On the Challenge to Correctly Identify Rasboras (Teleostei: Cyprinidae: Danioninae) Inhabiting the Mesangat Wetlands, East Kalimantan, Indonesia

Within the subfamily Danioninae, rasborine cyprinids are known as a ‘catch-all’ group, diagnosed by only a few characteristics. Most species closely resemble each other in morphology. Species identification is therefore often challenging. In this study, we attempted to determine the number of rasborine species occurring in samples from the Mesangat wetlands in East Kalimantan, Indonesia, by using different approaches. Morphological identification resulted in the distinction of five species (Trigonopoma sp., Rasbora cf. hubbsi Brittan, 1954, R. rutteni Weber and de Beaufort, 1916, R. trilineata Steindachner, 1870, and R. vaillantii, Popta 1905). However, genetic species delimitation methods (Poisson tree processes (PTP) and multi-rate PTP (mPTP)) based on DNA barcodes and principal component analysis (PCA) based on homologous geometric morphometric landmarks, revealed a single cluster for Trigonopoma sp. and R. trilineata, respectively, whereas the remaining traditionally identified species were distinguished neither by DNA barcodes nor by the morphometry approach. A k-mean clustering based on the homologous landmarks divided the sample into 13 clusters and was thus found to be inappropriate for landmark data from species extremely resembling each other in morphology. Due to inconsistent results between the applied methods we refer to the traditional identifications and distinguish five rasborine species for the Mesangat wetlands.

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The diversity of Smilax (Smilacaceae) in Besiq-Bermai and Bontang Forests, East Kalimantan, Indonesia

Biodiversitas Journal of Biological Diversity ◽

10.13057/biodiv/d200145 ◽

2018 ◽

Vol 20 (1) ◽

pp. 279-287

Author(s):

SITI SOFIAH ◽

LULUT DWI SULISTYANINGSIH

Keyword(s):

Principal Component Analysis ◽

Random Sampling ◽

Principal Component ◽

Environmental Data ◽

Taxonomic Study ◽

East Kalimantan ◽

Taxonomic Description ◽

Lack Of Information ◽

Growing Environment ◽

Species Occurrences

Sofiah S, Sulistyaningsih LD. 2019. The diversity of Smilax (Smilacaceae) in Besiq-Bermai and Bontang Forests, East Kalimantan, Indonesia. Biodiversitas 20: 279-287. The genus Smilax has taxonomic complexity problems and spacious distribution. Taxonomic study to reveal the diversity of Smilax species had been done in some regions, such as America, China, Japan, Thailand, and Indonesia. However, there is lack of information of Smilax species diversity in Kalimantan especially in East Kalimantan which lies in Sundaland biogeographic. This study was carried out to explore and record the diversity of Smilax species including the ecological and environmental data in Besiq-Bermai and Bontang forests in East Kalimantan, Indonesia. This research conducted on February and August in 2012 and July-August 2015 using exploration methods. Purposive random sampling was used to do the botanical sampling. The principal component analysis (PCA) was performed to determine the relationships between environmental components and Smilax species occurrences. There were five species of Smilax which were housed in those forests in East Kalimantan, namely, Smilax leucophylla Blume, Smilax gigantea Merr., Smilax odoratissima Blume, Smilax zeylanica L., and Smilax modesta A.DC. Smilax leucophylla and Smilax zeylanica are the most widely used by the local people for medicine. The taxonomic description, distribution, use, and vernacular name were given. The environmental factors that contribute significantly to Smilax's growing environment are temperature and light intensity.

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Characteristic Structural Knowledge for Morphological Identification and Classification in Meso-Scale Simulations Using Principal Component Analysis

Polymers ◽

10.3390/polym13162581 ◽

2021 ◽

Vol 13 (16) ◽

pp. 2581

Author(s):

Natthiti Chiangraeng ◽

Michael Armstrong ◽

Kiattikhun Manokruang ◽

Vannajan Sanghiran Lee ◽

Supat Jiranusornkul ◽

...

Keyword(s):

Principal Component Analysis ◽

Diblock Copolymers ◽

Principal Component ◽

Component Analysis ◽

Structural Knowledge ◽

Morphological Identification ◽

Particle Dynamic ◽

Structural Formation ◽

Macromolecular Systems ◽

Meso Scale

Meso-scale simulations have been widely used to probe aggregation caused by structural formation in macromolecular systems. However, the limitations of the long-length scale, resulting from its simulation box, cause difficulties in terms of morphological identification and insufficient classification. In this study, structural knowledge derived from meso-scale simulations based on parameters from atomistic simulations were analyzed in dissipative particle dynamic (DPD) simulations of PS-b-PI diblock copolymers. The radial distribution function and its Fourier-space counterpart or structure factor were proposed using principal component analysis (PCA) as key characteristics for morphological identification and classification. Disorder, discrete clusters, hexagonally packed cylinders, connected clusters, defected lamellae, lamellae and connected cylinders were effectively grouped.

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Discrimination of the species of the Crassiphycus corneus/C. usneoides complex (Gracilariaceae, Rhodophyta) through geometric morphometric analysis

Nova Hedwigia ◽

10.1127/nova_hedwigia/2019/0543 ◽

2019 ◽

Vol 109 (3) ◽

pp. 291-301 ◽

Cited By ~ 1

Author(s):

Martha Isabel Vilchis ◽

Jiri Neustupa ◽

Kurt Dreckmann ◽

Alejandra Quintanar ◽

Abel Sentíes

Keyword(s):

Principal Component Analysis ◽

Morphometric Analysis ◽

Principal Component ◽

Fourier Descriptors ◽

Cortical Cells ◽

Geometric Morphometric ◽

Phenotypic Differences ◽

Geometric Morphometric Analysis ◽

Elliptic Fourier Descriptors ◽

Manova Analysis

The results of the discrimination by geometric morphometry of the species within the Crassiphycus corneus/C. usneoides complex is presented, from the shape of its cortical, subcortical and medullary cells in the apical, medium and basal portions of thallus. Principal component analysis, based on the elliptic Fourier descriptors of cellular outline shapes and NP-MANOVA analysis, show that only the cortical cells in the medium portion were significantly wider in C. corneus than in C. usneoides. The isoperimetric quotients (Q) indicated that these cells were significantly more circular in C. corneus than in C. usneoides. We conclude that the outline analyses efficiently recovered phenotypic differences between the species defined by molecular systematics and considered to be cryptic, so far.

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Centric Allometry: Studying Growth Using Landmark Data

Evolutionary Biology ◽

10.1007/s11692-020-09530-w ◽

2021 ◽

Author(s):

Fred L. Bookstein

Keyword(s):

Principal Component ◽

Shape Space ◽

Allometric Growth ◽

Differential Growth ◽

Data Set ◽

Geometric Morphometric ◽

Franz Boas ◽

Landmark Data ◽

Per Se ◽

Algebraic Constraints

AbstractThe geometric morphometric (GMM) construction of Procrustes shape coordinates from a data set of homologous landmark configurations puts exact algebraic constraints on position, orientation, and geometric scale. While position as digitized is not ordinarily a biologically meaningful quantity, and orientation is relevant mainly when some organismal function interacts with a Cartesian positional gradient such as horizontality, size per se is a crucially important biometric concept, especially in contexts like growth, biomechanics, or bioenergetics. “Normalizing” or “standardizing” size (usually by dividing the square root of the summed squared distances from the centroid out of all the Cartesian coordinates specimen by specimen), while associated with the elegant symmetries of the Mardia–Dryden distribution in shape space, nevertheless can substantially impeach the validity of any organismal inferences that ensue. This paper adapts two variants of standard morphometric least-squares, principal components and uniform strains, to circumvent size standardization while still accommodating an analytic toolkit for studies of differential growth that supports landmark-by-landmark graphics and thin-plate splines. Standardization of position and orientation but not size yields the coordinates Franz Boas first discussed in 1905. In studies of growth, a first principal component of these coordinates often appears to involve most landmarks shifting almost directly away from their centroid, hence the proposed model’s name, “centric allometry.” There is also a joint standardization of shear and dilation resulting in a variant of standard GMM’s “nonaffine shape coordinates” where scale information is subsumed in the affine term. Studies of growth allometry should go better in the Boas system than in the Procrustes shape space that is the current conventional workbench for GMM analyses. I demonstrate two examples of this revised approach (one developmental, one phylogenetic) that retrieve all the findings of a conventional shape-space-based approach while focusing much more closely on the phenomenon of allometric growth per se. A three-part Appendix provides an overview of the algebra, highlighting both similarities to the Procrustes approach and contrasts with it.

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Habitat suitability for Proboscis Monkey (Nasalis larvatus Wurmb, 1781) in the mangrove forest of Kutai National Park, East Kalimantan

Bonorowo Wetlands ◽

10.13057/bonorowo/w060102 ◽

2016 ◽

Vol 6 (1) ◽

pp. 12-25

Author(s):

SUWARTO SUWARTO ◽

LILIK BUDI PRASETYO ◽

AGUS PRIYONO KARTONO

Keyword(s):

Principal Component Analysis ◽

Spatial Modeling ◽

Habitat Suitability ◽

Mangrove Forest ◽

National Park ◽

Principal Component ◽

Component Analysis ◽

Proboscis Monkey ◽

Nasalis Larvatus ◽

East Kalimantan

Suwarto, Prasetyo LB, Kartono AP. 2016. Habitat suitability for Proboscis Monkey (Nasalis larvatus Wurmb, 1781) in the mangrove forest of Kutai National Park, East Kalimantan. Bonorowo Wetlands 6: 12-25. This study aims to identify the factors determining that influence the suitability proboscis monkey (Nasalis larvatus Wurmb, 1781) in the mangrove habitat Kutai National Park through spatial modeling. Habitat suitability was analyzed using Principal Component Analysis (PCA) and linear regression were integrated with geographical information systems. Principal Component Analysis is a technique to construct new variables that are linear combinations of the original variables by reducing the variables used. The presence of groups of proboscis monkey marked with GPS. Satellite images from Landsat 8 path 116 row 60 processed digitally to generate proboscis vegetation distribution and Normalization Difference Vegetation Index, Variable distance from roads, distance from settlements, the distance from the fishpond, and the distance from the source of water is obtained from the analysis euclidean distance of Indonesia Earth Appearance map. Spatial modeling using the coordinates of the encounter group proboscis as the dependent variable and the predictor variables used in the regression model is the distance from the road, the distance from the settlement, the distance from the pond, the distance from the source of water, the distance of Avicennia, distance from Bruguiera, distance from Rhizophora, distance from Sonneratia, and LAI (Leaf Area Index). The overall area of the study area was used to build the model is 7 343.88 hectares. The results habitat suitability modeling proboscis monkey in the mangroves of TNK showed that only 99.50 hectares or 1.35% have high compatibility, the suitability being has a total area of 384.58 hectares or 18.85%, whereas an area of 5 859.81 hectares or 79.79% low suitability. The results of models have explained that the distribution of the proboscis monkey habitat suitability is influenced by factors of disturbance.

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Scanning x-ray fluorescence microscopy and principal component analysis

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100133394 ◽

1992 ◽

Vol 50 (2) ◽

pp. 1752-1753

Author(s):

Brian Cross

Keyword(s):

Principal Component Analysis ◽

Fluorescence Microscopy ◽

Spatial Resolution ◽

High Speed ◽

Image Acquisition ◽

Principal Component ◽

Fluorescence Microscope ◽

Acquisition Rate ◽

X Ray ◽

Speed Up

A relatively new entry, in the field of microscopy, is the Scanning X-Ray Fluorescence Microscope (SXRFM). Using this type of instrument (e.g. Kevex Omicron X-ray Microprobe), one can obtain multiple elemental x-ray images, from the analysis of materials which show heterogeneity. The SXRFM obtains images by collimating an x-ray beam (e.g. 100 μm diameter), and then scanning the sample with a high-speed x-y stage. To speed up the image acquisition, data is acquired "on-the-fly" by slew-scanning the stage along the x-axis, like a TV or SEM scan. To reduce the overhead from "fly-back," the images can be acquired by bi-directional scanning of the x-axis. This results in very little overhead with the re-positioning of the sample stage. The image acquisition rate is dominated by the x-ray acquisition rate. Therefore, the total x-ray image acquisition rate, using the SXRFM, is very comparable to an SEM. Although the x-ray spatial resolution of the SXRFM is worse than an SEM (say 100 vs. 2 μm), there are several other advantages.

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A German version of the Intermittent Claudication Questionnaire (ICQ): cultural adaptation and validation

VASA ◽

10.1024/0301-1526/a000218 ◽

2012 ◽

Vol 41 (5) ◽

pp. 333-342 ◽

Cited By ~ 3

Author(s):

Kirchberger ◽

Finger ◽

Müller-Bühl

Keyword(s):

Principal Component Analysis ◽

Intermittent Claudication ◽

Completion Time ◽

Short Form ◽

Principal Component ◽

Component Analysis ◽

German Version ◽

Average Completion Time ◽

Sf 36 ◽

Related Quality

Background: The Intermittent Claudication Questionnaire (ICQ) is a short questionnaire for the assessment of health-related quality of life (HRQOL) in patients with intermittent claudication (IC). The objective of this study was to translate the ICQ into German and to investigate the psychometric properties of the German ICQ version in patients with IC. Patients and methods: The original English version was translated using a forward-backward method. The resulting German version was reviewed by the author of the original version and an experienced clinician. Finally, it was tested for clarity with 5 German patients with IC. A sample of 81 patients were administered the German ICQ. The sample consisted of 58.0 % male patients with a median age of 71 years and a median IC duration of 36 months. Test of feasibility included completeness of questionnaires, completion time, and ratings of clarity, length and relevance. Reliability was assessed through a retest in 13 patients at 14 days, and analysis of Cronbachs alpha for internal consistency. Construct validity was investigated using principal component analysis. Concurrent validity was assessed by correlating the ICQ scores with the Short Form 36 Health Survey (SF-36) as well as clinical measures. Results: The ICQ was completely filled in by 73 subjects (90.1 %) with an average completion time of 6.3 minutes. Cronbachs alpha coefficient reached 0.75. Intra-class correlation for test-retest reliability was r = 0.88. Principal component analysis resulted in a 3 factor solution. The first factor explained 51.5 of the total variation and all items had loadings of at least 0.65 on it. The ICQ was significantly associated with the SF-36 and treadmill-walking distances whereas no association was found for resting ABPI. Conclusions: The German version of the ICQ demonstrated good feasibility, satisfactory reliability and good validity. Responsiveness should be investigated in further validation studies.

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