DNA-hybridisation Studies of Marsupials and their Implications for Metatherian Classification

1997 ◽  
Vol 45 (3) ◽  
pp. 211 ◽  
Author(s):  
John A. W. Kirsch ◽  
Mark S. Springer ◽  
François-Joseph Lapointe
Keyword(s):  
Monophyletic Group ◽  
Pairwise Comparisons ◽  
South American ◽  
New Classification ◽  
Data Set ◽  
Hierarchical Levels ◽  
Dna Hybridisation ◽  
Taxon Tree ◽  
The Individual

We review past DNA-hybridisation studies of marsupials and present a reanalysis of the data, utilising results from our and additional studies to formulate and rationalise a new classification of Marsupialia. In the reanalysis, 13 individual DNA-hybridisation matrices, many lacking some pairwise comparisons, were sutured in stages to provide the basis for generating a tree of 101 marsupials plus an outgroup eutherian; a fourteenth matrix provided data for a tree including eight additional eutherians and a monotreme. Validation was achieved by jackknifing on taxa for each matrix as well as on tables combining two or more matrices generated during assembly of the 102-taxon data set. The results are consistent with most conclusions from the individual studies and dramatise the unevenness of hierarchical levels in current classifications of marsupials. In particular, the affinities of the American marsupial Dromiciops gliroides with, and the distinctness of marsupial bandicoots from, Australasian metatherians are reaffirmed, while opossums are shown to be as internally divergent as are most members of the order Diprotodontia. Calibration of the 102-taxon tree and dating of the major dichotomies suggest that no extant marsupial lineage originated before the latest Cretaceous, and that all of them together with most South American and all Australasian fossils should be recognised as a monophyletic group contrasting with a largely Laurasian (if possibly paraphyletic) taxon. These inferences, together with the details of the phylogeny, mandate that the misleading ‘Australian’ v. ‘American’ distinction be abandoned, even as a geographic convenience.

The type species of the threadsnake genus Tricheilostoma Jan revisited (Squamata, Leptotyphlopidae)

Zootaxa ◽  
2011 ◽  
Vol 3027 (1) ◽  
pp. 63 ◽  
Author(s):  
S. BLAIR HEDGES
Keyword(s):  
Type Species ◽  
South American ◽  
New Classification ◽  
Practical Concern ◽  
The Family ◽  
Taxonomic Problem ◽  
Taxonomic Changes

For most of the last 150 years, Tricheilostoma Jan, 1860 has resided in the synonymy of other snake genera such as Glauconia Gray, 1845 and Leptotyphlops Fitzinger, 1843 (Boulenger, 1893; McDiarmid et al., 1999). Thus there has been less practical concern over the identity of the type species. This changed recently with the proposal of a new classification of the family Leptotyphlopidae and resurrection of the Genus Tricheilostoma (Adalsteinsson et al., 2009). Pinto et al. (2010) alluded to a potential taxonomic problem with the type species of that genus, but determined that no change was necessary. However, the problem remains and affects 15 species of South American and African snakes. The purpose of this note is to resolve the issue and make the necessary taxonomic changes.

Neural Network Interpretation of Ultrasonic Response for Concrete Condition Assessment

1996 ◽  
Vol 1532 (1) ◽  
pp. 80-86
Author(s):  
Samir N. Shoukry ◽  
D.R. Martinelli
Keyword(s):  
Neural Network ◽  
Concrete Structures ◽  
Neural Nets ◽  
Training Data ◽  
Neural Network Modeling ◽  
Correct Classification ◽  
Data Set ◽  
Ultrasonic Signals ◽  
The Individual

Ultrasonic testing of concrete structures using the pitch-catch method is an effective technique for testing concrete structures that cannot be accessed on two opposing surfaces. However, the ultrasonic signals so measured are extremely noisy and contain a complicated pattern of multiple frequency-coupled reflections that makes interpretation a difficult task. In this investigation, a neural network modeling approach is used to classify ultrasonically tested concrete specimens into one of two classes: defective or nondefective. Different types of neural nets are used, and their performance is evaluated. It was found that correct classification of the individual ultrasonic signals could be achieved with an accuracy of 75 percent for the test set and 95 percent for the training set. These recognition rates lead to the correct classification of all the individual test specimens. The study shows that although some neural net architectures may show high performance using a particular training data set, their results might not be consistent. In this paper, the consistency of the network performance was tested by shuffling the training and testing data sets.

scholarly journals Formation of the crater suevite sequence from the Chicxulub peak ring: A petrographic, geochemical, and sedimentological characterization

2021 ◽  
Author(s):  
Pim Kaskes ◽  
Sietze J. de Graaff ◽  
Jean-Guillaume Feignon ◽  
Thomas Déhais ◽  
Steven Goderis ◽  
...  
Keyword(s):  
Compositional Data ◽  
Ocean Water ◽  
New Classification ◽  
Planktic Foraminifera ◽  
Data Set ◽  
Scientific Drilling ◽  
International Ocean Discovery Program ◽  
Chicxulub Impact ◽  
The Impact

This study presents a new classification of a ∼100-m-thick crater suevite sequence in the recent International Ocean Discovery Program (IODP)-International Continental Scientific Drilling Program (ICDP) Expedition 364 Hole M0077A drill core to better understand the formation of suevite on top of the Chicxulub peak ring. We provide an extensive data set for this succession that consists of whole-rock major and trace element compositional data (n = 212) and petrographic data supported by digital image analysis. The suevite sequence is subdivided into three units that are distinct in their petrography, geochemistry, and sedimentology, from base to top: the ∼5.6-m-thick non-graded suevite unit, the ∼89-m-thick graded suevite unit, and the ∼3.5-m-thick bedded suevite unit. All of these suevite units have isolated Cretaceous planktic foraminifera within their clastic groundmass, which suggests that marine processes were responsible for the deposition of the entire M0077A suevite sequence. The most likely scenario describes that the first ocean water that reached the northern peak ring region entered through a N-NE gap in the Chicxulub outer rim. We estimate that this ocean water arrived at Site M0077 within 30 minutes after the impact and was relatively poor in rock debris. This water caused intense quench fragmentation when it interacted with the underlying hot impact melt rock, and this resulted in the emplacement of the ∼5.6-m-thick hyaloclastite-like, non-graded suevite unit. In the following hours, the impact structure was flooded by an ocean resurge rich in rock debris, which caused the phreatomagmatic processes to stop and the ∼89-m-thick graded suevite unit to be deposited. We interpret that after the energy of the resurge slowly dissipated, oscillating seiche waves took over the sedimentary regime and formed the ∼3.5-m-thick bedded suevite unit. The final stages of the formation of the impactite sequence (estimated to be <20 years after impact) were dominated by resuspension and slow atmospheric settling, including the final deposition of Chicxulub impactor debris. Cumulatively, the Site M0077 suevite sequence from the Chicxulub impact site preserved a high-resolution record that provides an unprecedented window for unravelling the dynamics and timing of proximal marine cratering processes in the direct aftermath of a large impact event.

scholarly journals Cheaters, Liars, or Both? A New Classification of Dishonesty Profiles

2020 ◽  
Vol 31 (9) ◽  
pp. 1097-1106 ◽  
Author(s):  
David Pascual-Ezama ◽  
Drazen Prelec ◽  
Adrián Muñoz ◽  
Beatriz Gil-Gómez de Liaño
Keyword(s):  
Experimental Studies ◽  
Population Level ◽  
New Classification ◽  
Coin Toss ◽  
Individual Level ◽  
Die Roll ◽  
The Individual

Experimental studies of dishonesty usually rely on population-level analyses, which compare the distribution of claimed rewards in an unsupervised, self-administered lottery (e.g., tossing a coin) with the expected lottery statistics (e.g., 50/50 chance of winning). Here, we provide a paradigm that measures dishonesty at the individual level and identifies new dishonesty profiles with specific theoretical interpretations. We found that among dishonest participants, (a) some did not bother implementing the lottery at all, (b) some implemented but lied about the lottery outcome, and (c) some violated instructions by repeating the lottery multiple times until obtaining an outcome they felt was acceptable. These results held both in the lab and with online participants. In Experiment 1 ( N = 178), the lottery was a coin toss, which permitted only a binary honest/dishonest response; Experiment 2 ( N = 172) employed a six-sided-die roll, which permitted gradations in dishonesty. We replicated some previous results and also provide a new, richer classification of dishonest behavior.

Remarks on the subfam. Betoideae (Chenopodiaceae/Amaranthaceae sensu APGIV)

Phytotaxa ◽  
2019 ◽  
Vol 400 (3) ◽  
pp. 145 ◽  
Author(s):  
DUILIO IAMONICO
Keyword(s):  
New Taxa ◽  
Taxonomic Position ◽  
Monophyletic Group ◽  
New Classification ◽  
Beta Procumbens ◽  
Comprehensive View ◽  
Number Of Species

Subfam. Betoideae (Amaranthaceae Juss./Chenopodiaceae Vent. sensu APGIV) is a monophyletic group which comprises five genera (Aphanisma, Beta, Hablitzia, Oreoblitum, and Patellifolia) and an undefined number of species (11‒16 according to the available literature). While the taxonomic position of the various groups in Betoideae is quite well studied and clarified, nomenclature is still poorly investigated and several names remain to be untypified. The present research has the aim to present a comprehensive view of all taxa (at all ranks) beloning to Betoideae by a list of their accepted names, main synonyms, and types. Taxonomic considerations were also made. The names Aphanisma blitoides, Beta patula, Beta lomatogona, Beta macrorhiza, Beta nana, Beta macrocarpa, Beta bourgaei (= Beta macrocarpa), Oreobliton thesioides, and Beta procumbens are typified on specimens deposited respectively at K (lecto-), BM (lecto-), LE (lecto-), H (lecto-), K (neo-, isoneotypes a FI, GOET, K, WAG), PAL (neo-), G (lecto-, isolectoypes a G, K), P, and C (neo-). The typification of the name Hablitzia tamnoides by Menitsky was discussed and accepted. A new nomenclature change [Beta sect. Corollinae subsect. Nanae (Ulbr.) Iamonico, comb. et stat. nov.] and two new taxa (Beta sect. Beta subsect. Patulae Iamonico, subsect. nov., and Beta sect. Macrocarpae Iamonico, sect. nov.) were proposed. A new classification of Subfam. Betoideae was proposed, including 2 tribes (Beteae, and Hablitzieae), 5 genera (Aphanisma, Beta, Hablitzia, Oreoblitum, and Patellifolia), and for the genus Beta 3 sections and 4 subsections (sect. Beta subsect. Beta, Beta sect. Beta subsect. Patulae Iamonico subsect. nov., sect. Corollinae subsect. Corollinae, sect. Corollinae subsect. nanae (Ulbr.) Iamonico comb. et stat. nov., Beta sect. Macrocarpae Iamonico sect. nov.).

Algorithm Enhancements for Improvement of Localized Classification of Uterine Cervical Cancer Digital Histology Images

2018 ◽  
pp. 234-250
Author(s):  
Haidar Almubarak ◽  
Peng Guo ◽  
R. Joe Stanley ◽  
Rodney Long ◽  
Sameer Antani ◽  
...  
Keyword(s):  
Image Analysis ◽  
Execution Time ◽  
Classification Accuracy ◽  
Medial Axis ◽  
Intraepithelial Neoplasia ◽  
Uterine Cervical Cancer ◽  
Data Set ◽  
The Individual ◽  
Image Analysis Techniques

In prior research, the authors introduced an automated, localized, fusion-based approach for classifying squamous epithelium into Normal, CIN1, CIN2, and CIN3 grades of cervical intraepithelial neoplasia (CIN) from digitized histology image analysis. The image analysis approach partitioned the epithelium along the medial axis into ten vertical segments. Texture, cellularity, nuclear characterization and distribution, and acellular features were computed from each vertical segment. The individual vertical segments were CIN classified, and the individual classifications were fused to generate an image-based CIN assessment. In this chapter, image analysis techniques are investigated to improve the execution time of the algorithms and the CIN classification accuracy of the baseline algorithms. For an experimental data set of 117 digitized histology images, execution time for exact grade CIN classification accuracy was improved by 32.32 seconds without loss of exact grade CIN classification accuracy (80.34% vs. 79.49% previously reported) for this same data set.

Algorithms for automated montage synthesis of images from laser-scanning confocal microscopes

1995 ◽  
Vol 53 ◽  
pp. 650-651
Author(s):  
D. E. Becker
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Laser Scanning ◽  
Cell Counting ◽  
Wide Area ◽  
Data Set ◽  
Computational Synthesis ◽  
Automated Cell Counting ◽  
Partial View ◽  
The Individual

An efficient, robust, and widely-applicable technique is presented for computational synthesis of high-resolution, wide-area images of a specimen from a series of overlapping partial views. This technique can also be used to combine the results of various forms of image analysis, such as segmentation, automated cell counting, deblurring, and neuron tracing, to generate representations that are equivalent to processing the large wide-area image, rather than the individual partial views. This can be a first step towards quantitation of the higher-level tissue architecture. The computational approach overcomes mechanical limitations, such as hysterisis and backlash, of microscope stages. It also automates a procedure that is currently done manually. One application is the high-resolution visualization and/or quantitation of large batches of specimens that are much wider than the field of view of the microscope.The automated montage synthesis begins by computing a concise set of landmark points for each partial view. The type of landmarks used can vary greatly depending on the images of interest. In many cases, image analysis performed on each data set can provide useful landmarks. Even when no such “natural” landmarks are available, image processing can often provide useful landmarks.

Machine Learning Verdict of EEG Signals in Brain Computer Interface

2018 ◽  
pp. 429-441
Author(s):  
M. Jeyanthi ◽  
C. Velayutham
Keyword(s):  
Nearest Neighbor ◽  
Technology Development ◽  
Vital Role ◽  
Svm Classifier ◽  
K Nearest Neighbor ◽  
Data Mining Technique ◽  
Data Set ◽  
Eeg Data ◽  
Irrelevant Attributes

In Science and Technology Development BCI plays a vital role in the field of Research. Classification is a data mining technique used to predict group membership for data instances. Analyses of BCI data are challenging because feature extraction and classification of these data are more difficult as compared with those applied to raw data. In this paper, We extracted features using statistical Haralick features from the raw EEG data . Then the features are Normalized, Binning is used to improve the accuracy of the predictive models by reducing noise and eliminate some irrelevant attributes and then the classification is performed using different classification techniques such as Naïve Bayes, k-nearest neighbor classifier, SVM classifier using BCI dataset. Finally we propose the SVM classification algorithm for the BCI data set.

Sign in / Sign up

Export Citation Format

Share Document