Training Temporal Word Embeddings with a Compass

Temporal word embeddings have been proposed to support the analysis of word meaning shifts during time and to study the evolution of languages. Different approaches have been proposed to generate vector representations of words that embed their meaning during a specific time interval. However, the training process used in these approaches is complex, may be inefficient or it may require large text corpora. As a consequence, these approaches may be difficult to apply in resource-scarce domains or by scientists with limited in-depth knowledge of embedding models. In this paper, we propose a new heuristic to train temporal word embeddings based on the Word2vec model. The heuristic consists in using atemporal vectors as a reference, i.e., as a compass, when training the representations specific to a given time interval. The use of the compass simplifies the training process and makes it more efficient. Experiments conducted using state-of-the-art datasets and methodologies suggest that our approach outperforms or equals comparable approaches while being more robust in terms of the required corpus size.Comment: Accepted at AAAI201

Chapter Longitudinal profile of a set of biomarkers in predicting Covid-19 mortality using joint models

In survival analysis, time-varying covariates are endogenous when their measurements are directly related to the event status and incomplete information occur at random points during the follow-up. Consequently, the time-dependent Cox model leads to biased estimates. Joint models (JM) allow to correctly estimate these associations combining a survival and longitudinal sub-models by means of a shared parameter (i.e., random effects of the longitudinal sub-model are inserted in the survival one). This study aims at showing the use of JM to evaluate the association between a set of inflammatory biomarkers and Covid-19 mortality. During Covid-19 pandemic, physicians at Istituto Clinico di Città Studi in Milan collected biomarkers (endogenous time-varying covariates) to understand what might be used as prognostic factors for mortality. Furthermore, in the first epidemic outbreak, physicians did not have standard clinical protocols for management of Covid-19 disease and measurements of biomarkers were highly incomplete especially at the baseline. Between February and March 2020, a total of 403 COVID-19 patients were admitted. Baseline characteristics included sex and age, whereas biomarkers measurements, during hospital stay, included log-ferritin, log-lymphocytes, log-neutrophil granulocytes, log-C-reactive protein, glucose and LDH. A Bayesian approach using Markov chain Monte Carlo algorithm were used for fitting JM. Independent and non-informative priors for the fixed effects (age and sex) and for shared parameters were used. Hazard ratios (HR) from a (biased) time-dependent Cox and joint models for log-ferritin levels were 2.10 (1.67-2.64) and 1.73 (1.38-2.20), respectively. In multivariable JM, doubling of biomarker levels resulted in a significantly increase of mortality risk for log-neutrophil granulocytes, HR=1.78 (1.16-2.69); for log-C-reactive protein, HR=1.44 (1.13-1.83); and for LDH, HR=1.28 (1.09-1.49). Increasing of 100 mg/dl of glucose resulted in a HR=2.44 (1.28-4.26). Age, however, showed the strongest effect with mortality risk starting to rise from 60 years

Serous Retinal Detachments Complicating Interferon-α and Ribavirin Treatment in Patients with Hepatitis C

Purpose: To report the cases of two patients with chronic hepatitis C infection showing serous retinal detachments similar to Vogt-Koyanagi-Harada (VKH) disease. Methods: We reviewed the clinical records of two patients who were diagnosed with VKH-like disease during combined interferon-α (IFNα) and ribavirin treatment. Results: Interruption of IFNα and ribavirin treatment in association with oral corticosteroids resulted in a favorable visual outcome in the case of diffuse retinal detachment (case 1). On the contrary, visual acuity did not improve when late cicatricial stage disease was already present (case 2). Conclusion: There is increasing evidence of a link between hepatitis C virus infection treated with pegylated IFNα-2b and the development of VKH-like disease. Knowing the potential side effects of IFNα and ribavirin administration is fundamentally important, as is the need to closely follow up those patients that need to undergo this treatment

Power system investment optimization to identify carbon neutrality scenarios for Italy

In 2021, the European Commission has adopted the Fit-for-55 policy package, legally binding European countries to reduce their CO2 emissions by 55% with respect to 1990, a first step to achieve carbon neutrality in 2050. In this context, it is crucial to help national policymakers to choose the most appropriate technologies to achieve these goals and energy system modelling can be a valuable tool. This article presents a model of the Italian power system realized employing the open energy modelling framework Oemof. A Linear Programming Optimization is implemented to evaluate how to minimise system costs at decreasing CO2 emissions in 2030. The developed tool is applied to evaluate different research questions: i) pathway towards full decarbonization and power self-sufficiency of the electricity sector in Italy, ii) relevance of flexibility assets in power grids: li-ion batteries, hydrogen storage and transmission lines reinforcement. A 55% CO2 emissions reduction for the actual Italian power sector can be achieved through an increase of 30% of the total annual system cost. Full decarbonization can be reached with four times today's annual costs, which could be lowered with sector coupling and considering more technologies.Comment: 18 pages, 13 figure