Про участь НАН України в розробці наукових основ сталого розвитку України

Наведено основні напрями наукових досліджень установ НАН України з проблеми збереження навколишнього середовища і сталого розвитку України, що виконувались наприкінці ХХ та на початку ХХІ століть в світлі рішень Конференції ООН з навколишнього середовища і розвитку у Ріо-де-Жанейро (червень 1992 р.) та Всесвітнього саміту зі сталого розвитку в Йоганнесбурзі (26 серпня — 4 вересня 2002 р.). На основі узагальнення результатів опитування установ НАН України в 2005 році проведено кількісний (наукометричний) аналіз їх участі у вирішенні зазначеної міждисциплінарної проблеми за п’ятирічний період за рядом показників (фінансове і кадрове забезпечення досліджень, використання їх результатів, патентно-ліцензійна та видавнича діяльність тощо) і сформульовано пропозиції щодо здійснення відповідних заходів з підвищення ефективності використання фінансових і матеріальних ресурсів при виконанні наукових досліджень з проблеми, підвищення їх координації та результативності.Приведены основные направления научных исследований учреждений НАН Украины по проблеме сохранения окружающей среды и стойкого развития Украины, которые выполнялись в конце ХХ и в начале XXI столетий в свете решений Конференции ООН по окружающей среде и развитию в Рио-де-Жанейро (июнь 1992 г.) и Всемирного саммита по устойчивому развитию в Иоганнесбурге (26 августа — 4 сентября 2002 г.). На основе обобщения результатов опроса учреждений НАН Украины в 2005 году проведен количественный (наукометрический) анализ их участия в решении указанной междисциплинарной проблемы за пятилетний период по ряду показателей (финансовое и кадровое обеспечение исследований, использование их результатов, патентно-лицензионная и издательская деятельность и др.) и сформулированы предложения о выполнении соответствующих мероприятий по повышению эффективности использования финансовых и материальных ресурсов при выполнении научных исследований по проблеме, повышению их координации и результативности.Main areas for research in institutes of the Ukrainian NAS are shown, devoted to environmental protection and sustained development in Ukraine, performed at the end of XX and the beginning of XXI centuries in light of the decision taken by the UN Conference in Rio de Janeiro (June 1992) and the World Summit on Sustained Development in Johannesburg (26 August – 4 September 2002). On the basis of results from a survey on institutes of the Ukrainian NAS, conducted in 2005, a scientometric analysis of their contributions in solving the above interdisciplinary problem is made, covering the 5-year period, by several indicators (research funding and personnel, applications of results, patenting, licensing, printing and publishing etc.), and measures are offered to enhance the efficiency of relevant research in terms of resource utilization, coordination and produced results

The Gravitational Wave Universe Toolbox: a software package to simulate observations of the gravitational wave universe with different detectors

Computational astrophysicsHigh Energy Astrophysic

Endoscopic Versus Surgical Step-Up Approach for Infected Necrotizing Pancreatitis (ExTENSION): Long-term Follow-up of a Randomized Trial

BACKGROUND & AIMS: Previous randomized trials, including the Transluminal Endoscopic Step-Up Approach Versus Minimally Invasive Surgical Step-Up Approach in Patients With Infected Pancreatic Necrosis (TENSION) trial, demonstrated that the endoscopic step-up approach might be preferred over the surgical step-up approach in patients with infected necrotizing pancreatitis based on favorable short-term outcomes. We compared long-term clinical outcomes of both step-up approaches after a period of at least 5 years. METHODS: In this long-term follow-up study, we reevaluated all clinical data on 83 patients (of the originally 98 included patients) from the TENSION trial who were still alive after the initial 6-month follow-up. The primary end point, similar to the TENSION trial, was a composite of death and major complications. Secondary end points included individual major complications, pancreaticocutaneous fistula, reinterventions, pancreatic insufficiency, and quality of life. RESULTS: After a mean followup period of 7 years, the primary end point occurred in 27 patients (53%) in the endoscopy group and in 27 patients (57%) in the surgery group (risk ratio [RR], 0.93; 95% confidence interval [CI], 0.65-1.32; P = .688). Fewer pancreaticocutaneous fistulas were identified in the endoscopy group (8% vs 34%; RR, 0.23; 95% CI, 0.08-0.83). After the initial 6-month follow-up, the endoscopy group needed fewer reinterventions than the surgery group (7% vs 24%; RR, 0.29; 95% CI, 0.09-0.99). Pancreatic insufficiency and quality of life did not differ between groups. CONCLUSIONS: At long-term follow-up, the endoscopic step-up approach was not superior to the surgical step-up approach in reducing death or major complications in patients with infected necrotizing pancreatitis. However, patients assigned to the endoscopic approach developed overall fewer pancreaticocutaneous fistulas and needed fewer reinterventions after the initial 6-month follow-up.Cellular mechanisms in basic and clinical gastroenterology and hepatolog

Designing and Understanding Forensic Bayesian Networks using Argumentation

The rise of forensic evidence in court has confronted the legal domain with a number of difficulties. It appears that a communication gap may exist between forensic and legal experts.Judges, lawyers and other legal experts are accustomed to argumentative reasoning, whereas forensic experts usually quantify uncertainty with probabilities. This has resulted in a heated discussion among legal scholars about the role of numerical analyses of evidence in court. It has been argued that the source of the discussion may lie in the different ways in which experts (legal and forensic) deal with uncertainty of evidence. Argumentation theory and probability theory provide two different perspectives on uncertainty. In this thesis I combine these two perspectives in an attempt to unite the worlds of legal and forensic reasoning with uncertain legal evidence

A two-phase method for extracting explanatory arguments from Bayesian networks

Errors in reasoning about probabilistic evidence can have severe consequences. In the legal domain a number of recent miscarriages of justice emphasises how severe these consequences can be. These cases, in which forensic evidence was misinterpreted, have ignited a scientific debate on how and when probabilistic reasoning can be incorporated in (legal) argumentation. One promising approach is to use Bayesian networks (BNs), which are well-known scientific models for probabilistic reasoning. For non-statistical experts, however, Bayesian networks may be hard to interpret. Especially since the inner workings of Bayesian networks are complicated, they may appear as black box models. Argumentation models, on the contrary, can be used to show how certain results are derived in a way that naturally corresponds to everyday reasoning. In this paper we propose to explain the inner workings of a BN in terms of arguments. We formalise a two-phase method for extracting probabilistically supported arguments from a Bayesian network. First, from a Bayesian network we construct a support graph, and, second, given a set of observations we build arguments from that support graph. Such arguments can facilitate the correct interpretation and explanation of the relation between hypotheses and evidence that is modelled in the Bayesian network

A Structure-guided Approach to Capturing Bayesian Reasoning about Legal Evidence in Argumentation

Over the last decades the rise of forensic sciences has led to an increase in the availability of statistical evidence. Reasoning about statistics and probabilities in a forensic science setting can be a precarious exercise, especially so when in- dependencies between variables are involved. To facilitate the correct explanation of such evidence we investigate how argumentation models can help in the interpretation of statistical information. In this paper we focus on the connection between argumentation models and Bayesian belief networks, the latter being a common model to represent and reason with complex probabilistic information. We introduce the notion of a support graph as an intermediate structure between Bayesian networks and argumentation models. A support graph disentangles the complicating graphical properties of a Bayesian network and enhances its intuitive interpretation. Moreover, we show that this model can provide a suitable template for argumentative analysis. Especially in the context of legal reasoning, the correct treatment of statistical evidence is important