Principal Composition Analysis Research Articles

Side chain of confined xylan affects cellulose integrity leading to bending stem with reduced mechanical strength in ornamental plants

The stem support for fresh-cut flowers exerts a profound influence on the display of their blossoms. During vase insertion, bending stems significantly affect the ornamental value, but much remains unclear about the underlying reasons. In this study, six pairs of ornamental plants were screened for the contrast of bending and straight stems. The bending stems have weakened mechanical force and biomass recalcitrance compared with the straight ones. Meanwhile, cells in the bending stems became more loosely packed, along with a decrease in cell wall thickness and cellulose levels. Furthermore, wall properties characterizations show bending stems have decreased lignocellulosic CrI and cellulose DP, and enhanced the branching ratio of hemicellulose which is trapped in the cellulose. Given the distinct cell wall factors in different species, all data are grouped in standardized to eliminate the variations among plant species. The principal composition analysis and correlation analysis of the processed dataset strongly suggest that cellulose association factors determine the stem mechanical force and recalcitrance. Based on our results, we propose a model for how branches of confined hemicellulose interacted with cellulose to modulate stem strength support for the straight or bending phenotype in cut flowers.

The effects of prevalence of inequalities in mental disorders between groups using Blinder- Oaxaca decomposition.

The prevalence of inequalities in sociodemographic factors in some mental disorders (MDs) has been shown in previous reports. The aim of this study was to assess the main contributors that affected prevalence of inequalities in MDs between groups. This was a cross-sectional study that was conducted on adults in 10 cities from Ilam province. We selected participants using cluster sampling; clusters were cities (n1 = 10), geographical area (n2 = 153), and households (n3 = 382). Screening tools and clinical interview were applied through standardized and validated questionnaires, namely, GHQ-28 and DSM-IV-TR, respectively. Participants were divided into socioeconomic groups via principal composition analysis (PCA). Blinder-Oaxaca approach was applied to distinguish the gap in inequalities between groups. The prevalence of MDs in the advantage group was 22.6% and, in disadvantages was 35.6%. The concentration index (CI) of the MD prevalence rate was -0.013 (95% CI: -0.022, -0.004) which indicated that MDs were more common in the disadvantaged groups. The odds of MDs in advantaged people was 81% more compared to the disadvantaged group (OR: 1.81; 95% CI: 1.28, 2.57), also in females compared to males (1.60; 95% CI: 1.21, 2.24). Analysis of gap inequality between groups showed that the gap in prevalence rates of MDs between groups was 12%. This study revealed a socioeconomic inequality in MD rates in the adult population. Therefore, results of this study provide contributors in MDs inequality in order to control and reduce the prevalence of MDs in the community.

Effects of Financial Inclusion on Economic Growth, Poverty, Sustainability, and Financial Efficiency: Evidence from the G20 Countries

The main purpose of this study is to scrutinize the effect of financial inclusion on financial sustainability, financial efficiency, gross domestic product, and human development in the context of G20 nations. This study has employed annual data of 15 developed and emerging economies during the period from 2004 to 2017. The current study has utilized a single index for financial inclusion, financial sustainability, and financial efficiency by employing principal composite analysis (PCA). The outcomes of the panel stationarity test confirmed the ARDL model for both the long and short runs. Equally, the findings of the ARDL Model 1 showed no association between financial inclusion and financial sustainability in the short run, however, in the long run, inclusive finance showed a significant impact on sustainability. Likewise, the ARDL Model 2 showed that financial inclusion has no effect on efficiency in the short run, while it positively influenced financial efficiency in the long run. The results of the ARDL Model 3 are also similar to Models 1 and 2 where inclusive finance showed no effect on poverty in the short run, but a significant effect in long run. Similarly, the ARDL Model 4 also presented no association between GDP and inclusive finance in the short run, while it showed significant relationships in the long run. Moreover, the outcomes of the GMM Model 1 showed a significant impact of inclusive finance on financial stability, and these results were similar to the GMM Model 2 between financial inclusion and financial efficiency. Additionally, GMM Models 3 and 4 have shown that inclusive finance has a statistically significant impact on poverty and economic expansion, respectively. The outcomes of this article are essential for policymakers, academics, regulators, and practitioners with valuable and convincing debate over financial inclusion, economic growth, poverty, sustainability, and financial efficiency.

Assessing energy security in Africa based on multi-dimensional approach of principal composite analysis.

The concept of energy securityhas become an increasingly challenging issue in Africa, forcing energy-deficient countries to forge mutual partnerships with energy sufficient countries to access it for their domestic consumption. This study formulates a composite index of energy security in Africa as well as evaluates its impacts and trends using a sample of 28 countries on the continent, during the 2000-2018 period by using a principal composite factor analysis (PCA), with the series of 13 variables. Further interpretation was carried out using these tests: Kaiser-Meyer-Olkin measure of sampling adequacy and Bartlett's test of sphericity, Pearson correlation test, and Cronbach's alpha test. The key results show a trend of energy insecurity among the countries studied, as energy imports loads high in most countries as well as per capita emission, together with fossil fuel source consumption correlating high. These results validate the stark reality on the African continent. The inference from the results of the anaylsis conclude that the principal component analysis (PCA) results of the energy index were considered fit and reliable for the analysis, with the most important Cronbach's alpha test coefficient of 0.8797, far above the standard 0.6 model reliability level. Based on this study, the paper proffers there should be increased intra-regional trading of energy among the various power pools on the continent and increased regional renewable energy investments as well as investment in energy infrastructure, measures to reduce electricity system losses, environmental sustainability, and the adoption of energy in efficiency on the continent.

Can financial inclusion be an effective mitigation measure? evidence from panel data analysis of the environmental Kuznets curve

This study demonstrates the existence of financial inclusion-based environment Kuznets curve (EKC) by analyzing a panel of 103 countries during 2004–2014. The relationship between financial inclusion and CO2 emissions is found to be an inverted U-shape. This finding is robust to different measurements of the financial inclusion index constructed by principal composite analysis and modifications of the estimation model. The existence of a financial inclusion-based EKC provides an important policy insight that financial inclusion can be used as a mitigation measure. Therefore, policy makers should consider the synergy effect of financial inclusion in designing development and climate change policies.

Quality characteristics and evaluation for sponge cakes made of rice flour

Indica rice, japonica rice, and glutinous rice flour were used as raw material to substitute 25%, 50%, 75%, and 100% (w/w) of low-gluten flour to make sponge cakes. The influence of the types and dosages of rice flour on the 12 quality indicators of sponge cakes made of rice flour was evaluated. Results showed that indica rice flour would increase the specific volume of the cakes, japonica rice flour would increase moisture and decrease the specific volume, while glutinous rice flour would decrease the specific volume, hardness and resilience, but enhance the adhesiveness. The cakes made of 75% glutinous rice flour had the highest sensory score at 7.78. A comprehensive model of principal composition analysis was developed and the first principal component factor had the highest correlation to the total sensory score of the cakes. The proposed model based on the principal component analysis was feasible and convenient in evaluating the cake quality. Practical applications This study provides a method for evaluating the edible quality of sponge cake made of rice fours based on the principal component analysis, having reference value to increasing the added value for (broken) rice via the transformation into bakery products like sponge cake. In addition, the establishment of quality evaluation models contributes to predict the acceptability of the cakes before they are made industrially.

Computational Geometric Analysis for <i>C. elegans</i> Trajectories on Thermal and Salinity Gradient

Elegans are one of the best model organisms in neural researches, and tropism movement is a typical learning and memorizing activity. Based on one imaging technique called Fast Track-Capturing Microscope (FTCM), we investigated the movement regulation. Two movement patterns are extracted from various trajectories through analysis on turning angle. Then we applied this classification on trajectory regulation on the compound gradient field, and theoretical results corresponded with experiments well, which can initially verify the conclusion. Our breakthrough is performed computational geometric analysis on trajectories. Several independent features were combined to describe movement properties by principal composition analysis (PCA) and support vector machine (SVM). After normalizing all data sets, no-supervising machine learning was processed along with some training under certain supervision. The final classification results performed perfectly, which indicates the further application of such computational analysis in biology researches combining with machine learning.

Quality assessment of Indian rice varieties, evaluation of its relationship with their Glycemic index

The preference for a particular rice quality trait varies regionally, with the shift of choice towards better quality varieties. The qualitative properties namely amylose content, gelatinization temperature, hardness and Glycaemic Index (GI) were studied. Eight rice varieties (Basmati, Non-Basmati, Parboiled) 1121 Mini Sella Mogra (1121 MSM), Mini Sella Mogra (MSM), Noorjahan Basmati (NB), White Sella Dubar (WSD), Golden Sella (GS), Parmal Sella (PSe), Parmal Silky (PSi), Hari Bhari Parmal Sella (HBPS) were selected. Amylose content were highest in WSD (41 ± 0.05%) and PSe (40.99 ± 0.02%). Onset temperature during gelatinization was high in NB (98.28 ± 0.28 °C) and PSe (95.54 ± 0.47 °C). PSe showed the highest positive cycle peak in texture profile analysis (hardness 3900 ± 41 g) while least in PSi (1300.09 ± 0.64 g). GI was lowest of WSD and PSe (GI ~ 41). A positive correlation was found between amylose content, hardness and gelatinization temperature, which inversely related to GI. Principal Composition Analysis (PCA) has generated PC1 (55.68%) and PC2 (26.26%), the two principal components describing total 82.12% of data distribution. The Agglomerative hierarchical clustering divided all the samples into three clusters (C1–C3), based on percentage contribution. PSe was found to be best with high amylose percentage (40.99 ± 0.02%), high onset gelatinization temperature (95.54 ± 0.47 °C), maximum hardness (3900 ± 41 g) and low GI (GI ~ 41).

Identification of quality markers of Xiaojin Pills using a combination of high-performance liquid chromatographtandem mass spectrometry and multivariate analysis

Purpose: To establish an appropriate quality control method for Xiaojin pills using high-performance liquid chromatograph-tandem mass spectrometry combined with multivariate analysis.Methods: High-performance liquid chromatograph-tandem mass spectrometry was established to detect and quantify 13 chemical components of Xiaojin Pills. In order to evaluate the quality difference between diverse specimens of Xiaojin Pills, several multivariate statistical techniques were applied to analyze the dissimilarity between different batches of samples, including principal composition analysis method and clustering methodology.Results: Five chemical components were identified as primary quality markers, which can be used to accurately distinguish various samples and command the quality of Xiaojin Pills.Conclusion: The results afford a professionally scientific basis for the quality monitoring of Xiaojin Pills and also furnishes reasonable ideas and suggestions for the quality control of other traditional drugs.Keywords: Xiaojin Pills, HPLC-MS/MS, Quality control, Chemometrics, Quality markers

Polyphenolic profile of Cichorium intybus L. endemic varieties from the Veneto region of Italy

The present study was aimed at the investigation, through HPLCDAD-ESI-MS/MS, of polyphenols in seven autochthonous C. intybus varieties, already known from literature to contain various substances with antioxidant properties, from the Veneto region of Italy, namely 'Castelfranco', 'Chioggia', 'Rosa di Gorizia', 'Rosa di Verona', 'Treviso Precoce', 'Treviso Tardivo' and 'Verdon da Cortèl'. Thirteen polyphenols, belonging to hydroxycinnamic acid, flavone, flavonol and anthocyanin classes, were detected in most samples. The developed analytical method was validated in agreement with ICH guidelines. The total amount of polyphenols ranged from 52 to 386 (mean: 254) mg/100g fresh weight (F.W.). The results were further confirmed by Principal Composition Analysis (PCA), which highlighted peculiar features and similarities among analysed samples for each variety (except for 'Chioggia' samples). The developed method is suitable for routine analyses, as well as geographical characterization, selection of different C. intybus varieties and for the determination of related polyphenols dietary recommended intakes.

Antioxidant capacity and major polyphenol composition of teas as affected by geographical location, plantation elevation and leaf grade

Tea polyphenols have been a topic of discussion due to their health benefits. Nevertheless, detailed studies on the antioxidant capacity and polyphenol contents of teas in relation to factors including geographical locations, plantation elevations and leaf grades have been limited. In this study, 53 tea samples were analysed to determine the individual and total catechin and theaflavin contents by HPLC and the total antioxidant capacity by Oxygen Radical Absorbance Capacity (ORAC) methods. Results show that the polyphenol (catechins and theaflavins) contents were significantly influenced by plantation location. Black tea from low plantation elevation contained 22–28% more polyphenols than those from high elevation. Small tea leaves had up to 15% more polyphenols than larger leaves from similar elevation. The results were further confirmed by Principal Composition Analysis (PCA), which grouped the black and green tea samples into 3 different clusters, respectively.

THE DYNAMIC MONITORING OF RURAL RESIDENTIAL LAND IN BEIJING AND DRIVING FORCE ANALYSIS BASED ON MULTI-SOURCE REMOTE SENSING DATA

Based on remote sensing and GIS technology,the authors extracted Beijing rural residential land by using multi-source remote sensing data(MSS Landsat images,TM or ETM+ image,"Beijing 1" small satellite data).The status of Beijing occupied residential land in 2005 was fully analyzed by referring to the DEM data.The districts of Beijing were reclassified by improving the traditional method for defining the geographical borderline.Beijing rural residential land was dynamically monitored in three periods(1980~1995,1995~2000,and 2000~2005).Some indices were used to analyze the spatial-temporal and landscape characteristics of rural residential land in Beijing.14 social economic indices were chosen to analyze the driving forces that affect the change of rural residential land by using the principal composition analysis method.The results of this study can play a guiding role in rural reasonable planning.