Sustainable Public Procurement in Portugal – State of the Art and Future Prospects

Author(s):  
M. da Silva Gomes
2019 ◽  
Vol 19 (25) ◽  
pp. 2348-2356 ◽  
Author(s):  
Neng-Zhong Xie ◽  
Jian-Xiu Li ◽  
Ri-Bo Huang

Acetoin is an important four-carbon compound that has many applications in foods, chemical synthesis, cosmetics, cigarettes, soaps, and detergents. Its stereoisomer (S)-acetoin, a high-value chiral compound, can also be used to synthesize optically active drugs, which could enhance targeting properties and reduce side effects. Recently, considerable progress has been made in the development of biotechnological routes for (S)-acetoin production. In this review, various strategies for biological (S)- acetoin production are summarized, and their constraints and possible solutions are described. Furthermore, future prospects of biological production of (S)-acetoin are discussed.


2020 ◽  
Vol 1 ◽  
pp. 1-24
Author(s):  
Daniel J. Egger ◽  
Claudio Gambella ◽  
Jakub Marecek ◽  
Scott McFaddin ◽  
Martin Mevissen ◽  
...  

ChemInform ◽  
2014 ◽  
Vol 45 (16) ◽  
pp. no-no
Author(s):  
Diego Lopez Barreiro ◽  
Wolter Prins ◽  
Frederik Ronsse ◽  
Wim Brilman

2019 ◽  
Vol 12 (3) ◽  
pp. 58-75
Author(s):  
Artiсle Editorial

On April 4–5, 2019, the Russian Helmholtz National Medical Research Center of Eye Diseases held a scientific and practical conference with international participation «Retinopathy of prematurity and retinoblastoma 2019». The conference, which became a platform for discussion of the most acute and burning issues of pediatric ophthalmology, was a great success. The proceedings reflect the state-of-the-art in the treatment of infants and children with retinopathy of prematurity and retinoblastoma, new technical and methodological solutions, controversial issues, and future prospects.


Author(s):  
Amir Mosavi ◽  
Sina Faizollahzadeh Ardabili ◽  
Shahabodin Shamshirband

Electricity demand prediction is vital for energy production management and proper exploitation of the present resources. Recently, several novel machine learning (ML) models have been employed for electricity demand prediction to estimate the future prospects of the energy requirements. The main objective of this study is to review the various ML models applied for electricity demand prediction. Through a novel search and taxonomy, the most relevant original research articles in the field are identified and further classified according to the ML modeling technique, perdition type, and the application area. A comprehensive review of the literature identifies the major ML models, their applications and a discussion on the evaluation of their performance. This paper further makes a discussion on the trend and the performance of the ML models. As the result, this research reports an outstanding rise in the accuracy, robustness, precision and the generalization ability of the prediction models using the hybrid and ensemble ML algorithms.


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