Riber Yilmaz (raincello3)

and generalize findings.The classification of the main pattern types, arch, loop and whorls, is based on the number and location of deltas or triradii, which are areas defined by the confluence of three ridge systems carrying different directions on the fingerprint. Despite being areas that give place to an important morphological variability, their study has only been approached from the quantitative point of view, in relation to the number with which they appear per finger, hand, or individual (intensity pattern), and their sexual and population differences; while the qualitative aspects have not been evaluated so far. The following paper aims to study and analyze the qualitative variability, both intra and interpopulation, of the frequency of occurrence of the different types of deltas or triradii, in four fingerprint samples from males of different population origin 100 individuals from China, 100 individuals from Colombia, 100 individuals from Nigeria and 100 individuals from Romania, which has meant the analysis of 4000 fingerprints. For this purpose, the classification of 24 types used by the Scientific Police and Criminalist Departments of the Guardia Civil of Spain has been employed. The results obtained showed the non-equiprobability of the frequency distribution of the different delta types in the four populations. In all cases, sunk open total deltas (Hat), sunk open total with point (Hat(p)) and tripod long (Tl) were the most frequent types, while the sunk closed total with point (Hct(p)) had the lowest frequency. Furthermore, for the first time, interpopulation differences in the frequency distribution of different types of deltas have become noticeable. The data provided in this paper are a pioneer in the field of dactyloscopy and can be used as a reference by the departments of criminalistics of the different countries for the estimation of the scientific value of the evidence in dactyloscopy.Neuron image segmentation has wide applications and important potential values for neuroscience research. Due to the complexity of the submicroscopic structure of neurons cells and the defects of the image quality such as anisotropy, boundary loss and blurriness in electron microscopy-based (EM) imaging, and one faces a challenge in efficient automated segmenting large-scale neuron image 3D datasets, which is an essential prerequisite front-end process for the reconstruction of neuron circuits. Here, a neuron image segmentation method by combining Chan-Vest (CV) model with Deep Boltzmann Machine (DBM) is proposed, and a generative model is used to model and generate the target shape, it take this as a prior information to add global target shape feature constraint to the energy function of CV model, and the shape priori information is fused to assist neuron image segmentation. We applied our method to two 3D-EM datasets from different types of nerve tissue and achieved the best performance consistently across two classical evaluation metrics of neuron segmentation accuracy, namely Variation of Information (VoI) and Adaptive Rand Index (ARI). Experimental results show that the fusion algorithm has high segmentation accuracy, strong robustness, and can characterize the sub-microstructure information of neuron images well.Di-n-butyl phthalate (DBP) is widely used as a plasticizer in personal care and medical products and is known to induce toxicity in the male reproductive organs in both mammals and birds. In this study, there was investigation of the effects of DBP on the epithelium of the rete testis, proximal, and distal efferent ductules and epididymal duct of adult Japanese quail (Coturnix japonica) following treatment with varying doses during the pre-pubertal and peri-pubertal periods. Pre-pubertal quail (n = 25) 4 weeks post-hatching were dosed orally with 10, 50, 200 and 400 mg DBP/kg/d, for 30 days and control birds were administered corn-oil only (n = 5 per group). Histo-metrically, there was lesser (P less then