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Fig. 5 in Evolution of Poecilimon jonicus group (Orthoptera: Tettigoniidae): a history linked to the Aegean Neogene paleogeography

Fig. 5 Phylo-spatial dimension of the P. jonicus group based on the mtDNA phylogeny (data combined from COI+ND2 and 16S rRNA+12S rRNA datasets). Blue, "Anatolian" lineage; green, "Cretan" lineage; orange, "Balkan" lineage including Poecilimon inflatus

Fig. 3 in Evolution of Poecilimon jonicus group (Orthoptera: Tettigoniidae): a history linked to the Aegean Neogene paleogeography

Fig. 3 Phylogenetic relationships of the members of the Poecilimon jonicus group sensu lato with four outgroups from the genus Poecilimon and two outgroups from additional genera of Barbitistini (P, Poecilimon; L., Leptophyes; I., Isophya) based on Bayesian inference analysis of ITS1+ITS2 sequences. a 665 bp alignment-tree of sequences obtained in this study and from GenBank (Ullrich et al. 2010) and b 717 bp alignment-tree of sequences available from Ullrich et al. (2010). Node support is shown at (below) resolved branches

Fig. 2 in Evolution of Poecilimon jonicus group (Orthoptera: Tettigoniidae): a history linked to the Aegean Neogene paleogeography

Fig. 2 Distribution of the members of the Poecilimon jonicus group sensu lato—ranges of all species currently considered within the groups P. jonicus and P. inflatus including subspecies of P. jonicus shown with different colors as marked in the plates

Fig. 1 in Evolution of Poecilimon jonicus group (Orthoptera: Tettigoniidae): a history linked to the Aegean Neogene paleogeography

Fig. 1 General appearance of representatives of the Poecilimon jonicus group. a, b P. jonicus lobulatus (a male, b female); c P. werneri (female); d, e P. erimanthos (d male, e female); f P. inflatus lyciae (male); g, h

Figure 6. Interface of FFE program-Impact of Ethnic Group on Human Emotion Recognition Using Backpropagation Neural Network

Points, Features Extraction and save all input information for the classifier (Features, Ethnic group, Gender and emotion). Figure 6 shows the interface of FFE program.

Figure 7. Samples of MSFDE dataset-Impact of Ethnic Group on Human Emotion Recognition Using Backpropagation Neural Network

We performed groups of experiments to study the impact of ethnic group (race) in the accuracy of emotion recognition with three kinds of ethnic groups (Asian, Caucasian as African). So we have three experiments, each experiment has a neural network as a classifier, and each neural network has three layers where there are 16 neurons in the hidden layer except Asian network has 17 neurons (the best result with 17 neurons for Asians).

Figure 3. 46 points are selected on face elements to describe the emotions.-Impact of Ethnic Group on Human Emotion Recognition Using Backpropagation Neural Network

The number of points and the position of points are not standardized, but it is depending on the features that will be extracted, and used for the classifier. Many researches use various number of points and positions based on their view about the feature to be considered [13] [18] [19]. Figure 3 shows the points we used.

Figure 1. A proposed approach-of Ethnic Group on Human Emotion Recognition Using Backpropagation Neural Network

Our proposed approach uses the face expression to detect the emotions through five steps that shows in Figure 1.

Figure. 2. Examples of Angry from different races. (A,B) African. (C,D) Asian. (E,F) Caucasian.-Impact of Ethnic Group on Human Emotion Recognition Using Backpropagation Neural Network

We chose 46 points which are distributed over human face image and use these points for features extraction. The choice of these points is to determine the shape of each element of the face (eyes, eyebrows and mouth), because the shape of these elements is changeable for each emotion, but these changes are different for each race as shown in Figure 2.

Figure 4. Distance between eyebrow and eye.-Impact of Ethnic Group on Human Emotion Recognition Using Backpropagation Neural Network

Based on what we stated above, we need to extract 28 features, which describe the distances between certain points explained in the previous stage, these features are classified into six groups, and each group describes the features of one face element. All features are a vertical distances between two points. Group one contains seven features for mouth, groups two and three contains 14 features for eyes, groups four and five contain six features for eyebrows, and the last group has one feature only which is the distance between the beginning of the eyebrow and the beginning of the eye in same side, this is significant (from point 23 to 15) because it is used to measure the distance of eyebrow from the eye. This feature is shown in Figure 4 by a line.

Figure 5. ANN Structure 4.-Impact of Ethnic Group on Human Emotion Recognition Using Backpropagation Neural Network

For classification purpose of the emotions, we use ANN of supervised learning based on backpropagation algorithm. Backpropagation neural network architecture is used with its standards learning function with 28 inputs representing the extracted features and 6 outputs representing 6 emotions, happy, sad, angry, fear, shame and disgust. the emotions. We have also a hidden layer with 16 nodes selected after various trails to obtain the best results. The used ANN is depicted in Figure 5.

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BRAIN Journal-Electrophysiological Neuroimaging using sLORETA Comparing 100 Schizophrenia Patients to 48 Patients with Major Depression -Figure 1. Group comparisons designed for isolating the mesolimbic Dopamine D2

All patients diagnosed with Schizophrenia were medicated with atypical antipsychotics, Olanzapine (dose 5mg/day to 20mg/day) or Risperidone (dose 1mg/day to 4mg/day) blocking both Dopamine D2 and Serotonin 5-HT2 receptors. Whereas, all of the patients diagnosed with Major Depression or Depressive Episode were medicated with Sertraline (50mg/day to 200mg/day maximum dose) or Citalopram (20mg/day to 40mg/day maximum dose). This research protocol was approved by the Bioethical Commission of the Medical University of Lublin.

Fig. 4 in Taxonomy of the poorly known Quedius mutilatus group of wingless montane species from Middle Asia (Coleoptera: Staphylinidae: Staphylinini)

Fig. 4. Aedeagi in the Quedius mutilatus group. A–B. Quedius mutilatus Eppelsheim, 1888. C–D. Quedius kalabi Smetana, 1995. E–F. Quedius kungeicus sp. nov. G–N. Quedius equus Smetana, 2014 (Karkara Valley, Kazakhstan), variability of the structure of the aedeagus. A, C, E, G, I, K, M = median lobe, laterally. B, D, F, H, J, L, N = paramere (dissected from median lobe), underside (side facing median lobe). Scale bars: 1 mm.

Fig. 3 in Taxonomy of the poorly known Quedius mutilatus group of wingless montane species from Middle Asia (Coleoptera: Staphylinidae: Staphylinini)

Fig. 3. Holotype of Quedius kalabi Smetana, 1995. A. Habitus. B. Permanent preparation of the aedeagus. Scale bars: 1 mm.

Fig. 5 in Taxonomy of the poorly known Quedius mutilatus group of wingless montane species from Middle Asia (Coleoptera: Staphylinidae: Staphylinini)

Fig. 5. Quedius kungeicus sp. nov. A. Habitus. B. Aedeagus, laterally. C. Median lobe, in parameral view (paramere detached). D. Paramere, underside (side facing median lobe). Scale bars: 1 mm.

Fig. 2 in Taxonomy of the poorly known Quedius mutilatus group of wingless montane species from Middle Asia (Coleoptera: Staphylinidae: Staphylinini)

Fig. 2. Lectotype of Quedius mutilatus Eppelsheim, 1888. A. Habitus. B. Permanent preparaion of the aedeagus. Scale bars: 1 mm.

Fig. 1 in Taxonomy of the poorly known Quedius mutilatus group of wingless montane species from Middle Asia (Coleoptera: Staphylinidae: Staphylinini)

Fig. 1. Distribution and aedeagus variability of the Quedius mutilatus group in the Tien-Shan Mountains. Numbers are specified in Table 1. Empty symbols = type spcimens (for Q. kalabi precise locality of the holotype unknown);? = ambiguously labelled or undetermined material. Scale bar: 0.5 mm.

Fig. 2 in Revision of the Astyanax orthodus species-group (Teleostei: Characidae) with descriptions of three new species

Fig. 2. Astyanax embera sp. nov., holotype, 83.0 mm SL, Telembí River at mouth of Yamunde River, 1 km below Barbacoas, Municipality of Barbacoas, Nariño, Pacific coast of Colombia (IUQ 3614). Scale bar = 1 cm.

Fig. 3 in Revision of the Astyanax orthodus species-group (Teleostei: Characidae) with descriptions of three new species

Fig. 3. Shape of caudal-peduncle spot in species of the Astyanax orthodus species-group. A. Astyanax orthodus Eigenmann, 1907. B. Astyanax embera sp. nov. Scale bar = 1 cm.

Fig. 10. Astyanax superbus Myers, 1942, 70.4 in Revision of the Astyanax orthodus species-group (Teleostei: Characidae) with descriptions of three new species

Fig. 10. Astyanax superbus Myers, 1942, 70.4 mm SL, Guache River, Garabote, Portuguesa state, Venezuela (MCNG 36349). Scale bar = 1 cm.