Vilnius Gediminas Technical University

A nanostructured metamaterial absorber composed of alternating semiconductor and dielectric layers is presented and numerically analyzed in this article. The development of a semiconductor adjustable absorber in the THz will open up new possibilities for quantum information science, imaging, health, and sensing applications, particularly those that need to be portable. Here, we build a unique semiconductor nanostructured metamaterial that exhibits increased absorption efficiency at various temperatures by carefully organizing and shaping the nanostructured semiconductor metamaterial geometry. The stability of absorption properties is observed for a large range of the alternating layers width values. This discovery paves the way for the potential development of a new generation of THz quantum detectors that operate close to room temperature and offer exceptional improved absorption for a broader variety of applications.

The paper presents comparative laboratory investigations of tension fastener models that attach rails to concrete sleepers. The aim of the paper was to assess the influence of geometric nonconformity of the actual industrial product that meets the PKP Polskie Linie Kolejowe S.A. requirements on the operation of a tension-fastening clamp under stress. Due to the cost and limited possibility of research of the actual industrial product, an additional objective of the research was to validate the usefulness of it in the comparative assessment of the models. In the research, the authors used models of tension fastening clamps manufactured in incremental engineering technology (3D print) on scale 1:2. The properties of the fastening clamps (in their nominal shape) were compared (described in the PKP Polskie Linie Kolejowe S.A. documentation) with the fastening clamps of the actual shape. In the investigation, the authors have confirmed the negative influence of the non-conformance of the shape of the actual fastening clamps with the nominal ones.

The globe faces human capital deterioration, climate change, poverty, and inequality. The principal vision of the United Nations (UN) is to transform the world through sustainable development. Human capital is one of the significant affectees and the most essential component of the sustainable development goals (SDGs) of the organization of economic cooperation and development. Human capital management concerning corporate social responsibility (CSR) covers the social aspects of sustainability. The focus of this study is to explore and review the role of socially responsible human resource management (SRHRM) for employee well-being, specifically in the context of employee voice enhancement strategies and catering to employee silence. The research trends regarding focus on employee voice in the area of SRHRM are determined through bibliometric analysis, applying R-Tool, and systematic literature review using PRISMA methodology. The research results indicate how the emergence of sustainable human resource management (HRM) has enhanced the well-being of employees in the context of encouraging the voice of the employee, who is the most important internal stakeholder of organizations. It also entails providing productive employment opportunities and investment and development of Human capital. Findings fill the research gaps, identifying where HRM practitioners, policymakers, and researchers need to focus in the future. Additionally, this study sheds light on the methodologies and theories used to explain the employee voice phenomenon in previous studies.

Calcium electroporation (CaEP) is an efficient approach for ovarian cancer treatment. It causes cell death by introducing elevated levels of calcium into cells. In this work, the research focused on two types of cell lines: CHO-K1, representing normal ovary cells, and OvBH-1, representing ovarian clear carcinoma cells. Those cell lines exhibited distinct reactions to calcium electroporation (CaEP). Also, we have evaluated the effects of 17β-estradiol following CaEP and electrochemotherapy (ECT) with cisplatin (CPP). The combination of ECT with CPP and CaEP with prior E 2 preincubation resulted in approximately 23.55 % and 39 % decreases in cell survival compared to the control cells (exposed to CPP and CaCl 2 alone) for ovarian cancer cells. The obtained results showed that ovarian cancer cells preincubated with 17β-estradiol after exposure to pulsed electric fields undergo primary necrosis. Additionally, preincubation of ovarian cancer cells with 17β-estradiol can significantly improve the effectiveness of both chemotherapy and electrochemotherapy involving cisplatin and calcium chloride.

This systematic review explores the concept of creativity in crisis communication, a widely used but poorly conceptualised phenomenon. It draws on empirical research and case studies to highlight the diversity of creative approaches during major crises such as natural disasters, health crises, or conflicts. The focus is particularly on situations where these crises are protracted, and creativity is required to deal with the “fog of warning” caused by repeated alerts. It is also important to exercise creativity in order to control the meaning of information and combat the spread of misinformation and conspiracy theories. Creativity in crisis communication during major crises is described as the dynamic generation of novel and contextually relevant strategies using unconventional or metaphorical elements to engage audiences, reshape their understanding, and drive behavioural change for effective crisis resolution and recovery. The study provides a framework for understanding creativity in crisis communication by synthesising existing academic knowledge. Using the preferred reporting items for systematic reviews and meta-analyses methodology, 42 articles were analysed and categorised into three areas of communication: meaning making, behaviour framing, and reputation preservation. The framework illustrates the multiple facets of creativity: metaphorical creativity promotes critical reflection; visual representation enhances accessibility; humour and creative solutions engage and motivate diverse audiences; artistic elements, serious games and creative scenarios facilitate behaviour change. This framework underscores the critical role of creativity in crisis contexts, bridging the gap between standard communication and innovative, contextually relevant strategies in crisis communication strategies.

The European University Initiative established 64 transnational alliances of higher education institutions. Each of these European Universities Alliances seeks to align universities to enhance academic excellence and competitiveness of the European Higher Education Area. While branding of higher education institutions has become a professionalized practice, creating a transnational alliance poses challenges beyond traditional academic visual identity. The aim is to map out visual and discursive self-representation patterns of European University Alliances on their websites, involving European values such as for example, international cooperation, student mobility, and inclusivity. Using multimodal discourse analysis, this study examines online construction of academic identities of selected European University Alliances. It analyses (1) composition, colour, and typography used in European University Alliances’ logotypes; (2) the features of photographs and graphics; and (3) the typology of names and keywords in mission statements. The findings highlight the importance of generic imagery and compositional devices evoking positive emotional responses as well as recognizable cultural symbols and colours that align with the values of academia and “Europeanness”.

Recyclable construction waste can be used as a low-cost material to reduce stormwater pollution caused by various pollutants. In recent years, studies have reported increased water contamination from chlorine and chlorine compounds and its negative impact on aquatic ecosystems. When assessing the need for waste recycling, circularity, and stormwater reuse, it is worth evaluating the capacities of construction waste materials to reduce stormwater pollution from residual chlorine. Laboratory experiments using bentonite waste material (bentonite clay) and sodium hypochlorite solutions were carried out to analyze the potential of bentonite clay to retain residual chlorine in stormwater and evaluate its capacity to be applied as filtration media in green infrastructure. In the first stage, the particle size distribution and texture of bentonite clay were assessed using laboratory sieve analysis and microscopy. The results of the experiments indicated that the optimal grain size to retain pollutants was 0.8-2.0 mm. The microstructure analysis showed the capacity of bentonite to retain residual chlorine. The results of the static and dynamic experiments (leaching and filtration tests) show that the bentonite clay retained up to 44% of the residual chlorine. The obtained results indicate that bentonite clay might be suitable for application as filtration media in green infrastructure to reduce stormwater contamination.

Plain language summary How Media Exposure Influences Gambling Intentions and Problem Gambling: Insights from Lithuanian Gamblers A study was conducted to predict how media exposure and customer behavior affect people’s intentions to gamble and problem gambling. The study used the social cognitive theory and the theory of planned behavior to analyze 1,777 observations of Lithuanian gamblers. The results showed that media exposure can strengthen attitudes, subjective norms, and perceived control. This, in turn, increases the intention to gamble. However, subjective norms had a negative impact on gambling intention. The study also found that gambling intention directly affects problem gambling severity. By combining social cognitive theory and theory of planned behavior, the study provides a clearer understanding of how gambling exposure in various forms of media can affect attitudes, subjective norms, and perceived behavioral control. These findings have important implications for policymakers, health organizations, and marketers, and enhance discussions on gambling behavior

Lingonberries (Vaccinium vitis‐idaea L.), rowanberries (Sorbus aucuparia L.) and rosehips (Rosa canina L.) positively affect human health due to their healing properties, determined by a high content of bioactive compounds. The consumption of unprocessed wild berries is relevant and encouraged, making their in‐depth microbiological characterization essential for food safety. This study presents the first high‐throughput sequencing analysis of bacterial and fungal communities distributed on the surface of lingonberries, rowanberries and rosehips. Significant plant‐defined differences in the taxonomic composition of prokaryotic and eukaryotic microbiota were observed. The bacterial community on rosehips was shown to be prevalent by Enterobacteriaceae, lingonberries by Methylobacteriaceae and rowanberries by Sphingomonadaceae representatives. Among the fungal microbiota, Dothioraceae dominated on rosehips and Exobasidiaceae on lingonberries; meanwhile, rowanberries were inhabited by a similar level of a broad spectrum of fungal families. Cultivable yeast profiling revealed that lingonberries were distinguished by the lowest amount and most distinct yeast populations. Potentially pathogenic to humans or plants, as well as beneficial and relevant biocontrol microorganisms, were identified on tested berries. The combination of metagenomics and a cultivation‐based approach highlighted the wild berries‐associated microbial communities and contributed to uncovering their potential in plant health, food and human safety.

The aim of the article is to analyse the relationship between company growth, measured as an increase in Earnings Per Share (EPS) in 3- and 5-year periods, and companies’ financial condition, measured using the Altman z-Score (AS) model. The study was carried out on the example of companies included in the WIG Index and Warsaw Stock Exchange Index (in Polish: Warszawski Indeks Giełdowy – WIG) Environmental, Social, and Governance (ESG) between 2013 and 2020. Furthermore, among the companies included in the WIG index, companies belonging to the logistics industry were distinguished. An analysis of linear and panel relationships was used to verify the nature of the relationships between the variables taken into account. The z-Altman index was found to have a positive effect on company growth in a 3-year period for companies from the transport and logistics industry and all companies included in the WIG ESG index. Regarding company growth over the longer 5-year period, the influence of the z-Altman index on growth was not observed. Therefore, the results for companies in the WIG index show that for company growth in both the 3- and 5-year periods, the financial and economic condition of a company, measured by the z-Altman index, has no impact on the size of this growth, which was also confirmed by panel models.

Purpose Poor lung cancer patients’ outcomes and survival rates demand the discovery of new biomarkers for the specific, significant, and less invasive detection of non-small cell lung cancer (NSCLC) progression. The present study aimed to investigate the potential of miRNA expression as biomarkers in NSCLC utilizing a preclinical cell culture setup based on screening of miRNAs in NSCLC cells grown in 3D cell culture. Patients and Methods The study was performed using lung cancer cell lines, varying in different levels of aggressiveness: NCI-H1299, A549, Calu-1, and NCI-H23, as well as noncancerous bronchial epithelial cell line HBEC3, which were grown in 3D cell culture. Total RNA from all cell lines was extracted and small RNA libraries were prepared and sequenced using the Illumina NGS platform. The expression of 8 differentially expressed miRNAs was further validated in 89 paired tissue specimens and plasma samples obtained from NSCLC patients. Statistical analysis was performed to determine whether miRNA expression and clinicopathological characteristics of NSCLC patients could be considered as independent factors significantly influencing PFS or OS. Results Differentially expressed miRNAs, including let-7d-3p, miR-10a-3p, miR-28-3p, miR-28-5p, miR-100-3p, miR-182-5p, miR-190a-5p, and miR-340-5p, were identified through next-generation sequencing in NSCLC cell lines with varying levels of aggressiveness. Validation of patient samples, including tumor and plasma specimens, revealed that out of the 8 investigated miRNAs, only plasma miR-10a-3p showed a significant increase, which was associated with significantly extended progression-free survival (PFS) (p=0.009). Furthermore, miR-10a-3p in plasma emerged as a statistically significant prognostic variable for NSCLC patients’ PFS (HR: 0.5, 95% CI: 0.3–0.9, p=0.029). Conclusion Our findings of screening miRNA expression patterns in NSCLC cells grown in 3D cell culture indicated that the expression level of circulating miR-10a-3p has the potential as a novel non-invasive biomarker to reflect the short-term prognosis of NSCLC patients.

Sustainable food supply chain management (SFSC) can control food loss and waste by reducing resource consumption and environmental pollution, thereby ensuring sustainable food consumption and production patterns. Scholars have investigated specific aspects or links in SFSC but rarely studied the sustainability evaluation and selection of a whole supply chain to provide management suggestions under uncertain decision-making environments. This paper presents a comprehensive multiple criteria decision-making method called the SMAA-ORESTE method for SFSC selection. To reduce experts’ efforts, the holistic acceptability index in the SMAA-2 method is used to screen inferior SFSCs from a large number of alternatives. Then, the ORESTE method is combined with the SMAA method to evaluate SFSCs under uncertain information. The ORESTE method can specifically analyze the relationship between alternatives, and the SMAA method can analyze alternatives with unknown criteria weights by Monte Carlo simulation. The proposed method ensures the robustness and credibility of obtained ranking results. An illustrative example validates the applicability and robustness of the proposed method in selecting SFSCs with unknown criteria weights.

Machine learning (ML) methods are among the most promising technologies with wide-ranging research opportunities, particularly in the field of education, where they can be used to enhance student learning outcomes. This study explores the potential of machine learning algorithms to build and train models using log data from the "3D Modeling" e-course on the Moodle platform at TTK University of Applied Sciences, Tallinn, Estonia. By predicting trends, identifying patterns, and optimizing resource allocation, machine learning can improve the efficiency of e-learning and provide students with tailored recommendations for acquiring relevant knowledge and skills. The results of the study show that machine learning algorithms can be used to process the available e-course log data, using the clickstream of e-course resources and for their automated processing. The results suggest potential applications in personalized course recommendations, prediction and dropout prevention strategies, resulting in a more effective and personalized educational experience. Future research will focus on improving models of available registration data, exploring and using advanced machine learning techniques to improve the accuracy and usefulness of predictions, and providing faster recommendations to help students navigate their studies more effectively.

A visually impaired individual (VI) encounters numerous challenges in their daily activities, particularly in tasks reliant on visual systems such as navigation, educational pursuits, and shopping. Online shopping poses a heightened difficulty due to its reliance on visual representations of products in digital formats. The impact of visual impairment on product selection based on reviews remains inadequately investigated. This study endeavors to address two primary objectives. Firstly, we propose the creation of a dataset comprising product review videos (referred to as PVS10) tailored for visually impaired individuals. Secondly, we present a foundational summarization methodology designed to facilitate access to pertinent and informative content within extensive video collections for visually impaired individuals. Our dataset, gathered from YouTube, encompasses 10 distinct products, each associated with the top 10 review videos, totaling 100 videos of varying lengths. Utilizing the search term "review videos of PRODUCT NAME", we assembled the dataset to facilitate automated summarization processes aimed at maximizing salient information, minimizing redundant content, and preserving the overarching sentiment conveyed in the reviews. This research focuses on the challenges faced by visually impaired people in online shopping, particularly when selecting products based on customer reviews. Our study demonstrates that people with visual impairments may actively explore product reviews and only acquire the information they require.

The shift towards sustainable transportation is becoming increasingly important as the negative impact of traditional fuel-powered vehicles on the environment becomes more evident. Electric Vehicles (EVs) are considered a viable solution to this problem, and understanding the factors that influence consumer intention to purchase EVs is crucial for their widespread adoption. This study investigates the factors that influence individuals’ intention to purchase EVs. 4 independent variables were considered: Perceived Environmental Benefit (PEB), Perceived Performance Benefit (PPB), Perceived Performance Risk (PPR), and Perceived Financial Risk (PFR). A survey was conducted with 398 respondents, and the data collected were analysed using Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modelling (SEM). The results indicate that PEB, PPB, PPR, and PFR have significant effects on Purchase Intention (PI). Specifically, PEB and PPB positively affect PI, while PPR and PFR negatively affect it. These findings suggest that improving the PEBs and PPBs of EVs and reducing perceived performance and financial risks could encourage more individuals to purchase them.

The removal of particulate matter (PM) from air streams is essential for advancing environmental technologies and safeguarding public health. This study explores the performance of an electrostatic precipitator (ESP) in eliminating fine and ultra-fine PM under varied experimental conditions. It uniquely examines the influence of PM size and feed rate on ESP removal efficiency. The system’s use of low voltages enhances energy sustainability, while its innovative design improves corona discharge, leading to significant reductions in fine and ultra-fine PM emissions. Plants using electrical devices are increasingly being incorporated into material processing lines to reduce pollution in the surrounding work area, as well as to collect particle emissions in the atmosphere. It is also possible to recycle some raw materials in this way with low energy consumption. This cleaning technology increases the added value of industrial equipment, which affects its competitiveness and its impact on sustainable manufacturing. The experimental results indicate a steady electrostatic field voltage of 15.1 kilovolts, with an airflow maintained at 0.8 m/s through a doser at 2.5 bar, eliminating the need for a fan. The PM feed rate varied between 2 and 20 mm/h, with six trials conducted to ensure the data were consistent. Preliminary studies devoid of ESP intervention demonstrated little PM removal, since buildup on the chamber walls distorted the results. The installation of the ESF markedly enhanced the removal efficiency, achieving up to 95.5%. Further analysis revealed that ESP performance depended on PM concentration in the agglomeration chamber, achieving a clearance rate exceeding 98% under optimal conditions. Fine PM (0.35 to 8.7 µm) was more efficiently removed than ultra-fine PM (0.2 to 0.35 µm). The highest removal efficiency was observed at a feed rate of 0.962 mg/s, while the lowest occurred at 0.385 mg/s. A strong positive correlation between particle concentration and removal efficiency (Pearson value up to 0.829) was observed, particularly at feed rates of 0.128, 0.641, and 1.283 mg/s. The study’s findings confirm that the ESP is highly effective in removing particulate matter, particularly fine and ultra-fine particles, with an optimal feed rate, significantly enhancing the system’s performance.

Purpose of the review The use of robots in the health system is inevitable and covers many fields and scopes. Therefore, their organization and categorization are very important. However, the current classification of robots in the healthcare sector lacks coherence and consistency, leading to a fragmented understanding of their roles and capabilities. To address these issues, this review paper proposes a new classification based on healthcare processes and the intrinsic properties of robotic devices, such as minimally robotic manipulators, autonomous mobile robots, cobots, and artificial intelligence (AI)-based software. Recent findings Existing classifications often conflate established robots, experimental prototypes, and hypothetical concepts, creating a disorganized view of healthcare system robotics. Laboratory robots, notably absent from many classifications, further highlight the inconsistencies. Despite the promising advancements, the lack of a systematic classification obscures the trends in this dynamic field. Summary A comprehensive classification system for healthcare robots would help developers navigate complex regulations, identify relevant standards, and streamline the commercialization of robotic products. This would enable quicker development and market entry while ensuring compliance with safety and quality standards.

The growing interest in biodegradable scaffolds for bone regeneration created a need to investigate new materials suitable for scaffold formation. Poly(lactic acid) (PLA) is a polymer commonly used in biomedical engineering, e.g. in tissue engineering as a biodegradable material. However, the mechanical behavior of PLA along its degradation time is still not explored well. For this reason, the mechanical properties of PLA scaffolds affected by incubation in physiological medium needs to be investigated to show the potential of PLA to be used as a material for biodegradable scaffold formation. The purpose of this research is to determine the mechanical properties of PLA scaffolds before and after incubation, and to apply constitutive material models for further behavior prediction. Two sets of PLA scaffolds were printed by the 3D printer “Prusa i3 MK3S” and sterilized by ultraviolet light and ethanol solution. The first set of specimens was incubated in DMEM (Dulbecco’s Modified Eagle Medium) for 60, 120, and 180 days maintaining 36.5 °C temperature. The mechanical properties of the scaffolds were determined after performing the compression test in the “Mecmesin MultiTest 2.5-i” testing stand with a force applied at two different speed modes. The obtained data was curve fitted with the hyperelastic material models for a model suitability study. The second set of specimens was incubated in PBS (Phosphate Buffered Saline) for 20 weeks and used in a polymer degradation study. The obtained results show that the mechanical properties of PLA scaffolds do not decrease during incubation in physiological medium for a predicted new bone tissue formation period, though hydrolysis starts at the very beginning and increases with time. PLA as a material seems to be suitable for the use in bone tissue engineering as it allows to form biocompatible and biodegradable scaffolds with high mechanical strength, required for effective tissue formation.

Layered double hydroxides (LDHs) belong to a class of layered materials with a general chemical formula of [[M II 1-x M III x (OH) 2 ] x+ (A m- ) x/m ]·nH 2 O. The structure of LDH is formed by positively charged metal hydroxide layers [M II 1-x M III x (OH) 2 ] x+ and negatively charged anions (A m- ) x/m in the interlayer space. As a rule, H 2 O molecules are also present in the interlayer space. A large number of LDHs can be synthesised by varying either the nature of the cations or anions. Consequently, new materials can be obtained with specific properties. LDHs could be used as efficient adsorbents for liquid ions and gas molecules for the removal of anionic toxins (arsenate, chromate, selenite and other) and also toxic metals ions for water purification; as catalyst supports; as catalysts for oxidation, reduction and other reactions; LDHs within inorganic membranes in sensor devices; for anticorrosion protection of metal alloys; as bio-nanohybrids with ability to incorporate large molecules for drug and gens delivery, cosmetics, cancer therapy and biosensing and other. Recently, we developed indirect sol-gel synthesis methods for the fabrication of LDHs. This sol-gel chemistry approach is perfect synthesis method to fabricate substituted with transition and rare earth metals LDHs with specific properties. The Mg 2 Al 1 , Mg 2-x Zn x Al 1 and Mg 2 Al 1-x La x LDHs were successfully synthesized by a simple sol-gel synthetic approach. These results are presented and discussed in this study.