Institutional Repository of Klaipėda University
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Detection of oncogene hotspot mutations in female NSCLC tumor DNA and cell-free DNA /
No full textNon-small-cell lung cancer (NSCLC) is the most prevalent type of lung cancer, with extensively characterized mutational spectra. Several biomarkers (such as EGFR, BRAF, KRAS gene mutations, etc.) have emerged as predictive and prognostic markers for NSCLC. Unfortunately, the quality of the available tumor biopsy and/or cytology material is not always adequate to perform the necessary molecular testing, prompting the search for alternatives. Cell-free DNA (cfDNA) found in plasma is emerging as a highly promising avenue or a supplementary method for assessing the efficacy of cancer treatments. This is especially valuable in instances where conventional biopsy specimens, like formalin-fixed, paraffin-embedded (FFPE), or freshly frozen tumor tissues prove inadequate for conducting molecular pathology analyses subsequent to the initial diagnostic procedures. By leveraging cfDNA from plasma, clinicians gain an additional tool to gauge the effectiveness of cancer therapies, thereby enhancing their ability to optimize tailored treatment strategies. In this study, 51 Lithuanian females with NSCLC were analyzed, with adenocarcinoma being the predominant pathology diagnosis in 40 cases (78%). Target mutations were identified in 38 out of 51 patients (74.5%) in tumor tissue samples, while in plasma samples, they were identified in only 10 patients’ samples (19.6%). Even though we did not have enough voluminous plasma samples in our study, gene mutations were detected in plasma from ten women, three of whom were diagnosed with early stages of lung cancer (stages I and II). For these patients, the following mutations were detected: deletion in exon 19 of the EGFR gene and single nucleotide polymorphisms in the TP53 and MET genes. All other women were diagnosed with stages III or IV of lung cancer. This indicates that the later stages of cancer contribute more cfDNA in plasma, making extraction less complicated
Causal modeling of academic activity and study process management /
No full textThis article presents a causal modeling approach for analyzing the processes of an academic institution. Academic processes consist of activities that are considered self-managed systems and are defined as management transactions (MTs). The purpose of this article is to present a method of causal modeling of organizational processes, which helps to determine the internal model of the current process under consideration, its activities, and the processes’ causal dependencies in the management hierarchy of the institution, as well as horizontal and vertical coordination interactions and their content. Internal models of the identified activities were created, corresponding to the MT framework. In the second step, based on the causal model, a taxonomy of characteristics is presented, which helps to systematize the process quality assessment and ensures the completeness of the characteristics and indicators. Predefined structures of characteristic types are the basis of activity content description templates. Based on the proposed method, two causal models are created: the “to-be” causal model of the target study process (based on expert knowledge) and the “as-is” documented (existing) model of the study process used to evaluate the study process’s quality. The principles and examples of comparing the created “to-be” causal model with the existing study process monitoring method are presented, enabling the detection of the shortcomings in the existing method for assessing academic performance. Causal modeling allows for the rethinking of existing interactions and the identification of necessary interactions to improve the quality of studies. The comparison based on causal modeling allows for a systematic analysis of regulations and the consistent identification of new characteristics (indicators) that evaluate relevant aspects of academic processes and activities
"Job announcement portal" graphic interface project.
No full textThe project focuses on creating a modern job portal with a user-friendly interface using the MERN (MongoDB, Express.js, React.js, Node.js) technology stack. The goal is to seamlessly integrate functionality with user experience to meet the needs of both job seekers and employers. The graphical interface is designed using the Figma platform, allowing for detailed visualization and alignment with technical requirements. The MERN architecture, known for its reliability, collaboration capabilities, and strong developer community support, ensures high-speed data management, efficiency, and security. The software analysis outlines the MERN architecture components, including MongoDB, Express.js, React.js, and Node.js, and additional libraries like Tailwind CSS, PostCSS, Autoprefixer, and Notistack for styling and user interface management. MongoDB, chosen for its document-oriented structure, scalability, and performance, stores job and user data. The creation of the MongoDB database involves modeling the data structure based on a Unified Modeling Language (UML) diagram. The implementation includes user authentication, job listing retrieval, and other essential features using Express.js and Node.js. The user interface design process is conducted collaboratively using the Figma platform, taking inspiration from popular job portals' user experiences. The React.js library is employed for interface development, creating reusable components for a clean and organized code structure. The use of React hooks, axios for asynchronous calls, and CSS-in-JS solutions like styled-components and Tailwind CSS ensures an interactive and visually appealing user interface. In conclusion, the "Job Portal" graphical interface project successfully combines technical implementation with a usercentric approach. It provides a flexible and intuitive platform for job seekers and employers, facilitating easy navigation, job posting, and administration. The project's MERN architecture and Figma-based design make it adaptable for various needs, with an open scope for future enhancements and improvements. The project accomplishes its objectives of creating a functional and aesthetically pleasing job portal with a seamless user experience. Reach aim. Create a user-friendly website for job searching and posting. Research problem. In today's digital age, job searching is a crucial online activity for many people. However, numerous platforms offering job search capabilities are often challenging to navigate or impose fees for access. Our website prototype is designed to make this experience easier by simplifying the process of job searching, enabling users to engage with a fully functional web application that is free from constraints or financial requirements. Key results and conclusion. This paper analyses development of the job posting website. It introduces the general concept of whole development process. The job posting website was realized and a graphical user interface was presented. Keywords. Job searching, website, user interface, database, programming
Impact and technical solutions of hydrodynamic and thermodynamic processes in liquefied natural gas regasification process /
No full textTransporting natural gas in liquid form increases opportunities for storage and export worldwide, thus making transportation more sustainable. However, liquefied natural gas (LNG) is in an unsteady state, leading to LNG conversion to the gas state occurring throughout the storage, loading, unloading, and transportation processes. To observe the transition of LNG to natural gas, mathematical models are developed to monitor technical parameters. This research analyses a floating storage and regasification unit for and adopts a mathematical model of the LNG regasification system, aiming for improved observation of hydrodynamic, dynamic, and thermo-physical properties. The complex mathematical model of the system was implemented using the Fortran programming language and MATLAB R28a. From the investigation of the total LNG regasification system, it could be concluded that increasing the outlet pressure of the system results in a decrease in the velocity of LNG. It was found that the total hydraulic energy losses of the total LNG regasification system were approximately 41.3 kW (with outlet pressure of 2 MPa), 12.75 kW (with outlet pressure of 5 MPa), and 4.24 kW (with outlet pressure of 7 MPa)
Air pollution in the port city of Lithuania: characteristics of the distribution of nitrogen dioxide and solid particles when assessing the demographic distribution of the population /
No full textThis research addresses a gap in localized air quality assessments by measuring pollution levels in Klaipeda, a Baltic port city, using passive solid particle collectors and nitrogen dioxide (NO2) diffusion tubes. Passive sampling techniques were employed due to their cost-effectiveness and ease of deployment, allowing for practical monitoring over short-term periods. By targeting diverse functional zones, this study aims to provide a comprehensive analysis of air pollution patterns and seasonal variations in the region. Air pollution, primarily from NO2 and particulate matter (PM), poses significant risks to public health, especially in densely populated urban areas. Air quality was assessed by measuring total suspended particulates (TSP) and NO2 concentrations across 19 strategically chosen sites, covering key functional zones, such as industrial areas, green spaces, residential neighborhoods, transport hubs, and the port. Results show elevated pollution levels near major roads and the port area, likely driven by heavy traffic, industrial emissions, and port activities. These patterns correlate with areas of higher population density, highlighting the intersection of air quality challenges with human health risks in urbanized zones. Seasonal data reveal a notable peak in NO2 concentrations during winter, likely due to increased heating demand and reduced atmospheric dispersion. These findings suggest that air quality management strategies should be adaptive to seasonal fluctuations, particularly by addressing emissions from heating sources in colder months. The study underscores the necessity of integrating sustainable urban planning with targeted air quality interventions. Expanding green spaces, enhancing traffic regulation, and establishing protective zones near industrial areas are critical strategies for mitigating pollution. These insights are essential for guiding both urban development and public health policies in Klaipeda and other coastal cities facing similar environmental challenges
Leisure-time physical activity improves happiness, health, and mood profile better than work-related physical activity /
No full textBackground In an online survey of Lithuanian adults (n = 1140) aged 18 to 64 years, we sought to better understand the factors influencing the structure of physical activity (PA). We hypothesised that the PA paradox (i.e. the benefits of PA will be much greater during leisure-time than work-related or household moderate to vigorous PA) occurs more subjectively for psychological well-being indicators, than physiological well-being indicators, and should not depend on age or gender. Methods An online questionnaire was distributed as to potential participants through the Facebook social networking website within the period May 2021 to December 2021. PA was assessed using the long version of the International Physical Activity Questionnaire (IPAQ). Mood responses were assessed using the Brunel Mood Scale (BRUMS-LTU). Emotional intelligence was assessed using the Schutte Self-Report Emotional Intelligence Test (SSREIT). Perceived stress was assessed using the 10-item Perceived Stress Scale (PSS-10). Descriptive analysis, a two-way analysis of variance, and linear regression analysis were used to interpret the data. Results The results revealed that a PA paradox occurred in women and men in terms of health, happiness, vigour and perceived stress, and only in women according to morbidity and overeating. According to the regression analysis, women’s and men’s subjective health (β = 0.135; p < 0.001), happiness (β = 0.084; p = 0.018) and vigour (β = 0.169; p < 0.001) were significantly positively, and perceived stress (β = -0.088; p = 0.009) negatively correlated (regardless of age) only with leisure-time moderate to vigorous PA. ‘Healthy’, i.e. the amount of leisure-time PA in men decreases with age, while it does not change in women. Conclusions We believe that this study has expanded a clearer understanding of the PA paradox and its possible application to improving the health of individuals of different age groups
Enhancing global sustainability: the role of the blue economy in preserving natural capital /
No full textThis investigation delineates the critical role of the Blue Economy in preserving the planet's natural capital, a cornerstone for sustainable development. A systematic analysis of theoretical research and policy documents was conducted to elucidate the integration of economic systems with environmental conservation. Correlation and regression analyses were employed to evaluate the interactions between economic activities and the status of natural capital, with particular emphasis on Gross Domestic Product (GDP), population growth, ecological footprints, and biocapacity over the period from 1994 to 2020. The results revealed that prevalent economic practices are contributing to significant depletion of natural capital, thereby posing severe risks to both ecological and economic stability. Moreover, the efficacy of the Blue Economy in mitigating these risks was demonstrated, showcasing its potential to align economic growth with environmental preservation. This study provides compelling evidence that a transition towards the Blue Economy is not merely viable but imperative for sustainable development. The implications of these findings are pivotal for policymakers, stakeholders, and industries, underscoring the urgent need to revise economic strategies to prioritize environmental sustainability. Such a shift is deemed crucial for realizing long-term sustainability goals and ensuring economic resilience in the face of environmental challenges
Analysis of virtual tourism opportunities in Klaipėda, Lithuania /
No full textIn the current article the possibilities of virtual tourism in the city of Klaipėda are analysed. Over the past few decades, digital technology has helped the travel and tourism industry increase its reach. As the world faces the COVID-19 pandemic, virtual tourism has become relevant when the pandemic has made it more difficult to travel in real life. Therefore, it is important to determine whether the prospect of virtual tourism is visible in the city of Klaipėda, and to determine the possibilities of virtual tourism in the city of Klaipėda. The article reviews the concept of virtual tourism and virtual tourism technologies, analyses the idea of virtual tourism products, identifies the classification of virtual tourism products. The trends of virtual tourism in the world and in Lithuania are reviewed. The analysis is based on a detailed analysis of scientific literature, journalistic articles and statistical data. A total of 137 publications were analyzed. Presenting virtual tourism products in Lithuania and the city of Klaipėda. The possibilities of virtual tourism and virtual tourism products of the city of Klaipėda are determined. Such results can be used as a positive role model of the small city virtual tourism attraction and system creation
Neurorinkodara: vartotojų elgsenos suvokimo metodika.
No full textThis paper studies the concept of neuromarketing in consumer behaviour, emphasising the fact that consumers are not entirely rational in their decision-making process, because emotions influence their behaviour. Consequently, the neuromarketing field emerged as a way to understand the subconscious motivations of consumers. The scientific problem of this paper is to analyse how neuromarketing techniques can be effectively integrated with traditional marketing research methods to provide a comprehensive understanding of consumer behaviour. It emphasises the fact that traditional marketing research tools may not reveal all essential insights into consumer behaviour research. Therefore, market research practices should employ neuromarketing tools such as eye tracking, facial expression analysis, biometrics and neuronal activity measurements. First, six principal neuromarketing research areas are identified: branding, product design and innovation, advertising effectiveness, shopper decision-making, online experiences, and entertainment effectiveness. Next, a simplified human behaviour model, consisting of three phases, unconscious, conscious and observable, is discussed. Finally, the paper focuses on criticisms of neuromarketing and ethical issues
Coverage estimation of benthic habitat features by semantic segmentation of underwater imagery from South-eastern Baltic reefs using deep learning models /
No full textUnderwater imagery (UI) is an important and sometimes the only tool for mapping hard-bottom habitats. With the development of new camera systems, from hand-held or simple “drop-down” cameras to ROV/AUV-mounted video systems, video data collection has increased considerably. However, the processing and analysing of vast amounts of imagery can become very labour-intensive, thus making it ineffective both time-wise and financially. This task could be simplified if the processes or their intermediate steps could be done automatically. Luckily, the rise of AI applications for automatic image analysis tasks in the last decade has empowered researchers with robust and effective tools. In this study, two ways to make UI analysis more efficient were tested with eight dominant visual features of the Southeastern Baltic reefs: 1) the simplification of video processing and expert annotation efforts by skipping the video mosaicking step and reducing the number of frames analysed; 2) the application of semantic segmentation of UI using deep learning models. The results showed that the annotation of individual frames provides similar results compared to 2D mosaics; moreover, the reduction of frames by 2–3 times resulted in only minor differences from the baseline. Semantic segmentation using the PSPNet model as the deep learning architecture was extensively evaluated, applying three variants of validation. The accuracy of segmentation, as measured by the intersection-over-union, was mediocre; however, estimates of visual coverage percentages were fair: the difference between the expert annotations and model-predicted segmentation was less than 6–8%, which could be considered an encouraging result