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Genetic variation in C-reactive protein (CRP) gene is associated with retinopathy and hypertension in adolescents with type 1 diabetes
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Phase transitions and microstructure of emulsion systems prepared with acylglycerols/zinc stearate emulsifier
PublicationZbadano przemiany fazowe jakim ulegają układy emulsyjne w czasie procesu emulgowania, prowadzonego w obecności emulgatora acyloglicerolowego modyfikowanego stearynianem cynku. Rodzaj przemian mikrostrukturalnych jakim ulegały emulsje zależny był w głównej mierze od temperatury oraz zawartości fazy wodnej. Obserwowano powstawanie emulsji typu W/O, która wraz z obniżaniem temperatury ulegała inwersji prowadzącej do powstania dyspersji...
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The role of bile salts in digestion
PublicationBile salts (BS) are bio-surfactants present in the gastrointestinal tract (GIT) that play a crucial role in the digestion and absorption of nutrients. The importance of BS for controlled release and transport of lipid soluble nutrients and drugs has recently stimulated scientific interest in these physiological compounds. BS are so-called facial amphiphiles showing a molecular structure that is very distinct from classical surfactants....
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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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Detection of Cystic Fibrosis Symptoms Based on X-Ray Images Using Machine Learning- Pilot Study
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Influence of geometry of iron poles on the cogging torque of a field control axial flux permanent magnet machine
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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublicationOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublicationNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublicationOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublicationAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublicationMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublicationOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Development of an emulation platform for synchronous machine power generation system using a nonlinear functional level model
PublicationThe article presents the Power Hardware in the Loop (PHIL) approach for an autonomous power system analysis based on the synchronous generator model incorporating magnetic saturation effects. The model was prepared in the MATLAB/Simulink environment and then compiled into the C language for the PHIL platform implementation. The 150 kVA bidirectional DC/AC commercial-grade converter was used to emulate the synchronous generator....
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Ecology In Tribology: Selected Problems of Eliminating Natural Oil-Based Lubricants from Machine Friction Couples
PublicationThe elimination of mineral oil-based lubricants from machines has multiple beneficial effects on the natural environment. Firstly – these lubricants are a direct threat to the environment in the event of leaks; secondly – their elimination reduces the demand for crude oil from which they are obtained. In addition, in many cases, e.g. when replacing traditional lubricants with water, friction losses in the bearings can also be reduced...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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Control of induction machine supplied by a current source inverter using the multi-scalar transformation and backstepping approach
PublicationThe paper describes the voltage control technique of squire-cage induction machines supplied by a current source inverter. The control system is based on new transformation of the electric drive system (machine and inverter) state variables to the multi-scalar variables form. The backstepping approach is used to obtain the feedback control law. The control system contains the structure of the observer...
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Control Strategy of a Five-Phase Induction Machine Supplied by the Current Source Inverter With the Third Harmonic Injection
PublicationIn the five-phase induction machine (IM), it is possible to better use the electromagnetic circuit than in the three-phase IM. This requires the use of an adequate converter system which will be supplied by an induction machine. The electric drive system described, in this article, includes the five-phase induction machine supplied by the current source inverter (CSI). The proposed novelty—not presented previously—is the control...
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Chip suction system in circular sawing machine: empirical research and computational fluid dynamics numerical simulations
PublicationThe experimental analysis of the wood chip removing system during its redesigning in the existing sliding table circular saw and computational fluid dynamic (CFD) numerical simulations of the air flow process is presented in the paper. The attention was focused on the extraction hood and the bottom shelter of the actual existing system. The main aim was to perform experimental research on the pressure distribution inside the...
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Performance analysis of mobility protocols and handover algorithms for IP-based networks
PublicationA rapid growth of IP-based networks and services has created the vast collection of resources and functionality available to users by means of a universal method of access - an IP protocol. At the same time, advances in design of mobile electronic devices have allowed them to reach utility level comparable to stationary, desktop computers, while still retaining their mobility advantage. Following this trend multiple extensions...
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The use of LiFePO4 technology in autonomous PV systems
PublicationBattery manufacturing based on the flow of lithium ions is currently the fastest growing and the most promising technology. It is used in many applications - from the smallest electronic devices to the large-scale energy trays. However, in the PV systems lead-acid batteries are still the most commonly used. As they are much cheaper they also come with a number of significant disadvantages. It is anticipated that they will be replaced...
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NEW SOLUTIONS FOR THE SOLAR CHARGE CONTROLLERS DESIGN FOR OBTAINING TRUE MPP IN PARTLY SHADED PV MODULES
PublicationSoft shading sources such as tree limbs, structural elements of buildings and chimneys, scatter and refract sunlight, significantly reducing the amount of radiation reaching the surface of the module. The hard shadings located directly on the surface (i.e. bird droppings, leaves, snow) tend to stop sunlight completely. These phenomena significantly affects the output characteristics of photovoltaic modules and often contribute...
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AN INTELLIGENT SYSTEM TO SUPPORT THE DESIGN PROCESS OF HYBRID PHOTOVOLTAIC INSTALLATIONS
PublicationThe paper presents the final version of intelligent system to support the design process of hybrid photovoltaic systems supported by fuel cells and / or thermoelectric generators developed and constructed at the Institute of Electron Technology, as well as to conduct experiments and research. A block diagram of the system and the selection of its components is described and discussed. The paper considers the availability of the...
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Modélisation d'ordre non entier des machines synchrones. Modèle fréquentiel non linéaire, identification des paramètres, calcul de la réponse temporelle.
PublicationDans les réseaux d'énergie électrique contemporains, on assiste à une diversification considérable des différentes sources d'énergie. L'énergie produite est transformée par une grande quantité de dispositifs électriques pour être finalement acheminée à diverses installations électriques. Il devient donc primordial d'améliorer les modèles des différents composants électriques afin de pouvoir prévoir les interactions entre eux et...
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Limiting distribution of the three-state semi-Markov model of technical state transitions of ship power plant machines and its applicability in operational decision-making.
PublicationThe article presents the three-state semi-Markov model of the process {W(t): t 0} of state transitions of a ship power plant machine, with the following interpretation of these states: s1 – state of full serviceability, s2 – state of partial serviceability, and s3 – state of unserviceability. These states are precisely defined for the ship main engine (ME). A hypothesis is proposed which explains the possibility of application...
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Quasi Real-Time XRF Spectrometer in Source Apportionment of PM10 in a Typical Suburban Area
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Diffusion process modeling by using fractional-order models
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Fractional Variable-Order Derivative and Difference Operators and Their Applications to Dynamical Systems Modelling
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Liposomal cytarabine in the prophylaxis and treatment of CNS lymphoma: toxicity analysis in a retrospective case series study conducted at Polish Lymphoma Research Group Centers
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Novel single-stranded DNA-binding proteins from extreme psychrophilic bacterium Psychromonas ingrahamii 37
PublicationWe report the identification and characterization of the single-stranded DNA binding protein (SSB) from extreme psychrophilic bacterium Psychromonas ingrahamii 37 (PinSSB) that grows expotentially at -12°C and may well grow at even lower temperatures. PinSSB is one of the largest known bacterial SSB protein consisting 222 amino acid residues with a calculated molecular mass of 25.1 kDa. The analysis by gel filtration chromatography...
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Scope and limitations of the synthesis of functionalized quinolizidinones and related compounds by a simple precursor approach via addition of lithium allylmagnesates to 2-pyridones and RCM as key steps
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Sequential Synthesis of Organosilicon‐Linked 2‐Methoxypyridines by Non‐Cryogenic ortho‐Metallation Using the nBu2TMPMg·Li Reagent and Hydrosilylation
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9,10-Dioxoanthracenyldithiocarbamates effectively inhibit the proliferation of non-small cell lung cancer by targeting multiple protein tyrosine kinases
PublicationAnthraquinones have attracted considerable interest in the realm of cancer treatment owing to their potent anticancer properties. This study evaluates the potential of a series of new anthraquinone derivatives as anticancer agents for non-small-cell lung cancer (NSCLC). The compounds were subjected to a range of tests to assess their cytotoxic and apoptotic properties, ability to inhibit colony formation, pro-DNA damage functions,...
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Serum Cholesteryl Ester Transfer Protein (CETP) and Sortilin (SORT) in Patients with Psoriasis with Relation to Systemic Treatment
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Higher Serum Selenoprotein P Level as a Novel Inductor of Metabolic Complications in Psoriasis
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Galectin-3 as a Novel Multifaceted and Not Only Cardiovascular Biomarker in Patients with Psoriasis with Regard to Systemic Treatment—Preliminary Data
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Adipocyte Fatty Acid‐Binding Protein as a Novel Marker of Psoriasis and Clinical Response to Acitretin
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Potential Predictive Value of Serum Pentraxin 3 and Paraoxonase 1 for Cardiometabolic Disorders Development in Patients with Psoriasis—Preliminary Data
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Coping Strategies and Psychopathological Responses Among Medical and Non-medical Professionals – a Cross-Sectional Online Survey
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The Portrait of Cyberchondria—A Cross-Sectional Online Study on Factors Related to Health Anxiety and Cyberchondria in Polish Population during SARS-CoV-2 Pandemic
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Social Support Mediates the Association between Health Anxiety and Quality of Life: Findings from a Cross-Sectional Study
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Various modes of action of dietary phytochemicals, sulforaphane and phenethyl isothiocyanate, on pathogenic bacteria
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<title>Correction of fiber optic ion sensor readings using a fiber optic temperature sensor</title>
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Immersive Technologies that Aid Additive Manufacturing Processes in CBRN Defence Industry
PublicationTesting unique devices or their counterparts for CBRN (C-chemical, B-biological, R-radiological, N-nuclear) defense relies on additive manufacturing processes. Immersive technologies aid additive manufacturing. Their use not only helps understand the manufacturing processes, but also improves the design and quality of the products. This article aims to propose an approach to testing CBRN reconnaissance hand-held products developed...
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Integrated Processing: Quality Assurance Procedure of the Surface Layer of Machine Parts during the Manufacturing Step "Diamond Smoothing"
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Presentation of Novel Architecture for Diagnosis and Identifying Breast Cancer Location Based on Ultrasound Images Using Machine Learning
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Molecular Simulations Using Boltzmann’s Thermally Activated Diffusion - Implementation on ARUZ – Massively-parallel FPGA-based Machine
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
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