Sustainable visions: unsupervised machine learning insights on global development goals.

The 2030 Agenda for Sustainable Development of the United Nations outlines 17 goals for countries of the world to address global challenges in their development. However, the progress of countries towards these goal has been slower than expected and, consequently, there is a need to investigate the reasons behind this fact. In this study, we have used a novel data-driven methodology to analyze time-series data for over 20 years (2000-2022) from 107 countries using unsupervised machine learning (ML) techniques.

Corrigendum: Neutrophil to lymphocyte ratio and principal component analysis offer prognostic advantage for dogs with mammary tumors.

[This corrects the article DOI: 10.3389/fvets.2023.

Modelling the creation of friends and foes groups in small real social networks.

Although friendship networks have been extensively studied, few models and studies are available to understand the reciprocity of friendship and foes. Here a model is presented to explain the directed friendship and foes network formation observed in experiments of Mexican and Hungarian schools. Within the presented model, each agent has a private opinion and a public one that shares to the group.

Socio-economic pandemic modelling: case of Spain.

A global disaster, such as the recent Covid-19 pandemic, affects every aspect of our lives and there is a need to investigate these highly complex phenomena if one aims to diminish their impact in the health of the population, as well as their socio-economic stability. In this paper we present an attempt to understand the role of the governmental authorities and the response of the rest of the population facing such emergencies. We present a mathematical model that takes into account the epidemiological features of the pandemic and also the actions of people responding to it, focusing only on three aspects of the system, namely, the fear of catching this serious disease, the impact on the economic activities and the compliance of the people to the mitigating measures adopted by the authorities.

Neutrophil to lymphocyte ratio and principal component analysis offer prognostic advantage for dogs with mammary tumors.

Introduction: In veterinary medicine, cancer is the leading cause of death in companion animals, and mammary gland tumors represent the most common neoplasm in female dogs. Several epidemiological risk factors, such as age, breed, hormones, diet, and obesity have been reported to be relevant for canine mammary tumors. Nowadays, the gold standard for diagnosis of canine mammary tumors is the pathological examination of the suspected tissue.