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Wyniki wyszukiwania dla: MOLECULAR MODELING,MOLECULES,NEURAL NETWORKS,SOLVENTS,VISCOSITY
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Social media for e-learning of citizens in smart city
PublikacjaThe rapid development of social media can be applied for citizens’ e-learning in a smart city. Big cities have to cope with several open issues like a growing population or a traffic congestion. Especially, a home and public space is supposed to be used in more efficient way. Sustainable homes and buildings can be planned with using some modern techniques. Even currently, there is a huge problem with a lack of key resources like...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublikacjaA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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From Data to Decision: Interpretable Machine Learning for Predicting Flood Susceptibility in Gdańsk, Poland
PublikacjaFlood susceptibility prediction is complex due to the multifaceted interactions among hydrological, meteorological, and urbanisation factors, further exacerbated by climate change. This study addresses these complexities by investigating flood susceptibility in rapidly urbanising regions prone to extreme weather events, focusing on Gdańsk, Poland. Three popular ML techniques, Support Vector Machine (SVM), Random Forest (RF), and...
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Data fusion of sparse, heterogeneous, and mobile sensor devices using adaptive distance attention
PublikacjaIn environmental science, where information from sensor devices are sparse, data fusion for mapping purposes is often based on geostatistical approaches. We propose a methodology called adaptive distance attention that enables us to fuse sparse, heterogeneous, and mobile sensor devices and predict values at locations with no previous measurement. The approach allows for automatically weighting the measurements according to a priori...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublikacjaOne 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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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublikacjaLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Mass spectrometry based identification of geometric isomers during metabolic stability study of a new cytotoxic sulfonamide derivatives supported by quantitative structure-retention relationships
PublikacjaA set of 15 new sulphonamide derivatives, presenting antitumor activity have been subjected to a metabolic stability study. The results showed that besides products of biotransformation, some additional peaks occurred in chromatograms. Tandem mass spectrometry revealed the same mass and fragmentation pathway, suggesting that geometric isomerization occurred. Thus, to support this hypothesis, quantitative structure-retention relationships...
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Modeling lignin extraction with ionic liquids using machine learning approach
PublikacjaLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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Sathwik Prathapagiri
OsobySathwik was born in 2000. In 2022, he completed his Master’s of Science in Biological Sciences and Bachelor’s of Engineering in Chemical Engineering in an integrated dual degree program from Birla Institute Of Technology And Science, Pilani, India. During his final year, he worked as a research intern under Dr Giri P Krishnan at Bazhenov lab, University of California San Diego school of medicine to pursue his Master’s Thesis on...
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Experimental and theoretical investigation of conformational states and noncovalent interactions in crystalline sulfonamides with a methoxyphenyl moiety
PublikacjaFour sulfonamide derivatives with a methoxyphenyl moiety, namely N-{4-[(2-methoxyphenyl)sulfamoyl] phenyl}acetamide (1a), N-{4-[(3-methoxyphenyl)sulfamoyl]phenyl}acetamide (1b), 4-amino-N-(2- methoxyphenyl)benzenesulfonamide (2a) and 4-amino-N-(3-methoxyphenyl)benzenesulfonamide (2b), have been synthesized and characterized physiochemically by CHNS, MS, FT-IR, 1H NMR, 13C NMR, PXRD and TG methods. Crystal structures were determined...
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Adaptacyjny system oświetlania dróg oraz inteligentnych miast
PublikacjaPrzedmiotem rozprawy jest zbadanie praktycznej możliwości wykrywania w czasie rzeczywistym anomalii w systemie oświetlenia drogowego w oparciu o analizę danych ze inteligentnych liczników energii. Zastosowanie inteligentnych liczników energii elektrycznej (Smart Meter) w systemach oświetlenia drogowego stwarza nowe możliwości w zakresie automatycznej diagnostyki takich niepożądanych zjawisk jak awarie lamp, odstępstwa od harmonogramu...
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Preparation and characterization of dummy-template molecularly imprinted polymers as potential sorbents for the recognition of selected polybrominated diphenyl ethers
PublikacjaThe main aim of this work was to conduct the preliminary/basic research concerning the preparation process of a new dummy molecularly imprinted polymer (DMIP) materials. Developed DMIPs were proposed as a sorption material in solid-phase extraction (SPE) technique for recognition of selected low mass polybrominated diphenyl ethers (PBDEs) e PBDE-47 and PBDE-99. Four new DMIPs were synthesized employing bulky polymerization technique...
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Continuum contact model for friction between graphene sheets that accounts for surface anisotropy and curvature
PublikacjaUnderstanding the interaction mechanics between graphene layers and co-axial carbon nanotubes (CNTs) is essential for modeling graphene and CNT-based nanoelectromechanical systems. This work proposes a new continuum contact model to study interlayer interactions between curved graphene sheets. The continuum model is calibrated and validated using molecular dynamics (MD) simulations. These are carried out employing the reactive...
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On-line Search in Two-Dimensional Environment
PublikacjaWe consider the following on-line pursuit-evasion problem. A team of mobile agents called searchers starts at an arbitrary node of an unknown network. Their goal is to execute a search strategy that guarantees capturing a fast and invisible intruder regardless of its movements using as few searchers as possible. We require that the strategy is connected and monotone, that is, at each point of the execution the part of the graph...
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Rapid Design of 3D Reflectarray Antennas by Inverse Surrogate Modeling and Regularization
PublikacjaReflectarrays (RAs) exhibit important advantages over conventional antenna arrays, especially in terms of realizing pencil-beam patterns without the employment of the feeding networks. Unfortunately, microstrip RA implementations feature narrow bandwidths, and are severely affected by losses. A considerably improved performance can be achieved for RAs involving grounded dielectric layers, which are also easy to manufacture using...
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Optimal Design of Transmitarray Antennas via Low-Cost Surrogate Modelling
PublikacjaOver the recent years, reflectarrays and transmitarrays have been drawing a considerable attention due to their attractive features, including a possibility of realizing high gain and pencil-like radiation patterns without the employment of complex feeding networks. Among the two, transmitarrays seem to be superior over reflectarrays in terms of achieving high radiation efficiency without the feed blockage. Notwithstanding, the...
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Anionic states of C6Cl6 probed in electron transfer experiments
PublikacjaThis is the first comprehensive investigation on the anionic species formed in collisions of fast neutral potassium (K) atoms with neutral hexachlorobenzene (C6Cl6) molecules in the laboratory frame range from 10 up to 100 eV. In such ion-pair formation experiments, we also report a novel K+ energy loss spectrum obtained in the forward scattering giving evidence of the most accessible electronic states. The vertical electron affinity...
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Neutral Dissociation of Pyridine Evoked by Irradiation of Ionized Atomic and Molecular Hydrogen Beams
PublikacjaThe 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,...
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Nanofiltration-Assisted Concentration Processes of Phenolic Fractions and Carotenoids from Natural Food Matrices
PublikacjaIn new food formulations, carotenoids and phenolic compounds are likely to be the most sought after food ingredients according to their bioactivity, nutraceutical, nutritional value, and compatibility properties once incorporated into food formulations. Such solutes are naturally present in many plant-based sources, and some portions are directly consumed when enriching food products and formulations; however, some portions, which...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublikacjaAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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A review on computer‐aided chemogenomics and drug repositioning for rational COVID ‐19 drug discovery
PublikacjaApplication of materials capable of energy harvesting to increase the efficiency and environmental adaptability is sometimes reflected in the ability of discovery of some traces in an environment―either experimentally or computationally―to enlarge practical application window. The emergence of computational methods, particularly computer-aided drug discovery (CADD), provides ample opportunities for the rapid discovery and development...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Development of an AI-based audiogram classification method for patient referral
PublikacjaHearing loss is one of the most significant sensory disabilities. It can have various negative effects on a person's quality of life, ranging from impeded school and academic performance to total social isolation in severe cases. It is therefore vital that early symptoms of hearing loss are diagnosed quickly and accurately. Audiology tests are commonly performed with the use of tonal audiometry, which measures a patient's hearing...
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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublikacjaThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
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Segmentation Quality Refinement in Large-Scale Medical Image Dataset with Crowd-Sourced Annotations
PublikacjaDeployment of different techniques of deep learning including Convolutional Neural Networks (CNN) in image classification systems has accomplished outstanding results. However, the advantages and potential impact of such a system can be completely negated if it does not reach a target accuracy. To achieve high classification accuracy with low variance in medical image classification system, there is needed the large size of the...
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Progress in ATRP-derived materials for biomedical applications
PublikacjaThe continuing wave of technological breakthroughs and advances is critical for engineering well- defined materials, particularly biomaterials, with tailored microstructure and properties. Over the last few decades, controlled radical polymerization (CRP) has become a very promising option for the synthesis of precise polymeric materials with an unprecedented degree of control over mo lecular architecture. Atom transfer radical...
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Synthesis and biological evaluation of fluorinated N-benzoyl and N-phenylacetoyl derivatives of 3-(4-aminophenyl)-coumarin-7-O-sulfamate as steroid sulfatase inhibitors
PublikacjaIn the present work, we report convenient methods for the synthesis of 3-(4-aminophenyl)-coumarin-7-O-sulfamate derivatives N-acylated with fluorinated analogues of benzoic or phenylacetic acid as steroid sulfatase (STS) inhibitors. The design of these potential STS inhibitors was supported by molecular modeling techniques. Additionally, computational docking methods were used to determine the binding modes of the synthesized inhibitors...
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Survey on fuzzy logic methods in control systems of electromechanical plants
PublikacjaРассмотрены алгоритмы управления электромеханическими системами с использованием теории нечеткой логики, приводятся основные положения их синтеза, рассматриваются методы анализа их устойчивости на основе нечетких функций Ляпунова. Эти алгоритмы чаще всего реализуются в виде различных регуляторов, применение которых целесообразно в системах, математическая модель которых не известна, не детерминирована или является строго нелинейной,...
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Highly Conserved Homotrimer Cavity Formed by the SARS-CoV-2 Spike Glycoprotein: A Novel Binding Site
PublikacjaAn important stage in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) life cycle is the binding of the spike (S) protein to the angiotensin converting enzyme-2 (ACE2) host cell receptor. Therefore, to explore conserved features in spike protein dynamics and to identify potentially novel regions for drugging, we measured spike protein variability derived from 791 viral genomes and studied its properties by molecular...
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Solvothermal synthesis and structural characterization of three polyoxotitanium-organic acid clusters
PublikacjaThree new titanium oxo-clusters Ti4O2(OiPr)10(OOCPhMe)2 (I), Ti6O4(OEt)8(OOCPhMe)8 (II) and Ti6O6(OEt)6(OOCCHPh2)6 (III) were obtained by easy one-step solvothermal reactions of titanium(IV) isopropoxide, alcohols and carboxylic acids. The three compounds were characterized by single-crystal and powder X-ray diffraction, TGA/DSC, optical and electron microscopy, and FTIR and NMR spectroscopy. X-ray powder diffraction and spectroscopy...
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The Metal-Free Regioselective Deuteration of 2-Methylquinolin-8-ol and 2,5-Dimethylquinolin-8-ol, Spectroscopic and Computational Studies
PublikacjaAbstract: Aim and Background: Introducing deuterium to a molecule is of interest to a wide variety of research, including investigation of reaction mechanisms or kinetics, analysis of drug metabolism, structural elucidation of molecules, and syntheses of isotopically labeled materials used for NMR spectroscopy and medicinal research. Objective: The transition-metal-free regioselective deuteration of 2-methylquinolin-8-ol...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublikacjaAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Faults and Fault Detection Methods in Electric Drives
PublikacjaThe chapter presents a review of faults and fault detection methods in electric drives. Typical faults are presented that arises for the induction motor, which is valued in the industry for its robust construction and cost-effective production. Moreover, a summary is presented of detectable faults in conjunction with the required physical information that allow a detection of specific faults. In order to address faults of a complete...
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System for automatic singing voice recognition
PublikacjaW artykule przedstawiono system automatycznego rozpoznawania jakości i typu głosu śpiewaczego. Przedstawiono bazę danych oraz zaimplementowane parametry. Algorytmem decyzyjnym jest algorytm sztucznych sieci neuronowych. Wytrenowany system decyzyjny osiąga skuteczność ok. 90% w obydwu kategoriach rozpoznawania. Dodatkowo wykazano przy pomocy metod statystycznych, że wyniki działania systemu automatycznej oceny jakości technicznej...
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Combined Single Neuron Unit Activity and Local Field Potential Oscillations in a Human Visual Recognition Memory Task
PublikacjaGOAL: Activities of neuronal networks range from action potential firing of individual neurons, coordinated oscillations of local neuronal assemblies, and distributed neural populations. Here, we describe recordings using hybrid electrodes, containing both micro- and clinical macroelectrodes, to simultaneously sample both large-scale network oscillations and single neuron spiking activity in the medial temporal lobe structures...
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On Memory-Based Precise Calibration of Cost-Efficient NO2 Sensor Using Artificial Intelligence and Global Response Correction
PublikacjaNitrogen dioxide (NO2) is a prevalent air pollutant, particularly abundant in densely populated urban regions. Given its harmful impact on health and the environment, precise real-time monitoring of NO2 concentration is crucial, particularly for devising and executing risk mitigation strategies. However, achieving precise measurements of NO2 is challenging due to the need for expensive and cumbersome equipment. This has spurred...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublikacjaComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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Computationally Efficient Surrogate-Assisted Design of Pyramidal-Shaped 3D Reflectarray Antennas
PublikacjaReflectarrays (RAs) have been attracting considerable interest in the recent years due to their appealing features, in particular, a possibility of realizing pencil-beam radiation patterns, as in the phased arrays, but without the necessity of incorporating the feeding networks. These characteristics make them attractive solutions, among others, for satellite communications or mobile radar antennas. Notwithstanding, available microstrip...
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Problem of aggregation in dye-DNA interaction, calorimetry studies
PublikacjaNucleic acids are the biological target for many antimicrobial, antitumor and antiviral drugs. Ligand-DNA interactions can be classified into two major categories: 1. covalent binding, which can provide to intermolecular adducts, 2. physico-chemical interactions, which can be divided into intercalation (e.g. adriamycin) or groove binding (e.g. dystamycin). There are several methods to investigate interactions between drug and DNA....
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Marine and Cosmic Inspirations for AI Algorithms
PublikacjaArtificial Intelligence (AI) is a scientific area that currently sees an enormous growth. Various new algorithms and methods are developed and many of them meets practical, successful applications. Authors of new algorithms draw different inspirations. Probably the most common one is the nature. For example, Artificial Neural Networks were inspired by the structure of human brain and nervous system while the classic Genetic Algorithm...
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Dynamic GPU power capping with online performance tracing for energy efficient GPU computing using DEPO tool
PublikacjaGPU accelerators have become essential to the recent advance in computational power of high- performance computing (HPC) systems. Current HPC systems’ reaching an approximately 20–30 mega-watt power demand has resulted in increasing CO2 emissions, energy costs and necessitate increasingly complex cooling systems. This is a very real challenge. To address this, new mechanisms of software power control could be employed. In this...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Orken Mamyrbayev Professor
Osoby1. Education: Higher. In 2001, graduated from the Abay Almaty State University (now Abay Kazakh National Pedagogical University), in the specialty: Computer science and computerization manager. 2. Academic degree: Ph.D. in the specialty "6D070300-Information systems". The dissertation was defended in 2014 on the topic: "Kazakh soileulerin tanudyn kupmodaldy zhuyesin kuru". Under my supervision, 16 masters, 1 dissertation...
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Triplet–Triplet Annihilation Upconverting Liposomes: Mechanistic Insights into the Role of Membranes in Two-Dimensional TTA-UC
PublikacjaTriplet−triplet annihilation upconversion (TTA-UC) implemented in nanoparticle assemblies is of emerging interest in biomedical applications, including in drug delivery and imaging. As it is a bimolecular process, ensuring sufficient mobility of the sensitizer and annihilator to facilitate effective collision in the nanoparticle is key. Liposomes can provide the benefits of two-dimensional confinement and condensed concentration...
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Direct injection liquid chromatography-mass spectrometry (DI-LC-MS) analysis for rapid lipidomic profiling of extracellular vesicles
PublikacjaExtracellular vesicles (EVs) are small, spherical particles produced by eukaryotic and prokaryotic cells, surrounded by a bilayer membrane and carrying various bioactive molecules, such as proteins, surface receptors, membrane and soluble proteins, lipids, and nucleic acids. EVs are of substantial interest because of their important roles in cell communication, epigenetic regulation and possible application in disease diagnosis...
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Fusion of Taq DNA polymerase with single-stranded DNA binding-like protein of Nanoarchaeum equitans—Expression and characterization
PublikacjaDNA polymerases are present in all organisms and are important enzymes that synthesise DNA molecules. They are used in various fields of science, predominantly as essential components for in vitro DNA syntheses, known as PCR. Modern diagnostics, molecular biology and genetic engineering need DNA polymerases which demonstrate improved performance. This study was aimed at obtaining a new NeqSSB-TaqS fusion DNA polymerase from the...
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Implementing artificial intelligence in forecasting the risk of personal bankruptcies in Poland and Taiwan
PublikacjaResearch background: The global financial crisis from 2007 to 2012, the COVID-19 pandemic, and the current war in Ukraine have dramatically increased the risk of consumer bankruptcies worldwide. All three crises negatively impact the financial situation of households due to increased interest rates, inflation rates, volatile exchange rates, and other significant macroeconomic factors. Financial difficulties may arise when the...
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Verification of the Parameterization Methods in the Context of Automatic Recognition of Sounds Related to Danger
PublikacjaW artykule opisano aplikację, która automatycznie wykrywa zdarzenia dźwiękowe takie jak: rozbita szyba, wystrzał, wybuch i krzyk. Opisany system składa się z bloku parametryzacji i klasyfikatora. W artykule dokonano porównania parametrów dedykowanych dla tego zastosowania oraz standardowych deskryptorów MPEG-7. Porównano też dwa klasyfikatory: Jeden oparty o Percetron (sieci neuronowe) i drugi oparty o Maszynę wektorów wspierających....
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Vehicle detector training with minimal supervision
PublikacjaRecently many efficient object detectors based on convolutional neural networks (CNN) have been developed and they achieved impressive performance on many computer vision tasks. However, in order to achieve practical results, CNNs require really large annotated datasets for training. While many such databases are available, many of them can only be used for research purposes. Also some problems exist where such datasets are not...