Globally diffeomorphic σ -harmonic mappings

Given a two-dimensional mapping U whose components solve a divergence structure elliptic equation,we give necessary and sufficient conditions on the boundary so that U is a global diffeomorphism

Deep Learning for Short-Term Prediction of Available Bikes on Bike-Sharing Stations

Bike-sharing is adopted as a valid option replacing traditional public transports since they are eco-friendly, prevent traffic congestions, reduce any possible risk of social contacts which happen mostly on public means. However, some problems may occur such as the irregular distribution of bikes on related stations/racks/areas, and the difficulty of knowing in advance what the rack status will be like, or predicting if there will be bikes available in a specific bike-station at a certain time of the day, or if there will be a free slot to leave the rented bike. Thus, providing predictions can be useful to improve the service quality, especially in those cases where bike racks are used for e-bikes, which need to be recharged. This paper compares the state-of-the-art techniques to predict the number of available bikes and free bike-slots in bike-sharing stations (i.e., bike racks). To this end, a set of features and predictive models were compared to identify the best models and predictors for short-term predictions, namely of 15, 30, 45, and 60 minutes. The study has demonstrated that deep learning and in particular Bidirectional Long Short-Term Memory networks (Bi-LSTM) offers a robust approach for the implementation of reliable and fast predictions of available bikes, even with a limited amount of historical data. This paper has also reported an analysis of feature relevance based on SHAP that demonstrated the validity of the model for different cluster behaviours. Both solution and its validation were derived by using data collected in bike-stations in the cities of Siena and Pisa (Italy), in the context of Sii-Mobility National Research Project on Mobility and Transport and Snap4City Smart City IoT infrastructure

Results from a meta-analysis of immune checkpoint inhibitors in first-line renal cancer patients: does PD-L1 matter?

Background: The aim of this study was to perform a literature-based meta-analysis to assess the efficacy of the novel immune checkpoint inhibitors (ICIs) in first-line metastatic renal cell carcinoma (RCC), focusing on the predictive role of PD-L1 expression. Methods: The primary outcome was overall survival, and secondary outcomes were progression-free survival (PFS) and objective response. We planned a subgroup analysis for overall survival according to PD-L1 status. Results: Five studies were included in the analysis for a total of 4063 cases. Overall survival was greater in PD-L1 positive tumours (HR = 0.49, 95% CI: 0.36\u20130.67; p < 0.001). The pooled analysis of the unselected cases showed a statistically significative improvement in PFS with the use of ICIs (HR = 0.85, 95% CI: 0.72\u20130.99; p = 0.04) and we found a greater PFS benefit (HR = 0.65, 95% CI: 0.57\u20130.74; p < 0.001) in patients with PD-L1 positive tumours. Conclusions: This study supports the efficacy of ICIs and, although a significant clinical benefit has been reported in PD-L1 negative patients, a greater efficacy of ICIs was observed in PD-L1 positive patients. More prospective randomized studies are needed to clarify the role of PDL-1 status in metastatic RCC treated with ICIs

The antiquity of hydrocephalus: the first full palaeo-neuropathological description

The Pathology Museum of the University of Florence houses a rich collection of anatomical specimens and over a hundred waxworks portraying pathological conditions occurring in the nineteenth century, when the museum was established. Clinical and autopsy findings of these cases can still be retrieved from the original museum catalogue, offering a rare opportunity for retrospective palaeo-pathological diagnostics. We present a historical case of severe hydrocephalus backed by modern-day anthropological, radiological and molecular analyses conducted on the skeleton of an 18-month-old male infant deceased in 1831. Luigi Calamai (1796-1851), a wax craftsman of La Specola workshop in Florence, was commissioned to create a life-sized wax model of the child's head, neck and upper thorax. This artwork allows us to appreciate the cranial and facial alterations determined by 30&nbsp;lb of cerebrospinal fluid (CSF) accumulated within the cerebral ventricular system. Based on the autopsy report, gross malformations of the neural tube, tumours and haemorrhage could be excluded. A molecular approach proved helpful in confirming sex. We present this case as the so-far most compelling case of hydrocephalus in palaeo-pathological research

Multi Clustering Recommendation System for Fashion Retail

Fashion retail has a large and ever-increasing popularity and relevance, allowing customers to buy anytime finding the best offers and providing satisfactory experiences in the shops. Consequently, Customer Relationship Management solutions have been enhanced by means of several technologies to better understand the behaviour and requirements of customers, engaging and influencing them to improve their shopping experience, as well as increasing the retailers’ profitability. Current solutions on marketing provide a too general approach, pushing and suggesting on most cases, the popular or most purchased items, losing the focus on the customer centricity and personality. In this paper, a recommendation system for fashion retail shops is proposed, based on a multi clustering approach of items and users’ profiles in online and on physical stores. The proposed solution relies on mining techniques, allowing to predict the purchase behaviour of newly acquired customers, thus solving the cold start problems which is typical of the systems at the state of the art. The presented work has been developed in the context of Feedback project partially founded by Regione Toscana, and it has been conducted on real retail company Tessilform, Patrizia Pepe mark. The recommendation system has been validated in store, as well as online

Microservices suite for smart city applications

Smart Cities are approaching the Internet of Things (IoT) World. Most of the first-generation Smart City solutions are based on Extract Transform Load (ETL); processes and languages that mainly support pull protocols for data gathering. IoT solutions are moving forward to event-driven processes using push protocols. Thus, the concept of IoT applications has turned out to be widespread; but it was initially &ldquo;implemented&rdquo; with ETL; rule-based solutions; and finally; with true data flows. In this paper, these aspects are reviewed, highlighting the requirements for smart city IoT applications and in particular, the ones that implement a set of specific MicroServices for IoT Applications in Smart City contexts. Moreover; our experience has allowed us to implement a suite of MicroServices for Node-RED; which has allowed for the creation of a wide range of new IoT applications for smart cities that includes dashboards, IoT Devices, data analytics, discovery, etc., as well as a corresponding Life Cycle. The proposed solution has been validated against a large number of IoT applications, as it can be verified by accessing the https://www.Snap4City.org portal; while only three of them have been described in the paper. In addition, the reported solution assessment has been carried out by a number of smart city experts. The work has been developed in the framework of the Select4Cities PCP (PreCommercial Procurement), funded by the European Commission as Snap4City platform

Public crowdsensing of heat waves by social media data

Abstract. Investigating on society-related heat wave hazards is a global issue concerning the people health. In the last two decades, Europe experienced several severe heat wave episodes with catastrophic effects in term of human mortality (2003, 2010 and 2015). Recent climate investigations confirm that this threat will represent a key issue for the resiliency of urban communities in next decades. Several important mitigation actions (Heat-Health Action Plans) against heat hazards have been already implemented in some WHO (World Health Organization) European region member states to encourage preparedness and response to extreme heat events. Nowadays, social media (SM) offer new opportunities to indirectly measure the impact of heat waves on society. Using the crowdsensing concept, a micro-blogging platform like Twitter may be used as a distributed network of mobile sensors that react to external events by exchanging messages (tweets). This work presents a preliminary analysis of tweets related to heat waves that occurred in Italy in summer 2015. Using TwitterVigilance dashboard, developed by the University of Florence, a sample of tweets related to heat conditions was retrieved, stored and analyzed for main features. Significant associations between the daily increase in tweets and extreme temperatures were presented. The daily volume of Twitter users and messages revealed to be a valuable indicator of heat wave impact at the local level, in urban areas. Furthermore, with the help of Generalized Additive Model (GAM), the volume of tweets in certain locations has been used to estimate thresholds of local discomfort conditions. These city-specific thresholds are the result of dissimilar climatic conditions and risk cultures

A new tow maneuver of a damaged boat through a swarm of autonomous sea drones

Given the huge rising interest in autonomous drone swarms to be employed in actual marine applications, the present paper explores the possibility to recover a distressed vessel by means of the other agents belonging to the swarm itself. Suitable approaches and control strategies are developed and tested to find the highest performance algorithms. Different rules are exploited to obtain a correct behaviour in terms of swarm interaction, namely collective and coordinated, and individual. An innovative feedback control strategy is adopted and demonstrated its effectiveness. Extensive simulation runs have been conducted, whose results validate the approach