When bats go viral : negative framings in virological research imperil bat conservation

The recent upsurge in bat-borne virus research has attracted substantial news coverage worldwide. A systematic review of virological literature revealed that bats were described as a major concern for public health in half of all studies (51%), and that their key role in delivering ecosystem services was disregarded in almost all studies (96%). Although research on zoonoses is of the utmost importance, biased framings of bats can undermine decades of conservation efforts. We urge researchers and science communicators to consider the conservation impacts of how research findings are presented to the public carefully, and, whenever possible, to highlight the ecological significance of bats, their dire conservation situation and their importance for human well-being.Peer reviewe

The role of the dental surgeon in the early diagnosis of oral cancer: a concise systematic review

Introduction: Oral cancers (OC) represent more than 90% of cases. It is estimated that more than 400,000 new cases of oral cancer are diagnosed each year worldwide. OC is preventable as most of the different identified risk factors, such as tobacco use, alcohol consumption, and betel nut chewing, are behaviors that increase the likelihood of the disease. Surgical biopsy remains the gold standard, but adjunctive tools have been developed to aid diagnoses, such as vital toluidine blue staining and autofluorescence imaging. Objective: To emphasize and present the importance of the dental surgeon in the early diagnosis and prevention of oral cancer. Methods: The survey was conducted from July 2021 to August 2021 and developed based on Scopus, PubMed, Science Direct, Scielo, and Google Scholar, following the rules of Systematic Review-PRISMA. Study quality was based on the GRADE instrument and the risk of bias was analyzed according to the Cochrane instrument. Results: Early detection and treatment of OC were found to be important predictors for improving survival and reducing mortality. A thorough clinical inspection of the oral cavity can detect up to 99% of oral cancers. Other diagnostic types have been developed to help overcome the limits of standard oral clinical examination, highlighting toluidine blue staining, light-based detection techniques, and salivary biomarkers. Self-examination is an effective strategy to reduce the levels of mortality and morbidity caused by this pathology. A gain of 8.09% more in sensitivity and 11.36% more in specificity was observed with the fluorescence test. Conclusion: The findings clearly showed that early diagnosis of oral cancer is essential to increase the chances of cure and survival of patients, avoiding invasive surgical intervention. Currently, there are several diagnostic tools for screening and visual devices for the early detection of oral lesions through auxiliary methods, logically maintaining biopsy as the gold standard

O GOVERNO LULA E A INDICAÇÃO DE MINISTROS PARA O SUPREMO TRIBUNAL FEDERAL

This article aims to make some observations about the indications of President Lula’s government for the posts of Minister of the brazilian Federal Suprem Court. The analysis begins with the definition of political and legal fields. Therefore, it will be developed some considerations on the current legal mechanism for appointing the individuals that will belonging to that Court. Furthermore, we discuss some of the motivations and decision strategies used to this purpose.O presente artigo objetiva realizar algumas observações a respeito das indicações do Governo Lula às vagas de Ministro do Supremo Tribunal Federal brasileiro, a partir da abordagem preliminar dos conceitos de campo jurídico e político, acrescentando considerações sobre o atual mecanismo legal de indicação dos agentes que integram esse órgão de Estado, além discutir algumas das motivações e estratégias utilizadas

Quality of Hotels' Websites: Proposal for the Development of an Assessment Methodology

In this article we propose a research whose main objective will be to reach a methodology for assessment, comparing and improving the quality of hotels Websites. The need for this methodology is justified by the fact that, so far, we haven´t identified any methodology that widely integrates and focus the technical quality and the content quality of the Websites

Quality of Hotels' Websites: Proposal for the Development of an Assessment Methodology

In this article we propose a research whose main objective will be to reach a methodology for assessment, comparing and improving the quality of hotels Websites. The need for this methodology is justified by the fact that, so far, we haven´t identified any methodology that widely integrates and focus the technical quality and the content quality of the Websites

Maturity models in the hospital information systems management initial research

Os modelos de maturidade são instrumentos facilitadores da gestão das organizações, incluindo a gestão da sua função sistemas de informação, não sendo exceção as organizações hospitalares. Neste artigo apresenta-se uma investigação inicial que visa o desenvolvimento de um abrangente modelo de maturidade para a gestão dos sistemas de informação hospitalares. O desenvolvimento deste modelo justifica-se porque os modelos de maturidade atuais no domínio da gestão dos sistemas informação hospitalares ainda se encontram numa fase embrionária de desenvolvimento, sobretudo porque são pouco detalhados, não disponibilizam ferramentas para determinação da maturidade e não apresentam as características dos estágios de maturidade estruturadas por diferentes fatores de influência

Counterfactual explanation of Bayesian model uncertainty

Artificial intelligence systems are becoming ubiquitous in everyday life as well as in high-risk environments, such as autonomous driving, medical treatment, and medicine. The opaque nature of the deep neural network raises concerns about its adoption in high-risk environments. It is important for researchers to explain how these models reach their decisions. Most of the existing methods rely on softmax to explain model decisions. However, softmax is shown to be often misleading, particularly giving unjustified high confidence even for samples far from the training data. To overcome this shortcoming, we propose Bayesian model uncertainty for producing counterfactual explanations. In this paper, we compare the counterfactual explanation of models based on Bayesian uncertainty and softmax score. This work predictively produces minimal important features, which maximally change classifier output to explain the decision-making process of the Bayesian model. We used MNIST and Caltech Bird 2011 datasets for experiments. The results show that the Bayesian model outperforms the softmax model and produces more concise and human-understandable counterfactuals