Morphometrics and compositional classes. The stuy of anthropomorphic sculptures from Teotihuacan (México)

Morphometry is defined as the measurement of the external and perceptible characteristics, i.e., in a first approximation, of the shape or morphology of an object. It includes information related to the object’s appearance as well as to its physical and diachronic constitution (Verrecchia, 2003). Morphometric studies attempt to describe this form or shape through mathematical relationships that allow numerical data, and this can be achieved in different ways. In general, tow main types of analysis can be performed whether they are or they are not based on the study of the contourn. In several instances, the actual contourn is not supposed to be really informative. Instead, elementary Euclidean geometrical measurements or the definition of significant points (landmarks or semi-landmarks), referenced in coordinates systems, are used

New Self-Sufficient Shelter Solutions for Big Cities’ Collapsed Rental Markets

Nowadays, there is a wide variety of problems in the big cities related to the urban frame and to housing. Architects have to provide solutions that not only improve people’s well-being but also have to be efficient during the building’s entire life cycle. Within the European context, big cities like Paris, Berlin and Amsterdam have a huge demand for housing coming mainly from two different groups: people looking for temporary shelter and people looking for a more stable situation. In both cases, the need for new housing have resulted in inefficient urban developments, collapsed city centres and developed satellite cities where low and medium class people have tried to find somewhere to live, running away from infra-housing. In Paris, urban regulations set the minimum area for a rented apartment as 10m2. The research described in this paper analyzes the current situation in big cities from two points of view: apartment sizes and medium fees for temporary shelter. It defines the average architectural conditions of the “affordable” shelter and with this data; an experimental approach for a new completely self-sufficient housing module is provided, placed in a worthless space of existing buildings (roofs). This new module is defined by its sustainability and self-sufficiency and it gives the rental market an opportunity to increase the offer of shelter to rent in the big cities. At the end of the research, the development of an analysis of life cost cycle of the new module shows it as an alternative to the existing examples of infra housing with very short periods for recovering the investment

Visual Impact of Large and Giant Congenital Naevi: Comparison of Surgical Scars with Naevi Before Surgery

Surgical attempts to remove large/giant congenital melanocytic naevi (LGCMN) are supported mainly by the theoretical improvement in patients’ self-image; however such surgery can result in unaesthetic scarring. We hypothesize that difference in appearance itself has an impact, and hence surgery cannot negate this impact. The aim of this cross-sectional study was to explore how LGCMN and scarring are perceived by non-affected people. We surveyed the visual impact on 1,015 health and non-health professionals working in a university hospital. Participants were assigned to 1 of 3 surveys, which, based on photographs of children: (i) assessed the visual impact of LGCMN; (ii) the visual impact of scarring; (iii) compared the impact of LGCMN and scarring. Feelings and perceptions evoked by images of children, either with LGCMN or with scarring, were remarkably similar. However, when the images of the same child (with LGCMN or scarring) were shown together, respondents showed significantly increased preference for scarring

The effect of diet and sociopolitical change on physiological stress and behavior in late Roman‐Early Byzantine (300–700 AD) and Islamic (902–1,235 AD) populations from Ibiza, Spain

Objectives This study evaluated chronological changes in physiological stress and levels of habitual loading of Ibizan populations from the Late Roman-Early Byzantine to the Islamic period (300-1235 AD) using measures of body size and bone cross-sectional properties. It also explored the effect of diet, modeled using stable isotopes, on physiological stress levels and behavior. Materials and Methods American Journal of Physical Anthropology, Volume 172, Issue 2, June 2020 pp. 189-213 DOI:10.1002/ajpa.24062 Published by Wiley. This is the Author Accepted Manuscript issued with: Creative Commons Attribution Non-Commercial License (CC:BY:NC 4.0). The final published version (version of record) is available online at DOI:10.1002/ajpa.24062. Please refer to any applicable publisher terms of use. 2 The sample comprised individuals from three archaeological populations: Urban Late Roman- Early Byzantine (LREB) (300-700 AD), Medieval Urban Islamic (902-1235 AD), and Rural Islamic. Bone lengths, femoral head dimensions, and diaphyseal products and circumferences were compared to assess differences in body size and habitual loading in 222 adult individuals. Ordinary least squares regression evaluated the correlations between these measures and carbon (δ13C) and nitrogen (δ15N) stable isotope ratios in 115 individuals for whom both isotope values and osteological measures are available. Results The Rural Islamic group had shorter stature and reduced lower limb cross-sectional properties compared to the two urban groups. In both LREB and Islamic groups, body mass and femur length was positively correlated with δ13C values, and δ15N shows a positive correlation with left humerus shape in the LREB Urban sample. Conclusions The low stature and cross-sectional properties of the Rural Islamic group are most likely an indicator of greater physiological stress, potentially due to poorer diet. Positive correlations between measures of body size and δ13C values further suggest that greater access to C4 resources improved diet quality. Alternatively, this relationship could indicate greater body size among migrants from areas where individuals consumed more C4 resources

Computational approaches to explainable artificial intelligence: Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.MCIU - Nvidia(UMA18-FEDERJA-084

Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications

COVID-19 in breast cancer patients: a subanalysis of the OnCovid registry

BACKGROUND: Cancer patients are at higher risk of COVID-19 complications and mortality than the rest of the population. Breast cancer patients seem to have better prognosis when infected by SARS-CoV-2 than other cancer patients. METHODS: We report a subanalysis of the OnCovid study providing more detailed information in the breast cancer population. RESULTS: We included 495 breast cancer patients with a SARS-CoV-2 infection. Mean age was 62.6 years; 31.5% presented more than one comorbidity. The most frequent breast cancer subtype was luminal-like (n = 245, 49.5%) and 177 (35.8%) had metastatic disease. A total of 332 (67.1%) patients were receiving active treatment, with radical intent in 232 (47.6%) of them. Hospitalization rate was 58.2% and all-cause mortality rate was 20.3%. One hundred twenty-nine (26.1%) patients developed one COVID-19 complication, being acute respiratory failure the most common (n = 74, 15.0%). In the multivariable analysis, age older than 70 years, presence of COVID-19 complications, and metastatic disease were factors correlated with worse outcomes, while ongoing anticancer therapy at time of COVID-19 diagnosis appeared to be a protective factor. No particular oncological treatment was related to higher risk of complications. In the context of SARS-CoV-2 infection, 73 (18.3%) patients had some kind of modification on their oncologic treatment. At the first oncological reassessment (median time: 46.9 days ± 36.7), 255 (51.6%) patients reported to be fully recovered from the infection. There were 39 patients (7.9%) with long-term SARS-CoV-2-related complications. CONCLUSION: In the context of COVID-19, our data confirm that breast cancer patients appear to have lower complications and mortality rate than expected in other cancer populations. Most breast cancer patients can be safely treated for their neoplasm during SARS-CoV-2 pandemic. Oncological treatment has no impact on the risk of SARS-CoV-2 complications, and, especially in the curative setting, the treatment should be modified as little as possible