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Search results for: machine learning for error detection in manufacturing processes
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Method for the determination of carboxylic acids in industrial effluents using dispersive liquid-liquid microextraction with injection port derivatization gas chromatography–mass spectrometry
PublicationThe paper presents a new method for the determination of 15 carboxylic acids in samples of postoxidative effluents from the production of petroleum bitumens using ion-pair dispersive liquid-liquid microextraction and gas chromatography coupled to mass spectrometry with injection port derivatization. Several parameters related to the extraction and derivatization efficiency were optimized. Under optimized experimental conditions,the...
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Surface Plasmon-Coupled Emission of Rhodamine 110 Aggregates in a Silica Nanolayer
PublicationFirst analysis of strong directional surface plasmon-coupled emission(SPCE) of ground-state formed intermolecular aggregates of Rhodamine 110 (R110) insilica nanofilms deposited on silver nanolayers is reported. Until now, the processes ofenergy transport and its trapping due to aggregate formation have not been studied in the presence of SPCE. A new approach to multicomponent systems with weakly and strongly fluorescent centers...
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Organic Vapor Sensing Mechanisms by Large-Area Graphene Back-Gated Field-Effect Transistors under UV Irradiation
PublicationThe gas sensing properties of graphene back-gated field-effect transistor (GFET) sensors toward acetonitrile, tetrahydrofuran, and chloroform vapors were investigated with the focus on unfolding possible gas detection mechanisms. The FET configuration of the sensor device enabled gate voltage tuning for enhanced measurements of changes in DC electrical characteristics. Electrical measurements were combined with a fluctuation-enhanced...
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CyberEye: New Eye-Tracking Interfaces for Assessment and Modulation of Cognitive Functions beyond the Brain
PublicationThe emergence of innovative neurotechnologies in global brain projects has accelerated research and clinical applications of BCIs beyond sensory and motor functions. Both invasive and noninvasive sensors are developed to interface with cognitive functions engaged in thinking, communication, or remembering. The detection of eye movements by a camera offers a particularly attractive external sensor for computer interfaces to monitor,...
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Nonlocal elasticity analysis of moderately thick porous functionally graded plates in a hygro-thermal environment
PublicationThis work performs a novel quasi three-dimensional (3D) bending analysis for a moderately thick functionally graded material (FGM) made of nanoceramics and metal powders, in presence of porosities due to some incorrect manufacturing processes. Such porosities can appear within the plate in two forms, namely, even and uneven distributions. The modeled system assumes a polymer matrix where both shear and transverse factors coexist....
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Proposition of the methodology for Data Acquisition, Analysis and Visualization in support of Industry 4.0
PublicationIndustry 4.0 offers a comprehensive, interlinked, and holistic approach to manufacturing. It connects physical with digital and allows for better collaboration and access across departments, partners, vendors, product, and people. Consequently, it involves complex designing of highly specialized state of the art technologies. Thus, companies face formidable challenges in the adoption of these new technologies....
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Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublicationLand Use and Land Cover (LULC) monitoring is crucial for global transformation, sustainable land control, urban planning, urban growth prediction, and the establishment of climate regulations for long-term development. Remote sensing images have become increasingly important in many environmental planning and land use surveys in recent times. LULC is evaluated in this research using the Sat 4, Sat 6, and Eurosat datasets. Various...
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Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems
PublicationThe rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. The significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance...
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Review of Segmentation Methods for Coastline Detection in SAR Images
PublicationSynthetic aperture radar (SAR) images acquired by airborne sensors or remote sensing satellites contain the necessary information that can be used to investigate various objects of interest on the surface of the Earth, including coastlines. The coastal zone is of great economic importance and is also very densely populated. The intensive and increasing use of coasts and changes of coastlines motivate researchers to try to assess...
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Neural network training with limited precision and asymmetric exponent
PublicationAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
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Quantifying inconsistencies in the Hamburg Sign Language Notation System
PublicationThe advent of machine learning (ML) has significantly advanced the recognition and translation of sign languages, bridging communication gaps for hearing-impaired communities. At the heart of these technologies is data labeling, crucial for training ML algorithms on a huge amount of consistently labeled data to achieve models that generalize well. The adoption of language-agnostic annotations is essential to connect different sign...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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A note on the applications of artificial intelligence in the hospitality industry: preliminary results of a survey
PublicationIntelligent technologies are widely implemented in different areas of modern society but specific approaches should be applied in services. Basic relationships refer to supporting customers and people responsible for services offering for these customers. The aim of the paper is to analyze and evaluate the state-of-the art of artificial intelligence (AI) applications in the hospitality industry. Our findings show that the major...
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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublicationCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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Anisotropic optical properties of few-layer black phosphorus coatings: from fundamental insights to opto-electrochemical sensor design
PublicationFew-layer black phosphorus (FLBP) is characterised by a tuneable bandgap, high carrier mobility and anisotropic optical properties. It therefore has the potential to find applications in electronics and photonics. FLBP oxidizes upon exposure to air, limiting its utility in devices and components. To address this issue, the thesis introduces methods and tools developed for studying FLBP's optical parameters, with a particular emphasis...
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Dobór cech elementu skończonego do wyznaczania naprężeń w tkance kostnej
PublicationBadania dotyczące obliczeń metodą elementów skończonych dla tkanki kostnej często wykorzystują metodologię budowy maszyn, gdzie używa się materiałów konstrukcyjnych o jednolitych właściwościach. Rzadko uwzględniają zróżnicowanie modułu Younga w obszarze elementów skończonych, gdzie informacje o rozkładzie sztywności tkanki pochodzą z obrazów tomograficznych. Celem pracy jest opracowanie metody modelowania tkanki kostnej uwzględniającej...
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Golden artefacts, resin figurines, body adhesives and tomb sediments from the pre-Columbian burial site El Caño (Gran Coclé, Panamá): tracing organic contents using molecular archaeometry
PublicationThis research aimed to determine the origin of organic residues from funerary contexts in the El Ca~no settlement (Gran Cocl�e area, Panam�a, Central America) by means of multiple molecular probing techniques (GC-MS of organic solvent extracts and pyrolysis-GC-MS, THM-GC-MS and FTIR of solid samples). The samples include particles of precious resin figurines, fillings of golden objects, tomb sediments, plant exudates from extant...
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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublicationIn this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model has been used. The task is to predict simultaneously and independent of each characteristic parameters of a buried object of several radii at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable...
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On adaptive covariance and spectrum estimation of locally stationary multivariate processes
PublicationWhen estimating the correlation/spectral structure of a locally stationary process, one has to make two important decisions. First, one should choose the so-called estimation bandwidth, inversely proportional to the effective width of the local analysis window, in the way that complies with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive...
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Polychlorinated Biphenyls (PCBs) and Polycyclic Aromatic Hydrocarbons (PAHs): Sediments and Water Analysis
PublicationUnfavorable side effects of different forms of anthropogenic activities can be found anywhere in the world. One of the basic characteristics of pollutants entering marine and ocean waters is their spread and movement in the global ocean. A portion of the substances entering the marine environment is rapidly degraded by chemical processes occurring in the air, sediments, and water, thereby losing their toxic properties. The biggest...
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Resource productivity and environmental degradation in EU-27 countries: context of material footprint
PublicationThis study explores the relationship between the resource productivity and environmental degradation in European Union-27 countries. This study tests this relationship in context of high, moderate, and low material footprint sub-samples; these samples are formed utilizing the expectation–maximization machine learning algorithm. Using the panel data set of EU-27 countries from 2000 to 2020, linear and non-linear autoregressive distributed...
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublicationAs the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability in cloud environments. This paper presents a novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs a game-theoretic approach based on particle swarm optimization (PSO) (PSO-GTA). The proposed approach leverages...
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Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublicationIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
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Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
PublicationFiber-reinforced concrete (FRC) is extensively used in diverse structural engineering applications, and its mechanical properties are crucial for designing and evaluating its performance. The compressive, flexural, splitting tensile, and shear strengths of FRCs are among the most important attributes, which have been discussed more extensively than other properties. The accurate prediction of these properties, which are required...
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Remote measurement of building usable floor area - Algorithms fusion
PublicationRapid changes that are taking place in the urban environment have significant impact on urban growth. Most cities and urban regions all over the world compete to increase resident and visitor satisfaction. The growing requirements and rapidity of introducing new technologies to all aspects of residents' lives force cities and urban regions to implement "smart cities" concepts in their activities. Real estate is one of the principal...
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Rapid Multi-Criterial Antenna Optimization by Means of Pareto Front Triangulation and Interpolative Design Predictors
PublicationModern antenna systems are designed to meet stringent performance requirements pertinent to both their electrical and field properties. The objectives typically stay in conflict with each other. As the simultaneous improvement of all performance parameters is rarely possible, compromise solutions have to be sought. The most comprehensive information about available design trade-offs can be obtained through multi-objective optimization...
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Computational Methods for Liver Vessel Segmentation in Medical Imaging: A Review
PublicationThe segmentation of liver blood vessels is of major importance as it is essential for formulating diagnoses, planning and delivering treatments, as well as evaluating the results of clinical procedures. Different imaging techniques are available for application in clinical practice, so the segmentation methods should take into account the characteristics of the imaging technique. Based on the literature, this review paper presents...
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A new index for statistical analyses and prediction of travelling ionospheric disturbances
PublicationTravelling Ionospheric Disturbances (TIDs) are signatures of atmospheric gravity waves (AGWs) observed in changes in the electron density. The analysis of TIDs is relevant for studying coupling processes in the thermosphere–ionosphere system. A new TID index is introduced, which is based on an easy extension of the commonly used approach for TID detection. This TID activity index, which can be applied for individual Global Navigation...
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Study of vibrational surface topography measurement errors of LPBF Inconel 718 alloy after shot peening process
PublicationA study of surface topography can provide valuable information on the product. Since the material finishing relies on the measured topography, the manufacturing process can be controlled by studying the roughness. The Laser Power Bed Fusion (LPBF) materials belong to the commonly used surfaces in the industry. Measuring this type of material with a contactless method can be found in many practical implementations. The white light interference...
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The role of hydrogen bonding on tuning hard-soft segments in bio-based thermoplastic poly(ether-urethane)s
PublicationThis work describes the preparation of bio-based thermoplastic poly(ether-urethane)s (TPU) via a prepolymer method and investigates the effect of varying the interphase hydrogen-bonding (H-bonding) on physicochemical, thermal and mechanical properties. This was achieved by varying the glycol type and molar ratio of [NCO]/[OH] groups used during the prepolymer chain extending step. The TPUs’ chemical structure was analyzed by Fourier...
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Technical Engine for Democratization of Modeling, Simulations, and Predictions
PublicationComputational science and engineering play a critical role in advancing both research and daily-life challenges across almost every discipline. As a society, we apply search engines, social media, and se- lected aspects of engineering to improve personal and professional growth. Recently, leveraging such aspects as behavioral model analysis, simulation, big data extraction, and human computation is gain- ing momentum. The nexus...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublicationWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublicationWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this objective...
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Mutagenic and Carcinogenic Compounds in Food
PublicationFood is a major environmental human cancer risk factor. One of the reasons for this is that food products contain substances that exhibit mutagenic and carcinogenic potential which may induce the transformation of normal somatic cells into cancerous cells. These compounds occur in food as a result of microbial contaminations (mycotoxins produced by molds), are generated from natural food components upon processing (e.g. heterocyclic...
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Dissociative photo-double-ionization of isoxazole
PublicationIn the present communication, we present results on the photo-double-ionization and fragmentation of the isoxazole molecules. The experiments were carried out at the CiPo beamline at the Elettra-Sincrotrone radiation facility exploiting the VUV excitation and the ion time-of-flight spectrometry combined with the PEPICO technique. The dissociative processes where only one electron is emitted are quite well known [1]. However, double...
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Semantic segmentation training using imperfect annotations and loss masking
PublicationOne of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate...
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Discrete identification of continuous non-linear and non-stationary dynamical systems that is insensitive to noise correlation and measurement outliers
PublicationThe paper uses specific parameter estimation methods to identify the coefficients of continuous-time models represented by linear and non-linear ordinary differential equations. The necessary approximation of such systems in discrete time in the form of utility models is achieved by the use of properly tuned `integrating filters' of the FIR type. The resulting discrete-time descriptions retain the original continuous parameterization...
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublicationThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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Monte Carlo simulations of the fracture resistance degradation of asphalt concrete subjected to environmental factors
PublicationThe paper presents the results of laboratory tests of SCB (semi-circular beam) samples of asphalt concrete, subjected to the destructive effect of water and frost as well as the aging processes. The determined values of material parameters show significant dispersions, which makes the design of mixtures difficult. Statistical analysis of the test results supplemented by computer simulations made with the use of the proprietary...
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A New Approach of Solidification Analysis in Modular Latent Thermal Energy Storage Unit Based on Image Processing
PublicationThe solidification process of RT18HC in a cylindrical shell and tube storage unit has been studied using a new methodology based on image processing. The main idea of the algorithm is to label the region of solidification and use statistical functions to calculate the dimensions of the solidification front over time. Said analysis includes two methods. The first method is to measure the solid fraction changes during solidification....
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The influence of selected metal oxides and laser modification on the surfaces of titanium alloys – Bibliometric and systematic review
PublicationManufacturing of oxide coatings (ZnO, ZrO2 , CuO) and laser processing are methods for modifying the surface of titanium and its alloys. It is particularly useful in implantology, where these techniques allow for proper connection of the implant to human tissue. The article consists of two complementary parts: a bibliographic review and a literature survey. The results of a bibliographic analysis conducted for a set of 429 publications...
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Towards a Universal Model of Engineering Change Management
PublicationThe paper deals with the issue of engineering change management (ECM). ECM has received much less attention in the literature than general change management. Moreover, due to their specifics (complexity and multifaceted nature), hitherto developed ECM models are difficult to implement in companies. The paper aims to develop a simplified, universal, and hence easily applicable model of ECM. We based our assumptions on a case study...
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Green engineered biomaterials for bone repair and regeneration: Printing technologies and fracture analysis
PublicationDespite the exceptional self-regeneration properties of bone, severe injuries often require additional surgical intervention such as using artificial bone constructs. These structures need to meet a number of criteria regarding their structure, performance, alongside the rate and the mechanism of erosion and fracture when implanted, for stimulating the regeneration of defected bone and, more critically providing support in the...
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Surface Roughness Evaluation in Thin EN AW-6086-T6 Alloy Plates after Face Milling Process with Different Strategies
PublicationLightweight alloys made from aluminium are used to manufacture cars, trains and planes. The main parts most often manufactured from thin sheets requiring the use of milling in the manufacturing process are front panels for control systems, housing parts for electrical and electronic components. As a result of the final phase of the manufacturing process, cold rolling, residual stresses remain in the surface layers, which can influence...
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Moisture content during and after high- and normal-temperature drying processes of wood
PublicationThe aim of the article is to present the results of moisture content of wood during and after the high-temperature steam and air–steam mixture drying processes and after an open air-drying process. The knowledge of moisture content changes of wood in the process of its drying is one of the important parameters to economy drying process and to keep the quality of dried wood. Wood samples, namely, spruce (Picea abies K.) and beech...
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Objectivization of phonological evaluation of speech elements by means of audio parametrization
PublicationThis study addresses two issues related to both machine- and subjective-based speech evaluation by investigating five phonological phenomena related to allophone production. Its aim is to use objective parametrization and phonological classification of the recorded allophones. These allophones were selected as specifically difficult for Polish speakers of English: aspiration, final obstruent devoicing, dark lateral /l/, velar nasal...
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A Critical Reanalysis of Uncontrollable Washboarding Phenomenon in Metal Band Sawing
PublicationThe article analyzes the cutting process of hard bars. Investigations conducted in industrial conditions demonstrated the presence of surface errors in the machined workpieces in the form of washboard patterns. The purpose of this study was to analyze the results of cutting on band sawing machines with different band saw blades. The cutting processes were conducted on three different horizontal band sawing machine types. Analyzed...
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Hydrophobic deep eutectic solvents as “green” extraction media for polycyclic aromatic hydrocarbons in aqueous samples
PublicationThe paper presents novel nonionic and hydrophobic deep eutectic solvents which were synthesized from natural compounds, i.e., thymol, ±camphor, decanoic and 10-undecylenic acids. Fundamental physicochemical properties of the synthesized deep eutectic solvents were determined, followed by their application as extractants in ultrasound-assisted dispersive liquid-liquid microextraction to isolate and enrich polycyclic aromatic hydrocarbons...
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Determination of cyanide in urine and saliva samples by ion chromatography with pulsed amperometric detection
PublicationCommonly known as a highly toxic chemical, cyanide is also an essential reagent for many industrial processes. It naturally occurs in plant seeds as a cyanogenic glycosides. Another relatively common mode of cyanide exposure is inhalation of environmental tobacco smoke. This study concerns importance to determine cyanide ion in human biological samples. Urine and saliva samples were collected healthy volunteers exposed to tobacco...
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Uncertainty of antioxidant profiling in complex mixtures using liquid chromatography involving post-column derivatisation
PublicationThe main goal of this paper is to discuss the problems associated with antioxidant profiling in complex samples using a high-throughput HPLC system coupled with post-column derivatisation reactor. Based on the experimental data reported in the literature, we demonstrated that improper optimisation of temperature and/or pH assay conditions performed using an on-line derivatisation reactor may substantially change the antioxidant...