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Search results for: anna brillowska-Dąbrowska
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Reduced-Cost Microwave Design Closure by Multi-Resolution EM Simulations and Knowledge-Based Model Management
PublicationParameter adjustment through numerical optimization has become a commonplace of contemporary microwave engineering. Although circuit theory methods are ubiquitous in the development of microwave components, the initial designs obtained with such tools have to be further tuned to improve the system performance. This is particularly pertinent to miniaturized structures, where the cross-coupling effects cannot be adequately accounted...
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Expedited Globalized Antenna Optimization by Principal Components and Variable-Fidelity EM Simulations: Application to Microstrip Antenna Design
PublicationParameter optimization, also referred to as design closure, is imperative in the development of modern antennas. Theoretical considerations along with rough dimension adjustment through supervised parameter sweeping can only yield initial designs that need to be further tuned to boost the antenna performance. The major challenges include handling of multi-dimensional parameter spaces while accounting for several objectives and...
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Reduced-Cost Design Optimization of High-Frequency Structures Using Adaptive Jacobian Updates
PublicationElectromagnetic (EM) analysis is the primary tool utilized in the design of high-frequency structures. In vast majority of cases, simpler models (e.g., equivalent networks or analytical ones) are either not available or lack accuracy: they can only be used to yield initial designs that need to be further tuned. Consequently, EM-driven adjustment of geometry and/or material parameters of microwave and antenna components is a necessary...
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Expedited Design Closure of Antenna Input Characteristics by Trust Region Gradient Search and Principal Component Analysis
PublicationOptimization-based parameter tuning has become an inherent part of contemporary antenna design process. For the sake of reliability, it is typically conducted at the level of full-wave electromagnetic (EM) simulation models. This may incur considerable computational expenses depending on the cost of an individual EM analysis, the number of adjustable variables, the type of task (local, global, single-/multi-objective optimization),...
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Quasi-Global Optimization of Antenna Structures Using Principal Components and Affine Subspace-Spanned Surrogates
PublicationParametric optimization is a mandatory step in the design of contemporary antenna structures. Conceptual development can only provide rough initial designs that have to be further tuned, often extensively. Given the topological complexity of modern antennas, the design closure necessarily involves full-wave electromagnetic (EM) simulations and—in many cases—global search procedures. Both factors make antenna optimization a computationally...
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Resonator-Loaded Waveguide Notch Filters with Broad Tuning Range and Additive-Manufacturing-Based Operating Frequency Adjustment Procedure
PublicationThis article presents a new class of ring-resonator-loaded waveguide notch filters with a broad tuning range, low cost, and improved performance. The proposed approach employs a comple-mentary asymmetric split ring resonator coupled to a microstrip transmission line and excited in a rectangular waveguide. An equivalent circuit model is proposed to explain the working principle of the proposed notch filter. The adjustment of the...
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Frequency-Based Regularization for Improved Reliability Optimization of Antenna Structures
PublicationThe paper proposes a modified formulation of antenna parameter tuning problem. The main ingredient of the presented approach is a frequency-based regularization. It allows for smoothening the functional landscape of the assumed cost function, defined to encode the prescribed design specifications. The regularization is implemented as a special penalty term complementing the primary objective and enforcing the alignment of the antenna...
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Low-cost multi-criterial design optimization of compact microwave passives using constrained surrogates and dimensionality reduction
PublicationDesign of contemporary microwave circuits is a challenging task. Typically, it has to take into account several performance requirements and constraints. The design objectives are often conflicting and their simultaneous improvement may not be possible; instead, compromise solutions are to be sought. Representative examples are miniaturized microwave passives where reduction of the circuit size has a detrimental effect on its electrical...
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Cost-Efficient Two-Level Modeling of Microwave Passives Using Feature-Based Surrogates and Domain Confinement
PublicationA variety of surrogate modelling techniques has been utilized in high-frequency design over the last two decades. Yet, the curse of dimensionality still poses a serious challenge in setting up re-liable design-ready surrogates of modern microwave components. The difficulty of the model-ing task is only aggravated by nonlinearity of circuit responses. Consequently, constructing a practically usable surrogate model, valid across...
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Expedited Yield Optimization of Narrow- and Multi-Band Antennas Using Performance-Driven Surrogates
PublicationUncertainty quantification is an important aspect of engineering design, also pertaining to the development and performance evaluation of antenna systems. Manufacturing tolerances as well as other types of uncertainties, related to material parameters (e.g., substrate permittivity) or operating conditions (e.g., bending) may affect the antenna characteristics. In the case of narrow- or multi-band antennas, this usually leads to...
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Design-Oriented Two-Stage Surrogate Modeling of Miniaturized Microstrip Circuits with Dimensionality Reduction
PublicationContemporary microwave design heavily relies on full-wave electromagnetic (EM) simulation tools. This is especially the case for miniaturized devices where EM cross-coupling effects cannot be adequately accounted for using equivalent network models. Unfortunately, EM analysis incurs considerable computational expenses, which becomes a bottleneck whenever multiple evaluations are required. Common simulation-based design tasks include...
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Cost-Efficient Bi-Layer Modeling of Antenna Input Characteristics Using Gradient Kriging Surrogates
PublicationOver the recent years, surrogate modeling has been playing an increasing role in the design of antenna structures. The main incentive is to mitigate the issues related to high cost of electromagnetic (EM)-based procedures. Among the various techniques, approximation surrogates are the most popular ones due to their flexibility and easy access. Notwithstanding, data-driven modeling of antenna characteristics is associated with serious...
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Badania procesów degradacji wybranych związków organicznych w próbkach wód powierzchniowych i w rozpuszczalnikach organicznych.
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On Memory-Based Precise Calibration of Cost-Efficient NO2 Sensor Using Artificial Intelligence and Global Response Correction
PublicationNitrogen dioxide (NO2) is a prevalent air pollutant, particularly abundant in densely populated urban regions. Given its harmful impact on health and the environment, precise real-time monitoring of NO2 concentration is crucial, particularly for devising and executing risk mitigation strategies. However, achieving precise measurements of NO2 is challenging due to the need for expensive and cumbersome equipment. This has spurred...
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Exploring the Beam Squint Effects on Reflectarray Perfromance: A Comprehensive Analysis of the Specular and Scattered Reflection of the Unit Cell
PublicationIn this article, the phenomena of beam deviation in reflectarray is discussed. The radiation pattern of the unit cell, which plays a vital role in shaping the beam of the reflectarray, is analyzed by considering undesired specular and scattered reflections. These unwanted reflections adversely affect the pattern of the single unit cell, thereby reducing the overall performance of the reflectarray. To conduct our investigations,...
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Wideband High-Gain Low-Profile Series-Fed Antenna Integrated with Optimized Metamaterials for 5G millimeter Wave Applications
PublicationThis paper presents a series-fed four-dipole antenna with a broad bandwidth, high gain, and compact size for 5G millimeter wave (mm-wave) applications. The single dipole antenna provides a maximum gain of 6.2 dBi within its operational bandwidth, which ranges from 25.2 to 32.8 GHz. The proposed approach to enhance both gain and bandwidth involves a series-fed antenna design. It comprises four dipoles with varying lengths, and a...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublicationDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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Adaptive Hyperparameter Tuning within Neural Network-based Efficient Global Optimization
PublicationIn this paper, adaptive hyperparameter optimization (HPO) strategies within the efficient global optimization (EGO) with neural network (NN)-based prediction and uncertainty (EGONN) algorithm are proposed. These strategies utilize Bayesian optimization and multiarmed bandit optimization to tune HPs during the sequential sampling process either every iteration (HPO-1itr) or every five iterations (HPO-5itr). Through experiments using...
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Adaptive Sampling for Non-intrusive Reduced Order Models Using Multi-Task Variance
PublicationNon-intrusive reduced order modeling methods (ROMs) have become increasingly popular for science and engineering applications such as predicting the field-based solutions for aerodynamic flows. A large sample size is, however, required to train the models for global accuracy. In this paper, a novel adaptive sampling strategy is introduced for these models that uses field-based uncertainty as a sampling metric. The strategy uses...
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Efficient uncertainty quantification using sequential sampling-based neural networks
PublicationUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
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Constrained aerodynamic shape optimization using neural networks and sequential sampling
PublicationAerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...
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Design of a Coplanar Waveguide-Fed Wideband Compact-Size Circularly Polarized Antenna and polarization-sense alteration
PublicationThis paper presents the design and validation of a geometrically simple circularly polarized(CP) structure featuring flat gain in the sub-6 GHz 5th generation spectrum. The proposed structure is based on coplanar-waveguide-fed, modified wide slot etched in the ground plane. For generating CP waves, the coplanar ground planes are designed with slight asymmetry in both the horizontal and vertical directions. Furthermore, the ground...
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublicationAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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Enhanced uniform data sampling for constrained data‐driven modeling of antenna input characteristics
PublicationData-driven surrogates are the most popular replacement models utilized in many fields of engineering and science, including design of microwave and antenna structures. The primary practical issue is a curse of dimensionality which limits the number of independent parameters that can be accounted for in the modelling process. Recently, a performance-driven modelling technique has been proposed where the constrained domain of the...
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Bader Ginsburg, Ruth, oraz Hartnett, Mary i Williams, Wendy W. Moimi słowami. Przeł. Anna Halbersztat i Anna Klingofer-Szostakowska. Lublin: Fame Art, 2021 (ss. 400, ISBN 9788395409660)
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Fuzzy Methods and Models for a Team-Building Process
PublicationThis chapter contains an introduction to fuzzy-logic model-based approaches for a team-building process. Such appraches allow extending typical recruiting practice and selection processes to enable a wider and more precise assessment of a new team and/or existing team members, taking into account both their hard and soft skills. Moreover, as effectiveness of teams depends on the interpersonal skills and emotional intelligence...
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Role patterns in IT projects teams - design of a selection module using fuzzy logic techniques
PublicationPresented paper introduces an approach based on usage of role patterns and modelling by the use of fuzzy logic tool for selection process with limitation to the area of IT projects environment. The article shows a concept of role patterns structures and their further usage in process of forming a fuzzy model dedicated to candidate assessment process support
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Bandwidth-Controllable Third-Order Band Pass Filter Using Substrate Integrated Full- and Semi-Circular Cavities
PublicationThe article presents a novel circular substrate integrated waveguide (SIW) bandpass filter (BPF) with controllable bandwidth. The proposed BPF is configured using two microstrip feedlines, semi- circular SIW cavities, capacitive slots, and inductive vias. The circular cavity is bisected into two halves, with the two copies thereof being cascaded. Two bisected and cascaded structures obtained this way are subsequently connected...
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Analysis of Agricultural and Engineering Systems using Simulation Decomposition
PublicationThis paper focuses on the analysis of agricultural and engineering processes using simulation decomposition (SD). SD is a technique that utilizes Monte Carlo simulations and distribution decomposition to visually evaluate the source and the outcome of different portions of data. Here, SD is applied to three distinct processes: a model problem, a nondestructive evaluation testing system, and an agricultural food-water energy system....
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Neural Network-Based Sequential Global Sensitivity Analysis Algorithm
PublicationPerforming global sensitivity analysis (GSA) can be challenging due to the combined effect of the high computational cost, but it is also essential for engineering decision making. To reduce this cost, surrogate modeling such as neural networks (NNs) are used to replace the expensive simulation model in the GSA process, which introduces the additional challenge of finding the minimum number of training data samples required to...
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Optimal Design of Transmitarray Antennas via Low-Cost Surrogate Modelling
PublicationOver the recent years, reflectarrays and transmitarrays have been drawing a considerable attention due to their attractive features, including a possibility of realizing high gain and pencil-like radiation patterns without the employment of complex feeding networks. Among the two, transmitarrays seem to be superior over reflectarrays in terms of achieving high radiation efficiency without the feed blockage. Notwithstanding, the...
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Miniaturized Dual-Band SIW-Based Bandpass Filters Using Open-Loop Ring Resonators
PublicationThis article presents two novel architectures of dual-band substrate integrated waveguide (SIW) bandpass filters (BPFs). Initially, two identical open-loop ring resonators (OLRRs) are coupled face-to-face on the top of the SIW cavity to realize a dual-band single-pole BPF. To obtain two-pole dual-band characteristics, two OLRRs resonant units are assembled horizontally within the top metal layer of the SIW, which is a technique...
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Iterative Global Sensitivity Analysis Algorithm with Neural Network Surrogate Modeling
PublicationGlobal sensitivity analysis (GSA) is a method to quantify the effect of the input parameters on outputs of physics-based systems. Performing GSA can be challenging due to the combined effect of the high computational cost of each individual physics-based model, a large number of input parameters, and the need to perform repetitive model evaluations. To reduce this cost, neural networks (NNs) are used to replace the expensive physics-based...
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Optimization model of agile team’s cohesion
PublicationTeam’s cohesion is one of the most important factors of IT project execution effectiveness. Optimization of team’s cohesion gives the possibility of reducing the risk of project failure. It also allows to increase the teamwork efficiency and thus optimize time of tasks execution, increase the guarantee of maintaining the scope of the project and the chance of achieving a given level of products quality. This article presents determination...
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Uniwersyteckie Centrum Kompetencyjne Technologii Oprogramowania
PublicationPoniższy rozdział stanowi rodzaj case study, gdzie na przykładzie Uniwersyteckiego Centrum Kompetencyjnego Technologii Oprogramowania funkcjonującego przy Politechnice Gdańskiej przedstawiona została koncepcja powoływania i funkcjonowania centrów rozwijania technologii informatycznych tworzony przy uczelniach wyższych przy współpracy z partnerami biznesowymi. Przedstawione zostały potrzeby powoływania takich jednostek organizacyjnych,...
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Semantyczny portal wiedzy środowiskiem wsparcia procesów integracji uczelni i biznesu
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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...
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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublicationThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublicationThis work proposes a novel adaptive global surrogate modeling algorithm which uses two neural networks, one for prediction and the other for the model uncertainty. Specifically, the algorithm proceeds in cycles and adaptively enhances the neural network-based surrogate model by selecting the next sampling points guided by an auxiliary neural network approximation of the spatial error. The proposed algorithm is tested numerically...
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On Unsupervised Artificial-Intelligence-Assisted Design of Antennas for High-Performance Planar Devices
PublicationDesign of modern antenna structures is a challenging endeavor. It is laborious, and heavily reliant on engineering insight and experience, especially at the initial stages oriented towards the devel-opment of a suitable antenna architecture. Due to its interactive nature and hands-on procedures (mainly parametric studies) for validating suitability of particular geometric setups, typical antenna development requires many weeks...
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Stability studies of selected polycyclic aromatic hydrocarbons in different organic solvents and identification of their transformation products
PublicationGłównym problemem w laboratoriach analitycznych jest konserwacja próbek i ekstraktów przeznaczonych do analizy. Rozpatrując procesy degradacji z analitycznego punktu widzenia i związanej z tym wiarygodności uzyskiwanych wyników pod uwagę należy wziąć wpływ procesów degradacji w badanym elemencie środowiska na poziom stężenia składników śladowych; wpływ tych samych procesów na poziom składników śladowych w już pobranych próbkach...
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Degradacja związków organicznych w środowisku. Degradation of organic compounds in the environment
PublicationZwiązki organiczne w zależności od elementu środowiska, w jakim występują (gleba, osady denne, wody powierzchniowe i gruntowe), mogą ulegać - pod wpływem rozmaitych procesów chemicznych, fizycznych, biologicznych czy też foto-chemicznych - różnorakim przemianom. Przedstawiono drogi degradacji wybranych trwałych zanieczyszczeń organicznych w różnych warunkach. Omówiono problem pojawiania się produktów pośrednich w czasie degradacji...
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Degradacja związków organicznych w środowisku
PublicationOmówiono drogi degradacji wybranych trwałych zanieczyszczeń organicznych wróżnych warunkach oraz przedstawiono metodyki analityczne które są wykorzys-tywane w tego typu badaniach.
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Photodegradation and biodegradation study of benzo(a)pyrene in different liquid media.
PublicationPrzedstawiono wyniki badań dotyczące degradacji benzo(a)pirenu w różnych mediach ciekłych (woda, rozpuszczalniki organiczne). Zbadano wpływ różnych czynników : temperatura, czas przechowywania próbki, dostęp światła, obecność naturalnie występujących mikroorganizmów, na przebieg procesów degradacji benzo(a)pirenu. Degradacja w rozpuszczalnikach organicznych przebiega następująco: dichlorometan > acetonitryl >heksan > cykloheksan...
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The importance of degradation in the fate of selected organic compounds in the environment. Part II. Photodegradation and biodegradation
PublicationDegradacja jest naturalnym, wszechobecnym procesem rozkładu substancji organicznych obecnych w środowisku. Produkty degradacji lub pośrednie produkty rozkładu związków organicznych często wykazują inną toksyczność w stosunku do mikroorganizmów, zwierząt i ludzi niż związki wyjściowe. Procesy fotodegradacji i biodegradacji zachodzą zwykle jednocześnie. Fotodegradacja uznawana jest za wstępny proces, po którym następuje rozkład...
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The importance of degradation in the fate of selected organic compounds in the environment. Part. I. General considerations.
PublicationZwiązki organiczne, w zależności od elementu środowiska w jakim występują (gleba, osady denne, wody powierzzchniowe i gruntowe) mogą ulegać powolnym przemianom pod wpływem rozmaitych procesów fizycznych, chemicznych biologicznych czy też fotochemicznych. W pracy przedstawiono drogę degradacji wybranych trwałych zanieczyszczeń organicznych w różnych warunkach. Omówiono problem pojawiania się produktów pośrednich w czasie degradacji...
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Pathways and analytical tools in degradation studies of organic pollutants
PublicationWszystkie substancje chemiczne podlegają różnym procesom w wyniku wielu reakcji chemicznych, biochemicznych czy też fotochemicznych. W zależności od elementu środowiska w jakim znajduje się analit (np.: gleba, sedymenty, wody powierzchniowe i podziemne), może on ulegać powolnym przemianom w wyniku różnych procesów. W pracy przedstawiono niektóre drogi degradacji wybranych substancji w różnych warunkach. Omówiono problem identyfikacji...
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Stability studies of selected phenoxyacid herbicides in water samples and detrmination of their transformation products
PublicationZbadano procesy przemian fenoksykwasów (takich jak: 2,4-D, MCPA, mekoprop, dichlorprop) w różnych roztworach wodnych. Sprawdzono wpływ parametrów (światło, temperatura oraz czas przechowywania próbki) na stabilność fenoksykwasów. Oznaczeń końcowych dokonano przy użyciu techniki chromatografii cieczowej sprzężonej ze spektrometrem mas.