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Publikacje z roku 2022
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Nauka w świecie cyfrowym okiem młodego inżyniera - początki techniki wirtualnej rzeczywistości
- Karol Fidurski
- Przemysław Falkowski-Gilski
Istnieje wiele definicji wirtualnej rzeczywistości (VR – Virtual Reality), które mniej lub bardziej pokrywają się ze sobą w różnych obszarach naukowych. Obecnie, gdy używamy określenia „VR”, odnosi się ono konkretnie do obrazów generowanych komputerowo, które zostały specjalnie zaprojektowane tak, aby dostarczyć jak najbardziej immersyjnych wrażeń. Sporo opracowań mówi również, że VR musi być interaktywna. To odróżniałoby ją od takich rozwiązań jak filmy 3D, wideo 360 itp.
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Negative Poisson’s ratio from pentagons: A new auxetic structure combining three different auxetic mechanisms
- Szymon Winczewski
- Jarosław Rybicki
A novel class of two-dimensional auxetic structures based on the pentagon motif is proposed. Their mechanical properties are investigated by combining molecular mechanics simulations with a simple three-parameter mechanical model which assumes perfectly elastic behavior. It is predicted that the proposed structures – termed as double re-entrant honeycomb – may possess unique mechanical characteristics, which include complete and perfect auxeticity, as well as the negative Poisson’s ratio observed in both the tensile and compressive regimes. The behavior of the considered structures is explained in relation to well-known auxetic models. It is shown that the considered structures simultaneously implement three different mechanisms leading to a negative Poisson’s ratio: the opening of the re-entrant units, the rotation of the squares, and the flattening effect.
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Negative result about the construction of genuinely entangled subspaces from unextendible product bases
- Maciej Demianowicz
Unextendible product bases (UPBs) provide a versatile tool with various applications across different areas of quantum information theory. Their comprehensive characterization is thus of great importance and has been a subject of vital interest for over two decades now. An open question asks about the existence of UPBs, which are genuinely unextendible, i.e., they are not extendible even with biproduct vectors. In other words, the problem is to verify whether there exist genuinely entangled subspaces (GESs), subspaces composed solely of genuinely multiparty entangled states, complementary to UPBs. We solve this problem in the negative for many sizes of UPBs in different multipartite scenarios. In particular, in the all-important case of equal local dimensions, we show that there are always forbidden cardinalities for such UPBs, including the minimal ones corresponding to GESs of the maximal dimensions.
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
- Bartosz Puchalski
The paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected fractional operators. The paper investigates the impact of the number of neurons in the hidden layer, treated as a hyperparameter, on the quality of modeling error. Training of the established recurrent neural network was performed on synthetic data sets. Data for training was prepared based on the modified Grünwald-Letnikow definition of variable-order fractional operators suitable for numerical computing without memory effects. The research presented in this paper showed that recurrent network architecture based on GRU-type cells can satisfactorily approximate targeted simple yet functional variable-order fractional operators with minor modeling errors. The presented solution is a novel approach to the approximation of VO-FC operators. It has the advantage of automatic selection of neural approximator parameters by optimization based on data customized for specific requirements.
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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
- Krzysztof Laddach
- Rafał Łangowski
A problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and developing original specialised evolutionary operators. This resulted in a compromise between the size of neural network and its accuracy in capturing the response of the mathematical model under which it has been learnt. The research involved an extended validation study based on data generated from a mathematical model of an exemplary system as well as the fast processes occurring in a pressurised water nuclear reactor. The obtaining simulation results demonstrate the high effectiveness of the devised neural (black-box) models of dynamic systems with time delays.
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Neural network training with limited precision and asymmetric exponent
- Marek Blok
- Mariusz Pietrołaj
Along 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 and operational memory, but also computational power. Increasing complexity and variety of neural network architectures are vivid examples of such trends in the modern data-driven industry. In response to this situation, focusing on less demanding operations for inference and training of neural networks became a popular approach among many researchers to overcome resources related issues. This work aims to investigate one of the paths associated with the mentioned efficiency problems and shows the impact of floating-point precision limitation on convolutional neural networks, including experiments on various exponent and mantissa sizes. Additionally, authors explore floating-point numbers utilization and optimization techniques in the scope of neural network training. Based on conducted research a novel method of asymmetric exponent utilization is presented achieving almost identical accuracy of 32-bit floating-point parameters while training a neural network with only 12-bit variables without additional rounding.
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Neural Network-Based Sequential Global Sensitivity Analysis Algorithm
- Yen-Chen Liu
- Leifur Leifsson
- Sławomir Kozieł
- Anna Pietrenko-Dąbrowska
Performing 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 train the NNs accurately. In this work, a recently proposed NN-based GSA algorithm to accurately quantify the sensitivities is improved. The algorithm iterates over the number of samples required to train the NNs and terminates using an outer-loop sensitivity convergence criteria. The iterative surrogate-based GSA yields converged values for the Sobol’ indices and, at the same time, alleviates the specification of arbitrary accuracy metrics for the NN-based approximation model. In this paper, the algorithm is improved by enhanced NN modeling, which lead to an overall acceleration of the GSA process. The improved algorithm is tested numerically on problems involving an analytical function with three input parameters, and a simulation-based nondestructive evaluation problem with three input parameters.
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Neural networks and deep learning
- A. Pastor López-Monroy
- Jesus Garcia Salinas
In this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings for different scenarios and variants of CNNs. Finally, the third part presents Neural Networks for sequence modeling, in particular Recurrent Neural Networks (RNN), Gated Recurrent Units (GRU), Long Short-Term Memory (LSTM) and Attention Mechanisms. The description of the latter models are made in the context of different applications that allows to explain in a better way the details of each particular kind of neural network.
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Neuroeconomy and Neuromarketing: The Study of the Consumer Behaviour in the COVID-19 Context
- Juan Jose Blazquez-Resino
- Santiago Gutierrez-Broncano
- Edyta Gołąb-Andrzejak
To address the study of consumer behavior in the post-COVID-19 era, the present Research Topic brings together a set of papers that attempt to study how different factors triggered by the pandemic have achieved a significant effect on consumers' behavioral intentions. These papers examine different subtopics related to food, health products, collaborative economy and, of course, neuroscience. Globally, the objectives of this special issue try to broadly reach the different perspectives in the study of consumer behavior in the context of COVID-19, considering: - A study of the effects of COVID-19 on consumer behavior in the short term. - An analysis of the economic effects of COVID-19. - The social and psychological changes brought about by the current situation of social change. - A study of consumer behavior from the perspective of neuromarketing and/or neuroeconomics. - Forecasting of changes in habits and behaviors caused by COVID-19. - The development of new marketing and distribution systems aimed at meeting new market needs. - New retailing techniques adapted to consumer changes.
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Neuroobrazowanie u pacjentów uzależnionych od substancji psychoaktywnych
- Klaudia Malisz
Celem artykułu jest przedstawienie charakterystycznych zmian w obrębie mózgowia wynikających z zażywania substancji psychoaktywnych, możliwych do zaobserwowania za pomocą badań obrazowych.
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Neutral Dissociation of Pyridine Evoked by Irradiation of Ionized Atomic and Molecular Hydrogen Beams
- Tomasz Wąsowicz
The interactions of ions with molecules and the determination of their dissociation patterns are challenging endeavors of fundamental importance for theoretical and experimental science. In particular, the investigations on bond-breaking and new bond-forming processes triggered by the ionic impact may shed light on the stellar wind interaction with interstellar media, ionic beam irradiations of the living cells, ion-track nanotechnology, radiation hardness analysis of materials, and focused ion beam etching, deposition, and lithography. Due to its vital role in the natural environment, the pyridine molecule has become the subject of both basic and applied research in recent years. Therefore, dissociation of the gas phase pyridine (C5H5N) into neutral excited atomic and molecular fragments following protons (H+) and dihydrogen cations (H2+) impact has been investigated experimentally in the 5–1000 eV energy range. The collision-induced emission spectroscopy has been exploited to detect luminescence in the wavelength range from 190 to 520 nm at the different kinetic energies of both cations. High-resolution optical fragmentation spectra reveal emission bands due to the CH(A2Δ→X2Πr; B2Σ+→X2Πr; C2Σ+→X2Πr) and CN(B2Σ+→X2Σ+) transitions as well as atomic H and C lines. Their spectral line shapes and qualitative band intensities are examined in detail. The analysis shows that the H2+ irradiation enhances pyridine ring fragmentation and creates various fragments more pronounced than H+ cations. The plausible collisional processes and fragmentation pathways leading to the identified products are discussed and compared with the latest results obtained in cation-induced fragmentation of pyridine.
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New 2-[(4-Amino-6-N-substituted-1,3,5-triazin-2-yl)methylthio]-N-(imidazolidin-2-ylidene)-4-chloro-5-methylbenzenesulfonamide Derivatives, Design, Synthesis and Anticancer Evaluation
- Łukasz Tomorowicz
- Beata Żołnowska
- Krzysztof Szafrański
- Jarosław Chojnacki
- Ryszard Konopiński
- Ewa A. Grzybowska
- Jarosław Sławiński
- Anna Kawiak
In the search for new compounds with antitumor activity, new potential anticancer agents were designed as molecular hybrids containing the structures of a triazine ring and a sulfonamide fragment. Applying the synthesis in solution, a base of new sulfonamide derivatives 20–162 was obtained by the reaction of the corresponding esters 11–19 with appropriate biguanide hydrochlorides. The structures of the compounds were confirmed by spectroscopy (IR, NMR), mass spectrometry (HRMS or MALDI-TOF/TOF), elemental analysis (C,H,N) and X-ray crystallography. The cytotoxic activity of the obtained compounds toward three tumor cell lines, HCT-116, MCF-7 and HeLa, was examined. The results showed that some of the most active compounds belonged to the R1 = 4-trifluoromethylbenzyl and R1 = 3,5-bis(trifluoromethyl)benzyl series and exhibited IC50 values ranging from 3.6 μM to 11.0 μM. The SAR relationships were described, indicating the key role of the R2 = 4-phenylpiperazin-1-yl substituent for the cytotoxic activity against the HCT-116 and MCF- 7 lines. The studies regarding the mechanism of action of the active compounds included the assessment of the inhibition of MDM2-p53 interactions, cell cycle analysis and apoptosis induction examination. The results indicated that the studied compounds did not inhibit MDM2-p53 interactions but induced G0/G1 and G2/M cell cycle arrest in a p53-independent manner. Furthermore, the active compounds induced apoptosis in cells harboring wild-type and mutant p53. The compound design was conducted step by step and assisted by QSAR models that correlated the activity of the compounds against the HCT-116 cell line with molecular descriptors.
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New approach for the synthesis of Ag3PO4-graphene photocatalysts
- Łukasz Lewandowski
- Julia Zwara-Sidorko
- Anna Gołąbiewska
- Tomasz Klimczuk
- Grzegorz Trykowski
- Adriana Zaleska-Medynska
A facile and effective plasma sputtering method for the preparation of a visible light active photocatalyst - rhombic dodecahedral silver phosphate Ag3PO4 covered with nanographene (Ag3PO4-GR) with improved stability has been developed. Proposed method allows for the usage of readily available materials for nanographene sputtering and for easy scaling-up. The stability improvement, confirmed by visible light-induced phenol degradation experiment, could be attributed to the synergistic effect of the silver phosphate particles and graphene material allowing for migration of metallic silver nanoparticles from semiconductor’s surface to graphene body keeping the semiconductors surface “silver free”. Also due to its conductive properties, nanographene may additionally be preventing electron-hole recombination and metallic silver formation.
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New Architecture of Solid-State High-Voltage Pulse Generators
- Yahia Achour
- Jacek Starzyński
- Kazimierz Jakubiuk
The application of the nanosecond pulsed electric field (nsPEF) for biomedical treatments has gained more interest in recent decades due to the development of pulsed power technologies which provides the ability to control the electric field dose applied during tests. In this context, the proposed paper describes a new architecture of solid-state high-voltage pulse generators (SSHVPG) designed to generate fully customised sequences of quasi-rectangular pulses. The idea is based on the combination of semiconductor switches (IGBT/MOSFET) known for their flexibility and controllability with special magnetic switches to build compact and modular generators. The proposed structure is inspired by the most known pulse generator of Marx, but mixes its two variants for negative and positive polarities. Thus, the polarity of the generated pulses can be freely selected. In addition to that, the use of IGBTs/MOSFET ensures a tunable repetition rate and pulse width. The capacitors are charged via a series of magnetic switches and a flyback DC–DC converter which provides fast and efficient charging and also an adjustable amplitude of the output pulses. The design can be easily simplified giving two other modified structures, based on the same idea, for mono-polar operating (only positive or only negative pulses) with a reduced number of switches. A SPICE simulation of the generator and results of experimental tests carried out on a three stages generator are presented. The obtained results confirm the operating principle and the claimed performances of the new structure.
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New insights into modeling two-step nitrification in activated sludge systems – The effects of initial biomass concentrations, comammox and heterotrophic activities
- Mohamad-Javad Mehrani
- Dominika Sobotka
- Przemysław Kowal
- Jianhua Guo
- Jacek Mąkinia
In this study, the conventional two-step nitrification model was extended with complete ammonia oxidation (comammox) and heterotrophic denitrification on soluble microbial products. The data for model calibration/validation were collected at four long-term washout experiments when the solid retention time (SRT) and hydraulic retention time (HRT) were progressively reduced from 4 d to 1 d, with mixed liquor suspended solids (MLSS) of approximately 2000 mg/L at the start of each trial. A new calibration protocol was proposed by including a systematic calculation of the initial biomass concentrations and microbial relationships as the calibration targets. Moreover, the impact assessment of initial biomass concentrations (X) and maximum growth rates (µ) for ammonia-oxidizing bacteria (AOB), nitrite-oxidizing bacteria (NOB), comammox Nitrospira, and heterotrophs on the calibration accuracy were investigated using the response surface methodology (RSM). The RSM results revealed the strongest interaction of XAOB and µAOB on the model calibration accuracy. All the examined model efficiency measures confirmed that the extended model was accurately calibrated and validated. The estimated µ values were as follows: µAOB = 0.38±0.005 d-1, µNOB = 0.20±0.01 d-1, µCMX = 0.20±0.01 d-1, µHET = 1.0±0.03 d-1. For comparison, when using the conventional model, µAOB and µNOB increased respectively by 26 and 15% (µAOB = 0.48±0.02 d-1 and µNOB = 0.23±0.005 d-1). This study provides better understanding of the effects of the initial biomass composition and the accompanying processes (comammox and heterotrophic denitrification) on modeling two-step nitrification.
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New insights of nanomaterials usage toward superhydrophobic membranes for water desalination via membrane distillation: A review
- Emilia Gontarek-Castro
- Roberto Castro-Muñoz
- Marek Lieder
Membrane distillation (MD) is a promising technology for seawater desalination due to the ability to process high-salinity waters and the ability to be driven by low-grade or waste heat. However, practical applications of MD membranes are limited by the low vapor flux and fouling problem. Recently, there is a growing interest in developing novel MD membrane materials with enhanced hydrophobicity to improve the efficiency of desalination performance. Interestingly, the incorporation of nanomaterials for tailoring superhydrophobic properties of MD membranes has attracted enormous attention in MD. Herein, according to the new insights of the available literature data, the current trend for achieving superhydrophobic MD membranes by embedding inorganic nanomaterials is provided. The influence of the inorganic additives on membrane fouling, stability, separation performance, is also discussed. Finally, theoretical principles of MD, the milestones of the evolution of developing superhydrophobic membrane surfaces, and future trends are also given for the new readers in the field.
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New nanoadsorbent based on magnetic iron oxide containing 1,4,7,10-tetraazacyclododecane in outer chain (Fe3O4@SiO2-cyclen) for adsorption and removal of selected heavy metal ions Cd2+, Pb2+, Cu2+
- Amanda Kulpa-Koterwa
- Jacek Ryl
- Karolina Górnicka
- Paweł Niedziałkowski
Magnetic Fe3O4@SiO2-cyclen nanoparticles were prepared and used as adsorbent for Cd2+, Pb2+ and Cu2+ from aqueous solution removal process controlled with differential pulse anodic stripping voltammetry (DPASV) and hanging mercury drop electrode (HDME). Nanomaterial was synthesised in three-step process co-precipitation of Fe3O4 core, coating with silane and N-(3-(triethoxysilyl)propyl)-1,4,7,10-tetraazacyclododecane-1-carboxamide silane functionalisation. The effectiveness of each step of the synthesis was confirmed using scanning electron microscopy (SEM), high-resolution X-ray photoelectron spectroscopy (XPS), powder X-ray diffraction (pXRD) and fourier-transform infrared spectroscopy (FT-IR) techniques. The Fe3O4@SiO2-cyclen nanoparticles were employed for Cd2+, Pb2+ and Cu2+ ions elimination from individual and mixed solutions by carrying out titration with a suspension of nanocomposites. The binding level for all ions both in the individual solutions and in the mixture was very similar at high levels. For Cd2+ and Cu2+ ions sorption efficiency level was from 83% to 89%, while for Pb2+ ions it was slightly lower at the level over 73%. In all cases, the equilibrium adsorption capacity parameter was over 1 mg/g and reached definitely higher values for individual ions solutions. The research results revealed that Fe3O4@SiO2- cyclen nanoparticles can be a promising adsorbent for magnetic heavy metal ions water treatment agents.
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New Peptide Based Fluconazole Conjugates with Expanded Molecular Targets
- Wioletta Brankiewicz
- Joanna Okońska
- Katarzyna Serbakowska
- Jan Lica
- Marek Drab
- Natalia Ptaszyńska
- Anna Łęgowska
- Krzysztof Rolka
- Piotr Szweda
Infections of Candida spp. etiology are frequently treated with azole drugs. Among azoles, the most widely used in the clinical scenario remains fluconazole (FLC). Promising results in treatment of dangerous, systemic Candida infections demonstrate the advantages of combined therapies carried out with combinations of at least two different antifungal agents. Here, we report five conjugates composed of covalently linked FLC and cell penetrating or antimicrobial peptide: TP10-7-NH2, TP10-NH2, LFcinB(2-11)-NH2, LFcinB[Nle1,11]-NH2, and HLopt2-NH2, with aspects of design, chemical synthesis and their biological activities. Two of these compounds, namely FLCpOH-TP10-NH2 and FLCpOH-TP10-7-NH2, exhibit high activity against reference strains and fluconazole-resistant clinical isolates of C. albicans, including strains overproducing drug transporters. Moreover, both of them demonstrate higher fungicidal effects compared to fluconazole. Analysis performed with fluorescence and scanning electron microscopy as well as flow cytometry indicated the cell membrane as a molecular target of synthesized conjugates. An important advantage of FLCpOH-TP10-NH2 and FLCpOH-TP10-7-NH2 is their low cytotoxicity. The IC90 value for the human cells after 72 h treatment was comparable to the MIC50 value after 24 h treatment for most strains of C. albicans. In reported conjugates, FLC was linked to the peptide by its hydroxyl group. It is worth noting that conjugation of FLC by the nitrogen atom of the triazole ring led to practically inactive compounds. Two compounds produced by us and reported herein appear to be potential candidates for novel antifungal agents.
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New Performance Indices for Power System Stabilizers
- Michał Izdebski
- Robert Małkowski
- Piotr Miller
The subject of the article is issues related to innovative indices for power system stabilizers (PSSs). These new indices will be able to quickly show which PSS (among many other PSSs) is not working properly and that advanced optimization and simulation methods should be used to improve the PSS settings. The authors note the fact that the acceptance requirements for PSSs are different in various power systems. Moreover, the authors pay attention to the fact that transmission system operators (TSOs) often have different PSS requirements (tests) even though they work in the same large power system. The article reviews the requirements for the PSSs used by TSOs of various power systems. The need to supplement the required tests with new qualitative indices is demonstrated. In the paper, new performance indices are proposed to improve the evaluation of the PSS and to check the desired performance of the stabilizer. These indices are derived from the active power frequency response characteristic with PSS and without PSS (PSS ON and PSS OFF). Additionally, the new PSS indices allow the graphical visualization of the properties of all synchronous generators equipped with the PSS in a predefined area on a single 3D graph. Such visualization can be used to quickly detect weak points of the power system.
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New Simple and Robust Method for Determination of Polarity of Deep Eutectic Solvents (DESs) by Means of Contact Angle Measurement
- Łukasz Cichocki
- Dorota Warmińska
- Justyna Łuczak
- Andrzej Przyjazny
- Grzegorz Boczkaj
The paper presents a new method for evaluating the polarity and hydrophobicity of deep eutectic solvents (DESs) based on the measurement of the DES contact angle on glass. DESs consisting of benzoic acid derivatives and quaternary ammonium chlorides–tetrabutylammonium chloride (TBAC) and benzyldimethylhexadecylammonium chloride (16-BAC)—in selected molar ratios were chosen for the study. To investigate the DESs polarity, an optical goniometer and an ET(30) solvatochromic scale based on Reichardt’s dye were used. The research demonstrated the high accuracy and precision of the developed procedure. The simplicity of the examination and the availability of basic equipment allow for the implementation of the developed method in routine investigations of DESs.