A preliminary experiment combining marine robotics and citizenship engagement using imitation learning

In this paper, we describe a preliminary experiment of citizenship engagement in the context of marine robotics using imitation learning to train a controller that mimics human behavior. The experiment has been carried out during the Festival della Comunicazione in Camogli, Italy, in September 2019. In more detail, citizens have been asked to pilot a small, light, and safe autonomous surface vehicle in front of a crowded public beach with the goal of performing an S-shaped path. The trajectories and controls performed by non-expert human operators have been recorded with the aim of training an imitation system that, after collecting a sufficient number of trajectory-control pairs, has been able to drive the vehicle without human intervention. To learn the human behavior, echo state networks have been employed as approximating architectures. The resulting controller turned out to be very effective in successfully performing the considered experiment with a reduced amount of training trajectories by imitating the human behavior also in unknown situations. The success of this experiment may pave the way to new research processes where citizens are actively engaged. Copyright (C) 2020 The Authors

CONTRIBUIÇÃO AO PLANEJAMENTO DE RECURSOS HÍDRICOS EM BACIAHIDROGRÁFICA: GEOMORFOLOGIA E FRAGILIDADE GEOAMBIENTAL DA UGRH PARANAPANEMA

A gestão de bacias compartilhadas constitui um dos desafios na implementação dos instrumentos da Política Nacional de Recursos Hídricos no Brasil, necessitando de estudos detalhados, coordenação política e cooperação entre os participantes para que seja plenamente efetivada. Além de entraves relacionados a conflitos de interesses entre as unidades políticas usuárias desses recursos, o planejamento e a gestão de bacias hidrográficas que abrangem territórios de mais de um Município ou Estado da Federação Brasileira, se reveste de complexidade em função de questões peculiares relacionadas à articulação dos conhecimentos técnico-científicos disponíveis. Nesse sentido, a elaboração do Mapa Geomorfológico e do Mapa de Fragilidade Geoambiental da Unidade de Gestão de Recursos Hídricos Paranapanema com o objetivo principal de contribuir com as ações do CBH Paranapanema voltadas ao planejamento de recursos hídricos, exemplificam o desafio de integração de estudos produzidos com níveis de detalhamento diferenciados, decorrentes de procedimentos técnico-operacionais distintos. Assim, este artigo apresenta à comunidade geográfica os caminhos percorridos e as soluções encontradas para a compatibilização e integração de documentos cartográficos pré-existentes tais como o Mapa Geomorfológico do Estado de São Paulo, o Mapa Geomorfológico do Estado do Paraná e o Mapa de Vulnerabilidade Geoambiental do Estado do Paraná.The management of shared basins is one of the challenges in implementing the instruments of the National Water Resources Policy in Brazil, requiring detailed studies, policy coordination and cooperation between the participants to be fully effective. In addition to barriers related to conflicts of interest among users polities such resources, planning and management of the watershed covering the territory of more than one municipality or state of the Brazilian Federation, is of complexity based on peculiar issues related to the articulation of available technical and scientific knowledge. Thus, the elaboration of Geomorphological Map and the Geoenvironmental Fragility Map of Paranapanema Water Resources Management Unit with the main objective of contributing to the shares of CBH Paranapanema focused on the planning of water resources, exemplify the integration challenge studies produced with different levels of detail, resulting from different technical and operational procedures. This article presents for the geographic community the paths taken and solutions found for compatibility and integration of pre-existing cartographic documents, such as the Geomorphological Map of the São Paulo State, Geomorphological Map of the Paraná State and Geoenvironmental Vulnerability Map of the Paraná State

Beta-Blocker Use in Older Hospitalized Patients Affected by Heart Failure and Chronic Obstructive Pulmonary Disease: An Italian Survey From the REPOSI Register

Beta (β)-blockers (BB) are useful in reducing morbidity and mortality in patients with heart failure (HF) and concomitant chronic obstructive pulmonary disease (COPD). Nevertheless, the use of BBs could induce bronchoconstriction due to β2-blockade. For this reason, both the ESC and GOLD guidelines strongly suggest the use of selective β1-BB in patients with HF and COPD. However, low adherence to guidelines was observed in multiple clinical settings. The aim of the study was to investigate the BBs use in older patients affected by HF and COPD, recorded in the REPOSI register. Of 942 patients affected by HF, 47.1% were treated with BBs. The use of BBs was significantly lower in patients with HF and COPD than in patients affected by HF alone, both at admission and at discharge (admission, 36.9% vs. 51.3%; discharge, 38.0% vs. 51.7%). In addition, no further BB users were found at discharge. The probability to being treated with a BB was significantly lower in patients with HF also affected by COPD (adj. OR, 95% CI: 0.50, 0.37-0.67), while the diagnosis of COPD was not associated with the choice of selective β1-BB (adj. OR, 95% CI: 1.33, 0.76-2.34). Despite clear recommendations by clinical guidelines, a significant underuse of BBs was also observed after hospital discharge. In COPD affected patients, physicians unreasonably reject BBs use, rather than choosing a β1-BB. The expected improvement of the BB prescriptions after hospitalization was not observed. A multidisciplinary approach among hospital physicians, general practitioners, and pharmacologists should be carried out for better drug management and adherence to guideline recommendations

Antidiabetic Drug Prescription Pattern in Hospitalized Older Patients with Diabetes

Objective: To describe the prescription pattern of antidiabetic and cardiovascular drugs in a cohort of hospitalized older patients with diabetes. Methods: Patients with diabetes aged 65 years or older hospitalized in internal medicine and/or geriatric wards throughout Italy and enrolled in the REPOSI (REgistro POliterapuie SIMI—Società Italiana di Medicina Interna) registry from 2010 to 2019 and discharged alive were included. Results: Among 1703 patients with diabetes, 1433 (84.2%) were on treatment with at least one antidiabetic drug at hospital admission, mainly prescribed as monotherapy with insulin (28.3%) or metformin (19.2%). The proportion of treated patients decreased at discharge (N = 1309, 76.9%), with a significant reduction over time. Among those prescribed, the proportion of those with insulin alone increased over time (p = 0.0066), while the proportion of those prescribed sulfonylureas decreased (p < 0.0001). Among patients receiving antidiabetic therapy at discharge, 1063 (81.2%) were also prescribed cardiovascular drugs, mainly with an antihypertensive drug alone or in combination (N = 777, 73.1%). Conclusion: The management of older patients with diabetes in a hospital setting is often sub-optimal, as shown by the increasing trend in insulin at discharge, even if an overall improvement has been highlighted by the prevalent decrease in sulfonylureas prescription

The “Diabetes Comorbidome”: A Different Way for Health Professionals to Approach the Comorbidity Burden of Diabetes

(1) Background: The disease burden related to diabetes is increasing greatly, particularly in older subjects. A more comprehensive approach towards the assessment and management of diabetes’ comorbidities is necessary. The aim of this study was to implement our previous data identifying and representing the prevalence of the comorbidities, their association with mortality, and the strength of their relationship in hospitalized elderly patients with diabetes, developing, at the same time, a new graphic representation model of the comorbidome called “Diabetes Comorbidome”. (2) Methods: Data were collected from the RePoSi register. Comorbidities, socio-demographic data, severity and comorbidity indexes (Cumulative Illness rating Scale CIRS-SI and CIRS-CI), and functional status (Barthel Index), were recorded. Mortality rates were assessed in hospital and 3 and 12 months after discharge. (3) Results: Of the 4714 hospitalized elderly patients, 1378 had diabetes. The comorbidities distribution showed that arterial hypertension (57.1%), ischemic heart disease (31.4%), chronic renal failure (28.8%), atrial fibrillation (25.6%), and COPD (22.7%), were the more frequent in subjects with diabetes. The graphic comorbidome showed that the strongest predictors of death at in hospital and at the 3-month follow-up were dementia and cancer. At the 1-year follow-up, cancer was the first comorbidity independently associated with mortality. (4) Conclusions: The “Diabetes Comorbidome” represents the perfect instrument for determining the prevalence of comorbidities and the strength of their relationship with risk of death, as well as the need for an effective treatment for improving clinical outcomes

Intelligenza artificiale e sicurezza: opportunità, rischi e raccomandazioni

L'IA (o intelligenza artificiale) è una disciplina in forte espansione negli ultimi anni e lo sarà sempre più nel prossimo futuro: tuttavia è dal 1956 che l’IA studia l’emulazione dell’intelligenza da parte delle macchine, intese come software e in certi casi hardware. L’IA è nata dall’idea di costruire macchine che - ispirandosi ai processi legati all’intelligenza umana - siano in grado di risolvere problemi complessi, per i quali solitamente si ritiene che sia necessario un qualche tipo di ragionamento intelligente. La principale area di ricerca e applicazione attuale dell’IA è il machine learning (algoritmi che imparano e si adattano in base ai dati che ricevono), che negli ultimi anni ha trovato ampie applicazioni grazie alle reti neurali (modelli matematici composti da neuroni artificiali) che a loro volta hanno consentito la nascita del deep learning (reti neurali di maggiore complessità). Appartengono al mondo dell’IA anche i sistemi esperti, la visione artificiale, il riconoscimento vocale, l’elaborazione del linguaggio naturale, la robotica avanzata e alcune soluzioni di cybersecurity. Quando si parla di IA c'è chi ne è entusiasta pensando alle opportunità, altri sono preoccupati poiché temono tecnologie futuristiche di un mondo in cui i robot sostituiranno l'uomo, gli toglieranno il lavoro e decideranno al suo posto. In realtà l'IA è ampiamente utilizzata già oggi in molti campi, ad esempio nei cellulari, negli oggetti smart (IoT), nelle industry 4.0, per le smart city, nei sistemi di sicurezza informatica, nei sistemi di guida autonoma (drive o parking assistant), nei chat bot di vari siti web; questi sono solo alcuni esempi basati tutti su algoritmi tipici dell’intelligenza artificiale. Grazie all'IA le aziende possono avere svariati vantaggi nel fornire servizi avanzati, personalizzati, prevedere trend, anticipare le scelte degli utenti, ecc. Ma non è tutto oro quel che luccica: ci sono talvolta problemi tecnici, interrogativi etici, rischi di sicurezza, norme e legislazioni non del tutto chiare. Le organizzazioni che già adottano soluzioni basate sull’IA, o quelle che intendono farlo, potrebbero beneficiare di questa pubblicazione per approfondirne le opportunità, i rischi e le relative contromisure. La Community for Security del Clusit si augura che questa pubblicazione possa fornire ai lettori un utile quadro d’insieme di una realtà, come l’intelligenza artificiale, che ci accompagnerà sempre più nella vita personale, sociale e lavorativa.AI (or artificial intelligence) is a booming discipline in recent years and will be increasingly so in the near future.However, it is since 1956 that AI has been studying the emulation of intelligence by machines, understood as software and in some cases hardware. AI arose from the idea of building machines that-inspired by processes related to human intelligence-are able to solve complex problems, for which it is usually believed that some kind of intelligent reasoning is required. The main current area of AI research and application is machine learning (algorithms that learn and adapt based on the data they receive), which has found wide applications in recent years thanks to neural networks (mathematical models composed of artificial neurons), which in turn have enabled the emergence of deep learning (neural networks of greater complexity). Also belonging to the AI world are expert systems, computer vision, speech recognition, natural language processing, advanced robotics and some cybersecurity solutions. When it comes to AI there are those who are enthusiastic about it thinking of the opportunities, others are concerned as they fear futuristic technologies of a world where robots will replace humans, take away their jobs and make decisions for them. In reality, AI is already widely used in many fields, for example, in cell phones, smart objects (IoT), industries 4.0, for smart cities, cybersecurity systems, autonomous driving systems (drive or parking assistant), chat bots on various websites; these are just a few examples all based on typical artificial intelligence algorithms. Thanks to AI, companies can have a variety of advantages in providing advanced, personalized services, predicting trends, anticipating user choices, etc. But not all that glitters is gold: there are sometimes technical problems, ethical questions, security risks, and standards and legislation that are not entirely clear. Organizations already adopting AI-based solutions, or those planning to do so, could benefit from this publication to learn more about the opportunities, risks, and related countermeasures. Clusit's Community for Security hopes that this publication will provide readers with a useful overview of a reality, such as artificial intelligence, that will increasingly accompany us in our personal, social and working lives

ANÁLISE DA FRAGILIDADE POTENCIAL E EMERGENTE DO RELEVO DA UNIDADE DE GERENCIAMENTO DE RECURSOS HÍDRICOS PONTAL DO PARANAPANEMA, SÃO PAULO, BRASIL

O presente trabalho faz parte de um conjunto maior de investigações acerca da Unidade de Gerenciamento de Recursos Hídricos Pontal do Paranapanema (UGRHI-22), localizada no oeste do estado de São Paulo – Brasil, realizadas com objetivo de subsidiar ações voltadas ao planejamento ambiental e à gestão dos recursos hídricos. Este estudo foi realizado no Grupo de Pesquisa em Gestão Ambiental e Dinâmica Socioespacial (GADIS) da Universidade Estadual Paulista - UNESP, Campus Presidente Prudente, no qual foi elaborado o mapeamento da Fragilidade Potencial e Emergente do Relevo de acordo com a proposta metodológica de Ross (1990; 1994) a fim de identificar áreas que, em função de seus atributos naturais, apresentam maior ou menor fragilidade face às pressões antrópicas exercidas pelos diferentes usos e ocupações das terras

ANÁLISE DA FRAGILIDADE POTENCIAL E EMERGENTE DO RELEVO DA UNIDADE DE GERENCIAMENTO DE RECURSOS HÍDRICOS PONTAL DO PARANAPANEMA, SÃO PAULO, BRASIL

O presente trabalho faz parte de um conjunto maior de investigações acerca da Unidade de Gerenciamento de Recursos Hídricos Pontal do Paranapanema (UGRHI-22), localizada no oeste do estado de São Paulo – Brasil, realizadas com objetivo de subsidiar ações voltadas ao planejamento ambiental e à gestão dos recursos hídricos. Este estudo foi realizado no Grupo de Pesquisa em Gestão Ambiental e Dinâmica Socioespacial (GADIS) da Universidade Estadual Paulista - UNESP, Campus Presidente Prudente, no qual foi elaborado o mapeamento da Fragilidade Potencial e Emergente do Relevo de acordo com a proposta metodológica de Ross (1990; 1994) a fim de identificar áreas que, em função de seus atributos naturais, apresentam maior ou menor fragilidade face às pressões antrópicas exercidas pelos diferentes usos e ocupações das terras

A practical identification procedure for unmanned underwater vehicles - From modeling to experiments

The need of defining suitable dynamical models for Unmanned Underwater Vehicles (UUVs) is of absolute importance for the sake of a precise motion estimation (needed due the slow rate and low precision measurement usually provided by acoustic devices) and guidance & control system design, where regulation scheme and parameter setting have to be defined and evaluated on the basis of a reliable dynamical model