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The impact of digitalization on the employment structure and income of self-employed people in Lithuania.
No full textTechnological development and digitalization are constantly changing the structure of the labor market and affecting employment. Over time, self-employment is becoming more popular, for which digitalization has both positive and negative effects. There are many advantages to working in the form of self-employment, but it is important not to forget about uncertainty and lack of guarantees. The object of the research – self-employed individuals. The aim of the project – to determine the impact of digitalization on the employment structure and income changes of self-employed persons in Lithuania. The first part of the work analyzes the problem of the impact of digitalization on the employment and income of self-employed persons, during which the impact of digitalization on the labor market and employment is observed. A growth trend is observed in both the use of technologies and the internet and the number of self-employed persons in Lithuania. In the second part, after analyzing the scientific literature, the individual and structural level reasons that determine the choice of self-employment, which are decisive necessities or opportunities, are clarified. Five types of self-employment are analyzed: freelancers, independent contractors, entrepreneurs and independent professionals. Changes in the structure of self-employment employment in the context of digitalization and possible positive and negative effects of digitalization are clarified. It is clarified that digitalization affects both business and self-employed persons, providing both forms with new opportunities and the need to constantly improve and adapt to innovations. The third part presents the methodology of the planned research, according to which the impact of digitalization on self-employed persons and their income is further investigated. The fourth part presents the results of the research, which found variables that affect self-employment. The number of self-employed persons is influenced by the number of persons who used the internet for financial purposes. As the number of persons using the internet for financial purposes increases, the number of self-employed persons begins to decrease, but only up to a certain level. The reverse effect occurs with a 1–2 % growth in internet use for financial purposes, and with a higher growth, the number of self-employed persons increases. Another developed model shows that the number of households with broadband internet access affects monetary income from self-employment and as the number of households increases, income decreases. However, with a significant increase in internet access, the decline in income slows down and at a certain limit it begins to increase. Thus, a small part of the indicators reflecting digitalization in Lithuania are related to self-employment, therefore not all the insights of foreign authors are reflected in the Lithuanian case
Gyvavimo ciklo analizės taikymas infrastruktūros projektų tvarumo vertinime.
No full textThe construction and infrastructure sector has a significant environmental impact due to high resource consumption and greenhouse gas emissions. This Master’s thesis explores how Life Cycle Analysis (LCA), Circular Economy (CE) principles, and Digital Twin (DT) technologies can be combined to improve the sustainability of infrastructure projects. The aim of the study is to evaluate how digital and circular approaches can reduce environmental impacts throughout the infrastructure life cycle. The research is based on a literature review and a quantitative case study of the A5 highway overpass near Kaunas. The case study uses BIM-based data, and One Click LCA software to assess different design scenarios in accordance with ISO 14040/44 and EN 15804 standards. Several scenarios are analysed, ranging from a baseline design with conventional materials to more sustainable alternatives incorporating low-carbon materials, improved transport logistics, and circular design strategies. The results show that material production stages are the main source of carbon emissions. Replacing conventional concrete and steel with low-carbon and recycled alternatives achieved the greatest reduction in Global Warming Potential, while transport optimization provided smaller but additional benefits. The fully circular design scenario resulted in the highest overall emission reduction. The study also highlights the role of Digital Twin technologies in supporting circular infrastructure through real-time data monitoring and predictive maintenance. Although challenges remain, the integration of LCA, CE, and DT offers a practical pathway toward low-carbon and resource-efficient infrastructure development
Utilization of wood sawdust in artificial aggregate production and analysis of artificial aggregates.
No full textThis study evaluates the suitability of an artificial wood-sawdust-based aggregate for concrete. The performance of this aggregate was compared with other aggregates and concrete without aggregate. The experimental program included semi-adiabatic calorimetry, flexural and compressive strength tests, shrinkage deformation measurements, porosity, and water absorption analysis. Additionally, the resistance to salt-scaling was assessed, and the potential CO₂ reduction achieved by replacing traditional aggregates with wood-based granules was calculated. Lightweight artificial aggregates were produced and later used in mortars for further experiments, replacing sand in the mixtures. The results in the experimental part showed that the addition of wood sawdust reduces the heat released during hydration. When chemical admixtures were incorporated, the initial temperature increased and hydration accelerated. The bulk density of wood-sawdust granules was found to be twice that of expanded clay and foam glass granules. Most shrinkage occurred within the first two weeks, after which the deformation gradually stabilized. Overall, the findings indicate that wood-sawdust granules represent a promising sustainable aggregate alternative, potentially contributing to reduced CO₂ emissions in concrete production. Masters’ final work contains 19 tables, 36 figures, 62 references
Šiltnamio efektą sukeliančių dujų emisijų vertinimas taikant karštųjų taškų analizę ir mašininio mokymosi metodus.
No full textGreenhouse gas (GHG) emissions vary across countries due to differences in economic activity, energy use, technology, and other persistent country-specific factors. Empirical research on these differences typically relies on country-level panel data. While traditional panel-data regressions are widely used to control for unobserved heterogeneity, they impose restrictive functional forms. More flexible machine learning methods have also been applied to emissions data, but often in pooled settings that do not explicitly account for persistent country-level heterogeneity. At the same time, the emissions literature documents spatial clustering across countries, motivating the analysis of spatial dependence both in the raw data and in model residuals. This thesis analyses cross-country differences in production-based per-capita GHG emissions in Europe using a combination of exploratory spatial analysis and machine-learning methods for panel data. The analysis is based on a balanced panel of 25 European countries observed annually from 2000 to 2023. It addresses two main questions: whether GHG emissions exhibit spatial clustering, and how explicitly modelling persistent country-specific heterogeneity affects predictive performance, residual behaviour, and model interpretation in flexible machine-learning models. Spatial patterns in emissions are analysed using local hot spot analysis and spatio-temporal clustering methods, which identify statistically significant clusters of high and low per-capita emissions and characterise their evolution over time. Predictive modelling is conducted using Gaussian Process Boosting (GPBoost), estimated both in pooled form and with explicit country-specific intercepts and time trends. Models are trained and evaluated using time-respecting expanding-window cross-validation. Beyond average predictive accuracy, residuals are analysed across countries, time, and space to assess whether models capture persistent heterogeneity and spatial structure. Model interpretation is examined using SHAP values, with feature attributions compared across model specifications. The results show that European GHG emissions exhibit spatial clustering that is persistent in some regions and evolving in others. Explicitly accounting for country-level heterogeneity in GPBoost leads to only modest improvements in predictive accuracy, but clear improvements in residual behaviour, including reduced systematic country-level bias, lower within-country residual dispersion, and the removal of spatial structure in prediction errors. Differences in SHAP-based feature attributions demonstrate that the estimated contribution of observed variables depends on whether persistent country-specific heterogeneity is modelled, even when overall predictive performance changes little. These results indicate that unobserved heterogeneity should be explicitly considered when applying machine-learning methods to panel data, particularly for interpretation
Thermally stable and energy efficient newly synthesized bipolar emitters for yellow and green OLED devices /
No full textOrganic light-emitting diodes (OLEDs) have emerged as a leading high-resolution display and lighting technology, as well as for photo-therapeutic applications, due to their light weight, flexibility, and excellent color rendering. However, achieving long-term thermal stability and high energy efficiency remains a principal issue for their widespread adoption. Strong thermal robustness in OLED emitter materials is a critical parameter for achieving long device lifetimes, stable film morphology, reliable high-temperature processing, and sustained interface integrity in high-performance hosts. Bipolar emitters RB14 (N-(9-ethylcarbazole-3-yl)-4-(diphenylamino)phenyl-9H-carbazole-9-yl-1,8-naphthalimide), RB18 (N-phenyl-4-(diphenylamino)phenyl-9H-carbazole-9-yl-1,8-naphthalimide), and RB22 (N-phenyl-3-(2-methoxypyridin-3-yl)-9H-carbazole-9-yl-1,8-naphthalimide) were newly synthesized. RB18 is a yellow bipolar OLED emitter that has a glass transition temperature (Tg) of 162 °C and thermal durability (Td) of 431 °C, which is the highest reported value for naphthalimide-based bipolar emitter derivatives for yellow OLEDs. Meanwhile, RB14 and RB22 are green OLED emitters that have glass transition temperatures (Tg) of 133 °C and 167 °C, and thermal durabilities (Td) of 336 °C and 400 °C, respectively. We have fabricated OLED devices using these bipolar emitters dispersed in CBP host matrix, and we have found that the maximum EQEs (%) for RB14, RB18, and RB22 emitter-based devices are 7.93%, 3.40%, and 4.02%, respectively. For confirmation of thermal stability, we also used UV-visible spectroscopy measurements at variable temperatures on annealed spin-coated glass films of these emitter materials and found that RB22 is the most thermally stable emitter among these materials
Development of a semi-automated drive unit assembly process.
No full textIn this project, the workflow of the manual drive-unit assembly process was examined and a semi automated system was developed to reduce human-error probability and stabilize the final product quality. The main problem was related to the fact that manual assembly operations exhibited high FMEA RPN values, as errors were often not detected in real time, while the assembly of expensive mechanical and electronic components introduced additional risk. During the study, three sequentially operating semi-automated fixtures were designed, forming an integrated assembly system in which Poka–Yoke elements, mechanical positioning features, laser, inductive and photo sensors, step-based Siemens PLC logic, and HMI visual instructions were implemented. Experimental analysis included cycle-time evaluation and the creation of FMEA tables before and after system implementation to determine the extent to which human-factor risks were reduced. It was established that the overall assembly cycle decreased by approximately 16%, and that most manual-process risks were reduced by 62–93%. Depending on the operation, the average RPN value decreased from 224 to 46, representing a reduction of about 79%. The results demonstrated that automated checking mechanisms significantly improved the reliability of screw-tightening, rubber-seal installation, adhesive application, and connection verification. In summary, the semi-automated system enabled a more stable, clearly controlled, and reliable assembly process in which the majority of human-factor related risks were either eliminated or became easily manageable, and the resulting process quality no longer depended on operator experience. The findings can be applied in practical manufacturing environments to reduce defects, increase process stability, and improve the accuracy of quality control
Patvarus ženklinimas QR kodu skaitmeniniam produkto pasui mados pramonėje.
No full textThis study develops and tests a practical Digital Product Passport (DPP) solution for the fashion industry by combining durable QR-code labels on textiles with a simple, low-cost web system. The work responds to EU ESPR-related expectations that product information should be transparent, standardised, and available throughout the product lifecycle. A review of QR codes, RFID, and NFC shows that QR codes are the most appropriate option for consumer use because they are inexpensive, can be scanned with any smartphone, and require little supporting infrastructure, while RFID and NFC typically involve higher costs and more complex implementation.To examine performance under realistic conditions, an experimental programme assessed QR durability and long-term scannability on a 100% polyester knit fabric. Version 2 QR codes (25×25 modules) were produced in several physical sizes and applied using sublimation printing, heat transfer, and embroidery. The samples were exposed to domestic washing and tumble drying in line with ISO 6330 and to cyclic tensile loading in both fabric directions in line with ISO 20932-1. Readability was then evaluated using a controlled smartphone-scanning procedure consistent with ISO/IEC 15415 quality principles, supported by an ImageJ-based assessment of QR distortion.The findings show that long-term digital accessibility depends mainly on the application method and the minimum QR size. Sublimation remained reliably readable at sizes of 20 mm and above, and heat transfer stayed fully readable within the tested 30–50 mm range. Embroidery performed worst: readability decreased after mechanical loading and washing, and very small codes (10 mm) did not provide dependable scanning. Finally, a DPP prototype built with Google Sites, cloud-hosted data, and dynamic QR access demonstrated that structured product information can be presented clearly, updated in real time, and accessed across devices, offering a feasible pathway for cost-constrained SMEs
On the convergence rate of the caputo fractional difference logistic map of nilpotent matrices /
No full textThe convergence rate of the Caputo fractional difference logistic map of nilpotent matrices is investigated in this paper. The divergence rate of the auxiliary parameters governing the dynamics of nilpotents is exponential and is multiple to the Lyapunov exponent of the scalar non-fractional map. However, the convergence of the Caputo fractional difference logistic map of nilpotent matrices to a stable fixed point is governed by the interplay between the convergence rate of the scalar fractional map (the power law rate) and the exponential convergence induced by the nilpotent matrices. It is demonstrated that convergence is determined by the competition between the power law and exponential mechanisms, a feature not captured by scalar fractional maps, with higher-order auxiliary parameters diverging exponentially at increasingly higher rates. This paper provides insight into the complex dynamics of fractional maps of nilpotent matrices
Assessment of the innovativeness of Lithuania’s food industry.
No full textIn the 21st century, the importance of innovation in economic sectors has grown steadily, and innovativeness has become one of the key factors determining the competitiveness and long-term development of organisations. In the food industry, innovativeness is directly related to economic, social, and environmental trends, sustainability requirements, changes in consumer behaviour, and the regulatory environment. In the Lithuanian context, its relevance is reinforced by the sector's growth potential and increasing opportunities for innovation funding. The sector is dominated by small and medium-sized enterprises, whose innovation development is limited by resources, and the assessment of their innovativeness is complicated by informal or statistically unrecorded changes. Furthermore, there is currently no united, empirically based methodology for assessing innovativeness that is specific to the sector. For these reasons, the main problem of the project is how to assess the innovativeness of the Lithuanian food industry. The subject of the project is the innovativeness of the Lithuanian food industry. The aim of the project is to assess the innovativeness of the Lithuanian food industry based on the research methodology developed. To achieve the project's aim, six objectives were identified, the implementation of which is supported by the research results. An analysis of scientific literature revealed that the concept of innovativeness is broader than the creation or implementation of individual innovations and is associated with the continuous ability to generate, apply, and maintain new solutions. It was found that innovativeness is determined by interrelated internal and external factors, including human capital, organisational culture, management decisions, technological base, competition, regulatory environment, market development, knowledge exchange, and consumer expectations. An analysis of the methods used to assess innovativeness showed that general assessment methods provide an overall picture of innovativeness, but do not sufficiently reveal the internal processes of the food industry, therefore, a more tailored assessment methodology is needed to assess the innovativeness of the sector. Throughout the project, a methodology for assessing the innovativeness of the Lithuanian food industry was developed, based on expert assessment and analysis of official statistical indicators, allowing for a reliable assessment of the sector's innovativeness and calculation of the Lithuanian food industry's innovativeness index. An assessment of the innovativeness of the Lithuanian food industry has shown that the sector has a high level of innovativeness. The results show that the greatest contribution to the innovativeness of the Lithuanian food industry sector comes from the modernisation of production, digital solutions, and productivity increases, while in other areas related to human capital, sustainability, quality and food safety management, and investment in innovation, changes are progressing more slowly. Based on the results obtained, recommendations were made to apply expert assessment more widely, involving a larger number of experts from different areas of the food industry, to expand the system of indicators, and to analyse longer-term official statistical time series in further studies and examine the links between indicators of innovativeness and the performance of food industry companies
The impact of digital competencies on the resilience of public sector employees.
No full textRelevance of the topic. In the public sector, electronic services are being steadily expanded, data- driven solutions are being applied increasingly widely, and processes are being automated; therefore, employees’ day-to-day work is becoming increasingly dependent on information systems. This change is also relevant for workforce management, as employees’ preparedness and strain are not always assessed through the interaction of resilience and digital competencies. Service quality and operational continuity are directly linked to whether employees can maintain functioning under procedural requirements, the obligation to ensure accuracy and traceability, information flows, deadline pressure, and continuous change. When these requirements coincide with technological or process disruptions, the risk of errors increases and maintaining control over work becomes more difficult; therefore, it is important to understand which internal and organisational resources enable employees to restore control and continue working. Digital competencies are considered a necessary precondition for achieving digital transformation goals in the public sector, and strengthening resilience has practical significance because resilient employees tend to report higher job satisfaction and are less likely to leave the organisation. Since studies more often analyse organisational capacities and technological solutions, while the links between individual digital competencies and employees’ resilience are examined fragmentarily, and resilience and digital competencies are often analysed separately, a comprehensive approach is lacking in the Lithuanian context. The object of the study – the link between digital competencies and the resilience of public sector employees. The aim of the study – to examine how digital competencies affect the resilience of public sector employees. Main results of the study. The study found that the digital demands experienced by employees are most often associated with procedures, accuracy and traceability, information flows, the use of multiple systems, changes and deadlines, while technostress episodes become more salient when these demands intertwine with technological or process disruptions and unclear responsibility. Digital competencies function as an internal resource when they help employees navigate systems, reduce the likelihood of errors, find solutions faster, and restore control; however, resilience is significantly strengthened by organisational resources, especially the reliability of the support system, the clarity of instructions, opportunities for learning, and conditions for adaptation. In practice, resilience manifests through recurring pathways of action that include work organisation, quality assurance, problem solving, mobilising help, learning and adaptation, and wellbeing and boundary management; in situations of prolonged disruptions, this also includes disengagement or avoidance