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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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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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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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Isolation and Characterization of NP-POL Nonapeptide for Possible Therapeutic Use in Parkinson’s Disease
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Novel method of estimation of inertial and dissipative parameters of a railway pantograph model
PublicationAn increase in electric railway vehicles service velocity requires that correct interaction between the pantograph and the catenary is ensured. This implies the need for developing mathematical models of pantographs and catenaries and determining their parameters. The article presents a method to determine parameters of mechanical joints of a railway pantograph based on analysis of pantograph subassemblies in swinging motion. The...
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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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QSAR, QSPR and QSRR in Terms of 3-D-MoRSE Descriptors for In Silico Screening of Clofibric Acid Analogues
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Measurements of Path Loss in Off-Body Channels in Indoor Environments
PublicationThis paper presents a measurements of the path loss for validation of a statistical model for off-body radio channels in an indoor multipath environment, which considers the distance dependent mean path loss, and describes body shadowing and fast fading components in a statistical way. The measurement equipment and propagation indoor environment have been presented. Two different bodies and five static and two walking scenarios...
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Mental Health Consequences of SARS-CoV-2 Pandemic on Long-Term Care Facility Social Care Provider in Poland
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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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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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THE EFFECT OF WOOD DRYING METHOD ON THE GRANULARITY OF SAWDUST OBTAINED DURING THE SAWING PROCESS USING THE FRAME SAWING MACHINE
PublicationThe experimental results of the study focused on the effect of drying processes of warm air drying at the temperature of 6580°C and warm air-steam mixture drying at the temperature of 105°C of pine and beech wood to the size of sawdust grains created by cutting using RPW 15M frame saw is presented in the paper. Particle size analysis of dry sawdust was performed using two methods - screening method and optical method based on...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
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The Influence of Permanent Magnet Length and Magnet Type on Flux-control of Axial Flux Hybrid Excited Electrical Machine
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Molecular Simulations Using Boltzmann’s Thermally Activated Diffusion - Implementation on ARUZ – Massively-parallel FPGA-based Machine
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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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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing
PublicationRubbers combine the flexibility with mechanical strength, supporting myriad applications, but suffer from inherent flammability. Formulation and production of flame-retardant rubber composites (FRRCs) have intensively been practiced over years, but not comprehensively reviewed. This necessity has outlined collecting, analyzing, screening, classifying, and interpreting the literature with the aim of classifying the FRRCs. We quantified...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublicationWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublicationLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
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Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublicationIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
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A pilot study to assess manufacturing processes using selected point measures of vibroacoustic signals generated on a multitasking machine
PublicationThe article presents the method for the evaluation of selected manufacturing processes using the analysis of vibration and sound signals. This method is based on the use of sensors installed outside the machining zone, allowing to be used quickly and reliably in real production conditions. The article contains a developed measurement methodology based on the specific location of microphones and vibration transducers mounted on...
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Fundamentals of Communication Networks Resilience to Disasters and Massive Disruptions
PublicationCommunication networks are exposed to a variety of massive failure events following from activities of nature, weather-induced disruptions, technology-implied problems, and malicious human activities. In this chapter, we first highlight the characteristics of these scenarios and discuss example failure events reported during the last three decades. Next, we explain the concept of network resilience and present an overview of major...
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Bile salts in digestion and transport of lipids
PublicationBecause of their unusual chemical structure, bile salts (BS) play a fundamental role in intestinal lipid digestion and transport. BS have a planar arrangement of hydrophobic and hydrophilic moieties, which enables the BS molecules to form peculiar self-assembled structures in aqueous solutions. This molecular arrangement also has an influence on specific interactions of BS with lipid molecules and other compounds of ingested food...
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Stable and degradable microgels linked with cystine for storing and environmentally triggered release of drugs
PublicationEnvironmentally sensitive, degradable microgels based on poly(N-isopropylacrylamide) (pNIPA) crosslinked with the diacryloyl derivative of cystine (BISS) were synthesized by applying surfactant-free emulsion polymerization. pNIPA contributed the sensitivity to temperature to the microgels and the cross-linker made them degradable and sensitive to pH. The morphology of the microgels was investigated by using scanning and transmission...
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Complementary study with magnetic and acoustic techniques of A336 steel damage state due to creep
PublicationBadano możliwość detekcji w sposób nieniszczący zmian w mikrostrukturze stali A336 poddanej próbie pełzania. Testowano dwie magnetyczne techniki (klasyczny efekt Barkhausena i emisję magnetoakustyczną) oraz dwie nowe techniki ultradźwiękowe (pomiar współczynnika elasto-akustycznego oraz dwójłomność akustyczną). Wykazano, iż wyniki badań akustycznych są komplementarne do wyników badań magnetycznych.
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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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Palindromic carbazole derivatives: unveiling their antiproliferative effect via topoisomerase II catalytic inhibition and apoptosis induction
PublicationHuman DNA topoisomerases are essential for crucial cellular processes, including DNA replication, transcription, chromatin condensation, and maintenance of its structure. One of the significant strategies employed in cancer treatment involves the inhibition of a specific type of topoisomerase, known as topoisomerase II (Topo II). Carbazole derivatives, recognised for their varied biological activities, have recently become a significant...
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Zastosowanie spektroskopii ATR/FT-IR w badaniach polimerów zawierających ugrupowania pirolidonowe
PublicationW niniejszej pracy prezentujemy syntezę i analizę właściwości fizyko-chemicznych porowatych mikrosfer zawierających ugrupowania pirolidonowe otrzymanych technika suspensyjną. Ugrupowania pirolidonowe zostały wprowadzone w sieć polimerową w wyniku bezpośredniej reakcji z 1-winylo-2-pirolidonem (VP) z dimetakrylanem glikolu etylenowego (DMGE) oraz poprzez modyfikację pirolidonem grup epoksydowych obecnych w strukturze kopolimeru...
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Akebia quinata and Akebia trifoliata - a review of phytochemical composition, ethnopharmacological approaches and biological studies
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Machine Learning Algorithm-Based Tool and Digital Framework for Substituting Daylight Simulations In Early- Stage Architectural Design Evaluation
PublicationThe aim of this paper is to examine the new method of obtaining the simulation-based results using backpropagation of errors artificial neural networks. The primary motivation to conduct the research was to determine an alternative, more efficient and less timeconsuming method which would serve to achieve the results of daylight simulations. Three daylight metrics: Daylight Factor, Daylight Autonomy and Daylight Glare Probability have...
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STUDY IN MECHANICAL FAULT ELEMENT THERMOGRAPHY THROUGH THE MACHINE: The case of deep groove ball bearings of a career without screen.
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Modeling flatness deviation in face milling considering angular movement of the machine tool system components and tool flank wear
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Sawdust size distribution analysis of thermally modified and unmodified oak wood sawed on the frame sawing machine PRW15-M
PublicationW pracy przedstawiono wyniki analizy granulometrycznej składu wiórów drewna dębowego niemodyfikowanego i modyfikowanego termicznie uzyskanych podczas piłowania na pilarce ramowej PRW15-M z prędkością posuwu 1.67 mmin-1. Otrzymane trociny termicznie modyfikowanego drewna dębowego składają się z wiórów o ziarnistości w przedziale od 44.7 mm do 4.6 mm, podczas gdy dla drewna niemodyfikowanego zaobserwowano zmiany ziarnistości w granicach...
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Toward mechanosynthesis of diamondoid structures: V. Silicon as the material of choice for preliminary implementation of intermediate generation of nano-machine systems
PublicationStosując ostatnio wprowadzony przez Drexlera ''moduł skalowany stałą sieciową'' KLM, porównano dwa potencjalne nano-materiały, krzem i diament. Szczegółowe porównanie właściwości fizycznych i chemicznych wykazuje, że krzem może być rozważany jako materiał z wyboru dla pierwotnej implementacji pośredniej generacji nano-systemów.
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublicationControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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How Integration of a Brain-Machine Interface and Obstacle Detection System Can Improve Wheelchair Control via Movement Image
PublicationThis study presents a human-computer interaction combined with a brain-machine interface (BMI) and obstacle detection system for remote control of a wheeled robot through movement imagery, providing a potential solution for individuals facing challenges with conventional vehicle operation. The primary focus of this work is the classification of surface EEG signals related to mental activity when envisioning movement and deep relaxation...
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Influence of feed rate on the granularity and homogenity of oak sawdust obtained during the sawing process on the frame sawing machine PRW15M
PublicationOpisano wpływ prędkości posuwu na skład granulometryczny i jednorodność trocin dębowych otrzymanych podczas procesu przecinania na pilarce ramowej PRW15M. Wykazano, że otrzymane trociny mogą być wykorzystane w produkcji produktów drewnopochodnych w ilości 75% dla posuwu 0.36 m/min i 82% przy posuwie 1.67 m/min. Pozostałe trociny stanowią odpad.
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Machine Learning- and Artificial Intelligence-Derived Prediction for Home Smart Energy Systems with PV Installation and Battery Energy Storage
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Modeling of small molecule's affinity to phospholipids using IAM-HPLC and QSRR approach enhanced by similarity-based machine algorithms
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Prediction of Stress and Deformation Caused by Magnetic Attraction Force in Modulation Elements in a Magnetically Geared Machine Using Subdomain Modeling
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublicationMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...