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The expression and advancement of digital skills among human resources in the public sector.
No full textThe digital transformation that has begun determines the need for public sector organizations to exploit the full potential of digital technologies to modernize more and meet the needs of citizens. In the process of digital transformation, public sector employees in Lithuania and other EU countries are faced with the need to acquire digital competencies and the problem of their shortage. Therefore, it is important to determine the existing digital competencies of public sector employees, the level of their mastery, identify missing competencies and determine methods for effectively organizing the acquisition and development of missing digital competencies
The impact of the U.S. and China tariff war on the international economy.
No full textThe trade war between the US and China, which has been ongoing since 2018, is one of the most important geopolitical and economic conflicts of this decade. As these two countries control a large share of global trade, supply chains, and foreign investment, this conflict has had a particularly significant impact on the international economy. Although tariffs have mainly affected US and Chinese indicators, they have also damaged other regions, from the negative impact on Mexico and the European Union to the benefits for certain Asian and African countries. The result of this conflict includes growing international protectionism and the increasing relevance of tariffs and quotas, which leads to rising costs for companies, supply problems, reduced production efficiency, and higher prices for the end consumer. Thus, the tariff war is an important and sensitive issue for all interested countries and regions, and it should be assessed collectively, taking into account not only the impact on the US and China, but also the consequences for the regions concerned. The subject of this study is the international economy in the context of the tariff war, in which the most important role is played by the relationship between the two largest economies in the world – the US and China. The main objective of the study is to thoroughly assess the impact of the US-China tariff war on the international economy. To achieve this goal, an analysis of the selected problem will be carried out to help identify the essence of the conflict. This will be followed by theoretical solutions based on a review of the literature. Finally, the research methodology will be presented, and an empirical study will be carried out based on it, using factual data and statistics. In order to achieve the objective of the study, the following main research methods are used: analysis of scientific literature, graphical analysis, analysis of statistical data, correlation analysis, and regression analysis. A review of the literature revealed various shortcomings in the resolution of international conflicts. Even the main economic models used to analyze tariffs contradict each other, as some claim that tariffs lead to a loss of prosperity, while others say that protectionism is necessary to ensure the prosperity of the state. Organizations created to resolve such conflicts are also unable to resolve the conflict between China and the US. Although profit-seeking companies have essentially created new and more efficient production and supply chains, they do not fundamentally address the root cause of the problem – the ongoing disagreement between the US and China – and the steadily declining confidence in the future does nothing to restore production and investment levels to their former heights. The statistical analysis examined nine variables which, according to the literature review, were affected by changing customs tariffs. Although all variables were stationary, further correlation analysis showed that a statistically significant relationship exists only between the average US tariff level on Chinese goods and Chinese foreign investment. The most accurate regression model found and developed provided an equation according to which it can be stated that when tariffs increase by one unit, Chinese foreign investment decreases by an average of 0.131 units. As the conflict under analysis is still ongoing, it is recommended to monitor it and repeat the study in the future in order to potentially obtain a more accurate and long-term result
Naratyvinės politikos modelio taikymas analizuojant Sirijos pereinamąją valdyseną legitimumo krizės kontekste.
No full textSyria continues to be one of the most complex and deadliest conflicts of the 21st century. The power dynamic in the country changed by the end of 2024, when the Sunni Islamist militant group Hay’at Tahrir al-Sham, with its leader, Ahmed al-Sharaa overthrew the decades-long Bashar al-Assad regime. The ‘surprise offensive’ attracted attention from international actors and the media, whose coverage gradually shifted from narratives about the group’s extremist past towards discourses of legitimacy that positioned the group and its leader as the main power in Syria. The legitimacy of transitional governments is one of the most controversial and debated topics. This raises continuous discussions in international arena, as the validity can significantly influence diplomatic recognition and aid. The research focuses on the legitimacy crisis in Syria’s transitional governance due to the involvement of the controversial group Hay’at Tahrir al-Sham. It aims to analyse how the media create and frame narratives across different phases of Syria’s transitional governance. To achieve this, the research establishes four objectives: 1. To investigate how the political transition emerges from conflict dynamics and to define the main stages of the Syrian transition; 2. To review theories of political transition, legitimacy, framing, and agenda-setting in the context of the legitimacy crisis; 3. To identify leading narrative elements toward Syrian transitional governance, as portrayed in selected media outlets, using the Narrative Policy Framework; 4. To compare and evaluate whether shifts in media narratives correspond with changes in political developments reflected by the international community. The theoretical part is grounded in normative and discursive legitimacy, framing, and agenda-setting theories, employing a qualitative research design. The empirical part applies the Narrative Policy Framework, which allows for the systematic content analysis of narrative elements such as setting, plot, characters, and the moral of the story. News reports from two outlets, BBC News and Al Jazeera, are coded using Maxqda software. Later, the narrative circulation typology allows to investigate whether international political discourse corresponds to media narratives on the legitimacy of Syria’s new governance. The findings suggest that political transition unfolds in four stages: Deadlock, Violent trigger, Initial transition, and Post-Settlement Transition. The analysis concludes that the primary attempts to frame legitimacy in Syria emerged even before the official establishment of the new government, marked by the signing of a new constitutional declaration. Media narratives gradually shifted from delegitimizing Assad and associating HTS with terrorism in Deadlock to attempts to legitimize the group in later stages. The analysis of other stages revealed that BBC News frames the legitimacy of new Syrian authorities as a conditional and reversible process, whereas Al Jazeera frames legitimacy as a process, progressing together with governance developments. Overall, the findings demonstrate close alignment between media narratives and international political discourse, highlighting the strong connection between media discourse and political strategies
AI–driven multimodal sensing for early detection of health disorders in dairy cows /
No full textDigital technologies that continuously quantify animal behavior, physiology, and production offer significant potential for the early identification of health and welfare disorders of dairy cows. In this study, a multimodal artificial intelligence (AI) framework is proposed for real-time health monitoring of dairy cows through the integration of physiological, behavioral, production, and thermal imaging data, targeting veterinarian-confirmed udder, leg, and hoof infections. Predictions are generated at the cow-day level by aggregating multimodal measurements collected during daily milking events. The dataset comprised 88 lactating cows, including veterinarian-confirmed udder, leg, and hoof infections grouped under a single ‘sick’ label. To prevent information leakage, model evaluation was performed using a cow-level data split, ensuring that data from the same animal did not appear in both training and testing sets. The system is designed to detect early deviations from normal health trajectories prior to the appearance of overt clinical symptoms. All measurements, with the exception of the intra-ruminal bolus sensor, were obtained non-invasively within a commercial dairy farm equipped with automated milking and monitoring infrastructure. A key novelty of this work is the simultaneous integration of data from three independent sources: an automated milking system, a thermal imaging camera, and an intra-ruminal bolus sensor. A hybrid deep learning architecture is introduced that combines the core components of established models, including U-Net, O-Net, and ResNet, to exploit their complementary strengths for the analysis of dairy cow health states. The proposed multimodal approach achieved an overall accuracy of 91.62% and an AUC of 0.94 and improved classification performance by up to 3% compared with single-modality models, demonstrating enhanced robustness and sensitivity to early-stage disease
The prerequisites for development of LNG/CNG filling stations network: the crucial Role of Lithuania and the Baltic States in the North Sea–Baltic Sea corridor /
No full textThe multimodal North Sea–Baltic corridor, consisting of 6934 km of road, is an integral part of the EU’s trans-European transport network. However, an unsatisfied level of development of alternative fuels infrastructure for road transport is considered one of the obstacles to connecting northern Member States and North-East countries. A “what-if” scenario was employed to obtain useful insights into how a given situation might be handled, and a comparison of several paths forward to make better decisions was analysed. Environmental insights for transportation sector scenarios in 2030–2035 were explored and analysed using the COPERT v5.5.1 software program. In this study, the installation of natural gas infrastructures of various station sizes and with varying capacities and types of natural gas (LNG, CNG, bio-methane) dispensed was evaluated in detail. Replacement of the existing HDV fleet (heavy-duty vehicles) with LNG-powered trucks would result in the following investment to upgrade the existing network and build new stations to meet rising LNG demand: from €21.47 to €32.3 million (the scenario of 10% market share for HDVs running on LNG), €42.94 to €64.6 (20%), and €64.4 to €96.9 (30%). The dual-fuel 10–diesel fuel 90% scenario seems to be the safest option for a large-scale investment until 2035 which may lead to moderate emission savings of 84.6 kton CO2 eq. compared to 2022 levels
Single step nanosecond laser structuring for cost effective functional titanium surfaces with topography driven preosteoblast adhesion /
No full textEarly bone formation around implants depends on both the chemical composition and the micro-, nanoscale architecture of the implant surface. Nanoscale modifications can accelerate osseointegration, and laser processing offers a versatile method of creating such features. In this study, titanium substrates were modified using a single-step nanosecond laser treatment at two energy regimes (1.95 mJ/pulse for P_0.5; 4.00 mJ/pulse for P_0.4). The resulting surfaces were characterized by SEM, EDS, XRD, Raman spectroscopy, ToF-SIMS, contact angle, and topography measurements, with biological assessment performed using a mouse preosteoblast cell line. Analyses revealed various titanium oxo clusters (TiO3-, TiO2-, TiO-) and moderate oxidation levels (25-31 at% O). Both laser regimes produced rough, hydrophobic surfaces. Cytotoxicity tests confirmed that the materials were non-toxic, and proliferation assays showed increasing preosteoblast numbers over time, indicating that both surfaces supported cell division. Good adhesion of preosteoblasts was observed on P_0.4 and P_0.5. This work demonstrates that nanosecond laser processing alone can generate micro-, nanostructured titanium implant surfaces with favourable biocompatibility, achieving performance comparable to more complex femtosecond methods while offering a cost-effective and scalable surface engineering strategy
Geothermal energy potential map in Western Lithuania: data integration, kriging, simulation, and neural network prediction /
No full textThis study develops a reproducible regional screening workflow to assess geothermal potential in the Cambrian reservoir system ofWestern Lithuania under conditions of sparse and heterogeneous legacy subsurface data. The approach integrates data compilation, cleaning, and harmonization from archival well materials, ordinary kriging spatialization of key reservoir properties with uncertainty multipliers, standardized doublet simulations to derive comparative thermal performance indicators, and a neural network surrogate to accelerate regional inference. The workflow integrates 12 compiled reservoir control points into a gridded regional representation (25 × 30 cells; ~6750 km2) and evaluates uncertainty through low, mid and high scenarios (±10%). Physics-based simulations were executed for 303 representative grid locations per scenario, yielding cumulative extracted-energy indicators on the order of 105–107 MWh across cases (reported as comparative indicators). The neural network surrogate reproduced simulation outputs with a high predictive agreement (test R2 = 0.996; cross-validation mean R2 ≈ 0.99), enabling swift prediction across the remaining grid cells after training. Relative potential maps highlight spatially coherent zones of higher prospectivity and provide a transparent basis for prioritizing follow-up investigations and data acquisition. The proposed framework is modular and can be refined as improved geological constraints, thermophysical properties, and operational assumptions become available
Greening Generation Z: unraveling pro-environmental purchase intentions for green apparel in Lithuania through an extended theory of planned behavior, social media influence and environmental self-identity /
No full textThe rise of social media among Generation Z has led to changes in consumption patterns, especially in green apparel. This study aims to extend the theory of planned behavior model to include social media’s influence on attitudes, subjective norms and perceived behavioral control (PBC) regarding green apparel purchases. It also investigates the moderating role of environmental self-identity in these relationships
Use of silver particles obtained by green synthesis in nonwoven fabrics produced by electrospinning.
No full textThis project explores the possibilities of incorporating green synthesised silver nanoparticles into electrospun polyvinylpyrrolidone (PVP) nonwoven materials to create antibacterial and environmentally friendly materials. The study addresses a problem related to the application of sustainable nanoparticle production methods and the influence of incorporating these nanoparticles into a polymer matrix on fiber formation, morphology and material properties. The research plan included the preparation of marigold extract and its use for reducing silver ions, the electrospinning of PVP different solutions and various voltages The materials were analysed using SEM, TEM, viscosity measurements, conductivity and wettability tests, UV-VIS spectroscopy. The results showed that the size and shape of AgNPs formed during green synthesis are influenced by the properties of the extract, while the method of their incorporation determines changes in the viscosity and conductivity of the solutions, which directly affect the fiber diameter and the number of defects in the nonwoven materials. It was determined that marigold extract can successfully form silver nanoparticles whose morphology corresponds to that described in the literature, and that their incorporation into the PVP solution significantly alters the solution properties - small amounts of AgNPs increase viscosity, where higher concentrations reduce it due to aggregation, while electrical conductivity consistently increases with nanoparticle content. These changes had a direct impact on the electrospinning process: higher conductivity resulted in stronger electrostatic stretching and the formation of thinner, more uniform nanofibers, and appropriately selected synthesis and mixing conditions helped reduce the number of polymer beads and produce a more homogeneous nonwoven structure. Wettability tests revealed altered surface properties due to the incorporation of AgNPs. From a social and environmental perspective, green synthesized nanoparticles and their integration into nonwoven materials can reduce the use of chemical reagents and contribute to the development of sustainable technologies. Finally, the analysis confirmed that the incorporation of green-synthesized silver nanoparticles into electrospun nonwoven materials is a promising, safe, and socially valuable direction, enabling the creation of sustainable and functional materials whose properties can be deliberately controlled by adjusting solution preparation and electrospinning parameters, opening new application opportunities in medicine, filtration, and other fields of functional materials
Layer-by-layer integration of electrospun nanofibers in FDM 3D printing for hierarchical composite fabrication /
No full textThis study presents a novel integrated manufacturing approach that combines fused deposition modeling (FDM) 3D printing with in situ electrospinning to fabricate hierarchical composite structures composed of polylactic acid (PLA) reinforced with polyacrylonitrile (PAN) nanofibers. A mounting fixture was employed to enable layer-by-layer nanofiber deposition directly onto printed PLA layers in a continuous automated process, eliminating the need for prefabricated electrospun nanofiber mats. The influences of nozzle temperature (210-230 °C) and electrospinning time (5-15 min per layer) on mechanical, thermal, and morphological properties were systematically investigated. Optimal performance was achieved at an FDM nozzle temperature of 220 °C with 5 min of electrospinning time (sample E1), showing a 36.5% increase in tensile strength (71 MPa), a 33.3% increase in Young's modulus (2.8 GPa), and a 62.0% increase in flexural strength (128 MPa) compared with the neat PLA. This enhancement resulted from the complete infiltration of molten PLA into the thin nanofiber mats, creating true fiber-matrix integration. Excessive nanofiber content (15 min ES) caused a 36.5% reduction in strength due to delamination and incomplete infiltration. Thermal analysis revealed a decrease in glass transition temperature (1.2 °C) and onset of thermal degradation (5.3-15.2 °C) with nanofiber integration. Fracture morphology confirmed that to achieve optimal properties, it was critical to balance the nanofiber reinforcement content with the depth of infiltration, as excessive content created poorly bonded interleaved layers. This integrated fabrication platform enables the production of lightweight hierarchical composites with multiscale, custom-made reinforcement for applications in biomedical scaffolds, protective equipment, and structural components