scholarly journals Important Developments in Romanian Propolis Research

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Liviu Al Mărghitaş ◽  
Daniel S. Dezmirean ◽  
Otilia Bobiş
Keyword(s):  
Chemical Composition ◽  
Quality Criteria ◽  
Composition Analysis ◽  
International Studies ◽  
Pharmacological Properties ◽  
Practical Applications ◽  
Divisive Hierarchical Clustering ◽  
Clustering Approach ◽  
Chemical Composition Analysis ◽  
Medicinal Therapy

The most important developments in propolis analysis and pharmacological properties are discussed. In order to help in the Romanian propolis standardization, different methodologies for chemical composition analysis (UV-VIS, HP-TLC, and HPLC-DAD) are reviewed using new approaches and software (fuzzy divisive hierarchical clustering approach and ChromQuest software) and compared with international studies made until now in propolis research. Practical applications of Romanian propolis in medicinal therapy and cosmetics are reviewed, and quality criteria for further standardization are proposed.

scholarly journals Correction: Yu, D.Q., et al. Microscopic Characteristic and Chemical Composition Analysis of Three Medicinal Plants and Surface Frosts. Molecules 2019, 24, 4548

Molecules ◽  
2021 ◽  
Vol 26 (2) ◽  
pp. 379
Author(s):  
Da Qing Yu ◽  
Xiao Jing Han ◽  
Ting Yu Shan ◽  
Rui Xu ◽  
Jin Hu ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Medicinal Plants ◽  
Composition Analysis ◽  
Microscopic Characteristic ◽  
Chemical Composition Analysis

The authors would like to correct an error in the title paper [...]

Chemical composition analysis of carbohydrate fragmentation products

2021 ◽  
Vol 156 ◽  
pp. 105112
Author(s):  
Samin Fathalinejad ◽  
Esben Taarning ◽  
Peter Christensen ◽  
Jan H. Christensen
Keyword(s):  
Chemical Composition ◽  
Composition Analysis ◽  
Chemical Composition Analysis

Research on Process Mineralogy of Potassium-Rich Shale

2010 ◽  
Vol 158 ◽  
pp. 197-203 ◽  
Author(s):  
Jie Liu ◽  
Yue Xin Han ◽  
Wan Zhong Yin
Keyword(s):  
Chemical Composition ◽  
Mineral Composition ◽  
Potassium Feldspar ◽  
Composition Analysis ◽  
Research Results ◽  
Dsc Analyses ◽  
Process Mineralogy ◽  
Mineral Compositions ◽  
Chemical Composition Analysis

The process mineralogy of potassium-rich shale from Chaoyang of Liaoning, China, was studied. Research results showed there are much less variety and smaller quantities in mineral compositions. Calculated mineral composition by means of chemical composition analysis combined with XRD, MLA, IR and TG-DSC analyses showed that main minerals with were Potassium-feldspar, muscovite, biotite and illite, and gangue minerals were quartz and small amounts of hematite. Potassium-rich minerals such as potassium-feldspar and muscovite contact smoothly with quartz respectively, and there was the direction arrangement among potassium-feldspar, quartz and muscovite in the shale. And quartz and hematite were main cement in the shale. The influences of the research results on the potassium extraction from potassium-rich shale were distinct.

scholarly journals Chemical composition analysis of the essential oil of Solanumn nigrum L. by HS/SPME method and calculation of the biochemical coefficients of the components

2017 ◽  
Vol 10 ◽  
pp. S2372-S2375 ◽  
Author(s):  
Avat (Arman) Taherpour ◽  
Mohammad Mehdi Khodaei ◽  
Baram Ahmed Hama Ameen ◽  
Majid Ghaitouli ◽  
Nosratollah Mahdizadeh ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Essential Oil ◽  
Composition Analysis ◽  
Chemical Composition Analysis

Comparison of machine learning techniques to optimize the analysis of plutonium surrogate material via a portable LIBS device

2021 ◽  
Author(s):  
Ashwin P. Rao ◽  
Phillip R. Jenkins ◽  
John D. Auxier II ◽  
Michael B. Shattan
Keyword(s):  
Machine Learning ◽  
Chemical Composition ◽  
Machine Learning Techniques ◽  
Composition Analysis ◽  
Learning Techniques ◽  
Chemical Composition Analysis

Enhancing the analytical capabilities of a hand-held LIBS device for chemical composition analysis of a plutonium surrogate using different machine learning paradigms.

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