Ecological patterns of diatom assemblages from Mackenzie Delta lakes, Northwest Territories, Canada

2000 ◽  
Vol 78 (1) ◽  
pp. 19-33 ◽  
Author(s):  
Murray B Hay ◽  
Neal Michelutti ◽  
John P Smol
Keyword(s):  
Correspondence Analysis ◽  
Partial Least Squares Regression ◽  
Detrended Correspondence Analysis ◽  
Mackenzie Delta ◽  
Least Squares Regression ◽  
Diatom Assemblages ◽  
Hydrological Variability ◽  
Ecological Patterns ◽  
Macrophyte Growth ◽  
Mackenzie River

Sediment samples were collected from 77 lakes in the Mackenzie Delta representing a gradient of lakes from those having continual connection with the sediment-laden Mackenzie River to lakes having connection for only a couple of days every few years. Diatom assemblages in all lakes were dominated by a diverse benthic microflora, primarily from the genera Navicula and Nitzschia. Maximum relative abundance of the dominant taxon at all sites was less than 30%, and most taxa did not dominate in more than one or two lakes. Delta lake assemblages were distinct from diatom assemblages associated with other regional transects of upland tundra and forest lakes. Detrended correspondence analysis showed that nonmotile epiphytic genera, such as Cocconeis and Gomphonema, were more common in lakes having a lower influence from the Mackenzie River, reflecting the extensive macrophyte growth within these lakes. Species diversity decreased as macrophyte production increased. Taxa responses along this macrophyte production gradient were modeled using partial least squares regression. Diatoms were sensitive to the degree of river influence, and the related biological and limnological changes, suggesting assemblages can provide an indication of hydrological variability within Mackenzie Delta lakes.Key words: diatoms, detrended correspondence analysis, Mackenzie Delta, floodplain, lakes.

Use of reflectance spectroscopy to estimate the organic carbon and CaCO3 contents of soils

2012 ◽  
Vol 61 (2) ◽  
pp. 277-290 ◽  
Author(s):  
Ádám Csorba ◽  
Vince Láng ◽  
László Fenyvesi ◽  
Erika Michéli
Keyword(s):  
Organic Carbon ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Mean Squared Error ◽  
Reflectance Spectroscopy ◽  
Least Squares Regression ◽  
Root Mean Squared Error ◽  
Squared Error

Napjainkban egyre nagyobb igény mutatkozik olyan technológiák és módszerek kidolgozására és alkalmazására, melyek lehetővé teszik a gyors, költséghatékony és környezetbarát talajadat-felvételezést és kiértékelést. Ezeknek az igényeknek felel meg a reflektancia spektroszkópia, mely az elektromágneses spektrum látható (VIS) és közeli infravörös (NIR) tartományában (350–2500 nm) végzett reflektancia-mérésekre épül. Figyelembe véve, hogy a talajokról felvett reflektancia spektrum információban nagyon gazdag, és a vizsgált tartományban számos talajalkotó rendelkezik karakterisztikus spektrális „ujjlenyomattal”, egyetlen görbéből lehetővé válik nagyszámú, kulcsfontosságú talajparaméter egyidejű meghatározása. Dolgozatunkban, a reflektancia spektroszkópia alapjaira helyezett, a talajok ösz-szetételének meghatározását célzó módszertani fejlesztés első lépéseit mutatjuk be. Munkánk során talajok szervesszén- és CaCO3-tartalmának megbecslését lehetővé tévő többváltozós matematikai-statisztikai módszerekre (részleges legkisebb négyzetek módszere, partial least squares regression – PLSR) épülő prediktív modellek létrehozását és tesztelését végeztük el. A létrehozott modellek tesztelése során megállapítottuk, hogy az eljárás mindkét talajparaméter esetében magas R2értéket [R2(szerves szén) = 0,815; R2(CaCO3) = 0,907] adott. A becslés pontosságát jelző közepes négyzetes eltérés (root mean squared error – RMSE) érték mindkét paraméter esetében közepesnek mondható [RMSE (szerves szén) = 0,467; RMSE (CaCO3) = 3,508], mely a reflektancia mérési előírások standardizálásával jelentősen javítható. Vizsgálataink alapján arra a következtetésre jutottunk, hogy a reflektancia spektroszkópia és a többváltozós kemometriai eljárások együttes alkalmazásával, gyors és költséghatékony adatfelvételezési és -értékelési módszerhez juthatunk.

Speech Emotion Recognition Based on Sparse Representation

2013 ◽  
Vol 38 (4) ◽  
pp. 465-470 ◽  
Author(s):  
Jingjie Yan ◽  
Xiaolan Wang ◽  
Weiyi Gu ◽  
LiLi Ma
Keyword(s):  
Dimensionality Reduction ◽  
Emotion Recognition ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Speech Emotion Recognition ◽  
Least Squares Regression ◽  
Computer Science Pedagogy ◽  
Reduction Methods ◽  
Analysis Computer

Abstract Speech emotion recognition is deemed to be a meaningful and intractable issue among a number of do- mains comprising sentiment analysis, computer science, pedagogy, and so on. In this study, we investigate speech emotion recognition based on sparse partial least squares regression (SPLSR) approach in depth. We make use of the sparse partial least squares regression method to implement the feature selection and dimensionality reduction on the whole acquired speech emotion features. By the means of exploiting the SPLSR method, the component parts of those redundant and meaningless speech emotion features are lessened to zero while those serviceable and informative speech emotion features are maintained and selected to the following classification step. A number of tests on Berlin database reveal that the recogni- tion rate of the SPLSR method can reach up to 79.23% and is superior to other compared dimensionality reduction methods.

Multivariate micropollutants analysis in marine waters

1995 ◽  
Vol 32 (9-10) ◽  
pp. 341-348
Author(s):  
V. Librando ◽  
G. Magazzù ◽  
A. Puglisi
Keyword(s):  
Multivariate Data Analysis ◽  
Partial Least Squares Regression ◽  
Environmental Chemistry ◽  
Sampling Site ◽  
Principal Component ◽  
Least Squares Regression ◽  
Organic Micropollutants ◽  
Suspended Material ◽  
The Difference

The monitoring of water quality today provides a great quantity of data consisting of the values of the parameters measured as a function of time. In the marine environment, and especially in the suspended material, increasing importance is being given to the presence of organic micropollutants, particularly since some are known to be carcinogenic. As the number of measured parameters increases examining the data and their consequent interpretation becomes more difficult. To overcome such difficulties, numerous chemometric techniques have been introduced in environmental chemistry, such as Multivariate Data Analysis (MVDA), Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR). The use of the first technique in this work has been applied to the interpretation of the quality of Augusta bay, by measuring the concentration of numerous organic micropollutants, together with the classical water pollution parameters, in different sites and at different times. The MVDA has highlighted the difference between various sampling sites whose data were initially thought to be similar. Furthermore, it has allowed a choice of more significant parameters for future monitoring and more suitable sampling site locations.

Photochemical stability of warfarin potassium in powdered pharmaceutical tablets

2021 ◽  
Vol 32 (2) ◽  
pp. 115-129
Author(s):  
Emi Horiguchi-Babamoto ◽  
Makoto Otsuka
Keyword(s):  
High Performance ◽  
Partial Least Squares Regression ◽  
Pediatric Patients ◽  
Reversed Phase ◽  
Least Squares Regression ◽  
Brand Name ◽  
Pharmaceutical Tablets ◽  
Light Stability ◽  
Warfarin Potassium ◽  
The Stability

BACKGROUND: Warfarin potassium (Wf) commercial tablets originally formulated for adults are ground before administration to pediatric patients and elderly patients with dysphagia. OBJECTIVE: The present study investigated the effect of tablet grinding on the photostability of four types of commercial Wf tablets and predicted the photostability of the tablet powders by chemometric analysis. METHODS: The photodegradation of Wf content was evaluated by reversed-phase column high-performance liquid chromatography with ultraviolet (HPLC-UV). RESULTS: The bulk Wf powder was relatively photostable, whereas ground Wf tablets underwent substantial photodegradation. The photostability of the ground powders of a brand-name Wf commercial tablet and three generic Wf commercial tablets was quantitatively assessed and compared. In certain cases, the Wf in all the three ground generic tablets was less photostable than in the ground brand-name tablets. After 28 days of light irradiation, the Wf content decreased to 69.79% in the brand-name tablets, while it was 31.90% in some generic tablets. To clarify the factors influencing the relative photostability in various Wf formulations, we analyzed the intermolecular interactions between the active ingredient and the excipients by partial least-squares regression analysis based on photostability screening for each additive. CONCLUSION: The results suggested that the additives light anhydrous silicic acid and povidone adversely affect the stability of Wf tablets. In addition, the light stability of ground tablets was affected considerably by their formulation.

scholarly journals Rapid tannin profiling of tree fodders using untargeted mid-infrared spectroscopy and partial least squares regression

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Jordi Ortuño ◽  
Sokratis Stergiadis ◽  
Anastasios Koidis ◽  
Jo Smith ◽  
Chris Humphrey ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Multivariate Calibration ◽  
Plant Ecology ◽  
Coefficient Of Determination ◽  
Least Squares Regression ◽  
Mid Infrared ◽  
Mid Infrared Spectroscopy

Abstract Background The presence of condensed tannins (CT) in tree fodders entails a series of productive, health and ecological benefits for ruminant nutrition. Current wet analytical methods employed for full CT characterisation are time and resource-consuming, thus limiting its applicability for silvopastoral systems. The development of quick, safe and robust analytical techniques to monitor CT’s full profile is crucial to suitably understand CT variability and biological activity, which would help to develop efficient evidence-based decision-making to maximise CT-derived benefits. The present study investigates the suitability of Fourier-transformed mid-infrared spectroscopy (MIR: 4000–550 cm−1) combined with multivariate analysis to determine CT concentration and structure (mean degree of polymerization—mDP, procyanidins:prodelphidins ratio—PC:PD and cis:trans ratio) in oak, field maple and goat willow foliage, using HCl:Butanol:Acetone:Iron (HBAI) and thiolysis-HPLC as reference methods. Results The MIR spectra obtained were explored firstly using Principal Component Analysis, whereas multivariate calibration models were developed based on partial least-squares regression. MIR showed an excellent prediction capacity for the determination of PC:PD [coefficient of determination for prediction (R2P) = 0.96; ratio of prediction to deviation (RPD) = 5.26, range error ratio (RER) = 14.1] and cis:trans ratio (R2P = 0.95; RPD = 4.24; RER = 13.3); modest for CT quantification (HBAI: R2P = 0.92; RPD = 3.71; RER = 13.1; Thiolysis: R2P = 0.88; RPD = 2.80; RER = 11.5); and weak for mDP (R2P = 0.66; RPD = 1.86; RER = 7.16). Conclusions MIR combined with chemometrics allowed to characterize the full CT profile of tree foliage rapidly, which would help to assess better plant ecology variability and to improve the nutritional management of ruminant livestock.

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