A photographic system for the three-dimensional study of facial morphology.

Abstract Objectives: To test whether digital photographs supported by three-dimensional (3D) software are suitable for measuring the facial soft tissues of healthy subjects as compared with data obtained by a certified 3D computerized electromagnetic digitizer. Materials and Methods: Three-dimensional soft tissue facial landmarks were obtained from the faces of 15 healthy young adults, using a 3D computerized electromagnetic digitizer and a new low-cost photogrammetry system. Twelve linear and 18 angular measurements were computed. Errors between methods and repeatability of the new method were calculated. Results: Systematic errors between methods were found for only two distances and three angles (paired t-test, P < .05). The mean absolute differences between methods were always lower than 3 mm and 3 degrees. Repeated digitization of photographs showed that the method was repeatable (no systematic differences; random errors lower than 1.6 mm and 3 degrees). Repeated sets of photographs showed random errors of up to 5.3 mm and 5.6 degrees, without systematic biases. Conclusion: The 3D photogrammetry system can provide reliable facial measurements. The method is relatively fast and requires only inexpensive equipment. It is simple to use for private practice, research, or other practice

Questions of science: chatting with ChatGPT about complex systems

We present an overview of the complex systems field using ChatGPT as a representation of the community's understanding. ChatGPT has learned language patterns and styles from a large dataset of internet texts, allowing it to provide answers that reflect common opinions, ideas, and language patterns found in the community. Our exploration covers both teaching and learning, and research topics. We recognize the value of ChatGPT as a source for the community's ideas.Comment: This is a work in progres

Qualidade de habitat e métricas de macroinvertebrados bentônicos associadas a diferentes tipos de uso do solo

Os ecossistemas aquáticos estão sob fortes modificações antrópicas. Assim, comunidades biológicas dependentes desses ambientes também são alteradas. O objetivo deste estudo foi investigar os efeitos do desenvolvimento urbano em um ecossistema impactado. Foram selecionadas 15 seções de amostragem ao longo do Ribeirão Vermelho e em cada uma foi amostrada a comunidade de macroinvertebrados bentônicos e avaliada a diversidade de habitat e qualidade da água. Observou-se um gradiente de impacto ao longo do ribeirão, com alguns pontos de referência classificados como naturais e outros como impactados. Houve diferença significativa em todos os indicadores biológicos utilizados. O número total de táxons, riqueza de Diptera, Ephemeroptera, Plecoptera e Trichoptera, e os índices de diversidade, de qualidade da água e porcentagem de herbívoros, trituradores e predadores foram significativamente maiores nos pontos classificados como naturais e impactados. As abundâncias relativas de coletores, filtradores, quironomídeos e parasitas foram significativamente menores em sítios classificados como naturais em relação aos impactados. ­Observou-se que as métricas das comunidades bentônicas de macroinvertebrados e o Protocolo de Avaliação Rápida da Diversidade de Habitat foram influenciados pela degradação ambiental, sendo estas ferramentas úteis para ações de planejamento e desenvolvimento para a preservação de bacias hidrográficas e a priorização de sistemas de transmissão de alto valor para proteção e reabilitação de ecossistemas aquáticos.Aquatic ecosystems are under severe anthropogenic modifications. Thus, the dependent biological communities in these environments are also changed. The objective of this study was to investigate the effects of urban development in a highly impacted ecosystem. We selected 15 sampling points along the stream Ribeirão Vermelho, in which were sampled benthic macroinvertebrates and assessed the water and habitat diversity. It was found an impact gradient, with some the reference points classified as natural and others as impacted. There was a significant difference in all biological indicators used. The total number of taxa, the wealth of Diptera, the taxa Ephemeroptera, Plecoptera and Trichoptera, and the diversity indices, the Water Quality Indices, and the percentage of herbivores crushers and predators were significantly higher in points classified as natural and changed. The relative abundances of collectors, filter feeding, chironomids and parasites were significantly lower in sites classified as natural in relation to impacted ones. The metrics of the macroinvertebrate community benthic and Habitat Diversity Protocol were influenced by environmental degradation, being a useful tool for planning and development actions for the preservation of watersheds and the prioritization of high-value transmission systems for protection and rehabilitation of aquatic ecosystem

Emergence of Clusters in Growing Networks with Aging

We study numerically a model of nonequilibrium networks where nodes and links are added at each time step with aging of nodes and connectivity- and age-dependent attachment of links. By varying the effects of age in the attachment probability we find, with numerical simulations and scaling arguments, that a giant cluster emerges at a first-order critical point and that the problem is in the universality class of one dimensional percolation. This transition is followed by a change in the giant cluster's topology from tree-like to quasi-linear, as inferred from measurements of the average shortest-path length, which scales logarithmically with system size in one phase and linearly in the other.Comment: 8 pages, 6 figures, accepted for publication in JSTA

A Robust Learning Methodology for Uncertainty-aware Scientific Machine Learning models

Robust learning is an important issue in Scientific Machine Learning (SciML). There are several works in the literature addressing this topic. However, there is an increasing demand for methods that can simultaneously consider all the different uncertainty components involved in SciML model identification. Hence, this work proposes a comprehensive methodology for uncertainty evaluation of the SciML that also considers several possible sources of uncertainties involved in the identification process. The uncertainties considered in the proposed method are the absence of theory and causal models, the sensitiveness to data corruption or imperfection, and the computational effort. Therefore, it was possible to provide an overall strategy for the uncertainty-aware models in the SciML field. The methodology is validated through a case study, developing a Soft Sensor for a polymerization reactor. The results demonstrated that the identified Soft Sensor are robust for uncertainties, corroborating with the consistency of the proposed approach.Comment: 23 page