Effetto di olio essenziale di Satureja Montana ed estratto di Cotinus coggygria sulle curve di morte termica di Listeria monocytogenes e Saccharomyces cerevisiae

Negli ultimi anni, è aumentato notevolmente l'interesse per piante e prodotti vegetali, e composti da essi derivati od estratti, in alternativa ai conservanti chimici per prevenire o ritardare lo sviluppo microbico negli alimenti. Questo deriva dalla percezione negativa, ormai diffusa a livello pubblico, nei confronti di sostanze di sintesi che sono ampiamente utilizzate come conservanti nell’industria alimentare. Sono stati effettuati diversi studi sull’attività antimicrobica di questi composti negli alimenti, anche se il loro utilizzo a livello industriale è limitato. Ciò dipende dalla difficile standardizzazione di queste sostanze, dovuta alla variabilità della matrice alimentare che ne può alterarne l’attività antimicrobica. In questa sperimentazione si sono utilizzati l’olio essenziale di Sateureja montana e l’estratto di Cotinus coggygria e sono state fatte delle prove preliminari, determinandone le componenti volatili tramite gas-cromatografia abbinata a microestrazione in fase solida. Sono stati selezionati un ceppo di Listeria monocytogenes (Scott A) e uno di Saccharomyces cerevisiae (SPA), e sono stati utilizzati per realizzare curve di morte termica in sistema modello e in sistema reale. Dai risultati ottenuti si può affermare che Satureja montana e Cotinus coggygria possono essere presi in considerazione come antimicrobici naturali da impiegare per la stabilizzazione di alimenti, nonché per ridurre l’entità dei trattamenti termici atti a salvaguardare le proprietà nutrizionali ed organolettiche di alimenti, come ad esempio succhi di frutta, garantendone la sicurezza e qualità microbiologica.

Dynamic Workload Parallelization and System Calibration on Single-Chip Cloud Computer

Many-core systems are emerging from the need of more computational power and power efficiency. However there are many issues which still revolve around the many-core systems. These systems need specialized software before they can be fully utilized and the hardware itself may differ from the conventional computational systems. To gain efficiency from many-core system, programs need to be parallelized. In many-core systems the cores are small and less powerful than cores used in traditional computing, so running a conventional program is not an efficient option. Also in Network-on-Chip based processors the network might get congested and the cores might work at different speeds. In this thesis is, a dynamic load balancing method is proposed and tested on Intel 48-core Single-Chip Cloud Computer by parallelizing a fault simulator. The maximum speedup is difficult to obtain due to severe bottlenecks in the system. In order to exploit all the available parallelism of the Single-Chip Cloud Computer, a runtime approach capable of dynamically balancing the load during the fault simulation process is used. The proposed dynamic fault simulation approach on the Single-Chip Cloud Computer shows up to 45X speedup compared to a serial fault simulation approach. Many-core systems can draw enormous amounts of power, and if this power is not controlled properly, the system might get damaged. One way to manage power is to set power budget for the system. But if this power is drawn by just few cores of the many, these few cores get extremely hot and might get damaged. Due to increase in power density multiple thermal sensors are deployed on the chip area to provide realtime temperature feedback for thermal management techniques. Thermal sensor accuracy is extremely prone to intra-die process variation and aging phenomena. These factors lead to a situation where thermal sensor values drift from the nominal values. This necessitates efficient calibration techniques to be applied before the sensor values are used. In addition, in modern many-core systems cores have support for dynamic voltage and frequency scaling. Thermal sensors located on cores are sensitive to the core's current voltage level, meaning that dedicated calibration is needed for each voltage level. In this thesis a general-purpose software-based auto-calibration approach is also proposed for thermal sensors to calibrate thermal sensors on different range of voltages.

Minimally invasive video-assisted thyroid surgery: how can we improve the learning curve?

Objective. Minimally invasive video-assisted thyroidectomy (MIVAT) is a technically demanding procedure and requires a surgical team skilled in both endocrine and endoscopic surgery. A time consuming learning and training period is mandatory at the beginning of the experience. The aim of our report is to focus some aspects of the learning curve of the surgeon who practices video-assisted thyroid procedures for the first time, through the analysis of our preliminary series of 36 cases. Patients and methods. From September 2004 to April 2005 we selected 36 patients for minimally invasive video-assisted surgery of the thyroid. The patients were considered eligible if they presented with a nodule not exceeding 35mm in maximum diameter; total thyroid volume within normal range; absence of biochemical and echographic signs of thyroiditis. We analyzed surgical results, conversion rate, operating time, post-operative complications, hospital stay, cosmetic outcome of the series. Results. We performed 36 total thyroidectomy. The procedure was successfully carried out in 33/36 cases. Post-operative complications included 3 transient recurrent nerve palsies and 2 transient hypocalcemias; no definitive hypoparathyroidism was registered. All patients were discharged 2 days after operation. The cosmetic result was considered excellent by most patients. Conclusions. Advances in skills and technology have enabled surgeons to reproduce most open surgical techniques with video-assistance or laparoscopically. Training is essential to acquire any new surgical technique and it should be organized in detail to exploit it completely.

A methodology for building energy modelling and calibration in warm climates

PEDRINI, Aldomar; WESTPHAL, F. S.; LAMBERT, R.. A methodology for building energy modelling and calibration in warm climates. Building And Environment, Australia, n. 37, p.903-912, 2002. Disponível em: . Acesso em: 04 out. 2010.