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Influence of different chemical methods used for the deposition of CdSe/ZnO layers /
No full textThe present study employed the spin-coating method for the preparation of nanostructured crystalline zinc oxide (ZnO) thin films on FTO glass substrates. Subsequently, cadmium selenide (CdSe) layers were deposited on the surfaces using two distinct chemical methods: successive ionic layer adsorption and reaction (SILAR) and chemical bath deposition (CBD). The obtained films were then characterized by a variety of analytical methods, including XRD, SEM, AFM, EDX spectroscopy, UV–vis spectrophotometry, and linear sweep voltammetry. The XRD and SEM studies demonstrated that all of the films exhibited a polycrystalline nature, with the crystallinity of the cadmium selenide thin films prepared using the SILAR method exceeding that obtained by the CBD method. The SEM and AFM images revealed the uniformity of the cadmium selenide films on the FTO substrates, with no visible cracks or pores. The EDX spectra confirmed the presence of the expected elements in the thin films. The optical band gaps (Eg) for CdSe prepared with the SILAR or CBD method were determined to be 1.85 and 1.97 eV, respectively
Between past and present: age, period, and cohort effects on changing values in Lithuania /
No full textThis study examines the changes in Schwartz’s higher-order-value dimensions in Lithuanians over time. We analyze cross-sectional repeated survey data, with a sample of 11,199 respondents from six waves of the European Social Survey (ESS) during the years 2010–2020. Time-lag and cross-sectional analyses revealed age and period effects on self-enhancement and self-transcendence, and age, period, and cohort effects on openness to change and conservation. A comparison of political generations shows that the youngest cohort (independent EU generation) is more conservative, more self-transcending, less open to change, and less self-enhancing over time, in contrast to other generations. The Soviet legacy generations follow a different trajectory of openness to change and conservation than the Stalin and Independent EU generations, suggesting that historical context and current period effects are strong, and that the youngest political generation is particularly sensitive to societal-level disruptions. It is plausible that forces related to rapid societal change, for example, a decline in the working-age population after the collapse of the Soviet Union and, more recently, during the period of the study due to mass emigration, have left a generation trapped between scarcity and modernity
Climate change and public health: governance approaches and challenges in Lithuania /
No full textHuman-induced climate change is widely acknowledged to be one of the greatest threats to public health globally. The intersection of climate change impacts on public health and the governance of these risks remains a critical area of research. While there is a large body of work analysing both the public health risks and climate change governance, there is a lack of research on the governance of such risks in the specific region of northern Europe, which is characterized by relatively lower yet growing climate change susceptibility. This article presents a case study exploring the approaches to governance of climate change-induced risks to public health in Lithuania. In the studied case, climate change-induced risks to public health range from extreme heat events to infectious diseases. The analysis follows an integrated conceptual model based on the risk governance framework, the drivers-pressures-state-impact-response framework and health-in-all-policies approach. The analysis is based on literature review and document analysis. The results have revealed fragmented governance of climate change-induced public health risks in Lithuania, highlighting the need for integrated health and climate policies, stronger international engagement, enhanced intra- and cross- sectoral cooperation and improved monitoring. To ensure better preparedness and resilience to climate change-induced public health risks, more research is needed, especially exploring intra- and cross- sectorial collaboration, responses from diverseision-makers and reduction of health inequities. The analysis identified inadequate integration of health considerations into climate change governance strategies and insufficient stakeholder engagement across sectors. It also shows that Lithuania’s current governance framework lacks robust mechanisms for addressing health inequities exacerbated by climate change, and highlights a need for targeted interventions to enhance resilience and equity
Ūko kompiuterijos paslaugų dinaminio valdymo metodas.
No full textFog Computing conception was introduced by OpenFog Consortium which was established in 2015 by such companies as Cisco, Microsoft, Intel etc. This paradigm seeks to solve Cloud Computing issues. They are due to long transmission distances, higher data flow, data loss, latency, and energy consumption. Services have to be closer to end-users as a part of a solution. But, fog devices are known for being mobile and heterogenous. Their resources can be limited, and their availability can be constantly changing. A service placement optimization is needed to meet the QoS requirements. A service placement orchestration is proposed in this thesis, which functions as a multi-agent system. This two-step process is made of Multi-Objective Particle Swarm Optimization (IMOPSO) to generate particle sets as the first step and the Analytical Hierarchy Process (AHP) with a specific judgement matrix as the second step for service distribution priority decisions. This dynamic service orchestration method is important for its quality that it does not focus on a central control unit. It allows to make a service placement decision for any orchestrator which synchronizes its resource availabilities with other nodes within the fog network. It greatly improves scalability and resilience to fog node failures. It also supports mobility and adapts to resource availability changes
Hypertension types and associated cardiovascular risk factors in Lithuanians aged 50–54 years /
No full textBackground: Hypertension is one of the most common cardiovascular risk factors worldwide. Additionally, epidemiological studies show a worryingly high prevalence of treatment-resistant hypertension. Especially concerning is the frequent co-occurrence of other cardiovascular risk factors, including dyslipidaemia, smoking, and diabetes mellitus. Objectives: The aim of this study is to investigate the prevalence of arterial hypertension and other cardiovascular risk factors in patients aged 50–54 years. Methods: A retrospective study was conducted on patients participating in the Lithuanian High Cardiovascular Risk Primary Prevention Programme. Data were collected from self-report questionnaires, laboratory tests, and clinical assessment. Hypertension was confirmed if systolic blood pressure was ≥140 mmHg and/or diastolic blood pressure was ≥90 mmHg or the patient had been previously diagnosed. Results: In total, 49155 patients—32018 (62.4%) women and 17137 (37.6%) men—were enrolled in this study. A total of 24549 (49.9%) patients were diagnosed with arterial hypertension. The prevalence of non-resistant primary hypertension was 45.9%, while the prevalence of resistant primary hypertension was 4.1%. The prevalence of dyslipidaemia was 92.79% in the non-resistant primary arterial hypertension group and was 94.59% in the resistant primary arterial hypertension group. The prevalence of smoking was higher in the non-resistant primary arterial hypertension group compared to patients with resistant hypertension (22.43% and 17.09%, respectively). A total of 23.06% of patients with resistant primary arterial hypertension had diabetes mellitus. Conclusions: The prevalence of primary arterial hypertension in middle-aged Lithuanians was high, reaching almost 50% in both sexes. Patients tended to have many cardiovascular risk factors simultaneously, with dyslipidaemia being the most common (prevalence > 90%)
Green synthesis and characterization of silver nanoparticles using Hypericum perforatum l. extracts /
No full textIn the present study, the biosynthesis method was used to synthesize silver nanoparticles using extracts of Hypericum Perforatum L. plant in vivo and callus cultures in vitro. In this research, biologically active compounds in the extract functioned as reducing agents, while a silver nitrate solution served as the source of silver. Characterization of the synthesized nanoparticles was carried out using Fourier transform infrared spectroscopy (FTIR) TO identify functional in the reduction and stabilization process, Scanning Electron Microscope (SEM) to determine nanoparticles morphology and size distribution, and X-ray Diffraction (XRD) analysis to confirm the crystalline nature of the AgNPs
Investigation of machine learning-based methods for sleep apnea monitoring.
No full textSleep is a very important component of health and well-being, but its disorders, such as obstructive sleep apnea, are a serious problem that causes significant health complications. This master's thesis project conducted a comprehensive study on machine learning-based methods for monitoring and diagnosing sleep apnea using photoplethysmography (FPG) signals. The first part of the paper analyses the problem of sleep apnea, its clinical relevance and traditional diagnostic methods, such as polysomnography, and their disadvantages - high cost, complexity and patient discomfort. Non-invasive diagnostic alternatives are discussed, with particular emphasis on the potential of FPG technology due to its simplicity and convenience for use in the home environment. The second part of the paper presents detailed algorithms used in the research, their application methodology and evaluation criteria. Two main types of algorithms were analysed: one using features extracted directly from FPG signals (e.g. PPI and DAP), the other using deep learning transformer models that do not require manually extracted features. The experimental results presented in the third part show that the feature-based model, when processing 60-second intervals (0.5–7 Hz filter) and using the selected five most important features (Aoff, Adn, deltaT, Tsw10, Tdia), achieved the highest AUC – 84.3% and F1 – 77.4%. The transformer model with 10-second signals (0.5–7 Hz) recorded the best sensitivity indicator (71.2%) and AUC – 78.7%. In terms of resource consumption, the feature-based solution requires significantly less computational operations and memory, making it most suitable for embedded systems. The results obtained confirm that machine learning methods using FPG signals can be an effective alternative to traditional polysomnography and provide an opportunity for non-invasive apnea monitoring at home
Stable multipoint flux approximation (MPFA) saturation solution for two-phase flow on non-K-orthogonal anisotropic porous media /
No full textThis paper extends the multipoint flux approximation (MPFA-O) method to model coupled pressure and saturation dynamics in subsurface reservoirs with heterogeneous anisotropic permeability and non-K-orthogonal grids. The MPFA method is widely used for reservoir simulation to address the limitations of the two-point flux approximation (TPFA), particularly in scenarios involving full-tensor permeability and strong anisotropy. However, the MPFA-O method is known to suffer from spurious oscillations and numerical instability, especially in high-anisotropy scenarios. Existing stability-enhancing techniques, such as optimal quadrature schemes and flux-splitting methods, mitigate these issues but are computationally expensive and do not always ensure monotonicity or oscillation-free solutions. Building upon prior advancements in the MPFA-O method for pressure equations, this work incorporates the saturation equation to enable the simulation of a coupled multiphase flow in porous media. A unified framework is developed to address stability challenges associated with the tight coupling of pressure and saturation fields while ensuring local conservation and accuracy in the presence of full-tensor permeability. The proposed method introduces stability-enhancing modifications, including a local rotation transformation, to mitigate spurious oscillations and preserve physical principles such as monotonicity and the maximum principle. Numerical experiments on heterogeneous, anisotropic domains with non-K-orthogonal grids validate the robustness and accuracy of the extended MPFA-O method. The results demonstrate improved stability and performance in capturing the complex interactions between pressure and saturation fields, offering a significant advancement in subsurface reservoir modeling. This work provides a reliable and efficient tool for simulating coupled flow and transport processes, with applications in CO2 storage, hydrogen storage, geothermal energy, and hydrocarbon recovery