A proposal for a simple average-based progressive taxation system

This paper is a first theoretical presentation of a simple progressive taxation system. The system is based on two adaptations of one easily calculable formula that is based on the societal average income of the previous year. The system contributes to academic discussions as it is a novel approach. It is a progressive tax that does not discriminate against anyone as the progression increases continuously and the increase in tax payment does not go beyond the additional income. The analysis in the paper shows that the core advantage of the system is its simple, transparent and adaptable mechanism

Leukemia relapse via genetic immune escape after allogeneic hematopoietic cell transplantation

Graft-versus-leukemia (GvL) reactions are responsible for the effectiveness of allogeneic hematopoietic cell transplantation as a treatment modality for myeloid neoplasia, whereby donor T- effector cells recognize leukemia neoantigens. However, a substantial fraction of patients experiences relapses because of the failure of the immunological responses to control leukemic outgrowth. Here, through a broad immunogenetic study, we demonstrate that germline and somatic reduction of human leucocyte antigen (HLA) heterogeneity enhances the risk of leukemic recurrence. We show that preexistent germline-encoded low evolutionary divergence of class II HLA genotypes constitutes an independent factor associated with disease relapse and that acquisition of clonal somatic defects in HLA alleles may lead to escape from GvL control. Both class I and II HLA genes are targeted by somatic mutations as clonal selection factors potentially impairing cellular immune responses and response to immunomodulatory strategies. These findings define key molecular modes of post-transplant leukemia escape contributing to relapse

Is information and communication technology satisfying educational needs at school?

This paper assesses how the integration of ICT in education has affected the mathematics test scores for Italian students measured by the Programme for International Student Assessment 2012 data. The problem of endogeneity that affects survey data in this area, is addressed by applying the Bayesian Additive Regression Trees (BART) methodology as in Cabras & Tena Horrillo (2016). The BART methodology needs a prior and likelihood functions using the Markov Chain Monte Carlo (MCMC) algorithm to obtain the posterior distribution. Controlling for socioeconomic, demographic and school factors, the predicted posterior distribution implies an increase, on average, of 16 points in the test scores. The result indicates that the use of ICT at school has a positive and strong impact on mathematic test scores

Is information and communication technology satisfying educational needs at school?

This paper assesses how the integration of ICT in education has affected the mathematics test scores for Italian students measured by the Programme for International Student Assessment 2012 data. The problem of endogeneity that affects survey data in this area, is addressed by applying the Bayesian Additive Regression Trees (BART) methodology as in Cabras & Tena Horrillo (2016). The BART methodology needs a prior and likelihood functions using the Markov Chain Monte Carlo (MCMC) algorithm to obtain the posterior distribution. Controlling for socioeconomic, demographic and school factors, the predicted posterior distribution implies an increase, on average, of 16 points in the test scores. The result indicates that the use of ICT at school has a positive and strong impact on mathematic test scores

Is information and communication technology satisfying educational needs at school?

This paper assesses how the integration of ICT in education has affected the mathematics test scores for Italian students measured by the Programme for International Student Assessment 2012 data. The problem of endogeneity that affects survey data in this area, is addressed by applying the Bayesian Additive Regression Trees (BART) methodology as in Cabras & Tena Horrillo (2016). The BART methodology needs a prior and likelihood functions using the Markov Chain Monte Carlo (MCMC) algorithm to obtain the posterior distribution. Controlling for socioeconomic, demographic and school factors, the predicted posterior distribution implies an increase, on average, of 16 points in the test scores. The result indicates that the use of ICT at school has a positive and strong impact on mathematic test scores

Local governments’ efficiency and educational results: empirical evidence from Italian primary schools

In Italy, the provision of educational ancillary services (like meals and school transportation) is in charge of the municipalities. We investigate whether municipalities differ in their efficiency when providing these services and whether such heterogeneity explains some portion of the variability observed in pupils’ test scores. The paper is the first application of a nonparametric order-m model and a two-stage multilevel regression to a unique administrative dataset, made of the entire population of Italian pupils tested in reading and mathematics at grade 5 (academic years 2012/2013 and 2014/2015). Results demonstrate that local governments have different efficiency levels in providing services to schools. The test scores’ variability among pupils, however, is not explained by different efficiency levels of local government in producing ancillary services

Local governments’ efficiency and educational results: empirical evidence from Italian primary schools

In Italy, the provision of educational ancillary services (like meals and school transportation) is in charge of the municipalities. We investigate whether municipalities differ in their efficiency when providing these services and whether such heterogeneity explains some portion of the variability observed in pupils’ test scores. The paper is the first application of a nonparametric order-m model and a two-stage multilevel regression to a unique administrative dataset, made of the entire population of Italian pupils tested in reading and mathematics at grade 5 (academic years 2012/2013 and 2014/2015). Results demonstrate that local governments have different efficiency levels in providing services to schools. The test scores’ variability among pupils, however, is not explained by different efficiency levels of local government in producing ancillary services

DIAMIN: a software library for the distributed analysis of large-scale molecular interaction networks

Background Huge amounts of molecular interaction data are continuously produced and stored in public databases. Although many bioinformatics tools have been proposed in the literature for their analysis, based on their modeling through different types of biological networks, several problems still remain unsolved when the problem turns on a large scale. Results We propose DIAMIN, that is, a high-level software library to facilitate the development of applications for the efficient analysis of large-scale molecular interaction networks. DIAMIN relies on distributed computing, and it is implemented in Java upon the framework Apache Spark. It delivers a set of functionalities implementing different tasks on an abstract representation of very large graphs, providing a built-in support for methods and algorithms commonly used to analyze these networks. DIAMIN has been tested on data retrieved from two of the most used molecular interactions databases, resulting to be highly efficient and scalable. As shown by different provided examples, DIAMIN can be exploited by users without any distributed programming experience, in order to perform various types of data analysis, and to implement new algorithms based on its primitives. Conclusions The proposed DIAMIN has been proved to be successful in allowing users to solve specific biological problems that can be modeled relying on biological networks, by using its functionalities. The software is freely available and this will hopefully allow its rapid diffusion through the scientific community, to solve both specific data analysis and more complex tasks

SARS-CoV-2-Legionella Co-Infections: A Systematic Review and Meta-Analysis (2020-2021)

Legionnaires' Disease (LD) is a severe, sometimes fatal interstitial pneumonia due to Legionella pneumophila. Since the inception of the SARS-CoV-2 pandemic, some contradictory reports about the effects of lockdown measures on its epidemiology have been published, but no summary evidence has been collected to date. Therefore, we searched two different databases (PubMed and EMBASE) focusing on studies that reported the occurrence of LD among SARS-CoV-2 cases. Data were extracted using a standardized assessment form, and the results of such analyses were systematically reported, summarized, and compared. We identified a total of 38 articles, including 27 observational studies (either prospective or retrospective ones), 10 case reports, and 1 case series. Overall, data on 10,936 SARS-CoV-2 cases were included in the analyses. Of them, 5035 (46.0%) were tested for Legionella either through urinary antigen test or PCR, with 18 positive cases (0.4%). A pooled prevalence of 0.288% (95% Confidence Interval (95% CI) 0.129-0.641), was eventually calculated. Moreover, detailed data on 19 co-infections LD + SARS-CoV-2 were obtained (males: 84.2%; mean age: 61.9 years, range 35 to 83; 78.9% with 1 or more underlying comorbidities), including 16 (84.2%) admissions to the ICU, with a Case Fatality Ratio of 26.3%. In summary, our analyses suggest that the occurrence of SARS-CoV-2-Legionella infections may represent a relatively rare but not irrelevant event, and incident cases are characterized by a dismal prognosis