Studio e sperimentazione di strumenti software per presentazioni pubbliche basati su Raspberry Pi

Oggigiorno il mercato offre una varietà notevole di proiettori wireless; i modelli disponibili tuttavia presentano per alcuni aspetti, evidenti limitazioni nelle modalità di funzionamento e sono acquistabili a costi relativamente elevati. In questo elaborato viene discussa la realizzazione di un modello alternativo di proiettore wireless che sia in grado di superare questi vincoli. In particolare, il modello proposto è basato dal lato software, sulla condivisione dello schermo resa disponibile dalla tecnologia VNC e dal lato hardware, sull’utilizzo di due diverse versioni di Raspberry Pi. Il lavoro essenzialmente si configura come una serie di sperimentazioni sull’argomento, e può essere diviso in due parti: alla prima, in cui si è dotato un proiettore tradizionale di capacità wireless affiancandogli un Raspberry Pi, si succede una seconda parte nella quale è stata costruita un’estensione atta a rendere l’esperienza di proiezione, di documenti PDF in particolare, ancora più facile e immediata per l’utente

FLATLAND: A study of Deep Reinforcement Learning methods applied to the vehicle rescheduling problem in a railway environment

In the field of Reinforcement Learning the task is learning how agents should take sequences of actions in an environment in order to maximize a numerical reward signal. This learning process employed in combination with neural networks has given rise to Deep Reinforcement Learning (DRL), that is nowadays applied in many domains, from video games to robotics and self-driving cars. This work investigates possible DRL approaches applied to Flatland, a multi-agent railway simulation where the main task is to plan and reschedule train routes in order to optimize the traffic flow within the network. The tasks introduced in Flatland are based on the Vehicle Rescheduling Problem, for which determining an optimal solution is a NP-complete problem in combinatorial optimization and determining acceptably good solutions using heuristics and deterministic methods is not feasible in realistic railway systems. In particular, we analyze the tasks of navigation of a single agent inside a map, that from a starting position has to reach a target station in the minimum number of time steps and the generalization of this task to a multi-agent setting, with the new issue of conflicts avoidance and resolution between agents. To solve the problem we developed specific observations of the environment, so as to capture the necessary information for the network, trained with Deep Q-Learning and variants, to learn the best action for each agent, that leads to the solution that maximizes the total reward. The positive results obtained on small environments offer ideas for various interpretations and possible future developments, showing that Reinforcement Learning has the potential to solve the problem under a new perspective

Olive Fruit Ripening Degree and Water Content Relationships with Phenolic Acids and Alcohols, Secoiridoids, Flavonoids and Pigments in Fruit and Oil

: Olive drupe traits (i.e., ripening index and pericarp water content) and minor components (i.e., phenols and pigments in both fruit and oil) are important for human health and are affected by agronomic background. The aim of this study was to investigate the relationship between fruit traits, phenols, and pigments in samples derived from different soil and water management practices. Chromatographic (UHPLC-MS/MS) and spectroscopic (1HNMR and near UV-Vis spectroscopy) techniques were employed for the characterization of olive fruits and oils. The use of various techniques allowed the identification of interesting trace compounds. We observed that most of the fruit phenols (a total of 29 compounds) were correlated with the degree of ripening: most of the phenolic acids (and their derivatives), phenolic alcohols, and secoiridoids were negatively correlated, whereas the majority of the studied flavonoids were positively correlated. The relationship between the ripening index and fruit phenolic compounds appears to be dependent on the metabolic pathway that controls the synthesis of each individual compound. Conversely, the secoiridoids and pigments in olive oil showed a negative correlation with pulp moisture, probably because of the influence of the water content on the extractability and transfer in the oil phase of these minor components

Metformin as a new anti-cancer drug in adrenocortical carcinoma

Adrenocortical carcinoma (ACC) is a rare heterogeneous malignancy with poor prognosis. Since radical surgery is the only available treatment, more specific and effective drugs are urgently required. The anti-diabetic drug metformin has been associated with a decreased cancer prevalence and mortality in several solid tumors, prompting its possible use for ACC treatment. This paper evaluates the in vitro and in vivo anti-cancer effects of metformin using the ACC cell model H295R. Metformin treatment significantly reduces cell viability and proliferation in a dose- and time-dependent manner and associates with a significant inhibition of ERK1/2 and mTOR phosphorylation/activation, as well as with stimulation of AMPK activity. Metformin also triggers the apoptotic pathway, shown by the decreased expression of Bcl-2 and HSP27, HSP60 and HSP70, and enhanced membrane exposure of annexin V, resulting in activation of caspase-3 apoptotic effector. Metformin interferes with the proliferative autocrine loop of IGF2/IGF-1R, which supports adrenal cancer growth. Finally, in the ACC xenograft mouse model, obtained by subcutaneous injection of H295R cells, metformin intraperitoneal administration inhibits tumor growth, confirmed by the significant reduction of Ki67%. Our data suggest that metformin inhibits H295R cell growth both in vitro and in vivo. Further preclinical studies are necessary to validate the potential anti-cancer effect of metformin in patients affected by ACC

Rosiglitazone Inhibits Adrenocortical Cancer Cell Proliferation by Interfering with the IGF-IR Intracellular Signaling

Rosiglitazone (RGZ), a thiazolidinedione ligand of the peroxisome proliferator-activated receptor (PPAR)-γ, has been recently described as possessing antitumoral properties. We investigated RGZ effect on cell proliferation in two cell line models (SW13 and H295R) of human adrenocortical carcinoma (ACC) and its interaction with the signaling pathways of the activated IGF-I receptor (IGF-IR). We demonstrate a high expression of IGF-IR in the two cell lines and in ACC. Cell proliferation is stimulated by IGF-I in a dose- and time-dependent manner and is inhibited by RGZ. The analysis of the main intracellular signaling pathways downstream of the activated IGF-IR, phosphatidyl inositol 3-kinase (PI3K)-Akt, and extracellular signal-regulated kinase (ERK1/2) cascades reveals that RGZ rapidly interferes with the Akt and ERK1/2 phosphorylation/activation which mediates IGF-I stimulated proliferation. In conclusion, our results suggest that RGZ exerts an inhibitory effect on human ACC cell proliferation by interfering with the PI3K/Akt and ERK1/2 signaling pathways downstream of the activated IGF-IR