Revisione critica dei risultati e nuovi algoritmi decisionali sulla chirurgia dell'OSAS

Obstructive sleep apnoea/hypopnoea syndrome (OSAHS) is the periodic reduction or cessation of airflow during sleep. The syndrome is associated whit loud snoring, disrupted sleep and observed apnoeas. Surgery aims to alleviate symptoms of daytime sleepiness, improve quality of life and reduce the signs of sleep apnoea recordered by polysomnography. Surgical intervention for snoring and OSAHS includes several procedures, each designed to increase the patency of the upper airway. Procedures addressing nasal obstruction include septoplasty, turbinectomy, and radiofrequency ablation (RF) of the turbinates. Surgical procedures to reduce soft palate redundancy include uvulopalatopharyngoplasty with or without tonsillectomy, uvulopalatal flap, laser-assisted uvulopalatoplasty, and RF of the soft palate. More significant, however, particularly in cases of severe OSA, is hypopharyngeal or retrolingual obstruction related to an enlarged tongue, or more commonly due to maxillomandibular deficiency. Surgeries in these cases are aimed at reducing the bulk of the tongue base or providing more space for the tongue in the oropharynx so as to limit posterior collapse during sleep. These procedures include tongue-base suspension, genioglossal advancement, hyoid suspension, lingualplasty, and maxillomandibular advancement. We reviewed 269 patients undergoing to osas surgery at the ENT Department of Forlì Hospital in the last decade. Surgery was considered a success if the postoperative apnea/hypopnea index (AHI) was less than 20/h. According to the results, we have developed surgical decisional algorithms with the aims to optimize the success of these procedures by identifying proper candidates for surgery and the most appropriate surgical techniques. Although not without risks and not as predictable as positive airway pressure therapy, surgery remains an important treatment option for patients with obstructive sleep apnea (OSA), particularly for those who have failed or cannot tolerate positive airway pressure therapy. Successful surgery depends on proper patient selection, proper procedure selection, and experience of the surgeon. The intended purpose of medical algorithms is to improve and standardize decisions made in the delivery of medical care, assist in standardizing selection and application of treatment regimens, to reduce potential introduction of errors. Nasal Continuous Positive Airway Pressure (nCPAP) is the recommended therapy for patients with moderate to severe OSAS. Unfortunately this treatment is not accepted by some patient, appears to be poorly tolerated in a not neglible number of subjects, and the compliance may be critical, especially in the long term if correctly evaluated with interview as well with CPAP smart cards analysis. Among the alternative options in Literature, surgery is a long time honoured solution. However until now no clear scientific evidence exists that surgery can be considered a really effective option in OSAHS management. We have design a randomized prospective study comparing MMA and a ventilatory device (Autotitrating Positive Airways Pressure – APAP) in order to understand the real effectiveness of surgery in the management of moderate to severe OSAS. Fifty consecutive previously full informed patients suffering from severe OSAHS were enrolled and randomised into a conservative (APAP) or surgical (MMA) arm. Demographic, biometric, PSG and ESS profiles of the two group were statistically not significantly different. One year after surgery or continuous APAP treatment both groups showed a remarkable improvement of mean AHI and ESS; the degree of improvement was not statistically different. Provided the relatively small sample of studied subjects and the relatively short time of follow up, MMA proved to be in our adult and severe OSAHS patients group a valuable alternative therapeutical tool with a success rate not inferior to APAP.

Fingerprint Recognition: Enhancement, Feature Extraction and Automatic Evaluation of Algorithms

The identification of people by measuring some traits of individual anatomy or physiology has led to a specific research area called biometric recognition. This thesis is focused on improving fingerprint recognition systems considering three important problems: fingerprint enhancement, fingerprint orientation extraction and automatic evaluation of fingerprint algorithms. An effective extraction of salient fingerprint features depends on the quality of the input fingerprint. If the fingerprint is very noisy, we are not able to detect a reliable set of features. A new fingerprint enhancement method, which is both iterative and contextual, is proposed. This approach detects high-quality regions in fingerprints, selectively applies contextual filtering and iteratively expands like wildfire toward low-quality ones. A precise estimation of the orientation field would greatly simplify the estimation of other fingerprint features (singular points, minutiae) and improve the performance of a fingerprint recognition system. The fingerprint orientation extraction is improved following two directions. First, after the introduction of a new taxonomy of fingerprint orientation extraction methods, several variants of baseline methods are implemented and, pointing out the role of pre- and post- processing, we show how to improve the extraction. Second, the introduction of a new hybrid orientation extraction method, which follows an adaptive scheme, allows to improve significantly the orientation extraction in noisy fingerprints. Scientific papers typically propose recognition systems that integrate many modules and therefore an automatic evaluation of fingerprint algorithms is needed to isolate the contributions that determine an actual progress in the state-of-the-art. The lack of a publicly available framework to compare fingerprint orientation extraction algorithms, motivates the introduction of a new benchmark area called FOE (including fingerprints and manually-marked orientation ground-truth) along with fingerprint matching benchmarks in the FVC-onGoing framework. The success of such framework is discussed by providing relevant statistics: more than 1450 algorithms submitted and two international competitions.

Carbon fluxes and allocation pattern in an apple orchard

Carbon fluxes and allocation pattern, and their relationship with the main environmental and physiological parameters, were studied in an apple orchard for one year (2010). I combined three widely used methods: eddy covariance, soil respiration and biometric measurements, and I applied a measurement protocol allowing a cross-check between C fluxes estimated using different methods. I attributed NPP components to standing biomass increment, detritus cycle and lateral export. The influence of environmental and physiological parameters on NEE, GPP and Reco was analyzed with a multiple regression model approach. I found that both NEP and GPP of the apple orchard were of similar magnitude to those of forests growing in similar climate conditions, while large differences occurred in the allocation pattern and in the fate of produced biomass. Apple production accounted for 49% of annual NPP, organic material (leaves, fine root litter, pruned wood and early fruit drop) contributing to detritus cycle was 46%, and only 5% went to standing biomass increment. The carbon use efficiency (CUE), with an annual average of 0.68 ± 0.10, was higher than the previously suggested constant values of 0.47-0.50. Light and leaf area index had the strongest influence on both NEE and GPP. On a diurnal basis, NEE and GPP reached their peak approximately at noon, while they appeared to be limited by high values of VPD and air temperature in the afternoon. The proposed models can be used to explain and simulate current relations between carbon fluxes and environmental parameters at daily and yearly time scale. On average, the annual NEP balanced the carbon annually exported with the harvested apples. These data support the hypothesis of a minimal or null impact of the apple orchard ecosystem on net C emission to the atmosphere.

Autenticazione d’origine, stima della Freshness quality e studio del profilo nutrizionale come elementi fondanti per la valorizzazione dell’alimento ittico

Questa tesi è dedicata alla qualità dell'alimento ittico in tre delle sue possibili accezioni. Dopo aver spiegato il complicato rapporto del consumatore con gli alimenti ittici e come l'Unione Europea abbia cercato di fare chiarezza al riguardo, gli argomenti di discussione saranno: Autenticazione d'origine La polpa di 160 esemplari di spigola (Dicentrachus labrax), suddivisi tra selvatici, allevati intensivamente e allevati estensivamente, provenienti dall'Italia e dall'estero per un totale di 18 fonti indagate, è stati analizzata individualmente per caratterizzarne la componente lipidica, isotopica e minerale e verificare le potenzialità di queste informazioni ai fini della autenticazione di origine in senso lato. Stima della Freshness Quality Numerosi lotti di seppia (Sepia officinalis), nasello (Merluccius merluccius) e triglia di fango (Mullus barbatus) sono stati sottoposti a due possibili modalità di stoccaggio sotto ghiaccio fondente, per indagare come, nell’arco della loro vita commerciale, ne evolvessero importanti connotati chimici (cataboliti dell’ATP e loro rapporti), fisici (proprietà dielettriche dei tessuti) e sensoriali (Quality Index Methods specie-specifici. Studio del profilo nutrizionale La componente lipidica di numerosi lotti di mazzancolla (Penaeus kerathurus), canocchia (Squilla mantis) e seppia (Sepia officinalis) è stata caratterizzata allo stato crudo e dopo cottura secondo tecniche “dedicate” per stabilire il contributo di queste matrici come fonte di acidi grassi polinsaturi della serie omega 3 e per pervenire alla determinazione dei loro coefficienti di ritenzione vera.

Application Platforms for the Internet of Things: Theory, Architecture, Protocols, Data Formats, and Privacy

The Internet of Things (IoT) is the next industrial revolution: we will interact naturally with real and virtual devices as a key part of our daily life. This technology shift is expected to be greater than the Web and Mobile combined. As extremely different technologies are needed to build connected devices, the Internet of Things field is a junction between electronics, telecommunications and software engineering. Internet of Things application development happens in silos, often using proprietary and closed communication protocols. There is the common belief that only if we can solve the interoperability problem we can have a real Internet of Things. After a deep analysis of the IoT protocols, we identified a set of primitives for IoT applications. We argue that each IoT protocol can be expressed in term of those primitives, thus solving the interoperability problem at the application protocol level. Moreover, the primitives are network and transport independent and make no assumption in that regard. This dissertation presents our implementation of an IoT platform: the Ponte project. Privacy issues follows the rise of the Internet of Things: it is clear that the IoT must ensure resilience to attacks, data authentication, access control and client privacy. We argue that it is not possible to solve the privacy issue without solving the interoperability problem: enforcing privacy rules implies the need to limit and filter the data delivery process. However, filtering data require knowledge of how the format and the semantics of the data: after an analysis of the possible data formats and representations for the IoT, we identify JSON-LD and the Semantic Web as the best solution for IoT applications. Then, this dissertation present our approach to increase the throughput of filtering semantic data by a factor of ten.

Advanced Techniques for Face Recognition under Challenging Environments

Automatically recognizing faces captured under uncontrolled environments has always been a challenging topic in the past decades. In this work, we investigate cohort score normalization that has been widely used in biometric verification as means to improve the robustness of face recognition under challenging environments. In particular, we introduce cohort score normalization into undersampled face recognition problem. Further, we develop an effective cohort normalization method specifically for the unconstrained face pair matching problem. Extensive experiments conducted on several well known face databases demonstrate the effectiveness of cohort normalization on these challenging scenarios. In addition, to give a proper understanding of cohort behavior, we study the impact of the number and quality of cohort samples on the normalization performance. The experimental results show that bigger cohort set size gives more stable and often better results to a point before the performance saturates. And cohort samples with different quality indeed produce different cohort normalization performance. Recognizing faces gone after alterations is another challenging problem for current face recognition algorithms. Face image alterations can be roughly classified into two categories: unintentional (e.g., geometrics transformations introduced by the acquisition devide) and intentional alterations (e.g., plastic surgery). We study the impact of these alterations on face recognition accuracy. Our results show that state-of-the-art algorithms are able to overcome limited digital alterations but are sensitive to more relevant modifications. Further, we develop two useful descriptors for detecting those alterations which can significantly affect the recognition performance. In the end, we propose to use the Structural Similarity (SSIM) quality map to detect and model variations due to plastic surgeries. Extensive experiments conducted on a plastic surgery face database demonstrate the potential of SSIM map for matching face images after surgeries.

Stress abiotici e trattamenti ultra-diluiti: effetti fisiologici e molecolari sulla crescita in vitro di frumento

Gli stress abiotici determinando modificazioni a livello fisiologico, biochimico e molecolare delle piante, costituiscono una delle principali limitazioni per la produzione agricola mondiale. Nel 2007 la FAO ha stimato come solamente il 3,5% della superficie mondiale non sia sottoposta a stress abiotici. Il modello agro-industriale degli ultimi cinquant'anni, oltre ad avere contribuito allo sviluppo economico dell'Europa, è stato anche causa di inquinamento di acqua, aria e suolo, mediante uno sfruttamento indiscriminato delle risorse naturali. L'arsenico in particolare, naturalmente presente nell'ambiente e rilasciato dalle attività antropiche, desta particolare preoccupazione a causa dell'ampia distribuzione come contaminante ambientale e per gli effetti di fitotossicità provocati. In tale contesto, la diffusione di sistemi agricoli a basso impatto rappresenta una importante risorsa per rispondere all'emergenza del cambiamento climatico che negli anni a venire sottoporrà una superficie agricola sempre maggiore a stress di natura abiotica. Nello studio condotto è stato utilizzato uno stabile modello di crescita in vitro per valutare l'efficacia di preparati ultra diluiti (PUD), che non contenendo molecole chimiche di sintesi ben si adattano a sistemi agricoli sostenibili, su semi di frumento preventivamente sottoposti a stress sub-letale da arsenico. Sono state quindi condotte valutazioni sia a livello morfometrico (germinazione, lunghezza di germogli e radici) che molecolare (espressione genica valutata mediante analisi microarray, con validazione tramite Real-Time PCR) arricchendo la letteratura esistente di interessanti risultati. In particolare è stato osservato come lo stress da arsenico, determini una minore vigoria di coleptile e radici e a livello molecolare induca l'attivazione di pathways metabolici per proteggere e difendere le cellule vegetali dai danni derivanti dallo stress; mentre il PUD in esame (As 45x), nel sistema stressato ha indotto un recupero nella vigoria di germoglio e radici e livelli di espressione genica simili a quelli riscontrati nel controllo suggerendo un effetto "riequilibrante" del metabolismo vegetale.