5 resultados para Physical features iof Kerala

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Aims: Ripening evaluation of two different Pecorino cheese varieties ripened according either to a traditional method in plant and in cave. Different ripening features have been analyzed in order to evaluate the cave as possible ripening environment with the aim of obtaining a peculiar product which could also establish an added value to the cultural heritage of the local place in which it has been originally manufactured. Methods and Results: Chemical-physical features of Pecorino cheese have been initially analyzed into two different ripening environments and experimentations, among which: pH, weight reduction and subsequent water activity. Furthermore, the microbial composition has been characterized in relationship with the two different ripening environments, undertaking a variety of microbial groups, such as: lactic bacteria, staphylococci, yeasts, lactococci, enterobacteria, enterococci. Besides, an additional analysis for the in-cave adaptability evaluation has been the identification of biogenic amines inside the Pecorino cheese (2-phenilethylamine, putrescine, cadaverine, hystidine, tyramine, spermine and spermidine). Further analysis were undertaken in order to track the lipid profile evolution, reporting the concentration of the cheese free fatty acids in object, in relation with ripening time, environment and production. In order to analyse the flavour compounds present in Pecorino cheese, the SPME-GC-MS technique has been widely employed. As a result, it is confirmed the trend showed by the short-chain free fatty acids, that is to say the fatty acids which are mostly involved in conveying a stronger flavor to the cheese. With the purpose of assessing the protheolytic patterns of the above-mentioned Pecorino cheese in the two different ripening environments and testing methods, the technique SDS-PAGE has been employed into the cheese insoluble fraction, whereas the SDS-PAGE technique has been carried out into the cheese soluble portion. Furthermore, different isolated belonging to various microbial groups have been genotypically characterized though the ITS-PCR technique with the aim to identify the membership species. With reference to lactic bacillus the characterized species are: Lactobacillus brevis, Lactobacillus curvatus and Lactobacillus paraplantarum. With reference to lactococci the predominant species is Lactococcus lactis, coming from the employed starter used in the cheese manufacturing. With reference to enterococcus, the predominant species are Enterococcus faecium and Enterococcus faecalis. Moreover, Streptococcus termophilus and Streptococcus macedonicus have been identified too. For staphylococci the identified species are Staphyilococcus equorum, Staphylococcus saprophyfiticus and Staphylococcus xylosus. Finally, a sensorial analysis has been undertaken through on one side a consumer test made by inexperienced consumers, and on the other side through a panel test achieved by expert consumers. From such test Pecorino cheese ripened in cave were found to be more pleasant in comparison with Pecorino cheese ripened in plant. Conclusions: The proposed approach and the undertaken analysis showed the cave as preferential ripening environment for Pecorino cheese and for the development of a more palatable product and safer for consumers’ health.

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Lung ultrasound use is increasing in respiratory medicine thanks to its development in the latest years. Actually it allows to study diseases of the chest wall (traumas, infections, neoplasms), diaphragm (paralysis, ipokinesis), pleura (effusions, pneumothorax, thickenings, neoplasms) and lung parenchyma (consolidations, interstitial syndromes, peripheral lesions). One of the most useful application of chest ultrasound is the evaluation of effusions. However, no standardized approach for ultrasound-guided thoracenthesis is available. Our study showed that our usual ultrasonographic landmark (“V-point”) could be a standard site to perform thoracenthesis: in 45 thoracenthesis no pneumothorax occurred, drainage was always successful at first attempt. Values of maximum thickness at V-point and drained fluid volume showed a significative correlation. Proteins concentration of ultrasound patterns of effusions (anechoic, ipoechoic, moving echoic spots, dense moving spots, hyperechoic) were compared to those of the macroscopic features of fluids showing connection between light-yellow fluid and echoic moving spots pattern and between ipoechoic/dense moving spots and cloudy-yellow/serum-haematic fluids. These observations suggest that ultrasound could predict chemical-physical features of effusions. Lung ultrasound provides useful information about many disease of the lung, but actually there is not useful in obstructive bronchial diseases. Analysing diaphragmatic kinetics using M-mode through transhepatic scan we described a similarity between diaphragm excursion during an expiratory forced maneuver and the volume/time curve of spirometry. This allowed us to identify the M-mode Index of Obstruction (MIO), an ultrasound-analogue of FEV1/VC. We observed MIO values of normal subjects (9) and obstructed patients (9) comparing the two groups. FEV1/VC and MIO showed a significant correlation suggesting that MIO may be affected by airways obstruction; MIO values were significatively different between normal and obstructed so that it could identify an obstructive syndrome. The data show that it is possible to suspect the presence of obstructive syndrome of the airways using ultrasonography of the diaphragm.

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The aim of this thesis is to investigate the nature of quantum computation and the question of the quantum speed-up over classical computation by comparing two different quantum computational frameworks, the traditional quantum circuit model and the cluster-state quantum computer. After an introductory survey of the theoretical and epistemological questions concerning quantum computation, the first part of this thesis provides a presentation of cluster-state computation suitable for a philosophical audience. In spite of the computational equivalence between the two frameworks, their differences can be considered as structural. Entanglement is shown to play a fundamental role in both quantum circuits and cluster-state computers; this supports, from a new perspective, the argument that entanglement can reasonably explain the quantum speed-up over classical computation. However, quantum circuits and cluster-state computers diverge with regard to one of the explanations of quantum computation that actually accords a central role to entanglement, i.e. the Everett interpretation. It is argued that, while cluster-state quantum computation does not show an Everettian failure in accounting for the computational processes, it threatens that interpretation of being not-explanatory. This analysis presented here should be integrated in a more general work in order to include also further frameworks of quantum computation, e.g. topological quantum computation. However, what is revealed by this work is that the speed-up question does not capture all that is at stake: both quantum circuits and cluster-state computers achieve the speed-up, but the challenges that they posit go besides that specific question. Then, the existence of alternative equivalent quantum computational models suggests that the ultimate question should be moved from the speed-up to a sort of “representation theorem” for quantum computation, to be meant as the general goal of identifying the physical features underlying these alternative frameworks that allow for labelling those frameworks as “quantum computation”.

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Analog In-memory Computing (AIMC) has been proposed in the context of Beyond Von Neumann architectures as a valid strategy to reduce internal data transfers energy consumption and latency, and to improve compute efficiency. The aim of AIMC is to perform computations within the memory unit, typically leveraging the physical features of memory devices. Among resistive Non-volatile Memories (NVMs), Phase-change Memory (PCM) has become a promising technology due to its intrinsic capability to store multilevel data. Hence, PCM technology is currently investigated to enhance the possibilities and the applications of AIMC. This thesis aims at exploring the potential of new PCM-based architectures as in-memory computational accelerators. In a first step, a preliminar experimental characterization of PCM devices has been carried out in an AIMC perspective. PCM cells non-idealities, such as time-drift, noise, and non-linearity have been studied to develop a dedicated multilevel programming algorithm. Measurement-based simulations have been then employed to evaluate the feasibility of PCM-based operations in the fields of Deep Neural Networks (DNNs) and Structural Health Monitoring (SHM). Moreover, a first testchip has been designed and tested to evaluate the hardware implementation of Multiply-and-Accumulate (MAC) operations employing PCM cells. This prototype experimentally demonstrates the possibility to reach a 95% MAC accuracy with a circuit-level compensation of cells time drift and non-linearity. Finally, empirical circuit behavior models have been included in simulations to assess the use of this technology in specific DNN applications, and to enhance the potentiality of this innovative computation approach.

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Cancer research and development of targeting agents in this field is based on robust studies using preclinical models. The failure rate of standardized treatment approaches for several solid tumors has led to the urgent need to fine-tune more sophisticated and faithful preclinical models able to recapitulate the features of in vivo human tumors, with the final aim to shed light on new potential therapeutic targets. Epithelial Ovarian Cancer (EOC) serous histotype (HGSOC) is one of the most lethal diseases in women due to its high aggressiveness (75% of patients diagnosed at FIGO III-IV state) and poor prognosis (less of 50% in 5 years), whose therapy often fails as chemoresistance sets in. This thesis aimed at using the novel perfusion-based bioreactor U-CUP that provides direct perfusion throughout the tumor tissue seeking to obtain an EOC 3D ex vivo model able to recapitulate the features of the original tumor including the tumor microenvironment and maintaining its cellular heterogeneity. Moreover, we optimized this approach so that it can be successfully applied to slow-frozen tumoral tissues, further extending the usefulness of this tool. We also investigated the effectiveness of Plasma Activated Ringer’s Lactate solution (PA-RL) against Epithelial Ovarian Cancer (EOC) serous histotype in both 2D and 3D cultures using ex-vivo specimens from HGSOC patients. We propose PA-RL as a novel therapy with local intraperitoneal administration, which could act on primary or metastatic ovarian tumors inducing a specific cancer cell death with reduced damage on the surrounding healthy tissues.