Internet districts in Italy: is proximity an antidote against weak broadband competition?

We study the effects of proximity in the interconnections between Internet providers participating at the three main Italian Internet Exchange Points. We find that geographical proximity plays a role in driving Internet Providers’ interconnection, positively affecting the likelihood of an agreement. This suggests the existence of localized positive externalities in the form of mutual knowledge and reputation, one of the cited drivers underlying the formation of districts in non high-tech industries. We interpret these results as resulting from the necessity for cooperation in interconnection between smaller providers facing the weak competitiveness of the highly concentrated Italian broadband access market

Approaching public perceptions of datafication through the lens of inequality: a case study in public service media

In the emerging field of critical data studies, there is increasing acknowledgement that the negative effects of datafication are not experienced equally by all. Research on data and discrimination in particular has highlighted how already socially unequal populations are discriminated against in data-driven systems. Elsewhere, there is growing interest in public perceptions of datafication, amongst academic researchers interested in producing ‘bottom up’ understandings of the new roles of data in society and non-academic stakeholders keen to establish positive perceptions of data-driven systems. However, research into public perceptions rarely engages with the issue of inequality which is so central in data and discrimination scholarship. Bringing these two issues together, this paper explores public perceptions of datafication through the lens of inequality, focusing on the relationship between understandings and feelings within these perceptions. The paper draws on empirical focus group research into how audiences perceive the data practices that signing in to access BBC digital services enable. The paper shows how inequalities relating to age, dis/ability, poverty and their intersections played a role in shaping perceptions and that these social inequalities informed understandings of and feelings about data practices in complex and diverse ways. It concludes with reflections on the significance of these findings for future research and for data-related policy

Stability assessment of a tailings storage facility using a non-local constitutive model accounting for anisotropic strain-softening

Recent failures of upstream-raised tailings storage facilities (TSF) raised con-cerns on the future use of these dams. While being cost-effective, they entail higher risks than conventional dams, as stability largely relies on the strength of tailings, which are loose and normally-consolidated materials that may exhibit strain-softening during un-drained loading. Current design practice involves limit equilibrium analyses adopting a fully-softened shear strength; while being conservative, this practice neglects the work input required to start the softening process that leads to progressive failure. This paper describes the calibration and application of the NGI-ADPSoft constitutive model to evaluate the potential of static liquefaction of an upstream-raised TSF and provides an indirect measure of resilience. The constitutive model incorporates undrained shear strength anisotropy and a mesh-independent anisotropic post-peak strain softening. The calibration is performed using laboratory testing, including anisotropically-consolidated triaxial compression tests and direct simple shear tests. The peak and residual undrained shear strengths are validated by statistical interpretation of the available CPTu data. It is shown that this numerical exercise is useful to verify the robustness of the TSF design.Comment: NGI-ADPSoft, Plaxis 2D, Strain-softening, Tailings, Static Liquefactio

Feminicide & machine learning : detecting gender-based violence to strengthen civil sector activism

Although governments have passed legislation criminalizing feminicide, it is unaccompanied by relevant policy or robust data collection. This participatory action research project is designed to help sustain activist efforts to collect feminicide data through partially automated detection using machine learning. As a way to counter the impunity surrounding feminicide, activists have taken upon themselves to do the work that states have neglected. Partially automating detection supports efforts to systematize and sort data collection across contexts, and helps to inform policy advocacy through standardizing definitions and taxonomies. The ability to prioritize articles by likelihood of feminicide will make this intense research less gruelling

Issues related to piezocone sleeve friction measurement accuracy in soft sensitive clays

Over the past decades, the piezocone testing has been increasingly adopted for field investigation as it offers a quick and cost-effective methodology for subsoil profiling and geotechnical parameters estimation. Although the piezocone testing has revealed good applicability worldwide, difficulties are encountered in complex soil conditions, such as soft sensitive clays. One of the key issues in such soils is represented by the poor quality of the sleeve friction (fs) measurement due to inaccuracy and poor resolution of the sleeve sensor. This paper investigates the influence of fs data quality on soil parameters determination with particular emphasis on the soil behavior type (SBT) chart classification. The field investigation was conducted in a soft sensitive clay site located in Finland using two different penetrometers: a standard piezocone and an advanced piezocone characterized by enhance accuracy sleeve friction sensor. Results show that the use of high-resolution piezocone plays a key role in soft clays to avoid misleading soil type classification.publishedVersionPeer reviewe

A Hundred Thousand Lousy Cats (exploring drawing, AI and creativity)

This paper introduces a practice-led project that uses the Google Quick, Draw! project and dataset to explore the potential differences of algorithmic machine or digitally constructed drawings, and fictional associative hand-drawings. The authors use both digital 20-second sketching (the rule set for the Quick, Draw! Project) and more elaborate drawings and collages to then analyse and speculate about the results of these types of visualisations. At this phase of research it seems obvious to label and move the machine drawing to the reductive, the handdrawn to the more complex and associative realm but we seek to unpack this binary. Artificial intelligence and machine-learning are producing a wealth of creative projects, we select a couple of case studies to speak to particular visual artefacts that derive from algorithmic processing. For instance, the (IBM AI) Watson-composed film trailer for Morgan is considered as a creative artefact and looked at for its apparent allure and effect on a creative process. Through this inquiry we contemplate surprises and mistakes that come naturally when producing hand-made works, exploring then, what it means to draw and to work within classification systems in an algorithm-leaning world

Piezocone testing in Nordic soft clays : Comparison of high-quality databases

Soft and sensitive clays are widespread in Scandinavia. Piezocone correlations for Norwegian clays have been previously proposed based on high-quality block samples from several sites. Recently, a large database of Finnish soft clays was compiled by Tampere University from piezocone measurements as well as high-quality laboratory tests on specimens from large tube samples. Finnish and Norwegian clays exhibit some differences in terms of basic properties. Norwegian clays show lower water content, lower organic content, higher silt content and lower plasticity than the clays from Finland. This may be linked to the source of the materials, their depositional and post-depositional processes that in turn impact on the mechanical behaviour. This paper aims to compare piezocone Norwegian and Finnish data with focus on strength and stress history. The database trends are compared for relevant engineering parameters. The data and its variability are critically discussed considering differences in geological history, basic properties, sampling techniques and disturbance.publishedVersionPeer reviewe

The performance of the Italian housing market and its effects on the financial system

Developments in the real-estate sector are of crucial importance for the business cycle and financial stability. This study analyses developments in the Italian housing market on the basis of both real and financial variables. Following the sharp contraction of the market during the financial crisis and the more general fall in economic activity, a few signals suggests that the recession in the housing market is easing somewhat. However, the degree of uncertainty remains considerable. In recent months the ratio between the flow of bad debts to total outstanding loans to households and construction firms has reached the highest levels since the beginning of the decade. The paper also investigates three issues of a more structural nature. First, it examines the performance and the regulatory framework of real-estate investment funds in Italy. Second, it analyses the main characteristics of the taxation of residential housing, with reference to ownership, rentals and transactions. Finally, the paper estimates the impact on residential house prices of the growing demand for housing services by immigrants.housing market cycle, transactions, rentals, residential house prices, mortgages, real-estate investment funds, taxation of residential housing

Baricitinib retention rate: ‘real-life’ data from a mono-centric cohort of patients affected by rheumatoid arthritis

ObjectivesThe aim of this retrospective study was to evaluate baricitinib retention rate in patients affected by rheumatoid arthritis. Secondary aims were to compare the impact on treatment persistence of monotherapy and other variables such as systemic corticosteroid use, line of treatment, disease duration, sex, biomarkers positivity, and Herpes Zoster virus infection.Materials and methodsPatients with Rheumatoid Arthritis undergoing baricitinib were consecutively enrolled. Rheumatoid Arthritis diagnosis was performed with 2010 ACR/EULAR classification criteria. The cohort’s demographic, clinical and therapeutical data were retrospectively collected. The whole follow-up duration was 104 weeks.ResultsNinety-five patients affected by rheumatoid arthritis and treated with baricitinib were consecutively enrolled. At the end of follow-up, the overall retention rate was 69.3%. No statistically significant difference in retention rate was observed between patients treated with baricitinib in monotherapy or in combination with methotrexate (p = 0.638) while patients undergoing a steroidal treatment showed a significantly reduced treatment retention (p = 0.028). Contrarily, patients treated with baricitinib as a first-line b/tsDMARD showed higher drug retention (p = 0.002) compared to further treatment lines. Steroid employment, steroid dosage and previous treatment with bDMARDs correlated with risk of treatment discontinuation and at univariate analysis (p = 0.028, p < 0.001, and p = 0.002 respectively). Multivariate analysis confirmed significance for higher steroid dosage and previous treatment with bDMARDs (p = 0.002 and p = 0.046). No adverse events such as deep venous thrombosis, pulmonary embolism or tubercular infection/reactivation were reported during the study observation.ConclusionOur data show a good baricitinib retention rate after 12 and 24 months of observation (75.1 and 69.3%, respectively). In our cohort, concomitant treatment with methotrexate did not influence treatment persistence while retention was reduced in patients undergoing a steroidal treatment and/or in multi-failure subjects