A Dynamic Stroke Segmentation Technique for Sketched Symbol Recognition

In this paper, we address the problem of ink parsing, which tries to identify distinct symbols from a stream of pen strokes. An important task of this process is the segmentation of the users’ pen strokes into salient fragments based on geometric features. This process allows users to create a sketch symbol varying the number of pen strokes, obtaining a more natural drawing environment. The proposed sketch recognition technique is an extension of LR parsing techniques, and includes ink segmentation and context disambiguation. During the parsing process, the strokes are incrementally segmented by using a dynamic programming algorithm. The segmentation process is based on templates specified in the productions of the grammar specification from which the parser is automatically constructed

A user-centered approach for detecting emotions with low-cost sensors

AbstractDetecting emotions is very useful in many fields, from health-care to human-computer interaction. In this paper, we propose an iterative user-centered methodology for supporting the development of an emotion detection system based on low-cost sensors. Artificial Intelligence techniques have been adopted for emotion classification. Different kind of Machine Learning classifiers have been experimentally trained on the users' biometrics data, such as hearth rate, movement and audio. The system has been developed in two iterations and, at the end of each of them, the performance of classifiers (MLP, CNN, LSTM, Bidirectional-LSTM and Decision Tree) has been compared. After the experiment, the SAM questionnaire is proposed to evaluate the user's affective state when using the system. In the first experiment we gathered data from 47 participants, in the second one an improved version of the system has been trained and validated by 107 people. The emotional analysis conducted at the end of each iteration suggests that reducing the device invasiveness may affect the user perceptions and also improve the classification performance

Combustion CFD modeling of a spark ignited optical access engine fueled with gasoline and ethanol

Abstract In this study we present the Computational Fluid Dynamics (CFD) modeling of the combustion process using detailed chemistry in a spark-ignited (SI) optical access engine operated at part load using gasoline and ethanol as fuels. Simulation results are compared against experimental optical and indicating data. The engine is installed at the Department of Engineering of the University of Perugia, and it features a four-valve head, a transparent flat piston and a port-fuel-injection (PFI) system. Full open cycle simulations have been performed using the commercial code CONVERGE. The combustion process has been simulated using detailed chemistry and adaptive mesh refinement (AMR) to resolve in detail and track the reaction zone, in a Reynolds Averaged Navier-Stokes (RANS) modeling framework. In-cylinder pressure, heat release, and flame morphology have been compared with experimental indicating and imaging data. Tests and simulations span different air-fuel ratios in lean and rich conditions (relative air-fuel ratio λranges from 0.9 to 1.1). Results indicate that simulations are able to predict experimental data with high accuracy. Variations due to changing fuel type and air-fuel ratio are well captured. The computational cost to achieve grid-independent results has been evaluated and it is also not excessively high. Taking into account that the engine speed was quite low, i.e., 900 rpm, we conclude that, in this condition, detailed chemistry coupled with RANS works satisfactorily without turbulence chemistry interaction sub-models, and therefore without any tunings

A mobile augmented reality application for supporting real-time skin lesion analysis based on deep learning

AbstractMelanoma is considered the deadliest skin cancer and when it is in an advanced state it is difficult to treat. Diagnoses are visually performed by dermatologists, by naked-eye observation. This paper proposes an augmented reality smartphone application for supporting the dermatologist in the real-time analysis of a skin lesion. The app augments the camera view with information related to the lesion features generally measured by the dermatologist for formulating the diagnosis. The lesion is also classified by a deep learning approach for identifying melanoma. The real-time process adopted for generating the augmented content is described. The real-time performances are also evaluated and a user study is also conducted. Results revealed that the real-time process may be entirely executed on the Smartphone and that the support provided is well judged by the target users

Automatic Event Geo-Location in Twitter

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The diagnostic role of total-body 18F-FDG PET/CT in patients with multiple tumors: a report of the association of thyroid cancer with lung or renal tumors

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Whole-body radioiodine effective half-life in patients with differentiated thyroid cancer

Background: Radioactive 131I (RAI) therapy is used in patients with differentiated thyroid cancer (DTC) after total thyroidectomy for remnant ablation, adjuvant treatment or treatment of persistent disease. 131I retention data, which are used to indicate the time at which a 131I treated DTC patient can be released from the hospital, may bring some insights regarding clinical factors that prolong the length of hospitalization. The aim of this study was to investigate the 131I whole-body retention in DTC patients during 131I therapy. Methods: We monitored 166 DTC patients to follow the 131I whole-body retention during 131I therapy with a radioactivity detector fixed on the ceiling of each protected room. A linear regression fit permitted us to estimate the whole-body 131I effective half-life in each patient, and a relationship was sought between patients’ clinical characteristics and whole-body effective 131I half-life. Results: The effective 131I half-life ranged from 4.08 to 56.4 h. At multivariable analysis, longer effective 131I half-life was related to older age and extensive extra-thyroid disease. Conclusions: 131I effective half-life during 131I treatment in DTC patients is highly variable among patients and is significantly longer in older and in patients with RAI uptake in large thyroid remnants or in extrathyroidal disease that significantly prolongs the whole-body retention of 131I

Role of serial cardiac 18F-FDG PET-MRI in Anderson-Fabry disease: a pilot study

Aim: We investigated the value of serial cardiac 18F-FDG PET-MRI in Anderson–Fabry disease (AFD) and the potential relationship of imaging results with FASTEX score. Methods and results: Thirteen AFD patients underwent cardiac 18F-FDG PET-MRI at baseline and follow-up. Coefficient of variation (COV) of FDG uptake and FASTEX score were assessed. At baseline, 9 patients were enzyme replacement therapy (ERT) naïve and 4 patients were under treatment. Two patients presented a FASTEX score of 0 indicating stable disease and did not show any imaging abnormality at baseline and follow-up PET-MRI. Eleven patients had a FASTEX score > 20% indicating disease worsening. Four of these patients without late gadolinium enhancement (LGE) and with normal COV at baseline and follow-up had a FASTEX score of 35%. Three patients without LGE and with abnormal COV at baseline and follow-up had a FASTEX score ranging from 30 to 70%. Three patients with LGE and abnormal COV at baseline and follow-up had a FASTEX score between 35 and 75%. Finally, one patient with LGE and normal COV had a FASTEX score of 100%. Of the 12 patients on ERT at follow-up, FASTEX score was significantly higher in those 4 showing irreversible cardiac injury at baseline compared to 8 with negative LGE (66 ± 24 vs. 32 ± 21, p = 0.03). Conclusion: 18F-FDG PET-MRI may be effective to monitor cardiac involvement in AFD

Circulating extracellular vesicles expressing PD1 and PD-L1 predict response and mediate resistance to checkpoint inhibitors immunotherapy in metastatic melanoma

Background: The immunotherapy with immune checkpoints inhibitors (ICI) has changed the life expectancy in metastatic melanoma (MM) patients. Nevertheless, several patients do not respond hence, the identifcation and validation of novel biomarkers of response to ICI is of crucial importance. Circulating extracellular vesicles (EVs) such as PD-L1+ EV mediate resistance to anti-PD1, instead the role of PD1+ EV is not fully understood. Methods: We isolated the circulating EVs from the plasma of an observational cohort study of 71 metastatic melanoma patients and correlated the amount of PD-L1+ EVs and PD1+ EVs with the response to ICI. The analysis was performed according to the origin of EVs from the tumor and the immune cells. Subsequently, we analysed the data in a validation cohort of 22 MM patients to assess the reliability of identifed EV-based biomarkers. Additionally we assessed the involvement of PD1+ EVs in the seizure of nivolumab and in the perturbation of immune cells-mediated killing of melanoma spheroids. Results: The level of PD-L1+ EVs released from melanoma and CD8+ T cells and that of PD1+ EVs irrespective of the cellular origin were higher in non-responders. The Kaplan-Meier curves indicated that higher levels of PD1+ EVs were signifcantly correlated with poorer progression-free survival (PFS) and overall survival (OS). Signifcant correlations were found for PD-L1+ EVs only when released from melanoma and T cells. The multivariate analysis showed that high level of PD1+ EVs, from T cells and B cells, and high level of PD-L1+ EVs from melanoma cells, are independent biomarkers of response. The reliability of PD-L1+ EVs from melanoma and PD1+ EVs from T cells in predicting PFS was confrmed in the validation cohort through the univariate Cox-hazard regression analysis. Moreover we discovered that the circulating EVs captured nivolumab and reduced the T cells trafcking and tumor spheroids killing. Conclusion: Our study identifed circulating PD1+ EVs as driver of resistance to anti-PD1, and highlighted that the analysis of single EV population by liquid biopsy is a promising tool to stratify MM patients for immunotherapy

Mechanisms by which autophagy regulates memory capacity in ageing

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