Reltextrank: An open source framework for building relational syntactic-semantic text pair representations

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Semantic Linking in Convolutional Neural Networks for Answer Sentence Selection

State-of-the-art networks that model relations between two pieces of text often use complex architectures and attention. In this paper, instead of focusing on architecture engineering, we take advantage of small amounts of labelled data that model semantic phenomena in text to encode matching features directly in the word representations. This greatly boosts the accuracy of our reference network, while keeping the model simple and fast to train. Our approach also beats a tree kernel model that uses similar input encodings, and neural models which use advanced attention and compare-aggregate mechanisms

Physical dispersion and disappearance of bacteria in the Golfo di Palermo: the results of two surveys.

This paper reports on some results of two surveys at sea carried out in the surroundings of a urban wastewater discharge on the coast of the Golfo di Palermo, western Sicily (Italy). At the time of the surveys (year 2005) the stretch of water lying before the central part of the capital town received the untreated wastewater originating from about 200 000 inhabitants, which was discharged on-shore without any prior treatment by the free-surface outfall of “Porta Felice main sewer”. This outfall has crucial importance in the water quality; indeed, the Municipality is steadily implementing a plan featuring an intercepting main sewer along the coast and some pumping stations to connect all the main sewers to the main wastewater treatment plant, located in the SE boundary area of the town. At the moment of the surveys, however, no mitigation measure had been applied yet and the quality of the Gulf was still largely affected by it. Part of the Sanitation Plan was the characterization of the seawater; to this aim, in August and November, 2005, the Università degli Studi di Palermo - on behalf of the Municipality’s Ufficio del Centro Storico - carried out two survey cruises in which the most important seawater quality features were investigated. What will be reported on herein is the part dealing with microbiological indicators, taking the salinity field as background

Learning Contextual Embeddings for Structural Semantic Similarity using Categorical Information.

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Cross-Language Question Re-Ranking

We study how to find relevant questions in community forums when the language of the new questions is different from that of the existing questions in the forum. In particular, we explore the Arabic-English language pair. We compare a kernel-based system with a feed-forward neural network in a scenario where a large parallel corpus is available for training a machine translation system, bilingual dictionaries, and cross-language word embeddings. We observe that both approaches degrade the performance of the system when working on the translated text, especially the kernel-based system, which depends heavily on a syntactic kernel. We address this issue using a cross-language tree kernel, which compares the original Arabic tree to the English trees of the related questions. We show that this kernel almost closes the performance gap with respect to the monolingual system. On the neural network side, we use the parallel corpus to train cross-language embeddings, which we then use to represent the Arabic input and the English related questions in the same space. The results also improve to close to those of the monolingual neural network. Overall, the kernel system shows a better performance compared to the neural network in all cases.Comment: SIGIR-2017; Community Question Answering; Cross-language Approaches; Question Retrieval; Kernel-based Methods; Neural Networks; Distributed Representation

Saipem My Health Record: a model of an electronic health record for the management of workers' health

Introduction. Saipem is a contractor company in Oil and Gas industry. Saipem has developed an in-house medical department, whose main objective, apart the management of medical emergencies, is prevention, health protection and promotion. In order to make these principals available and applicable at all site worldwide Saipem decided to initiate and develop the implementation of e-medicine in its daily operations. Methods.The challenging goal of the Saipem Medical Service is to make available to all employees their health data, quickly, easily accessible and secure. The basis for achieving these objectives is the adoption of standards that allow the exchange of data between patient, public and private structures thus ensuring the interoperability of information. My Health Records (MHR) is the program that allows the visualization, consultation and sharing of health information and data that constitute the clinical and health history of each Saipem worker. My HR makes it possible to have secure and exclusive access to your healthcare profile, its portability and the consequent possibility to consult it and show it in case of need, even from remote extemporaneous stations from any device connected to the internet (PC, smartphone or tablet) . The digitization of health documents through MHR is aimed at ensuring a) faster and more direct communication between employer, medical staff and employee, b) immediate usability and portability of data c) the availability of a vast amount of data in a single space d) a reduction in costs through the dematerialization of the data Results.In order to assess the impact of MHR on the working population, Saipem has prepared to send a satisfaction questionnaire to approximately 6.000 employees in order to understand the impact on the working population and lead to even more innovative solutions. The purpose of the questionnaire is also to sensitize the user / employee in the autonomous and completely free of this application. The result are show and discussed. Conclusion. MHR was created to offer all Saipem employees the opportunity to access their health records. This project represents a model to be proposed to all Italian companies that, following the dictates of Legislative Decree 81/08, apply Health Surveillance to their workers. The advantages are represented by the dematerialization of the data, the relative cost saving (shipment of health documentation, reduction of hours / work dedicated to the expiry of visits, possibility for public health to use health data without repetition of clinical and instrumental tests, vaccinations, etc) and greater attention to all Italian workers, both EU and non-EU, with a definitely positive impact on Public Health. The strategy of the MHR launch is proving successful, and from 1 June 2017 to 1 June 2018 16,764 accesses were registered

Prevalence of major cardiovascular risk factors among oil and gas and energy company workers

Introduction. Cardiovascular diseases (CVD) remain the biggest cause of disability and premature death throughout the world. Aim. The aim of this study was to describe and determine the prevalence of major cardiovascular risk factors emerged at the first medical examination carried out by a group of an oil and gas contractor company workers in the observation period 2000-2010. Methods. An observational cross-sectional study was conducted on 1073 workers (mean age 41 years, SD = 9.5) presenting overweight BMI (body mass index) values, hypertension and cholesterol problems. Results. In particular, we found that workers > 45 years had significant higher risk to have obesity (OR = 3.8, CI 95% = 2.5-5.7), hypertension (OR = 2.7, CI 95% = 2.1-3.6), high blood fasting glucose (OR = 2.6, CI 95% = 1.2-5.5), high cholesterol (OR = 2.7, CI 95% = 2.0-3.6), high triglycerides (OR = 1.8, CI 95% = 1.4-2.4) compared to younger (< 45 years)