scholarly journals DIGITAL REPRESENTATION TECHNIQUES FOR OLFACTORY FEATURES

2021 ◽  
Vol 9 (1) ◽  
pp. 288-294
Author(s):  
Dewanand A. Meshram, Dipti D. Patil

Digital representation of odor has a basic principal of chemosensory organism of sensory molecules. A body organism responds to external odor environments. A body of animal/human perceives the odor in the form of molecule structure. But the questions still arises how that odor molecule is presented in the digital format. Also how it act a specific odor behavior. The mechanism used in animal/human body is to solve the problem as per thought process level. Thought process retrieve the stored molecule of odor in a visual smell. Similar concepts are carrying forward to store in a computer system with the help of electron. The system is applied to perform Machine-learned odor recognition from physico-chemical properties of volatile molecules. The properties of volatile molecules are to match the pattern of chemosensory organisms. Artificial intelligence is used to predict the molecule of smell by applying neural network. This paper focuses on the behavior of odors and its digital representation techniques for olfactory features.    

Author(s):  
H. Gross ◽  
H. Moor

Fracturing under ultrahigh vacuum (UHV, p ≤ 10-9 Torr) produces membrane fracture faces devoid of contamination. Such clean surfaces are a prerequisite foe studies of interactions between condensing molecules is possible and surface forces are unequally distributed, the condensate will accumulate at places with high binding forces; crystallites will arise which may be useful a probes for surface sites with specific physico-chemical properties. Specific “decoration” with crystallites can be achieved nby exposing membrane fracture faces to water vopour. A device was developed which enables the production of pure water vapour and the controlled variation of its partial pressure in an UHV freeze-fracture apparatus (Fig.1a). Under vaccum (≤ 10-3 Torr), small container filled with copper-sulfate-pentahydrate is heated with a heating coil, with the temperature controlled by means of a thermocouple. The water of hydration thereby released enters a storage vessel.


1990 ◽  
Vol 63 (03) ◽  
pp. 499-504 ◽  
Author(s):  
A Electricwala ◽  
L Irons ◽  
R Wait ◽  
R J G Carr ◽  
R J Ling ◽  
...  

SummaryPhysico-chemical properties of recombinant desulphatohirudin expressed in yeast (CIBA GEIGY code No. CGP 39393) were reinvestigated. As previously reported for natural hirudin, the recombinant molecule exhibited abnormal behaviour by gel filtration with an apparent molecular weight greater than that based on the primary structure. However, molecular weight estimation by SDS gel electrophoresis, FAB-mass spectrometry and Photon Correlation Spectroscopy were in agreement with the theoretical molecular weight, with little suggestion of dimer or aggregate formation. Circular dichroism studies of the recombinant molecule show similar spectra at different pH values but are markedly different from that reported by Konno et al. (13) for a natural hirudin-variant. Our CD studies indicate the presence of about 60% beta sheet and the absence of alpha helix in the secondary structure of recombinant hirudin, in agreement with the conformation determined by NMR studies (17)


1963 ◽  
Vol 79 (2) ◽  
pp. 263-293 ◽  
Author(s):  
E.M. Savitskii ◽  
V.F. Terekhova ◽  
O.P. Naumkin

1990 ◽  
Vol 39 (442) ◽  
pp. 996-1000 ◽  
Author(s):  
Ayao TAKASAKA ◽  
Hideyuki NEMOTO ◽  
Hirohiko KONO ◽  
Yoshihiro MATSUDA

Food Biology ◽  
1970 ◽  
pp. 19-23
Author(s):  
Nawal Abdel-Gayoum Abdel-Rahman

The aim of this study is to use of karkede (Hibiscus sabdariffa L.) byproduct as raw material to make ketchup instead of tomato. Ketchup is making of various pulps, but the best type made from tomatoes. Roselle having adequate amounts of macro and micro elements, and it is rich in source of anthocyanine. The ketchup made from pulped of waste of soaked karkede, and homogenized with starch, salt, sugar, ginger (Zingiber officinale), kusbara (Coriandrum sativum) and gum Arabic. Then processed and filled in glass bottles and stored at two different temperatures, ambient and refrigeration. The total solids, total soluble solids, pH, ash, total titratable acidity and vitamin C of ketchup were determined. As well as, total sugars, reducing sugars, colour density, and sodium chloride percentage were evaluated. The sensory quality of developed product was determined immediately and after processing, which included colour, taste, odour, consistency and overall acceptability. The suitability during storage included microbial growth, physico-chemical properties and sensory quality. The karkede ketchup was found free of contaminants throughout storage period at both storage temperatures. Physico-chemical properties were found to be significantly differences at p?0.05 level during storage. There were no differences between karkade ketchup and market tomato ketchup concerning odour, taste, odour, consistency and overall acceptability. These results are encouraging for use of roselle cycle as a raw material to make acceptable karkade ketchup.


2020 ◽  
Author(s):  
Artur Schweidtmann ◽  
Jan Rittig ◽  
Andrea König ◽  
Martin Grohe ◽  
Alexander Mitsos ◽  
...  

<div>Prediction of combustion-related properties of (oxygenated) hydrocarbons is an important and challenging task for which quantitative structure-property relationship (QSPR) models are frequently employed. Recently, a machine learning method, graph neural networks (GNNs), has shown promising results for the prediction of structure-property relationships. GNNs utilize a graph representation of molecules, where atoms correspond to nodes and bonds to edges containing information about the molecular structure. More specifically, GNNs learn physico-chemical properties as a function of the molecular graph in a supervised learning setup using a backpropagation algorithm. This end-to-end learning approach eliminates the need for selection of molecular descriptors or structural groups, as it learns optimal fingerprints through graph convolutions and maps the fingerprints to the physico-chemical properties by deep learning. We develop GNN models for predicting three fuel ignition quality indicators, i.e., the derived cetane number (DCN), the research octane number (RON), and the motor octane number (MON), of oxygenated and non-oxygenated hydrocarbons. In light of limited experimental data in the order of hundreds, we propose a combination of multi-task learning, transfer learning, and ensemble learning. The results show competitive performance of the proposed GNN approach compared to state-of-the-art QSPR models making it a promising field for future research. The prediction tool is available via a web front-end at www.avt.rwth-aachen.de/gnn.</div>


2019 ◽  
Author(s):  
Mariano Sánchez-Castellanos ◽  
Martha M. Flores-Leonar ◽  
Zaahel Mata-Pinzón ◽  
Humberto G. Laguna ◽  
Karl García-Ruiz ◽  
...  

Compounds from the 2,2’-bipyridine molecular family were investigated for use as redox-active materials in organic flow batteries. For 156 2,2’-bipyridine derivatives reported in the academic literature, we calculated the redox potential, the pKa for the first protonation reaction, and the solubility in aqueous solutions. Using experimental data on a small subset of derivatives, we were able to calibrate our calculations. We find that functionalization with electron-withdrawing groups leads to an increase of the redox potential and to an increase of the molecular acidity (as expressed in a reduction of the pKa value for the first protonation step). Furthermore, calculations of solubility in water indicate that some of the studied derivatives have adequate solubility for flow battery applications. Based on an analysis of the physico-chemical properties of the 156 studied compounds, we down-select five molecules with carbonyl- and nitro-based functional groups, whose parameters are especially promising for potential application as negative redox-active material inorganic flow batteries.


2019 ◽  
Author(s):  
Mariano Sánchez-Castellanos ◽  
Martha M. Flores-Leonar ◽  
Zaahel Mata-Pinzón ◽  
Humberto G. Laguna ◽  
Karl García-Ruiz ◽  
...  

Compounds from the 2,2’-bipyridine molecular family were investigated for use as redox-active materials in organic flow batteries. For 156 2,2’-bipyridine derivatives reported in the academic literature, we calculated the redox potential, the pKa for the first protonation reaction, and the solubility in aqueous solutions. Using experimental data on a small subset of derivatives, we were able to calibrate our calculations. We find that functionalization with electron-withdrawing groups leads to an increase of the redox potential and to an increase of the molecular acidity (as expressed in a reduction of the pKa value for the first protonation step). Furthermore, calculations of solubility in water indicate that some of the studied derivatives have adequate solubility for flow battery applications. Based on an analysis of the physico-chemical properties of the 156 studied compounds, we down-select five molecules with carbonyl- and nitro-based functional groups, whose parameters are especially promising for potential application as negative redox-active material inorganic flow batteries.


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