Taxonomic insights into ethereum smart contracts by linking application categories to security vulnerabilities.

The expansion of smart contracts on the Ethereum blockchain has created a diverse ecosystem of decentralized applications. This growth, however, poses challenges in classifying and securing these contracts. Existing research often separately addresses either classification or vulnerability detection, without a comprehensive analysis of how contract types are related to security risks.

The Women4Health cohort: a unique cohort to study women-specific mechanisms of cardio-metabolic regulation.

Aims: Epidemiological research has shown relevant differences between sexes in clinical manifestations, severity, and progression of cardiovascular and metabolic disorders. To date, the mechanisms underlying these differences remain unknown. Given the rising incidence of such diseases, gender-specific research on established and emerging risk factors, such as dysfunction of glycaemic and/or lipid metabolism, of sex hormones and of gut microbiome, is of paramount importance.

PARSEG: a computationally efficient approach for statistical validation of botanical seeds' images.

Human recognition and automated image validation are the most widely used approaches to validate the output of binary segmentation methods but, as the number of pixels in an image easily exceeds several million, they become highly demanding from both practical and computational standpoint. We propose a method, called PARSEG, which stands for PArtitioning, Random Selection, Estimation, and Generalization; being the basic steps within this procedure. Suggested method enables us to perform statistical validation of binary images by selecting the minimum number of pixels from the original image to be used for validation without deteriorating the effectiveness of the validation procedure.

Correction to: Using sentiment analysis to evaluate the impact of the COVID-19 outbreak on Italy's country reputation and stock market performance.

[This corrects the article DOI: 10.1007/s10260-023-00690-5.].

Using sentiment analysis to evaluate the impact of the COVID-19 outbreak on Italy's country reputation and stock market performance.

During the recent Coronavirus disease 2019 (COVID-19) outbreak, the microblogging service Twitter has been widely used to share opinions and reactions to events. Italy was one of the first European countries to be severely affected by the outbreak and to establish lockdown and stay-at-home orders, potentially leading to country reputation damage. We resort to sentiment analysis to investigate changes in opinions about Italy reported on Twitter before and after the COVID-19 outbreak.

Near-Infrared Spectroscopy and Machine Learning for Accurate Dating of Historical Books.

Non-destructive, fast, and accurate methods of dating are highly desirable for many heritage objects. Here, we present and critically evaluate the use of near-infrared (NIR) spectroscopic data combined with three supervised machine learning methods to predict the publication year of paper books dated between 1851 and 2000. These methods provide different accuracies; however, we demonstrate that the underlying processes refer to common spectral features.

The Bradley-Terry Regression Trunk approach for Modeling Preference Data with Small Trees.

This paper introduces the Bradley-Terry regression trunk model, a novel probabilistic approach for the analysis of preference data expressed through paired comparison rankings. In some cases, it may be reasonable to assume that the preferences expressed by individuals depend on their characteristics. Within the framework of tree-based partitioning, we specify a tree-based model estimating the joint effects of subject-specific covariates over and above their main effects.

Cost-Utility Analysis of Pharmacogenetic Testing Based on CYP2C19 or CYP2D6 in Major Depressive Disorder: Assessing the Drivers of Different Cost-Effectiveness Levels from an Italian Societal Perspective.

Background And Objectives: Major depressive disorder (MDD) is a common and severe psychiatric disorder that has enormous economical and societal costs. As pharmacogenetics is one of the key tools of precision psychiatry, we analyze the cost-utility of test screening of CYP2C19 and CYP2D6 for patients suffering from major depressive disorder (MDD) and try to understand the main drivers that influence the cost-utility.

Methods: We developed two pharmacoeconomic nonhomogeneous Markov models to test the cost-utility, from an Italian societal perspective, of pharmacogenetic testing genetic to characterize the metabolizing profiles of cytochrome P450 (CYP) 2C19 and CYP2D6 in a hypothetical case study of patients suffering from major depressive disorder (MDD).

Application of Eye Tracking Technology in Medicine: A Bibliometric Analysis.

Eye tracking provides a quantitative measure of eye movements during different activities. We report the results from a bibliometric analysis to investigate trends in eye tracking research applied to the study of different medical conditions. We conducted a search on the Web of Science Core Collection (WoS) database and analyzed the dataset of 2456 retrieved articles using VOSviewer and the Bibliometrix R package.

Cost utility analysis of Remdesivir and Dexamethasone treatment for hospitalised COVID-19 patients - a hypothetical study.

Background: Sars-Cov-2 is a novel corona virus associated with significant morbidity and mortality. Remdesivir and Dexamethasone are two treatments that have shown to be effective against the Sars-Cov-2 associated disease. However, a cost-effectiveness analysis of the two treatments is still lacking.

Protocol for a pharmacogenetic study of antidepressants: characterization of drug-metabolizing profiles of cytochromes CYP2D6 and CYP2C19 in a Sardinian population of patients with major depressive disorder.

The effectiveness of antidepressants shows high interindividual variability ranging from full symptomatologic remission to treatment-resistant depression. Many factors can determine the variation in the clinical response, but a fundamental role is played by genetic variation within the genes encoding for the enzymes most involved in the metabolism of antidepressant drugs: the CYP2D6 and CYP2C19 isoforms of the cytochrome P450 system. This study is poised to clarify whether the different metabolizing phenotypes related to CYP2D6 and CYP2C19 could have an impact on the clinical efficacy of antidepressants and whether the frequency of these phenotypes of metabolization shows differences in the population of Sardinian patients compared to other Caucasian populations.

On the Use of Markov Models in Pharmacoeconomics: Pros and Cons and Implications for Policy Makers.

We present an overview of the main methodological features and the goals of pharmacoeconomic models that are classified in three major categories: regression models, decision trees, and Markov models. In particular, we focus on Markov models and define a semi-Markov model on the cost utility of a vaccine for Dengue fever discussing the key components of the model and the interpretation of its results. Next, we identify some criticalities of the decision rule arising from a possible incorrect interpretation of the model outcomes.