Gas chromatographic analysis of cresols in aquatic solution by solid phase microextraction

A simple and sensitive method for analysis of a mixture of cresol isomers in aquatic solution was developed using headspace solid-phase microextraction (HS-SPME) and gas chromatography with flame ionization detection (GC-FID). Separation of o-, m-and pcresols in mixture was performed on an Elite Wax column. The effect of temperature, time and sodium chloride on cresol extraction as well as the effect of temperature and time on the desorption of the compounds was established. The following conditions were revealed to be optimal: headspace extraction at 40 °C for 60 min in the presence of 0.3 g/mL of sodium chloride and desorption at 210 ºC for 60 s. Detection limits for o-cresol, m-cresol and p-cresol were established to be 0.68, 0.96 and 1.31 µg/L, respectively, when PDMS-DVB fibre was used. The relative standard deviation (RSD) of the measurements was ≤ 5.9%. The dose-response relationship was linear within the range 1.5 to 10.0 mg/L (R 2 = 0.997)

MDA-Based Approach for Blockchain Smart Contract Development

Blockchain smart contracts can support the decentralisation of business processes, but due to smart contracts’ specifics, their development is a complicated process. Introducing model-driven development principles in smart contract development can facilitate requirement specification, design, and implementation activities. This paper presents a model-driven development method MDAsmartCD (Model-Driven Architecture-based Smart Contract Development) to alleviate smart contract development by supporting the complete MDA life cycle, covering the definition of Computation-Independent Model, Platform-Independent Model, and two instances of Platform-Specific Models. In MDAsmartCD, model transformations (model-to-model and model-to-text) are used to produce smart contract code in the Hyperledger Fabric platform Go and the Ethereum platform Solidity programming languages. The method application was demonstrated by implementing the smart contract for the hackathon solution and executing the generated Solidity and Go smart contracts in the workflow of issuing certificates for hackathon participants. During the execution of the workflow, both deployed smart contracts behaved identically and recorded analogous results in respective blockchain data storages. This demonstrated that the MDAsmartCD method enables the generation of compilable and executable smart contract code, ready for deployment on a blockchain platform

MDA-Based Approach for Blockchain Smart Contract Development

Blockchain smart contracts can support the decentralisation of business processes, but due to smart contracts’ specifics, their development is a complicated process. Introducing model-driven development principles in smart contract development can facilitate requirement specification, design, and implementation activities. This paper presents a model-driven development method MDAsmartCD (Model-Driven Architecture-based Smart Contract Development) to alleviate smart contract development by supporting the complete MDA life cycle, covering the definition of Computation-Independent Model, Platform-Independent Model, and two instances of Platform-Specific Models. In MDAsmartCD, model transformations (model-to-model and model-to-text) are used to produce smart contract code in the Hyperledger Fabric platform Go and the Ethereum platform Solidity programming languages. The method application was demonstrated by implementing the smart contract for the hackathon solution and executing the generated Solidity and Go smart contracts in the workflow of issuing certificates for hackathon participants. During the execution of the workflow, both deployed smart contracts behaved identically and recorded analogous results in respective blockchain data storages. This demonstrated that the MDAsmartCD method enables the generation of compilable and executable smart contract code, ready for deployment on a blockchain platform

Composition of young and aged shoot essential oils of the wild Ledum palustre L

Wild Ledum palustre L. plants were collected near Juodupė (Rokiškis region) and Šilėnai (Vilnius region) villages. Essential oils from young and aged shoots, obtained by hydrodistillation, were analysed using GC and GC/MS. The major constituents were palustrol (31.4-42.8%), ledol (23.6-30.8%), cyclocolorenones (4.0-9.3%), myrcene (1.2-8.6%) and limonene (11.0%). The essential oil from plants growing near Šilėnai village differed from that of L. palustre near Juodupė by a higher content of compounds with the menthane carbon skeleton (10.9-18.0% and ≤1.2%, respectively) and by the content of limonene (3.7-11.0% and not detected, respectively). All essential oils included furyl containing monoterpenoids. Young shoots biosynthesized 3-4 times larger amounts of essential oils and contained larger quantities of terpenoids than did aged shoots. The content of palustrol in the essential oils of aged shoots was higher than of young ones. The dependence of ledol quantities on the age of shoots was opposite in the localities under study. The sixty nine identified compounds comprised 98.0-99.4% of L. palustre essential oils

Pandemic-induced qualitative changes in the process of university studies from the perspective of university authorities

The pandemic COVID-19 period in education has brought many challenges to all organizations. The activities of the higher educational institutions are being affected and the situation may last for a long time. Under the current circumstances, it is important to shift to distance learning through online processes and improve educational processes at all organizational levels. Institutions have to ensure successful distance or remote learning process by identifying their opportunities, meeting challenges, and establishing the sustainable quality factors for remote or distance learning. This study aimed at identifying the pandemic-induced qualitative changes in studies that have occurred at the levels of university authorities, lecturers, and students. Universities of Lithuania were taken as a case study. The novelty of the research lies in the fact that the focus of analysis is not on the negative effects of the pandemic observed in higher education studies but on finding positive qualitative changes that are also of importance to future studies. Phenomenographic qualitative research strategy was chosen in the research and 15 in-depth semi-structured interviews with experts in university studies were conducted. Seven categories were distinguished during the research representing qualitative changes in studies at three levels authorities, lecturers, and students. The discussed levels seemed to have a mutual effect on each other. The external motivation of leaders and the support and establishment of work and online study conditions encouraged both external and internal qualitative changes in studies from the perspective of lecturers as well as students. Keywords: higher education; qualitative changes; distance learning; university authorities; lecturers; students

Enterprise knowledge-based generation of class model

The article presents Knowledge- Based MDA Class Model (UML notation) generation technique. Knowledge- Based MDA approach is a progressive Information Systems development method which combines the main components of traditional MDA and the best practices of Knowledge-Based Information Systems Engineering. The main advantage of such method is that problem domain knowledge acquainted at user requirements acquisition and business modelling stages are validated against formal criteria, in such way reducing empirical factors that could negatively impact the whole IS development process. The starting point of Class model generation process is a selection of particular entity from the Enterprise Model as the main class. System Analyst is able to select one of four elements types for class model generation process: Actor, Process, Information Activity and Flow. The main steps of Class model generation from Enterprise Model are presented in this article as well as Class model generation example. The final result of the generation process is the particular Class model that specifies static structure of the particular problem domain and can be used as business entities framework for developers of Information Systems

Degradation of naphthalene by thermophilic bacteria via a pathway, through protocatechuic acid

A number of thermophilic bacteria capable of utilizing naphthalene as a sole source of carbon were isolated from a high-temperature oilfield in Lithuania. These isolates were able to utilize several other aromatic compounds, such as anthracene, benzene, phenol, benzene-1, 3-diol, protocatechuic acid as well. Thermophilic isolate G27 ascribed to Geobacillus genus was found to have a high aromatic compound degrading capacity. Spectrophotometric determination of enzyme activities in cell-free extracts revealed that the last aromatic ring fission enzyme in naphthalene biotransformation by Geobacillus sp. G27 was inducible via protocatechuate 3, 4-dioxygenase; no protocatechuate 4, 5-dioxygenase, protocatechuate 2, 3-dioxygenase activities were detected. Intermediates such as o-phthalic and protocatechuic acids detected in culture supernatant confirmed that the metabolism of naphthalene by Geobacillus sp. G27 can proceed through protocatechuic acid via ortho-cleavage pathway and thus differs from the pathways known for mesophilic bacteria

Minimalistic Approach to Coreference Resolution in Lithuanian Medical Records

Coreference resolution is a challenging part of natural language processing (NLP) with applications in machine translation, semantic search and other information retrieval, and decision support systems. Coreference resolution requires linguistic preprocessing and rich language resources for automatically identifying and resolving such expressions. Many rarer and under-resourced languages (such as Lithuanian) lack the required language resources and tools. We present a method for coreference resolution in Lithuanian language and its application for processing e-health records from a hospital reception. Our novelty is the ability to process coreferences with minimal linguistic resources, which is important in linguistic applications for rare and endangered languages. The experimental results show that coreference resolution is applicable to the development of NLP-powered online healthcare services in Lithuania