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Cloud solutions as a platform for building advanced learning platform, that stimulate the real work environment for project managers
PublicationImproving skills of managers and executives require, that during the transfer of knowledge (in different ways: during studies, trainings, workshops and other forms of education) it is necessary to use tools and solutions that are (or will be) used in real world environments, where people being educated are working or will work. Cloud solutions allow educational entities (universities, training companies, trainers, etc.) to provide...
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublicationWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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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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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublicationAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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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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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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Mapping the Structural and Dynamic Determinants of pH-Sensitive Heparin Binding to Granulocyte Macrophage Colony Stimulating Factor
PublicationGranulocyte macrophage colony stimulating factor (GMCSF) is an immunomodulatory cytokine that is harnessed as a therapeutic. GMCSF is known to interact with other clinically important molecules, such as heparin, suggesting that endogenous and administered GMCSF has the potential to modulate orthogonal treatment outcomes. Thus, molecular level characterization of GMCSF and its interactions with biologically active compounds is critical...
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Do mistakes acceptance foster innovation? Polish and US cross-country study of tacit knowledge sharing in IT
PublicationAbstract Purpose – This study aims to understand and compare how the mechanism of innovative processes in the information technology (IT) industry – the most innovative industry worldwide – is shaped in Poland and the USA in terms of tacit knowledge awareness and sharing driven by a culture of knowledge and learning, composed of a learning climate and mistake acceptance. Design/methodology/approach – Study samples were drawn from...
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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublicationOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublicationNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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Process [Intellectual Output 2] Guidelines for a design process leading to a high-quality Baukultur in the digital age
PublicationThe main aim of the intellectual output “Process” is to identify, explore and evaluate new design processes for shaping the built environment, which are informed, collaborative, and adaptable, allow customization and are generally enabled by the application of digital tools. Further, it aims at creating methodological guidelines for future-oriented design processes leading to a high-quality Baukultur in the digital age. The guidelines...
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Experimental study on the feasibility of alternative materials for tilting pad thrust bearings operating in transition to mixed friction
PublicationIn hydrodynamic bearings traditional bearing alloys: Babbitts and bronzes are most frequently utilized. Polymer sliding layers are sometimes applied as a valuable alternative. Hard diamond-like carbon (DLC) coatings, which are also considered for certain applications may show some advantages, as well. Although material selection is of secondary importance in a full film lubrication regime it becomes important in mixed friction...
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Understanding Sustainable Knowledge-Sharing in Agile Projects: Utilizing Follow-the-Sun Technique (FTS) in Virtual Teams
PublicationIn Agile IT projects, promoting effective knowledge sharing is essential not only for achieving success but also for supporting Sustainable Development Goals (SDGs). However, Companies using virtual teams may face challenges in coordinating work, particularly when teams are distributed across different time zones, ultimately hindering their ability to consistently share knowledge. This can lead to delays and inefficiencies, ultimately...
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Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublicationThe rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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NLITED - New Level of Integrated Techniques for Daylighting Education: Preliminary Data on the Use of an E-learning Platform
PublicationProject NLITED – New Level of Integrated Techniques for Daylighting Education - is an educational project for students and professionals. The project's objective is to create and develop an online eLearning platform with 32 eModules dedicated to daylight knowledge. The project also offers e-learners two summer school training where the theory is put into practice. The platform was launched on January 31, 2022. The paper...
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublicationThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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Knowledge Sharing and Managing Intellectual Capital in the Times of COVID-19: Evidence from Polish Restaurant Industry
PublicationPurpose: The aim of this paper is to show how restaurants in Poland managed their intellectual capital (IC) in the COVID-19 crisis and how knowledge sharing (KS) helped them to survive in those dynamically changing conditions. Methodology: The study is based on qualitative research – semi-structured interviews with a few restaurant owners and managers responsible for the business operations during...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublicationMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Sliding bearings with sintered bronze bush lubricated by contaminated water with solid particles – Theoretical and experimental studies
PublicationSliding journal bearings lubricated with water coming directly from the environment are a solution used in shipbuilding, pumps and hydropower. However, the working fluid or surrounding water cannot always be filtered because of design limitations, which often causes the problem of premature wear of these sensitive bearings. The research conducted made it possible to assess the wear of sliding bearings lubricated with water containing...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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A multi‐industry and cross‐country comparison of technology contribution to formal and informal knowledge sharing processes for innovativeness
PublicationThe study explores the impact of organizational information technology (IT) competency on knowledge sharing, both explicit and tacit, in the context of innovativeness of products and processes. Knowledge sharing is then assessed in terms of tacit-to-explicit conversion and the impact of both types of knowledge on organizational innovation. Both process (internal) and product/service (external) innovation are included. As an extension,...
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Technological vs. Non-Technological Mindsets: Learning From Mistakes, and Organizational Change Adaptability to Remote Work
PublicationThe permanent implementation of the change in working methods, e.g., working in the virtual space, is problematic for some employees and, as a result, for management leaders. To explore this issue deeper, this study assumes that mindset type: technological vs. non-technological, may influence the organizational adaptability to change. Moreover, the key interest of this research is how non-technological mindsets...
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Scaled agile framework. Dealing with software process‐related challenges of a financial group with the action research approach
PublicationThis article reports on a domain-specific software development venture at Nordea. We explore organizational constraints, challenges, and corrective actions undertaken when scaling the agile development approach of their Core Banking Platform program. The fit and required customizations of the rather complex and rigid SAFe framework in a policy-heavy financial institution are audited against the organic growth of the program. In...
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublicationOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
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Post-comatose patients with minimal consciousness tend to preserve reading comprehension skills but neglect syntax and spelling
PublicationModern eye tracking technology provides a means for communication with patients suffering from disorders of consciousness (DoC) or remaining in locked-in-state. However, being able to use an eye tracker for controlling text-based contents by such patients requires preserved reading ability in the first place. To our knowledge, this aspect, although of great social importance, so far has seemed to be neglected. In the paper, we...
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Knowledge Sharing in the COVID-19 Era of Remote Teaching: What Can Academia Learn from Business?
PublicationPurpose: The aim of this paper is to investigate how universities may benefit from experiences of businesses that were also forced to use remote forms of business operations. Methodology: The paper uses in-depth interviews to explore the possibilities of knowledge sharing improvements at the university-level teaching, based on the experiences elicited in the business sector. The theoretical sampling was used to find informants...
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublicationIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublicationData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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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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Assessment of Failure Occurrence Rate for Concrete Machine Foundations Used in Gas and Oil Industry by Machine Learning
PublicationConcrete machine foundations are structures that transfer loads from machines in operation to the ground. The design of such foundations requires a careful analysis of the static and dynamic effects caused by machine exploitation. There are also other substantial differences between ordinary concrete foundations and machine foundations, of which the main one is that machine foundations are separated from the building structure....
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Four-state measurement method for direct-reading noise figure measurement of low-gain two-ports.
PublicationOmówiono problemy techniczne pomiaru współczynnika szumu dwuwrotników o małym wzmocnieniu mocy dysponowanej realizowanych przy stosowaniu znanych metod pomiaru współczynnika szumu. Przedstawiono nową czterostanową metodę pomiaru umożliwiającą uniezależnienie wskazań automatycznego miernika współczynnika szumu zarówno od wartośći wzmocnienia dwuwrotnika badanego jak i współczynnika szumu odbiornika pomiarowego. Wyprowadzone zależności...
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Projekt Leonardo da Vinci EMDEL (European Model for Distance Education and Learning) - otwarte szkolenia online.
PublicationW referacie zaprezentowano główne zadania oraz ofertę szkoleniową Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej (CEN PG) w kontekście realizowanych projektów Unii Europejskiej. Przedstawiono projekt Leonardo da Vinci EMDEL - European Model for Distance Education and learning - realizowany przez CEN PG w latach 2001-2005 oraz opisano doświadczenia w zakresie adaptacji i lokalizacji opracowanych przez partnerów projektu...
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Diagnostyka łożysk silnika indukcyjnego na podstawie prądu zasilającego przy użyciu sztucznych sieci neuronowych
PublicationW artykule zawarto wyniki badań dotyczące diagnostyki łożysk silnika indukcyjnego na podstawie pomiarów prądu zasilającego z wykorzystaniem sztucznych sieci neuronowych. Zaprezentowano wyniki uczenia sieci oraz rezultaty testów przeprowadzonych na danych spoza zbioru uczącego. Badania wykonane zostały na obiektach z celowo wprowadzonymi uszkodzeniami łożysk. Przedstawiona nowa koncepcja zakłada użycie zestawu sieci neuronowych...
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Design and Evaluation of the Platform for Weight-Shifting Exercises with Compensatory Forces Monitoring
PublicationDetails of a platform for the rehabilitation of people with severe balance impairment are discussed in the paper. Based upon a commercially available static parapodium, modified to fit force sensors, this device is designed to give a new, safe tool to physiotherapists. It is designed for the patients who cannot maintain equilibrium during a bipedal stance and need to hold to or lean on something during the rehabilitation. Visual,...
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Music information retrieval—The impact of technology, crowdsourcing, big data, and the cloud in art.
PublicationThe exponential growth of computer processing power, cloud data storage, and crowdsourcing model of gathering data bring new possibilities to music information retrieval (mir) field. Mir is no longer music content retrieval only; the area also comprises the discovery of expressing feelings and emotions contained in music, incorporating other than hearing modalities for helping this issue, users’ profiling, merging music with social...
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Possibility to use engine compression ignition engines in floating power plants marine
PublicationCompression-ignition engines used in ship technology as main propulsion engines are large units reaching even to 50-60 MW. The engines can be used in power industry for electricity generation in a simple or combined steam turbine system in combined heat and power plants. The leading engine in such an arrangement is an internal-combustion piston engine. The main propulsion engines are used in large piston internal-combustion engines...
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Ocena wybranych własności materiałowych polimerowej warstwy ślizgowej hydrodynamicznego łożyska wzdłużnego = An estimation of selected material properties of the hydrodynamic thrust bearing polymer lining
PublicationZaprezentowano metody pomiaru najważniejszych własności mechanicznych i cieplnych polimerowego pokrycia segmentowego łożyska wzdłużnego, do których zaliczyć należy moduł sprężystości wzdłużnej oraz współczynnik przewodności cieplnej materiału dodatkowym utrudnieniem planowanego zadania jest fakt, że próbka do badań dostępna będzie jedynie w formie wycinka z segmentu łożyskowego, z tego powodu nie jest możliwe zastosowanie ogólnie...
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Identification of lipid fraction constituents from grasshopper (Chorthippus spp.) abdominal secretion with potential activity in wound healing with the use of GC–MS/MS technique
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Keratin-Butyrate Scaffolds Promote Skin Wound Healing in Diabetic Rats Through Down-Regulation of IL-1β and Up-Regulation of Keratins 16 and 17
PublicationImpaired wound healing particularly in diabetics creates a significant healthcare burden. The study aimed to evaluate the effect of keratin-butyrate fibers (FKDP +0.1%NaBu) in a full-thickness skin wound model in 30 diabetic rats. Physicochemical examination showed that the obtained dressing possesses a heterogeneous structure and butyrate was slowly released into the wound. Moreover, the obtained dressing is nontoxic and supports...
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Analiza nośności zabytkowych fundamentów w kontekście jakości użytych zapraw Analysis of the Load-Bearing Capacity of Historical Foundations in the Context of the Quality of Mortar Used
PublicationStructures of historical buildings usually have the form of masonry elements. The weakest component of such elements is mortar, especially in stone foundations, which were often used in the with a focus on the modeling of mortar as a joint connecting stones in a characteristic medieval foundation. Different types of mortar: cement, cement-lime, lime and gypsum mortars, were examined. A numerical analysis was carried out on the...
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A surface-exposed DraD protein of uropathogenic Escherichia coli bearing Dr fimbriae may be expressed and secreted independently from DraC usher and DraE adhesin
PublicationOperon dra uropatogennych szczepów Escherichia coli Dr+ odpowiedzialny jest za proces bakteryjnej adhezji i inwazji. Operon dra kodujący fimbrie Dr zawiera sześć otwartych ramek odczytu - draA, draB, draC, draD, draP oraz draE. Fimbrie Dr zlokalizowane na powierzchni komórki bakteryjnej, zbudowane są z podjednostek białka DraE. Niewiele wiadomo na temat powierzchniowej ekspresji białka DraD oraz jego roli w procesie biogenezy fimbrii...
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Transformational leadership for researcher’s innovativeness in the context of tacit knowledge and change adaptability
PublicationThis study explores how a learning culture supported by transformational leadership influences tacit knowledge sharing and change adaptability in higher education and how these relations impact this sector’s internal and external innovativeness. The empirical model was tested on a sample of 368 Polish scientific staff using the structural equation modeling (SEM) method. Then results were expanded by applying OLS regression using...
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Professional activity, gender and disease-related emotions: The impact on parents' experiences in caring for children with phenylketonuria
PublicationIntroduction: Clinical management of rare diseases often fails to acknowledge the challenges faced by caregivers.Whilst management of phenylketonuria (PKU) may not be considered as dire as other conditions, most studiesprimarily concentrate on clinical issues, dietary adherence, or the quality of life of the PKU patients, leavingcaregivers in the background. The aim of the study was to evaluate the psychosocial...
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Professional activity, gender and disease-related emotions: The impact on parents' experiences in caring for children with phenylketonuria
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Evaluating the challenges and needs of parents caring for children with Williams syndrome: A preliminary study from Poland
PublicationBackground: Although physical, cognitive and behavioural manifestations of Williams syndrome(WS) affect every dimension of caregivers lives, no studies on the parental experiences of caringfor a WS child have to date been carried out in Poland.Methods: In order to identify the challenges and needs of Polish carers of WS children a survey wasconducted...
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Study of Non-Newtonian biomagnetic blood flow in a stenosed bifurcated artery having elastic walls
PublicationFluid structure interaction (FSI) gained attention of researchers and scientist due to its applications in science felds like biomedical engineering, mechanical engineering etc. One of the major application in FSI is to study elastic wall behavior of stenotic arteries. In this paper we discussed an incompressible Non-Newtonian blood fow analysis in an elastic bifurcated artery. A magnetic feld is applied along x direction. For...
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Bilingual advantage? Literacy and phonological awareness in Polish-speaking early elementary school children learning English simultaneously
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