Dental pathology of the wild Iberian wolf (Canis lupus signatus): The study of a 20th century Portuguese museum collection

For some wild canids, such as the Iberian wolf, there is a lack of in-depth knowledge about dental pathology. We aimed to evaluate it, in a standardized manner, in specimens from a Portuguese museum collection. Sixty-five deceased specimens of wild Iberian wolves, 61 complete skulls and 4 mandibles, collected in Portugal between 1977 and 1995, were analyzed. Sample comprised 18 females, 24 males and 23 individuals of undetermined sex. Teeth were evaluated by visual observation and dental radiography for tooth wear, periodontitis, fractures and other dental lesions. We have found several causes for teeth absence: artefactual, secondary to periodontitis and agenesia. About 30% of the teeth showed signs of wear. Only a small (<13%) fraction of maxillary and mandibular teeth did not show periodontitis. The tooth 308 showed periodontitis in all males (p = 0.017) and the tooth 104 was significantly affected by this condition in females (p = 0.020). A significant relationship was found between females and tooth wear in three teeth. Periodontitis showed a significant association with tooth wear (p < 0.001) and fractures (p = 0.027). Tooth fractures were more frequent in the maxilla than in the mandible. Seven periapical lesions, seven root fusions and three specimens with malocclusion were identified in the collection. Results are discussed integrating information from diet, habitat, genetic and spatial behavior. Dental radiography is here proposed as an approach for the age estimation in archaeological canids. This research contributes to the knowledge of the dental disease in the largest wolf population in Western Europe, a target subspecies of multiple conservation measures.info:eu-repo/semantics/publishedVersio

Segmentation of Biological Volume Datasets Using a Level-Set Framework

This paper presents a framework for extracting surface models from a broad variety of volume datasets. These datasets are produced from standard 3D imaging devices, and are all noisy samplings of complex biological structures with boundaries that have low and often varying contrasts. The level set segmentation method, which is well documented in the literature, creates a new volume from the input data by solving an initial-value partial differential equation (PDE) with user-defined feature-extracting terms. However, level set deformations alone are not sufficient, they must be combined with powerful initialization techniques in order to produce successful segmentations. Our level set segmentation approach consists of defining a set of suitable pre-processing techniques for initialization and selecting/tuning different feature-extracting terms in the level set algorithm. This collection of techniques forms a toolkit that can be applied, under the guidance of a user, to segment a variety of volumetric data.

A survey on smart automated computer-aided process planning (ACAPP) techniques

© 2018, The Author(s). The concept of smart manufacturing has become an important issue in the manufacturing industry since the start of the twenty-first century in terms of time and production cost. In addition to high production quality, a quick response could determine the success or failure of many companies and factories. One the most effective concepts for achieving a smart manufacturing industry is the use of computer-aided process planning (CAPP) techniques. Computer-aided process planning refers to key technology that connects the computer-aided design (CAD) and the computer-aided manufacturing (CAM) processes. Researchers have used many approaches as an interface between CAD and CAPP systems. In this field of research, a lot of effort has been spent to take CAPP systems to the next level in the form of automatic computer-aided process planning (ACAPP). This is to provide complete information about the product, in a way that is automated, fast, and accurate. Moreover, automatic feature recognition (AFR) techniques are considered one of the most important tasks to create an ACAPP system. This article presents a comprehensive survey about two main aspects: the degree of automation in each required input and expected output of computer-aided process planning systems as well as the benefits and the limitations of the different automatic feature recognition techniques. The aim is to demonstrate the missing aspects in smart ACAPP generation, the limitations of current systems in recognising new features, and justifying the process of selection.The authors of the paper would like to sincerely thank the Republic of Iraq Ministry of Higher Education & Scientific Research and the University of Technology, Baghdad for funding the project