Adaptive selection of classifiers for bug prediction: A large-scale empirical analysis of its performances and a benchmark study

2021 ◽  
Vol 205 ◽  
pp. 102611 ◽  
Author(s):  
Fabiano Pecorelli ◽  
Dario Di Nucci
1996 ◽  
Vol 76 (06) ◽  
pp. 0939-0943 ◽  
Author(s):  
B Boneu ◽  
G Destelle ◽  

SummaryThe anti-aggregating activity of five rising doses of clopidogrel has been compared to that of ticlopidine in atherosclerotic patients. The aim of this study was to determine the dose of clopidogrel which should be tested in a large scale clinical trial of secondary prevention of ischemic events in patients suffering from vascular manifestations of atherosclerosis [CAPRIE (Clopidogrel vs Aspirin in Patients at Risk of Ischemic Events) trial]. A multicenter study involving 9 haematological laboratories and 29 clinical centers was set up. One hundred and fifty ambulatory patients were randomized into one of the seven following groups: clopidogrel at doses of 10, 25, 50,75 or 100 mg OD, ticlopidine 250 mg BID or placebo. ADP and collagen-induced platelet aggregation tests were performed before starting treatment and after 7 and 28 days. Bleeding time was performed on days 0 and 28. Patients were seen on days 0, 7 and 28 to check the clinical and biological tolerability of the treatment. Clopidogrel exerted a dose-related inhibition of ADP-induced platelet aggregation and bleeding time prolongation. In the presence of ADP (5 \lM) this inhibition ranged between 29% and 44% in comparison to pretreatment values. The bleeding times were prolonged by 1.5 to 1.7 times. These effects were non significantly different from those produced by ticlopidine. The clinical tolerability was good or fair in 97.5% of the patients. No haematological adverse events were recorded. These results allowed the selection of 75 mg once a day to evaluate and compare the antithrombotic activity of clopidogrel to that of aspirin in the CAPRIE trial.


PIERS Online ◽  
2007 ◽  
Vol 3 (1) ◽  
pp. 106-110
Author(s):  
Shaogang Wang ◽  
Xinpu Guan ◽  
Dangwei Wang ◽  
Xingyi Ma ◽  
Yi Su

2021 ◽  
Vol 13 (6) ◽  
pp. 3571
Author(s):  
Bogusz Wiśnicki ◽  
Dorota Dybkowska-Stefek ◽  
Justyna Relisko-Rybak ◽  
Łukasz Kolanda

The paper responds to research problems related to the implementation of large-scale investment projects in waterways in Europe. As part of design and construction works, it is necessary to indicate river ports that play a major role within the European transport network as intermodal nodes. This entails a number of challenges, the cardinal one being the optimal selection of port locations, taking into account the new transport, economic, and geopolitical situation that will be brought about by modernized waterways. The aim of the paper was to present an original methodology for determining port locations for modernized waterways based on non-cost criteria, as an extended multicriteria decision-making method (MCDM) and employing GIS (Geographic Information System)-based tools for spatial analysis. The methodology was designed to be applicable to the varying conditions of a river’s hydroengineering structures (free-flowing river, canalized river, and canals) and adjustable to the requirements posed by intermodal supply chains. The method was applied to study the Odra River Waterway, which allowed the formulation of recommendations regarding the application of the method in the case of different river sections at every stage of the research process.


2021 ◽  
Vol 22 (15) ◽  
pp. 7773
Author(s):  
Neann Mathai ◽  
Conrad Stork ◽  
Johannes Kirchmair

Experimental screening of large sets of compounds against macromolecular targets is a key strategy to identify novel bioactivities. However, large-scale screening requires substantial experimental resources and is time-consuming and challenging. Therefore, small to medium-sized compound libraries with a high chance of producing genuine hits on an arbitrary protein of interest would be of great value to fields related to early drug discovery, in particular biochemical and cell research. Here, we present a computational approach that incorporates drug-likeness, predicted bioactivities, biological space coverage, and target novelty, to generate optimized compound libraries with maximized chances of producing genuine hits for a wide range of proteins. The computational approach evaluates drug-likeness with a set of established rules, predicts bioactivities with a validated, similarity-based approach, and optimizes the composition of small sets of compounds towards maximum target coverage and novelty. We found that, in comparison to the random selection of compounds for a library, our approach generates substantially improved compound sets. Quantified as the “fitness” of compound libraries, the calculated improvements ranged from +60% (for a library of 15,000 compounds) to +184% (for a library of 1000 compounds). The best of the optimized compound libraries prepared in this work are available for download as a dataset bundle (“BonMOLière”).


Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 295
Author(s):  
Yuan Gao ◽  
Anyu Zhang ◽  
Yaojie Yue ◽  
Jing’ai Wang ◽  
Peng Su

Suitable land is an important prerequisite for crop cultivation and, given the prospect of climate change, it is essential to assess such suitability to minimize crop production risks and to ensure food security. Although a variety of methods to assess the suitability are available, a comprehensive, objective, and large-scale screening of environmental variables that influence the results—and therefore their accuracy—of these methods has rarely been explored. An approach to the selection of such variables is proposed and the criteria established for large-scale assessment of land, based on big data, for its suitability to maize (Zea mays L.) cultivation as a case study. The predicted suitability matched the past distribution of maize with an overall accuracy of 79% and a Kappa coefficient of 0.72. The land suitability for maize is likely to decrease markedly at low latitudes and even at mid latitudes. The total area suitable for maize globally and in most major maize-producing countries will decrease, the decrease being particularly steep in those regions optimally suited for maize at present. Compared with earlier research, the method proposed in the present paper is simple yet objective, comprehensive, and reliable for large-scale assessment. The findings of the study highlight the necessity of adopting relevant strategies to cope with the adverse impacts of climate change.


2021 ◽  
Vol 11 (5) ◽  
pp. 2098
Author(s):  
Heyi Wei ◽  
Wenhua Jiang ◽  
Xuejun Liu ◽  
Bo Huang

Knowledge of the sunshine requirements of landscape plants is important information for the adaptive selection and configuration of plants for urban greening, and is also a basic attribute of plant databases. In the existing studies, the light compensation point (LCP) and light saturation point (LSP) have been commonly used to indicate the shade tolerance for a specific plant; however, these values are difficult to adopt in practice because the landscape architect does not always know what range of solar radiation is the best for maintaining plant health, i.e., normal growth and reproduction. In this paper, to bridge the gap, we present a novel digital framework to predict the sunshine requirements of landscape plants. First, the research introduces the proposed framework, which is composed of a black-box model, solar radiation simulation, and a health standard system for plants. Then, the data fitting between solar radiation and plant growth response is used to obtain the value of solar radiation at different health levels. Finally, we adopt the LI-6400XT Portable Photosynthetic System (Li-Cor Inc., Lincoln, NE, USA) to verify the stability and accuracy of the digital framework through 15 landscape plant species of a residential area in the city of Wuhan, China, and also compared and analyzed the results of other researchers on the same plant species. The results show that the digital framework can robustly obtain the values of the healthy, sub-healthy, and unhealthy levels for the 15 landscape plant species. The purpose of this study is to provide an efficient forecasting tool for large-scale surveys of plant sunshine requirements. The proposed framework will be beneficial for the adaptive selection and configuration of urban plants and will facilitate the construction of landscape plant databases in future studies.


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