Introduction: ‘The Intimacy of Strangers’

Of contagion and viruses La souillure elle-même est à peine une représentation et celle-ci est noyée dans une peur spécifique qui bouche la réflexion; avec la souillure nous entrons au règne de la Terreur. Paul Ricœur Reflection on dirt involves reflection on the relation of order to disorder, being to non-being, form to formlessness, life to death. Mary Douglas The role of Western medical science in the definition of diversity has been crucial and can be extended to other sciences such as bi..

Gerarchie e reti di città: tendenze e politiche

Collana dell’Associazione italiana di scienze regionali (AISRe)- PARTE I - Il quadro interpretativo #27- PARTEII - Il rapporto analisi-politiche alla scala del reticolo inter-urbano #123- PARTE III - Il rapporto analisi politiche alla scala metropolitana #25

Estudo comparativo sobre a evolução semântica dos termos mariage e casamento nas legislações francesa e brasileira do século XVI ao XIX

Neste trabalho, objetivamos verificar, à luz de uma perspectiva diacrônico-comparada, a evolução semântica dos termos mariage e casamento no domínio do Direito a partir do momento em que ocorreu a primeira regulamentação sobre os casamentos oficiais na França (1563) e no Brasil (1827) até o aparecimento inédito do conceito de casamento civil e laico nas legislações francesa e brasileira em 1791 e 1890, respectivamente. Além disso, pretendemos relacionar essa evolução aos aspectos socioculturais e históricos de cada país. Para tanto, fundamentamo-nos nos pressupostos teóricos e metodológicos da Terminologia (Cabré 1999; Barros 2004), mais especificamente nos da Terminologia Diacrônica (Dury 1999; Bortolato 2013), e em estudos das áreas do Direito da França e do Brasil, e de História da França e do Brasil. Assim, esperamos contribuir com o desenvolvimento dos estudos diacrônicos em Terminologia, que são raros no Brasil, bem como ampliar o conhecimento linguístico e cultural sobre a matéria.In the light of a diachronic-comparative perspective, we aim to verify the semantic and conceptual evolution of the terms mariage and casamento in the field of Law regarding the period from the first regulation on official marriages in France (1563) and Brazil (1824) until the unprecedented appearance of civil and secular marriages in the French and Brazilian legislations, respectively in 1791 and 1890. In addition, we intend to relate this evolution to the sociocultural and historical aspects of these countries. To do so, we based this study on the theoretical and methodological assumptions of Terminology, more specifically on Diachronic Terminology, and on research in the areas of French and Brazilian Law and History of France and Brazil

Outcome Prediction for SARS-CoV-2 Patients Using Machine Learning Modeling of Clinical, Radiological, and Radiomic Features Derived from Chest CT Images

Featured Application The present study demonstrates that semi-automatic segmentation enables the identification of regions of interest affected by SARS-CoV-2 infection for the extraction of prognostic features from chest CT scans without suffering from the inter-operator variability typical of segmentation, hence offering a valuable and informative second opinion. Machine Learning methods allow identification of the prognostic features potentially reusable for the early detection and management of other similar diseases. (1) Background: Chest Computed Tomography (CT) has been proposed as a non-invasive method for confirming the diagnosis of SARS-CoV-2 patients using radiomic features (RFs) and baseline clinical data. The performance of Machine Learning (ML) methods using RFs derived from semi-automatically segmented lungs in chest CT images was investigated regarding the ability to predict the mortality of SARS-CoV-2 patients. (2) Methods: A total of 179 RFs extracted from 436 chest CT images of SARS-CoV-2 patients, and 8 clinical and 6 radiological variables, were used to train and evaluate three ML methods (Least Absolute Shrinkage and Selection Operator [LASSO] regularized regression, Random Forest Classifier [RFC], and the Fully connected Neural Network [FcNN]) for their ability to predict mortality using the Area Under the Curve (AUC) of Receiver Operator characteristic (ROC) Curves. These three groups of variables were used separately and together as input for constructing and comparing the final performance of ML models. (3) Results: All the ML models using only RFs achieved an informative level regarding predictive ability, outperforming radiological assessment, without however reaching the performance obtained with ML based on clinical variables. The LASSO regularized regression and the FcNN performed equally, both being superior to the RFC. (4) Conclusions: Radiomic features based on semi-automatically segmented CT images and ML approaches can aid in identifying patients with a high risk of mortality, allowing a fast, objective, and generalizable method for improving prognostic assessment by providing a second expert opinion that outperforms human evaluation

Automated Prediction of the Response to Neoadjuvant Chemoradiotherapy in Patients Affected by Rectal Cancer

Simple Summary Colorectal cancer is the second most malignant tumor per number of deaths after lung cancer and the third per number of new cases after breast and lung cancer. The correct and rapid identification (i.e., segmentation of the cancer regions) is a fundamental task for correct patient diagnosis. In this study, we propose a novel automated pipeline for the segmentation of MRI scans of patients with LARC in order to predict the response to nCRT using radiomic features. This study involved the retrospective analysis of T-2-weighted MRI scans of 43 patients affected by LARC. The segmentation of tumor areas was on par or better than the state-of-the-art results, but required smaller sample sizes. The analysis of radiomic features allowed us to predict the TRG score, which agreed with the state-of-the-art results. Background: Rectal cancer is a malignant neoplasm of the large intestine resulting from the uncontrolled proliferation of the rectal tract. Predicting the pathologic response of neoadjuvant chemoradiotherapy at an MRI primary staging scan in patients affected by locally advanced rectal cancer (LARC) could lead to significant improvement in the survival and quality of life of the patients. In this study, the possibility of automatizing this estimation from a primary staging MRI scan, using a fully automated artificial intelligence-based model for the segmentation and consequent characterization of the tumor areas using radiomic features was evaluated. The TRG score was used to evaluate the clinical outcome. Methods: Forty-three patients under treatment in the IRCCS Sant'Orsola-Malpighi Polyclinic were retrospectively selected for the study; a U-Net model was trained for the automated segmentation of the tumor areas; the radiomic features were collected and used to predict the tumor regression grade (TRG) score. Results: The segmentation of tumor areas outperformed the state-of-the-art results in terms of the Dice score coefficient or was comparable to them but with the advantage of considering mucinous cases. Analysis of the radiomic features extracted from the lesion areas allowed us to predict the TRG score, with the results agreeing with the state-of-the-art results. Conclusions: The results obtained regarding TRG prediction using the proposed fully automated pipeline prove its possible usage as a viable decision support system for radiologists in clinical practice