Specific Nature of Spatial Awareness Formation of the Bachelor of Technical Higher Education Institution of Ukraine During the Basic Course

A formed spatial awareness is one of the main professionally important quality of a young professional, a graduate of Technical and Vocational Education and Training (TVET) and higher technical education institutions. The carried out analysis of graphical preparation in the process of school studying has allowed to ascertain that enrollees of basic technical specialties are prepared not at sufficient level, the spatial awareness is formed at a low level. The shortlisting of future students on the ground of the availability of elementary spatial awareness is not conducted. The formation of spatial awareness of students during the basic course in higher technical education institutions of Ukraine is rested exclusively on instructors. As a result of the literature sources and normative documentation analysis, we have developed a structural-stage model of the process of spatial awareness formation of a bachelor of higher technical education institutions which includes the initial, basic and professional stages. There were defined problems in the first stage of training at the level of basic knowledge of the spatial awareness, and was suggested to begin studying with consideration and solving of problems on the plane with the subsequent transfer of the solution to the spatial model. The transfer to the inverse process can be accomplished only after full understanding of the interrelation of the carried out geometric actions and learning the techniques and methods of solving metric and positional problems with two and three-dimensional figures. A logframe of classes conduction and measures for its realization have been developed. Carried out experimental investigations in regards to application of the specified approach in the training process have made it possible to increase the level of formation of the basic level of spatial awareness at the beginning of training

Perfectionism in the anesthesiological environment

Background Perfectionism today is understood as an individual’s psychological conviction that the ideal can and should be achieved, and the imperfect result of work (physical, intellectual, etc.), in their opinion, has no right to exist. The purpose of the study Our goal was to investigate levels and types of perfectionism among anesthesiology interns in comparison with the indicators of practicing anesthesiologists. Materials and methods An anonymous survey of 92 anesthesiology interns and 124 practicing anesthesiologists was conducted according to the Big-Three Perfectionism Scale (BTPS). Results The mean general level of perfectionism was average, with the total BTPS score of 124,38 ± 14,47 out of 225 in interns and 105,97 ± 10,31 in practicing anesthesiologists (p < 0,05). Both interns and practicing doctors leaned toward rigid perfectionism (mean score 32,32 ± 3,32 out of 50 in interns and 33,33 ± 3,23—in practicing doctors, p < 0,05) and self-critical perfectionism, with the average score of 52,08 ± 4,37 out of 90 in interns and 42,87 ± 4,76 in postgraduates (p < 0,05). Narcissistic perfectionism is the factor with the least relative score in both groups (39,99 ± 7,61 out of 85 in interns and 29,77 ± 4,20 in practicing doctors, p < 0,05). Conclusions Neither anesthesiology interns nor practicing anesthesiologists in general exhibited high levels of perfectionism. In both groups there was a moderate leaning towards rigid and self-critical perfectionism, which indicates a tendency for the individuals to set high standards for themselves and base their own self-worth on meeting these standards. In interns, the general perfectionism levels were significantly higher than in practicing doctors. Also the selfcritical type was more prominent among interns. This might indicate a sense of pressure to meet unrealistic outside expectations and an impostor syndrome which is common for the people at the start of their careers, but it’s also a significant risk factor for future burnout

Evaluation of seven European aerosol optical depth retrieval algorithms for climate analysis

Satellite data are increasingly used to provide observation-based estimates of the effects of aerosols on climate. The Aerosol-cci project, part of the European Space Agency's Climate Change Initiative (CCI), was designed to provide essential climate variables for aerosols from satellite data. Eight algorithms, developed for the retrieval of aerosol properties using data from AATSR (4), MERIS (3) and POLDER, were evaluated to determine their suitability for climate studies. The primary result from each of these algorithms is the aerosol optical depth (AOD) at several wavelengths, together with the Ångström exponent (AE) which describes the spectral variation of the AOD for a given wavelength pair. Other aerosol parameters which are possibly retrieved from satellite observations are not considered in this paper. The AOD and AE (AE only for Level 2) were evaluated against independent collocated observations from the ground-based AERONET sun photometer network and against “reference” satellite data provided by MODIS and MISR. Tools used for the evaluation were developed for daily products as produced by the retrieval with a spatial resolution of 10 × 10 km2 (Level 2) and daily or monthly aggregates (Level 3). These tools include statistics for L2 and L3 products compared with AERONET, as well as scoring based on spatial and temporal correlations. In this paper we describe their use in a round robin (RR) evaluation of four months of data, one month for each season in 2008. The amount of data was restricted to only four months because of the large effort made to improve the algorithms, and to evaluate the improvement and current status, before larger data sets will be processed. Evaluation criteria are discussed. Results presented show the current status of the European aerosol algorithms in comparison to both AERONET and MODIS and MISR data. The comparison leads to a preliminary conclusion that the scores are similar, including those for the references, but the coverage of AATSR needs to be enhanced and further improvements are possible for most algorithms. None of the algorithms, including the references, outperforms all others everywhere. AATSR data can be used for the retrieval of AOD and AE over land and ocean. PARASOL and one of the MERIS algorithms have been evaluated over ocean only and both algorithms provide good results

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

An update on the synergetic aerosol retrieval

At DLR-DFD a synergetic aerosol retrieval method SYNAER was developed (Holzer-Popp et al., JGR, 107, 2002), which exploits the complementary information content of the radiometer AATSR and the spectrometer SCIAMACHY, both onboard ENVISAT. This combination of two instruments allows to retrieve aerosol optical depth at 550 nm and aerosol speciation from a choice of pre-defined aerosol types. In the meantime, 3 years of ENVISAT AATSR and SCIAMACHY level 1 nadir data have been acquired (2003-2005). Processing of these data over the MSG field of view (Europe, Africa, Atlantic) has been started within the ESA GSE project PROMOTE, where SYNAER contributes to the air quality monitoring service. SYNAER products are provided daily in near-real time since June 2005 as input for data assimilation into chemistry transport models, and as long-term evolving archive. Furthermore, first examples of converting SYNAER AOD and aerosol type into near-surface particulate matter concentrations and assimilation into the EURAD chemistry-transport model to improve the treatment of episodic emission patterns have been achieved. Validation of these SYNAER results is an ongoing activity. The validation efforts so far showed the potential to estimate the aerosol type from space (AOD error around 0.1 from UV to NIR, which is in perfect match with the expected noise level for the exploited pixel size), but also revealed cases of large AOD errors. Suspected reasons for these are surfaces with higher albedo and cases, where the sun-photometer observation is not representative for the satellite pixel of 60x30km2. Several parts of the retrieval methodology have therefore been assessed in more detail to better understand these issues. This includes a stringent analysis of the information content for different surface-atmosphere conditions and illuminations (up to 3 degrees of freedom for the type of aerosol). Furthermore, an investigation of airborne surface spectra was conducted to improve the dark field treatment based on characterizing the 670nm surface albedo from 1.6 micron channel reflectance and vegetation index. Preliminary results of this refinement effort will be summarized and discussed. The mid-term perspective for the SYNAER products promises a long-term dataset ranging from 1995 with ERS-2 (ATSR-2 and GOME) to 2020 with METOP (AVHRR and GOME-2), as the algorithm development was always focused on applicability to all these 3 platforms (thus not using special features as e.g. SCIAMACHY mid infrared channels or ATSR dual view). This presentation summarizes the status of the activity ―Derivation of aerosol composition from space‖ as a contribution to subproject ACCENT-TROPOSAT-2 (AT2), Task Group 1 (and 2)

Satellite based mapping of Particulate Matter

Satellite based mapping of Particulate Matter was presented. Satellite retrieved aerosol optical depth products from SYNAER and MODIS were used to derive air quality over Germany and Europe. This work was done within the EU-Project myAir Pasodoble

Assimilation of satellite-based aerosol measurements in a chemical transport model using aerosol component information

Aerosol monitoring is of growing interest due to the impact of aerosol particle concentration on human health and the global climate. The key question of this paper is how the assimilation of satellite atmospheric aerosol observations improves the capability of a chemical transport model in reproducing the distribution of tropospheric particles. The study is carried out using the Model for Atmospheric Transport and Chemistry (MATCH). As measurement input vector for the assimilation procedure satellite data from GOME-2 and AVHRR instruments onboard MetOp was used. Synergetic Aerosol Retrieval (SYNAER) observational and model (MATCH) data can be coupled by means of data assimilation. MetOp-SYNAER measurements are able to distinguish between different aerosol components such as water-soluble, soot, sea salt and long-range transported mineral aerosols. Therefore, a component-wise assimilation approach is under development. During the assimilation procedure, the final analysis is highly dependent on the specification of the relative weights to both model and satellite source of information through the error covariance matrices. Since observation and background error covariance matrices are not perfectly known, a large potential for improvements of the analyses is offered by methods allowing their constructing and tuning. In this study, the method proposed by Desroziers and Ivanov (2001) is used to tune background and observational error statistics of the 3D-Var assimilation procedure. The assimilation system with improved background and observation error covariance matrices was tested for the period of 1 month in 2007. It can be clearly stated, that making use of component resolving satellite-based aerosol optical depth measurements leads to a significant improvement in aerosol forecast quality

Sensitivity analysis of synergetic aerosol retrieval and its application in assimilation procedure

Aerosol monitoring is of growing interest due to the impact of aerosol particle concentration on human health and the global climate. Air quality models as the EURopean Air pollution Dispersion model EURAD of the Rhenish Institute for Environmental Research (RIU) at the University of Cologne offer a continuous and operational monitoring and forecasting of the aerosol load in sufficient temporal and spatial resolution. But they fail in case of episodic emissions which are not covered by the underlying emission data bases used to describe aerosol sources. Satellite-based measurements available from ENVISAT offer global measurements over land and ocean as provided by the ESA GSE PROMOTE using the SYNAER method. Model and observational information can be coupled by means of data assimilation. ENVISAT-SYNAER measurements are able to distinguish between different aerosol components as sulphate/nitrate, soot, water insoluble erosion-based or industrial particles, sea salt and long-range transported mineral aerosols. Therefore, a component-wise assimilation approach is under development. During the assimilation procedure, the final analysis is highly dependent on the specification of the relative weights to each source of information through the error covariance matrices. The observation error covariance matrix is not perfectly known, so a large potential for improvements of the analyses is offered by methods allowing its tuning. The focus of the work is applying information theory for an analysis of the information content properties of the SYNAER method and its application for tuning of observation error variances in an assimilation algorithm for SYNAER data

Порівняння рішень задачі ранньої ідентифікації конфігураційних елементів ІТ-продукта методами ієархічної кластеризації

The object of this study is the IT project configuration management process. During the research, the problem of early identification of configuration items (CI) in the information system (IS) of enterprise management was solved. Research in this field is mainly aimed at solving the task of early identification of services and microservices during the refactoring of software systems. The issue of the application of artificial intelligence methods for the detection of CI has not been sufficiently investigated. During the study, the Chameleon hierarchical clustering method was adapted to solve the problem of early identification of CI IS. This method takes into account both the internal similarity and the connectivity of individual functions of the studied IS. The adapted Chameleon method was used when solving the task of early identification of CI in the functional task "Formation and maintenance of an individual plan of a scientific and pedagogical employee of the department". 10 functions and 12 essences of the problem database were considered as the initial CIs. The result of the solution is a dendrogram with all possible options for decomposition of the description of the task architecture into individual CIs. Based on the results, a comparative analysis of the use of Chameleon, DIANA, and AGNES methods for solving the problem of early identification was carried out. According to the criteria "Number of vertices of the dendrogram", "Number of levels of decomposition of the dendrogram", and "Evenness of filling the elements of the dendrogram", the results from using the Chameleon method are the best. Using the research results allows automating the procedure of forming backlogs of IT project implementation teams. This makes it possible to improve the quality of IS development by assigning IS containing similar functions to the same IT project executorОб’єкт дослідження – процес управління конфігурацією ІТ-проєкту. Під час дослідження вирішувалася проблема ранньої ідентифікації конфігураційних елементів (СІ) інформаційної системи (ІС) управління підприємством. Дослідження в цій галузі спрямовані, в основному, на вирішення задачі ранньої ідентифікації сервісів та мікросервісів під час рефакторингу програмних систем. Питання застосування методів штучного інтелекту для виявлення СІ досліджені недостатньо. Під час дослідження метод ієрархічної кластеризації Chameleon було адаптовано для вирішення задачі ранньої ідентифікації СІ ІС. Даний метод враховує як внутрішню схожість, так і зв’язність окремих функцій досліджуваної ІС. Адаптований метод Chameleon було використано під час вирішення задачі ранньої ідентифікації СІ функціональної задачі «Формування і ведення індивідуального плану науково-педагогічного працівника кафедри». Як вихідні CI було розглянуто 10 функцій та 12 сутей бази даних задачі. Результатом рішення є дендрограма з усіма можливими варіантами декомпозиції опису архітектури задачі на окремі CI. На основі отриманих результатів проведено порівняльний аналіз використання методів Chameleon, DIANA та AGNES для вирішення задачі ранньої ідентифікації. За критеріями «Кількість вершин дендрограми», «Кількість рівнів декомпозиції дендрограми» та «Рівномірність заповнення елементів дендрограми» найкращими є результати використання методу Chameleon. Використання отриманих результатів дослідження дозволяє автоматизувати процедуру формування беклогів команд виконавців ІТ-проєкту створення ІС. Це дозволяє підвищити якість розробки ІС за рахунок призначення СІ, що містить схожі функції, одному й тому ж виконавцю ІТ-проєкт