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Gdańsk University of Technology

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  • Multiple Cues-Based Robust Visual Object Tracking Method
    • Baber Khan
    • Abdul Jalil
    • Ahmad Ali
    • Khaled Alkhaledi
    • Khizer Mehmood
    • Khalid Mehmood Cheema
    • Maria Murad
    • Hanan Tariq
    • Ahmed M. El-Sherbeeny
    2022 Full text Electronics

    Visual object tracking is still considered a challenging task in computer vision research society. The object of interest undergoes significant appearance changes because of illumination variation, deformation, motion blur, background clutter, and occlusion. Kernelized correlation filter- (KCF) based tracking schemes have shown good performance in recent years. The accuracy and robustness of these trackers can be further enhanced by incorporating multiple cues from the response map. Response map computation is the complementary step in KCF-based tracking schemes, and it contains a bundle of information. The majority of the tracking methods based on KCF estimate the target location by fetching a single cue-like peak correlation value from the response map. This paper proposes to mine the response map in-depth to fetch multiple cues about the target model. Furthermore, a new criterion based on the hybridization of multiple cues i.e., average peak correlation energy (APCE) and confidence of squared response map (CSRM), is presented to enhance the tracking efficiency. We update the following tracking modules based on hybridized criterion: (i) occlusion detection, (ii) adaptive learning rate adjustment, (iii) drift handling using adaptive learning rate, (iv) handling, and (v) scale estimation. We integrate all these modules to propose a new tracking scheme. The proposed tracker is evaluated on challenging videos selected from three standard datasets, i.e., OTB-50, OTB-100, and TC-128. A comparison of the proposed tracking scheme with other state-of-the-art methods is also presented in this paper. Our method improved considerably by achieving a center location error of 16.06, distance precision of 0.889, and overlap success rate of 0.824.

  • Multiple jets impingement – numerical analysis by the ζ-f and hybrid VLES turbulence models
    • Tomasz Kura
    • Elżbieta Fornalik-Wajs
    • Jan Wajs
    • Sasa Kenjeres
    2022

    Presented paper summarizes the Authors findings referring to the numerical analyses of the jet impinging phenomena in the case of complex jets configurations in various applications e.g. in the heat exchangers. Multiple jets interference resulting in the cross-flow and the surface curvature are the factors which impose the need of advanced turbulence models utilization. The outcome of the research based on the ζ-f turbulence model as the common part in the RANS and the hybrid VLES formulations, is discussed. The advantage of the VLES model in the analysis of the complex interaction between the impinging jets has been demonstrated.

  • Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
    • Andrzej Stateczny
    • Shanthi Mandekolu Bolugallu
    • Parameshachari Bidare Divakarachari
    • Kavithaa Ganesan
    • Jamuna Rani Muthu
    2022 Full text Remote Sensing

    Land 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 spectral feature bands are involved, but unexpectedly little consideration has been given to these characteristics in deep learning models. Due to the wide availability of RGB models in computer vision, this research mainly utilized RGB bands. Once the pre-processing is carried out for the images of the selected dataset, the hybrid feature extraction is performed using Haralick texture features, an oriented gradient histogram, a local Gabor binary pattern histogram sequence, and Harris Corner Detection to extract features from the images. After that, the Improved Mayfly Optimization (IMO) method is used to choose the optimal features. IMO-based feature selection algorithms have several advantages that include features such as a high learning rate and computational efficiency. After obtaining the optimal feature selection, the LULC classes are classified using a multi-class classifier known as the Multiplicative Long Short-Term Memory (mLSTM) network. The main functionality of the multiplicative LSTM classifier is to recall appropriate information for a comprehensive duration. In order to accomplish an improved result in LULC classification, a higher amount of remote sensing data should be processed. So, the simulation outcomes demonstrated that the proposed IMO-mLSTM efficiently classifies the LULC classes in terms of classification accuracy, recall, and precision. When compared with ConvNet and Alexnet, the proposed IMO-mLSTM method accomplished accuracies of 99.99% on Sat 4, 99.98% on Sat 6, and 98.52% on the Eurosat datasets.

  • Multispectral Imaging Using Fluorescent Properties of Indocyanine Green and Methylene Blue in Colorectal Surgery—Initial Experience
    • Wojciech Polom
    • Marcin Migaczewski
    • Jaroslaw Skokowski
    • Maciej Swierblewski
    • Tomasz Cwalinski
    • Leszek Kalinowski
    • Michal Pedziwiatr
    • Marcin Matuszewski
    • Karol Polom
    2022 Full text Journal of Clinical Medicine

    Introduction: Image-guided surgery is becoming a new tool in colorectal surgery. Intraoperative visualisation of different structures using fluorophores helps during various steps of operations. In our report, we used two fluorophores—indocyanine green (ICG), and methylene blue (MB)— during different steps of colorectal surgery, using one camera system for two separate near-infrared wavelengths. Material and methods: Twelve patients who underwent complex open or laparoscopic colorectal surgeries were enrolled. Intravenous injections of MB and ICG at different time points were administered. Visualisation of intraoperative ureter position and fluorescent angiography for optimal anastomosis was performed. A retrospective analysis of patients treated in our departments during 2020 was performed, and data about ureter injury and anastomotic site complications were collected. Results: Intraoperative localisation of ureters with MB under fluorescent light was possible in 11 patients. The mean signal-to-background ratio was 1.58 0.71. Fluorescent angiography before performing anastomosis using ICG was successful in all 12 patients, and none required a change in position of the planned colon resection for anastomosis. The median signal-to-background ratios was 1.25 (IQR: 1.22–1.89). Across both centres, iatrogenic injury of the ureter was found in 0.4% of cases, and complications associated with anastomosis was found in 5.5% of cases. Conclusions: Our study showed a substantial opportunity for using two different fluorophores in colorectal surgery, whereby the visualisation of one will not change the possible quantification analysis of the other. Using two separate dyes during one procedure may help in optimisation of the fluorescent properties of both dyes when using them for different applications. Visualisation of different structures by different fluorophores seems to be the future of image-guided surgery, and shows progress in optical technologies used in image-guided surgery.

  • Multi-task Video Enhancement for Dental Interventions
    • Efkleidis Katsaros
    • Piotr Kopa Ostrowski
    • Krzysztof Włódarczak
    • Emilia Lewandowska
    • Jacek Rumiński
    • Damian Siupka-Mróz
    • Łukasz Lassmann
    • Anna Jezierska
    • Daniel Węsierski
    2022

    A microcamera firmly attached to a dental handpiece allows dentists to continuously monitor the progress of conservative dental procedures. Video enhancement in video-assisted dental interventions alleviates low-light, noise, blur, and camera handshakes that collectively degrade visual comfort. To this end, we introduce a novel deep network for multi-task video enhancement that enables macro-visualization of dental scenes. In particular, the proposed network jointly leverages video restoration and temporal alignment in a multi-scale manner for effective video enhancement. Our experiments on videos of natural teeth in phantom scenes demonstrate that the proposed network achieves state-of-the-art results in multiple tasks with near real-time processing. We release Vident-lab at https://doi.org/10.34808/1jby-ay90, the first dataset of dental videos with multi-task labels to facilitate further research in relevant video processing applications.

  • Multi-Temporal Analysis of Changes of the Southern Part of the Baltic Sea Coast Using Aerial Remote Sensing Data
    • Krystyna Michałowska
    • Ewa Głowienka
    2022 Full text Remote Sensing

    Understanding processes that affect changes in the coastal zone and the ability to predict these processes in the future depends on the period for which detailed monitoring is carried out and on the type of coast. This paper analyzes a southern fragment of the Baltic coast (30 km), where there has been no anthropogenic impact (Slowinski National Park). The study was carried out covering a time interval of 65 years. Historic and current aerial photographs (orthophotomaps) from the following years: 1951, 1964, 1975, 1984, 1995, 2004, and 2016 were used. Changes in the position of the foredune toe line (FTL) in each years’ images were used. For each time interval (1951–1964, 1964–1975, 1975–1984, 1984–1995, 1995–2004, 2004–2016), the coastal area over which morphodynamic processes (erosion and accumulation) took place was calculated. The calculated RL (reference line)—FTL positions allowed us to determine differences in the shoreline course in subsequent years and to determine the extent of shifts/changes of the coastline in each time period. The study results showed an equilibrium between the processes of accumulation and erosion, proving that the development of the studied natural coastline is balanced. There was only a change in the trend of the characteristics of changes from erosive into accumulative ones and vice versa. Moreover, along the studied coast section, a certain periodicity in the coastline changes can be observed. The intervals where predominant erosion occurs alternate with those when accumulation prevails, and then the cycle repeats. The analysis of historic/current aerial images and orthophotomaps from 1951–2016 indicated that strong storms have a significant impact on the magnitude of change (accumulation/erosion) and the formation of the studied coastline.

  • Multivariate Statistical Analysis for Mutual Dependence Assessment of Selected Polyphenols, Organic Acids and Metals in Cool-Climate Wines
    • Magdalena Fabjanowicz
    • Vasil Simeonov
    • Marcin Frankowski
    • Wojciech Wojnowski
    • Justyna Płotka-Wasylka
    2022 Full text MOLECULES

    Polyphenols, organic acids and metal ions are an important group of compounds that affect the human health and quality of food and beverage products, including wines. It is known that a specific correlation between these groups exist. While wines coming from the New World and the Old World countries are extensively studied, wines coming from cool-climate countries are rarely discussed in the literature. One of the goals of this study was to determine the elemental composition of the wine samples, which later on, together as polyphenols and organic acids content, was used as input data for chemometric analysis. The multivariate statistical approach was applied in order to find specific correlations between the selected group of compounds in the cool-climate wines and the features that distinguish the most and differ between red and white wines and rosé wines. Moreover, special attention was paid to resveratrol and its correlation with selected wine constituents.

  • Muramyl dipeptide-based analogs as potential anticancer compounds: Strategies to improve selectivity, biocompatibility, and efficiency
    • Eliza Iwicka
    • Justyna Hajtuch
    • Krystyna Dzierzbicka
    • Iwona Inkielewicz-Stępniak
    2022 Full text Frontiers in Oncology

    According to the WHO, cancer is the second leading cause of death in the world. This is an important global problem and a major challenge for researchers who have been trying to find an effective anticancer therapy. A large number of newly discovered compounds do not exert selective cytotoxic activity against tumorigenic cells and have too many side effects. Therefore, research on muramyl dipeptide (MDP) analogs has attracted interest due to the urgency for finding more efficient and safe treatments for oncological patients. MDP is a ligand of the cytosolic nucleotide-binding oligomerization domain 2 receptor (NOD2). This molecule is basic structural unit that is responsible for the immune activity of peptidoglycans and exhibits many features that are important for modern medicine. NOD2 is a component of the innate immune system and represents a promising target for enhancing the innate immune response as well as the immune response against cancer cells. For this reason, MDP and its analogs have been widely used for many years not only in the treatment of immunodeficiency diseases but also as adjuvants to support improved vaccine delivery, including for cancer treatment. Unfortunately, in most cases, both the MDP molecule and its synthesized analogs prove to be too pyrogenic and cause serious side effects during their use, which consequently exclude them from direct clinical application. Therefore, intensive research is underway to find analogs of the MDP molecule that will have better biocompatibility and greater effectiveness as anticancer agents and for adjuvant therapy. In this paper, we review the MDP analogs discovered in the last 10 years that show promise for antitumor therapy. The first part of the paper compiles the achievements in the field of anticancer vaccine adjuvant research, which is followed by a description of MDP analogs that exhibit promising anticancer and antiproliferative activity and their structural changes compared to the original MDP molecule.

  • Musical Instrument Identification Using Deep Learning Approach
    • Maciej Blaszke
    • Bożena Kostek
    2022 Full text SENSORS

    The work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related to musical instrument identification. It focuses on tasks performed, input type, algorithms employed, and metrics used. The paper starts with the background presentation, i.e., metadata description and a review of related works. This is followed by showing the dataset prepared for the experiment and its division into subsets: training, validation, and evaluation. Then, the analyzed architecture of the neural network model is presented. Based on the described model, training is performed, and several quality metrics are determined for the training and validation sets. The results of the evaluation of the trained network on a separate set are shown. Detailed values for precision, recall, and the number of true and false positive and negative detections are presented. The model efficiency is high, with the metric values ranging from 0.86 for the guitar to 0.99 for drums. Finally, a discussion and a summary of the results obtained follows.

  • Mussel‐inspired biomaterials: From chemistry to clinic
    • Ali Taghizadeh
    • Mohsen Taghizadeh
    • Mohsen Khodadadi Yazdi
    • Payam Zarrintaj
    • Joshua D. Ramsey
    • Farzad Seidi
    • Florian J. Stadler
    • Haeshin Lee
    • Mohammad Saeb
    • Masoud Mozafari
    2022 Full text Bioengineering & Translational Medicine

    After several billions of years, nature still makes decisions on its own to identify, develop, and direct the most effective material for phenomena/challenges faced. Likewise, and inspired by the nature, we learned how to take steps in developing new technologies and materials innovations. Wet and strong adhesion by Mytilidae mussels (among which Mytilus edulis—blue mussel and Mytilus californianus—California mussel are the most well-known species) has been an inspiration in developing advanced adhesives for the moist condition. The wet adhesion phenomenon is significant in designing tissue adhesives and surgical sealants. However, a deep understanding of engaged chemical moieties, microenvironmental conditions of secreted proteins, and other contributing mechanisms for outstanding wet adhesion mussels are essential for the optimal design of wet glues. In this review, all aspects of wet adhesion of Mytilidae mussels, as well as different strategies needed for designing and fabricating wet adhesives are discussed from a chemistry point of view. Developed muscle-inspired chemistry is a versatile technique when designing not only wet adhesive, but also, in several more applications, especially in the bioengineering area. The applications of muscle-inspired biomaterials in various medical applications are summarized for future developments in the field.

  • Nanocząstki w chemioterapii: charakterystyka, strategie projektowania, mechanizm wnikania oraz degradacja wewnątrzkomórkowa
    • Joanna Pilch
    2022 Full text Postępy Biochemii

    Pomimo znaczącego postępu w leczeniu nowotworów skuteczne metody ich leczenia po-zostają ograniczone. Wciąż jedną z głównych metod terapii pozostaje chemioterapia, jednakże często wywołuje ona wiele efektów ubocznych. Związane jest to m. in. z brakiem istotnych różnic pomiędzy komórkami nowotworowymi a prawidłowymi, właściwościami fizykochemicznymi samych chemioterapeutyków, a także zjawiskiem lekooporności. W celu obniżenia działań niepożądanych oraz podniesienia specyficzności chemioterapeuty-ków względem komórek nowotworowych poszukiwane są nowe metody ich dostarczania do komórek guza. Jedną z nich jest zastosowanie nanocząstek (ang. Nanoparticles, NPs) jako platform transportujących. W niniejszym artykule przedstawiono charakterystykę NPs po-siadających zastosowanie w chemioterapii m. in.: kropek kwantowych, nanocząstek złota, dendrymerów, miceli oraz liposomów. Omówiono także strategię w projektowaniu i opty-malizacji syntezy nanocząstek oraz oceny różnych mechanizmów ich wnikania do komórek, jak również ich degradację wewnątrzkomórkową oraz toksyczność.

  • Nanomaterials for photothermal and photodynamic cancer therapy
    • Behzad Nasseri
    • Effat Alizadeh
    • Farhad Bani
    • Soodabeh Davaran
    • Abolfazl Akbarzadeh
    • Navid Rabiee
    • Ali Bahadori
    • Mojtaba Ziaei
    • Mojtaba Bagherzadeh
    • Mohammad Saeb
    • Masoud Mozafari
    • Michael R. Hamblin
    2022 Applied Physics Reviews

    In recent years, the role of optically sensitive nanomaterials has become powerful moieties in therapeutic techniques and has become particularly emphasized. Currently, by the extraordinary development of nanomaterials in different fields of medicine, they have found new applications. Phototherapy modalities, such as photothermal therapy (PTT) by toxic heat generation and photodynamic therapy (PDT) by reactive oxygen species, are known as promising phototherapeutic techniques, which can overcome the limitations of conventional protocols. Moreover, nanomaterial-based PDT and PTT match the simultaneous immune therapy and increase the immune system stimulation resulting from the denaturation of cancer cells. Nevertheless, nanomaterials should have sufficient biocompatibility and efficiency to meet PDT and PTT requirements as therapeutic agents. The present review focuses on the therapeutic potency of PDT, PTT, and also their combined modalities, which are known alternative protocols with minimal morbidity integrated into gold standard treatments such as surgery, chemotherapy, and radiation therapy at tumor treatment and cancer-related infectious diseases. In addition, for deeper understanding, photoablation effects with emphasis on the nature, morphology, and size of photosensitive nanomaterials in PDT and PTT were studied. Finally, transportation techniques and moieties needed as carriers of photosensitizers and photothermal therapy agents to hard-accessed regions, for example, cancerous regions, were investigated

  • Nanosorbents as Materials for Extraction Processes of Environmental Contaminants and Others
    • María José Santoyo Treviño
    • Sergio Zarazúa
    • Justyna Płotka-Wasylka
    2022 Full text MOLECULES

    The aim of this work focuses on the application of nanomaterials (NMs) in different sorp- tive extraction techniques for the analysis of organic contaminants from environmental samples of distinct matrix compositions. Without any doubt, the integration of specific NMs such as carbona- ceous nanomaterials, magnetic nanoparticles (MNPs), metal–organic frameworks (MOFs), silica na- noparticles, and ion-imprinted NPs with so lid-phase extraction techniques counting d-SPE, solid- phase microextraction (SPME), and stir bar sorptive extraction (SBSE) impact on the improvements in analytical performance. The application of NMs assorbents in the extraction of organic pollutants in environmental samples allows for providing better sensitivity, repeatability, reproducibility, and reusability.

  • Nanostructure of the laser-modified transition metal nanocomposites for water splitting
    • Jakub Wawrzyniak
    • Jakub Karczewski
    • Emerson Coy
    • Jacek Ryl
    • Katarzyna Grochowska
    • Siuzdak Katarzyna
    2022 Full text NANOTECHNOLOGY

    Although hydrogen is considered by many to be the green fuel of the future, nowadays it is primarily produced through steam reforming, which is a process far from ecological. Therefore, emphasis is being put on the development of electrodes capable of the efficient production of hydrogen and oxygen from water. To make the green alternative possible, the solution should be cost-efficient and well processable, generating less waste which is a huge challenge. In this work, the laser-based modification technique of the titania nanotubes containing sputtered transition metal species (Fe, Co, Ni, and Cu) was employed. The characteristics of the electrodes are provided both for the hydrogen and oxygen evolution reactions, where the influence of the laser treatment has been found to have the opposite effect. The structural and chemical analysis of the substrate material provides insight into pathways towards more efficient, low-temperature water splitting. Laser-assisted integration of transition metal with the tubular nanostructure results in the match-like structure where the metal species are accumulated at the head. The electrochemical data indicates a significant decrease in material resistance that leads to an overpotential of only +0.69 V at 10 mA/cm2 for nickel-modified material.

  • Natural fish oil improves the differentiation and maturation of oligodendrocyte precursor cells to oligodendrocytes in vitro after interaction with the blood–brain barrier
    • Paweł Piatek
    • Natalia Lewkowicz
    • Sylwia Michlewska
    • Marek Wieczorek
    • Radosław Bonikowski
    • Karol Parchem
    • Przemysław Lewkowicz
    • Magdalena Namiecinska
    2022 Full text Frontiers in Immunology

    The blood–brain barrier (BBB) tightly controls the microenvironment of the central nervous system (CNS) to allow neurons to function properly. Additionally, emerging studies point to the beneficial effect of natural oils affecting a wide variety of physiological and pathological processes in the human body. In this study, using an in vitro model of the BBB, we tested the influence of natural fish oil mixture (FOM) vs. borage oil (BO), both rich in longchain polyunsaturated fatty acids (LC-PUFAs) and monounsaturated fatty acids (MUFAs) such as oleic acid (C18:1n9c) or nervonic acid (NA), on human oligodendrocyte precursor cells (hOPCs) during their maturation to oligodendrocytes (OLs) regarding their ability to synthesize myelin peptides and NA. We demonstrated that FOM, opposite to BO, supplemented endothelial cells (ECs) and astrocytes forming the BBB, affecting the function of hOPCs during their maturation. This resulted in improved synthesis of myelin basic protein (MBP), myelin oligodendrocyte glycoprotein (MOG), proteolipid protein (PLP), and NA in mature OLs. This effect is probably the result of BBB cell and hOPC stimulation via free fatty acid receptors (FFARs), which increases insulin growth factor-1 (IGF-1), ciliary neurotrophic factor (CNTF), and brainderived neurotrophic factor (BDNF) and inhibits fibroblast growth factor 2 (FGF-2) synthesis. The unique formula of fish oil, characterized by much more varied components compared to those of BOs, also improved the enhancement of the tight junction by increasing the expression of claudin-5 and VE-cadherin on ECs. The obtained data justify consideration of naturally derived fish oil intake in human diet as affecting during remyelination.

  • Natural sweeteners: Sources, extraction and current uses in foods and food industries
    • Roberto Castro-Muñoz
    • Mariela Correa-Delgado
    • Rafael Córdova-Almeida
    • David Lara-Nava
    • Mariana Chávez-Muñoz
    • Valeria Fernanda Velásquez-Chávez
    • Carlos Eduardo Hernández-Torres
    • Emilia Gontarek-Castro
    • Mohd Zamidi Ahmad
    2022 Full text FOOD CHEMISTRY

    Food producers have leaned towards alternative natural and synthetic sweeteners in food formulations to satisfy market demands. Even so, several synthetic sweeteners (e.g., aspartame, saccharin, sucralose) are becoming less popular due to health-related concerns, lower nutritional values, and controversies around their safety. Conversely, natural sweeteners confer favourable customer perceptions due to their association to a healthier lifestyle and higher nutritional values. This article discusses the evidence of natural sweeteners in the available commercial products. A comprehensive review of natural sweeteners is presented, which includes their resources, properties and extraction methods, as well as a discussion on several emerging technologies that offer improvements to the traditional extraction methods. Finally, the progress of natural sweeteners in the food industry is assessed, and the commercial food products containing these natural sweeteners are mentioned.

  • Nauka w świecie cyfrowym okiem młodego inżyniera - jakość życia a jakość powietrza w miastach
    • Bartosz Pingot
    • Przemysław Falkowski-Gilski
    2022 Pismo PG

    Obecne w powietrzu zanieczyszczenia biorą udział w procesach zmian klimatycznych, a także bezpośrednio wpływają na ludzkie zdrowie, przejawiając toksyczność w wyższych stężeniach oraz zwiększając ryzyko występowania szerokiej gamy chorób. Jest to szczególnie niebezpieczne dla mieszkańców dużych miast oraz tych znajdujących się w grupach ryzyka. Dlatego też bardzo ważna pozostaje kwestia monitorowania stanu zanieczyszczenia powietrza w miastach.

  • Nauka w świecie cyfrowym okiem młodego inżyniera - początki techniki wirtualnej rzeczywistości
    • Karol Fidurski
    • Przemysław Falkowski-Gilski
    2022 Pismo PG

    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.

  • Negative Poisson’s ratio from pentagons: A new auxetic structure combining three different auxetic mechanisms
    • Szymon Winczewski
    • Jarosław Rybicki
    2022 COMPUTATIONAL MATERIALS SCIENCE

    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.

  • Negative result about the construction of genuinely entangled subspaces from unextendible product bases
    • Maciej Demianowicz
    2022 Full text PHYSICAL REVIEW A

    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.

  • Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
    • Bartosz Puchalski
    2022 Full text IEEE Access

    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.

  • Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
    • Krzysztof Laddach
    • Rafał Łangowski
    2022

    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.

  • Neural network training with limited precision and asymmetric exponent
    • Marek Blok
    • Mariusz Pietrołaj
    2022 Full text Journal of Big Data

    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.

  • Neural Network-Based Sequential Global Sensitivity Analysis Algorithm
    • Yen-Chen Liu
    • Leifur Leifsson
    • Sławomir Kozieł
    • Anna Pietrenko-Dąbrowska
    2022

    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.

  • Neural networks and deep learning
    • A. Pastor López-Monroy
    • Jesus Garcia Salinas
    2022

    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.

  • Neuroeconomy and Neuromarketing: The Study of the Consumer Behaviour in the COVID-19 Context
    • Juan Jose Blazquez-Resino
    • Santiago Gutierrez-Broncano
    • Edyta Gołąb-Andrzejak
    2022 Full text Frontiers in Psychology

    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.

  • Neuroobrazowanie u pacjentów uzależnionych od substancji psychoaktywnych
    • Klaudia Malisz
    2022 INŻYNIER I FIZYK MEDYCZNY

    Celem artykułu jest przedstawienie charakterystycznych zmian w obrębie mózgowia wynikających z zażywania substancji psychoaktywnych, możliwych do zaobserwowania za pomocą badań obrazowych.

  • Neutral Dissociation of Pyridine Evoked by Irradiation of Ionized Atomic and Molecular Hydrogen Beams
    • Tomasz Wąsowicz
    2022 Full text INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

    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.

  • 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
    2022 Full text INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

    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.

  • New approach for the synthesis of Ag3PO4-graphene photocatalysts
    • Łukasz Lewandowski
    • Julia Zwara-Sidorko
    • Anna Gołąbiewska
    • Tomasz Klimczuk
    • Grzegorz Trykowski
    • Adriana Zaleska-Medynska
    2022 Full text MATERIALS SCIENCE IN SEMICONDUCTOR PROCESSING

    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.

  • New Architecture of Solid-State High-Voltage Pulse Generators
    • Yahia Achour
    • Jacek Starzyński
    • Kazimierz Jakubiuk
    2022 Full text ENERGIES

    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.

  • 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
    2022 Full text SCIENCE OF THE TOTAL ENVIRONMENT

    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.

  • New insights of nanomaterials usage toward superhydrophobic membranes for water desalination via membrane distillation: A review
    • Emilia Gontarek-Castro
    • Roberto Castro-Muñoz
    • Marek Lieder
    2022 Full text CRITICAL REVIEWS IN ENVIRONMENTAL SCIENCE AND TECHNOLOGY

    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.

  • 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
    2022 JOURNAL OF MOLECULAR LIQUIDS

    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.

  • 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
    2022 Full text Pharmaceutics

    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.

  • New Performance Indices for Power System Stabilizers
    • Michał Izdebski
    • Robert Małkowski
    • Piotr Miller
    2022 Full text ENERGIES

    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.

  • 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
    2022 Full text MOLECULES

    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.

  • Nieświadome sieci neuronowe
    • Stanisław Barański
    2022

    Coraz większą popularność zyskuje usługa predykcji za pomocą sieci neuronowych. Model ten zakłada istnienie serwera, który za pomocą wyuczonej sieci neuronowej dokonuje predykcji na danych otrzymanych od klienta. Model ten jest wygodny, ponieważ obie strony mogą skupić się na rozwoju w swojej specjalizacji. Wystawia on jednak na ryzyko utraty prywatności zarówno klienta, wysyła- jącego wrażliwe dane wejściowe, jak i serwer, udostępniający wy- uczony model sieci neuronowej. Niniejszy rozdział opisuje proces dokonywania nieświadomej predykcji za pomocą sieci neuronowych. Nieświadomość pozwala na dokonanie predykcji za pomocą sieci neu- ronowych przy zachowaniu prywatności danych wejściowych klienta oraz modelu serwera. Umożliwia świadczenie usług, które dotych- czas blokowane były przez regulacje prawne lub brak wiarygodności przetwarzających je systemów.

  • Niobate in silicate and phosphate glasses: Effect of glass basicity on crucible dissolution
    • Natalia Wójcik
    • Sharafat Ali
    • Efstratios Kamitsos
    • Doris Möncke
    2022 Full text International Journal of Applied Glass Science

    Using niobium crucibles for melting phosphate and silicate glasses of various modifier oxide contents, and therefore varying optical basicity (Λ), was found to result in varying dissolution rates of niobate during melting. Because of their high electronic polarizability, even small concentrations of niobates are detectable in the Raman spectra of glasses. Even less than 1 mol% Nb2O5 can be identified, as independently confirmed by SEM‐EDX analysis. Silica‐rich glasses (~60 % SiO2, Λ~0.6) did not show significant Nb dissolution from the crucible, while higher basicity metasilicate glasses (~ 50% SiO2, Λ~0.65) and pyrophosphate glasses (~30% P2O5, Λ~0.7) did show the typical niobate signature in the Raman spectra at 810‐840 cm‐1, depending on composition. While niobium is well dissolved throughout the pyrophosphate glass, metasilicate glasses showed a much more intense Raman signature of niobate units near the outer surface of the glass. Measurements along the cross section of a fractured metasilicate glass showed a steady decrease of the strength of the niobate signature from the surface toward the bulk of the material. Besides correlation with optical basicity, the tendency of melts to dissolve Nb crucible was discussed in terms of the connectivity or polymerization of the network and the corresponding melt viscosity.

  • Nitrate and nitrite silver complexes with weakly coordinating nitriles
    • Karolina Gutmańska
    • Anna Ciborska
    • Zbigniew Hnatejko
    • Anna Dołęga
    2022 Full text POLYHEDRON

    Simple system of weak nitrile ligands and silver nitrite/nitrate allowed the formation and isolation of coordination compounds of diverse nuclearity and dimensionality. The extension of the network does not enhance the luminescent properties of the ligands however it gives rise to the new MLCT bands in the visible region.

  • NLITED - New Level of Integrated Techniques for Daylighting Education: Preliminary Data on the Use of an E-learning Platform
    • Federica Giuliani
    • Natalia Sokół
    • Niko Gentile,
    • Mandana Khanie, Sarey
    • Valerio R.M. Lo Verso
    • Federica Caffaro
    2022

    Project NLITED – New Level of Integrated Techniques for Daylighting Education - is an educational project for students and professionals. The project's objective is to create and develop an online eLearning platform with 32 eModules dedicated to daylight knowledge. The project also offers e-learners two summer school training where the theory is put into practice. The platform was launched on January 31, 2022. The paper analyses the participation during the first four months of online activity until May 31, 2022. It discusses which eModules have received the highest participation rate and which have the lowest. These data are compared to the preferences on modules expressed by different panels of experts. The experts expressed their recommendations for specific educational content during workshops conducted in 2021, which led to the definition of the curriculum. Furthermore, participants also fill out an evaluation test on the quality and the usability of the eModule(s) they have taken. This information leads to the amendments of the ePlatform which are in the scope of action for the final year of the NLTED project.

  • Noise profiling for speech enhancement employing machine learning models
    • Krzysztof Kąkol
    • Grazina Korvel
    • Bożena Kostek
    2022 Full text Journal of the Acoustical Society of America

    This paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features derived from the Aurora noise dataset. This is to select the best-performing classifier in the context of noise profiling. Therefore, a comparison of all classifier outcomes is shown based on effectiveness metrics. Also, confusion matrices prepared for all tested models are presented. The second part of the experiment consists of selecting the algorithm that scored the best, i.e., Naïve Bayes, resulting in an accuracy of 96.76%, and using it in a noise-type recognition model to demonstrate that it can perform in a stable way. Classification results are derived from the real-life recordings performed in momentary and averaging modes. The key contribution is discussed regarding speech intelligibility improvements in the presence of noise, where identifying the type of noise is crucial. Finally, conclusions deliver the overall findings and future work directions.

  • Non-Adaptive Rotor Speed Estimation of Induction Machine in an Adaptive Full-Order Observer
    • Marcin Morawiec
    • Paweł Kroplewski
    • Charles Ikechukwu Odeh
    2022 Full text IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

    In the sensorless control system of an induction machine, the rotor speed value is not measured but reconstructed by an observer structure. The rotor speed value can be reconstructed by the classical adaptive law with the integrator. The second approach, which is the main contribution of this paper, is the non-adaptive structure without an integrator. The proposed method of the rotor speed reconstruction is based on an algebraic relationship – the rank of the mathematical model of the observer system is not increased. However, the problem with the stabilization of the observer structure does exist. For near to zero rotor speed or in the regenerating mode of an induction machine, the speed observer structure can be unstable. Therefore, in this paper, the new stabilization functions are proposed. The stability is provided by the Lyapunov theorem and the practical stability theorems in which the uncertainty of parameters is considered. In the proposed solution, the newly introduced stabilization functions guarantee observer stability during both the motoring and regenerating conditions at the chosen low rotor speed ranges and for different load torque values. All the theoretical considerations were confirmed by simulation and experimental tests during the chosen working modes and uncertainties of nominal parameters of the induction machine.

  • Non-Adaptive Speed and Position Observer of Doubly-Fed Induction Generator
    • Marcin Morawiec
    • Krzysztof Blecharz
    • Arkadiusz Lewicki
    2022

    The non-adaptive speed and position estimation of a doubly-fed induction generator (DFIG) is presented in this paper. The speed observer is based on the mathematical model of DFIG and to stabilize the structure the Lyapunov method is used. The classic stator field-oriented control to active and reactive power control is used in the sensorless control system. The performance of the proposed algorithm of a speed observer is validated by simulation and experimental results using the 2 kW generator. The stability analysis of the presented solution is confirmed by using the Lyapunov method and practical stability theorems.

  • Non-Contact Monitoring of ECG in the Home Environment—Selecting Optimal Electrode Configuration
    • Adam Bujnowski
    • Kamil Osiński
    • Piotr Przystup
    • Jerzy Wtorek
    2022 Full text SENSORS

    Capacitive electrocardiography (cECG) is most often used in wearable or embedded measurement systems. The latter is considered in the paper. An optimal electrocardiographic lead, as an individual feature, was determined based on model studies. It was defined as the possibly highest value of the R-wave amplitude measured on the back of the examined person. The lead configuration was also analyzed in terms of minimizing its susceptibility to creating motion artifacts. It was found that the direction of the optimal lead coincides with the electrical axis of the heart. Moreover, the electrodes should be placed in the areas preserving the greatest voltage and at the same time characterized by the lowest gradient of the potential. Experimental studies were conducted using the developed measurement system on a group of 14 people. The ratio of the R-wave amplitude (as measured on the back and chest, using optimal leads) was less than 1 while the SNR reached at least 20 dB. These parameters allowed for high-quality QRS complex detection with a PPV of 97%. For the “worst” configurations of the leads, the signals measured were practically uninterpretable.

  • Non-Contact Temperature Measurements Dataset
    • Aleksander Mroziński
    2022 Full text

    The dataset titled The influence of the distance of the pyrometer from the surface of the radiating object on the accuracy of measurements contains temperature measurements using a selection of four commercially available pyrometers (CHY 314P, TM-F03B, TFA 31.1125 and AB-8855) as a function of the measuring distance. The dataset allows a comparison of the accuracy and measuring precision of the devices, which are very important features in the reliable non-contact prediction of COVID-19 symptoms without interference from external disturbances during fast patient recognition.

  • Nonconventional 1,8-Diazafluoren-9-One Aggregates for Green Light Enhancement in Hybrid Biocompatible Media
    • Aneta Lewkowicz
    • Mattia Pierpaoli
    • Katarzyna Walczewska-Szewc
    • Martyna Czarnomska
    • Piotr Bojarski
    • Robert Bogdanowicz
    • Stanisław Pogorzelski
    • Leszek Kułak
    • Jakub Karczewski
    2022 Full text Materials

    Organic aggregates currently play a prominent role, mainly for their unique optoelectronic properties in the aggregated state. Such properties can be related to the aggregates’ structure and the molecular packing mode. In the literature, we have well-established models of H and J aggregates defined based on the molecular exciton model. However, unconventional aggregates, the most unrecognized forms, have been generating interest among researchers recently. Within unconventional aggregation, aggregation-induced emission systems (AIE) are considered. In the present work, we discuss the effect of the forming of unconventional aggregation together with the change in dye concentration on the surface energy characteristics of the materials. All materials were prepared as hybrid biocompatible thin films where the matrix is TiO2 or TiO2/carbon nanowalls (CNWs) with the incorporated dye in the form of 1,8-diazafluoren-9-one (DFO). Using the time-resolved emission spectra and the determination of surface parameters from contact angle measurements, we indicated the correlation between the changes in such parameters and the concentration of DFO dye in two types of TiO2 and TiO2/CNW structures. To examine the propensity of DFO for aggregation, the internal energy of the dye was assessed in several aggregate structures using Quantum chemistry calculations. The results emphasize that DFO is an attractive structure in the design of new fluorophores due to its low molecular weight, the presence of a nitrogen atom that provides good coordination properties, and the ability to form hydrogen bonds. Our studies show that when using suitable matrices, i.e., rigid media, it forms the preferred forms of aggregates in the excited state, characterized by high emission efficiency in the band maximum of around 550 nm.

  • Non-Isocyanate-Based Waterborne Polyurethanes
    • Marcin Włoch
    • Iga Carayon
    2022

    Non-isocyanate polyurethanes (NIPUs) are a greener alternative for the conventional polyurethanes synthesized using toxic and moisture-sensitive di- or polyisocyanates. The most often described method of NIPU synthesis involves the reaction of five-membered cyclic carbonates with amines, and resulting polymers containing primary and secondary hydroxyl groups (so they are also known as polyhydroxyurethanes), which can be further used for the functionalization of such macromolecules. What cannot be omitted is an application of bio-based substrates in the synthesis of NIPUs, which presently may constitute more than 50 wt.% of such NIPU systems. Waterborne non-isocyanate polyurethanes (WNIPUs) can be prepared as solids, solutions, or dispersions by several different synthetic pathways. Broad-spectrum synthesis methods and used compounds may lead to sufficient molecular masses and mechanical properties on a laboratory scale. Some semi-products of such reactions can be further processed into thin films, coatings, hydrogels, or functionalized nanoparticles. Thus, careful selection of substrates, as in the case of isocyanate-based polyurethanes, provides many opportunities for valuable product fabrication. WNIPUs in the form of dispersions may find an application to cast films with great success, whereas the formation of latexes allows for coating formation. Coatings are the largest group of proposed WNIPU applications due to excellent adhesion, gloss, mechanical properties (flexibility and impact resistance), and thermal stability. Hydrogels are just after coatings because they are characterized by favorable mechanical properties and swelling capability. In this chapter, we describe the synthesis and properties of WNIPUs.

  • Non-Least Square GNSS Positioning Algorithm for Densely Urbanized Areas
    • Jerzy Demkowicz
    2022 Full text Remote Sensing

    The paper introduces an essentially new algorithm for calculating the GNSS position as an alternative to the least-square method. The proposed approach can be widely applied to any positioning method that uses multiple position lines for position calculation and is an example ofhow using a numerical solution can improve position accuracy without access to historical data. In essence, the method is based on the adaptation of the median filtering method widely used in the field of image processing, while at the same time applying a combinatorial approach and order statistics. The proposed solution makes it possible to improve on and assess the credibility of a single measurement. The article highlights the differences between the proposed and currently used approaches, as well as their advantages and disadvantages. The algorithm has been extensively tested under various environmental and weather conditions. The tests were carried out in typical and also in very demanding conditions, thus taking into account the real application context, i.e., pedestrian and car navigation in densely urbanized areas.

  • Non-Linear Analysis of Structures Utilizing Load-Discretization of Stiffness Matrix Method with Coordinate Update
    • Najmadeen Saeed
    • Ahmed Manguri
    • Marcin Szczepański
    • Robert Jankowski
    2022 Full text Applied Sciences-Basel

    This paper proposes a stiffness method based structural analysis algorithm for geometrically non-linear structures. In this study, the applied load on the joints has been discretized to a sequence of a few loadings applied. Each loading step produces incremental external nodal displacements, which are added to the corresponding coordinates to get a new geometrical shape of the structure. This process is iteratively repeated until the sum of the loading of all iterations matches the total initial applied loading. The size of the increments affects the technique’s accuracy, subsequently affecting the number of iterations. The configuration of non-linear geometrical structures is vital in the work; a slight change of the coordinates makes a considerable variation of nodal displacements. In this paper, three pin-jointed assemblies and a cantilever beam have been examined using the proposed technique; significantly reasonable outcomes emerged, compared to the non-linear approaches, such as Dynamic Relaxation Method (DRM) and Non-linear approach by Kwan. In a numerical sense, the dissimilarity between the results of the conventional Stiffness Matrix (SM) method and the non-linear method is about 228%, while the maximum discrepancy between the proposed approach and the non-linear methods is just above 15%