Katalog Publikacji
Filtry
wszystkich: 63031
wyświetlamy 1000 najlepszych wyników Pomoc
Katalog Publikacji
Rok 2023
-
Cytokine IL6, but not IL-1β, TNF-α and NF-κB is increased in paediatric cancer patients
PublikacjaCytokines are responsible for maintaining homeostasis as cell growth, differentiation, migration and apoptosis mediators. They play a pivotal role in immune responses to inflammatory reactions. In oncological diseases, the cross-talk between cells of the immunological system and cells of the tumour microenvironment is led by cytokines. Also, the overproduction of cytokines may change the tumour microenvironment and stimulate tumour...
-
Cywilizacja wojny. Rosja w ideologii Dugina. Rozmowa prof. Zbigniewa Kaźmierczyka z ks. prof. Marcinem Składanowskim. Zapisała Katarzyna Wojan
Publikacja -
Czy chemia wszechświata różni się od chemii na planecie Ziemia?
PublikacjaAstronomowie, fizycy i chemicy od lat zadają sobie pytanie na ile nasza planeta jest wyjątkowa. Żyjemy na jednym z nielicznych ciał niebieskich, na którym występuje woda w stanie ciekłym. Na naszej planecie pojawiła się niezwykle szeroka gama prostych i wyjątkowo skomplikowanych związków organicznych. Warto jednak zadać pytanie czy faktycznie ziemia jest tak wyjątkowa pod kątem chemicznym, a jeśli tak to co na to wpływa. Współcześnie...
-
Czynniki kształtujące skuteczność outsourcingu w podmiotach leczniczych
PublikacjaProblem badawczy podjęty przez autorów tej książki można więc sformułować następująco: Jakie procesy podlegają outsourcingowi i jakie czynniki decydują o ich skuteczności w szpitalach w Polsce? W konsekwencji celem badawczym przyjętym w niniejszej pracy jest identyfikacja procesów zlecanych na zewnątrz w polskich szpitalach wraz z czynnikami warunkującymi ich skuteczność. Celem utylitarnym jest zaś opracowanie metody umożliwiającej...
-
Damage Detection in Composite Materials Using Hyperspectral Imaging
Publikacja -
Data and knowledge supporting decision-making for the urban Food-Water-Energy nexus
PublikacjaCities are hubs of innovation and wealth creation, and magnets for an increasing urban population. Cities also face unprecedented challenges in terms of food, water and energy scarcity, and governance and management. Urban environmental issues are no longer problems for experts to address but have become issues of public debate, in which knowledge from multiple sectors is needed to support inclusive governance approaches. Consequently,...
-
Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublikacjaIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
-
DATA INTEROPERABILITY AND THE OPEN DATA ECOSYSTEM: ROLES AND RESEARCH AREAS
PublikacjaSustainability and value-creation are considered important parameters to measure the success of an open data system. Unfortunately, existing open data systems are not meeting their promises to achieve a sustainable and value-based open data system. Van Loenen et al. (2021) proposed a sustainable and value-creating open data ecosystem. According to their study, the open data ecosystem needs to be user-driven, inclusive, circular,...
-
Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublikacjaThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
-
Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublikacjaIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
-
Dataset Related Experimental Investigation of Chess Position Evaluation Using a Deep Neural Network
PublikacjaThe idea of training Articial Neural Networks to evaluate chess positions has been widely explored in the last ten years. In this paper we investigated dataset impact on chess position evaluation. We created two datasets with over 1.6 million unique chess positions each. In one of those we also included randomly generated positions resulting from consideration of potentially unpredictable chess moves. Each position was evaluated...
-
Debonding of coin-shaped osseointegrated implants: Coupling of experimental and numerical approaches
PublikacjaWhile cementless implants are now widely used clinically, implant debonding still occur and is difficult to anticipate. Assessing the biomechanical strength of the bone–implant interface can help improving the understanding of osseointegration phenomena and thus preventing surgical failures. A dedicated and standardized implant model was considered. The samples were tested using a mode III cleavage device to assess the mechanical...
-
Decomposition of the induced magnetism degaussing problem for fast determination of currents in demagnetization coils wrapped outside an object under arbitrary external field conditions
PublikacjaSafe passage of ships in the presence of sea mines can be ensured by limiting or reducing the ship’s magnetic footprint. For vessels with plastic hulls, the main component that requires magnetic damping is the engine. Demagnetization of such an object can be achieved by wrapping it with coils and setting the direct current appropriately. For each specific geographic location, the currents in the coils can be determined iteratively...
-
Deep Eutectic Solvent Stir Bar Sorptive Extraction: A Rapid Microextraction Technique for the Determination of Vitamin D3 by Spectrophotometry
Publikacja -
Deep eutectic solvents – Ideal solution for clean air or hidden danger?
PublikacjaThe 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...
-
Deep eutectic solvents in analytical sample preconcentration Part B: Solid-phase (micro)extraction
PublikacjaOne 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...
-
Deep Eutectic Solvents: Properties and Applications in CO2 Separation
PublikacjaNowadays, 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...
-
Deep learning approach for delamination identification using animation of Lamb waves
Publikacja -
Deep learning super-resolution for the reconstruction of full wavefield of Lamb waves
Publikacja -
Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublikacjaAccurate 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...