On the role of public policies supporting Free/Open Source Software: an European perspective

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On the role of public policies supporting Free/Open Source software. An European perspective

Governments’ interest in Free/Open Source (F/OS) software is steadily increasing. Several policies aimed at supporting Free/Open Source (F/OS) software have been taken or are currently under discussion all around the world. In this paper, we review the basic (economic) rationales for such policy interventions and we present some summary statistics on policies taken within the European countries. We claim that in order to evaluate correctly the consequences of such interventions one has to consider both the role and the administrative level at which such decision are taken as well as the typology of software which is involved. Moreover, we argue that the level playing field cannot be taken for granted in software markets. Therefore, non-intrusive public policies that currently prevail at the European level in terms, for instance, of the promotion of open standards or in terms of campaigns aimed at informing IT decision–makers, are likely to be welfare enhancing.Free/open source software, public policies, software market

Combining the Morris Method and Multiple Error Metrics to Assess Aquifer Characteristics and Recharge in the Lower Ticino Basin, in Italy

Groundwater flow model accuracy is often limited by the uncertainty in model parameters that characterize aquifer properties and aquifer recharge. Aquifer properties such as hydraulic conductivity can have an uncertainty spanning orders of magnitude. Meanwhile, parameters used to configure model boundary conditions can introduce additional uncertainty. In this study, the Morris Method sensitivity analysis is performed on multiple quantities of interest to assess the sensitivity of a steady-state groundwater flow model to uncertain input parameters. The Morris Method determines which of these parameters are less influential on model outputs. Uninfluential parameters can be set constant during subsequent parameter optimization to reduce computational expense. Combining multiple quantities of interest (e.g., RMSE, groundwater fluxes) when performing both the Morris Method and parameter optimization offers a more complete assessment of groundwater models, providing a more reliable and physically consistent estimate of uncertain parameters. The parameter optimization procedure also provides us an estimate of the residual uncertainty in the parameter values, resulting in a more complete estimate of the remaining uncertainty. By employing such techniques, the current study was able to estimate the aquifer hydraulic conductivity and recharge rate due to rice field irrigation in a groundwater basin in Northern Italy, revealing that a significant proportion of surficial aquifer recharge (approximately 81-94%) during the later summer is due to the flood irrigation practices applied to these fields.Comment: second submission after minor revision

A deep Natural Language Inference predictor without language-specific training data

In this paper we present a technique of NLP to tackle the problem of inference relation (NLI) between pairs of sentences in a target language of choice without a language-specific training dataset. We exploit a generic translation dataset, manually translated, along with two instances of the same pre-trained model - the first to generate sentence embeddings for the source language, and the second fine-tuned over the target language to mimic the first. This technique is known as Knowledge Distillation. The model has been evaluated over machine translated Stanford NLI test dataset, machine translated Multi-Genre NLI test dataset, and manually translated RTE3-ITA test dataset. We also test the proposed architecture over different tasks to empirically demonstrate the generality of the NLI task. The model has been evaluated over the native Italian ABSITA dataset, on the tasks of Sentiment Analysis, Aspect-Based Sentiment Analysis, and Topic Recognition. We emphasise the generality and exploitability of the Knowledge Distillation technique that outperforms other methodologies based on machine translation, even though the former was not directly trained on the data it was tested over.Comment: Conference: ICIAP202

Combining noisy well data and expert knowledge in a Bayesian calibration of a flow model under uncertainties: an application to solute transport in the Ticino basin

Groundwater flow modeling is commonly used to calculate groundwater heads, estimate groundwater flow paths and travel times, and provide insights into solute transport processes within an aquifer. However, the values of input parameters that drive groundwater flow models are often highly uncertain due to subsurface heterogeneity and geologic complexity in combination with lack of measurements/unreliable measurements. This uncertainty affects the accuracy and reliability of model outputs. Therefore, parameters' uncertainty must be quantified before adopting the model as an engineering tool. In this study, we model the uncertain parameters as random variables and use a Bayesian inversion approach to obtain a posterior,data-informed, probability density function (pdf) for them: in particular, the likelihood function we consider takes into account both well measurements and our prior knowledge about the extent of the springs in the domain under study. To keep the modelistic and computational complexities under control, we assume Gaussianity of the posterior pdf of the parameters. To corroborate this assumption, we run an identifiability analysis of the model: we apply the inversion procedure to several sets of synthetic data polluted by increasing levels of noise, and we determine at which levels of noise we can effectively recover the "true value" of the parameters. We then move to real well data (coming from the Ticino River basin, in northern Italy, and spanning a month in summer 2014), and use the posterior pdf of the parameters as a starting point to perform an Uncertainty Quantification analysis on groundwater travel-time distributions.Comment: First submissio

Public intervention for Free/Open Source Software

Ce papier passe en revue les principaux arguments théoriques et pratiques pour et contre les politiques en faveur du logiciel libre. À partir d’informations recueillies à partir du site OSOR.eu, nous construisons une base de données sur les interventions publiques liées au logiciel libre, établissant qu’en Europe le soutien public au logiciel libre se fait le plus souvent par une adoption directe du partenaire public ou par ses avis favorables à une telle adoption. Notre analyse suggère qu’une analyse sérieuse de la rationalité, des motivations et des conséquences de telles interventions publiques passe par un examen attentif des différents rôles des pouvoirs publics et des différentes catégories de logiciels en jeu. Les arguments empiriques que nous apportons établissent que le soutien au logiciel libre est plus fort i) quand les services en ligne de l’État sont largement disponibles, et ii) quand l’industrie locale du logiciel est en retard. Cette observation empirique va dans le sens de conceptions partagées par les défenseurs du logiciel libre.This paper reviews the main theoretical and practical arguments in favor and against government policies supporting Free/Open Source Software (F/OSS). Using information gathered from the OSOR.eu website, we build an original dataset about public interventions related to F/OSS, showing that across Europe public adoption and advisory are the most common policies. Our analysis suggests that, to evaluate in a meaningful way rationales, motivations and consequences of such public interventions, one has to properly distinguish between the various roles played by policy makers and the different categories of software involved. We provide empirical evidence that F/OSS support is stronger in countries i) where e-government services are more largely available, and ii) where the domestic software industry is lagging behind. This evidence supports common views among F/OSS advocates

Influenza anti-stalk antibodies: Development of a new method for the evaluation of the immune responses to universal vaccine

Growing interest in universal influenza vaccines and novel administration routes has led to the development of alternative serological assays that are able to detect antibodies against conserved epitopes. We present a competitive ELISA method that is able to accurately determine the ratio of serum immunoglobulin G directed against the different domains of the hemagglutinin, the head and the stalk. Human serum samples were treated with two variants of the hemagglutinin protein from the A/California/7/2009 influenza virus. The signals detected were assigned to different groups of antibodies and presented as a ratio between head and stalk domains. A subset of selected sera was also tested by hemagglutination inhibition, single radial hemolysis, microneutralization, and enzyme-linked lectin assays. Pre-vaccination samples from adults showed a quite high presence of anti-stalk antibodies, and the results were substantially in line with those of the classical serological assays. By contrast, pre-vaccination samples from children did not present anti-stalk antibodies, and the majority of the anti-hemagglutinin antibodies that were detected after vaccination were directed against the head domain. The presented approach, when supported by further assays, can be used to assess the presence of specific anti-stalk antibodies and the potential boost of broadly protective antibodies, especially in the case of novel universal influenza vaccine approaches

Flexibility assessment of a biorefinery distillation train: Optimal design under uncertain conditions

Multicomponent mixtures can be separated into their single components by mean of different distillation system configurations. The typical distillation train design procedure consists of the assessment of the optimal columns configuration according to the economic and operational aspects. However, this optimal design is strictly related to the operating conditions, i.e. perturbations, when present, can seriously compromise the operation profitability. In these cases a flexibility analysis could be of critical importance to assess the operating conditions range of better performance for different system configurations. This is the typical case of biorefineries where the floating nature of the feedstock causes composition disturbances downstream the fermenter across the year’s seasons. A brand new ABE/W mixture separation case study has been set up - this mixture derives from an upstream microbial conversion process and the successful recovery of at least biobutanol and acetone is crucial for the return on the investments. This paper then compares the possible distillation train configurations from a flexibility point of view. The analysis is focused in particular in highlighting the differences, if present, between the economic optimal solution and flexibility optimal configuration that could not be the same, causing this way a very profitable design to be much less performant under perturbated conditions. Furthermore, a detailed analysis correlating the complex thermodynamics to the operation under uncertain conditions is thoroughly discussed. The proposed design procedure allowed to highlight the differences between weak and strong flexibility constraints and resulted in a dedicated “additional costs vs. flexibility” trend useful to improve the decision making

Characterisation of SARS-CoV-2 Lentiviral Pseudotypes and Correlation between Pseudotype-Based Neutralisation Assays and Live Virus-Based Micro Neutralisation Assays

The recent outbreak of a novel Coronavirus (SARS-CoV-2) and its rapid spread across the continents has generated an urgent need for assays to detect the neutralising activity of human sera or human monoclonal antibodies against SARS-CoV-2 spike protein and to evaluate the serological immunity in humans. Since the accessibility of live virus microneutralisation (MN) assays with SARS-CoV-2 is limited and requires enhanced bio-containment, the approach based on "pseudotyping" can be considered a useful complement to other serological assays. After fully characterising lentiviral pseudotypes bearing the SARS-CoV-2 spike protein, we employed them in pseudotype-based neutralisation assays in order to profile the neutralising activity of human serum samples from an Italian sero-epidemiological study. The results obtained with pseudotype-based neutralisation assays mirrored those obtained when the same panel of sera was tested against the wild type virus, showing an evident convergence of the pseudotype-based neutralisation and MN results. The overall results lead to the conclusion that the pseudotype-based neutralisation assay is a valid alternative to using the wild-type strain, and although this system needs to be optimised and standardised, it can not only complement the classical serological methods, but also allows serological assessments to be made when other methods cannot be employed, especially in a human pandemic context