Metodi innovativi di monitoraggio e di analisi di dati di traffico per la soluzione di problemi di ottimizzazione stocastica di impianti semaforici coordinati.

Lo sviluppo dell\u2019informatica e l\u2019implementazione dei progetti di Smart City hanno permesso in pochi anni di disporre di un\u2019enorme quantit\ue0 di dati. Come mettere a frutto queste informazioni \ue8 l\u2019obiettivo del presente lavoro. Il campo dell\u2019Intelligent Transportation Systems (ITS) \ue8 uno dei settori nel quale la ricerca sui nuovi dati, combinata con l\u2019Artificial Intelligent (AI), ha iniziato a mostrare risultati interessanti. L\u2019ITS permette di fornire servizi innovativi e avanzati relativi alle modalit\ue0 di trasporto e gestione del traffico e consente agli utenti di fare scelte pi\uf9 intelligenti quando utilizzano le reti di trasporto. Questo ha effetto diretto sull'efficacia dell'infrastruttura nelle citt\ue0 intelligenti urbane. La ricerca scientifica nel settore del traffico e dei trasporti ha messo a disposizione big data sul traffico in modo diretto con la necessit\ue0 di studiare modelli di analisi e di rappresentazione dei dati che vanno oltre alla classica modellistica (c.d. simulation agent model based). Grazie ai big data sul traffico e le tecniche di IA e Machine Learning (ML) \ue8 oggi possibile studiare nuovi modelli di previsione dei comportanti degli utenti della strada (c.d. data-driven models). Questo lavoro vuole essere un concreto esempio dell\u2019utilizzo di differenti sistemi innovativi di monitoraggio dei dati di traffico, di modelli di traffico e di ottimizzazione applicati in un caso reale. Le intersezioni semaforizzate analizzate sono state oggetto di una campagna di monitoraggio di video aereo con innovativa strumentazione, dell\u2019applicazione di software di computer vision ed elaborazione dei dati di traffico, di elaborazione di dati FCD, e, infine, di risoluzione di un problema di programmazione stocastica per il coordinamento ottimale. Nella stesura dell\u2019elaborato, trattandosi di uno studio misto di ricerca applicata e di un caso reale, \ue8 stata orientata pi\uf9 possibile al mantenimento di un forte contatto con il campo professionale e di reale applicabilit\ue0 dei risultati.The development of information technology and the implementation of smart city projects have made it possible in a few years to have an enormous amount of data. How to put this information to good use is the goal of this work. The field of Intelligent Transportation Systems (ITS) is one of the areas in which research on new data, combined with Artificial Intelligent (AI), has begun to show interesting results. ITS allows for the provision of innovative and advanced services relating to modes of transport and traffic management and allows users to make smarter choices when using transport networks. This has a direct effect on the effectiveness of the infrastructure in urban smart cities. Scientific research in the traffic and transport sector has made big data on traffic available directly with the need to study models of analysis and representation of data that go beyond the classic modeling (so-called simulation agent model based). Thanks to big data on traffic and AI and Machine Learning (ML) techniques, it is now possible to study new models for predicting the behavior of road users (so-called data-driven models). This work is intended to be a concrete example of the use of different innovative systems for monitoring traffic data, traffic models and optimization applied in a real case. The traffic light intersections analyzed were the subject of an aerial video monitoring campaign with innovative instrumentation, the application of computer vision software and traffic data processing, FCD data processing, and, finally, the resolution of a problem of stochastic programming for optimal coordination. In drafting the paper, since it was a mixed study of applied research and a real case, it was oriented as much as possible to maintaining a strong contact with the professional field and real applicability of the results

[The complexity of risk stratification in older patient candidate to non-cardiac surgery]

During the last decades the older patients who are candidates for surgery have grown esponentially due to the increase in life expectancy and the surgery technique improvement. Despite this, the mortality remains high and our ability to predict the surgery outcomes continues to be low in the elderly. The main reason is related to different difficulties; we are unable to differentiate properly the chronological from the biological age, and the current surgery and cardiology risk scores are poorly geriatric-oriented. We must underline how the measure of comorbidity during the preoperative evaluation is often limited to a simple count of comorbid conditions, without a more detailed assessment of their severity. On the other hand different comorbidity scores have been validated in geriatric populations showing a good correlation with prognosis, such as the Index of Coexisting Disease-ICED or the Geriatric Index of Comorbidity-GIC. Our predictive deficiency about the outcomes is linked to poor attention for identifying the frail patients that are already at high risk of disability. Recently, the evaluation of frailty is a key target for geriatric medicine, and geriatricians have developed various methods for measuring this parameter and suggesting the physical performance indexes as a reliable surrogate of frailty. Surrogate frailty measures, such as the "gait speed" or the "Short Physical Performance Battery-SPPB" seem to be the valid tools for evaluating older surgery patients due to their simplicity and short administration time. We think that the future challenge will be their widespread use in this specific clinical setting

Health Management in Italian Prisons during {COVID}-19 Outbreak: A Focus on the Second and Third Wave

The SARS-CoV-2 spread is a threatening and challenging issue for correctional systems worldwide because of many factors, particularly overcrowding and of the intrinsic characteristics of the population. The prevention measures adopted by the Italian Government were aimed to protect and preserve both inmates’ and prison workers’ health. The present study aimed to evaluate the efficacy of the adopted strategies. Methods: Data regarding Italian prisons’ occupation and prisoners’ population from January 2019 to June 2021, as well as the cumulative weekly increase of confirmed cases and the number of doses of vaccine administered among the population of inmates, the prison workers, and Italian population from November 2020 to the end of June 2021, were collected. Results: Prisons’ occupation dropped from 120% to 106% after the beginning of the pandemics. The confirmed cases between inmates were consistently lower than among the Italian population and prison workers. A time-series chart showed a time lag of one week between the peaks of the different population. Conclusions: The containing strategies adopted by the Italian correctional system have proved their effectiveness in terms of the prevention and protection of both inmate and staff health

A SERS affinity bioassay based on ion-exchanged glass microrods

14noThe well-known enhancement effect of surface-enhanced Raman spectroscopy (SERS) is associated with the presence of metallic nanostructures at the substrate surface. Different bottom-up and top-down processes have been proposed to impart the substrate with such a nanostructured layer. The former approaches are low cost but may suffer from reusability and stability. The latter strategies are expensive, time consuming and require special equipment that complicate the fabrication process. Here, we present the possibility to obtain stable and reusable SERS substrates by a low-cost silver-sodium ion-exchange process in soda-lime glass microrods. The microrods were obtained by cutting the tip of the ion-exchanged soda-lime fiber, resulting in disks of about few millimeters in length and one hundred microns in diameter. A thermal annealing post-process was applied to trigger the reduction of Ag+ ions into nanoparticles (AgNPs) within the ion-exchanged glass microrods. Afterwards, ion-exchange and thermal treatments were carefully tuned to assure the presence of silver NPs exposed on the surface of the microrods, without using any chemical etching. An AFM analysis confirmed the presence of AgNPs with size of tens of nm on the surface of the fiber probe. A SERS affinity bioassay was developed on the probe with the final aim of detecting microRNA fragments acting as biomarkers of different diseases. Specifically a DNA hybridization assay was built up by anchoring a molecular beacon containing a Raman tag on the Ag surface via thiol chemistry. Initial SERS experiments confirmed the presence of the beacon on the NPs embedded on the microrods surface, as monitored by detecting main spectral bands ascribed to the oligonucleotide chain. Finally, the ability of the platform to interact with the target microRNA sequence was assessed. The analysis was repeated on a number of miRNA sequences differing from the target to evaluate the specificity of the proposed assay.openopenBerneschi, Simone; D'Andrea, Cristiano; Giannetti, Ambra; De Angelis, Marella; Banchelli, Martina; Barucci, Andrea; Boetti, Nadia Giovanna; Pelli, Stefano; Baldini, Francesco; Pini, Roberto; Janner, Davide; Pugliese, Diego; Milanese, Daniel; Matteini, PaoloBerneschi, Simone; D'Andrea, Cristiano; Giannetti, Ambra; De Angelis, Marella; Banchelli, Martina; Barucci, Andrea; Boetti, Nadia Giovanna; Pelli, Stefano; Baldini, Francesco; Pini, Roberto; Janner, Davide; Pugliese, Diego; Milanese, Daniel; Matteini, Paol

Ion-exchanged glass microrods for SERS detection of DNA

Different chemical or physical deposition processes have been previously proposed to equip surfaces with a layer of plasmonic NPs to produce effective SERS responses. Here, we present a SERS biosensor obtained by an ion-exchange process in soda-lime glass microrods for efficient DNA detection

Adiponectin, diabetes and ischemic heart failure: a challenging relationship

Abstract Background Several peptides, named adipokines, are produced by the adipose tissue. Among those, adiponectin (AD) is the most abundant. AD promotes peripheral insulin sensitivity, inhibits liver gluconeogenesis and displays anti-atherogenic and anti-inflammatory properties. Lower levels of AD are related to a higher risk of myocardial infarction and a worse prognosis in patients with coronary artery disease. However, despite a favorable clinical profile, AD increases in relation to worsening heart failure (HF); in this context, higher adiponectinemia is reliably related to poor prognosis. There is still little knowledge about how certain metabolic conditions, such as diabetes mellitus, modulate the relationship between AD and HF. We evaluated the level of adiponectin in patients with ischemic HF, with and without type 2 diabetes, to elucidate whether the metabolic syndrome was able to influence the relationship between AD and HF. Results We demonstrated that AD rises in patients with advanced HF, but to a lesser extent in diabetics than in non-diabetics. Diabetic patients with reduced systolic performance orchestrated a slower rise of AD which began only in face of overt HF. The different behavior of AD in the presence of diabetes was not entirely explained by differences in body mass index. In addition, NT-proBNP, the second strongest predictor of AD, did not differ significantly between diabetic and non-diabetic patients. These data indicate that some other mechanisms are involved in the regulation of AD in patients with type 2 diabetes and coronary artery disease. Conclusions AD rises across chronic heart failure stages but this phenomenon is less evident in type 2 diabetic patients. In the presence of diabetes, the progressive increase of AD in relation to the severity of LV dysfunction is hampered and becomes evident only in overt HF.</p

Psychological treatments and psychotherapies in the neurorehabilitation of pain. Evidences and recommendations from the italian consensus conference on pain in neurorehabilitation

BACKGROUND: It is increasingly recognized that treating pain is crucial for effective care within neurological rehabilitation in the setting of the neurological rehabilitation. The Italian Consensus Conference on Pain in Neurorehabilitation was constituted with the purpose identifying best practices for us in this context. Along with drug therapies and physical interventions, psychological treatments have been proven to be some of the most valuable tools that can be used within a multidisciplinary approach for fostering a reduction in pain intensity. However, there is a need to elucidate what forms of psychotherapy could be effectively matched with the specific pathologies that are typically addressed by neurorehabilitation teams. OBJECTIVES: To extensively assess the available evidence which supports the use of psychological therapies for pain reduction in neurological diseases. METHODS: A systematic review of the studies evaluating the effect of psychotherapies on pain intensity in neurological disorders was performed through an electronic search using PUBMED, EMBASE, and the Cochrane Database of Systematic Reviews. Based on the level of evidence of the included studies, recommendations were outlined separately for the different conditions. RESULTS: The literature search yielded 2352 results and the final database included 400 articles. The overall strength of the recommendations was medium/low. The different forms of psychological interventions, including Cognitive-Behavioral Therapy, cognitive or behavioral techniques, Mindfulness, hypnosis, Acceptance and Commitment Therapy (ACT), Brief Interpersonal Therapy, virtual reality interventions, various forms of biofeedback and mirror therapy were found to be effective for pain reduction in pathologies such as musculoskeletal pain, fibromyalgia, Complex Regional Pain Syndrome, Central Post-Stroke pain, Phantom Limb Pain, pain secondary to Spinal Cord Injury, multiple sclerosis and other debilitating syndromes, diabetic neuropathy, Medically Unexplained Symptoms, migraine and headache. CONCLUSIONS: Psychological interventions and psychotherapies are safe and effective treatments that can be used within an integrated approach for patients undergoing neurological rehabilitation for pain. The different interventions can be specifically selected depending on the disease being treated. A table of evidence and recommendations from the Italian Consensus Conference on Pain in Neurorehabilitation is also provided in the final part of the pape

Epicardial adipose tissue and insulin resistance in patients with coronary artery disease with or without left ventricular dysfunction

Background. Epicardial adipose tissue (EAT) is a visceral fat that fulfills two important functions: lipid-storage and secretion of adipokines with pro-inflammatory and pro-atherogenic properties. It has been suggested that EAT may affect the pathogenesis of atherosclerosis and the clinical course of coronary artery disease (CAD). In patients with obesity, diabetes and metabolic syndrome, the epicardial adipose tissue is enlarged. Little is known about the role of EAT in left ventricular dysfunction. Aim of this study was to evaluate the ability of insulin resistance to predict EAT thickness in patients with significant CAD and systolic dysfunction. Methods. We enrolled 114 subjects diagnosed with CAD by angiography. The majority underwent revascularization after an acute coronary syndrome. Patients were considered affected by significant left ventricular dysfunction when EF wa