Cross-validated Discriminant Analysis Research Articles

A machine learning approach for the classification of sports based on a coaches’ perspective of environmental, individual and task requirements: A sports profile analysis

ABSTRACT Well-designed talent programmes in sports with a focus on talent identification, orientation, development, and transfer support the engagement of young individuals and the pursuit of elite performance. To facilitate these processes, an analysis of task, environmental and individual characteristics per sport is much needed. The aims of this study were to 1) analyse whether unique profiles per sport could be established by generic characteristics and 2) to discuss similarities and differences for the potential application in talent development and transfer. By means of a validated survey, 1247 coaches from 34 sports ranked 18 characteristics on importance to their sports (0 = not important − 10 = very important). To discriminate the responses per sport a Discriminant Analysis (DA) was carried out. To refine the DA-classification, Uniform Manifold Approximation and Projection (UMAP) with CatBoost classifier was performed. To test the performance of the CatBoost classifier-algorithm, a confusion-matrix was generated. The cross-validated DA showed that 70.2% of the coaches were correctly classified to their sport. The UMAP/CatBoost technique revealed 75.1% accuracy with correctly predicted responses per sport ranging from 18.2% (sailing) to 98.2% (soccer). With varying precision, the algorithm was able to differentiate sports by importance of its characteristics indicating similarities and differences per sport.

Glioma genetic profiles associated with electrophysiologic hyperexcitability.

Distinct genetic alterations determine glioma aggressiveness, however, the diversity of somatic mutations contributing to peritumoral hyperexcitability and seizures over the course of the disease is uncertain. This study aimed to identify tumor somatic mutation profiles associated with clinically significant hyperexcitability. A single center cohort of adults with WHO grades 1-4 glioma and targeted exome sequencing (n = 1716) was analyzed and cross-referenced with a validated EEG database to identify the subset of individuals who underwent continuous EEG monitoring (n = 206). Hyperexcitability was defined by the presence of lateralized periodic discharges and/or electrographic seizures. Cross-validated discriminant analysis models trained exclusively on recurrent somatic mutations were used to identify variants associated with hyperexcitability. The distribution of WHO grades and tumor mutational burdens were similar between patients with and without hyperexcitability. Discriminant analysis models classified the presence or absence of EEG hyperexcitability with an overall accuracy of 70.9%, regardless of IDH1 R132H inclusion. Predictive variants included nonsense mutations in ATRX and TP53, indel mutations in RBBP8 and CREBBP, and nonsynonymous missense mutations with predicted damaging consequences in EGFR, KRAS, PIK3CA, TP53, and USP28. This profile improved estimates of hyperexcitability in a multivariate analysis controlling for age, sex, tumor location, integrated pathologic diagnosis, recurrence status, and preoperative epilepsy. Predicted somatic mutation variants were over-represented in patients with hyperexcitability compared to individuals without hyperexcitability and those who did not undergo continuous EEG. These findings implicate diverse glioma somatic mutations in cancer genes associated with peritumoral hyperexcitability. Tumor genetic profiling may facilitate glioma-related epilepsy prognostication and management.

‘I know the tiger by his paw’: A non-invasive footprint identification technique for monitoring individual Amur tigers (Panthera tigris altaica) in snow

Apex predator populations are in decline around the world. Many exist at low density and are elusive, making the acquisition of reliable data on their numbers and distribution a considerable challenge. The Amur tiger (Panthera tigris altaica) is the largest of the five extant sub-species of tiger. The single most significant, contiguous population, an estimated 550 animals, exists in the Russian Far East, with smaller populations on the far eastern Sino-Russian border. For the last few decades, active efforts on the part of Chinese authorities have encouraged the recolonization of these populations back to their former ranges in Northeast China. Reliable data on Amur tiger numbers and distribution are required to assess population recovery at the landscape scale. Footprints, ubiquitous in the snow over range areas, could inform on these baseline data. This paper describes a statistically robust, cost-effective and non-invasive footprint identification technique (FIT) to identify individual tigers from footprints in snow. It is based on a rigorous data collection and data-processing protocol, combined with a cross-validated discriminant analysis method. A Ward's clustering technique provides a visual output of individual classification. The analytical tools are packaged in a user-friendly analytical interface. Between December 2011 and December 2012, we collected a series of 605 footprint images from 44 captive individual Amur tigers for a reference database from which to derive a classification algorithm. The 23 females and 21 males ranged in age from 3 to 13 years (female mean age 7.95 +/− 0.18; male mean age 8.08 +/− 0.19). 128 measurements (areas, lengths and angles) were taken from each print and analyzed with the FIT add-in to JMP software. The derived classification algorithm was then applied to 21 footprint trails collected from an unknown number of free-ranging Amur tigers during 2012 and 2015/2016. The algorithm predicted 7 Amur tigers at the site surveyed in 2012, and 4 tigers surveyed at two sites in 2015/16. We demonstrate that the footprint identification technique translates traditional tracking methodologies into a statistically robust and objective analytical tool that can be deployed by both scientists and local communities to monitor the recovery of big cat populations.

Chemometric Study of Fatty Acid Composition of Virgin Olive Oil from Four Widespread Greek Cultivars.

Virgin olive oil (VOO) is one of the key components of the Mediterranean diet owing to the presence of monounsaturated fatty acids and various bioactive compounds. These beneficial traits, which are usually associated with the cultivar genotype, are highlighting the demand of identifying characteristics of olive oil that will ensure its authenticity. In this work, the fatty acid (FA) composition of 199 VOO samples from Koroneiki, Megaritiki, Amfissis, and Manaki cultivars was determined and studied by chemometrics. Olive cultivar greatly influenced the FA composition, namely, oleic acid (from 75.36% for Amfissis to 65.81% for Megaritiki) and linoleic acid (from 13.35% for Manaki to 6.70% for Koroneiki). Spearman’s rho correlation coefficients revealed differences and similarities among the olive oil cultivars. The use of the forward stepwise algorithm identified the FAs arachidonic acid, gadoleic acid, linoleic acid, α-linolenic acid, palmitoleic acid, and palmitic acid as the most significant for the differentiation of samples. The application of linear and quadratic cross-validation discriminant analysis resulted in the correct classification of 100.00% and 99.37% of samples, respectively. The findings demonstrated the special characteristics of the VOO samples derived from the four cultivars and their successful botanical differentiation based on FA composition.

Morphometric analysis of the inter-mastoid triangle for sex determination: Application of statistical shape analysis.

PurposeSex determination can be done by morphological analysis of different parts of the body. The mastoid region, with its anatomical location at the skull base, is ideal for sex identification. Statistical shape analysis provides a simultaneous comparison of geometric information on different shapes in terms of size and shape features. This study aimed to investigate the geometric morphometry of the inter-mastoid triangle as a tool for sex determination in the Iranian population.Materials and MethodsThe coordinates of 5 landmarks on the mastoid process on the 80 cone-beam computed tomographic images (from individuals aged 17-70 years, 52.5% female) were registered and digitalized. The Cartesian x-y coordinates were acquired for all landmarks, and the shape information was extracted from the principal component scores of generalized Procrustes fit. The t-test was used to compare centroid size. Cross-validated discriminant analysis was used for sex determination. The significance level for all tests was set at 0.05.ResultsThere was a significant difference in the mastoid size and shape between males and females (P<0.05). The first 2 components of the Procrustes shape coordinates explained 91.3% of the shape variation between the sexes. The accuracy of the discriminant model for sex determination was 88.8%.ConclusionThe application of morphometric geometric techniques will significantly impact forensic studies by providing a comprehensive analysis of differences in biological forms. The results demonstrated that statistical shape analysis can be used as a powerful tool for sex determination based on a morphometric analysis of the inter-mastoid triangle.

Abstract PO-033: Metabolic differences between human papillomavirus-related and smoking-related squamous cell carcinoma of the head and neck independently predict overall patient survival

Abstract Background: Human papillomavirus (HPV) status and tobacco use are the strongest prognostic factors of survival for squamous cell carcinoma of the head and neck (SCCHN). Patients with HPV-related SCCHN live more than twice as long as patients with tobacco-related SCCHN. The underlying metabolic dysregulation characterizing these two clinically distinct groups may pose exciting translational targets that are yet unknown. Using a metabolome-wide approach, we investigated the metabolic differences of HPV vs smoking-related SCCHN in a large patient population. We then linked those metabolic differences to patient survival. Methods: We recruited 137 patients from Emory University hospitals and clinics: 55 HPV-positive never smokers (i.e., HPV-related SCCHN) and 82 HPV-negative current or former smokers (i.e., smoking-related SCCHN). We performed untargeted high-resolution metabolomics using liquid chromatography-mass spectrometry on pre-treatment patient plasma at the Emory Clinical Biomarkers Laboratory. Our statistical approach has three steps. 1) Metabolite feature selection: We aggregated the results from two selection algorithms (5-fold cross-validated partial least squares discriminant analysis and support vector machine) to determine the metabolites that differentiated HPV vs smoking-related SCCHN. 2) Metabolic pathway analysis (Mummichog): We identified statistically significant (P&amp;lt;0.05) metabolic pathways stemming from the step 1 metabolites. 3) Metabolic profile and survival analysis: We created a metabolite-based linear principal component using the significant pathway metabolites in step 2 and estimated its association with overall survival using adjusted Cox models. Results: Of the 9,640 extracted metabolites, the two models found 229 that differentiated HPV vs smoking-related SCCHN. Metabolic pathway analysis found fatty acid and steroid metabolism was significantly upregulated in HPV patients: bile acid biosynthesis (P&amp;lt;0.0001), 21-carbon steroid hormone metabolism (P=&amp;lt;0.0001), fatty acid beta-oxidation (P=0.04). Pathways related to sugar metabolism were significantly upregulated in smoking patients: galactose metabolism (P=0.003), starch and sucrose metabolism (P=0.007), hexose phosphorylation (P=0.03), sialic acid metabolism (P=0.03). A principal component comprised of the 16 pathway metabolites was significantly associated with overall survival (HR=1.27 per standard deviation, P=0.01, 95% CI: 1.06-1.51) independent of HPV, smoking, tumor site, age, sex, race, and body mass index. Conclusions: Metabolites corresponding to fatty acid, steroid, and sugar metabolism differentiated HPV-related SCCHN from smoking-related SCCHN. They may be clinically informative as prognostic markers of survival. Our novel findings in patient plasma parallel those from HPV positive vs negative SCCHN cell lines, suggesting that metabolites in blood may be putative biomarkers of tumor metabolic activity and thus potentially useful for drug discovery. Citation Format: Ronald C. Eldridge, Karan Uppal, Jonathan Beitler, Kristin Higgins, Evanthia C. Wommack, Dong M. Shin, Nabil F. Saba, Andrew Miller, Deborah W. Bruner, Canhua Xiao. Metabolic differences between human papillomavirus-related and smoking-related squamous cell carcinoma of the head and neck independently predict overall patient survival [abstract]. In: Abstracts: AACR Special Virtual Conference on Epigenetics and Metabolism; October 15-16, 2020; 2020 Oct 15-16. Philadelphia (PA): AACR; Cancer Res 2020;80(23 Suppl):Abstract nr PO-033.

Do the Fish Scales Shape of Mugil curema Reflect the Genetic Structure Using Microsatellites Markers and the Mexican Marine Ecoregions Classification?

Mugil curema is a teleost fish of economic importance that shows wide phenotypic variability in the coasts of Mexico. Intraspecific morphological variability might replicate either genetic dissimilarity between groups or environmental conditions according to phenotypic plasticity. Fish scales shape were used to discriminate location variants, genetic structure obtained by microsatellite markers and ichthyological provinces of Mexico. The present study uses landmarks and geometric morphometric statistical approaches to address the specific question: if and how fish scale shape varies with genetic structure or with ichthyological provinces. This is assessed using seven landmarks by scale, the coordinates of which were subjected to a generalized Procrustes analysis, followed by a principal components analysis and quadratic discriminant analysis with cross-validation analysis on shape. Also, the significance of classifications was assessed by Mancova. The proportion of total shape variance explained by total length and by centroid size was 3.8% and 3.0%, respectively. Therefore, only shape (without size), was used for the analysis. Mancova was significant in all cases, with locations, genetic structure and ichthyological provinces. The cross-validated discriminant analysis by location correctly classified 42.2% while with the genetic structure prearrangement and ichthyological provinces the identification rates were 58.3 and 57.0%, respectively. It was surprising that, as the same as in the genetic structure (microsatellite analysis), San Antonio Bay, Texas formed a group with Sabancuy, Campeche, Celestun and Sisal, Yucatan (the Caribbean locations). Likewise, Huave Lagoon System, Oaxaca located in the Pacific coast is more similar to the Caribbean sites unlike the other locations from the Pacific area, which are similar results depicted with microsatellite analysis. On the other hand, using the ichthyological provinces arrangement, the findings indicate that the Mexican and the Panamanian provinces were very different as opposed to the two provinces from the Gulf of Mexico more similar in fish scale shape. The Mexican province shows more identification rate (80.4%) while the rest of provinces discriminate less than 53.3%. Possibly, hydrographic features as currents or upwellings circumscribe boundaries between provinces and this could produce inherent genetic structure.

Geometric morphometrics species discrimination within the Genus Nemipterus from Malaysia and its surrounding seas

Imtiaz A, Md Naim D. 2018. Geometric morphometrics species discrimination within the Genus Nemipterus from Malaysia and its surrounding seas. Biodiversitas 19: 2316-2322. High demand of fish protein diet and exposure of marine fish to a challenging marine environment has increased the importance of advanced fisheries research especially in Malaysian waters, particularly research related to taxonomy, biology, diversity, population structure as well as phylogenetic histories of commercially important marine fish species to ensure continuous supply of fish and fish products. This current research aimed to explore the potential of geometric morphometrics method to discriminate among taxa of genus Nemipterus through body size and shape differences. A total of 171 individuals representing ten species of genus Nemipterus collected from Malaysia and its surrounding seas were examined. The resulting homologous landmarks were subjected to generalized procustes analysis followed by principal component analysis. Principle component scores were further investigated to cross-validated discriminant analysis to determine the efficacy of landmarks in discriminating by taxon. Our finding shows that species within the genus Nemipterus can be differentiated using geometric morphometrics method as strongly depicted by canonical variance analysis. This current study is the first report utilizing geometric morphometrics approach conducted on the genus Nemipterus from Malaysian waters.

Morphometric variation of fish scales among some species of rattail fish from New Zealand waters

New Zealand rattail fish are of great interest both to biologists who study their phylogenetics and in fisheries. In contrast, their morphological evolution is little studied and poorly understood. Geometric morphometric methods based on scale shape were applied in this study to determine differences among species and genera. Scale shapes were described using seven landmarks, the coordinates of which were subjected to a generalized Procrustes analysis, followed by a principal components analysis. A cross-validated discriminant analysis was applied to assess and compare the size-shape (centroid size plus shape variables) efficacy in the species and the discrimination of the genera. Two main phenetic groups were identified: cluster no. 1 with eight species and cluster no. 2 with six species. Coelorhinchus aspercephalus and Mesovagus antipodum were more separated from the other species in the first cluster. The cross-validated canonical discriminant analysis correctly classified 74% at the genus level, with most misclassifications occurring between Coelorhinchus and Coryphaenoides, whereas the best classified genera were Mesovagus and Trachyrincus. The discrimination of correctly classified species ranged from 41.2 to 100%. The highest correct classification rates were recorded for Coryphaenoides armatus, Coelorhinchus innotabilis, Trachyrincus longirostris and Mesovagus antipodum.

Morphometrics and allometry of the larvae of five Characiformes species in the Paraíba do Sul River Basin.

The aim of this study was to analyse the morphology and allometry of larvae belonging to five potamodromous species. Five breeding species belonging to the order Characiformes [Salminus brasiliensis (Cuvier, 1816), Leporinus steindachneri, Eigenmann, 1907, Prochilodus lineatus (Valenciennes, 1837), Prochilodus vimboides (Kner,1859) and Brycon insignis, Steindachner, 1877] were used to obtain larvae samples during the pre-flexing, post-flexing, and juvenile developmental stages. When we observed the degree-hour (DH) amplitude time values, we found three developmental groups based on allometry and morphometrics within the period between the pre-flexing and post-flexing phases. Group 1 consists of the species S. brasiliensis and B. insignis, Group 2 consists of P. lineatus and P. vimboides, and Group 3 consists of L. steindachneri. Group 1 requires less development time and has more slender larvae. Group 2 has a moderate development time and larvae with a more rounded shape. Group 3 presents a greater development time and an intermediate larval morphology. It was possible to classify the larvae through cross-validated discriminant analyses based on seven morphometric variables with 90% accuracy in B. insignis, 83% in L. steindachneri, 91% in P. lineatus, 80% in P. vimboides, and 96% in S. brasiliensis. These results indicate larval characteristics that can be used for the taxonomic identification of the icthyoplankton.

The challenge of monitoring elusive large carnivores: An accurate and cost-effective tool to identify and sex pumas (Puma concolor) from footprints.

Acquiring reliable data on large felid populations is crucial for effective conservation and management. However, large felids, typically solitary, elusive and nocturnal, are difficult to survey. Tagging and following individuals with VHF or GPS technology is the standard approach, but costs are high and these methodologies can compromise animal welfare. Such limitations can restrict the use of these techniques at population or landscape levels. In this paper we describe a robust technique to identify and sex individual pumas from footprints. We used a standardized image collection protocol to collect a reference database of 535 footprints from 35 captive pumas over 10 facilities; 19 females (300 footprints) and 16 males (235 footprints), ranging in age from 1–20 yrs. Images were processed in JMP data visualization software, generating one hundred and twenty three measurements from each footprint. Data were analyzed using a customized model based on a pairwise trail comparison using robust cross-validated discriminant analysis with a Ward’s clustering method. Classification accuracy was consistently > 90% for individuals, and for the correct classification of footprints within trails, and > 99% for sex classification. The technique has the potential to greatly augment the methods available for studying puma and other elusive felids, and is amenable to both citizen-science and opportunistic/local community data collection efforts, particularly as the data collection protocol is inexpensive and intuitive.

Detection of mycobacteria by volatile organic compound analysis of invitro cultures using differential ion mobility spectrometry.

Differential ion mobility spectrometry (DMS) is an analytical technique used to detect volatile organic compounds (VOCs) in gaseous samples at very low concentration ranges from ppb to ppt. The aim of this study was to investigate whether VOC analysis by DMS is capable of detecting Mycobacterium avium subsp. paratuberculosis (MAP). Headspaces of in vitro cultures of two different MAP strains at 1, 2, 3, 4 and 6 weeks after inoculation (each at two dilutions) were analysed with DMS in comparison to control samples without viable bacteria [(i) blank medium, (ii) medium inoculated with heat-inactivated MAP and (iii) sterile-filtered MAP culture broth]. Furthermore, VOC patterns in the headspace over cultures of six non-tuberculous mycobacterial species were compared to MAP-derived VOC patterns. Data analysis included peak detection, cluster analysis, identification of discriminating VOC features (Mann-Whitney U test) and different cross-validated discriminant analyses. VOC analysis resulted in up to 127 clusters and revealed highly significant differences between MAP strains and controls at all time points. In addition, few clusters allowed differentiation between MAP and other non-tuberculous mycobacteria and even between different MAP strains. Compounds have not been characterized. VOC analysis by DMS was able to identify MAP-positive samples after 1 week of in vitro growth. This study provides strong evidence that VOC analysis of headspace over mycobacterial cultures in combination with appropriate data analysis has the potential to become a valuable method to identify positive samples much earlier than with current standard procedures.

Sexual Wing Shape Dimorphism in Piophila casei (Linnaeus, 1758 Diptera: Piophilidae)

The Piophilidae are synanthropic flies that grow and develop on cheese, fish, cured meat, among others substrates. Some species represents an important forensic indicator associated to carcasses, because the adults are common during the bloat stage, and the larvae are associated to the advanced to dry stages. Recently, the geometric morphometrics has been used to quantified the sexual shape dimorphism in medical important insects. We proposed to evaluate the shape sexual dimorphism in Piophila casei through the wing geometric morphometrics. Were collected 34 P. casei specimens and sorted by sex (17 females and 17 males), later the wing was dissected and slide mounted for digitalizing eight landmarks. The x, y coordinates were aligned by Generalized Procrustes Analysis to extract the matrix configurations and centroid size. The sexual shape dimorphism differences were evaluated by means a Discriminant Analysis (DA), and the size with non-parametric ANOVA. We didn't found differences in centroid size between females and males; however, the shape was significantly different between sex. In the cross-validation DA, 82% specimens were correctly classified into females and 88% males. Our study represents the first investigation that quantifies the sexual shape and size dimorphism in Piophila casei, and this could be a basis for further studies that combines geometric morphometrics tools and forensic entomology.

Discrimination analysis of phenotypic stocks comparing fish otolith and scale shapes

The effectiveness of discrimination of phenotypic stocks was compared between otolith and scale shapes for Mugil curema specimens collected at five different locations in the Gulf of Mexico and two locations along the Pacific coast during two consecutive years. Geometric morphometric methods were used to determine the discrimination among locations using seven and 22 landmarks for scales and otoliths, respectively. The cross-validated discriminant analysis by location correctly classified 43.2 and 40.2% based on shape variables (Principal Components scores) for otoliths for all locations jointly, while for scales the classification percentages were 48.7 and 47.4% for the first and second years, respectively. Classification results improved when the discrimination analyses were carried out for pairs of locations, with 51.4 to 82.6% for otoliths and 72.7 to 97.1% for scales. The analysis was run for two consecutive years and the results for both years were best for the scales. Thus, fish scale shape offers a straightforward, non-destructive, accessible, quick and inexpensive method to trace fish phenotypic stocks.

Verifying the geographical origin of poultry: The application of stable isotope and trace element (SITE) analysis

Stable isotope and elemental analysis, together with statistical processing of the resultant data has been used to determine the geographical origin of poultry and hence provide a means to verify poultry labels originating from major producing countries/regions. Multivariate statistical analysis has demonstrated that 18 variables, including carbon, hydrogen and nitrogen stable isotope ratios and elemental concentrations of magnesium, thallium, rubidium and molybdenum, are important parameters in poultry origin determination. Using cross-validated discriminant analysis 88.3% of poultry geographical origins were correctly classified (n = 339). Individual correct-classification rates were as follows; China, 100% (n = 36); Brazil, 94.1% (n = 101); Europe 92% (n = 87); Chile 82.6% (n = 46); Thailand, 70.3% (n = 46) and Argentina 50% (n = 10). The main identification errors were associated with miss-classification of Argentinean samples with those originating from Chile and Thailand. Carbon stable isotope ratios of chicken meat indicate the quantity of maize in the diet and this leads to useful discrimination between a large proportion of European poultry and poultry reared in locations such as South America, Thailand and China where maize feeding predominates. The use of poultry carbon isotope values as a simple ‘screening’ parameter to differentiate European poultry meat from other major importers is not as reliable as for the differentiation of European and South American beef. However carbon isotope ratios will be useful in most instances to corroborate suspicion of mislabelling of non corn-fed European poultry. The stable isotopes of hydrogen and oxygen in chicken meat change in a similar way to surface waters around the globe. Our findings support the hypothesis that the global isotopic variation of stable isotopes in drinking water and feed are transferred into animal tissue and can be used to help establish an animal's geographic origin. This is a significant finding and mirrors our observations for beef skeletal muscle δ2H ‰ and δ18O ‰ values. These systematic variations can be exploited to give a ‘low-resolution’ indication of an animal's geographic origin (e.g. Northern Europe versus the tropics).

3D-Geomorphometrics tooth shape analysis in hypodontia.

Assessment of tooth morphology is an important part of the diagnosis and management of hypodontia patients. Several techniques have been used to analyze tooth form in hypodontia patients and these have shown smaller tooth dimensions and anomalous tooth shapes in patients with hypodontia when compared with controls. However, previous studies have mainly used 2D images and provided limited information. In the present study, 3D surface-imaging and statistical shape analysis were used to evaluate tooth form differences between hypodontia and control patients. Eighteen anatomical landmarks were recorded on the clinical crown of the lower left first permanent molar of 3D scanned study models of hypodontia and control subjects. The study sample group comprised of 120 hypodontia patients (40 mild, 40 moderate, and 40 severe hypodontia patients) and 40 age- and sex-matched controls. Procrustes coordinates were utilized to scale and superimpose the landmark coordinate data and then were subjected to principal component analysis (PCA). Subsequently, differences in shape as well as size were tested statistically using allometric analysis and MANOVA. Significant interaction was found between the two factor variables “group” and “sex” (p < 0.002). Overall expected accuracies were 66 and 56% for females and males, respectively, in the cross-validated discriminant-analysis using the first 20 PCs. Hypodontia groups showed significant shape differences compared with the control subjects (p < 0.0001). Significant differences in tooth crown shape were also found between sexes (p < 0.0001) within groups. Furthermore, the degree of variation in tooth form was proportional to the degree of the severity of the hypodontia. Thus, quantitative measurement of tooth shape in hypodontia patients may enhance the multidisciplinary management of those patients.

An Improved Motion Compensation Algorithm Based on Discriminant Analysis

Considering the problem that vibration signals which are generated by three-axis accelerations will impact turbulence signal, an improved motion compensation algorithm based on discriminant analysis is proposed. The characteristics of three axis acceleration signals are got by using cross validation discriminant analysis method to test the performance of de-noising among different filtering orders which are got by three-axis accelerations vibration signals. Finally the discriminant function is found to get the optimal filter order. The results of simulation and real sea experiment data statistical analysis shows that the algorithm improves the de-noising performance and can be better applied to ocean turbulence signal de-noising processing.

Reflectance changes due to pine sawfly attack detected using multitemporal SPOT satellite data

This study investigates the relationship between Leaf Area Index (LAI) reduction in pine stands caused by pine sawfly (Neodiprion sertifier) larva and reflectance change measured using multitemporal optical satellite data. The study was carried out in 552 Scots Pine (Pinus sylvestris)-dominated stands in southern Norway (60° 41′ N, 12° 18′ E). Post-damage Satellite Pour l'Observation de la Terre (SPOT) satellite data were calibrated to surface reflectance using reflectance products of the moderate-resolution imaging spectroradiometer (MODIS). Standwise reflectance change was then computed by subtracting a pre-damage SPOT image that had been relative calibrated to the post-damage image using histogram matching. The reflectance changes were related to changes in LAI obtained from multitemporal lidar data calibrated with field measurements made with a LiCOR LAI-2000 plant canopy analyser. The reduced needle biomass growth due to the insect damage caused an increase in reflectance on the order of 0.002–0.015 in the visible and short-wave infrared SPOT bands and a decrease of 0.01 in the near infrared (NIR) band compared with a large reference data set with normally developed stands. A cross-validated discriminant analysis showed that 79% of the damaged stands could be separated from the undamaged stands by using the SPOT data.

Population connectivity among geographic variants within the Lutjanidae (Pisces) of the Mexican Pacific coast through fish scale shape recognition

Fish scale shape was used to identify geographic variants among Lutjanidae ( Lutjanus argentiventris, L. guttatus and L. peru ). Specimens were collected from three different geographic areas, north to south of the tropical Pacific coast of Mexico: Puerto Vallarta (PV), Manzanillo (MA) and Caleta de Campos (CC). Configuration of landmark coordinates of fish scales were scaled, translated and rotated using generalized procrustes analysis, followed by principal components analysis of resulting shape coordinates. Principal component scores were submitted to cross-validated discriminant analysis to determine the efficacy of scale landmarks for discrimination by geographic variants. This was done with shape and form (shape plus size). PV and MA were recognized as one population different from the CC sampling area. Using only shape (without size), identification rates predicted geographic variant membership much better than chance (91.3%, 70.6% and 85.4% for L. argentiventris, L. guttatus and L. peru , respectively), and taking size into account, classification is somewhat improved (90.6%, 80.1% and 87.5% for L. argentiventris, L. guttatus and L. peru , respectively). Consistency of the two populations for the three species shows non-fortuitous events. Population discrimination confirmed previous genetic studies that show a zoogeographic barrier between the North Equatorial Current and the California Current. The method is non-destructive, fast and less expensive than genetic analysis, thus allowing screening of many individuals for traceability of fish.

Differentiating short- and long-term effects of diet in the obese mouse using 1H-nuclear magnetic resonance metabolomics

This study determined whether targeted metabolomic profiling of serum, using 1H nuclear magnetic resonance, could be employed to distinguish the effects of obesity from those of diet in mice. Following weaning, littermates were randomly divided into two diet groups: chow and high fat. After 12 weeks of dietary manipulation, fat-fed animals were obese and hyperglycaemic. Mice from each treatment either maintained their current diet or switched to the opposite diet for a final week. Differences in metabolite levels were determined using orthogonal projection to latent structures and cross-validated discriminant analysis. The short- and long-term effects of each diet could be clearly distinguished. Short-term diet effects are the major contributor to the metabolic profile, underscoring the need for controls beyond the standard fast before serum collection. This work shows the importance of dietary controls when attempting to isolate obesity-related changes and highlights the ability of metabolomics to identify subtle changes when experiments are properly structured.