46 research outputs found
Leisure of family as a pedagogical problem
Full text linkThe pedagogical value of family leisure forms is that they actively involve and intensively use various communication mechanisms: family - children, family - family, children - children, children - teenagers - adults. The simultaneity of these contacts gives the family leisure emotional appeal, sincerity, warmth. Intra-family leisure relationships are already in themselves rehabilitative function, actively influencing the creation of a favorable psychological climate in the family.Педагогическая ценность семейных досуговых форм состоит в том, что в них активно включены и интенсивно задействованы различные механизмы общения: семья - дети, семья - семья, дети - дети, дети - подростки - взрослые. Одновременность этих контактов придает семейному досугу эмоциональную привлекательность, душевность, теплоту. Внутрисемейные досуговые отношения уже сами по себе несут реабилитирующую функцию, активно воздействуют на создание благоприятного психологического климата в семье
Technological aspects of the organization of sports work in preschool educational institutions
Full text linkThe article presents the results of the analysis of morbidity of preschool children and provides practical recommendations for the organization and implementation of work in preschool educational institutions, taking into account the health of students.В статье представлены результаты анализа заболеваемости детей дошкольного возраста и даны практические рекомендации по организации и осуществлению работы в дошкольных образовательных учреждениях с учетом здоровья занимающихся
Factors that promote or inhibit the implementation of e-health systems: an explanatory systematic review
Get PDFOBJECTIVE: To systematically review the literature on the implementation of e-health to identify: (i) barriers and facilitators to e-health implementation, and (ii) outstanding gaps in research on the subject.METHODS: MEDLINE, EMBASE, CINAHL, PSYCINFO and the Cochrane Library were searched for reviews published between 1 January 1995 and 17 March 2009. Studies had to be systematic reviews, narrative reviews, qualitative metasyntheses or meta-ethnographies of e-health implementation. Abstracts and papers were double screened and data were extracted on country of origin; e-health domain; publication date; aims and methods; databases searched; inclusion and exclusion criteria and number of papers included. Data were analysed qualitatively using normalization process theory as an explanatory coding framework.FINDINGS: Inclusion criteria were met by 37 papers; 20 had been published between 1995 and 2007 and 17 between 2008 and 2009. Methodological quality was poor: 19 papers did not specify the inclusion and exclusion criteria and 13 did not indicate the precise number of articles screened. The use of normalization process theory as a conceptual framework revealed that relatively little attention was paid to: (i) work directed at making sense of e-health systems, specifying their purposes and benefits, establishing their value to users and planning their implementation; (ii) factors promoting or inhibiting engagement and participation; (iii) effects on roles and responsibilities; (iv) risk management, and (v) ways in which implementation processes might be reconfigured by user-produced knowledge.CONCLUSION: The published literature focused on organizational issues, neglecting the wider social framework that must be considered when introducing new technologies.<br/
The Incidence Of Prescribing Errors In An Eye Hospital
Get PDFBACKGROUND: Relatively little is known about the incidence of prescribing errors and there has been no work on this in a single specialty ophthalmic hospital. Knowing where and when errors are most likely to occur is generally felt to be the first step in trying to prevent these errors. This study is an attempt in, the setting of an eye hospital, to try to identify and attribute these medication errors. METHODS: The study setting was a single specialty eye hospital geographically separated from the main general hospital. Pharmacists prospectively recorded the number of errors of prescribing during a 4 week period at an eye hospital in UK. The errors were categorised as error of prescription writing or drug error. Potential significance of the errors was not addressed. RESULTS: Overall 144/1952 (8%)prescription sheets had errors. 7% of the total errors were errors of prescription writing while 1% were drug errors. The majority of errors were made by junior doctors and no drug errors were made by senior doctors. The outpatients department had by far the highest prevalence of errors. CONCLUSION: Certain areas within the hospital and certain grades of staff are more prone to drug errors. Further study is required to look at the reasons why this is so and what systems can be put in place to reduce these errors
Impact of computerized physician order entry (CPOE) system on the outcome of critically ill adult patients: a before-after study
Get PDF<p>Abstract</p> <p>Background</p> <p>Computerized physician order entry (CPOE) systems are recommended to improve patient safety and outcomes. However, their effectiveness has been questioned. Our objective was to evaluate the impact of CPOE implementation on the outcome of critically ill patients.</p> <p>Methods</p> <p>This was an observational before-after study carried out in a 21-bed medical and surgical intensive care unit (ICU) of a tertiary care center. It included all patients admitted to the ICU in the 24 months pre- and 12 months post-CPOE (Misys<sup>®</sup>) implementation. Data were extracted from a prospectively collected ICU database and included: demographics, Acute Physiology and Chronic Health Evaluation (APACHE) II score, admission diagnosis and comorbid conditions. Outcomes compared in different pre- and post-CPOE periods included: ICU and hospital mortality, duration of mechanical ventilation, and ICU and hospital length of stay. These outcomes were also compared in selected high risk subgroups of patients (age 12-17 years, traumatic brain injury, admission diagnosis of sepsis and admission APACHE II > 23). Multivariate analysis was used to adjust for imbalances in baseline characteristics and selected clinically relevant variables.</p> <p>Results</p> <p>There were 1638 and 898 patients admitted to the ICU in the specified pre- and post-CPOE periods, respectively (age = 52 ± 22 vs. 52 ± 21 years, p = 0.74; APACHE II = 24 ± 9 vs. 24 ± 10, p = 0.83). During these periods, there were no differences in ICU (adjusted odds ratio (aOR) 0.98, 95% confidence interval [CI] 0.7-1.3) and in hospital mortality (aOR 1.00, 95% CI 0.8-1.3). CPOE implementation was associated with similar duration of mechanical ventilation and of stay in the ICU and hospital. There was no increased mortality or stay in the high risk subgroups after CPOE implementation.</p> <p>Conclusions</p> <p>The implementation of CPOE in an adult medical surgical ICU resulted in no improvement in patient outcomes in the immediate phase and up to 12 months after implementation.</p
Basic ICT adoption and use by general practitioners: an analysis of primary care systems in 31 European countries
Full text linkThematic Modelling of News Archive from University Website
No full textThis dataset contains a set of files to suuport and illustrate successive steps of thematic modeling for news line’s text docs and data for further investigations.The file "etalon export_file.csv" presents 2000 Russian language news records, which is a part of the archive of the university website sstu.ru. Each record has a numerical record identifier, head of news, and URL-code of news.The excel-file "News_tokens.xlsx" contains information about extracted tokens for news records after text processing. Text processing included tag eliminating, text cleaning, and word stemming as usual. The file column values are: "Record number", "Identifier of news", Head of news", "Number of words in the news", "Number of unique tokens in news", and "List of news tokens".Then, thematic modeling was done for news in a Vowpal Wabbit format based on the probabilistic distribution of keywords in the text. The results of thematic modeling via the BigARTM platform (https://github.com/bigartm/bigartm, doi:10.5281/zenodo.288960) are presented in the files "phi_matrix.xlsx" and "theta_matrix.xlsx". After a series of experiments six topics were identified. Each of the 2000 lines in the "Theta_matrix" defines the probability of relevant news documents belonging to six topics. In the "Phi_matrix" we see the topic's probabilities for tokens. Under consideration of most frequent tokens (keywords) for each topic, the names for the topics were formulated as follows: "Events", "Holidays", "Science and Innovations", "Educational and Scientific Activities", "Student Competitions", '"Admission Campaign".To determine the most significant topics for news, the probability values in "Theta_matrix" greater than some specially calculated bound were rounded to 1, i.e., the defuzzification of news distribution had been done. The Venn diagram on the picture in file "Venn_diagram.png" illustrates the belonging of news docs to the topics. The multiple sets visualization was performed using the "supervenn" package (https://github.com/gecko984/supervenn/tree/v0.3.1, doi:10.5281/zenodo.4016732).Thus, the dataset of Newsline's docs can be used for educational purposes and science research in text processing, machine learning fields.The full archive of news for 2009-2021 years, scrambled from the site www.sstu.ru, is in the file “News_Articles.csv”.The source of new data was the archive of news articles of the Saratov State University (SSU) from April 2007 to May 2022. The primary data file was formed as a result of the web scrapping of the newsline of the SSU website from the start page www.sgu.ru/news/all. Then, duplicate records, as well as records with empty fields were removed, and text processing had been processed. As a result, the excel file "News_SGU_31077_Processed_1.xlsx" of 31077 records was formed.The presented dataset can use for data modeling, as well as in sociological science investigations
Thematic Modelling of News Archive from University Website
No full textThis dataset contains a set of files illustrating successive steps of thematic modeling for newsline’s text docs.The basic file "etalon export_file.csv" is a part of the archive of the university website sstu.ru and presents 2000 Russian language news records about the university's life events in 2010-2014 years.Each record of the file has fields: numerical record identifier, head of news, and code of news in HTML format.The excel-file "News_tokens.xlsx" contains information about extracting tokens for news records after text processing. Text processing included as usual tag eliminating, text cleaning, and word stemming. The file column values are: "Record number", "Identifier of news", "Head of news", "Number of words in the news", "Number of unique tokens in news", and "List of news tokens".Then, thematic modeling, based on probabilistic distribution of keywords in the text, was done for news in a Vowpal Wabbit format. The results of thematic modeling via the BigARTM platform (https://github.com/bigartm/bigartm, doi:10.5281/zenodo.288960) are present in the files "phi_matrix.xlsx" and "theta_matrix.xlsx". After a series of experiments, six topics were identified. Each of the 2000 lines in the "Theta_matrix" corresponds to a news document and defines the probabilities of belonging to six topics. In the "Phi_matrix" we see the topic's probabilities for tokens. Under consideration of most frequent tokens (keywords) for each topic, the topic’s names were formulated as follows: "Events", "Holidays", "Science and Innovations", "Educational and Scientific Activities", "Student Competitions", '"Admission Campaign".To determine the most significant topics for news, the probability values in "Theta_matrix" greater than some specially calculated bound were rounded to 1, i.e., the defuzzification of news distribution had been done. The Venn diagram on the picture in file "Venn_diagram.png" illustrates a belonging of news docs to the topics. The multiple sets visualization was performed using the "supervenn" package (https://github.com/gecko984/supervenn/tree/v0.3.1, doi:10.5281/zenodo.4016732).Thus, the dataset of newsline's docs can be used for educational purposes and science research in text processing and machine learning fields.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV
Thematic Modelling of News Archive from University Website
No full textThis dataset contains a set of files to suuport and illustrate successive steps of thematic modeling for news line’s text docs and data for further investigations.The file "etalon export_file.csv" presents 2000 Russian language news records, which is a part of the archive of the university website sstu.ru. Each record has a numerical record identifier, head of news, and URL-code of news.The excel-file "News_tokens.xlsx" contains information about extracted tokens for news records after text processing. Text processing included tag eliminating, text cleaning, and word stemming as usual. The file column values are: "Record number", "Identifier of news", Head of news", "Number of words in the news", "Number of unique tokens in news", and "List of news tokens".Then, thematic modeling was done for news in a Vowpal Wabbit format based on the probabilistic distribution of keywords in the text. The results of thematic modeling via the BigARTM platform (https://github.com/bigartm/bigartm, doi:10.5281/zenodo.288960) are presented in the files "phi_matrix.xlsx" and "theta_matrix.xlsx". After a series of experiments six topics were identified. Each of the 2000 lines in the "Theta_matrix" defines the probability of relevant news documents belonging to six topics. In the "Phi_matrix" we see the topic's probabilities for tokens. Under consideration of most frequent tokens (keywords) for each topic, the names for the topics were formulated as follows: "Events", "Holidays", "Science and Innovations", "Educational and Scientific Activities", "Student Competitions", '"Admission Campaign".To determine the most significant topics for news, the probability values in "Theta_matrix" greater than some specially calculated bound were rounded to 1, i.e., the defuzzification of news distribution had been done. The Venn diagram on the picture in file "Venn_diagram.png" illustrates the belonging of news docs to the topics. The multiple sets visualization was performed using the "supervenn" package (https://github.com/gecko984/supervenn/tree/v0.3.1, doi:10.5281/zenodo.4016732).Thus, the dataset of Newsline's docs can be used for educational purposes and science research in text processing, machine learning fields.The full archive of news for 2009-2021 years, scrambled from the site www.sstu.ru, is in the file “News_Articles.csv”.The source of new data was the archive of news articles of the Saratov State University (SSU) from April 2007 to May 2022. The primary data file was formed as a result of the web scrapping of the newsline of the SSU website from the start page www.sgu.ru/news/all. Then, duplicate records, as well as records with empty fields were removed, and text processing had been processed. As a result, the excel file "News_SGU_31077_Processed_1.xlsx" of 31077 records was formed.The presented dataset can use for data modeling, as well as in sociological science investigations.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV
Enhance the efficiency of the internal threads cutting process with taps by applying ultrasonic vibrations
No full textThe paper considers a technological process of an advanced method of cutting internal threads using ultrasonic vibrations. A special ultrasonic device is shown, which makes it possible to realize this method of ultrasonic processing. The paper also presents research findings of ultrasonic vibrations influence on the process of cutting internal threads
