Smallholder rubber agroforestry farming in the non-traditional areas of Sri Lanka: An application of assets-based livelihood capital indicator approach

This study focuses on Livelihood Capital Index (LCI) as a useful tool in assessing the livelihood assets of rubber-based agroforestry farm households. It evaluates systematically all the livelihood capitals of rubber agroforestry farm households through developing an LCI. A total of 10 livelihood assets variables were broadly classified into five livelihood capital indicators namely; human, financial, physical, natural, and social. Data collected from 220 farm households through a questionnaire survey were normalized to construct five livelihood capital indicators and LCI. The appropriate weights for the livelihood capital indicators were assigned based on the principal component analysis (PCA). The average composite LCI was 0.49 for rubber-based agroforestry farm households and the human capital corresponds to the highest livelihood assets indicator (0.15) followed by financial (0.14), social (0.11), physical (0.05), and natural (0.05). The highest average LCI was reported by the rubber-based groundnut practice (0.54) followed by rubber-based cattle (0.53), cocoa (0.51), passion fruit (0.51), pepper (0.49), maize (0.49), and banana (0.48). Except for physical capital, it also indicates a statistically significant difference in livelihood capital indicators among the rubber agroforestry farmers and other income earners. A significant difference exists in the livelihood capital indicators except for human capital among the Divisional Secretariat. The outcome of this study suggests that the use of LCI is a more analytically rigorous comprehensive tool that can assess the livelihood of rubber agroforestry farmers and enable them to be improved their livelihood assets.

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

Bioscience Journal ◽

10.14393/bj-v35n6a2019-39814 ◽

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.

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IM-03 IMMUNOLOGICAL SUBTYPES OF GLIOBLASTOMA BASED ON TUMOR INFILTRATING CELLS

Neuro-Oncology Advances ◽

10.1093/noajnl/vdz039.052 ◽

2019 ◽

Vol 1 (Supplement_2) ◽

pp. ii12-ii12

Author(s):

Kushihara Yoshihiro ◽

Syota Tanaka ◽

Erika Yamasawa ◽

Tsukasa Koike ◽

Taijun Hana ◽

...

Keyword(s):

Principal Component Analysis ◽

T Cell ◽

Tumor Microenvironment ◽

Nk Cells ◽

Principal Component ◽

Component Analysis ◽

Gene Set ◽

Significant Difference

Abstract To discover novel biological targets in glioblastoma, genomic and immunological analysis were performed using The Cancer Genome Atlas (TCGA) data set. The RNA-seq data of 156 primary glioblastoma cases were subjected to CIBERSORT to detect tumor infiltrating cell fractions. Principal component analysis was performed on this data to detect factors that strongly contribute to the first principal component, and hierarchical clustering was performed. Survival curves were compared for each of the derived clusters. Finally, Gene Set Enrichment Analysis (GSEA) using HALLMARK Gene Set was performed. In the principal component analysis, we detected seven factors (NK cells resting, T cell regulatory, NK cells activated, Macrophage type 0, T cell gamma delta, Macrophage type 2, Macrophage type 1) which strongly contribute to the first principal component. Based on these seven factors, hierarchical cluster analysis resulted in T cell regulatory (Treg), Macrophage type 0 (M0), Macrophage type 2 (M2) and Macrophage type 1 (M1) clusters. There was no significant difference between these groups in CD8 T cell. M2 and M1 clusters displayed better OS with a significant difference. TNFA signaling via NFκB in Treg group, IFNα response, IFNγ response and ALLOGRAFT response in M2 group, G2M CHECKPOINT, GLYCOLYSIS, WNTβ catenin signaling, MITOTIC SPINDLE and TGFβ signaling in M1 group were upregulated. In conclusion, tumor microenvironment of glioblastoma can be divided into 4 immunological subtypes, Treg, M0, M1, and M2. Because of the contribution of innate immunity for shaping the tumor microenvironment of glioblastoma, immunotherapies targeting these innate immune cells are anticipated.

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Study on the Ability for Jilin Province of China to Undertake Outsourced International Service

Journal on Innovation and Sustainability RISUS ISSN 2179-3565 ◽

10.24212/2179-3565.2011v2i3p86-90 ◽

2011 ◽

Vol 2 (3) ◽

pp. 86

Author(s):

Liu Liqin

Keyword(s):

Principal Component Analysis ◽

Human Capital ◽

Influencing Factors ◽

Index System ◽

Principal Component ◽

Component Analysis ◽

Jilin Province ◽

Service Outsourcing ◽

International Service

Technology, economy, human capital and policy are essential facilities of undertaking international service outsourcing for an area based on analyzing the influencing factors. With principal component analysis, this paper evaluates the ability to undertake international service outsourcing in Jilin Province of China with the purpose of constructing an index system. It shows that the ability in Jilin Province is weak. It is essential for Jilin province of China to improve the technology, to train and introduce talents, and to perfect the soft environment in order to further develop the ability to undertake international service outsourcing.

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Effect of Livelihood Interactions on Farmers' Adaptive Capacity to Climate Change: Insight from Medenine Governorate, Southeast Tunisia

International Journal of Environment and Climate Change ◽

10.9734/ijecc/2020/v10i1230319 ◽

2020 ◽

pp. 422-430

Author(s):

Fatma Aribi ◽

Mongi Sghaier

Keyword(s):

Adaptive Capacity ◽

Policy Development ◽

Capacity Planning ◽

Methodological Approach ◽

Principal Component ◽

Farming Systems ◽

Farm Households ◽

Sustainable Livelihood ◽

Livelihood Capitals ◽

The Impact

The Sustainable Livelihood Approach (SLA) assumes that all capitals are complementary and that more capital assets would lead to greater adaptive capacity. However, the SLA neglects the interactions and transformations between different livelihood capitals. This paper suggests a methodological approach to understand how different capitals may be structured, transformed, and used to improve the farm households’ adaptive capacity to climatic stresses. Data for this study were gathered by means of a questionnaire survey during 2018 from 100 farm households representing the main farming systems of Medenine governorate, Southeast of Tunisia. The analyses were carried out using three tools following a stepwise approach. First, to understand the interactions that exist between the different capitals, a Principal Component Analysis (PCA) was carried out. Then, the adaptive capacity was calculated using the PCA results. Finally, using the Pearson's correlation index, the impact of livelihood assets on adaptive capacity was tested. The results demonstrated that households are trying to compensate for the lack of certain assets through interactions with others in order to improve their adaptive capacity. Moreover, human, natural and financial capital seem to better influence the adaptive capacity of farmers, while the impacts of physical and social capital are relatively less important. These results have improved our comprehension of the livelihood capital purpose for strengthening the existing approaches that enhance the adaptive capacity. Finally, this study has demonstrated that exploring the interactions between livelihood capitals is a first concern, which should be incorporated into adaptive capacity planning and policy development.

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Mining and livelihood: a microanalysis in Odisha, India

International Journal of Social Economics ◽

10.1108/ijse-03-2015-0044 ◽

2017 ◽

Vol 44 (1) ◽

pp. 93-113

Author(s):

Minati Sahoo ◽

Dharmabrata Mohapatra ◽

Dukhabandhu Sahoo

Keyword(s):

Agricultural Land ◽

Principal Component ◽

Physical Capital ◽

Financial Capital ◽

Sustainable Livelihood ◽

Content Type ◽

Significant Difference ◽

Physical Assets ◽

The Impact ◽

Impact Of Mining

Purpose The purpose of this paper is to study the impact of mining on the livelihood of the inhabitants of Keonjhar district in Odisha, through creation of physical and financial capital using the sustainable livelihoods framework. Design/methodology/approach Principal component analysis technique and discriminant analysis were used to assess the impact of mining on the financial capital. A cross-tabulation analysis with χ2-test has also been carried out to find its impact on physical capital. Findings The study reveals that though iron ore mining helps in the augmentation of financial capital of the households, its impact on physical capital is mixed. Households in mining villages enjoy higher average annual and per capita income than those in nonmining villages. There is also a significant difference in the financial capital index of mining and nonmining villages. Even owning of physical assets like TV and motorcycle is significantly higher in mining villages than its nonmining counterparts. But mining has failed to develop the infrastructural facilities and has rendered most of the agricultural land uncultivated. Originality/value It is difficult to sustain the benefits arising out of mining over long run due to its finite life span and calls for policy interventions that can lead to sustainable livelihood to the local inhabitants.

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Silvering of European eel (Anguilla anguilla L.): seasonal changes of morphological and metabolic parameters

Animal Biology ◽

10.1163/157075607780002014 ◽

2007 ◽

Vol 57 (1) ◽

pp. 63-77 ◽

Cited By ~ 48

Author(s):

S. Paul Balm ◽

Caroline Durif ◽

Vincent van Ginneken ◽

Erik Antonissen ◽

Ron Boot ◽

...

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Anguilla Anguilla ◽

Component Analysis ◽

Metabolic Energy ◽

Hepatosomatic Index ◽

European Eel ◽

Silver Eel ◽

Migratory Activity ◽

Significant Difference

AbstractThe transformation of yellow eel into silver eel is called 'silvering', and takes place prior to migration. We found the sedentary yellow phase in spring, the migratory silver phase in autumn, while August was a cross-over month. We used principal component analysis (PCA) to characterise the morphological and physiological changes that accompany silvering in the European eel (Anguilla anguilla L.). Silvering is positively related to external parameters such as eye size, internal maturation parameters like GSI, vitellogenine (VIT), and blood-substrates such as phospholipids, Free Fatty Acids (FFA), and cholesterol. The Hepatosomatic Index was not significantly different between yellow and silver groups. In contrast, a significant difference was observed for parameters of body constitution (fat, protein, dry matter) between yellow and silver stages. Furthermore, the process of silvering is accompanied with increased levels of cortisol in autumn, which plays a role in mobilisation of metabolic energy from body stores towards migratory activity and gonadal growth. Based on Principal Component Analysis (PCA) with physiological, morphological and endocrinological parameters, it is concluded that during the process of silvering, several developmental stages can be recognised, with a timeframe of the premigratory sedentary yellow phase from April until July, August is a cross-over month, and the migratory silver phase is found from September until November.

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Slovak Creativity Index – A PCA Based Approach

European Spatial Research and Policy ◽

10.1515/esrp-2016-0003 ◽

2016 ◽

Vol 23 (1) ◽

pp. 47-64 ◽

Cited By ~ 2

Author(s):

Oto Hudec ◽

Slávka Klasová

Keyword(s):

Principal Component Analysis ◽

Human Capital ◽

Principal Component ◽

Component Analysis ◽

Cultural Environment ◽

Creative Performance ◽

Creative Potential ◽

Advanced Method ◽

Regional Comparison

The article aims at transferring the European Creativity Index (ECI) assessment from the country to regional comparison basis, focusing on the case of Slovakia. The newly created Slovak Creativity Index (SCI) has the power to assess the creativity potential found in the Slovak regions. The Principal Component Analysis has been chosen as an advanced method for establishing a well-designed overall Index and six sub-indices to show differences and variability according to all dimensions of the creative potential. The research also explains several relations between creative performance of the regions by several factors such as urbanisation, cultural environment, human capital and tolerance.

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Description of facial symmetry in patients with unilateral cleft lip and palate using geometric morphometry and computerized tomography

Revista Estomatología ◽

10.25100/re.v22i1.5770 ◽

2017 ◽

Vol 22 (1) ◽

pp. 20-25

Author(s):

Sthepanie Ruiz ◽

Anderson Silva ◽

Mayra Celis ◽

Rocio Ruales ◽

Francined Pardo ◽

...

Keyword(s):

Principal Component Analysis ◽

Thin Plate ◽

Cleft Lip ◽

Cleft Lip And Palate ◽

Principal Component ◽

Component Analysis ◽

Small Sample ◽

Geometric Methods ◽

Affected Side ◽

Significant Difference

Objective: To describe the maxillary asymmetry in patients with single cleft lip and palate by using morphometrics geometric methods. Materials and Methods: Applied morphometrics geometric methods to analyze images captured from 3D reconstructions of CT scans of 9 patients with unilateral cleft lip and palate, mean age of 13.7 years was used. Tps Dig2 software was used to digitalize 6 maxillary landmarks shaping both the affected and the sides unaffected. TpsPower and TpsPLS to a small sample for relative warps and consensus for superimposition. Thin plate function and asymmetry was used applying ASI-CLIC® package, and the principal component analysis was performed with the PAST software version 2.17.0. Results: There is a statistically significant difference (p<0.05) between the conformation of the maxilla on the affected side compared to unaffected. The study of asymmetry indicated different degrees and differences in the nature of the asymmetry that characterizes different deformities of unilateral cleft lip and palate. The principal component analysis demonstrates both inter-group variability and recognizes two principal components, 39.4%, to the first component and 27.5% to the second component. There is a high correlation between the formation of the unaffected side and affected side conformation r= 0.93847. The thin plate deformation is uniform. The allometry study indicated that there is no association between the shape and size. Conclusions: Morphometry Geometric method is a useful tool for assessing preoperative maxillary conformations in patients with unilateral cleft lip and palate. The side without the cleft is also affected, and is associated with the formation on the side of the cleft. The frontonasal suture is also affected, in a greater proportion than the fronto zigomatic.

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Agronomic Performance and Organoleptic Characteristics of Local Varieties of Sweet Potato (Ipomea batatas) Cultivated in Mbaiki (Central African Republic)

Asian Journal of Agricultural and Horticultural Research ◽

10.9734/ajahr/2021/v8i430120 ◽

2021 ◽

pp. 1-11

Author(s):

Gorgon Igor Touckia ◽

Lucie Aba-toumnou ◽

Ephrem Kosh Komba ◽

Cherubin Dan-zi ◽

Kouami Kokou

Keyword(s):

Principal Component Analysis ◽

Sweet Potato ◽

Central African Republic ◽

Principal Component ◽

Component Analysis ◽

Growth And Yield ◽

P Value ◽

Local Varieties ◽

Organoleptic Characteristics ◽

Significant Difference

In the Central African Republic, there are a multitude of local varieties of sweet potato. However, few studies have been carried their agro morphological and organoleptic characteristics. A Fisher random block device was set up on the three local varieties of sweet potato. The growing and production parameters were evaluated as well as the organoleptic characteristics through the food taste test. The parameters of growing and production were assessed by means of analysis of variance (ANOVA) with one classification criterion using the R software version 3.1.3. A Principal Component Analysis (PCA) was also performed with the growth and yield parameters in order to highlight the correlations between these different parameters. The variety 1 (V1) produced the plants with the largest diameters (1.30 cm), while the smallest diameters was observed in the variety 2 (V2) with 0.55 cm. There is a significant difference (P-value = 0.0001) between the different varieties according to the ANOVA test. According to the length of the tuber, the V2 produced the longest tuberous root than the others with an average of 28.53 cm. The smallest length is observed in the V3 with an average of 25.12 cm. There is not significant (p-value = 0.216) in relation with the length of the tuber for the cultivated varieties of the sweet potato. The eigenvalues of the two main axes extracted from the Principal Component Analysis explained 53.68% and 16.82% of the matrix growth/ yield information. Along the factor axes, apart from parameters such as tuber diameters and length which are not positively correlated, there is little variability between the other parameters which are strongly correlated.

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Dear Program Director: Deciphering Letters of Recommendation

Journal of Graduate Medical Education ◽

10.4300/jgme-d-17-00712.1 ◽

2018 ◽

Vol 10 (3) ◽

pp. 261-266 ◽

Cited By ~ 15

Author(s):

Kris Saudek ◽

David Saudek ◽

Robert Treat ◽

Peter Bartz ◽

Rachel Weigert ◽

...

Keyword(s):

Principal Component Analysis ◽

Repeated Measures ◽

Principal Component ◽

Component Analysis ◽

Program Director ◽

Cross Sectional ◽

Likert Score ◽

Significant Difference ◽

Fellowship Programs ◽

Letters Of Recommendation

ABSTRACT Background Letters of recommendation (LORs) are an important part of applications for residency and fellowship programs. Despite anecdotal use of a “code” in LORs, research on program director (PD) perceptions of the value of these documents is sparse. Objective We analyzed PD interpretations of LOR components and discriminated between perceived levels of applicant recommendations. Methods We conducted a cross-sectional, descriptive study of pediatrics residency and fellowship PDs. We developed a survey asking PDs to rate 3 aspects of LORs: 13 letter features, 10 applicant abilities, and 11 commonly used phrases, using a 5-point Likert scale. The 11 phrases were grouped using principal component analysis. Mean scores of components were analyzed with repeated-measures analysis of variance. Median Likert score differences between groups were analyzed with Mann-Whitney U tests. Results Our survey had a 43% response rate (468 of 1079). “I give my highest recommendation” was rated the most positive phrase, while “showed improvement” was rated the most negative. Principal component analysis generated 3 groups of phrases with moderate to strong correlation with each other. The mean Likert score for each group from the PD rating was calculated. Positive phrases had a mean (SD) of 4.4 (0.4), neutral phrases 3.4 (0.5), and negative phrases 2.6 (0.6). There was a significant difference among all 3 pairs of mean scores (all P < .001). Conclusions Commonly used phrases in LORs were interpreted consistently by PDs and influenced their impressions of candidates. Key elements of LORs include distinct phrases depicting different degrees of endorsement.

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