scholarly journals Cranial variability and differentiation among golden jackals (Canis aureus) in Europe, Asia Minor and Africa

ZooKeys ◽  
2020 ◽  
Vol 917 ◽  
pp. 141-164 ◽  
Author(s):  
Stoyan Stoyanov
Keyword(s):  
North Africa ◽  
Principal Component ◽  
Distinct Species ◽  
Asia Minor ◽  
Golden Jackal ◽  
Genetic Studies ◽  
The Caucasus ◽  
Linear Discriminant ◽  
Canis Aureus ◽  
Morphological Studies

Golden jackal (Canis aureus) expansion in the last decades has triggered research interest in Europe. However, jackal phylogeny and taxonomy are still controversial. Morphometric studies in Europe found differences between Dalmatian and the other European jackals. Recent genetic studies revealed that African and Eurasian golden jackals are distinct species. Moreover, large Canis aureus lupaster may be a cryptic subspecies of the African golden jackal. Although genetic studies suggest changes in Canis aureus taxonomy, morphological and morphometric studies are still needed. The present study proposes the first comprehensive analysis on a wide scale of golden jackal skull morphometry. Extensive morphometric data of jackal skulls from Europe (including a very large Bulgarian sample), Asia Minor, and North Africa were analysed, by applying recently developed statistical tools, to address the following questions: (i) is there geographic variation in skull size and shape among populations from Europe, Anatolia and the Caucasus?, (ii) is the jackal population from the Dalmatian coast different?, and (iii) is there a clear distinction between the Eurasian golden jackal (Canis aureus) and the African wolf (Canis lupaster sensu lato), and among populations of African wolves as well? Principal component analysis and linear discriminant analysis were applied on the standardized and log-transformed ratios of the original measurements to clearly separate specimens by shape and size. The results suggest that jackals from Europe, Anatolia and the Caucasus belong to one subspecies: Canis aureus moreotica (I. Geoffroy Saint-Hilaire, 1835), despite the differences in shape of Dalmatian specimens. The present study confirmed morphometrically that all jackals included so far in the taxon Canis aureus sensu lato may represent three taxa and supports the hypothesis that at least two different taxa (species?) of Canis occur in North Africa, indicating the need for further genetic, morphological, behavioural and ecological research to resolve the taxonomic uncertainty. The results are consistent with recent genetic and morphological studies and give further insights on golden jackal taxonomy. Understanding the species phylogeny and taxonomy is crucial for the conservation and management of the expanding golden jackal population in Europe.

scholarly journals An assessment of the taxonomic validity of three species of marsupial frogs (Anura: Hemiphractidae: Gastrotheca) from the Yungas of Bolivia based on external morphology and cranial osteology

Zootaxa ◽  
2021 ◽  
Vol 5068 (2) ◽  
pp. 211-239
Author(s):  
CLAUDIA LANSAC ◽  
RODRIGO AGUAYO ◽  
IGNACIO DE LA RIVA
Keyword(s):  
Principal Component ◽  
Taxonomic Status ◽  
Ct Scanning ◽  
Developmental State ◽  
Morphological Characters ◽  
Biological Entity ◽  
Nominal Species ◽  
Linear Discriminant ◽  
Morphological Studies ◽  
Cranial Osteology

The genus Gastrotheca (Anura: Hemiphractidae) is a group of marsupial frogs particularly diverse in Andean regions. Several taxonomic studies of this genus have been conducted in the humid cloud forests—or Yungas—of the Andean eastern slopes of central Bolivia (departments of Cochabamba and Santa Cruz). Yet, the distinction among three species that occur sympatrically in these forests, G. lauzuricae (proposed as a junior synonym of G. coeruleomaculatus in 2015), G. piperata, and G. splendens, remains unclear since the morphological characters that purportedly support their differentiation are variable and partly shared among them. We have carried out external morphological studies, including multivariate morphometric analyses, to assess how they support the taxonomic status of these three species. We also evaluated characters of the cranial osteology of a sample of six individuals using micro CT-scanning. Principal component and linear discriminant analyses resulted in a great overlap among the putative species. Cranial osteological comparisons did not reveal highly significant differences among them, but suggested that different degrees of hyperossification could be related to the developmental state of individuals. Our results indicate that most morphological and osteological reported differences between the three species likely represent intraspecific variation. Thus, we propose that the three nominal species belong to a single biological entity, for which the name Gastrotheca splendens (Schmidt, 1857) has priority. We also restrict the name Gastrotheca coeruleomaculatus (Werner, 1899) to externally similar congeneric populations from the Yungas forests of department of La Paz, but highlighting the need of a detailed evaluation of their taxonomic identity.  

scholarly journals Presence ofLeishmaniaandBrucellaSpecies in the Golden JackalCanis aureusin Serbia

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Duško Ćirović ◽  
Dimosthenis Chochlakis ◽  
Snežana Tomanović ◽  
Ratko Sukara ◽  
Aleksandra Penezić ◽  
...  
Keyword(s):  
Eastern Europe ◽  
Potential Role ◽  
Zoonotic Diseases ◽  
Golden Jackal ◽  
The Caucasus ◽  
Tissue Samples ◽  
Canis Aureus ◽  
The Past ◽  
South Eastern Europe

The golden jackalCanis aureusoccurs in south-eastern Europe, Asia, the Middle East, the Caucasus, and Africa. In Serbia, jackals neared extinction; however, during the last 30 years, the species started to spread quickly and to increase in number. Few studies in the past have revealed their potential role as carriers of zoonotic diseases. Animal samples were collected over a three-year period (01/2010–02/2013) from 12 sites all over Serbia. Of the tissue samples collected, spleen was chosen as the tissue to proceed; all samples were tested forLeishmaniaspecies andBrucellaspecies by real-time PCR. Of the 216 samples collected, 15 (6.9%) were positive forLeishmaniaspecies, while four (1.9%) were positive forB. canis. The potential epidemiologic role of the golden jackal in carrying and dispersing zoonotic diseases in Serbia should be taken under consideration when applying surveillance monitoring schemes.

scholarly journals A preliminary Revision of the Genus Dociostaurus, Fieb

1921 ◽  
Vol 11 (4) ◽  
pp. 397-407 ◽  
Author(s):  
B. P. Uvarov
Keyword(s):  
Eastern Europe ◽  
North Africa ◽  
Individual Variability ◽  
Natural System ◽  
Asia Minor ◽  
The Caucasus ◽  
South Eastern ◽  
Western Asia ◽  
South Eastern Europe ◽  
Dociostaurus Maroccanus

The genus Dociostaurus, Fieb., which is synonymous with Stauronotus, Fisch., includes several species of locusts and grasshoppers injurious to agriculture in South-Eastern Europe, Central and Western Asia and North Africa, the well known Moroccan locust (Dociostaurus maroccanus, Thunb.) being one of the worst pests in Algeria, Tunisia, Asia Minor, the Caucasus and Turkestan. The systematics of the species of this genus are in a very unsatisfactory state, and this, together with the tendency of the species to individual variability, is the cause of many mistakes in their identification on the part of economic entomologists. The object of this paper is, therefore, to establish a more or less natural system of the species enabling everyone to identify them with certainty.

Through the Lens of Gurdjieff

2016 ◽  
Vol 11 (1) ◽  
pp. 36-52
Author(s):  
Michael Pittman
Keyword(s):  
Participant Observation ◽  
Field Research ◽  
Spiritual Transformation ◽  
Spiritual Practice ◽  
Asia Minor ◽  
Eastern Asia ◽  
The Caucasus ◽  
Successive Generations ◽  
Spiritual Conversation

G. I. Gurdjieff (c.1866–1949) was born in Gyumri, Armenia and raised in the Caucasus and eastern Asia Minor. He also traveled extensively throughout Turkey to places of pilgrimage and in search of Sufi teachers. Through the lens of Gurdjieff’s notion of legominism, or the means by which spiritual teachings are transmitted from successive generations, this article explores the continuing significance of spiritual practice and tradition and the ways that these forms remain relevant in shaping contemporary trends in spirituality. Beginning with Gurdjieff’s use of legominism, the article provides reflection on some early findings done in field research in Turkey— through site visits, interviews and participant-observation—conducted in the summers of 2014 and 2015. The aim of the project is both to meet individuals and groups, particularly connected to Sufism, that may have some contact with the influences that Gurdjieff would have been familiar with, and to visit some of the sites that were part of Gurdjieff’s early background and which served to inform his work. Considerations of contemporary practices include the view of spiritual transmission, and practices of pilgrimage, prayer and sohbet, or spiritual conversation, in an ongoing discourse about spiritual transformation.

scholarly journals Real Time Breath Analysis Using Portable Gas Chromatography for Adult Asthma Phenotypes

Metabolites ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 265
Author(s):  
Ruchi Sharma ◽  
Wenzhe Zang ◽  
Menglian Zhou ◽  
Nicole Schafer ◽  
Lesa A. Begley ◽  
...  
Keyword(s):  
Gas Chromatography ◽  
Real Time ◽  
Rapid Assessment ◽  
Principal Component ◽  
Corticosteroid Treatment ◽  
Breath Analysis ◽  
Blood Eosinophil ◽  
Exhaled Breath ◽  
Respiratory Illnesses ◽  
Linear Discriminant

Asthma is heterogeneous but accessible biomarkers to distinguish relevant phenotypes remain lacking, particularly in non-Type 2 (T2)-high asthma. Moreover, common clinical characteristics in both T2-high and T2-low asthma (e.g., atopy, obesity, inhaled steroid use) may confound interpretation of putative biomarkers and of underlying biology. This study aimed to identify volatile organic compounds (VOCs) in exhaled breath that distinguish not only asthmatic and non-asthmatic subjects, but also atopic non-asthmatic controls and also by variables that reflect clinical differences among asthmatic adults. A total of 73 participants (30 asthma, eight atopic non-asthma, and 35 non-asthma/non-atopic subjects) were recruited for this pilot study. A total of 79 breath samples were analyzed in real-time using an automated portable gas chromatography (GC) device developed in-house. GC-mass spectrometry was also used to identify the VOCs in breath. Machine learning, linear discriminant analysis, and principal component analysis were used to identify the biomarkers. Our results show that the portable GC was able to complete breath analysis in 30 min. A set of nine biomarkers distinguished asthma and non-asthma/non-atopic subjects, while sets of two and of four biomarkers, respectively, further distinguished asthmatic from atopic controls, and between atopic and non-atopic controls. Additional unique biomarkers were identified that discriminate subjects by blood eosinophil levels, obese status, inhaled corticosteroid treatment, and also acute upper respiratory illnesses within asthmatic groups. Our work demonstrates that breath VOC profiling can be a clinically accessible tool for asthma diagnosis and phenotyping. A portable GC system is a viable option for rapid assessment in asthma.

scholarly journals A model for spectroscopic food sample analysis using data sonification

2021 ◽  
Author(s):  
Hsein Kew
Keyword(s):  
Dimensionality Reduction ◽  
Classification Accuracy ◽  
Reduction Method ◽  
Real Life ◽  
Principal Component ◽  
Relevant Information ◽  
Analysis Model ◽  
Linear Discriminant ◽  
Audio Output ◽  
Dimensionality Reduction Method

AbstractIn this paper, we propose a method to generate an audio output based on spectroscopy data in order to discriminate two classes of data, based on the features of our spectral dataset. To do this, we first perform spectral pre-processing, and then extract features, followed by machine learning, for dimensionality reduction. The features are then mapped to the parameters of a sound synthesiser, as part of the audio processing, so as to generate audio samples in order to compute statistical results and identify important descriptors for the classification of the dataset. To optimise the process, we compare Amplitude Modulation (AM) and Frequency Modulation (FM) synthesis, as applied to two real-life datasets to evaluate the performance of sonification as a method for discriminating data. FM synthesis provides a higher subjective classification accuracy as compared with to AM synthesis. We then further compare the dimensionality reduction method of Principal Component Analysis (PCA) and Linear Discriminant Analysis in order to optimise our sonification algorithm. The results of classification accuracy using FM synthesis as the sound synthesiser and PCA as the dimensionality reduction method yields a mean classification accuracies of 93.81% and 88.57% for the coffee dataset and the fruit puree dataset respectively, and indicate that this spectroscopic analysis model is able to provide relevant information on the spectral data, and most importantly, is able to discriminate accurately between the two spectra and thus provides a complementary tool to supplement current methods.

Anatomization of the systems of dimension relaxation for facial recognition

2020 ◽  
pp. 1-11
Author(s):  
Mayamin Hamid Raha ◽  
Tonmoay Deb ◽  
Mahieyin Rahmun ◽  
Tim Chen
Keyword(s):  
Face Recognition ◽  
Main Idea ◽  
Principal Component ◽  
Feature Space ◽  
Projection Methods ◽  
Data Representation ◽  
Linear Discriminant ◽  
Class Differences ◽  
Underlying Space ◽  
Maximum Variance

Face recognition is the most efficient image analysis application, and the reduction of dimensionality is an essential requirement. The curse of dimensionality occurs with the increase in dimensionality, the sample density decreases exponentially. Dimensionality Reduction is the process of taking into account the dimensionality of the feature space by obtaining a set of principal features. The purpose of this manuscript is to demonstrate a comparative study of Principal Component Analysis and Linear Discriminant Analysis methods which are two of the highly popular appearance-based face recognition projection methods. PCA creates a flat dimensional data representation that describes as much data variance as possible, while LDA finds the vectors that best discriminate between classes in the underlying space. The main idea of PCA is to transform high dimensional input space into the function space that displays the maximum variance. Traditional LDA feature selection is obtained by maximizing class differences and minimizing class distance.

scholarly journals Habitat use of golden jackals (Canis aureus) in riverine areas of northern Bosnia and Herzegovina

2021 ◽  
Vol 67 (1) ◽  
Author(s):  
Aldin Selimovic ◽  
Eva Maria Schöll ◽  
Larissa Bosseler ◽  
Jennifer Hatlauf
Keyword(s):  
Habitat Use ◽  
Bosnia And Herzegovina ◽  
Agricultural Practices ◽  
Binary Logistic Regression ◽  
Food Sources ◽  
Golden Jackal ◽  
Canis Aureus ◽  
Logistic Regression Models ◽  
Habitat Analysis ◽  
Group Density

AbstractRecently confirmed expansion of golden jackals (Canis aureus) into countries without any previous records poses questions, one of them focusing on the species potential and possibly varying habitat use. In this study, we investigated the presence and distribution of golden jackals in northern Bosnia and Herzegovina, where knowledge about golden jackal distribution and habitat use is still scarce. We used bioacoustic stimulation as a non-invasive tool to gather data on golden jackal presence. Habitat structures potentially selected by the species were assessed at 92 calling stations and used as input for binary logistic regression models. Our study area covered approximately 1150 km2, and bioacoustic stimulation within this area resulted in an estimated minimum relative group density of 3.5 territorial groups per 100 km2. We found territorial groups at distances between 15 and 38 km southwards from the river Sava but always within a maximum range of 3 km to perennial watercourses. Habitat analysis identified shrub vegetation and pastures as structures with a significant effect on the presence of resident golden jackals. Probability that golden jackals answered at calling stations increased with increasing surface area covered with pastures and shrubs. Distances between golden jackal territories and the nearest human settlement were relatively small. Our results indicate that structures like transitional woodland-shrubs and pastures, together with other potential influencing factors like local agricultural practices, low hunting pressure, diverse natural and anthropogenic food sources, could have benefited the settlement of golden jackals in the northern lowlands of Bosnia and Herzegovina.

scholarly journals Multiscale Supervised Classification of Point Clouds with Urban and Forest Applications

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4523 ◽  
Author(s):  
Carlos Cabo ◽  
Celestino Ordóñez ◽  
Fernando Sáchez-Lasheras ◽  
Javier Roca-Pardiñas ◽  
and Javier de Cos-Juez
Keyword(s):  
Random Forest ◽  
Laser Scanning ◽  
Supervised Classification ◽  
Computing Time ◽  
Principal Component ◽  
Point Clouds ◽  
Support Vector ◽  
Linear Discriminant ◽  
Vector Machines ◽  
Input Variables

We analyze the utility of multiscale supervised classification algorithms for object detection and extraction from laser scanning or photogrammetric point clouds. Only the geometric information (the point coordinates) was considered, thus making the method independent of the systems used to collect the data. A maximum of five features (input variables) was used, four of them related to the eigenvalues obtained from a principal component analysis (PCA). PCA was carried out at six scales, defined by the diameter of a sphere around each observation. Four multiclass supervised classification models were tested (linear discriminant analysis, logistic regression, support vector machines, and random forest) in two different scenarios, urban and forest, formed by artificial and natural objects, respectively. The results obtained were accurate (overall accuracy over 80% for the urban dataset, and over 93% for the forest dataset), in the range of the best results found in the literature, regardless of the classification method. For both datasets, the random forest algorithm provided the best solution/results when discrimination capacity, computing time, and the ability to estimate the relative importance of each variable are considered together.

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