Search results for: MOLECULAR MODELING,MOLECULES,NEURAL NETWORKS,SOLVENTS,VISCOSITY
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TINKTEP: A fully self-consistent, mutually polarizable QM/MM approach based on the AMOEBA force field
PublicationWe present a novel quantum mechanical/molecular mechanics (QM/MM) approach in which a quantum subsystem is coupled to a classical subsystem described by the AMOEBA polarizable force field. Our approach permits mutual polarization between the QM and MM subsystems, effected through multipolar electrostatics. Self-consistency is achieved for both the QM and MM subsystems through a total energy minimization scheme. We provide an expression...
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Synthesis of green benzamide-decorated UiO-66-NH2 for biomedical applications
PublicationMetal-organic frameworks (MOFs) biocompatible systems can host enzymes/bacteria/viruses. Herein we synthesized a series of fatty acid amide hydrolase (FAAH)-decorated UiO-66-NH2 based on Citrus tangerine leaf extract for drug delivery and biosensor applications. Five chemically manipulated FAAH-like benzamides were localized on the UiO-66-NH2 surface with physical interactions. Comprehensive cellular and molecular analyses were...
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Effect of Aromatic System Expansion on Crystal Structures of 1,2,5-Thia- and 1,2,5-Selenadiazoles and Their Quaternary Salts: Synthesis, Structure, and Spectroscopic Properties
PublicationRational manipulation of secondary bonding interactions is a crucial factor in the construction of new chalcogenadiazole-based materials. This article reports detailed experimental studies on phenanthro[9,10-c][1,2,5]chalcogenadiazolium and 2,1,3-benzochalcogenadiazolium salts and their precursors. The compounds were synthesized, characterized employing NMR and UV-Vis spectroscopy. TD-DFT calculations were also performed. The influence...
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Deciphering the Molecular Mechanism of Substrate-Induced Assembly of Gold Nanocube Arrays toward an Accelerated Electrocatalytic Effect Employing Heterogeneous Diffusion Field Confinement
PublicationThe complex electrocatalytic performance of gold nanocubes (AuNCs) is the focus of this work. The faceted shapes of AuNCs and the individual assembly processes at the electrode surfaces define the heterogeneous conditions for the purpose of electrocatalytic processes. Topographic and electron imaging demonstrated slightly rounded AuNC (average of 38 nm) assemblies with sizes of ≤1 μm, where the dominating patterns are (111) and...
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PTD4 Peptide Increases Neural Viability in an In Vitro Model of Acute Ischemic Stroke
PublicationIschemic stroke is a disturbance in cerebral blood flow caused by brain tissue ischemia and hypoxia. We optimized a multifactorial in vitro model of acute ischemic stroke using rat primary neural cultures. This model was exploited to investigate the pro-viable activity of cell-penetrating peptides: arginine-rich Tat(49–57)-NH2 (R49KKRRQRRR57-amide) and its less basic analogue, PTD4 (Y47ARAAARQARA57-amide). Our model included glucose...
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Social media for e-learning of citizens in smart city
PublicationThe 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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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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Pedestrian detection in low-resolution thermal images
PublicationOver one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany 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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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublicationA 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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Exergy and Energy Analyses of Microwave Dryer for Cantaloupe Slice and Prediction of Thermodynamic Parameters Using ANN and ANFIS Algorithms
PublicationThe study targeted towards drying of cantaloupe slices with various thicknesses in a microwave dryer. The experiments were carried out at three microwave powers of 180, 360, and 540 W and three thicknesses of 2, 4, and 6 mm for cantaloupe drying, and the weight variations were determined. Artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) were exploited to investigate energy and exergy indices of...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid 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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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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Super-resolved Thermal Imagery for High-accuracy Facial Areas Detection and Analysis
PublicationIn this study, we evaluate various Convolutional Neural Networks based Super-Resolution (SR) models to improve facial areas detection in thermal images. In particular, we analyze the influence of selected spatiotemporal properties of thermal image sequences on detection accuracy. For this purpose, a thermal face database was acquired for 40 volunteers. Contrary to most of existing thermal databases of faces, we publish our dataset...
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Comparative study on the effectiveness of various types of road traffic intensity detectors
PublicationVehicle detection and speed measurements are crucial tasks in traffic monitoring systems. In this work, we focus on several types of electronic sensors, operating on different physical principles in order to compare their effectiveness in real traffic conditions. Commercial solutions are based on road tubes, microwave sensors, LiDARs, and video cameras. Distributed traffic monitoring systems require a high number of monitoring...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublicationAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
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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
PublicationA 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
PublicationLignin, 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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Experimental and theoretical investigation of conformational states and noncovalent interactions in crystalline sulfonamides with a methoxyphenyl moiety
PublicationFour 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
PublicationPrzedmiotem 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
PublicationThe 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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Optimal Design of Transmitarray Antennas via Low-Cost Surrogate Modelling
PublicationOver 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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Rapid Design of 3D Reflectarray Antennas by Inverse Surrogate Modeling and Regularization
PublicationReflectarrays (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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On-line Search in Two-Dimensional Environment
PublicationWe 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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Nanofiltration-Assisted Concentration Processes of Phenolic Fractions and Carotenoids from Natural Food Matrices
PublicationIn 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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Anionic states of C6Cl6 probed in electron transfer experiments
PublicationThis 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
PublicationThe 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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Sathwik Prathapagiri
PeopleSathwik 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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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir 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
PublicationApplication 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
PublicationIn 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
PublicationHearing 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
PublicationThe 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
PublicationDeployment 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
PublicationThe 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
PublicationIn 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
PublicationРассмотрены 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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The Metal-Free Regioselective Deuteration of 2-Methylquinolin-8-ol and 2,5-Dimethylquinolin-8-ol, Spectroscopic and Computational Studies
PublicationAbstract: 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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Highly Conserved Homotrimer Cavity Formed by the SARS-CoV-2 Spike Glycoprotein: A Novel Binding Site
PublicationAn 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
PublicationThree 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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System for automatic singing voice recognition
PublicationW 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
PublicationGOAL: 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
PublicationNitrogen 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
PublicationComplexity 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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Faults and Fault Detection Methods in Electric Drives
PublicationThe 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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Problem of aggregation in dye-DNA interaction, calorimetry studies
PublicationNucleic 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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Computationally Efficient Surrogate-Assisted Design of Pyramidal-Shaped 3D Reflectarray Antennas
PublicationReflectarrays (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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Dynamic GPU power capping with online performance tracing for energy efficient GPU computing using DEPO tool
PublicationGPU 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
PublicationIn 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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Marine and Cosmic Inspirations for AI Algorithms
PublicationArtificial 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...