Automatic pre-bended customized prosthesis for pectus excavatum minimal invasive surgery correction

Pectus excavatum is the most common deformity of the thorax. A minimally invasive surgical correction is commonly carried out to remodel the anterior chest wall, by employing an intrathoracic convex prosthesis in substernal position. The process of prosthesis modeling and bending still remains an area of improvement. The authors developed a new system, i3DExcavatum, which can automatically model and bend the bar preoperatively based on a thoracic CT-scan. This paper presents a comparison between automatic and manual bending. The i3DExcavatum was used to personalize prosthesis for 41 patients who underwent pectus excavatum surgical correction between 2007 and 2012. Regarding the anatomic variations, the soft tissue thicknesses external to the ribs show that symmetric or asymmetric patients have always asymmetric variations by comparing both patients’ sides. It highlighted that the prosthesis bar should be modeled according to each patient ribs position and dimension. The average differences between the skin and costal line curvature lengths were 84±4 mm and 96±11mm, for male and female patients, respectively. On the other hand, the i3DExcavatum ensured a smooth curvature of the surgical prosthesis and was capable to predict and simulate a virtual shape and size of the bar for asymmetric or symmetric patients. In conclusion, the i3DExcavatum allows preoperative personalization according to the thoracic morphology of each patient. It reduces surgery time and minimizes the margin error induced by the manual bended bar shape that only uses a template that copies the chest wall curvature

Validation Diagnostics for SBI algorithms based on Normalizing Flows

Building on the recent trend of new deep generative models known as Normalizing Flows (NF), simulation-based inference (SBI) algorithms can now efficiently accommodate arbitrary complex and high-dimensional data distributions. The development of appropriate validation methods however has fallen behind. Indeed, most of the existing metrics either require access to the true posterior distribution, or fail to provide theoretical guarantees on the consistency of the inferred approximation beyond the one-dimensional setting. This work proposes easy to interpret validation diagnostics for multi-dimensional conditional (posterior) density estimators based on NF. It also offers theoretical guarantees based on results of local consistency. The proposed workflow can be used to check, analyse and guarantee consistent behavior of the estimator. The method is illustrated with a challenging example that involves tightly coupled parameters in the context of computational neuroscience. This work should help the design of better specified models or drive the development of novel SBI-algorithms, hence allowing to build up trust on their ability to address important questions in experimental science.Comment: 7 pages, 2 figures, 1 appendix, published at "Machine Learning and the Physical Sciences" workshop (NeurIPS 2022): https://ml4physicalsciences.github.io/2022

L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inference

Many recent works in simulation-based inference (SBI) rely on deep generative models to approximate complex, high-dimensional posterior distributions. However, evaluating whether or not these approximations can be trusted remains a challenge. Most approaches evaluate the posterior estimator only in expectation over the observation space. This limits their interpretability and is not sufficient to identify for which observations the approximation can be trusted or should be improved. Building upon the well-known classifier two-sample test (C2ST), we introduce L-C2ST, a new method that allows for a local evaluation of the posterior estimator at any given observation. It offers theoretically grounded and easy to interpret - e.g. graphical - diagnostics, and unlike C2ST, does not require access to samples from the true posterior. In the case of normalizing flow-based posterior estimators, L-C2ST can be specialized to offer better statistical power, while being computationally more efficient. On standard SBI benchmarks, L-C2ST provides comparable results to C2ST and outperforms alternative local approaches such as coverage tests based on highest predictive density (HPD). We further highlight the importance of local evaluation and the benefit of interpretability of L-C2ST on a challenging application from computational neuroscience.Comment: 20 pages, 4 figures, 7 appendices, in proceeding

Validation of percutaneous puncture trajectory during renal access using 4D ultrasound reconstruction

"Progress in Biomedical Optics and Imaging, vol. 16, nr. 43"Background: An accurate percutaneous puncture is essential for disintegration and removal of renal stones. Although this procedure has proven to be safe, some organs surrounding the renal target might be accidentally perforated. This work describes a new intraoperative framework where tracked surgical tools are superimposed within 4D ultrasound imaging for security assessment of the percutaneous puncture trajectory (PPT). Methods: A PPT is first generated from the skin puncture site towards an anatomical target, using the information retrieved by electromagnetic motion tracking sensors coupled to surgical tools. Then, 2D ultrasound images acquired with a tracked probe are used to reconstruct a 4D ultrasound around the PPT under GPU processing. Volume hole-filling was performed in different processing time intervals by a tri-linear interpolation method. At spaced time intervals, the volume of the anatomical structures was segmented to ascertain if any vital structure is in between PPT and might compromise the surgical success. To enhance the volume visualization of the reconstructed structures, different render transfer functions were used. Results: Real-time US volume reconstruction and rendering with more than 25 frames/s was only possible when rendering only three orthogonal slice views. When using the whole reconstructed volume one achieved 8-15 frames/s. 3 frames/s were reached when one introduce the segmentation and detection if some structure intersected the PPT. Conclusions: The proposed framework creates a virtual and intuitive platform that can be used to identify and validate a PPT to safely and accurately perform the puncture in percutaneous nephrolithotomy.The authors acknowledge to Foundation for Science and Technology (FCT) - Portugal for the fellowships with references: SFRH/BD/74276/2010.info:eu-repo/semantics/publishedVersio

Remoção de arsénio em águas para consumo humano

A presença de arsénio nas origens de água para consumo humano é um problema que tem suscitado uma preocupação crescente em termos de saúde pública. A poluição por arsénio das águas naturais, designada por hidroarsenismo, converteu-se num problema sanitário internacional afectando, actualmente, mais de 40 milhões de pessoas e manifesta-se pelo aparecimento de lesões cutâneas graves e pela ocorrência de perturbações neurológicas. As conclusões de vários estudos epidemiológicos vieram confirmar a potencial acção cancerígena de algumas espécies de arsénio, quando presentes em concentrações elevadas, levando a OMS, em 1993, a recomendar um valor guia muito restritivo (0,01 mg/L) como norma de qualidade das águas destinadas a consumo humano, Esta recomendação foi adoptada na legislação portuguesa em vigor (Decreto-Lei n.º 306/2007, de 27 de Agosto), tendo a sua aplicação originado alguns constrangimentos operacionais e de sustentabilidade às entidades gestoras de sistemas de abastecimento público de água com origens de água (geralmente subterrâneas) em que os valores da concentração de arsénio excedem, ainda que sazonalmente, este limite paramétrico mais restritivo. Efectivamente, em algumas regiões afectadas pela presença de arsénio nas águas naturais a substituição dessas fontes de abastecimento, em certas épocas do ano, por outra mais segura pode ser impossível ou demasiado dispendiosa, mesmo numa perspectiva de complementaridade, visando uma diluição dos volumes de água provenientes das captações afectadas. Assim sendo, a remoção do arsénio na água bruta coloca-se como a única opção viável para se obter uma água segura para consumo humano, tornando pertinente o incremento, a nível europeu, de investigação aplicada visando o desenvolvimento de tecnologias inovadoras de remoção de arsénio, mais eficientes e sustentáveis, nomeadamente para sistemas de abastecimento a pequenos e médios aglomerados populacionais Este trabalho inicia-se com uma referência às causas do aparecimento de arsénio em diversas massas de água e à presença de arsénio em alguns dos mananciais hídricos da Península Ibérica, tendo-se efectuado uma pesquisa sobre os principais impactos do hidroarsenismo na saúde humana. Procedeu-se também a uma revisão dos principais processos de tratamento para remoção de arsénio, não só os convencionais, como também alternativos (oxidação avançada e fotocatálise heterogénea) e a uma análise das respectivas eficiências, de modo a estabelecer critérios de selecção dessas tecnologias em função das características da água bruta a tratar e/ou dos esquemas de tratamento, no caso de ETA já existentes. Por fim, apresenta-se uma metodologia inovadora de remoção de arsénio, baseada numa conjugação dos processos convencionais com técnicas de oxidação solar, visando a sustentabilidade dos sistemas de tratamento, através duma redução significativa dos custos de exploração e de um aproveitamento racional de energias renováveis

Automated image analysis of lung branching morphogenesis from microscopic images of fetal rat explants

Article ID 820214Background. Regulating mechanisms of branching morphogenesis of fetal lung rat explants have been an essential tool for molecular research. This work presents a new methodology to accurately quantify the epithelial, outer contour, and peripheral airway buds of lung explants during cellular development from microscopic images. Methods. The outer contour was defined using an adaptive and multiscale threshold algorithm whose level was automatically calculated based on an entropy maximization criterion. The inner lung epithelium was defined by a clustering procedure that groups small image regions according to the minimum description length principle and local statistical properties. Finally, the number of peripheral buds was counted as the skeleton branched ends from a skeletonized image of the lung inner epithelia. Results. The time for lung branching morphometric analysis was reduced in 98% in contrast to the manual method. Best results were obtained in the first two days of cellular development, with lesser standard deviations. Nonsignificant differences were found between the automatic and manual results in all culture days. Conclusions. The proposed method introduces a series of advantages related to its intuitive use and accuracy, making the technique suitable to images with different lighting characteristics and allowing a reliable comparison between different researchers.The authors acknowledge Foundation for Science and Technology (FCT), Portugal, for the fellowship with the references: SFRH/BD/74276/2010 and SFRH/BPD/46851/2008

Real-time transmission of scalable video over peer-to-peer networks

Dissertação de mest., Engenharia Elétrica e Eletrónica (Tecnologias da Informação e Telecomunicações), Instituto Superior de Engenharia, Univ. do Algarve, 2012Nos últimos anos temos assistido ao expressivo crescimento na procura de conteúdos de vídeo na Internet. Esse crescimento tem surgido associado ao aumento da diversidade dos terminais com capacidades para receber conteúdos de vídeo e ao aumento na procura de conteúdos em alta definição, colocando novos desafios de heterogeneidade e escalabilidade às redes que servem de suporte à distribuição desses conteúdos. O problema da escalabilidade tem sido resolvido tradicionalmente nas redes IPTV (Internet Protocol Television) recorrendo ao IP Multicast, suportado em redes e equipamentos administrados por operadores privados e que por isso têm mecanimos de controlo que reduzem os riscos associados ao mesmo. No entanto, na Internet, tais riscos levaram a que o IP Multicast não fosse adotado, o que por sua vez condiciona a distribuição em larga escala de vídeo. Neste sentido, os fornecedores de conteúdos vêm-se por isso obrigados a recorrer a soluções ditas de nível de aplicação ou também denominadas de soluções sobrepostas. Neste âmbito as soluções Peer-to-Peer são hoje extensivamente utilizadas como suporte à troca de ficheiros, o que poderia fazer delas uma possível solução à distribuição ponto-multiponto de vídeo. Em relação ao problema da heterogeneidade de terminais, a introdução recente de normas de compressão escalável de vídeo permitem ir ao encontro da variabilidade de equipamentos com diferentes definições e capacidades de processamento. Neste âmbito, a investigação efectuada nesta dissertação pretende combinar as soluções Peer-to-Peer mais importantes, com o vídeo escalável, no sentido de obter um sistema que, suportado na Internet, permita a distribuição ponto-multiponto de conteúdos com requisitos de tempo real para um número elevado de terminais com características heterogéneas

A decision-support system to Analyse Customer Satisfaction Applied to a Tourism Transport Service

Due to the perishable nature of tourist products, which impacts supply and demand, the possibility of analysing the relationship between customers’ satisfaction and service quality can contribute to increased revenues. Machine learning techniques allow the analysis of how these services can be improved or developed and how to reach new markets, and look for the emergence of ideas to innovate and improve interaction with the customer. This paper presents a decision-support system for analysing consumer satisfaction, based on consumer feedback from the customer’s experience when transported by a transfer company, in the present case working in the Algarve region, Portugal. The results show how tourists perceive the service and which factors influence their level of satisfaction and sentiment. One of the results revealed that the first impression associated with good news is what creates the most value in the experience, i.e., “first impressions matter”..info:eu-repo/semantics/publishedVersio

Diet and Asthma: A Narrative Review

Asthma is a chronic respiratory disease that impacts millions of people worldwide. Recent studies suggest that diet may play a role in asthma pathophysiology. Several dietary factors have been recognized as potential contributors to the development and severity of asthma for its inflammatory and oxidative effects. Some food groups such as fruits and vegetables, whole grains, and healthy fats appear to exert positive effects on asthma disease. On the other hand, a high consumption of dietary salt, saturated fats, and trans-fat seems to have the opposite effect. Nonetheless, as foods are not consumed separately, more research is warranted on the topic of dietary patterns. The mechanisms underlying these associations are not yet fully understood, but it is thought that diet can modulate both the immune system and inflammation, two key factors in asthma development and exacerbation. The purpose of this review is to examine how common food groups and dietary patterns are associated with asthma. In general, this research demonstrated that fruits and vegetables, fiber, healthy fats, and dietary patterns considered of high quality appear to be beneficial to asthma disease. Nonetheless, additional research is needed to better understand the interrelation between diet and asthma, and to determine the most effective dietary interventions for asthma prevention and management. Currently, there is no established dietary pattern for asthma management and prevention, and the nuances of certain food groups in relation to this disease require further investigation

A modified closed-form maximum likelihood estimator

The maximum likelihood estimator plays a fundamental role in statistics. However, for many models, the estimators do not have closed-form expressions. This limitation can be significant in situations where estimates and predictions need to be computed in real-time, such as in applications based on embedded technology, in which numerical methods can not be implemented. This paper provides a modification in the maximum likelihood estimator that allows us to obtain the estimators in closed-form expressions under some conditions. Under mild conditions, the estimator is invariant under one-to-one transformations, consistent, and has an asymptotic normal distribution. The proposed modified version of the maximum likelihood estimator is illustrated on the Gamma, Nakagami, and Beta distributions and compared with the standard maximum likelihood estimator