Search results

1

An advanced multivariate statistical approach to study coastal sediment data

100%

Simeonova P., Sarbu C., Spanos T., Simeonov V., Tsakovski S.

Open Chemistry

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2006

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vol. 4

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issue 1

68-80

EN

The present paper deals with the application of classical and fuzzy principal components analysis to a large data set from coastal sediment analysis. Altogether 126 sampling sites from the Atlantic Coast of the USA are considered and at each site 16 chemical parameters are measured. It is found that four latent factors are responsible for the data structure (“natural”, “anthropogenic”, “bioorganic”, and “organic anthropogenic”). Additionally, estimating the scatter plots for factor scores revealed the similarity between the sampling sites. Geographical and urban factors are found to contribute to the sediment chemical composition. It is shown that the use of fuzzy PCA helps for better data interpretation especially in case of outliers.

2

Chemometric study of soil analysis data

88%

Spanos T., Simeonov V., Tsakovski S., Thiokas D.

Open Chemistry

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2004

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vol. 2

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issue 2

402-416

EN

The present paper deals with chemometric interpretation of soil analysis data collected from 31 sampling sites in the region of Kavala and Drama, Northern Greece. The determination of 16 different chemical and physicochemical characteristics is principally needed for prognosis of the land treatment and fertilizing. The study carried out indicates that the application of multivariate statistical approaches could reveal new and specific information about sampling sites. It has been found that they could be divided into four general patterns: pattern 1 contains dominantly inorganic and alkaline soil samples from semi-mountainous regions in close proximity to the seacoast; pattern 2 indicates the same soil sample type and regional location as pattern 1 but is far from the coastal line; pattern 3 includes samples from sites from the plains with organic and alkaline soils with close proximity to the coast; pattern 4 resembles pattern 3 as soil type but involves samples from sites far from the shore. Further, six latent factors were identified, conditionally named “structural”, “acidic”, “nutritional”, “salt”, “microcomponents” and “organic”. Finally, an apportioning procedure was carried out to find the source contributions in the measured analytical values. In this way the routine estimation of the soil quality could be improved.

3

Chemometrics in the assessment of the sustainable development rule implementation

88%

Astel A., Głosińska G., Sobczyński T., Boszke L., Simeonov V., Siepak J.

Open Chemistry

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2006

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vol. 4

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issue 3

543-564

EN

The sustainable development rule implementation is tested by the application of chemometrics in the field of environmental pollution. A data set consisting of Cd, Pb, Cr, Zn, Cu, Mn, Ni, and Fe content in bottom sediment samples collected in the Odra River (Germany/Poland) is treated using cluster analysis (CA), principal component analysis (PCA), and source apportionment techniques. Cluster analysis clearly shows that pollution on the German bank is higher than on the Polish bank. Two latent factors extracted by PCA explain over 88 % of the total variance of the system, allowing identification of the dominant “semi-natural” and “anthropogenic” pollution sources in the river ecosystem. The complexity of the system is proved by MLR analysis of the absolute principal component scores (APCS). The apportioning clearly shows that Cd, Pb, Cr, Zn and Cu participate in an “anthropogenic” source profile, whereas Fe and Mn are “semi-natural”. Multiple regression analysis indicates that for particular elements not described by the model, the amounts vary from 4.2 % (Mn) to 13.1 % (Cr). The element Ni participates to some extent to each source and, in this way, is neither pure “semi-natural” nor pure “anthropogenic”. Apportioning indicates that the whole heavy metal pollution in the investigated river reach is 12510.45 mg·kg−1. The contribution of pollutants originating from “anthropogenic sources” is 9.04 % and from “semi-natural” sources is 86.53 %.

4

Correlation between bean seed surface lipids and Acanthoscelides obtectus Say development

75%

Nietupski M., Szafranek B., Ciepielewska D., Synak E., Fornal Ł., Szafranek J.

Journal of Plant Protection Research

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2005

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vol. 45

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issue 2

5

Narzędzia budowania wiedzy o procesie wytwarzania produktu leczniczego w myśl koncepcji Quality by Design.

75%

Ronowicz J.

Farmacja Polska

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2019

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vol. 75

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issue 11

648-655

EN

The significant change in the pharmaceutical quality approach (QbD concept, PAT strategy) and focusing on improving the quality of drug products by reducing variability in the manufacturing process force the use of effective tools to discover knowledge about the process and product. The Quality by Design concept is an essential part of the modern approach to pharmaceutical quality. Due to the current trend of being QbD compliant, the use of chemometrics in pharmaceutical sciences is increasing. This strategy can shorten a drug development phase and reduce the overall experimental work and costs. Moreover, continuous process monitoring requires the application of advanced, often non-invasive instrumental analytical techniques that generate a huge amount of process data. Their effective analysis and interpretation is possible thanks to chemometrics. The appropriate chemometric algorithms allow to detect cause-effect relations between the raw materials properties, process parameters and the drug product quality. The detected relations can be easily translated into accurate and rationally justified technological decisions, leading to manufacturing process optimization and consequently significant improvement of drug product quality. The effective building of process and product knowledge within the QbD concept is possible by means of non-invasive analytical methods generating process data sets which in-depth analysis and interpretation is possible with the use of the appropriate chemometric algorithms. The use of chemometric techniques enables better understanding of the effect of material attributes and process factors on the final drug product quality. Prognostic mathematical models can be generated to describe in detail the interrelations between excipients and the critical quality attribute of final formulation. This approach should be taken into consideration by industrial formulation scientists to support rational decision making at the drug product development stage.

PL

Zmiana podejścia do problemu zapewnienia jakości w farmacji przemysłowej (koncepcja QbD, strategia PAT), ukierunkowanie na poprawę jakości produktu leczniczego poprzez redukcję zmienności w procesie wytwarzania wymusza użycie efektywnych narzędzi budowania wiedzy o procesie i produkcie. Ciągłe monitorowanie procesu wytwarzania wymaga zastosowania zaawansowanych, często nieinwazyjnych metod analizy instrumentalnej, które generują ogromną ilość danych procesowych. Ich efektywna analiza i interpretacja jest możliwa dzięki metodom chemometrycznym. Odpowiednie algorytmy chemometryczne pozwalają wykryć zależności przyczynowo-skutkowe między właściwościami użytych surowców, parametrami procesu a jakością produktu leczniczego. Wykryte zależności przekładają się na trafne i racjonalnie uzasadnione decyzje technologiczne, prowadzące do optymalizacji procesu wytwarzania oraz poprawy jakości produktu leczniczego. Efektywne budowanie wiedzy o procesie i produkcie w ramach koncepcji QbD jest możliwe przy użyciu nieinwazyjnych metod analizy instrumentalnej generujących dane procesowe, których dogłębna analiza i interpretacja jest możliwa z wykorzystaniem odpowiednich algorytmów chemometrycznych.

6

Comparison of Five Svd-Based Algorithms for Calibration of Spectrophotometric Analyzers

75%

Wagner J., Morawski R. Z., Miękina A.

Metrology and Measurement Systems

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2014

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issue 2

7

Measurement Data Processing in Spectrophotometric Analysers of Food

75%

Morawski R. Z.

Metrology and Measurement Systems

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2012

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issue 4

8

Chemometric Analysis of Heavy Metals Coexistence in Different Plant Matrices in The Upper Silesian Industrial District / Analiza Chemometryczna Metali Ciężkich Pochodzących Z Różnych Matryc Roślinnych Z Terenów Górnośląskiego Okręgu Przemysłowego

51%

Pieszko C., Sajdak M.

Ecological Chemistry and Engineering S

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2013

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vol. 20

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issue 1

79-91

EN

Contents of Zn, Cd, Ni, Mn, Cu, Pb and Fe in 36 samples of Scots pine collected in 9 sites located in the Upper Silesia Province have been determined using AAS technique. The samples were digested before the analysis. On the basis of cluster analysis the existence of links between the quantitative composition, the sampling sites and the type of the matrix have been found. The coexistence of certain groups of elements was found and described.

PL

Oszacowano stężenia Zn, Cd, Ni, Mn, Cu, Pb, Fe, w 36 próbkach sosny zwyczajnej pobranych w 9 punktach umieszczonych na terenie województwa śląskiego. Mineralizaty były badane na zawartość wyżej wymienionych pierwiastków przy zastosowaniu AAS. Największe stężenie oznaczanych analitów stwierdzono w Jaworznie. Na podstawie analizy skupień stwierdzono istnienie powiązań pomiędzy składem ilościowym a miejscami pobrania próbek oraz typem matrycy, a także stwierdzono i opisano współwystępowanie obok siebie określonych grup pierwiastków

Refine search results

An advanced multivariate statistical approach to study coastal sediment data

Chemometric study of soil analysis data

Chemometrics in the assessment of the sustainable development rule implementation

Correlation between bean seed surface lipids and Acanthoscelides obtectus Say development

Narzędzia budowania wiedzy o procesie wytwarzania produktu leczniczego w myśl koncepcji Quality by Design.

Comparison of Five Svd-Based Algorithms for Calibration of Spectrophotometric Analyzers

Measurement Data Processing in Spectrophotometric Analysers of Food

Chemometric Analysis of Heavy Metals Coexistence in Different Plant Matrices in The Upper Silesian Industrial District / Analiza Chemometryczna Metali Ciężkich Pochodzących Z Różnych Matryc Roślinnych Z Terenów Górnośląskiego Okręgu Przemysłowego