The list of national projects SAS
Institute of Measurement Science
EEG data analysis by blind source separation methods
Analýza EEG signálu pomocou metód hľadania skrytých zdrojov
| Duration: |
1.9.2024 - 31.8.2026 |
| Program: |
|
| Project leader: |
Mgr. Rošťáková Zuzana PhD. |
| Annotation: | Blind source separation (BSS) approaches are unsupervised machine learning methods focused on the detection of hidden, directly unobservable (latent) structure of real-world data. They play a crucial role in image processing, medical imaging, and music. The proposed project focuses mainly on human electroencephalogram (EEG), for which BSS is beneficial when detecting the narrowband brain oscillations representing brain processes either in health or disease. Two-dimensional BSS methods like principal or independent component analysis are easily applicable and understandable for a broader medical and neurophysiological community. However, the estimated latent component properties are usually incompatible with the real electrophysiological signal character. Consequently, they miss their neurophysiological interpretation. Tensor decomposition is a complex but more flexible mathematical procedure that allows adapting the model structure and constraints to the solution to mimic real-world signal characteristics. The proposed project focuses on tensor decomposition as a tool for i) EEG preprocessing, artefact detection and removal, ii) EEG latent structure analysis using a nonnegative tensor decomposition with block structure allowing to model various relationships between latent components, and iii) post-decomposition analysis of latent component dynamic properties. Obtaining comprehensive information about EEG latent structure and developing novel, user-friendly algorithms is crucial for better understanding brain processes and new methods for treating neurophysiological diseases and disorders. |
Automatic data evaluation tool from the longitudinal quantitative MRI studies of articular cartilage
Automatický softvérový nástroj na výhodnocovanie kvantitatívnych MRI štúdií artikulárných chrupaviek v čase
| Duration: |
1.7.2022 - 30.6.2026 |
| Program: |
SRDA |
| Project leader: |
Ing. Dr. Szomolányi Pavol (PhD.) |
| Annotation: | The aim of the project is to design a comprehensive tool for automatic evaluation of human articular cartilage data from quantitative MRI. Data obtained from the Osteoarthritis Initiative database, and measured at Institute of Measurement Science and Medical University of Vienna will be segmented using an automated segmentation tool based on convolutional neural networks. The annotated data will then be registered on quantitative MRI data that will be available from the database (T2 and T1rho mapping, gagCEST, sodium MR) using automated or semiautomated tools developed within this project. The data obtained will be evaluated at multiple time points according to MR measurements that will be available. In addition to quantitative MR data, this will include volumetric data, cartilage thickness, and texture analysis of quantitative maps. Patient evaluation will be based on risk factor groups (transverse ligament rupture, meniscus rupture and menisectomy). The expected number of patients is approximately 4000 divided into individual groups in the ratio 40/30/30. The output of the project will be a compiled version of an automatic cartilage evaluation tool that will be available in a public source (such as website of Institute of Measurement). |
Trustworthy human–robot and therapist–patient interaction in virtual reality
Dôveryhodná interakcia človek–robot a terapeut–pacient vo virtuálnej realite
| Duration: |
1.7.2022 - 30.6.2026 |
| Program: |
SRDA |
| Project leader: |
Ing. Mgr. Rosipal Roman DrSc. |
| Annotation: | We aim to study specific forms of social interaction using state-of-the-art technology - virtual reality (VR) which is
motivated by its known benefits. The project has two main parts, human–robot interaction (HRI) and therapist–
patient interaction (TPI). The interactions are enabled using head-mounted displays and controllers allowing the
human to act in VR. We propose two research avenues going beyond the state-of-the-art in respective contexts. In
HRI, we will develop scenarios allowing the humanoid robot to learn, understand and imitate human motor actions
using flexible feedback. Next, we develop scenarios for testing and validating human trust in robot behavior based
on multimodal signals. We will also investigate physical interaction with a humanoid robot NICO. In TPI with stroke
patients, we develop a series of VR-based occupational therapy procedures for motor and cognitive impairment
neurorehabilitation using an active and passive brain-computer interface, and we will validate these procedures.
We expect observations from HRI experiments to be exploited in TPI. The proposed project is highly
multidisciplinary, combining knowledge and research methods from psychology, social cognition, robotics, machine
learning and neuroscience. We expect to identify features and mechanisms leading to trustworthy processes with a
human in the loop, as a precondition of success, be it a collaborative task or treatment in VR. |
Identification of stress-induced alterations in expression of NRF2 target genes in rat models of prehypertension: the effect of comorbid hypertriglyceridemia and dimethyl fumarate treatment
Identifikácia stresom vyvolaných zmien v expresii cieľových génov NRF2 v potkaních modeloch prehypertenzie: vplyv komorbidnej hypertriglyceridémie a liečby dimetylfumarátom
| Duration: |
1.7.2023 - 30.6.2027 |
| Program: |
SRDA |
| Project leader: |
Ing. Maňka Ján CSc. |
| Annotation: | The nuclear transcription factor erythroid 2-related factor 2 (NRF2) is a key molecular link between several non-
communicable diseases, as it regulates the expression of approximately 250 target genes, including those involved
in maintenance of redox balance, the development of metabolic disorders, cardiovascular and liver diseases, as
well as in immune responses. Borderline elevated blood pressure (prehypertension) is a common cardiovascular
disorder in humans, and elevated blood pressure has been found to be positively correlated with triglyceride levels.
In addition, chronic stress is an etiological factor in the development of non-communicable diseases, including
elevated blood pressure and hypertriglyceridemia (HTG). In experimental studies, borderline hypertensive rats
(BHR) and hypertriglyceridemic rats (HTGR) are suitable models of prehypertension without and with comorbid
hypertriglyceridemia. These models are relevant for investigating the effects of stress as well as for investigating
the role of changes in expression of NRF2 target genes in the development of hypertension associated with
metabolic diseases. To understand better the role of NFR2 as well as the impact of chronic social stress on the
mentioned diseased states, the aims of this project are: 1) to identify differences in expression of NRF2 target
genes in two experimental models of prehypertension - without (in BHR) and with (in HTGR) comorbid HTG - in
control conditions and during chronic social stress, 2) to determine if NRF2 activator dimethyl fumarate can reduce
stress-induced pathologies in prehypertensive rats, especially in those with comorbid HTG, and 3) to specify a set
of suitable whole blood RNA biomarkers for evaluation of changes in NRF2 target genes in prehypertension and
HTG and those genes altered by chronic social stress. |
Innovations in the Transfer Entropy Method: Implementing Alternative Entropic Measures for More Robust Causal Inference
Inovácie v metóde prenosovej entropie: Implementácia alternatívnych entropických mier pre robustnejšiu kauzálnu inferenciu
| Duration: |
1.7.2025 - 30.6.2026 |
| Program: |
|
| Project leader: |
Mgr. Mezeiová Kristína PhD. |
| Annotation: | The aim of the project is to explore the use of alternative entropy measures, such as Rényi entropy, Tsallis entropy, and permutation entropy, in the transfer entropy method to enhance the accuracy, robustness, and computational efficiency of causal analysis in complex systems. The project will focus on the software implementation of appropriately modified causal algorithms, their testing on synthetic and real-world data, and the identification of areas where the proposed innovations provide significant advantages. |
Smart deep brain stimulation as a treatment strategy in treatment-resistant depression
Inteligentná hĺbková mozgová stimulácia ako inovatívna stratégia pre liečbu mozgových porúch
| Duration: |
1.1.2022 - 31.12.2025 |
| Program: |
VEGA |
| Project leader: |
Ing. Mgr. Rosipal Roman DrSc. |
| Annotation: | Impaired connectivity between different brain areas underlines the pathophysiology of multiple brain disorders. It is possible that impaired connectivity between the prefrontal cortex and ventral pallidum is involved in depression. Smart deep brain simulation, combining real-time detection of the neuronal activity in the prefrontal cortex with the stimulation of the ventral tegmental area might be thus effective in depression. We aim to examine the cortico-tegmental connectivity and to test the antidepressant-like effectiveness of the smart deep brain stimulation in an animal model of depression. |
Causal analysis of measured signals and time series
Kauzálna analýza nameraných signálov a časových radov
| Duration: |
1.1.2022 - 31.12.2025 |
| Program: |
VEGA |
| Project leader: |
RNDr. Krakovská Anna CSc. |
| Annotation: | The project is focused on the causal analysis of measured time series and signals. It builds on the previous results of the team, concerning the generalization of the Granger test and the design of new tests in the reconstructed state spaces. The aim of the project is the development of new methods for bivariate and multidimensional causal analysis. We will see the investigated time series and signals as one-dimensional manifestations of complex systems or subsystems. We will also extend the detection of causality to multivariate cases - dynamic networks with nodes characterized by time series. Such complex networks are common in the real world. Biomedical applications are among the best known. Brain activity, determined by multichannel electroencephalographic signals, is a crucial example. We want to help show that causality research is currently at a stage that allows for ambitious goals in the study of effective connectivity (i.e., directed interactions, not structural or functional links) in the brain. |
Multi-lead ECG measurement to create a personalized model of the electric field of the heart and research the possibilities of its use for the diagnosis and optimization of cardiac arrhythmia therapy
Mnohozvodové meranie EKG na vytvorenie personalizovaného modelu elektrického poľa srdca a výskum možností jeho využitia na diagnostiku a optimalizáciu terapie srdcových arytmií
| Duration: |
1.1.2025 - 31.12.2028 |
| Program: |
VEGA |
| Project leader: |
Ing. Švehlíková Jana PhD. |
| Annotation: | In the proposed project, we plan to link multi-lead ECG measurements on the chest with a personalized
model of the heart and chest of the measured patient obtained from a CT scan. We intend to implement the physiological properties of healthy myocardium into the heart chamber model, as well as some pathological morphological and structural changes, such as left ventricular hypertrophy or left bundle branch block in heart failure.
Using simulations of activation propagation in the heart chambers, we will study changes in ECG signals in
the above diagnoses, as well as the consequences of different settings of supportive stimulation in resynchronization therapy for heart failure.
We will implement advanced methods of signal processing and calculation of selected characteristics in quasi-real
time into a new multi-lead ECG measurement system with wireless data transmission to a control computer. |
Design of a Methodology and its Verification for the Measurement of Selected Parameters of Ti Implants in the Manufacturing Process
Návrh metodiky a jej overenie pre meranie vybraných parametrov Ti implantátov vo výrobnom procese
| Duration: |
1.7.2023 - 30.6.2027 |
| Program: |
SRDA |
| Project leader: |
RNDr. Hain Miroslav PhD. |
| Annotation: | The project focuses on the development and application of measurement and non-destructive testing methods in
the manufacturing of titanium dental implants. Dental implants are medical devices that have to comply with the
technical requirements given by regulation of the European Parliament and Council EU 2017/745 from 5 Apr 2017.
Under this regulation, among other obligations, the manufacturer must ensure that these devices are safe and
effective and do not compromise the clinical condition or patients safety. The dental implants should also meet a
high level of health and safety protection, taking into account the generally accepted state of the art in science and
technology. In this project we will address the requirements related to the design and manufacturing and in
particular: the compatibility of the different parts of the device, the influence of processes on the properti es of the
materials, the mechanical properties of the materials used such as strength, ductility, resistance to wear and
fatigue, the properties of the surfaces, and confirmation that the device meets all defined physical specifications as
well as the identification of contaminants in the manufacturing process. To ensure these requirements, we intend to
use state-of-the-art measurement methods such as X-ray microtomography (microCT), scanning electron
microscopy (SEM), optical measurement of surface roughness, SQUID magnetometry. Since the above
measurement methods are time consuming and do not allow their full application in the production, the solution will
also include the design of effective methods of statistical quality control, which will be applied at the manufacturer
of dental titanium implants MARTIKAN, s.r.o. The objectives of the proposed project correlate with the Research
and Innovation Strategy for Smart Specialisation of the Slovak Republic 2021-2027 (SK RIS3 2021+), while they
affect two defined domains, namely Innovative Industry for the 21st Century and Healthy Society. |
Optimization and Standardization of Quantitative Magnetic Resonance Imaging Methods. Suppression of Metallic Artifacts on low-field MR Scanners
Optimalizácia a štandardizácia kvantitatívnych metód zobrazovania magnetickou rezonanciou. Potlačenie kovových artefaktov na nízkopolových MR skeneroch
Collaborative BCI post-stroke neurorehabilitation using a patient-therapist interactive VR environment
Pacient-terapeut kolaboratívna BCI-VR neurorehabilitácia po cievnej mozgovej príhode
| Duration: |
1.9.2024 - 31.8.2026 |
| Program: |
|
| Project leader: |
Ing. Mgr. Rosipal Roman DrSc. |
| Annotation: | A growing body of evidence suggests that integrated brain-computer interface (BCI) technologies and virtual reality (VR) environments provide a flexible platform for a range of neurorehabilitation therapies, including significant motor recovery and cognitive-behavioral therapy following stroke. When a subject is immersed in such an environment, their perceptual level of social interaction is often impaired due to a suboptimal interface quality that lacks the social aspect of human interactions. The project proposes a user-friendly intelligent BCI system with a suitable VR environment in which both patient and therapist interact through their person-specific avatar representations. On the one hand, the patient voluntarily and at his/her own pace controls his/her activity in the environment and interacts with the therapist through a BCI-driven mental imagery process. On the other hand, the therapist's unrestricted motor and communication skills allow for full control of the environment. Thus, the VR environment can be flexibly modified by the therapist, allowing for the creation and selection of different occupational therapy scenarios according to the patient's recovery needs, mental states, and immediate reactions. |
Advanced diagnostics of neurodegenerative disorders using magnetic resonance techniques and artificial intelligence
Pokročilá diagnostika neurodegeneratívnych ochorení pomocou techník magnetickej rezonancie a umelej inteligencie
| Duration: |
1.7.2023 - 30.6.2027 |
| Program: |
SRDA |
| Project leader: |
Ing. Gogola Daniel PhD. |
| Annotation: | Neurodegenerative diseases (ND) are becoming a severe problem in developed countries. Since we currently have
no effective therapies available, early diagnosis is critical to ensure a good quality of life for ND patients. ND are
characterized by iron accumulation and magnetite mineralization in brain tissue, with ferritin as a precursor. Due to
its low relaxivity, physiological ferritin is at the edge of visibility using magnetic resonance imaging (MRI)
techniques. On the contrary, "pathological" ferritin causes a significant shortening of MRI relaxation times. This
creates hypointense artifacts, which theoretically allow the distinguishability of both proteins. Since iron
accumulation precedes the clinical symptoms of the disease, MRI has the potential to become a non -invasive
diagnostic method for the early stages of ND. At present, however, this is limited by the insufficient characterization
of the relaxation properties of biogenic iron and the uncertainty in the interpretation of clinical data. Therefore, our
basic goal (application output) is the development of a comprehensive methodology (FERINO software tool) for the
unequivocal diagnosis of the early stages of ND. To reach our goal, we will use a combination of several diagnostic
techniques and artificial intelligence tools. The diagnostic techniques include in-vitro, in-silico, and in-vivo
characteristics of ferritin relaxation, structural MRI, magnetic resonance spectroscopy (MRS), neurological tests,
and clinical biochemistry biomarkers. The cornerstone of the methodology will be the FerroQuant software tool,
which was proposed by the principal investigator within the APVV 2012. It enables the analysis and quantification
of iron-related clinical MRI data but lacks new findings in iron MRI (false-positive artifacts, ferritin's mineral phases).
FerroQuant also does not use artificial intelligence and does not combine different diagnostic data, whic h, however,
will be an integral part of the FERINO tool. |
Advanced mathematical and statistical methods for measurement and metrology
Pokročilé matematické a štatistické metódy pre meranie a metrológiu
| Duration: |
1.7.2022 - 31.12.2025 |
| Program: |
SRDA |
| Project leader: |
Doc. RNDr. Witkovský Viktor CSc. |
| Annotation: | Mathematical models and statistical methods for analysing measurement data, including the correct determination of measurement uncertainty, are key to expressing the reliability of measurements, which is a prerequisite for progress in science, industry, health, the environment and society in general. The aim of the project is to build on traditional metrological approaches and develop new alternative mathematical and statistical methods for modelling and analysing measurement data for technical and biomedical applications. The originality of the project lies in the application of modern mathematical methods for modelling and detecting dependence and causality, as well as statistical models, methods and algorithms for determining measurement uncertainty using advanced probabilistic and computational methods based on the use of the characteristic function approach (CFA). In contrast to traditional approximation and simulation methods, the proposed methods allow working with complex and at the same time accurate probabilistic measurement models and analytical methods. Particular emphasis is placed on stochastic methods for combining information from different independent sources, on modelling dependence and causality in dynamic processes, on accurate methods for determining the probability distribution of values that can be reasonably attributed to the measured quantity based on a combination of measurement results and expert knowledge, and on the development of methods for comparative calibration, including the probabilistic representation of measurement results with a calibrated instrument. An important part of the project is the development of advanced numerical methods and efficient algorithms for calculating complex probability distributions by combining and inverting characteristic functions. These methods are widely applicable in various fields of measurement and metrology. In this project they are applied to the calibration of temperature and pressure sensors. |
Determination of Iron in blood and tissues of laboratory animals using SQUID magnetometer.
Stanovenie množstva železa v krvi a tkanivách laboratórnych zvierat pomocou SQUID magnetometra
| Duration: |
1.9.2024 - 31.8.2026 |
| Program: |
|
| Project leader: |
Mgr. Škrátek Martin PhD. |
| Annotation: | Iron is an essential chemical element that is part of many metabolic processes. However, the amount of iron in the body must be balanced, as its excess or deficiency can lead to serious health conditions. Iron is found in the body in ferritin, hemoglobin or transferrin proteins. Deoxyhemoglobin, methemoglobin, and myoglobin are known to exhibit paramagnetism, which originates from the Fe2+ Fe3+ ions embedded in their molecules. Ferritin, as an iron storage protein, contains Fe atoms mineralized in the form of oxyhydroxide nanoparticles, whose behavior is superparamagnetic. SQUID magnetometry offers the possibility of detecting and quantifying different forms of iron with high sensitivity and could be more useful than other established methods (colorimetric, spectrophotometric, histochemical or atomic absorption spectrometry) in determining the amount of iron in small samples. |
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Štipendiá pre excelentných PhD. študentov a študentky R1
| Duration: |
1.9.2023 - 31.8.2026 |
| Program: |
|
| Project leader: |
Ing. Pajanová Iveta |
| Annotation: | PhD Topic: Application of deep-learning algorithms on automated MRI data processing.
Annotation: Automated identification and segmentation of clinical data, obtained primary by MRI, is very desirable. The reason is typically large size of data and therefore enormous time, which radiologist has to invest into the manual segmentation. Availability of powerful hardware open new capabilities to automate this processes and speedup via deep learning techniques using convolutional neural networks (CNN). Therefore, student will learn the fundamental functionality principles of MRI device (theoretically and practically), try manual segmentation of volumetric MRI data, and theoretically and practically learn principles of CNN. Student will design own architecture of CNN for automated segmentation of volumetric data, further train, validate and implement on testing data.
The output of this dissertation should be a CNN capable of deployment in clinical practice, in the diagnosis and quantitative analysis of selected tissues (cartilage, ligaments, tendons, menisci, subcutaneous fat, etc.). It is theoretical work, in which programming basics and knowledge of some programming language are necessary. As the programming environment, for design and implementation of CNN, will be used Python with module TensorFlow. |
Theoretical properties and applications of special families of probability distributions
Teoretické vlastnosti a aplikácie špeciálnych tried rozdelení pravdepodobnosti
| Duration: |
1.1.2024 - 31.12.2027 |
| Program: |
VEGA |
| Project leader: |
Doc. RNDr. Witkovský Viktor CSc. |
| Annotation: | In the project, problems related to probability distributions and their applications in mathematical modeling will be studied. We will analyze some classes of distributions (distributions generated by partial summations, the Schröter family) and study properties of distributions belonging to these classes. Issues related to calibration regression models will be addressed. New methods for solving multivariate statistical problems will be developed. These methods will be based on the calculation of exact probability distributions using the inverse transformation of the characteristic function of the distribution of the output variable. Entropy, another property of probability distributions, plays an important role in detecting causality in time series. The primary area of application is the
use of the distribution of test statistics in hypothesis testing. The new results obtained during the solution of the project will also be applied to mathematical modeling in metrology, linguistics and actuarial mathematics. |
Effects of low-frequency and pulsed electromagnetic fields at a cellular level
Účinky nízkofrekvenčných a pulzných elektromagnetických polí na bunkovej úrovni
| Duration: |
1.1.2025 - 31.12.2028 |
| Program: |
VEGA |
| Project leader: |
Mgr. Teplan Michal PhD. |
| Annotation: | Although there is ongoing interest in the adverse and beneficial effects of electromagnetic fields (EMF), a clear
explanation of EMF's influence on living structures is lacking. To investigate low-frequency (LF) magnetic fields
(MF), we will enhance our experimental platform to test their possible inhibitory or stimulatory effects based on
frequency and magnetic flux density parameters. As a model organism yeast strain Saccharomyces cerevisiae
will be used. Its response to time-harmonic and pulsed MF will be studied by measuring cell growth curve using
turbidimetry, impedance spectroscopy and microscopy. Moreover, the ion parametric resonance interaction
model will be verified for biogenic ions and the magnitude of the ambient static geomagnetic field. The importance
of this area of research lies in exploring physical methods for manipulating biological structures, with potential
benefits for biotechnology and medical treatment. |
Assessment of restitution of normal ventricular activation by ECG mapping
Vyhodnotenie reštitúcie normálnej komorovej aktivácie pomocou EKG mapovania
Research of Dental Implant Components for the Creation of Personalized 3D Models
Výskum digitalizácie komponentov dentálnych implantátov za účelom
Research on the correlation dependences of magnetic, structural, and optical properties of aluminate glasses, titanium alloys, and titanium-based nanocolloids, and ion liquids
Výskum korelačných závislostí magnetických, štruktúrnych a optických vlastností hlinitanových skiel, titánových zliatin a nanokoloidov na báze titánu a iónových kvapalín
| Duration: |
1.1.2025 - 31.12.2028 |
| Program: |
SRDA |
| Project leader: |
Mgr. Škrátek Martin PhD. |
| Annotation: | The project focuses on the development of magnetic measurement methods for selected areas of materials
research and biomedicine, for a deeper understanding of the physical and chemical properties associated with
changes in the distribution of electrical charges, and for their utilization in designing revised technological
procedures and diagnosing surface properties. First goal of the project is to investigate the influence of
composition, precursor powder preparation methods, and the preparation method of aluminate
glasses/glass-ceramics on their structure and magnetic properties. The second goal is the investigation of the
influence of properties and composition of ion liquids on the phase composition, shape, size distribution, and
stability of titanium-based nanoparticles and nanostructures. The physicochemical and magnetic properties of
nanocolloids will be studied with attention to the surface properties of biomedical Ti-alloys, especially
nanostructures based on titanium oxide. |
Research of the metal organ pipe collections of historical pipe organs in Slovakia
Výskum kovového píšťalového fondu historických organov na Slovensku
| Duration: |
1.9.2025 - 31.8.2028 |
| Program: |
SRDA |
| Project leader: |
RNDr. Krafčík Andrej PhD. |
| Annotation: | The sound-stylistic quality of historical organs is determined by various factors, including the material used for the organ pipes and the scaling (mensuration) of individual pipes and entire stops. The proposed project will examine organ metal as a key sound-stylistic determinant of historical organs, with consideration of the constructional evolution of organs in Slovakia from the 17th to the 20th century. The project will be conducted in four phases. The first phase will focus on the chemical composition analysis of organ pipe metal from selected instruments. These pipes and entire stops will undergo mensuration analysis, leading to the development of a mathematical model. The next phase will involve the visual recording (collection) of signings—etched or stamped markings indicating the specific tone for which a pipe is constructed. The signings of pipes from instruments with known builders will be documented to create a standard that will enable the use of neural networks (AI) to identify the authorship of organs whose builders are currently unknown. The research will also address the technical condition of organ metal, particularly corrosion, which affects not only the sound properties but also the preservation of the metal components of these historical instruments. The project's outcomes will include an online map of organ metal composition, corrosion, mensurations, an atlas of various types of corrosion and defects in organ pipes, as well as a comprehensive mapping of the metal and mensurations of studied stops. Furthermore, we will establish a method for gradually authorizing organs whose builders remain unidentified. All findings will be contextualized within the sound-stylistic development of historical organ building on Slovak territory. |
Research of reference standards and measurement methods ensuring determination of the relationship of geometric specifications and qualitative indicators of 3D objects created by additive technologies
Výskum referenčného etalónu a meracích metód zabezpečujúcich určenie vzťahu geometrických špecifikácií a kvalitatívnych ukazovateľov 3D objektov vytvorených aditívnymi technológiami
| Duration: |
1.7.2024 - 31.12.2027 |
| Program: |
SRDA |
| Project leader: |
RNDr. Hain Miroslav PhD. |
| Annotation: | The present project is aimed at evaluating the quality of additive manufacturing, a reference test artefact designed and developed for this purpose. The development of the reference artefact and the quantification of its parameters will make use of the latest knowledge in additive manufacturing, state-of-the-art measurement strategies implemented using X-ray microtomography, magnetometry, coordinate measuring devices, optical and electron scanning microscopes and methods of mathematical-statistical processing of measured data. Additive manufacturing technologies are capable of producing parts with very complex geometries that conform to the desired design without further machining. It is for this reason that they are very promising and their use in industry is growing. In order for additive manufacturing products to fully replace conventionally machined parts, they must meet the required quality criteria such as shape and dimensional accuracy, surface roughness, internal defects, residual stresses, etc. The final quality of parts produced by additive manufacturing technology is influenced by the characteristics of the raw material and the parameters and settings of the system. The aim of the project is to investigate the production of modified monofilaments and the measurement methods necessary for the realization of a stable and reproducible reference test artifact, which would be used to assess not only the geometric capability of additive manufacturing systems but also the internal structure and selected properties of the final product. |
Research of properties of magnetic nanoparticles for imaging purposes in biomedical diagnostics based on magnetic resonance methods
Výskum vlastností magnetických nanočastíc pre účely zobrazovania v biomedicínskej diagnostike na báze metód magnetickej rezonancie
| Duration: |
1.1.2023 - 31.12.2025 |
| Program: |
VEGA |
| Project leader: |
Dr. Ing. Přibil Jiří (PhD.) |
| Annotation: | The project focuses on experimental and theoretical research in the field of magnetic resonance imaging (MRI)
methods. The following issues will be addressed in the project: 1. Research of properties of magnetic
nanoparticles in external magnetic fields regarding creation of a theoretical model and its subsequent
experimental verification. 2. Analysis of MRI scanning effect on cardiovascular system of a tested person in order
to find appropriate methods of detection, quantification, and design of measures to minimize them. 3. Analysis of
metabolic processes in order to map the rate of energy production in the human heart and muscles in order to
diagnose the slowing down of energy production in the heart. 4. Automated processing of MR images of the
human knee in order to obtain quantitative characteristics and morphological quantities of individual tissues. 5.
Calibration of gradient fields to ensure undistorted morphology in measured MR images. Mapping of
inhomogeneities into magn. fields using MRI methods |
Development and standardization of MR-based methods for detecting and evaluating metabolic and structural adaptations of aging muscles to exercise
Vývoj a štandardizácia MR metód na detekciu a vyhodnocovanie metabolických a štrukturálnych adaptácií svalov na starnutie a cvičenie
| Duration: |
1.9.2025 - 31.8.2029 |
| Program: |
SRDA |
| Project leader: |
Mgr. Klepochová Radka PhD. |
| Annotation: | Aging is associated with a loss of muscle mass and the functional capacity of skeletal muscles; however, regular exercise can slow down these processes. The focus of this project is on examining the metabolic, functional, and structural parameters in the lower limb muscles, which we can non-invasively and repeatedly measure using innovative magnetic resonance methods (MR). This allows us to compare the trajectories of aging in skeletal muscles of sedentary individuals and those who are physically active. One of the key parameters that define a muscle's ability to efficiently mobilize and use energy for muscle work is called metabolic flexibility. The aim of the project is to develop innovative MR methods to study metabolic flexibility and structural changes in skeletal muscles during aging, and relate them to whole-body metabolic flexibility, as well as the metabolic phenotype and structural and molecular changes in the skeletal muscles of older adults. As part of the project, we will standardize the measurement of dynamic changes in metabolites in muscle during exercise using proton (1H) MR spectroscopy, create standard procedures for quality control of acquired MR spectroscopy data, and a key aspect of the project will also be the development of an automated segmentation method based on a convolutional neural network, which will enable more efficient and reliable evaluation of MR images of skeletal muscles. These innovative methods will be validated using data from ongoing longitudinal studies at the Biomedical Center of the Slovak Academy of Sciences, and their results will be directly compared with parallel changes in metabolic health, functional capacity, histological structure, and molecular mediators of metabolic flexibility in skeletal muscles. The results may not only improve our understanding of the processes that define metabolic flexibility during aging but may also offer relevant strategies to support metabolically healthy aging. |
Changes in fossil lizard communities at older and younger Cenozoic sites in and around Europe as a result of dramatic global climate change – the key to understanding our future is in the past
Zmeny v spoločenstvách fosílnych jašterov na lokalitách staršieho a mladšieho kenozoika v Európe a okolí ako dôsledok dramatických globálnych klimatických zmien – kľúčom k budúcnosti je chápanie minulosti
| Duration: |
1.1.2024 - 31.12.2026 |
| Program: |
VEGA |
| Project leader: |
RNDr. Hain Miroslav PhD. |
| Annotation: | Terrestrial ecosystems in Europe, but practically everywhere, changed significantly during the Cenozoic due to
global climatic changes. The importance of their better understanding is magnified by present global climate
change. In that respect, lizards are widely regarded as excellent indicators of past climates, particularly ambient
temperatures. The project is focused on the research of new, often complete finds from localities of different ages
such as the Paleocene site of Walbeck in Germany, the Lower Eocene sites of Dormaal in Belgium, Cos,
Pasturat and Viélase in France. We also include new complete finds from the Middle Eocene German Messel
locality (Unesco). Furthermore, fossils from the Oligocene and Lower Miocene sites of Phosphorites du Quercy
(France), Miocene to Pliocene sites in Austria, Slovakia, Poland, Hungary, but also in Africa (Kenya) will be
studied. The aim is this research using CT is an interpretation of the phylogenetic relationships of studied taxa
and changes in their communities. |
The total number of projects: 25
