scholarly journals A comparison of demographic behaviour between the CR regions using multivariate statistical methods

2008 ◽  
Vol 56 (6) ◽  
pp. 103-112
Author(s):  
Marie Prášilová ◽  
Jan Grosz ◽  
Pavla Hošková
Keyword(s):  
Human Reproduction ◽  
Agglomerative Clustering ◽  
Biological Structure ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Selection Of Variables ◽  
Solution Selection ◽  
And Migration ◽  
Demographic Behaviour ◽  
Selection Of

The inhabitants of separate CR regions show varying demographic behaviour that presents itself in the demographic measures´ values. The paper offers a comparison of the development of selected measures of size and movement of the population in the regions of CR in 1993 and 2006 years. Attention is paid to the changes in measures of economic and biological structure, life expectancy and some of the measures of human reproduction, patterns of growth and migration. Multivariate analysis methods have been employed for the solution. Selection of variables has been carried out in each year using factor analysis and similarity of the regions has been described by the hierarchic agglomerative clustering method. During the thirteen years, changes occurred in demographic behaviour of the regions. Currently the Capital Prague and the Středočeský Region differ significantly. All the regions remaining have been stabilized as concerns the demographic measures and they show homogeneity.

scholarly journals Application of multivariate techniques in the evaluation of melt granulation products

2011 ◽  
Vol 47 (4) ◽  
pp. 733-741
Author(s):  
Ana Teresa Ochoa Andrade
Keyword(s):  
Principal Component ◽  
Manufacturing Processes ◽  
Multivariate Techniques ◽  
Efficient Production ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Compaction Behavior ◽  
And Cluster Analysis ◽  
Melt Granulation ◽  
Selection Of

In this work, principal component analysis and cluster analysis were applied as helping tools to extract useful information in the development of formulations and manufacturing processes of melt granulates. Two melt granulation processes that differ in the shear stress applied to the solid bed during melting step were designed. These processes employ equipment frequently used in the local pharmaceutical industry. The selected binders include both hydrophilic and hydrophobic excipients, which were used alone or in binary mixtures. Granulates were characterized regarding their physicomechanical properties, including their compaction behavior. The resulting tablets were also evaluated. The selected multivariate statistical methods proved to be useful in facilitating the interpretation of the collected data and the study of the properties of granulates and tablets, as well as the selection of more efficient production processes.

scholarly journals NONUNIFORM COURSE OF ACUTE PERIOD OF HEMORRHAGIC STROKE: ANALYSIS USING METHODS OF MULTIVARIATE STATISTICS

2021 ◽  
Vol 9 (1) ◽  
pp. 59-67
Author(s):  
I.S. Kurepina ◽  
◽  
R.A. Zorin ◽  
V.A. Zhadnov ◽  
O.A. Sorokin ◽  
...  
Keyword(s):  
Hemorrhagic Stroke ◽  
Dimensional Space ◽  
Expert Assessment ◽  
Multivariate Statistical ◽  
Acute Period ◽  
Canonical Correlations ◽  
Satisfactory Condition ◽  
Selection Of Variables ◽  
Expert Assessments ◽  
Selection Of

Background. Hemorrhagic stroke is an important medical and social problem both in the world and in the Russian Federation due to high parameters of morbidity, mortality and disability. Aim. To compare expert assessments and formalized multivariate statistical procedures in analysis of clinical inhomogeneity of patients with intracranial hematoma of supratentorial location. Materials and Methods. 75 Patients who took treatment in the neurovascular department of Ryazan Regional Clinical Hospital with the diagnosis of hemorrhagic stroke, were examined. Of them, there were 40 men and 35 women with the mean age 68.1 years. Results. Primarily, on the basis of expert assessments, the patients were divided to 2 groups: with unfavorable course and with relatively favorable course – satisfactory condition, regress of symptoms, recovery of the level of consciousness. In the first stage, in result of the primary expert assessment, the patients were divided to subgroups with favorable and unfavorable course. After that, significant for selection of groups variables were used in selection of clusters: method of hierarchial tree for determination of the number of groups; k-means method for identification of their elements. Discrimination analysis was used for selection of variables in NIHSS and GCS, and also for assessment of canonical correlations. After that, cluster analysis of NIHSS and GCS dynamics was conducted on the 1st, 3rd, 21st day for selection of groups in high-dimensional space of signs with exclusion of subjective expert assessments. Three main groups of patients were selected. In the second stage, in accordance with the number of groups, patients belonging to the corresponding clusters were identified using the k-means method. Cluster 1 included patients with a poor prognosis, clusters 2 and 3 suggested a more favorable course of the acute period with worse parameters in cluster 2. Conclusions. Use of discriminant functions confirms the role of severity of depression of consciousness and of the volume of hematoma in the unfavorable course.

scholarly journals AMMI VERSUS NONPARAMETRIC ANALYSIS FOR INVESTIGATION OF GE INTERACTION OF PLANT DISEASE EVALUATION

AGROFOR ◽  
2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Naser Sabaghnia
Keyword(s):  
Disease Severity ◽  
Plant Disease Resistance ◽  
Plant Disease ◽  
Gray Leaf Spot ◽  
Multivariate Statistical Methods ◽  
Ge Interaction ◽  
Multivariate Statistical ◽  
Stability Parameters ◽  
Multivariate Procedures ◽  
Selection Of

In breeding for plant disease resistance programs, a large number of new improvedgenotypes are tested over a range of test pathogens or environments and theunderlying statistics used to model this system may be rather complicated. Due toordinal nature of most measured traits of disease responses, some nonparametricmethods used for analyzing genotype × environment (GE) interaction in twodatasets for disease severity of gray leaf spot of maize (with ten genotypes plantedin 10 and 11 environments). Usually, the presence of the GE interaction effectcomplicates the selection of the most favorable genotypes and there are severalstatistical procedures available to analyze these dataset including a range ofunivariate, nonparametric and multivariate procedures. Present analysis separatednonparametric methods based on dynamic concept from those which are based onthe static type indicated that RS statistic following to S6, NP2, NP3 and RSstatistics were found to be useful in detecting the non-complicated phenotypicstability in disease severity dataset. In complicated GE interaction, the ability ofAMMI stability parameters especially SPC1, SPCF, D1, DF, EV1, EVF and ASVstatistics were high in the detection of stability in complicated GE interaction. Ingeneral, nonparametric methods are useful alternatives to parametric methods andallow drawing valid conclusions with considerably better chances of detecting theGE interaction in experiments of plant pathology. Also, in some cases the GEinteraction structure is too complex to be summarized by only one parameter andso, it is essential to use multivariate statistical methods like AMMI.

Long-term variations in individual particle types in the aerosol of Phoenix, Arizona, as determined using automated electron microprobe analysis and multivariate statistical techniques

1993 ◽  
Vol 51 ◽  
pp. 742-743
Author(s):  
Karen A. Katrinak ◽  
James R. Anderson ◽  
Peter R. Buseck
Keyword(s):  
Electron Microprobe ◽  
Fine Fraction ◽  
Coarse Fraction ◽  
Motor Vehicles ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
X Ray ◽  
Mineral Particles ◽  
Anthropogenic Air Pollutants

Aerosol samples were collected in Phoenix, Arizona on eleven dates between July 1989 and April 1990. Elemental compositions were determined for approximately 1000 particles per sample using an electron microprobe with an energy-dispersive x-ray spectrometer. Fine-fraction samples (particle cut size of 1 to 2 μm) were analyzed for each date; coarse-fraction samples were also analyzed for four of the dates.The data were reduced using multivariate statistical methods. Cluster analysis was first used to define 35 particle types. 81% of all fine-fraction particles and 84% of the coarse-fraction particles were assigned to these types, which include mineral, metal-rich, sulfur-rich, and salt categories. "Zero-count" particles, consisting entirely of elements lighter than Na, constitute an additional category and dominate the fine fraction, reflecting the importance of anthropogenic air pollutants such as those emitted by motor vehicles. Si- and Ca-rich mineral particles dominate the coarse fraction and are also numerous in the fine fraction.

Pollen morphology of some Tamarix (Tamaricaceae) species of Iran

2020 ◽  
Vol 62 (1-2) ◽  
pp. 151-161
Author(s):  
T. Shagholi ◽  
M. Keshavarzi ◽  
M. Sheidai
Keyword(s):  
North Africa ◽  
Pollen Grains ◽  
Ecological Niches ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Qualitative And Quantitative ◽  
Petal Length ◽  
Electron Microscopes ◽  
High Level ◽  
Scanning Electron Microscopes

Tamarix L. (Tamaricaceae) is a halophytic shrub in different parts of Asia and North Africa. Taxonomy and species limitation of Tamarix is very complex. This genus has three sections as Tamarix, Oligadenia, and Polyadenia, which are mainly separated by petal length, the number of stamens, the shape of androecial disk and attachment of filament on the androecial disk. As there was no palynological data on pollen features of Tamarix species of Iran, in the present study 12 qualitative and quantitative pollen features were evaluated to find diagnostic ones. Pollen grains of 8 Tamarix species were collected from nature. Pollen grains were studied without any treatment. Measurements were based on at least 50 pollen grains per specimen. Light and scanning electron microscopes were used. Multivariate statistical methods were applied to clarify the species relationships based on pollen data. All species studied showed monad and tricolpate (except some individuals of T. androssowii). Some Tamarix species show a high level of variability, in response to ecological niches and phenotypic plasticity, which make Tamarix species separation much more difficult. Based on the results of the present study, pollen grains features are not in agreement with previous morphological and molecular genetics about the sectional distinction.

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