Impiego di batteri lattici autoctoni per il miglioramento igienico-sanitario del Pecorino Siciliano DOP

Il Pecorino Siciliano DOP \ue8 considerato il pi\uf9 antico formaggio prodotto in Sicilia e, probabilmente, d\u2019Europa. Le citazioni storiche sulla sua antica origine risalgono al IX secolo a.C. in uno dei passi pi\uf9 famosi dell\u2019odissea di Omero, quando Ulisse incontra Polifemo. In seguito, anche Aristotele e Plinio esaltano il gusto unico di questo formaggio. In particolare, proprio Plinio, nella sua opera \u201cNaturalis Historia\u201d, redige una carta dei formaggi nella quale vengono citati, tra i migliori pecorini,quelli provenienti da Agrigento. Fra le caratteristiche peculiari del Pecorino Siciliano DOP vanno annoverati il sapore leggermente piccante e l\u2019incantevole profumo di pascolo. Il Pecorino Siciliano DOP \ue8 un formaggio a pasta dura, semicotto, prodotto con latte intero crudo di pecora. L\u2019areale di produzione si estende su tutta la regione Sicilia. La forma \ue8 cilindrica a facce piane o lievemente concave, pesa dai 4 ai 12 kg, lo scalzo \ue8 di 10-18 cm. La crosta \ue8 bianca-giallognola,con la superficie rugosa per la modellatura lasciata dal canestro in giunco dove avviene la formatura, spesso viene cappata con olio. La pasta \ue8 compatta, di colore bianco o giallo paglierino, con occhiatura scarsa. Il sapore \ue8 piccante e caratteristico, l\u2019aroma \ue8 intenso. La stagionatura minima prevista dal disciplinare \ue8 di 4 mesi. Il Pecorino Siciliano ha acquisito la certificazione DO nel 1955 e la DOP nel 1996 con regolamento CE n. 1107/96 della Commissione del 12 giugno 1996 (Gazzetta Ufficiale Comunit\ue0 Europea L 148 del 21/6/1996). Attualmente, le attivit\ue0 di promozione, valorizzazione e vigilanza sono affidate al Consorzio di tutela del Pecorino Siciliano DOP, che \ue8 stato riconosciuto dal ministero delle Politiche agricole, alimentari e forestali (Mi- Paaf) dal 2005 a oggi. L\u2019elevata eterogeneit\ue0 del prodotto osservata nelle forme presenti sul mercato \ue8 dovuta sia ai metodi di produzione artigianali sia al vecchissimo disciplinare di produzione, risalente al 1956. Ci\uf2 ha indotto il consorzio di tutela a intraprendere una proficua collaborazione tecnico-scientifica con l\u2019Universit\ue0 degli Studi di Palermo prima e l\u2019Istituto Zooprofilattico Sperimentale della Sicilia, il Corfilac e l\u2019Universit\ue0 di Catania successivamente, con l\u2019obiettivo di migliorare la qualit\ue0 igienico-sanitaria del formaggio Pecorino Siciliano DOP e ridurre l\u2019eccessiva variabilit\ue0 qualitativa fra le forme ottenute da differenti caseificazioni

Subcutaneous emphysema, pneumomediastinum and pneumoperitoneum after diagnostic colonoscopy for ulcerative colitis: A rare but possible complication in patients with multiple risk factors

LETTER TO EDITO

THE MOSAIC OF THE FRIGIDARIUM OF “VILLA BONANNO” IN PALERMO: MINERALOGICAL AND PETROGRAPHIC ANALYSES FOR IN SITU CONSERVATION AND RESTORATION INTERVENTIONS

The topic of this study was the mineralogical and petrographic characterization of bedding mortars (made of different layers) and tesserae of Roman age (3rd century A.D.), taken from the mosaic of the Frigidarium of “Villa Bonanno”, brought to light by archaeological excavations conducted in the historical centre of Palermo. The collected samples have been analysed by thin-section optical microscopy (PLM), and scanning electron microscopy coupled with energy dispersive spectrometry (SEM-EDS). The study was aimed to define the “recipe” (composition of aggregate and binder, aggregate size distribution, aggregate/binder ratio), in order to assess the provenance of raw materials (supply site/area) and to acquire useful information in order to formulate "restoration mortars" that should be most comparable with the original ones, for replacements and/or integration. Rock types constituting the coloured tesserae were also characterized by thin-section optical microscopy. The mineralogical and petrographic investigations allowed establishing two different recipes used for the formulation of the studied mortars in terms of both compositional and textural features. The aggregate is composed by diverse proportions of detritic calcareous granules (both bioclasts and limestone fragments deriving from the local outcropping biocalcarenites and limestones), siliceous sand (monocrystalline quartz, chert and quartzarenite fragments), volcanic ash (pozzolana) and sometimes cocciopesto. The resulting hydraulic binder was the product of the „pozzolanic reaction‟ between volcanic ash and the aerial lime (specifically made by the calcination of locally available magnesian limestone or dolostone). The coloured tesserae can be all classified as compact limestones of Mesozoic or Cenozoic age, likely of local provenance

A Comparison of Deep Learning Techniques for Arterial Blood Pressure Prediction

Continuous vital signal monitoring is becoming more relevant in preventing diseases that afflict a large part of the world’s population; for this reason, healthcare equipment should be easy to wear and simple to use. Non-intrusive and non-invasive detection methods are a basic requirement for wearable medical devices, especially when these are used in sports applications or by the elderly for self-monitoring. Arterial blood pressure (ABP) is an essential physiological parameter for health monitoring. Most blood pressure measurement devices determine the systolic and diastolic arterial blood pressure through the inflation and the deflation of a cuff. This technique is uncomfortable for the user and may result in anxiety, and consequently affect the blood pressure and its measurement. The purpose of this paper is the continuous measurement of the ABP through a cuffless, non-intrusive approach. The approach of this paper is based on deep learning techniques where several neural networks are used to infer ABP, starting from photoplethysmogram (PPG) and electrocardiogram (ECG) signals. The ABP was predicted first by utilizing only PPG and then by using both PPG and ECG. Convolutional neural networks (ResNet and WaveNet) and recurrent neural networks (LSTM) were compared and analyzed for the regression task. Results show that the use of the ECG has resulted in improved performance for every proposed configuration. The best performing configuration was obtained with a ResNet followed by three LSTM layers: this led to a mean absolute error (MAE) of 4.118 mmHg on and 2.228 mmHg on systolic and diastolic blood pressures, respectively. The results comply with the American National Standards of the Association for the Advancement of Medical Instrumentation. ECG, PPG, and ABP measurements were extracted from the MIMIC database, which contains clinical signal data reflecting real measurements. The results were validated on a custom dataset created at Neuronica Lab, Politecnico di Torino

Understanding Neurosurgery Through Experimental and Computer Models

Endovascular neurosurgery is an evolving field, with the goal of treating neurological disease with minimal invasion of the body. The current approach is to deliver focused therapies via catheters traveling through the vascular tree. Refinement and advancement of these techniques requires not just new ideas, but new ideas that hold up when tested through the scientific method. Before clinical trials can begin, ethics and law demand that the ideas are tested first under experimental models. One benefit of these pre-clinical tests is the early identification of side effects. Another is the opportunity to practice and polish surgical technique in advance of human surgery. Historically, the best models of human systems have been similar systems in appropriate animals. Like human care, animal use is governed by strict laws and regulations. Violating these rules can not only result in criminal penalties, they can also make the research worthless: an animal poorly cared for may have physical symptoms that mask or confound the response to treatment. As computing power has increased, mathematical models have become more popular. The advantages of computational models include relative costs and relative speed. No animals, drugs or equipment have to be purchased, just a computer and software. The disadvantage is that the computational model can only represent those aspects of the modeled system that are understood and quantifiable. This article is an overview of how both animal and computational models have been used to approximate neurovascular conditions by researchers seeking to explore treatment options