SOME ASPECTS OF THE INFLUENCE OF URANIUM EXPLOITATION ON THE ENVIRONMENT

Gamma-ray spectrometric measurements of samples of riverbed sediments and soil samples taken along the valley of a river, which runs very close to a uranium mine retaining dam are performed. The content of 238U, 226Ra, 210 Pb, 232Th, and 40K is analyzed. Up to a distance of about 6 km away from the retaining dam, 238U, 226Ra and 210Pb have high concentrations and the content in the sediments samples is consistently higher than the content in the soil samples. In the same interval are observed considerable fluctuations in the contents related to the swamping of the river. Receding at a greater distance from the retaining dam, the concentration of 238U, 226Ra and 210Pb decreases and has values close to the average ones. A very close correlation is established between the contents of the three radioactive nuclides. Regarding 232Th and 40K, the distribution characteristics along the profile are different in comparison with those of the 238U family members. The performed research contributes to the estimate of the radioactive contamination in a specific area situated in the vicinity of a uranium deposit exploited through underground mining

Permeation of organometallic compounds through phspholipid membranes

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Modelling of pedagogical patterns through e-learning objects

Програмні платформи для електронного навчання підтримують різні варіанти подання навчального контенту. Одним із способів для його організації та структурування є так звані педагогічні моделі. Вони є методом для відображення і розповсюдження отриманих знань та практичного досвіду. Педагогічні моделі використовуються для опису педагогічних ситуацій, які неодноразово виникають під час навчання. У контексті систем електронного навчання існують різні підходи до цифровізації педагогічних моделей. Мета роботи – показати, як побудувати педагогічні моделі, використовуючи педагогічні об’єкти електронного навчання, які можна легко та зручно впровадити як моделі в адаптивному середовищі електронного навчання. Педагогічний об’єкт електронного навчання – це абстрактне поняття, яке може бути представлено в конкретній формі об’єкта електронного навчання, методичного об’єкта електронного навчання, об’єкта електронного навчання для моніторингу та діагностики чи об’єкта електронного навчання з результатами навчання. Ці об'єкти є базовими блоками для побудови педагогічних моделей. У даній роботі детально розглянуто питання створення педагогічних моделей з використанням чотирьох типів педагогічних об’єктів електронного навчання. Представлений приклад педагогічної моделі призначений для досягнення певних освітніх цілей. Приклади моделей, створених з використанням певних об’єктів електронного навчання, представляють навчальні блоки, які використовуються залежно від контексту певної педагогічної ситуації. Педагогічні об’єкти електронного навчання та педагогічні моделі, призначені для їх застосування як засоби навчання в адаптивному середовищі електронного навчання, застосовуються в Moodle LMS відповідно до тенденції програмного забезпечення з метою допомоги викладачу або заміни деяких його функцій, а роль викладача піднімається на більш високий організаційний, педагогічний та методичний рівень. За допомогою педагогічних об’єктів електронного навчання створено три приклади педагогічних моделей: «Ранній зворотний зв’язок», «Сендвіч - метод зворотного зв’язку» та «Послідовна метафора» в LMS Moodle, які були апробовані в навчальному курсі «Моделювання навчальних курсів у Moodle» під час осіннього триместру 2021/2022 навчального року на факультеті математики та інформатики Пловдивського університету “Паїсій Хілендарський”, Болгарія.Software platforms for e-learning support various options for presenting educational content. One of the ways to organize and structure it is via so-called pedagogical patterns. They are a method for describing and sharing knowledge and practical experience. Pedagogical patterns are used to describe pedagogical situations that occur repeatedly in the learning process. In the context of e-learning systems, there are various approaches to digitalization of pedagogical patterns. The purpose of the paper is to show how to build instances of pedagogical patterns using e-learning pedagogical objects, which can be easily and conveniently used as models in an adaptive e-learning environment. An e-learning pedagogical object is an abstract concept that can be presented in the concrete form of an e-learning object, an e-learning methodological object, an e-learning object for monitoring and diagnostics or an e-learning object with learning outcomes. These objects are building blocks for constructing instances of pedagogical patterns. This paper thoroughly discusses the issue of creating instances of pedagogical patterns of the four types of e-learning pedagogical objects. The instance of a pedagogical pattern is meant to serve to create subsections of educational topics. The instances of the patterns built of e-learning objects are learning units that are used depending on the context of a particular pedagogical situation. The e-learning pedagogical objects and the pedagogical pattern instances are intended to be applied in an adaptive e-learning environment as teaching aids. Their theoretical models are applied in Moodle LMS in line with the tendency for software to assist and replace some of the teacher functions, while the teacher’s role is raised to a higher organizational, pedagogical and methodological level. Three instances of pedagogical patterns have been created through e-learning pedagogical objects: “Early Feedback”, “Feedback Sandwich” and “Consistent Metaphor” in LMS Moodle, which have been tested in the training course “Modeling of training courses in Moodle” during the autumn trimester of the academic year 2021/2022 at the Faculty of Mathematics and Informatics of Paisii Hilendarski University of Plovdiv, Bulgaria

Predicting Isoform-Selective Carbonic Anhydrase Inhibitors via Machine Learning and Rationalizing Structural Features Important for Selectivity

Carbonic anhydrases (CAs) catalyze the physiological hydration of carbon dioxide and are among the most intensely studied pharmaceutical target enzymes. A hallmark of CA inhibition is the complexation of the catalytic zinc cation in the active site. Human (h) CA isoforms belonging to different families are implicated in a wide range of diseases and of very high interest for therapeutic intervention. Given the conserved catalytic mechanisms and high similarity of many hCA isoforms, a major challenge for CA-based therapy is achieving inhibitor selectivity for hCA isoforms that are associated with specific pathologies over other widely distributed isoforms such as hCA I or hCA II that are of critical relevance for the integrity of many physiological processes. To address this challenge, we have attempted to predict compounds that are selective for isoform hCA IX, which is a tumor-associated protein and implicated in metastasis, over hCA II on the basis of a carefully curated data set of selective and nonselective inhibitors. Machine learning achieved surprisingly high accuracy in predicting hCA IX-selective inhibitors. The results were further investigated, and compound features determining successful predictions were identified. These features were then studied on the basis of X-ray structures of hCA isoform-inhibitor complexes and found to include substructures that explain compound selectivity. Our findings lend credence to selectivity predictions and indicate that the machine learning models derived herein have considerable potential to aid in the identification of new hCA IX-selective compounds

Workflows in Dynamic Software Systems

Business software systems and applications use business process management concepts to organize and automate processes. Incorporating a business process management system in existing business applications is a pretty complex task and, as well, is very expensive in terms of time and human resources. The article presents a newly conceived Framework for Dynamic Business Applications - a software platform that allows business users (domain experts) to defne at run time all business objects that they will work with, their properties, relationships, and restrictions of their business/domain model. This is very similar to what can be done with business ontologies regarding representation of entities, ideas, and events, along with their properties and relations. After defning them, business users can use them to populate data in the application and later apply this data for data extraction, analysis, visualization, and reporting. ACM Computing Classifiation Sstem (1998): D.2.2, D.4.1, H.4.1

People of TM: Video Data Science Academy Fellows

The video will be used for an external social media engagement campaign on platforms like you-tube, linked-in, facebook etc. featruing stories of people in TM. No IP related content

Identifying Promiscuous Compounds with Activity against Different Target Classes

Compounds with multitarget activity are of high interest for polypharmacological drug discovery. Such promiscuous compounds might be active against closely related target proteins from the same family or against distantly related or unrelated targets. Compounds with activity against distinct targets are not only of interest for polypharmacology but also to better understand how small molecules might form specific interactions in different binding site environments. We have aimed to identify compounds with activity against drug targets from different classes. To these ends, a systematic analysis of public biological screening data was carried out. Care was taken to exclude compounds from further consideration that were prone to experimental artifacts and false positive activity readouts. Extensively assayed compounds were identified and found to contain molecules that were consistently inactive in all assays, active against a single target, or promiscuous. The latter included more than 1000 compounds that were active against 10 or more targets from different classes. These multiclass ligands were further analyzed and exemplary compounds were found in X-ray structures of complexes with distinct targets. Our collection of multiclass ligands should be of interest for pharmaceutical applications and further exploration of binding characteristics at the molecular level. Therefore, these highly promiscuous compounds are made publicly available