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Search results for: ARTIFICIAL GENE REGULATORY NETWORKS
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Evolving gene regulatory networks controlling foraging strategies of prey and predators in an artificial ecosystem
PublicationCo-evolution of predators and prey is an example of an evolutionary arms race, leading in nature to selective pressures in positive feedback. We introduce here an artificial life ecosystem in which such positive feedback can emerge. This ecosystem consists of a 2-dimensional liquid environment and animats controlled by evolving artificial gene regulatory networks encoded in linear genomes. The genes in the genome encode chemical...
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Evolution of Animats Following a Moving Target in an Artificial Ecosystem
PublicationMany biological animals, even microscopically small, are able to track moving sources of food. In this paper, we investigate the emergence of such behavior in artificial animals (animats) in a 2-dimensional simulated liquid environment. These "predators" are controlled by evolving artificial gene regulatory networks encoded in linear genomes. The fate of the predators is determined only by their ability to gather food and reproduce—no...
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Evolution of artificial single-cell organisms foraging for resources in a 3-dimensional environment
PublicationForaging for resources is a simple cognitive task that even one-celled biological organisms can ac- complish. We present an Artificial Life system in which artificial unicellular organisms (animats) forage for food in a 3-dimensional simulated liquid environment. The movement of animats is controlled by evolving artificial gene regulatory networks encoded in linear genomes. When an animat consumes enough food, it produces offspring...
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Evolution of chemotaxis in single-cell artificial organisms
PublicationThe model of a liquid two-dimensional environment, which is based on physics of diffusion, allows us to simulate the diffusion of morphogenes. Artificial organisms move using a chemotaxis reacting to concentration difference. Organisms are controlled by a gene regulatory network coded in a linear genome and reproduce by division. We made a lot of experiments presenting organisms’ behaviour in various environment conditions. We...
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Small regulatory bacterial RNAs regulating the envelope stress response
PublicationMost bacteria encode a large repertoire of RNA-based regulatory mechanisms. Recent discoveries have revealed that the expression of many genes is controlled by a plethora of base-pairing noncoding small regulatory RNAs (sRNAs), regulatory RNA-binding proteins and RNA-degrading enzymes. Some of these RNA-based regulated processes respond to stress conditions and are involved in the maintenance of cellular homeostasis. They achieve...
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I, Robot: between angel and evil
PublicationThe boosting of most digital innovations within recent technology progress by artificial intelligence (AI) constitutes a growing topic of interest. Besides its technical aspects, increasing research activity may be observed in the domain of security challenges, and therefore of responsibility related to the controlled or hypothetically uncontrolled or autonomous emergence of AI solutions. Consequently, responsibility and ethics...
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Molecular and structural basis of inner core lipopolysaccharide alterations in Escherichia coli: incorporation of glucuronic acid and phosphoethanolamine in the heptose region.
PublicationIt is well established that lipopolysaccharide (LPS) often carries nonstoichiometric substitutions in lipid A and in the inner core. In this work, the molecular basis of inner core alterations and their physiological significance are addressed. A new inner core modification of LPS is described, which arises due to the addition of glucuronic acid on the third heptose with a concomitant loss of phosphate on the second heptose. This...
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Data governance: Organizing data for trustworthy Artificial Intelligence
PublicationThe rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements....
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A mechanistically approached review upon assorted cell lines stimulated by athermal electromagnetic irradiation
PublicationThe probable influence of electromagnetic irradiation on cancer treatment has been deduced from the interaction of artificial electromagnetic emissions with biological organisms. Nonetheless, the suspected health effects induced by electromagnetic-based technology imply that such a treatment may contaminate the adjacent healthy cells. Thus, gaining mechanistic insights into the problem is required to avoid athermal health hazards....
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An Impact Analysis of Artificial Light at Night (ALAN) on Bats. A Case Study of the Historic Monument and Natura 2000 Wisłoujście Fortress in Gdansk, Poland
PublicationThe artificial light at night (ALAN) present in many cities and towns has a negative impact on numerous organisms that live alongside humans, including bats. Therefore, we investigated if the artificial illumination of the historic Wisłoujście Fortress in Gdańsk, Poland (part of the Natura 2000 network), during nighttime events, which included an outdoor electronic dance music (EDM) festival, might be responsible for increased...
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Transcriptome profiling reveals distinctive traits of retinol metabolism and neonatal parallels in the MRL/MpJ mouse
PublicationBackground: The MRL/MpJ mouse is a laboratory inbred strain known for regenerative abilities which are manifested by scarless closure of ear pinna punch holes. Enhanced healing responses have been reported in other organs. A remarkable feature of the strain is that the adult MRL/MpJ mouse retains several embryonic biochemical characteristics, including increased expression of stem cell markers. Results: We explored the transcriptome...
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Loop-mediated isothermal amplification (LAMP) as a diagnostic tool in detection of infectious diseases
PublicationLoop-mediated isothermal amplification (LAMP) is a gene amplification method which amplifies DNA with high specificity and efficiency under isothermal conditions. Because of its rapidity and simplicity, it is a valuable diagnostic tool in the early detection and identification of infectious diseases. LAMP method is based on the use of a set of four to six specially designed primers spanning six to eight distinct sequences on the...
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Pregnane X receptor dependent up-regulation of CYP2C9 and CYP3A4 in tumor cells by antitumor acridine agents, C-1748 and C-1305, selectively diminished under hypoxia
PublicationInduction of proteins involved in drug metabolism and in drug delivery has a significant impact on drug-drug interactions and on the final therapeutic effects. Two antitumor acridine derivatives selected for present studies, C-1748 (9-(2’-hydroxyethylamino)-4-methyl-1-nitroacridine) and C-1305 (5-dimethylaminopropylamino-8-hydroxy-triazoloacridinone), expressed high and low susceptibility to metabolic transformations with liver...
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DNA methylation as a mediator of HLA-DRB1*15:01 and a protective variant in multiple sclerosis
PublicationThe human leukocyte antigen (HLA) haplotype DRB1*15:01 is the major risk factor for multiple sclerosis (MS). Here, we find that DRB1*15:01 is hypomethylated and predominantly expressed in monocytes among carriers of DRB1*15:01. A differentially methylated region (DMR) encompassing HLA-DRB1 exon 2 is particularly affected and displays methylation-sensitive regulatory properties in vitro. Causal inference and Mendelian randomization...
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A MODEL FOR FORECASTING PM10 LEVELS WITH THE USE OF ARTIFICIAL NEURAL NETWORKS
PublicationThis work presents a method of forecasting the level of PM10 with the use of artificial neural networks. Current level of particulate matter and meteorological data was taken into account in the construction of the model (checked the correlation of each variable and the future level of PM10), and unidirectional networks were used to implement it due to their ease of learning. Then, the configuration of the network (built on the...
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Digital Innovations and Smart Solutions for Society And Economy: Pros and Cons
PublicationRecent developments in artificial intelligence (AI) may involve significant potential threats to personal data privacy, national security, and social and economic stability. AI-based solutions are often promoted as “intelligent” or “smart” because they are autonomous in optimizing various processes. Be-cause they can modify their behavior without human supervision by analyzing data from the environ-ment, AI-based systems may be...
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Regulated assembly of lipopolysaccharide and sensing of its alterations in Escherichia coli
PublicationThis thesis describes mechanism of the regulation of the transcription of the rpoE gene encoding an essential RNA polymerase subunit in Escherichia coli. The RpoE regulates extracytoplasmic stress response regulon and is required to initiate transcription of genes, whose products are involvedin the folding of periplasmic proteins and synthesis and transport of outer membrane components. The transcriptional regulation of the rpoE...
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Regulation of LPS assembly via controlled proteolysis and sensing of LPS stress in Escherichia coli
PublicationLipopolysaccharide (LPS) is a complex glycolipid, essential for the bacterial viability and along with phospholipids, it constitutes the major amphiphilic component of outer membrane (OM) in most of the Gram-negative bacteria, including Escherichia coli. LPS molecules confer an effective permeability barrier to the OM and play a crucial role in bacteria-environment and -host interactions. The synthesis and accumulation of this...
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USING ARTIFICIAL NEURAL NETWORKS FOR PREDICTING SHIP FUEL CONSUMPTION
PublicationIn marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types...
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Genome-Wide DNA Methylation and Gene Expression in Patients with Indolent Systemic Mastocytosis
PublicationMastocytosis is a clinically heterogenous, usually acquired disease of the mast cells with a survival time that depends on the time of onset. It ranges from skin-limited to systemic disease, including indolent and more aggressive variants. The presence of the oncogenic KIT p. D816V gene somatic mutation is a crucial element in the pathogenesis. However, further epigenetic regulation may also affect the expression of genes that...
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NADPH Oxidase Gene Polymorphism is Associated with Mortality and Cardiovascular Events in 7-Year Follow-Up
PublicationThe CYBA gene encodes the regulatory subunit of NADPH oxidase, which maintains the redox state within cells and in the blood vessels. That led us to investigate the course of coronary artery disease (CAD) with regards to CYBA polymorphisms. Thus, we recruited 1197 subjects with coronary atherosclerosis and observed them during 7-year follow-up. Three CYBA polymorphisms: c.214C>T (rs4673), c.-932G>A (rs9932581), and c.*24G>A (1049255)...
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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublicationThis paper contains research results of the diagnostics of induction motor bearings based on measurement of the supply current with usage of artificial neural networks. Bearing failure amount is greater than 40% of all engine failures, which makes their damage-free operation crucial. Tests were performed on motors with intentionally made bearings defects. Chapter 2 introduces the concept of artificial neural networks. It presents...
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Application of Artificial Neural Networks to Predict Insulation Properties of Lightweight Concrete
PublicationPredicting the properties of concrete before its design and application process allows for refining and optimizing its composition. However, the properties of lightweight concrete are much harder to predict than those of normal weight concrete, especially if the forecast concerns the insulating properties of concrete with artificial lightweight aggregate (LWA). It is possible to use porous aggregates and precisely modify the composition...
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Predicting the impact of traffic–induced vibrations on buildings using artificial neural networks
PublicationTraffic–induced vibrations may constitute a considerable load to a building, cause cracking of plaster, cracks in load–bearing elements or even a global structural collapse of the whole structure [1-4]. Vibrations measurements of real structures are costly and laborious, not justified in all cases. The aim of the paper is to create an original algorithm, to predict the negative dynamic impact on the examined residential building...
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Artificial Neural Networks for Comparative Navigation
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Modeling of Surface Roughness in Honing Processes by UsingFuzzy Artificial Neural Networks
PublicationHoning processes are abrasive machining processes which are commonly employed to improve the surface of manufactured parts such as hydraulic or combustion engine cylinders. These processes can be employed to obtain a cross-hatched pattern on the internal surfaces of cylinders. In this present study, fuzzy artificial neural networks are employed for modeling surface roughness parameters obtained in finishing honing operations. As...
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Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening
PublicationBeta-glucosidase inhibitors play important medical and biological roles. In this study, simple two-variable artificial neural network (ANN) classification models were developed for beta-glucosidase inhibitors screening. All bioassay data were obtained from the ChEMBL database. The classifiers were generated using 2D molecular descriptors and the data miner tool available in the STATISTICA package (STATISTICA Automated Neural...
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The treatment of wastewater containing pharmaceuticals in microcosm constructed wetlands: the occurrence of integrons (int1–2) and associated resistance genes (sul1–3, qacEΔ1)
PublicationThe aim of this study was to analyze the occurrence of sulfonamide resistance genes (sul1–3) and other genetic elements as antiseptic resistance gene (qacEΔ1) and class 1 and class 2 integrons (int1–2) in the upper layer of substrate and in the effluent of microcosm constructed wetlands (CWs) treating artificial wastewater containing diclofenac and sulfamethoxazole (SMX), which is a sulfonamide antibiotic. The bacteria in the substrate...
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Ship Resistance Prediction with Artificial Neural Networks
PublicationThe paper is dedicated to a new method of ship’s resistance prediction using Artificial Neural Network (ANN). In the initial stage selected ships parameters are prepared to be used as a training and validation sets. Next step is to verify several network structures and to determine parameters with the highest influence on the result resistance. Finally, other parameters expected to impact the resistance are proposed. The research utilizes...
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Applying artificial intelligence for cellular networks optimization
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublicationThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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Artificial Neural Networks in Microwave Components and Circuits Modeling
PublicationArtykuł dotyczy wykorzystania sztucznych sieci neuronowych (SNN) w projektowaniu i optymalizacji układów mikrofalowych.Zaprezentowano podstawowe zasady i założenia modelowania z użyciem SNN. Możliwości opisywanej metody opisano wykorzystując przykładowyprojekt anteny łatowej. Przedstawiono różne strategie modelowania układów, które wykorzystują możliwości opisywanej metody w połączeniu zwiedzą mikrofalową. Porównano również dokładność...
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The Use of Artificial Neural Networks and Decision Trees to Predict the Degree of Odor Nuisance of Post-Digestion Sludge in the Sewage Treatment Plant Process
PublicationThis paper presents the application of artificial neural networks and decision trees for the prediction of odor properties of post-fermentation sludge from a biological-mechanical wastewater treatment plant. The input parameters were concentrations of popular compounds present in the sludge, such as toluene, p-xylene, and p-cresol, and process parameters including the concentration of volatile fatty acids, pH, and alkalinity in...
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Methylation level of the regulatory regions of the estrogen receptor type 1 gene in paravertebral muscles of girls with idiopathic scoliosis
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Predicting Performance of Lightweight Concrete with Granulated Expanded Glass and Ash Aggregate by Means of Using Artificial Neural Networks
PublicationLightweight concrete (LWC) is a group of cement composites of the defined physical, mechanical, and chemical performance. The methods of designing the composition of LWC with the assumed density and compressive strength are used most commonly. The purpose of using LWC is the reduction of the structure’s weight, as well as the reduction of thermal conductivity index. The highest possible strength, durability and low thermal conductivity...
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Automatic singing quality recognition employing artificial neural networks
PublicationCelem artykułu jest udowodnienie możliwości automatycznej oceny jakości technicznej głosów śpiewaczych. Pokrótce zaprezentowano w nim stworzoną bazę danych głosów śpiewaczych oraz zaimplementowane parametry. Przy pomocy sztucznych sieci neuronowych zaprojektowano system decyzyjny, który oceniono w pięciostopniowej skali jakość techniczną głosu. Przy pomocy metod statystycznych udowodniono, że wyniki generowane przez ten system...
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Forecasting of currency exchange rates using artificial neural networks
PublicationW rozdziale tym autor przedstawił wyniki swoich badań nad wykorzystaniem sztucznych sieci neuronowych do prognozowania kursu walut (na przykładzie pary walutowej PLN-USD).Głównym celem badań było porównanie skuteczności przewidywania kursu złotówki w latach 1997 - 2005 przy pomocy różnych rodzajów sieci neuronowych.
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Application of Artificial Neural Networks in Investigations of Steam Turbine Cascades
PublicationZaprezentowano wyniki badań numerycznych zastosowania sieci neuronowych przy obliczeniach przepływów w palisadach turbin parowych. Na podstawie uzyskanych wyników wykazano, że sieci neuronowe mogą być używane do szacowania przestrzennego rozkładu parametrów przepływu, takich jak entalpia, entropia, ciśnienie czy prędkość czynnika w kanale przepływowym. Omówiono również zastosowania tego typu metod przy projektowaniu palisad, stopni...
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Applying artificial neural networks for modelling ship speed and fuel consumption
PublicationThis paper deals with modelling ship speed and fuel consumption using artificial neural network (ANN) techniques. These tools allowed us to develop ANN models that can be used for predicting both the fuel consumption and the travel time to the destination for commanded outputs (the ship driveline shaft speed and the propeller pitch) selected by the ship operator. In these cases, due to variable environmental conditions, making...
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The concept of application of artificial neural networks for cultivation controlof cartilages in bioreactors.
PublicationNowym elementem niniejszej pracy jest omówienie problemów związanych z możliwością sterowania parametrami hydrodynamicznymi hodowanej w bioreaktorze chrząstki stawowej przy wykorzystaniu sztucznych sieci neuronowych. Przedstawiona została architektura strategii sterowania hodowlą tkanki z zastosowaniem tych sieci.
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Processing of musical data employing rough sets and artificial neural networks
PublicationArtykuł opisuje założenia systemu automatycznej identyfikacji muzyki i dźwięków muzycznych. Dokonano przeglądu standardu MPEG-7, ze szczególnym naciskiem na parametry opisowe dźwięku. Przedyskutowano problemy analizy danych audio, związane z zastosowaniami wykorzystującymi MPEG-7. W oparciu o eksperymenty przedstawiono efektywność deskryptorów niskiego poziomu w automatycznym rozpoznawaniu dźwięków instrumentów muzycznych. Przedyskutowano...
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Processing of musical data employing rough sets and artificial neural networks
PublicationArtykuł opisuje założenia systemu automatycznej identyfikacji muzyki i dźwięków muzycznych. Dokonano przeglądu standardu MPEG-7, ze szczególnym naciskiem na parametry opisowe dźwięku. Przedyskutowano problemy analizy danych audio, związane z zastosowaniami wykorzystującymi MPEG-7. W oparciu o eksperymenty przedstawiono efektywność deskryptorów niskiego poziomu w automatycznym rozpoznawaniu dźwięków instrumentów muzycznych. Przedyskutowano...
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Analysis of electrical patterns activity in artificial multi-stable neural networks
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Artificial Neural Networks for Prediction of Antibacterial Activity in Series of Imidazole Derivatives
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The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification
PublicationDeveloping of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and...
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Artificial Neural Networks in Classification of Steel Grades Based on Non-Destructive Tests
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Designing the Composition of Cement Stabilized Rammed Earth Using Artificial Neural Networks
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The Influence of Input Data Standardization Method on Prediction Accuracy of Artificial Neural Networks
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Self-organizing Artificial Neural Networks into Hydrographic Big Data Reduction Process
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Heavy duty vehicle fuel consumption modelling using artificial neural networks
PublicationIn this paper an artificial neural network (ANN) approach to modelling fuel consumption of heavy duty vehicles is presented. The proposed method uses easy accessible data collected via CAN bus of the truck. As a benchmark a conventional method, which is based on polynomial regression model, is used. The fuel consumption is measured in two different tests, performed by using a unique test bench to apply the load to the engine. Firstly,...