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Search results for: alphafold, blind prediction, capri, casp, deep learning, protein assemblies, protein complexes, protein-protein interaction
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Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning
PublicationMy doctoral dissertation is intended as the compound of four publications considering: structure and randomness in planning and reinforcement learning, continuous control with ensemble deep deterministic policy gradients, toddler-inspired active representation learning, and large-scale deep reinforcement learning costs.
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublicationHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Distinct hippocampal-prefrontal neural assemblies coordinate memory encoding, maintenance, and recall
PublicationShort-term memory enables incorporation of recent experience into subsequent decision-making. This processing recruits both the prefrontal cortex and hippocampus, where neurons encode task cues, rules, and outcomes. However, precisely which information is carried when, and by which neurons, remains unclear. Using population decoding of activity in rat medial prefrontal cortex (mPFC) and dorsal hippocampal CA1, we confirm that mPFC...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublicationIn this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model has been used. The task is to predict simultaneously and independent of each characteristic parameters of a buried object of several radii at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable...
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Zastosowanie addytywów w separacji pianowej białek serwatkowych i białek mlecznych
PublicationZaproponowano proces separacji pianowej do wydzielania białek ze strumieni poprodukcyjnych przemysłu mleczarskiego Ponadto zaproponowano zastosowanie w separacji pianowej białek serwatkowych i mlecznych addytywów dopuszczonych ustawą do stosowania w żywności. Jako cel pracy przyjęto uzyskanie wyników uzasadniających wybór takich addytywów, które intensyfikują przebieg i polepszają wynik procesu separacji pianowej białek. W części...
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Learning Culture and Social Interaction
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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublicationHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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AGAR a Microbial Colony Dataset for Deep Learning Detection
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Musical Instrument Identification Using Deep Learning Approach
PublicationThe work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related to musical instrument identification. It focuses on tasks performed, input type, algorithms employed, and metrics used. The paper starts with the background presentation, i.e., metadata...
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Monitoring of lysozyme thermal denaturation by volumetric measurements and nanoDSF technique in the presence of N-butylurea
PublicationThe results of thermal studies of denaturation of hen egg white lysozyme (HEWL) in water and an aqueous solution of N-butylurea (BU) are presented. High-precision densimetric measurements were used to characterize and analyze the changes of the specific volume, v, during temperature elevation. The temperature of the midpoint of protein denaturation was also determined by nanoDSF technique (differential scanning fluorimetry). The...
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Aravind Ayyolath
PeopleI am interested in the biology of bacterial stress response and its growth under stress conditions. Our lab focuses on two aspects; protein folding and lipopolysaccharide biosynthesis and we address them with Escherichia coli models. Our recent studies have provided more evidence regarding several genes involved in the survival of bacteria under stress. I am also interested in disease biology and also in identifying proper therapeutic...
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Self-assemblies of novel magnesium porphyrins mimicking natural chlorosomal bacteriochlorophylls
PublicationSelf-assembling porphyrins are promising materials to mimic natural bacteriochlorophylls c, d, or e encountered in the chlorosomes of photosynthetic bacteria. We have studied four novel magnesium porphyrins mimicking this chlorosomal antenna system. In contrast to previous articles reporting synthetic Zn-porphyrins, our studies focus on porphyrins with Mg as the central atom, which mimic more closely the natural bacteriochlorophylls....
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Color Processing for Color-Blind Individuals Using Smart Glasses
PublicationIn this paper we investigated image processing methods for color-blind individuals. In particular we experimentally verified color naming procedure, generation of maps with color perception differences for average observers and for dichromats, and two color transformation methods. In experiments 7 mobile devices were used: 3 smart glasses and 4 smartphones. User studies were performed with 38 average observers and 9 dichromats....
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublicationThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublicationBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublicationCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
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Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublicationThe Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...
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DentalSegmentator: robust deep learning-based CBCT image segmentation
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Generation of microbial colonies dataset with deep learning style transfer
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Deep learning-based waste detection in natural and urban environments
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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublicationIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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Natural fish oil improves the differentiation and maturation of oligodendrocyte precursor cells to oligodendrocytes in vitro after interaction with the blood–brain barrier
PublicationThe blood–brain barrier (BBB) tightly controls the microenvironment of the central nervous system (CNS) to allow neurons to function properly. Additionally, emerging studies point to the beneficial effect of natural oils affecting a wide variety of physiological and pathological processes in the human body. In this study, using an in vitro model of the BBB, we tested the influence of natural fish oil mixture (FOM) vs. borage oil...
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AmiP from hyperthermophilic Thermus parvatiensis prophage is a thermoactive and ultrathermostable peptidoglycan lytic amidase
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Molecular simulation study of cooperativity in hydrophobic association
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In silico epitope prediction of Borrelia burgdorferi sensu lato antigens for the detection of specific antibodies
PublicationDespite many years of research, serodiagnosis of Lyme disease still faces many obstacles. Difficulties arise mainly due to the low degree of amino acid sequence conservation of the most immunogenic antigens among B. burgdorferi s.l. genospecies, as well as differences in protein production depending on the environment in which the spirochete is located. Mapping B-cell epitopes located on antigens allows for a better understanding...
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The structurally similar TRFH domain of TRF1 and TRF2 dimers shows distinct behaviour towards TIN2
PublicationThe telomere repeat binding-factor 1 and 2 (TRF1 and TRF2) proteins of the shelterin complex bind to duplex telomeric DNA as homodimers, and the homodimerization is mediated by their TRFH (TRF-homology) domains. We performed molecular dynamic (MD) simulations of the dimer forms of TRF1TRFH and TRF2TRFH in the presence/absence of the TIN2TBM (TIN2, TRF-interacting nuclear protein 2, TBM, TRF-binding motif) peptide. The MD results...
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Amides as models to study the hydration of proteins and peptides — spectroscopic and theoretical approach on hydration in various temperatures
PublicationInteractions with water are one of the key factors which determine protein stability and activity in aqueous solutions. However, the protein hydration is still insufficiently understood. N-methylacetamide (NMA) is regarded as a minimal part of the peptide backbone and the relative simplicity of its structure makes it a good model for studies on protein–water interactions. In this paper, the influence of NMA and N,N-dimethylacetamide...
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Effect of osmolytes on the thermal stability of proteins: replica exchange simulations of Trp-cage in urea and betaine solutions
PublicationAlthough osmolytes are known to modulate the folding equilibrium, the molecular mechanism of their effect on thermal denaturation of proteins is still poorly understood. Here, we simulated the thermal denaturation of a small model protein (Trp-cage) in the presence of denaturing (urea) and stabilizing (betaine) osmolytes, using the all-atom replica exchange molecular dynamics simulations. We found that urea destabilizes Trp-cage...
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Tuning Ferulic Acid Solubility in Choline-Chloride- and Betaine-Based Deep Eutectic Solvents: Experimental Determination and Machine Learning Modeling
PublicationDeep eutectic solvents (DES) represent a promising class of green solvents, offering particular utility in the extraction and development of new formulations of natural compounds such as ferulic acid (FA). The experimental phase of the study undertook a systematic investigation of the solubility of FA in DES, comprising choline chloride or betaine as hydrogen bond acceptors and six different polyols as hydrogen bond donors....
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Agnieszka Landowska dr hab. inż.
PeopleAgnieszka Landowska works for Gdansk University of Technology, FETI, Department of Software Engineering. Her research concentrates on usability, accessibility and technology adoption, as well as affective computing methods. She initiated Emotions in HCI Research Group and conducts resarch on User eXperiene evaluation of applications and other technologies.
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Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review
PublicationBackground: In the context of Warehouse Management Systems, knowledge related to motion trajectory prediction methods utilizing machine learning techniques seems to be scattered and fragmented. Objective: This study seeks to fill this research gap by using a systematic literature review approach. Methods: Based on the data collected from Google Scholar, a systematic literature review was performed, covering the period from 2016...
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Role of the Solvation Water in Remote Interactions of Hyperactive Antifreeze Proteins with the Surface of Ice
PublicationMost protein molecules do not adsorb onto ice, one of the exceptions being so-called antifreeze proteins. In this paper, we describe that there is a force pushing an antifreeze protein molecule away from the ice surface when it is not oriented with its ice-binding plane toward the ice and that this pushing force may be also present even when the protein is oriented with its ice-binding plane toward the ice. This force is absent...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Smartphone application supporting independent movement of the blind
PublicationImproving comfort of life of blind people is a problem of great importance. Neither a white canenor a guide dog, although both very useful, can be considered as a tool for achieving fullindependence in everyday movement around the city. On the market there are some navigation toolsinspired by car navigation systems, but they have many flaws, ranging from positioninginaccuracies to high prices. The authors present their own solution...
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Client-server Approach in the Navigation System for the Blind
PublicationThe article presents the client‐server approach in the navigation system for the blind ‐ “Voice Maps”. The authors were among the main creators of the prototype and currently the commercialization phase is being finished. In the implemented prototype only exemplary, limited spatial data were used, therefore they could be stored and analysed (for path-finding process) in the mobile device’s memory without any difficulties. The...
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Extracting functional groups of ALLINI to design derivatives of FDA‐approved drugs: Inhibition of HIV‐1 integrase
PublicationHIV‐1 integrase (IN) is crucial for integration of viral DNA into the host genome and a promising target in development of antiretroviral inhibitors. In this work, six new compounds were designed by linking the structures of two different class of HIV‐1 IN inhibitors (active site binders and allosteric IN inhibitors (ALLINIs)). Among newly designed compounds, INRAT10b was found most potent HIV‐1 IN inhibitor considering different...
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Pilicides effectively hinder chaperone-usher interactions in all Gram-negative bacteria
PublicationThe chaperone-usher pathway of adhesive structures biogenesis is highly conserved in all Gram-negative bacteria. Pili are polymers of thousands protein subunits that possess conserved immunoglobuline-like structure denoted by lack of the seventh G strand. The effect of this structural defect is a hydrophobic acceptor cleft. The folding of protein subunits is strictly dependent on the action of specific periplasmic chaperone protein...
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Voice Maps - portable, dedicated GIS for supporting street navigtion and self-dependent movement of the blind
PublicationThe concept and the prototype application of the system supporting the street navigation and independent, outdoor movement of the blind is presented. The system utilises the GIS database of geometric network of the pedestrian paths in the city and is capable of finding the route from the indicated source to destination. Subsequently, the system supports the movement of the blind along the found route. The information on the user's...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublicationNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Deep learning approach for delamination identification using animation of Lamb waves
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Deep learning super-resolution for the reconstruction of full wavefield of Lamb waves
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OmicSelector: automatic feature selection and deep learning modeling for omic experiments
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublicationObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Remote Spatial Database Access in the Navigation System for the Blind
PublicationThe article presents the problem of a database access in the navigation systems. The authors were among the main creators of the prototype navigation system for the blind - “Voice Maps”. In the implemented prototype only exemplary, limited spatial data were used, therefore they could be stored in the mobile device’s memory without any difficulties. Currently the aforementioned system is being prepared for commercialization - the...
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Structural studies on radiopharmaceutical DOTA-minigastrin analogue (CP04) complexes and their interaction with CCK2 receptor
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Molecular dynamics study on the role of solvation water in the adsorption of hyperactive AFP to the ice surface
PublicationUsing computer simulations, the early stages of the adsorption of the CfAFP molecule to the ice surface were analyzed. We found that the ice and the protein interact at least as early as when the protein is about 1 nm away from the ice surface. These interactions are mediated by interfacial solvation water and are possible thanks to the structural ordering of the solvent. This ordering leads to positional preference of the protein...