A review on machine learning algorithms for the ionic liquid chemical space

There are thousands of papers published every year investigating the properties and possible applications of ionic liquids. Industrial use of these exceptional fluids requires adequate understanding of their physical properties, in order to create the ionic liquid that will optimally suit the application. Computational property prediction arose from the urgent need to minimise the time and cost that would be required to experimentally test different combinations of ions. This review discusses the use of machine learning algorithms as property prediction tools for ionic liquids (either as standalone methods or in conjunction with molecular dynamics simulations), presents common problems of training datasets and proposes ways that could lead to more accurate and efficient models.

In this review article, the authors discuss the use of machine learning algorithms as tools for the prediction of physical and chemical properties of ionic liquids.     

Identification of metabolic markers in patients with type 2 Diabetes by Ultrafast gas chromatography coupled to electronic nose. A pilot study

Metabolomics is a potential tool for the discovery of new biomarkers in the early diagnosis of diseases. An ultra-fast gas chromatography system equipped to an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of Volatile Organic Compounds (VOCs) in type 2 diabetes (T2D) urine from Mexican population. A cross-sectional, comparative, and clinical study with translational approach was performed. We recruited twenty T2D patients and twenty-one healthy subjects. Urine samples were taken and analyzed by FGC eNose. Eighty-eight compounds were identified through Kovats's indexes. A natural variation of 30% between the metabolites, expressed by study groups, was observed in Principal Component 1 and 2 with a significant difference (p < 0.001). The model, performed through a Canonical Analysis of Principal coordinated (CAP), allowed a correct classification of 84.6% between healthy and T2D patients, with a 15.4% error. The metabolites 2-propenal, 2-propanol, butane- 2,3-dione and 2-methylpropanal, were increased in patients with T2D, and they were strongly correlated with discrimination between clinically healthy people and T2D patients. This study identified metabolites in urine through FGC eNose that can be used as biomarkers in the identification of T2D patients. However, more studies are needed for its implementation in clinical practice.     

GDME-based methodology for the determination of free formaldehyde in cosmetics and hygiene products containing formaldehyde releasers

Analytical and Bioanalytical Chemistry - Formaldehyde is often applied in the industrial production of different products, such as textiles, insulation materials, or cosmetics, due to its...     

Three New Polyoxygenated Steroids from Two Species of the South China Sea Gorgonian Muricella flexuosa and Menella verrucosa Brundin

Three new polyoxygenated steroids, muricesteroid ( 1 ), and menellsteroids A ( 2 ) and B ( 3 ), were isolated from two species of the South China Sea gorgonian Muricella flexuosa and Menella verrucosa Brundin , respectively. The structures of these new compounds were elucidated on the basis of extensive spectroscopic analysis, chemical methods and comparison with known related compounds.     

The first total syntheses of (±)-Preussomerins K and L using 2-arylacetal anion technology

The first syntheses of newly isolated members of the Preussomerin family, Preussomerins K and L, are reported. Key steps include the functionalisation of a 2-arylacetal anion, one-pot Friedel-Crafts cyclisation-deprotection and reductive opening of epoxides.     

Heavy Majorana neutrinos in e + e − → W + W−

In this paper we investigate the effects of heavy Majorana neutrinos in the reaction e ⁺ e ^? → W ⁺ W ^?. We consider neutrino masses in the 1–10 TeV region. We show that at LEP II and NLC energies it is possible to use this processes to verify indirect evidence of heavy neutral particles with mixing angles of the order sin² α = 0.01. We discuss the unitarity restrictions that can be obtained for vector singlet and fermion-mirror-fermion models.     

The Assessment of Reservation Prices of an Intermediate R&amp;D Result and Patent Reward Under Oligopolistic Competitive Behaviour

One of the shortcomings of R&D evaluation is a lack of emphasis on analytical assessment of the value of an on-going R&D project. This paper addresses the problem concerning the distributive aspect of access to superior knowledge. Decision tree analysis and probability models appear to be appropriate tools for assessing the values of an intermediate result and patent reward of a firm's R&D decision in an environment of perfect information and oligopolistic competition. The assessed values are used as minimum prices acceptable to the firm when the knowledge is disseminated to the public. This paper will attempt to resolve this problem through the determination of the appropriate values of the reservation price of the first-stage invention in terms of the final reward and of a patent reward for which the inventor is willing to apply.