scholarly journals Sedimentary nitrogen fractions and source assignment from different inflows to a receiving lake

2020 ◽  
Vol 20 (5) ◽  
pp. 1950-1964
Author(s):  
Xiaojun Li ◽  
Yanping Zhao ◽  
Guoxiang Wang ◽  
Ruiming Han ◽  
Xinyi Dang ◽  
...  
Keyword(s):  
Total Nitrogen ◽  
Quantitative Estimation ◽  
Lake Taihu ◽  
Principal Component ◽  
Nitrogen Loading ◽  
Limiting Factors ◽  
Phosphorus Loading ◽  
Estimation Model ◽  
Significant Difference ◽  
Pca Method

Abstract The spatial distribution of the sediment nitrogen in ten typical estuaries of Lake Taihu was determined. A simple quantitative estimation model and principal component analysis (PCA) method were applied to find the source and major factors of estuarine sediment nitrogen loading. The average concentrations of total nitrogen (TN), organic nitrogen (Org-N), ammonium nitrogen and nitrate-nitrogen in the sediments of the ten estuaries were 1315.5, 1220.1, 82.53 and 6.45 mg/kg, with the organic fraction dominating. Results showed a significant difference for the TN concentration in sediments of different estuaries, which was mainly caused by geographical location, land use type and vegetation restoration measures. An important result was that sediment nitrogen in 80% of the estuaries was mainly originated from autochthonous algae and presettled organic matter, although there has been continuous pollution input from inflow rivers. The source estimation results found that the autochthonous aquaculture excretion, algae and hydrophyte debris and buried biodetritus accounted for 58.9% of the total nitrogen loading, which dominated the nitrogen sources compared with the pollution input. In addition, the PCA method was used to find that phosphorus loading and redox conditions were the major limiting factors affecting the distribution of inorganic and , respectively.

scholarly journals Range of soil and climate characteristics appropriate for Pistacia atlantica forest development and rehabilitation (case study: Fars province, Iran)

2017 ◽  
Vol 32 (1) ◽  
pp. 71-78 ◽  
Author(s):  
Masoud Nejabat ◽  
Mohammadreza Negahdarsaber ◽  
Gholamreza Ghahari
Keyword(s):  
Soil Depth ◽  
Principal Component ◽  
Soil Characteristics ◽  
Limiting Factors ◽  
Soil Conditions ◽  
Fars Province ◽  
Pistacia Atlantica ◽  
Pca Method ◽  
Physical And Chemical

Abstract Investigation of ranges of soil and climate characteristics appropriate for the tolerant species: Pistacia atlantica subsp. mutica according to field study was the main objective of this research. This study was carried out based on random sampling across 20×20 km wild pistachio forests of Fars province (Iran). Results showed that mountainous and hilly lands are the main land types that pistachio species have evolved on. Statistical analysis of physical and chemical soil characteristics based on principal component analysis (PCA) method showed that wide ranges in soil characteristics, even up to about 40% differentiation in some measured properties, did not restricts this subspecies natural growth. The main growth limiting factors were shallow soil depth and light soil texture that decreased storage capacity of soil moisture, necessary for wild pistachios survival during drought and long dry periods. Climatic elements were analysed through the same approach and showed that temperature, precipitation and wind with overall variability of 85.9% were the most effectual factors. Pistacia atlantica subsp. mutica is one of the species refractory to various soil conditions and adapted to weak soils for the establishment and rehabilitation of forests in semi-arid regions.

scholarly journals Volatile components obtained from oolong teas and preliminary evaluation on consumer preferences for these products

2018 ◽  
Vol 1 (2) ◽  
pp. 21-28
Author(s):  
Thanh Hai Phan Thi ◽  
To Quynh Cung Thi ◽  
◽  
Keyword(s):  
Solid Phase ◽  
Consumer Preferences ◽  
Principal Component ◽  
Consumer Preference ◽  
Volatile Components ◽  
Preliminary Evaluation ◽  
Significant Difference ◽  
Linalool Oxide ◽  
Pca Method ◽  
Consumer Preference Analysis

Six types of oolong tea products from four different regions were investigated. Their volatile components were obtained by Solid Phase Microextraction (SPME) method and analyzed by GC – MS. Results showed that hexanal (ranged from 1.08-1.52%), 6-methyl-5-hepten-2-one (0.55-4.30%), (Z)-linalool oxide (5.44-17.95%), (E)-linalool oxide (4.86-12.13%), linalool (1.23-8.26%), epoxylinalool (0.80-1.16%) and methyl salicylate (0.70-2.51%) could be identified as the major compounds of all six tea products. These products were also classified into 3 groups based on their volatile compositions by Principal Component Analysis (PCA) method. The consumer preference analysis (n = 84) showed a significant difference in odor preference levels of these products.  

scholarly journals Inertial Sensor-Based Step Length Estimation Model by Means of Principal Component Analysis

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3527
Author(s):  
Melanija Vezočnik ◽  
Roman Kamnik ◽  
Matjaz B. Juric
Keyword(s):  
Principal Component Analysis ◽  
Human Body ◽  
Inertial Sensor ◽  
Principal Component ◽  
Step Length ◽  
Component Analysis ◽  
Indoor Positioning ◽  
Estimation Model ◽  
Length Estimation ◽  
Proposed Model

Inertial sensor-based step length estimation has become increasingly important with the emergence of pedestrian-dead-reckoning-based (PDR-based) indoor positioning. So far, many refined step length estimation models have been proposed to overcome the inaccuracy in estimating distance walked. Both the kinematics associated with the human body during walking and actual step lengths are rarely used in their derivation. Our paper presents a new step length estimation model that utilizes acceleration magnitude. To the best of our knowledge, we are the first to employ principal component analysis (PCA) to characterize the experimental data for the derivation of the model. These data were collected from anatomical landmarks on the human body during walking using a highly accurate optical measurement system. We evaluated the performance of the proposed model for four typical smartphone positions for long-term human walking and obtained promising results: the proposed model outperformed all acceleration-based models selected for the comparison producing an overall mean absolute stride length estimation error of 6.44 cm. The proposed model was also least affected by walking speed and smartphone position among acceleration-based models and is unaffected by smartphone orientation. Therefore, the proposed model can be used in the PDR-based indoor positioning with an important advantage that no special care regarding orientation is needed in attaching the smartphone to a particular body segment. All the sensory data acquired by smartphones that we utilized for evaluation are publicly available and include more than 10 h of walking measurements.

scholarly journals Inhibition of Kynurenine Metabolism and Its Effect in Mitochondrial Function in Hepatocellular Carcinoma

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 124-125
Author(s):  
Raul Castro-Portuguez ◽  
Samuel Freitas ◽  
George Sutphin
Keyword(s):  
Hepatocellular Carcinoma ◽  
Mitochondrial Function ◽  
De Novo ◽  
Principal Component ◽  
Kynurenine Pathway ◽  
The Cancer Genome Atlas ◽  
Wilcoxon Test ◽  
Nad Synthesis ◽  
Significant Difference ◽  
Kynurenine Metabolism

Abstract Hepatocellular carcinoma (HCC) is the most prevalent cancer in the liver. The majority of ingested tryptophan is processed in the liver through the kynurenine pathway, the endpoint of which is de novo NAD+ biosynthesis. Dysregulation of tryptophan-kynurenine metabolism and NAD+ synthesis may promote mitochondrial malfunction, tumor reprogramming, and carcinogenesis. Using a publicly available gene expression dataset from liver hepatocellular carcinoma (LIHC) samples available through The Cancer Genome Atlas (TCGA; n = 371), we employed Principal Component Analysis (PCA), hierarchical clustering, gene-pattern expression profiling, and survival analysis to cluster patients and determine overall survival. Our analysis of genes encoding kynurenine pathway enzymes determined that patients with high QPRT expression had a poor prognosis with decreased median survival, with no effect on the maximum survival. There is a significant difference in the survival between patients with high QPRT expression relative to patients with high HAAO/AFMID expression (HR = 1.2, [95% CI 0.5-1.8] P = 0.0181, Gehan-Breslow-Wilcoxon Test). Patients with high QPRT expression have higher survival rates compared with low QPRT expression (HR = 1.4, [95% CI 0.9-2.2] P = 0.0344, Gehan-Breslow-Wilcoxon Test). To test the consequences of kynurenine-pathway inhibition in mitochondrial function and morphology we use 4-Cl-3HAA, an irreversible HAAO inhibitor, and observed a small increase in mitochondrial fragmentation in HepG2 cells after 24 hours of treatment. We conclude that kynurenine metabolism may be useful as a biomarker to predict patient prognosis among HCC patients. In ongoing work, we are testing QPRT inhibitors in cell culture as a potential adjuvant for chemotherapies.

The Design of Index about Corporate Governance Based on PCA Method

2014 ◽  
Vol 926-930 ◽  
pp. 4085-4088
Author(s):  
Chuan Jun Li
Keyword(s):  
Principal Component Analysis ◽  
Corporate Governance ◽  
Principal Components ◽  
Principal Component ◽  
Component Analysis ◽  
Contribution Rate ◽  
Variance Contribution ◽  
Pca Method

This article uses the PCA method (Principal component analysis) to evaluate the level of corporate governance. PCA is used to analyze the correlation among 10 original indicators, and extract some principal components so that most of the information of the original indicators is extracted. The formulation of the index of corporate governance can be got by calculating the weight based on the variance contribution rate of the principal component, which can comprehensively evaluate corporate governance.

scholarly journals Patch-Based Principal Component Analysis for Face Recognition

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Tai-Xiang Jiang ◽  
Ting-Zhu Huang ◽  
Xi-Le Zhao ◽  
Tian-Hui Ma
Keyword(s):  
Principal Component Analysis ◽  
Face Recognition ◽  
Nearest Neighbor ◽  
Spatial Information ◽  
Principal Component ◽  
Component Analysis ◽  
Two Dimensional ◽  
Face Images ◽  
Pca Method ◽  
Local Spatial Information

We have proposed a patch-based principal component analysis (PCA) method to deal with face recognition. Many PCA-based methods for face recognition utilize the correlation between pixels, columns, or rows. But the local spatial information is not utilized or not fully utilized in these methods. We believe that patches are more meaningful basic units for face recognition than pixels, columns, or rows, since faces are discerned by patches containing eyes and noses. To calculate the correlation between patches, face images are divided into patches and then these patches are converted to column vectors which would be combined into a new “image matrix.” By replacing the images with the new “image matrix” in the two-dimensional PCA framework, we directly calculate the correlation of the divided patches by computing the total scatter. By optimizing the total scatter of the projected samples, we obtain the projection matrix for feature extraction. Finally, we use the nearest neighbor classifier. Extensive experiments on the ORL and FERET face database are reported to illustrate the performance of the patch-based PCA. Our method promotes the accuracy compared to one-dimensional PCA, two-dimensional PCA, and two-directional two-dimensional PCA.

scholarly journals Estimation of total bacteria by real-time PCR in patients with periodontal disease

2016 ◽  
Vol 144 (1-2) ◽  
pp. 10-14 ◽  
Author(s):  
Gavrilo Brajovic ◽  
Branka Popovic ◽  
Miljan Puletic ◽  
Marija Kostic ◽  
Jelena Milasin
Keyword(s):  
Periodontal Disease ◽  
Real Time ◽  
Copy Number ◽  
Quantitative Estimation ◽  
Periodontal Diseases ◽  
Gene Copy Number ◽  
Gene Copy ◽  
Additional Tool ◽  
Significant Difference ◽  
Total Bacteria

Introduction. Periodontal diseases are associated with the presence of elevated levels of bacteria within the gingival crevice. Objective. The aim of this study was to evaluate a total amount of bacteria in subgingival plaque samples in patients with a periodontal disease. Methods. A quantitative evaluation of total bacteria amount using quantitative real-time polymerase chain reaction (qRT-PCR) was performed on 20 samples of patients with ulceronecrotic periodontitis and on 10 samples of healthy subjects. The estimation of total bacterial amount was based on gene copy number for 16S rRNA that was determined by comparing to Ct values / gene copy number of the standard curve. Results. A statistically significant difference between average gene copy number of total bacteria in periodontal patients (2.55.107) and healthy control (2.37.106) was found (p=0.01). Also, a trend of higher numbers of the gene copy in deeper periodontal lesions (>7 mm) was confirmed by a positive value of coefficient of correlation (r=0.073). Conclusion. The quantitative estimation of total bacteria based on gene copy number could be an important additional tool in diagnosing periodontitis.

scholarly journals Leaf geometric morphometrics among populations of Dalbergia ecastaphyllum (L.) Taub.

2019 ◽  
Vol 35 (6) ◽  
Author(s):  
Daniel Vieira de Morais ◽  
Lorena Andrade Nunes ◽  
Vandira Pereira da Mata ◽  
Maria Angélica Pereira de Carvalho Costa ◽  
Geni da Silva Sodré ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Geometric Morphometrics ◽  
Cross Validation ◽  
Abiotic Factors ◽  
Principal Component ◽  
Canonical Variate ◽  
Validation Test ◽  
Significant Difference ◽  
Variate Analysis ◽  
Geographical Distances

Leaves are plant structures that express important traits of the environment where they live. Leaf description has allowed identification of plant species as well as investigation of abiotic factors effects on their development, such as gases, light, temperature, and herbivory. This study described populations of Dalbergia ecastaphyllum through leaf geometric morphometrics in Brazil. We evaluated 200 leaves from four populations. The principal component analysis (PCA) showed that the first four principal components were responsible for 97.81% of variation. The non-parametric multivariate analysis of variance (NPMANOVA) indicated significant difference between samples (p = 0.0001). The Mentel test showed no correlation between geographical distances and shape. The canonical variate analysis (CVA) indicated that the first two variables were responsible for 96.77 % of total variation, while the cross-validation test showed an average of 83.33%. D. ecastaphyllum leaves are elliptical and ovate.

scholarly journals Effect of Different Edaphic Crop Conditions on the Free Amino Acid Profile of PH-16 Dry Cacao Beans

Agronomy ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1637
Author(s):  
Quintino Reis de Araujo ◽  
Guilherme Amorim Homem de Abreu Loureiro ◽  
Cid Edson Mendonça Póvoas ◽  
Douglas Steinmacher ◽  
Stephane Sacramento de Almeida ◽  
...  
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Glutamic Acid ◽  
Free Amino Acid ◽  
Free Amino Acids ◽  
Free Amino ◽  
Principal Component ◽  
Amino Acid Profile ◽  
Gamma Aminobutyric Acid ◽  
Significant Difference

Free amino acids in cacao beans are important precursors to the aroma and flavor of chocolate. In this research, we used inferential and explanatory statistical techniques to verify the effect of different edaphic crop conditions on the free amino acid profile of PH-16 dry cacao beans. The decreasing order of free amino acids in PH-16 dry cacao beans is leucine, phenylalanine, glutamic acid, alanine, asparagine, tyrosine, gamma-aminobutyric acid, valine, isoleucine, glutamine, lysine, aspartic acid, serine, tryptophan, threonine, glycine. With the exception of lysine, no other free amino acid showed a significant difference between means of different edaphic conditions under the ANOVA F-test. The hydrophobic free amino acids provided the largest contribution to the explained variance with 58.01% of the first dimension of the principal component analysis. Glutamic acid stands out in the second dimension with 13.09%. Due to the stability of the biochemical profile of free amino acids in this clonal variety, it is recommended that cacao producers consider the genotype as the primary source of variation in the quality of cacao beans and ultimately the chocolate to be produced.

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