26 research outputs found
ЗАСТОСУВАННЯ ТЕОРІЇ РАДІОЄМНОСТІ СЕРЕДОВИЩА ДЛЯ ОЦІНКИ МІГРАЦІЇ ВАЖКИХ МЕТАЛІВ В ЕКОСИСТЕМІ
The article describes the usage of the theory of the environment capacity for assessment of heavy metals migration in ecosystem. Possibility of adaptation of the ecosystem boxes model for investigation of heavy metals migration in biotic and abiotic components of ecosystem based on radionuclide 114Cd usage as tracer, which is radioactive analog of heavy metal Cd is demonstrated. Using of indicator - factor of the environment capacity on artificial tracer - 114Cd for the assessment of the system holding ability, which is under technogenic loading caused by heavy metals, is demonstratedВ работе обосновано применение теории емкости среды для оценки миграции тяжелых металлов в экосистеме. Показана возможность адаптации камерной модели экосистемы для исследования миграции тяжелых металлов в абиотических и биотических компонентах экосистемы на основе использования в качестве трассера радионуклида 114Cd, который является радиоактивным аналогом тяжелого металла Cd. Показано использование показателя – фактора емкости среды по искусственному трассеру – 114Cd для оценки удерживающей способности экосистемы, которая испытывает техногенной нагрузки тяжелыми металлами.У роботі обгрунтовано застосування теорії ємності середовища для оцінки міграції важких металів в екосистемі. Показано можливість адаптації камерної моделі екосистеми для дослідження міграції важких металів у абіотичних та біотичних компонентах екосистеми на основі використання в якості трасеру радіонукліду 114Cd, який є радіоактивним аналогом важкого металу Cd. Показано використання показника – фактору ємності середовища по штучному трасеру – 114Cd для оцінки утримуючої здатності екосистеми, яка зазнає техногенного навантаження важкими металам
Early PCD events in male gametophyte development of isopropyl-N-phenyl carbamate resistant Nicotiana sylvestris mutant lines
Indicators of the cell-mediated immunity in surgical patients with gastroduodenal ulcers complicated by bleeding
The aim: To determine the peculiarities of indicators dynamic of cellular level of immunity in patients with gastroduodenal ulcer complicated by bleeding and microbial
contamination the periulcerous area.
Materials and methods: 80 patients with gastroduodenal ulcers complicated by bleeding were studied. Among patients in the main group, 18 (22.5%) cases were patients with
bleeding gastric ulcer, 56 (70%) patients with bleeding ulcer of duodenum. The study of cellular immunity are B - CD19, Natural killers(NK) - CD16, T-helpers - CD4, T-regulatory - CD8.
Results: An active bleeding according to the Forrest classification in patients with gastric ulcer 81.7% and in patients with ulcer of the duodenum 88.3%. Depending on the
endoscopic hemostasis, there was a marked decrease in T-lymphocyte indices with CD4 growth to the reference rates in cases of active bleeding (from 13±2.4% to 26.4±1.2%
p<0.05) and in hemostasis with high recurrence rate from 20.8±2.3% to 31.3±2.9% and from 22.6±1.3% to 39.8±2.9% p<0.05, respectively.
Conclusions: The study found a decrease in CD16 from 3.6±1.1% to 2.6±1.1% (p<0.05) and an increase in the level of CD4, CD8, CD19 to 37.4±1.1%, 4.4±1.1% (p<0.05) and
30.8±1.2% (p<0.05), respectively, indicating that there is a decrease in the immune response in patients with gastroduodenal bleeding of ulcerative genesis.
In patients with microbial contamination of the periulcerous area by Streptococcus β-haemoliticus (107 CFU) and Klebsiella pneumoniae (106 CFU), gastric ulcers decreased the
level of CD8 population from 7.3±2.1% to 7.3±2.1% to 6.4±7% (p<0.05) and from 5.8±2.8% to 4.1±2.3% (p<0.05), respectively, which may create favorable conditions for
the development of recurrent bleeding
Prophylaxis of thrombo-haemorrhagic complications in surgical treatment of multi-drug-resistant pulmonary tuberculosis
Проведено аналіз профілактики тромбогеморагічних ускладнень у післяопераційний період у 98 хворих, що страждали на різні форми хіміорезистентного туберкульозу легень. Встановлено, що з метою профілактики таких ускладнень доцільним є призначення ге¬парина перед операцією та під час неї у мінімальних дозах або фраксипарину. Це дозволяє значно знизити рівень предтромботичного фону, попередити розвиток тромбогеморагічних ускладнень, а при їх розвитку — із мінімальними втратами впоратися з клінічними проявами тромботичного чи геморагічного характеру.The study of prophylactic approach for thrombo-haemorrhagic complications presents 98 patients with different forms of multi-drug-resistant pulmonary tuberculosis in postoperative period. The study indicated that pre- and intra-operational administration of heparin or fraxiparine in minimal doses provided prophylactic aid in development of thrombo-haemorrhagic complications. The usage of this scheme permitted to reduce significantly the level of pre-thrombotic baseline, to prevent the development of thrombo-haemorrhagic complications, and even to treat effectively in case of clinically evident thrombo-haemorrhagic event
The New Method for Analyzing Technology Trends of Smart Energy Asset Performance Management
The development of emerging technologies not only has recently affected current industrial production but also has generated promising manufacturing opportunities that impact significantly on social and economic factors. Exploring upcoming renovation tendencies of technologies prematurely is essential for governments, research and development institutes, and industrial companies in managing strategies to achieve dominant advantages in business competitiveness. Additionally, the prospective changes, the scientific research directions, and the focus of technologies are crucial factors in predicting promising technologies. On the other hand, Industry 4.0 revolutionizes standards and models by accompanying significant technology developments in numerous sectors, including the sector of Smart energy. Moreover, asset performance management is always a prominent topic that has attained prevalence over the last decade because numerous challenges force all industrial companies to optimize their asset usability. However, to the best of our knowledge, no study reported an analysis of technology trends of asset performance management in the Smart energy sector by using proper data mining methods. Hence, this paper aims to fill in this gap and provide an analysis of technology trends of asset performance management in the Smart energy sector by structuring and exploring research subjects, considering problems, and solving methods with numerous experiments on scientific papers and patent data
The Software Cache Optimization-Based Method for Decreasing Energy Consumption of Computational Clusters
Reducing the consumption of electricity by computing devices is currently an urgent task. Moreover, if earlier this problem belonged to the competence of hardware developers and the design of more cost-effective equipment, then more recently there has been an increased interest in this issue on the part of software developers. The issues of these studies are extensive. From energy efficiency issues of various programming languages to the development of energy-saving software for smartphones and other gadgets. However, to the best of our knowledge, no study has reported an analysis of the impact of cache optimizations on computing devices’ power consumption. Hence, this paper aims to provide an analysis of such impact on the software energy efficiency using the original software design procedure and computational experiments. The proposed Software Cache Optimization (SCO)-based Methodology was applied to one of the key linear algebra transformations. Experiments were carried out to determine software energy efficiency. RAPL (Running Average Power Limit) was used—an interface developed by Intel, which provides built-in counters of Central Processing Unit (CPU) energy consumption. Measurements have shown that optimized software versions reduce power consumption up to 4 times in relation to the basic transformation scheme. Experimental results confirm the effectiveness of the SCO-based Methodology used to reduce energy consumption and the applicability of this technique for software optimization
The Software Cache Optimization-Based Method for Decreasing Energy Consumption of Computational Clusters
Reducing the consumption of electricity by computing devices is currently an urgent task. Moreover, if earlier this problem belonged to the competence of hardware developers and the design of more cost-effective equipment, then more recently there has been an increased interest in this issue on the part of software developers. The issues of these studies are extensive. From energy efficiency issues of various programming languages to the development of energy-saving software for smartphones and other gadgets. However, to the best of our knowledge, no study has reported an analysis of the impact of cache optimizations on computing devices’ power consumption. Hence, this paper aims to provide an analysis of such impact on the software energy efficiency using the original software design procedure and computational experiments. The proposed Software Cache Optimization (SCO)-based Methodology was applied to one of the key linear algebra transformations. Experiments were carried out to determine software energy efficiency. RAPL (Running Average Power Limit) was used—an interface developed by Intel, which provides built-in counters of Central Processing Unit (CPU) energy consumption. Measurements have shown that optimized software versions reduce power consumption up to 4 times in relation to the basic transformation scheme. Experimental results confirm the effectiveness of the SCO-based Methodology used to reduce energy consumption and the applicability of this technique for software optimization
The New Method for Analyzing Technology Trends of Smart Energy Asset Performance Management
The development of emerging technologies not only has recently affected current industrial production but also has generated promising manufacturing opportunities that impact significantly on social and economic factors. Exploring upcoming renovation tendencies of technologies prematurely is essential for governments, research and development institutes, and industrial companies in managing strategies to achieve dominant advantages in business competitiveness. Additionally, the prospective changes, the scientific research directions, and the focus of technologies are crucial factors in predicting promising technologies. On the other hand, Industry 4.0 revolutionizes standards and models by accompanying significant technology developments in numerous sectors, including the sector of Smart energy. Moreover, asset performance management is always a prominent topic that has attained prevalence over the last decade because numerous challenges force all industrial companies to optimize their asset usability. However, to the best of our knowledge, no study reported an analysis of technology trends of asset performance management in the Smart energy sector by using proper data mining methods. Hence, this paper aims to fill in this gap and provide an analysis of technology trends of asset performance management in the Smart energy sector by structuring and exploring research subjects, considering problems, and solving methods with numerous experiments on scientific papers and patent data