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The experimental results of diesel fuel spray with marine engine injector
Dane BadawczeThe data set presents the measurement of the diesel fuel spray from with marine engine injector. The main target presents results is a study of the time course of macro parameters (spray tip penetration, spray cone angle) of fuel spray in the cylinder of marine diesel engine. The impact of ambient conditions and the geometrical parameters of the injector...
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Analysis of Factors Affecting Quality of Life in Patients Treated for Maxillofacial Fractures
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Kernel PCA in Application to Leakage Detection in Drinking Water Distribution System
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Kernel PCA in Application to Leakage Detection in Drinking Water Distribution System
PublikacjaMonitoring plays an important role in advanced control of complex dynamic systems. Precise information about system's behaviour, including faults detection, enables efficient control. Proposed method- Kernel Principal Component Analysis (KPCA), a representative of machine learning, skilfully takes full advantage of the well known PCA method and extends its application to nonlinear case. The paper explains the general idea of KPCA...
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Wykorzystanie sieci neuronowych do diagnostyki poprawności wykonania płytek drukowanych
PublikacjaArtykuł opisuje stanowisko badawcze do diagnostyki optycznej poprawności wykonania płytek drukowanych przesuwających się po taśmie produkcyjnej. Diagnostyka optyczna dokonywana jest poprzez kamerę. Obraz z kamery przekazywany jest do komputera PC, gdzie trafia do zaprojektowanego systemu diagnostycznego, zaimplementowanego w środowisku Matlab. Po odpowiednim przetworzeniu obrazy kierowane są do właściwego systemu diagnostycznego...
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Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublikacjaThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...
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Effect of User Mobility upon Trust Building among Autonomous Content Routers in an Information-Centric Network
PublikacjaThe capability of proactive in-network caching and sharing of content is one of the most important features of an informationcentric network (ICN). We describe an ICN model featuring autonomous agents controlling the content routers. Such agents are unlikely to share cached content with other agents without an incentive to do so. To stimulate cooperation between agents, we adopt a reputation and trust building scheme that is able...
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Rozpoznawanie obiektów przez głębokie sieci neuronowe
PublikacjaW referacie zaprezentowane zostaną wyniki badań nad rozpoznawaniem obiektów w różnych warunkach za pomocą głębokich sieci neuronowych. Przeanalizowano działanie dwóch struktur – ResNet50 oraz VGG19. Systemy rozpoznawania obrazu wytrenowano oraz przetestowano na reprezentatywnej, bazie zawierającej 25 tys. zdjęć psów oraz kotów, która znacznie upraszcza analizowanie działania systemów ze względu na łatwość interpretacji zdjęć przez...
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OBRONA SIECI INFORMACJOCENTRYCZNEJ PRZED ZATRUWANIEM TREŚCI PRZEZ NIEZAUFANYCH WYDAWCÓW Z UŻYCIEM MODELU INFEKCJI W GRAFACH
PublikacjaSieci informacjocentryczne narażone są na ataki zatruwania treści przez intruza, który przejął klucz prywatny wydawcy treści. Efektem jest podmiana treści oryginalnych na zatrute. W pracy zaproponowano model ataku opierający się na analogii z procesami infekcji w grafach i przeanalizowano prosty mechanizm obronny. Symulacje przeprowadzone w sieciach informacjocentrycz-nych o topologiach...
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The 41Σ+ electronic state of LiCs molecule
PublikacjaThe 41Σ+ state of LiCs molecule is observed experimentally for the first time. The inverted perturbation approach (IPA) method is used to derive the potential energy curve of the state from the measured spectra. The experiment is accompanied by theoretical calculations of adiabatic potentials for excited states in LiCs including 41Σ+, performed with the MOLPRO program package. The irregular shape of the 41Σ+ state potential predicted...
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Determination of Urinary Pterins by Capillary Electrophoresis Coupled with LED-Induced Fluorescence Detector
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Synthesis and Characterization of Poly(zwitterionic) Structures for Energy Conversion and Storage
PublikacjaZwitterions are unique class of molecules that possess two functional groups bearing electric charges, one positive and second negative. This setup results in peculiar properties such as high water retention and anti-fouling capability. Therefore, zwitterionic coatings and gels are commonly applied in e.g. biosensing and bioelectronic devices. Despite those applications, there are other perspectives for zwitterionic materials....
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Supervised model predictive control of wastewater treatment plant
PublikacjaAn optimizing control of a wastewater treatment plant (WWTP), allowing for cost savings over long time period and fulfilling effluent discharge limits at the same time, requires application of advanced control techniques. Model Predictive Control (MPC) is a very suitable control technology for a synthesis of such a truly multivariable controller that can handle constraints and accommodate model-based knowledge combined with hard...
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Data augmentation for improving deep learning in image classification problem
PublikacjaThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Analiza istotności cech znamion skórnych dla celów diagnostyki czerniaka złośliwego
PublikacjaPomimo dynamicznego rozwoju metod uczenia maszynowego i ich wdrażania do praktyki lekarskiej, automatyczna analiza znamion skórnych wciąż jest nierozwiązanym problemem. Poniższy artykuł proponuje zastosowanie algorytmu ewolucyjnego do zaprojektowania, wytrenowania i przetestowania całych populacji klasyfikatorów (sztucznych sieci neuronowych) oraz ich iteracyjnego udoskonalania w każdej kolejnej populacji, w celu osiągnięcia jak...
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The impact of last 15 minutes of surgery on the hemorrhagic complications after laparoscopic sleeve gastrectomy. Case-control study
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The impact of the last ten minutes of surgery on hemorrhagic complications after laparoscopic sleeve gastrectomy. Case-control study
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Data-driven models for fault detection using kernel PCA: A water distribution system case study
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Pipeline System for Heat Transportation from Nuclear Power Plant – an Optimizing Approach
PublikacjaOver the last few years heat piping insulation technology and pump systems efficiency have been significantly improved. Reduced thermal losses encourage heat transportation over long distances. It provides an opportunity for increasing thermodynamic efficiency of Nuclear Power Plants (NPPs) that are often located in rural areas because of safety issues. It can be achieved by Combined Heat and Power (CHP) generation, as heat produced...
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Optimising approach to designing kernel PCA model for diagnosis purposes with and without a priori known data reflecting faulty states
PublikacjaFault detection plays an important role in advanced control of complex dynamic systems since precise information about system condition enables efficient control. Data driven methods of fault detection give the chance to monitor the plant state purely based on gathered measurements. However, they especially nonlinear, still suffer from a lack of efficient and effective learning methods. In this paper we propose the two stages learning...
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BADANIE EFEKTYWNOŚCI WYKRYWANIA ANOMALII PROCESOWYCH W DZIAŁANIU TURBINY PAROWEJ ELEKTROWNI JĄDROWEJ PRZY POMOCY METOD WIELOWYMIAROWEJ ANALIZY STATYSTYCZNEJ
PublikacjaW artykule przedstawiono analizę możliwości wykrywania anomalii procesowych w działaniu turbiny parowej elektrowni jądrowej przy pomocy metod wielowymiarowej analizy statystycznej. Zasymulowano symptomy dwóch rodzajów uszkodzeń turbiny parowej tj. uderzenie wodne oraz, wyciek pary z zaworu części niskoprężnej. Jako narzędzie diagnostyczne wykorzystano Metodę Składników Podstawowych PCA (z ang. Principal Component Analysis). Jako...
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ANALIZA MOŻLIWOŚCI ZASTOSOWANIA STEROWANIA PREDYKCYJNEGO TURBINĄ PAROWĄ ELEKTROWNI JĄDROWEJ
PublikacjaArtykuł przedstawia wyniki wstępnej analizy możliwości zastosowania sterowania predykcyjnego MPC turbiną parową elektrowni jądrowej. Tradycyjnie przyjmuje się, że turbina pracuje w jednym punkcie pracy odpowiadającym jej mocy nominalnej, co pozwala na stosowanie klasycznych regulatorów PID. Synteza sterowania dla warunków zmiennego punktu pracy wymaga uwzględnienia nieliniowego charakteru procesów turbiny oraz możliwości naruszania...
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Application of data driven methods in diagnostic of selected process faults of nuclear power plant steam turbine
PublikacjaArticle presents a comparison of process anomaly detection in nuclear power plant steam turbine using combination of data driven methods. Three types of faults are considered: water hammering, fouling and thermocouple fault. As a virtual plant a nonlinear, dynamic, mathe- matical steam turbine model is used. Two approaches for fault detection using one class and two class classiers are tested and compared.
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Multicriteria Optimization Approach to Design and Operation of District Heating Supply System over its Life Cycle
PublikacjaDistrict Heating (DH) systems are commonly supplied using local heat sources. Nowadays, modern insulation materials allow for effective and economically viable heat transportation over long distances (over 20 km). In the paper a method for optimized selection of design and operating parameters of long distance Heat Transportation System (HTS) is proposed. The method allows for evaluation of feasibility and effectivity of heat transportation...
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe 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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Decision support system for design of long distance heat transportation system
PublikacjaDistrict Heating (DH) systems are commonly supplied using local heat sources. Nowadays, modern insulation materials allow for effective and economically viable heat transportation over long distances (over 20 km). The paper proposes a Decision Support System (DSS) for optimized selection of design and operating parameters of a long distance Heat Transportation System (HTS). The method allows for evaluation of feasibility and effectiveness...
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Deep neural network architecture search using network morphism
PublikacjaThe 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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Diagnozowanie stanu retinopatii cukrzycowej przy pomocy głębokich sieci neuronowych
PublikacjaW referacie opisano problem wykrywania oraz klasyfikacji stanu retinopatii cukrzycowej ze zdjęć dna oka przy pomocy głębokich sieci neuronowych. Retinopatia cukrzycowa jest chorobą oczu często występującą u osób z cukrzycą. Nieleczona prowadzi do uszkodzenia wzroku, a nawet ślepoty. W pracy badawczej opracowano system wykrywania retinopatii cukrzycowej na podstawie zdjęć dna oka. Opracowana sieć neuronowa przypisuje stan choroby...
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Data-driven models for fault detection using kernel pca:a water distribution system case study
PublikacjaKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
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Intelligent control structure for control of integrated wastewater systems.
PublikacjaArtykuł przedstawia podejście do tworzenia struktury sterowania zintegrowanym systemem oczyszczania ścieków (sieć kanalizacyjna- oczyszczalnia ścieków), w pełnym zakresie jego obciążeń hydraulicznych. System sterowania jest hierarchicznie zdekomponowany, tworząc wielopoziomową-wielowarstwową. Główną technologią sterowania wykorzystaną na poziomie optymalizacyjnym jest krzepkie sterowanie predykcyjne (RMPC) przy obecności niepewności...
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Functionalization of indium-tin-oxide electrodes by laser-nanostructured gold thin films for biosensing applications
Publikacjaof a relatively large area formed by pulsed laser nanostructuring of thin gold films arereported and discussed. The SEM inspection of modified electrodes reveals the presence of the nearlyspherical and disc-shaped particles of dimensions in the range of 40–120 nm. The NP-array geometry canbe controlled by selection of the laser processing conditions. It is shown that particle size and packingdensity of the array are important factors...
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The interaction of the pulsed laser irradiation with titania nanotubes - Theoretical studies on the thermal effect
PublikacjaThis paper reports temperature dispersion simulations of titania nanotubes irradiated by the 355 nm, pulsed, nanosecond laser. The modelling with the use of Finite Elements Method concerns titania nanotubes of the length and the wall thickness in the range of 0.5–2 μm and 5–20 nm, respectively. The uniqueness of the morphology was preserved by ensuring the wall thickness variation along the height of the tube, which was determined...
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Review on robust laser light interaction with titania – Patterning, crystallisation and ablation processes
PublikacjaTitanium dioxide is regarded as a very promising semiconducting material that is widely applied in many everyday-use products, devices, and processes. In general, those applications can be divided into energy or environmental categories, where a high conversion rate, and energy and power density are of particular interest. Therefore, many efforts are being put towards the elaboration of novel production routes, and improving the...
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A facile method for Tauc exponent and corresponding electronic transitions determination in semiconductors directly from UV–Vis spectroscopy data
PublikacjaIn this work, a facile method allowing for estimation of the exponent in the Tauc equation directly from the UV–vis spectra is presented. It is based on the Taylor expansion of the logarithmic version of the Tauc equation. The Tauc exponent is calculated from the tangent slope of the absorption data. Knowledge of this coefficient provides information about the optical transition types and is used as an input for the calculations...
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A Flexible Nafion Coated Enzyme‐free Glucose Sensor Based on Au‐dimpled Ti Structures
PublikacjaThe detection of glucose at low concentrations using electrochemical sensors is of great importance due to the possibility of using different human body fluids than blood, such as e.g. urine, saliva, sweat or tears. The interest behind those biofluids is related to their utility in non-invasive sugar determination. In this work, we present flexible, fully biocompatible electrode material based on Au nanoparticles immobilized onto...
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Research of IPM electrical machine with flux barriers
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SYSTEM WSPOMAGAJĄCY DIAGNOSTYKĘ CZERNIAKA ZŁOŚLIWEGO PRZY POMOCY METOD PRZETWARZANIA OBRAZU I ALGORYTMÓW INTELIGENCJI OBLICZENIOWEJ
PublikacjaNowotwory skóry są najczęściej spotykanymi nowotworami na świecie. Czerniaki złośliwe stanowią od około 5 do 7% wszystkich nowotworów złośliwych skóry u człowieka. Ich wczesne zdiagnozowanie jest kluczowym czynnikiem w późniejszej pomyślnej terapii. Niniejsza praca zawiera propozycję rozwinięcia i zautomatyzowania najważniejszej metody diagnozowania czerniaków, metody ABCD Stoltza. W artykule przedstawiono koncepcję i implementację...
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Neural Architecture Search for Skin Lesion Classification
PublikacjaDeep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture. This is a tedious and time-consuming process that requires expert knowledge. Different tasks need very different architectures to obtain satisfactory results. The group of methods called the neural architecture search (NAS) helps to find effective architecture...
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Intelligent system supporting diagnosis of malignant melanoma
PublikacjaMalignant melanomas are the most deadly type of skin cancers. Early diagnosis is a key for successful treatment and survival. The paper presents the system for supporting the process of diagnosis of skin lesions in order to detect a malignant melanoma. The paper describes the development process of an intel-ligent system purposed for the diagnosis of malignant melanoma. Presented sys-tem can be used as a decision support system...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe 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 neural networks approach to skin lesions classification — A comparative analysis
PublikacjaThe 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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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublikacjaMalignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublikacjaMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublikacjaIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublikacjaDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublikacjaTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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TOWARDS EXPLAINABLE CLASSIFIERS USING THE COUNTERFACTUAL APPROACH - GLOBAL EXPLANATIONS FOR DISCOVERING BIAS IN DATA
PublikacjaThe paper proposes summarized attribution-based post-hoc explanations for the detection and identification of bias in data. A global explanation is proposed, and a step-by-step framework on how to detect and test bias is introduced. Since removing unwanted bias is often a complicated and tremendous task, it is automatically inserted, instead. Then, the bias is evaluated with the proposed counterfactual approach. The obtained results...
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Expression of a GDSL esterase from Pseudomonas sp. S9 in Pichiapastoris
PublikacjaCold active lipolytic enzymes are promising to replace the conventional enzymes processes of biotechnological industries. One of the most important feature of the cold-active lipases and esterases is that they offer economic benefits through energy saving. In general, they exhibit high activity at low temperatures and low thermostability at moderate temperatures. Lipolytic enzyme EstS9 was isolated from Pseudomonas sp. S9. A multiple...
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BIOSYNTEZA ESTERAZY Z PSEUDOMONAS SP. S9 W KOMÓRKACH PICHIA PASTORIS, OCZYSZCZANIE I CHARAKTERYSTYKA
PublikacjaEnzymy lipolityczne ze względu na swoje unikalne właściwości takie jak stereo-, chemo- i regiospecyficzność znajdują szereg zastosowań w różnych gałęziach przemysłu. Lipazy i esterazy wykorzystywane są w przemyśle chemicznym, farmaceutycznym, spożywczym oraz w syntezie organicznej. W ramach wcześniejszych badań zidentyfikowałam i scharakteryzowałam aktywną w niskiej temperaturze esterazę z Pseudomonas sp. S9. Esteraza Pseudomonas...
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An NO2 sensor based on WO3 thin films for automotive applications in the microwave frequency range
PublikacjaA microwave system dedicated to the detection of nitrogen dioxide in the harsh environment of the Norway highways is proposed. An optimized transmission line type of sensor coated with a tungsten trioxide thin film that changes its electrical properties under NO2 gas exposure is developed. The sensors' response (S) is given in °/GHz and it is calculated based on wideband measurements. The advantage of wideband measurements in comparison...