylation impair both lysogenization by and lytic development of Shiga toxin-converting bacteriophages
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Year 2014
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Deep compaction control of sandy soils
PublicationVibroflotation, vibratory compaction, micro-blasting or heavy tamping are typical improvement methods for the cohesionless deposits of high thickness. The complex mechanism of deep soil compaction is related to void ratio decrease with grain rearrangements, lateral stress increase, prestressing effect of certain number of load cycles, water pressure dissipation, aging and other effects. Calibration chamber based interpretation...
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Defence in depth conception in nuclear power plants and requirements for instrumentation and control systems
PublicationThe aim of this article is to identify and discuss some issues of the safety systems’ design for nuclear power plants equipped with the light water reactors using a defence in depth (D-in-D) conception. Because the functional safety solutions play nowadays an important role for the risk control, the basic requirements for the instrumentation and control systems are specified with regard to relevant international standards. For...
Year 2017
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublicationThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Deep Features Class Activation Map for Thermal Face Detection and Tracking
PublicationRecently, capabilities of many computer vision tasks have significantly improved due to advances in Convolutional Neural Networks. In our research, we demonstrate that it can be also used for face detection from low resolution thermal images, acquired with a portable camera. The physical size of the camera used in our research allows for embedding it in a wearable device or indoor remote monitoring solution for elderly and disabled...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublicationThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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Defining efficient modes range for plasma spraying coatings
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Year 2022
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Deep eutectic solvent (DES) with silver nanoparticles (Ag-NPs) based assay for analysis of lead (II) in edible oils
PublicationThis paper presents an application of silver nanoparticles impregnated by Deep Eutectic Solvents (DES) as ultrasonication aided microextraction system for lead (II) determination in edible oils. The paper presents a systematic optimization of method parameters and examples of its application for analysis of real samples. Maximum recovery for lead (II) extraction was obtained for choline chloride and phenol with a 1:2 molar ratio....
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Deep eutectic solvents – A new platform in membrane fabrication and membrane-assisted technologies
PublicationDeep eutectic solvents (DESs) are a new class of solvents that can offset some of the primary drawbacks of typical solvents and ionic liquids (ILs). Since DESs fall into the guidelines of “Twelve Principles of Green Chemistry”, their implementation in several types of applications has exponentially increased over the last years. The usage of DESs has been directed to the designing, manufacture and purification of new materials...
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Deep Eutectic Solvents and Their Uses for Air Purification
PublicationChemical compounds released into the air by the activities of industrial plants and emitted from many other sources, including in households (paints, waxes, cosmetics, disinfectants, plastic (PVC) flooring), may affect the environment and human health. Thus, air purification is an important issue in the context of caring for the condition of the environment. Deep eutectic solvents (DESs) as liquids with environmentally friendly...
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Deep Eutectic Solvents for Starch Treatment
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Deep eutectic solvents microbial toxicity: Current state of art and critical evaluation of testing methods
PublicationDeep eutectic solvents (DESs) were described at the beginning of 21st century and they consist of a mixture of two or more solid components, which gives rise to a lower melting point compared to the starting materials. Over the years, DESs have proved to be a promising alternative to traditional organic solvents and ionic liquids (ILs) due to their low volatility, low inflammability, easy preparation, and usually low cost of compounds...
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Deep Eutectic Solvents or Eutectic Mixtures? Characterization of Tetrabutylammonium Bromide and Nonanoic Acid Mixtures
PublicationDeep eutectic solvents have quickly attracted the attention of researchers because they better meet the requirements of green chemistry and thus have the potential to replace conventional hazardous organic solvents in some areas. To better understand the nature of these mixtures, as well as expand the possibilities of their use in different industries, a detailed examination of their physical properties, such as density, viscosity,...
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Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Deep Learning Approaches in Histopathology
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublicationObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
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Deep learning-based waste detection in natural and urban environments
PublicationWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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Deep learning-based waste detection in natural and urban environments
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Defending against Fake VIP in Scant-Transparency Information Systems with QoS Differentiation
PublicationIn client-server information systems with quality of service (QoS) differentiation, Client may deplete Server’s resources by demanding unduly high QoS level. Such QoS abuse has eluded systematic treatment; known defenses using Client authorization, payments, or service request inspection prior to QoS assignment, are heuristic and environment-specific. We offer a game-theoretic approach on the premise that a service request is occasionally...
Year 2023
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Deep Eutectic Solvent Stir Bar Sorptive Extraction: A Rapid Microextraction Technique for the Determination of Vitamin D3 by Spectrophotometry
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Deep eutectic solvents – Ideal solution for clean air or hidden danger?
PublicationThe industrial sector is one of the fastest-growing sources of greenhouse gases, due to its excessive energy consumption to meet the rapidly growing demand for energy-intensive products. The use of deep eutectic solvents (DESs) has been studied extensively in order to cope with these harmful gases, but their usage can be an issue in respect to ecological reasons. Do deep eutectic solvents harm the atmosphere? Yes, these solvents...
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Deep eutectic solvents in analytical sample preconcentration Part B: Solid-phase (micro)extraction
PublicationOne of the key challenges of modern analytical chemistry is the monitoring of trace amounts of contaminants using sensitive and selective instrumental techniques. Due to the variety and complexity of some samples, it is often necessary to properly prepare a sample and to perform a preconcentration of trace amounts of analytes. In line with the principles of Green Analytical Chemistry (GAC), it is important for an analytical procedure...
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Deep Eutectic Solvents: Properties and Applications in CO2 Separation
PublicationNowadays, many researchers are focused on finding a solution to the problem of global warming. Carbon dioxide is considered to be responsible for the “greenhouse” effect. The largest global emission of industrial CO2 comes from fossil fuel combustion, which makes power plants the perfect point source targets for immediate CO2 emission reductions. A state-of-the-art method for capturing carbon dioxide is chemical absorption using...
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Deep learning approach for delamination identification using animation of Lamb waves
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Deep learning super-resolution for the reconstruction of full wavefield of Lamb waves
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
Year 2024
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Deep eutectic solvent-based shaking-assisted extraction for determination of bioactive compounds from Norway spruce roots
PublicationPolyphenolic compounds play an essential role in plant growth, reproduction, and defense mechanisms against pathogens and environmental stresses. Extracting these compounds is the initial step in assessing phytochemical changes, where the choice of extraction method significantly influences the extracted analytes. However, due to environmental factors, analyzing numerous samples is necessary for statistically significant results,...
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Deep Eutectic Solvents as Agents for Improving the Solubility of Edaravone: Experimental and Theoretical Considerations
PublicationIn this study, both practical and theoretical aspects of the solubility of edaravone (EDA) in Deep Eutectic Solvents (DESs) were considered. The solubility of edaravone in some media, including water, can be limited, which creates the need for new efficient and environmentally safe solvents. The solubility of EDA was measured spectrophotometrically and the complex intermolecular interactions within the systems were studied with...
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Deep Eutectic Solvents as Agents for Improving the Solubility of Edaravone: Experimental and Theoretical Considerations
PublicationIn this study, both practical and theoretical aspects of the solubility of edaravone (EDA) in Deep Eutectic Solvents (DESs) were considered. The solubility of edaravone in some media, including water, can be limited, which creates the need for new efficient and environmentally safe solvents. The solubility of EDA was measured spectrophotometrically and the complex intermolecular interactions within the systems were studied with...
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Deep eutectic solvents with solid supports used in microextraction processes applied for endocrine-disrupting chemicals
PublicationThe determination of endocrine-disrupting chemicals (EDCs) has become one of the biggest challenges in Analytical Chemistry. Due to the low concentration of these compounds in different kinds of samples, it becomes necessary to employ efficient sample preparation methods and sensitive measurement techniques to achieve low limits of detection. This issue becomes even more struggling when the principles of the Green Analytical Chemistry...
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Deep Infiltrating Endometriosis in Adolescence: Early Diagnosis and Possible Prevention of Disease Progression
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublicationBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Defected Ag/Cu-MOF as a modifier of polyethersulfone membranes for enhancing permeability, antifouling properties and heavy metal and dye pollutant removal
PublicationIn this study, a novel bimetallic metal-organic framework (MOF) i.e. Ag/Cu-MOF was synthesized using a solvothermal method and later incorporated at different concentrations (0.1–2 wt%) using a phase inversion method for modification and antifouling property improvement of polyethersulfone (PES) membranes. The resulting Ag/Cu-MOF characteristics were investigated using different techniques, such as FTIR, XRD, FE-SEM and EDX. The...