Sleep disorders in Multiple System Atrophy: a longitudinal study

Introduction: A higher frequency of sleep and breathing disorders in Multiple System Atrophy (MSA) populations is documented in literature. The analysis of disease progression and prognosis in patients with sleep and breathing disorders could shed light on specific neuropathology and pathophysiology of MSA. Objective: To characterize sleep disorders and their longitudinal modifications during disease course in MSA patients, and to determine their prognostic value. Methods: This is a retrospective and prospective cohort study including 182 MSA patients (58.8% males). Type of onset was defined by the first reported motor or autonomic symptom/sign related to MSA. The occurrence of symptoms/signs and milestones of disease progression and their latency were collected. REM sleep behaviour disorder (RBD) and stridor were video-polysomnography (VPSG)-confirmed. VPSG recordings were analysed in a standardized fashion during the disease course. Survival data were based on time to death from the first symptom of disease. Results: Isolated RBD represented the first MSA symptom in 30% of patients, preceding disease onset according to international criteria with a median of 3(1–5) years. Patients developing early stridor or presenting with RBD at disease onset showed a more rapid and severe disease progression. These features had independent negative prognostic value for survival. Sleep architecture was characterized by peculiar features which could represent negative markers in MSA prognosis. Patients with stridor treated with tracheostomy showed a reduced risk of death. Conclusions: This is one of the first studies focusing on longitudinal progression of sleep in MSA. Sleep disorders are key features of disease, playing a role in presentation, prognosis and progression. In our MSA cohort, RBD represented the most frequent mode of disease presentation. Moreover, some specific clinical and instrumental sleep features could represent a hallmark of MSA and could be involved in prognosis and, in particular, in sudden death and death during sleep.

Design and Development of Network Monitoring Strategies in P4-enabled Programmable Switches

Network monitoring is of paramount importance for effective network management: it allows to constantly observe the network’s behavior to ensure it is working as intended and can trigger both automated and manual remediation procedures in case of failures and anomalies. The concept of SDN decouples the control logic from legacy network infrastructure to perform centralized control on multiple switches in the network, and in this context, the responsibility of switches is only to forward packets according to the flow control instructions provided by controller. However, as current SDN switches only expose simple per-port and per-flow counters, the controller has to do almost all the processing to determine the network state, which causes significant communication overhead and excessive latency for monitoring purposes. The absence of programmability in the data plane of SDN prompted the advent of programmable switches, which allow developers to customize the data-plane pipeline and implement novel programs operating directly in the switches. This means that we can offload certain monitoring tasks to programmable data planes, to perform fine-grained monitoring even at very high packet processing speeds. Given the central importance of network monitoring exploiting programmable data planes, the goal of this thesis is to enable a wide range of monitoring tasks in programmable switches, with a specific focus on the ones equipped with programmable ASICs. Indeed, most network monitoring solutions available in literature do not take computational and memory constraints of programmable switches into due account, preventing, de facto, their successful implementation in commodity switches. This claims that network monitoring tasks can be executed in programmable switches. Our evaluations show that the contributions in this thesis could be used by network administrators as well as network security engineers, to better understand the network status depending on different monitoring metrics, and thus prevent network infrastructure and service outages.

Determinazione gascromatografica di composti organici volatili e semi-volatili (VOCs e SVOCs) in poliolefine ed effetti delle condizioni di lavorazione

A relevant problem of polyolefins processing is the presence of volatile and semi-volatile compounds (VOCs and SVOCs) such as linear chains alkanes found out in final products. These VOCs can be detected by customers from the unpleasant smelt and can be an environmental issue, at the same time they can cause negative side effects during process. Since no previously standardized analytical techniques for polymeric matrix are available in bibliography, we have implemented different VOCs extraction methods and gaschromatographic analysis for quali-quantitative studies of such compounds. In literature different procedures can be found including microwave extraction (MAE) and thermo desorption (TDS) used with different purposes. TDS coupled with GC-MS are necessary for the identification of different compounds in the polymer matrix. Although the quantitative determination is complex, the results obtained from TDS/GC-MS show that by-products are mainly linear chains oligomers with even number of carbon in a C8-C22 range (for HDPE). In order to quantify these linear alkanes by-products, a more accurate GC-FID determination with internal standard has been run on MAE extracts. Regardless the type of extruder used, it is difficult to distinguish the effect of the various processes, which in any case entails having a lower-boiling substance content, lower than the corresponding virgin polymer. The two HDPEs studied can be distinguished on the basis of the quantity of analytes found, therefore the production process is mainly responsible for the amount of VOCs and SVOCs observed. The extruder technology used by Sacmi SC allows to obtain a significant reduction in VOCs compared to the conventional screw system. Thus, the result is significantly important as a lower quantity of volatile substances certainly leads to a lower migration of such materials, especially when used for food packaging.

Study on health status and remediation potential of Phragmites australis employed in an Emilia Romagna (IT) Constructed Wetland to assess zonal variability of the facility.

Phragmites australis (Cav.) Trin. ex Steud. is a hydrophyte particularly resistant to harsh conditions, e.g. drought, high salinity, contaminants, such as heavy metals and toxic molecules, and high nutrients concentrations. These resistances render the plant suitable for water depuration, where its particular metabolism is exploited to remove pollutants and excessive nutrients from the environment. In constructed wetlands, this principle is applied to phyto-purify wastewater with various origins, such as industrial, agricultural and household, with the aim to improve its quality to an extent which would render its reuse possible. In the framework of a pre-existing project of Department of Agricultural and Food Sciences (DiSTAl), this work integrates the knowledge and data relative to an Emilia Romagna (IT) constructed wetland plant, in order to expand the knowledge about this particular facility and of the system in general. By assaying antioxidants, both non- enzymatic and enzymatic, chlorophylls content and net photosynthetic rates, and by measuring the elemental composition of the specimens, the health status and the elemental uptake of the wetland plants sampled in different areas were investigated. The results were compared amongst the examined specimens with the aim to detect areas where there may be a higher stress due to a different wastewater composition, potentially varying along the constructed route. In addition, different parameters regarding the extraction and assay protocols were investigated, in order to optimise the procedure and to select the best conditions to perform the analyses, as well as to integrate information missing in literature or found as contradictory.

Automatic detection of the inferior alveolar nerve in CT scans with CenterNet

The inferior alveolar nerve (IAN) lies within the mandibular canal, named inferior alveolar canal in literature. The detection of this nerve is important during maxillofacial surgeries or for creating dental implants. The poor quality of cone-beam computed tomography (CBCT) and computed tomography (CT) scans and/or bone gaps within the mandible increase the difficulty of this task, posing a challenge to human experts who are going to manually detect it and resulting in a time-consuming task.Therefore this thesis investigates two methods to automatically detect the IAN: a non-data driven technique and a deep-learning method. The latter tracks the IAN position at each frame leveraging detections obtained with the deep neural network CenterNet, fined-tuned for our task, and temporal and spatial information.

A 3D biomimetic in vitro model: a novel strategy to investigate glioma biology

Gliomas are one of the most frequent primary malignant brain tumors. Acquisition of stem-like features likely contributes to the malignant nature of high-grade gliomas and may be responsible for the initiation, growth, and recurrence of these tumors. In this regard, although the traditional 2D cell culture system has been widely used in cancer research, it shows limitations in maintaining the stemness properties of cancer and in mimicking the in vivo microenvironment. In order to overcome these limitations, different three-dimensional (3D) culture systems have been developed to mimic better the tumor microenvironment. Cancer cells cultured in 3D structures may represent a more reliable in vitro model due to increased cell-cell and cell-extracellular matrix (ECM) interaction. Several attempts to recreate brain cancer tissue in vitro are described in literature. However, to date, it is still unclear which main characteristics the ideal model should reproduce. The overall goal of this project was the development of a 3D in vitro model able to reproduce the brain ECM microenvironment and to recapitulate pathological condition for the study of tumor stroma interactions, tumor invasion ability, and molecular phenotype of glioma cells. We performed an in silico bioinformatic analysis using GEPIA2 Software to compare the expression level of seven matrix protein in the LGG tumors with healthy tissues. Then, we carried out a FFPE retrospective study in order to evaluate the percentage of expression of selected proteins. Thus, we developed a 3D scaffold composed by Hyaluronic Acid and Collagen IV in a ratio of 50:50. We used two astrocytoma cell lines, HTB-12 and HTB-13. In conclusion, we developed an in vitro 3D model able to reproduce the composition of brain tumor ECM, demonstrating that it is a feasible platform to investigate the interaction between tumor cells and the matrix.

Fluorogenic hyaluronan-based probe: characterization and use in advanced microscopy

Among all, the application of nanomaterials in biomedical research and most recently in the environmental one has opened the fields of nanomedicine and nanoremediation. Sensing methods based on fluorescence optical probe are generally requested for their selectivity, sensitivity. However, most imaging methods in literature rely on a fluorescent covalent labelling of the system. Therefore, the main aim of this project was to synthetise a biocompatible fluorogenic hyaluronan probe (HA) polymer functionalised with a rhomadine B (RB) moieties and study its behaviour as an optical probe with different materials with microscopy techniques. A derivatization of HA with RB (HA-RB) was successfully obtained providing a photophysical characterization showing a particular fluorescence mechanism of the probe. Firstly, we tested the interaction with different lab-grade micro and nanoplastics in water. Thanks to the peculiar photophysical behaviour of the probe nanoplastics can be detected with confocal microscopy and more interestingly their nature can be discriminated based on the fluorescence lifetime decay with FLIM microscopy. After, the interaction of a model plant derived metabolic enzyme GAPC1 undergoing oxidative-triggered aggregation was explored with the HA-RB. We highlighted the probe interaction with the protein even at early stage of the kinetic. Moreover, nanoparticle tracking analysis (NTA) experiment demonstrates that the probe is in fact able to interact with the small pre-aggregates in the early stage of the aggregation kinetic. Ultimately, we focused on the possibility to apply the probe in a super resolution microscopy technique, PALM, exploiting its aspecific interaction to characterize the surface topography of PTFE polydisperse microplastics. Optimal conditions were reached at high concentration of the probe (70 nM) where 0.5-5 nM is always advisable for this technique. Thanks to the polymeric nature and fluorescence mechanism of the probe, this technique was able to reveal features of PTFE surface under the diffraction limit (< 250 nm).

Depth Estimation in Stereo Biomedical Images via Proxy-Supervised Deep Learning

In order to estimate depth through supervised deep learning-based stereo methods, it is necessary to have access to precise ground truth depth data. While the gathering of precise labels is commonly tackled by deploying depth sensors, this is not always a viable solution. For instance, in many applications in the biomedical domain, the choice of sensors capable of sensing depth at small distances with high precision on difficult surfaces (that present non-Lambertian properties) is very limited. It is therefore necessary to find alternative techniques to gather ground truth data without having to rely on external sensors. In this thesis, two different approaches have been tested to produce supervision data for biomedical images. The first aims to obtain input stereo image pairs and disparities through simulation in a virtual environment, while the second relies on a non-learned disparity estimation algorithm in order to produce noisy disparities, which are then filtered by means of hand-crafted confidence measures to create noisy labels for a subset of pixels. Among the two, the second approach, which is referred in literature as proxy-labeling, has shown the best results and has even outperformed the non-learned disparity estimation algorithm used for supervision.

Temperature measurements in turbulent pipe flow with cold wire anemometry

Passive scalars measurements in turbulent pipe flows are difficult to perform and only few experimental data are available in literature. The present thesis deals with the experimental acquisition and study of the first turbulent temperature profile inside the CICLoPE wind tunnel through cold wire anemometry technique at Reτ = 6000 and Reτ = 9500. This type of measurements provides not only useful data on temperature (and passive scalars) behaviour and statistics in turbulent pipe flows, but could be used also for temperature correction of turbulent velocity profiles. In the present work, subsequent acquisitions of temperature and velocity profiles has been performed at the same Reynolds number and in the same points, through cold wire and hot wire techniques respectively. Taking as reference data from both DNS and experimental campaigns, the activity has been carried out obtaining satisfactory results. We have verified the presence of turbulent temperature profile inside the CICLoPE wind tunnel and then studied its statistical and spectral behaviours obtaining results in agreement with existing data from Hishida, Nagano, and Ferro. Cold wire temperature data were then used to correct hot wire velocity data, obtaining a slightly improvement in the near wall region.

Uv-vis Spectra As An Alternative To The Lowry Method For Quantify Hair Damage Induced By Surfactants.

It is well known that long term use of shampoo causes damage to human hair. Although the Lowry method has been widely used to quantify hair damage, it is unsuitable to determine this in the presence of some surfactants and there is no other method proposed in literature. In this work, a different method is used to investigate and compare the hair damage induced by four types of surfactants (including three commercial-grade surfactants) and water. Hair samples were immersed in aqueous solution of surfactants under conditions that resemble a shower (38 °C, constant shaking). These solutions become colored with time of contact with hair and its UV-vis spectra were recorded. For comparison, the amount of extracted proteins from hair by sodium dodecyl sulfate (SDS) and by water were estimated by the Lowry method. Additionally, non-pigmented vs. pigmented hair and also sepia melanin were used to understand the washing solution color and their spectra. The results presented herein show that hair degradation is mostly caused by the extraction of proteins, cuticle fragments and melanin granules from hair fiber. It was found that the intensity of solution color varies with the charge density of the surfactants. Furthermore, the intensity of solution color can be correlated to the amount of proteins quantified by the Lowry method as well as to the degree of hair damage. UV-vis spectrum of hair washing solutions is a simple and straightforward method to quantify and compare hair damages induced by different commercial surfactants.

A Metabolomic Protocol For Plant Systematics By Matrix-assisted Laser-desorption/ionization Time-of Flight Mass Spectrometry.

Matrix-assisted laser desorption/ionization time-of flight mass spectrometry (MALDI-TOF MS) has been widely used for the identification and classification of microorganisms based on their proteomic fingerprints. However, the use of MALDI-TOF MS in plant research has been very limited. In the present study, a first protocol is proposed for metabolic fingerprinting by MALDI-TOF MS using three different MALDI matrices with subsequent multivariate data analysis by in-house algorithms implemented in the R environment for the taxonomic classification of plants from different genera, families and orders. By merging the data acquired with different matrices, different ionization modes and using careful algorithms and parameter selection, we demonstrate that a close taxonomic classification can be achieved based on plant metabolic fingerprints, with 92% similarity to the taxonomic classifications found in literature. The present work therefore highlights the great potential of applying MALDI-TOF MS for the taxonomic classification of plants and, furthermore, provides a preliminary foundation for future research.

Aerodinâmica de leitos vibrofluidizados: uma revisão

Application of mechanical vibration to aid fluidization and to improve heat, mass and momentum transfer are usual processes in agricultural industry and it has found nowadays extensive applications in particle processing of materials difficult-to-fluidized. Equations and experimental data found in literature for the aerodynamics characteristics of vibro-fluidized beds are presented and discussed, emphasizing the vibration effect in the bed.

Influência da temperatura do ar de secagem no calor latente de vaporização de água em feijão macassar (Vigna unguiculata (L.) Walp.), variedade sempre-verde

In order to determine the energy needed to artificially dry an agricultural product the latent heat of vaporization of moisture in the product, H, must be known. Generally, the expressions for H reported in the literature are of the form H = h(T)f(M), where h(T) is the latent heat of vaporization of free water, and f(M) is a function of the equilibrium moisture content, M, which is a simplification. In this article, a more general expression for the latent heat of vaporization, namely H = g(M,T), is used to determine H for cowpea, always-green variety. For this purpose, a computer program was developed which automatically fits about 500 functions, with one or two independent variables, imbedded in its library to experimental data. The program uses nonlinear regression, and classifies the best functions according to the least reduced chi-squared. A set of executed statistical tests shows that the generalized expression for H used in this work produces better results of H for cowpea than other equations found in literature.

Estimativa de parâmetros biofísicos de plantios de café a partir de imagens orbitais de alta resolução espacial

Remote sensing data are each time more available and can be used to monitor the vegetal development of main agricultural crops, such as the Arabic coffee in Brazil, since that the relationship between spectral and agronomical data be well known. Therefore, this work had the main objective to assess the use of Quickbird satellite images to estimate biophysical parameters of coffee crop. Test area was composed by 25 coffee fields located between the cities of Ribeirão Corrente, Franca and Cristais Paulista (SP), Brazil, and the biophysical parameters used were row and between plants spacing, plant height, LAI, canopy diameter, percentage of vegetation cover, roughness and biomass. Spectral data were the reflectance of four bands of QUICKBIRD and values of four vegetations indexes (NDVI, GVI, SAVI and RVI) based on the same satellite. All these data were analyzed using linear and nonlinear regression methods to generate estimation models of biophysical parameters. The use of regression models based on nonlinear equations was more appropriate to estimate parameters such as the LAI and the percentage of biomass, important to indicate the productivity of coffee crop.

Metodologia para analise cinematica de volumes respiratorios parciais de nadadores

Universidade Estadual de Campinas . Faculdade de Educação Física