scholarly journals Classical Biomarker and Quantitative Extended Diamondoid Analysis Fingerprints for Crude Oils from Deepwater Developments in Block 17, Lower Congo Basin, Angola

2020 ◽  
Vol 17 (19) ◽  
pp. 7204
Author(s):  
Carlos Boente ◽  
Gonzalo Márquez ◽  
Patricia Marín ◽  
Emilio Romero ◽  
Cristina Rodrigues ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Organic Geochemistry ◽  
Hierarchical Cluster ◽  
Molecular Data ◽  
Congo Basin ◽  
Hydrocarbon Generation ◽  
Thermal Maturity ◽  
Maturity Level ◽  
Oil Type ◽  
Maturity Parameters

The organic geochemistry of six oil samples from the offshore Block 17 (Lower Congo Basin, northwestern Angola) was studied by a combination of classical biomarker and extended diamondoid analyses to elucidate source rock facies, the extent of biodegradation, and thermal maturity. Based on molecular data, oils are interpreted as depicting a mixture of two pulses of hydrocarbon generation probably from the Bucomazi and Malembo formations. Geochemical results also gave evidence of mixing of a lacustrine siliciclastic-sourced oil charge and a second more terrestrially derived oil type in the samples analyzed. A single genetic oil family was identified through hierarchical cluster analysis; however, two groups of oils were identified on the basis of their biodegradation levels using the Peters/Moldowan scale. Lower and upper Malembo oils have a slight depletion and a notable absence of n-alkanes, suggesting PM levels of 1 and 2, respectively. Most molecular maturity parameters of the oil samples suggest a maturity level equivalent to the onset of the peak of the oil generative window.

scholarly journals Origin and Biodegradation of Crude Oils from the Northernmost Fields in the Bolivar Coastal Complex (Zulia State, Venezuela)

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5615
Author(s):  
Marcos Escobar ◽  
Gonzalo Márquez ◽  
Blanca Guerrero ◽  
Patricia Marín ◽  
Carlos Boente ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Carbon Isotope ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Thermal Maturity ◽  
Classification Schemes ◽  
Maracaibo Basin ◽  
Lake Maracaibo ◽  
Marine Carbonate ◽  
Petroleum Generation

The organic geochemical features of 30 sampled oils from the northern Bolivar Coastal Complex (Lake Maracaibo Basin, NW Venezuela) were examined by combining carbon isotope, classical biomarker, and extended diamondoid analyses to clarify source facies and to assess the thermal maturity and extent of biodegradation of the oils analyzed. In this work, oils are understood as a mixture of two episodes of petroleum generation from the La Luna Formation: a paleobiodegraded oil pulse during Paleogene times and a late pulse having a higher maturity in the post-Oligocene. For the oil samples analyzed, results revealed a mixing composed of different proportions of almost a terrestrially derived siliciclastic-sourced and a purely marine carbonate-sourced oil pulse. Moreover, two main groups of oils were identified by means of hierarchical cluster analysis. Finally, inter- and intrafield variations in the extent of biodegradation were also assessed using two classification schemes (Peters and Moldowan, and Manco scales).

DRSA: a non-hierarchical clustering algorithm using k-NN graph and its application in vegetation classification

2015 ◽  
pp. 125-138 ◽  
Author(s):  
I. V. Goncharenko
Keyword(s):  
Cluster Analysis ◽  
Clustering Algorithm ◽  
Nearest Neighbor ◽  
Clustering Algorithms ◽  
Protein Structures ◽  
Hierarchical Cluster ◽  
Vegetation Classification ◽  
K Nearest Neighbor ◽  
Neighbor Graph ◽  
Nearest Neighbor Graph

In this article we proposed a new method of non-hierarchical cluster analysis using k-nearest-neighbor graph and discussed it with respect to vegetation classification. The method of k-nearest neighbor (k-NN) classification was originally developed in 1951 (Fix, Hodges, 1951). Later a term “k-NN graph” and a few algorithms of k-NN clustering appeared (Cover, Hart, 1967; Brito et al., 1997). In biology k-NN is used in analysis of protein structures and genome sequences. Most of k-NN clustering algorithms build «excessive» graph firstly, so called hypergraph, and then truncate it to subgraphs, just partitioning and coarsening hypergraph. We developed other strategy, the “upward” clustering in forming (assembling consequentially) one cluster after the other. Until today graph-based cluster analysis has not been considered concerning classification of vegetation datasets.

Quality evaluation of tugaksheeree samples by ATR-FTIR spectroscopy using multicomponent analysis

2020 ◽  
Vol 10 ◽  
Author(s):  
Nikunj D. Patel ◽  
Niranjan S. Kanaki
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Quality Evaluation ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Attenuated Total Reflectance ◽  
Chemometric Methods ◽  
Total Reflectance ◽  
Fingerprint Region ◽  
Ftir Technique

Background: Numerous Ayurvedic formulations contains tugaksheeree as key ingredient. Tugaksheereeis the starch gained from the rhizomes of two plants, Curcuma angustifoliaRoxb. (Zingiberaceae) and Marantaarundinacea (MA) Linn. (Marantaceae). Objective: The primary concerns in quality assessment of Tugaksheeree occur due to adulteration or substitution. Method: In current study, Fourier transform infrared (FTIR) technique with attenuated total reflectance (ATR) facility was used to evaluate tugaksheeree samples. Total 10 different samples were studied and transmittance mode was kept to record the spectra devoid of pellets of KBR. Further treatment was given with multi component tools by considering fingerprint region of the spectra. Multivariate analysis was performed by various chemometric methods. Result: Multi component methods like Principal Component Analysis (PCA), and Hierarchical Cluster Analysis (HCA)were used to discriminate the tugaksheeree samples using Minitab software. Conclusion: This method can be used as a tool to differentiate samples of tugaksheeree from its adulterants and substitutes.

scholarly journals Diversity of Common Bean Landraces Collected in the Western and Eastern Carpatien

2011 ◽  
Vol 39 (No. 3) ◽  
pp. 73-83 ◽  
Author(s):  
O. Horňáková ◽  
M. Závodná ◽  
M. Žáková ◽  
J. Kraic ◽  
F. Debre
Keyword(s):  
Cluster Analysis ◽  
Common Bean ◽  
Morphological Characters ◽  
Molecular Data ◽  
Seed Traits ◽  
Phaseolus Vulgaris L ◽  
Growth Type ◽  
Banding Patterns ◽  
Polymorphism Detection ◽  
Thousand Seed Weight

The study of diversity in common bean was based on morphological and agronomical characteristics, differentiation of collected accessions by morphological and molecular markers, detection of genetic variation, and duplicates detection in bean landraces. The analysed 82 accessions of common bean (Phaseolus vulgaris L.) were collected in the Western andEastern Carpatien as landrace mixtures. Their seeds were segregated and pooled according to their characteristics; they were further multiplicated, and introduced into the collection. An extensive variation in plant and seed traits was discovered in thirty-three morphological and agronomical characteristics. Nevertheless, some of the accessions were identical in these characteristics. Cluster analysis grouped genotypes into two main branches, reflecting the growth type, seed size parameters, and thousand-seed weight. Molecular differentiation studies were performed by multilocus polymorphism detection in microsatellite and minisatellite DNA regions. Cluster analysis based on molecular data also grouped genotypes but no linkage to morphological traits was revealed. Bean accessions with very similar or identical morphological characters were clearly distinguished by DNA banding patterns. The presence of duplicates was excluded.  

Extraordinary circumstances: Covid-19 – Italian Serie A scenario

2021 ◽  
pp. 175433712110192
Author(s):  
Milan Radojicic ◽  
Aleksandar Djokovic ◽  
Nikola Cvetkovic
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Round Robin ◽  
The Past ◽  
Novel Approach ◽  
Round Robin Tournaments

Unpredictable and uncontrollable situations have happened throughout history. Inevitably, such situations have an impact on various spheres of life. The coronavirus disease 2019 has affected many of them, including sports. The ban on social gatherings has caused the cancellation of many sports competitions. This paper proposes a methodology based on hierarchical cluster analysis (HCA) that can be applied when a need occurs to end an interrupted tournament and the conditions for playing the remaining matches are far from ideal. The proposed methodology is based on how to conclude the season for Serie A, a top-division football league in Italy. The analysis showed that it is reasonable to play 14 instead of the 124 remaining matches of the 2019–2020 season to conclude the championship. The proposed methodology was tested on the past 10 seasons of the Serie A, and its effectiveness was confirmed. This novel approach can be used in any other sport where round-robin tournaments exist.

scholarly journals Sexual behaviour patterns and STI risk: results of a cluster analysis among men who have sex with men in Portugal

BMJ Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. e033290
Author(s):  
Karel Blondeel ◽  
Sonia Dias ◽  
Martina Furegato ◽  
Armando Seuc ◽  
Ana Gama ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Sexual Behaviour ◽  
Hierarchical Cluster ◽  
Risk Behaviour ◽  
Sexual Partners ◽  
Hiv Positive ◽  
Research Approach ◽  
Cross Sectional ◽  
Combination Prevention ◽  
Sex With Men

ObjectivesPortugal has the highest HIV incidence rate in Western Europe. The proportion assigned to sexual contact between men recently increased to more than 30% of all HIV infections. Men who have sex with men (MSM) are vulnerable to the acquisition of other sexually transmitted infections (STIs), increasing the per-contact risk of HIV infection. Building on syndemic theory, the aim of this analysis was to identify patterns of current sexual behaviour in MSM, and explore their relationship with self-reported current, past STI diagnoses and HIV positive serostatus.DesignA cross-sectional behavioural survey was conducted in Portugal among MSM, using a community-based participatory research approach. Hierarchical cluster analysis was used to identify patterns including behavioural and demographic factors.ResultsThe analysis resulted in six clusters. Three clusters showed higher rates of current STI diagnosis (ranging from 11.7% to 17.1%), past STI diagnosis (ranging from 25.5% to 41.5%) and HIV positive serostatus (ranging from 13.0% to 16.7%). From the three clusters scoring lower on current and past STI and HIV diagnoses, one was characterised by a high number of sexual partners (62% had more than 12 partners in the last year), a high proportion (94.6%) of frequent visits to gay venues to meet sexual partners and high alcohol use (46.1%). The other two clusters scored lower on high risk sexual behaviour.ConclusionFactors other than sexual behaviour appear to reinforce the vulnerability to STIs and HIV of some MSM in this study, suggesting a syndemic of STIs, HIV and other adverse conditions. More research is needed to better understand the drivers of the STI/HIV epidemic in Portuguese MSM, using a concept that goes beyond risk behaviour, to develop effective combination prevention interventions.

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