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

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.

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

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.

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

2007 ◽  
Vol 57 (1) ◽  
pp. 63-77 ◽  
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.

scholarly journals Hyperspectral Sea Ice Image Classification Based on the Spectral-Spatial-Joint Feature with the PCA Network

2021 ◽  
Vol 13 (12) ◽  
pp. 2253
Author(s):  
Yanling Han ◽  
Xi Shi ◽  
Shuhu Yang ◽  
Yun Zhang ◽  
Zhonghua Hong ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Sea Ice ◽  
Image Classification ◽  
Spatial Information ◽  
Gabor Filter ◽  
Principal Component ◽  
Component Analysis ◽  
Small Sample ◽  
Bohai Bay ◽  
Hybrid Strategy

Sea ice is one of the most prominent causes of marine disasters occurring at high latitudes. The detection of sea ice is particularly important, and the classification of sea ice images is an important part of sea ice detection. Traditional sea ice classification based on optical remote sensing mostly uses spectral information only and does not fully extract rich spectral and spatial information from sea ice images. At the same time, it is difficult to obtain samples and the resulting small sample sizes used in sea ice classification has limited the improvement of classification accuracy to a certain extent. In response to the above problems, this paper proposes a hyperspectral sea ice image classification method involving spectral-spatial-joint features based on the principal component analysis (PCA) network. First, the method uses the gray-level co-occurrence matrix (GLCM) and Gabor filter to extract textural and spatial information about sea ice. Then, the optimal band combination is extracted with a band selection algorithm based on a hybrid strategy, and the information hidden in the sea ice image is deeply extracted through a fusion of spectral and spatial features. Then, the PCA network is designed based on principal component analysis filters in order to extract the depth features of sea ice more effectively, and hash binarization maps and block histograms are used to enhance the separation and reduce the dimensions of features. Finally, the low-level features in the data form more abstract and invariant high-level features for sea ice classification. In order to verify the effectiveness of the proposed method, we conducted experiments on two different data collection points in Bohai Bay and Baffin Bay. The experimental results show that, compared with other single feature and spectral-spatial-joint feature algorithms, the proposed method achieves better sea ice classification results (94.15% and 96.86%) by using fewer training samples and a shorter training time.

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

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.

scholarly journals Dear Program Director: Deciphering Letters of Recommendation

2018 ◽  
Vol 10 (3) ◽  
pp. 261-266 ◽  
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 &lt; .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.

scholarly journals Long Term Evaluation Of Maxillary Growth After ‘The Non Denuded Palatoplasty’ Technique

2019 ◽  
Vol 5 (2) ◽  
pp. 203-210
Author(s):  
Prasetyanugraheni Kreshanti ◽  
Siti Handayani ◽  
Maulina Rachmasari ◽  
Julieta Pancawati ◽  
Amila Jeni Susanto ◽  
...  
Keyword(s):  
Cleft Lip ◽  
Cleft Lip And Palate ◽  
Small Sample Size ◽  
Small Sample ◽  
Wound Contraction ◽  
Class Iii ◽  
Significant Difference ◽  
Term Evaluation ◽  
Growth Evaluation ◽  
Maxillary Growth

Background : Conventional Two Flap Palatoplasty technique will produce lateral defects without any periosteal coverage. These denuded lateral defects are prone to contamination and infection. These will result in wound contraction, scar formation and maxillary growth impairment. In 2011, we studied “The Non Denuded Palatoplasty” technique. This technique precipitated the epithelialization process of the lateral defects. Faster epithelialization is expected to decrease wound contraction and good maxillary growth. Method : This is a case control study to compare the maxillary growth of 2 groups consists of unilateral cleft lip and palate patients repaired with “The Non Denuded Palatoplasty” technique and Conventional Two Flap Palatoplasty. The outcome will be evaluated from cephalometry and the dental cast for each patient is evaluated using GOSLON YARDSTICK method. Data will be analyzed using SPSS version 20. Result : A total of 4 patients in The Non Denuded Palatoplasty group and 10 in the Conventional Two Flap Palatoplasty. The cephalometric SNA, SNB and ANB point showed Class III skeletal jaw relationship or deficient maxilla. Meanwhile the GOSLON yardstick type III are the most common GOSLON on both group with good inter-ratter reliability (p=0.839) based on Mann Whitney test. In these study, there was no correlation between cephalometric variables with GOSLON score. Conclusion: Our results showed that modification (The Non Denuded Palatoplasty) technique made no statistically significant difference to the maxillary growth. However this study has several limitations, one of which being the small sample size due to family, social and other factors that are beyond the control of the investigating team. Also the evaluation was conducted in patients aged 7-9 years, hence the result of this study is not the final outcome. Keywords: maxillary growth evaluation, cephalometry, Goslon Yardstick, two flap palatoplasty

scholarly journals Comparison of Geographical Traceability of Wild and Cultivated Macrohyporia Cocos With Different Data Fusion Approaches

2021 ◽  
Author(s):  
Qinqin Wang ◽  
Yuan-Zhong Wang ◽  
Yunmei Wang
Keyword(s):  
Principal Component Analysis ◽  
Feature Extraction ◽  
Random Forest ◽  
Data Fusion ◽  
Principal Component ◽  
Component Analysis ◽  
Level Data ◽  
Significant Difference ◽  
High Level ◽  
Geographical Traceability

Abstract Background Poria originated from the dried sclerotium of Macrohyporia cocos is an edible traditional Chinese medicine with high economic value. Due to the significant difference in quality between wild and cultivated M. cocos, the study aimed to trace the origin of the fungus from the perspectives of wild and cultivation. In addition, there were quite limited studies about data fusion, a potential strategy, employed and discussed in the geographical traceability of M. cocos. Therefore, we traced the origin of M. cocos from the perspectives of wild and cultivation using multiple data fusion approaches. Methods Supervised pattern recognition techniques like partial least squares discriminant analysis (PLS-DA) and random forest, were employed in this study using. Five types of data fusion involving low-, mid- and high-level data fusion strategies were performed. Two feature extraction approaches including the selecting variables by a random forest-based method—Boruta algorithm and producing principal components by the dimension reduction technique of principal component analysis were considered in data fusion. Results (1) the difference of wild and cultivated samples did exist in terms of the content analysis of vital chemical component and fingerprint analysis. (2) the cultivated samples from different origins could be easily identified by Fourier transform infrared spectroscopy or liquid chromatography, while the wild required data fusion. (3) Boruta outperformed principal component analysis (PCA) in feature extraction. (4) Mid-level-Boruta preceded Mid-level-PCA, low-level and high-level data fusion and individual techniques. The Mid-level-Boruta PLS-DA model took full advantage of information synergy and showed the best performance. Conclusions This study proved that both geographical traceability and optimal identification methods of cultivated and wild samples were different, and data fusion was a potential technique in the geographical identification.

scholarly journals Impact of sample size on principal component analysis ordination of an environmental data set: effects on eigenstructure

2016 ◽  
Vol 35 (2) ◽  
pp. 173-190 ◽  
Author(s):  
S. Shahid Shaukat ◽  
Toqeer Ahmed Rao ◽  
Moazzam A. Khan
Keyword(s):  
Principal Component Analysis ◽  
Sample Size ◽  
Principal Component ◽  
Component Analysis ◽  
Small Sample ◽  
Environmental Data ◽  
Data Matrix ◽  
Data Sets ◽  
Data Set ◽  
The Impact

AbstractIn this study, we used bootstrap simulation of a real data set to investigate the impact of sample size (N = 20, 30, 40 and 50) on the eigenvalues and eigenvectors resulting from principal component analysis (PCA). For each sample size, 100 bootstrap samples were drawn from environmental data matrix pertaining to water quality variables (p = 22) of a small data set comprising of 55 samples (stations from where water samples were collected). Because in ecology and environmental sciences the data sets are invariably small owing to high cost of collection and analysis of samples, we restricted our study to relatively small sample sizes. We focused attention on comparison of first 6 eigenvectors and first 10 eigenvalues. Data sets were compared using agglomerative cluster analysis using Ward’s method that does not require any stringent distributional assumptions.

scholarly journals Combination of Principal Component Analysis and Time-Frequency Representation for P-Wave Arrival Detection

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Jacek Wodecki ◽  
Justyna Hebda-Sobkowicz ◽  
Adam Mirek ◽  
Radosław Zimroz ◽  
Agnieszka Wyłomańska
Keyword(s):  
Principal Component Analysis ◽  
High Efficiency ◽  
Onset Time ◽  
Principal Component ◽  
Component Analysis ◽  
P Wave ◽  
Time Frequency ◽  
Frequency Representation ◽  
Significant Difference ◽  
Wave Arrival

Seismic events are phenomena which commonly occur in the mining industry. Due to their dangerous character, such information as the energy of the potential event, the location of hazardous regions with higher seismic activity is considered valuable. However, the acquisition of this information is almost impossible without the ability to detect the onset time of the seismic event. The main objectives of algorithms in finding P-wave are high accuracy, reasonable time of operation, and automatic detection of wave arrival. In this paper, an innovative method which incorporates principal component analysis (PCA) with time-frequency representation of the signal is proposed. Due to the significant difference between the spectra of recorded seismic wave and pure noise which precedes the event, time-frequency representation allows for better accuracy of signal change detection. However, with an additional domain, the complexity rises. Thus, the incorporation of PCA (which is known for high efficiency in lowering data dimensions while maintaining original information) seems to be recommended. In order to show the feasibility of the method, it will be tested on real data originating from monitoring system used in underground mine.

Sign in / Sign up

Export Citation Format

Share Document