La végétation des combes à neige du golfe de Richmond, Québec nordique

1986 ◽  
Vol 64 (8) ◽  
pp. 1515-1524 ◽  
Author(s):  
Hubert Morin ◽  
Serge Payette
Keyword(s):  
Principal Component Analysis ◽  
Altitudinal Gradient ◽  
Principal Component ◽  
Hudson Bay ◽  
Snow Melt ◽  
Principal Factors ◽  
Vegetation Characteristics ◽  
Abiotic Variables

An exhaustive survey of snow patches, along an altitudinal gradient situated in an area of about 10 km2 along the Hudson Bay highlands, underlines the role of altitude, exposition, and topography in maintaining these habitats. The principal component analysis from a stratified sampling of the snow patches in the three cuesta lithological zones (arkose, dolomite, and basalt) stresses the effect of the snow melt gradient on species distribution within a snow patch. The ordination of abiotic variables performed on the ordination frame of snow patches shows that lithology and substratum are the principal factors responsible for the vegetation characteristics, allowing the determination of two main types of snow patches in the arkose and dolomite zones and three types in the basalt zone.

Determination of Agarwood oil’s significant chemical compounds using principal component analysis

2020 ◽  
Author(s):  
Mohamad Hushnie Haron ◽  
Mohd Nasir Taib ◽  
Nurlaila Ismail ◽  
Nor Azah Mohd Ali ◽  
Saiful Nizam Tajuddin
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Chemical Compounds ◽  
Component Analysis ◽  
Significant Chemical

scholarly journals The lung microbiota in Korean patients with non-tuberculous mycobacterial pulmonary disease

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sung-Yoon Kang ◽  
Hyojung Kim ◽  
Sungwon Jung ◽  
Sang Min Lee ◽  
Sang Pyo Lee
Keyword(s):  
Principal Component Analysis ◽  
Respiratory Tract ◽  
Pulmonary Disease ◽  
Beta Diversity ◽  
Lower Respiratory Tract ◽  
Principal Component ◽  
Control Group ◽  
Flexible Bronchoscope ◽  
Bronchial Washing

Abstract Background The microbiota of the lower respiratory tract in patients with non-tuberculous mycobacterial pulmonary disease (NTM-PD) has not been fully evaluated. We explored the role of the lung microbiota in NTM-PD by analyzing protected specimen brushing (PSB) and bronchial washing samples from patients with NTM-PD obtained using a flexible bronchoscope. Results Bronchial washing and PSB samples from the NTM-PD group tended to have fewer OTUs and lower Chao1 richness values compared with those from the control group. In both bronchial washing and PSB samples, beta diversity was significantly lower in the NTM-PD group than in the control group (P = 2.25E-6 and P = 4.13E-4, respectively). Principal component analysis showed that the PSBs and bronchial washings exhibited similar patterns within each group but differed between the two groups. The volcano plots indicated differences in several phyla and genera between the two groups. Conclusions The lower respiratory tract of patients with NTM-PD has a unique microbiota distribution that is low in richness/diversity.

scholarly journals A-49 Visual Memory Errors and Intelligence: The Role of Verbal Mediation

2019 ◽  
Vol 34 (6) ◽  
pp. 908-909
Author(s):  
K Hakinson ◽  
J Moses ◽  
J RIvera ◽  
A Guerra ◽  
M Davis ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Perceptual Organization ◽  
Visual Memory ◽  
Principal Component ◽  
Component Analysis ◽  
Spoken Language ◽  
Verbal Mediation ◽  
Memory Errors ◽  
Shared Variance

Abstract Objective Examine the relationship of verbal mediation with visual memory errors and intelligence to understand the role of spoken language on other assessment measures. Method Assessment records were obtained from a Veteran Affairs clinic for veterans (n=100) with diverse neuropsychiatric conditions who completed the Wechsler Adult Intelligence Scale, third edition (WAIS-III), Multilingual Aphasia Examination (MAE), and Benton Visual Retention Test (BVRT). A Principal Component Analysis (PCA) was used to examine the interrelationship among these assessments. The components of spoken language, types of errors on the BVRT, and the four factors of the WAIS-III were factored using the PCA to identify common sources of variance. Results A principal component analysis revealed a six-factor model explaining 68.16% of the shared variance among the WAIS-III factors, MAE components, and BVRT Errors. Omission errors loaded with Processing Speed and Controlled Word Association. Distortions and size errors loaded with Perceptual Organization. Size errors also loaded with Verbal Comprehension and Visual Naming. Misplacements loaded with Working Memory and Sentence Repetition. Misplacements, perseverations, and omissions loaded with the Token Test (a measure associated with auditory comprehension). Rotation errors loaded with Perceptual Organization. Conclusions Results indicated significant shared variance between visual memory errors, spoken language, and intelligence factors. This suggests that spoken language is involved in the process of visual memory, and deficits in spoken language may result in increased errors on visual memory tasks. Therefore, treatment recommendations for visual memory difficulties should take into consideration verbal capabilities and intelligence factors to better individualize treatment.

Chemometric Approach to a Rapid Attenuated Total Reflection Fourier Transform Infrared Analysis of Complex Heroin-Based Mixtures

2020 ◽  
pp. 000370282096971
Author(s):  
Nataša Radosavljević Stevanović ◽  
Milena Jovanović ◽  
Federico Marini ◽  
Slavica Ražić
Keyword(s):  
Principal Component Analysis ◽  
Fourier Transform ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Total Reflection ◽  
Attenuated Total Reflection ◽  
Illegal Market ◽  
Ft Ir

Heroin is one of the most frequently seized drugs in Southeastern Europe. Due to the position in the Balkan route, the Republic of Serbia keeps important role in suppression of the trafficking of heroin for domestic and foreign illegal market. This research is aimed to provide a good scientific approach in the field of seized heroin analysis. Two different forms of heroin are present in the illegal market, mostly in mixtures with typical “cutting” agents: caffeine, paracetamol, and sugars. It was observed that the quantity of pure heroin in seized samples slightly increases from year to year. The aim of this study was to produce a reliable and fast procedure for classification of illicit heroin samples and determination of the concentration range of heroin in the samples. For that purpose, the attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) technique was used and combined with such chemometric methods as principal component analysis, cluster analysis, and partial least squares. Principal component analysis (PCA) as an unsupervised model was used for exploratory purposes to identify trends, similarities, and differences between samples by reducing the dimensionality of the data. The cluster classification of examined samples turned out to be extremely useful to evaluate the possibilities of the ATR FT-IR technique to classify the samples appropriately into the patterns, the constituted clusters. Additionally, partial least square was the suitable method for the purpose of determination of the heroin hydrochloride concentration range in examined samples. It is proved that the joined application of spectroscopy and chemometrics can be extremely convenient and useful for forensic and drugs control laboratories.

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