861 resultados para advanced glycation end_products


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Over the years the Differential Quadrature (DQ) method has distinguished because of its high accuracy, straightforward implementation and general ap- plication to a variety of problems. There has been an increase in this topic by several researchers who experienced significant development in the last years. DQ is essentially a generalization of the popular Gaussian Quadrature (GQ) used for numerical integration functions. GQ approximates a finite in- tegral as a weighted sum of integrand values at selected points in a problem domain whereas DQ approximate the derivatives of a smooth function at a point as a weighted sum of function values at selected nodes. A direct appli- cation of this elegant methodology is to solve ordinary and partial differential equations. Furthermore in recent years the DQ formulation has been gener- alized in the weighting coefficients computations to let the approach to be more flexible and accurate. As a result it has been indicated as Generalized Differential Quadrature (GDQ) method. However the applicability of GDQ in its original form is still limited. It has been proven to fail for problems with strong material discontinuities as well as problems involving singularities and irregularities. On the other hand the very well-known Finite Element (FE) method could overcome these issues because it subdivides the computational domain into a certain number of elements in which the solution is calculated. Recently, some researchers have been studying a numerical technique which could use the advantages of the GDQ method and the advantages of FE method. This methodology has got different names among each research group, it will be indicated here as Generalized Differential Quadrature Finite Element Method (GDQFEM).

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Constant developments in the field of offshore wind energy have increased the range of water depths at which wind farms are planned to be installed. Therefore, in addition to monopile support structures suitable in shallow waters (up to 30 m), different types of support structures, able to withstand severe sea conditions at the greater water depths, have been developed. For water depths above 30 m, the jacket is one of the preferred support types. Jacket represents a lightweight support structure, which, in combination with complex nature of environmental loads, is prone to highly dynamic behavior. As a consequence, high stresses with great variability in time can be observed in all structural members. The highest concentration of stresses occurs in joints due to their nature (structural discontinuities) and due to the existence of notches along the welds present in the joints. This makes them the weakest elements of the jacket in terms of fatigue. In the numerical modeling of jackets for offshore wind turbines, a reduction of local stresses at the chord-brace joints, and consequently an optimization of the model, can be achieved by implementing joint flexibility in the chord-brace joints. Therefore, in this work, the influence of joint flexibility on the fatigue damage in chord-brace joints of a numerical jacket model, subjected to advanced load simulations, is studied.

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Advanced optical biosensor platforms exploiting long range surface plasmons (LRSPs) and responsive N-isopropylacrylamide (NIPAAm) hydrogel binding matrix for the detection of protein and bacterial pathogen analytes were carried out. LRSPs are optical waves that originate from coupling of surface plasmons on the opposite sites of a thin metallic film embedded between two dielectrics with similar refractive indices. LRSPs exhibit orders of magnitude lower damping and more extended profile of field compared to regular surface plasmons (SPs). Their excitation is accompanied with narrow resonance and provides stronger enhancement of electromagnetic field intensity that can advance the sensitivity of surface plasmon resonance (SPR) and surface plasmon-enhanced fluorescence spectroscopy (SPFS) biosensors. Firstly, we investigated thin gold layers deposited on fluoropolymer surface for the excitation of LRSPs. The study indicates that the morphological, optical and electrical properties of gold film can be changed by the surface energy of fluoropolymer and affect the performance of a SPFS biosensor. A photo-crosslinkable NIPAAm hydrogel was grafted to the sensor surface in order to serve as a binding matrix. It was modified with bio-recognition elements (BREs) via amine coupling chemistry and offered the advantage of large binding capacity, stimuli responsive properties and good biocompatibility. Through experimental observations supported by numerical simulations describing diffusion mass transfer and affinity binding of target molecules in the hydrogel, the hydrogel binding matrix thickness, concentration of BREs and the profile of the probing evanescent field was optimized. Hydrogel with a up to micrometer thickness was shown to support additional hydrogel optical waveguide (HOW) mode which was employed for probing affinity binding events in the gel by means of refractometric and fluorescence measurements. These schemes allow to reach limits of detection (LODs) at picomolar and femtomolar levels, respectively. Besides hydrogel based experiments for detection of molecular analytes, long range surface plasmon-enhanced fluorescence spectroscopy (LRSP-FS) was employed for detection of bacterial pathogens. The influence of capture efficiency of bacteria on surfaces and the profile of the probing field on sensor response were investigated. The potential of LRSP-FS with extended evanescent field is demonstrated for detection of pathogenic E. coli O157:H7 on sandwich immunoassays . LOD as low as 6 cfu mL-1 with a detection time of 40 minutes was achieved.rn

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In the present thesis, a new methodology of diagnosis based on advanced use of time-frequency technique analysis is presented. More precisely, a new fault index that allows tracking individual fault components in a single frequency band is defined. More in detail, a frequency sliding is applied to the signals being analyzed (currents, voltages, vibration signals), so that each single fault frequency component is shifted into a prefixed single frequency band. Then, the discrete Wavelet Transform is applied to the resulting signal to extract the fault signature in the frequency band that has been chosen. Once the state of the machine has been qualitatively diagnosed, a quantitative evaluation of the fault degree is necessary. For this purpose, a fault index based on the energy calculation of approximation and/or detail signals resulting from wavelet decomposition has been introduced to quantify the fault extend. The main advantages of the developed new method over existing Diagnosis techniques are the following: - Capability of monitoring the fault evolution continuously over time under any transient operating condition; - Speed/slip measurement or estimation is not required; - Higher accuracy in filtering frequency components around the fundamental in case of rotor faults; - Reduction in the likelihood of false indications by avoiding confusion with other fault harmonics (the contribution of the most relevant fault frequency components under speed-varying conditions are clamped in a single frequency band); - Low memory requirement due to low sampling frequency; - Reduction in the latency of time processing (no requirement of repeated sampling operation).

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The specific energy of lithium-ion batteries (LIBs) is today 200 Wh/kg, a value not sufficient to power fully electric vehicles with a driving range of 400 km which requires a battery pack of 90 kWh. To deliver such energy the battery weight should be higher than 400 kg and the corresponding increase of vehicle mass would narrow the driving range to 280 km. Two main strategies are pursued to improve the energy of the rechargeable lithium batteries up to the transportation targets. The first is the increase of LIBs working voltage by using high-voltage cathode materials. The second is the increase of battery capacity by the development of a cell chemistry where oxygen redox reaction (ORR) occurs at the cathode and metal lithium is the anode (Li/O2 battery). This PhD work is focused on the development of high-voltage safe cathodes for LIBs, and on the investigation of the feasibility of Li/O2 battery operating with ionic liquid(IL)-based electrolytes. The use of LiMn1-xFexPO4 as high-voltage cathode material is discussed. Synthesis and electrochemical tests of three different phosphates, more safe cathode materials than transition metal oxides, are reported. The feasibility of Li/O2 battery operating in IL-based electrolytes is also discussed. Three aspects have been investigated: basic aspects of ORR, synthesis and characterization of porous carbons as positive electrode materials and study of limiting factors to the electrode capacity and cycle-life. Regarding LIBs, the findings on LiMnPO4 prepared by soluble precursors demonstrate that a good performing Mn-based olivine is viable without the coexistence of iron. Regarding Li/O2 battery, the oxygen diffusion coefficient and concentration values in different ILs were obtained. This work highlighted that the O2 mass transport limits the Li/O2 capacity at high currents; it gave indications on how to increase battery capacity by using a flow-cell and a porous carbon as cathode.

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Several countries have acquired, over the past decades, large amounts of area covering Airborne Electromagnetic data. Contribution of airborne geophysics has dramatically increased for both groundwater resource mapping and management proving how those systems are appropriate for large-scale and efficient groundwater surveying. We start with processing and inversion of two AEM dataset from two different systems collected over the Spiritwood Valley Aquifer area, Manitoba, Canada respectively, the AeroTEM III (commissioned by the Geological Survey of Canada in 2010) and the “Full waveform VTEM” dataset, collected and tested over the same survey area, during the fall 2011. We demonstrate that in the presence of multiple datasets, either AEM and ground data, due processing, inversion, post-processing, data integration and data calibration is the proper approach capable of providing reliable and consistent resistivity models. Our approach can be of interest to many end users, ranging from Geological Surveys, Universities to Private Companies, which are often proprietary of large geophysical databases to be interpreted for geological and\or hydrogeological purposes. In this study we deeply investigate the role of integration of several complimentary types of geophysical data collected over the same survey area. We show that data integration can improve inversions, reduce ambiguity and deliver high resolution results. We further attempt to use the final, most reliable output resistivity models as a solid basis for building a knowledge-driven 3D geological voxel-based model. A voxel approach allows a quantitative understanding of the hydrogeological setting of the area, and it can be further used to estimate the aquifers volumes (i.e. potential amount of groundwater resources) as well as hydrogeological flow model prediction. In addition, we investigated the impact of an AEM dataset towards hydrogeological mapping and 3D hydrogeological modeling, comparing it to having only a ground based TEM dataset and\or to having only boreholes data.

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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.

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In this work, the well-known MC code FLUKA was used to simulate the GE PETrace cyclotron (16.5 MeV) installed at “S. Orsola-Malpighi” University Hospital (Bologna, IT) and routinely used in the production of positron emitting radionuclides. Simulations yielded estimates of various quantities of interest, including: the effective dose distribution around the equipment; the effective number of neutron produced per incident proton and their spectral distribution; the activation of the structure of the cyclotron and the vault walls; the activation of the ambient air, in particular the production of 41Ar, the assessment of the saturation yield of radionuclides used in nuclear medicine. The simulations were validated against experimental measurements in terms of physical and transport parameters to be used at the energy range of interest in the medical field. The validated model was also extensively used in several practical applications uncluding the direct cyclotron production of non-standard radionuclides such as 99mTc, the production of medical radionuclides at TRIUMF (Vancouver, CA) TR13 cyclotron (13 MeV), the complete design of the new PET facility of “Sacro Cuore – Don Calabria” Hospital (Negrar, IT), including the ACSI TR19 (19 MeV) cyclotron, the dose field around the energy selection system (degrader) of a proton therapy cyclotron, the design of plug-doors for a new cyclotron facility, in which a 70 MeV cyclotron will be installed, and the partial decommissioning of a PET facility, including the replacement of a Scanditronix MC17 cyclotron with a new TR19 cyclotron.

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Descrizione dell'algoritmo crittografico AES, criteri adottati dal NIST per la scelta di AES e considerazioni sulla sua sicurezza.

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Many of developing countries are facing crisis in water management due to increasing of population, water scarcity, water contaminations and effects of world economic crisis. Water distribution systems in developing countries are facing many challenges of efficient repair and rehabilitation since the information of water network is very limited, which makes the rehabilitation assessment plans very difficult. Sufficient information with high technology in developed countries makes the assessment for rehabilitation easy. Developing countries have many difficulties to assess the water network causing system failure, deterioration of mains and bad water quality in the network due to pipe corrosion and deterioration. The limited information brought into focus the urgent need to develop economical assessment for rehabilitation of water distribution systems adapted to water utilities. Gaza Strip is subject to a first case study, suffering from severe shortage in the water supply and environmental problems and contamination of underground water resources. This research focuses on improvement of water supply network to reduce the water losses in water network based on limited database using techniques of ArcGIS and commercial water network software (WaterCAD). A new approach for rehabilitation water pipes has been presented in Gaza city case study. Integrated rehabilitation assessment model has been developed for rehabilitation water pipes including three components; hydraulic assessment model, Physical assessment model and Structural assessment model. WaterCAD model has been developed with integrated in ArcGIS to produce the hydraulic assessment model for water network. The model have been designed based on pipe condition assessment with 100 score points as a maximum points for pipe condition. As results from this model, we can indicate that 40% of water pipeline have score points less than 50 points and about 10% of total pipes length have less than 30 score points. By using this model, the rehabilitation plans for each region in Gaza city can be achieved based on available budget and condition of pipes. The second case study is Kuala Lumpur Case from semi-developed countries, which has been used to develop an approach to improve the water network under crucial conditions using, advanced statistical and GIS techniques. Kuala Lumpur (KL) has water losses about 40% and high failure rate, which make severe problem. This case can represent cases in South Asia countries. Kuala Lumpur faced big challenges to reduce the water losses in water network during last 5 years. One of these challenges is high deterioration of asbestos cement (AC) pipes. They need to replace more than 6500 km of AC pipes, which need a huge budget to be achieved. Asbestos cement is subject to deterioration due to various chemical processes that either leach out the cement material or penetrate the concrete to form products that weaken the cement matrix. This case presents an approach for geo-statistical model for modelling pipe failures in a water distribution network. Database of Syabas Company (Kuala Lumpur water company) has been used in developing the model. The statistical models have been calibrated, verified and used to predict failures for both networks and individual pipes. The mathematical formulation developed for failure frequency in Kuala Lumpur was based on different pipeline characteristics, reflecting several factors such as pipe diameter, length, pressure and failure history. Generalized linear model have been applied to predict pipe failures based on District Meter Zone (DMZ) and individual pipe levels. Based on Kuala Lumpur case study, several outputs and implications have been achieved. Correlations between spatial and temporal intervals of pipe failures also have been done using ArcGIS software. Water Pipe Assessment Model (WPAM) has been developed using the analysis of historical pipe failure in Kuala Lumpur which prioritizing the pipe rehabilitation candidates based on ranking system. Frankfurt Water Network in Germany is the third main case study. This case makes an overview for Survival analysis and neural network methods used in water network. Rehabilitation strategies of water pipes have been developed for Frankfurt water network in cooperation with Mainova (Frankfurt Water Company). This thesis also presents a methodology of technical condition assessment of plastic pipes based on simple analysis. This thesis aims to make contribution to improve the prediction of pipe failures in water networks using Geographic Information System (GIS) and Decision Support System (DSS). The output from the technical condition assessment model can be used to estimate future budget needs for rehabilitation and to define pipes with high priority for replacement based on poor condition. rn

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The thesis aims to expose the advances achieved in the practices of captive breeding of the European eel (Anguilla anguilla). Aspects investigated concern both approaches livestock (breeding selection, response to hormonal stimulation, reproductive performance, incubation of eggs) and physiological aspects (endocrine plasma profiles of players), as well as engineering aspects. Studies conducted on various populations of wild eel have shown that the main determining factor in the selection of wild females destined to captive breeding must be the Silver Index which may determine the stage of pubertal development. The hormonal induction protocol adopted, with increasing doses of carp pituitary extract, it has proven useful to ovarian development, with a synchronization effect that is positively reflected on egg production. The studies on the effects of photoperiod show how the condition of total darkness can positively influence practices of reproductions in captivity. The effects of photoperiod were also investigated at the physiological level, observing the plasma levels of steroids ( E2, T) and thyroid hormones (T3 and T4) and the expression in the liver of vitellogenin (vtg1 and vtg2) and estradiol membrane receptor (ESR1). From the comparison between spontaneous deposition and insemination techniques through the stripping is inferred as the first ports to a better qualitative and quantitative yield in the production of eggs capable of being fertilized, also the presence of a percentage of oocytes completely transparent can be used to obtain eggs at a good rate of fertility. Finally, the design and implementation of a system for recirculating aquaculture suited to meet the needs of species-specific eel showed how to improve the reproductive results, it would be preferable to adopt low-flow and low density incubation.

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The thesis is divided in three chapters, each one covering one topic. Initially, the thermo-mechanical and impact properties of materials used for back protectors have been analysed. Dynamical mechanical analysis (DMTA) has shown that materials used for soft-shell protectors present frequency-sensitive properties. Furthermore, through impact tests, the shock absorbing characteristics of the materials have been investigated proving the differences between soft and hard-shell protectors; moreover it has been demonstrated that the materials used for soft-shell protectors maintain their protective properties after multi-impacts. The second chapter covers the effect of the visco-elastic properties of the thermoplastic polymers on the flexural and rebound behaviours of ski boots. DMTA analysis on the materials and flexural and rebound testing on the boots have been performed. A comparison of the results highlighted a correlation between the visco-elastic properties and the flexural and rebound behaviour of ski boots. The same experimental methods have been used to investigate the influence of the design on the flexural and rebound behaviours. Finally in the third chapter the thermoplastic materials employed for the construction of ski boots soles have been characterized in terms of chemical composition, hardness, crystallinity, surface roughness and coefficient of friction (COF). The results showed a relation between material hardness and grip, in particular softer materials provide more grip with respect to harder materials. On the contrary, the surface roughness has a negative effect on friction because of the decrease in contact area. The measure of grip on inclined wet surfaces showed again a relation between hardness and grip. The performance ranking of the different materials has been the same for the COF and for the slip angle tests, indicating that COF can be used as a parameter for the choice of the optimal material to be used for the soles of ski boots.

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The aim of the Research of this Ph D Project is to improve the medical management after surgery for advanced heart failure, both after left ventricular assist devices (LVAD) implantation, and after heart transplantation in the long-term. Regarding heart transplantation (HTx), the Research Project is focused on diagnostics, classification, prevention and treatment of cardiac allograft vasculopathy (CAV), and on treatment of post-HTx cancers; the results are presented in the first part of this Thesis. In particular, the main aspect investigated are the prognostic role of information derived from coronary angiography, coronary tomography and intravascular ultrasound, and the different sensitivity of these techniques in predicting outcomes and in diagnosing CAV. Moreover, the role of mTOR inhibitors on CAV prevention or treatment is investigated, both alone and in combination with different anti-CMV prevention strategies, as well as the impact of mTOR inhibitors on clinical outcomes in the long term. Regarding LVAD, the main focus is on the role of transthoracic echocardiography in the management of patients with a continuous-flow, centrifugal, intrapericardial pump (HVAD, Heartware); this section is reported in the second part of this Thesis. The main aspects investigated are the use of echocardiography in patients with HVAD device and its interaction with the information derived from pump curves' analysis in predicting aortic valve opening status, a surrogate of the condition of support provided by the LVAD.

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Data deduplication describes a class of approaches that reduce the storage capacity needed to store data or the amount of data that has to be transferred over a network. These approaches detect coarse-grained redundancies within a data set, e.g. a file system, and remove them.rnrnOne of the most important applications of data deduplication are backup storage systems where these approaches are able to reduce the storage requirements to a small fraction of the logical backup data size.rnThis thesis introduces multiple new extensions of so-called fingerprinting-based data deduplication. It starts with the presentation of a novel system design, which allows using a cluster of servers to perform exact data deduplication with small chunks in a scalable way.rnrnAfterwards, a combination of compression approaches for an important, but often over- looked, data structure in data deduplication systems, so called block and file recipes, is introduced. Using these compression approaches that exploit unique properties of data deduplication systems, the size of these recipes can be reduced by more than 92% in all investigated data sets. As file recipes can occupy a significant fraction of the overall storage capacity of data deduplication systems, the compression enables significant savings.rnrnA technique to increase the write throughput of data deduplication systems, based on the aforementioned block and file recipes, is introduced next. The novel Block Locality Caching (BLC) uses properties of block and file recipes to overcome the chunk lookup disk bottleneck of data deduplication systems. This chunk lookup disk bottleneck either limits the scalability or the throughput of data deduplication systems. The presented BLC overcomes the disk bottleneck more efficiently than existing approaches. Furthermore, it is shown that it is less prone to aging effects.rnrnFinally, it is investigated if large HPC storage systems inhibit redundancies that can be found by fingerprinting-based data deduplication. Over 3 PB of HPC storage data from different data sets have been analyzed. In most data sets, between 20 and 30% of the data can be classified as redundant. According to these results, future work in HPC storage systems should further investigate how data deduplication can be integrated into future HPC storage systems.rnrnThis thesis presents important novel work in different area of data deduplication re- search.

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Combustion-derived and manufactured nanoparticles (NPs) are known to provoke oxidative stress and inflammatory responses in human lung cells; therefore, they play an important role during the development of adverse health effects. As the lungs are composed of more than 40 different cell types, it is of particular interest to perform toxicological studies with co-cultures systems, rather than with monocultures of only one cell type, to gain a better understanding of complex cellular reactions upon exposure to toxic substances. Monocultures of A549 human epithelial lung cells, human monocyte-derived macrophages and monocyte-derived dendritic cells (MDDCs) as well as triple cell co-cultures consisting of all three cell types were exposed to combustion-derived NPs (diesel exhaust particles) and to manufactured NPs (titanium dioxide and single-walled carbon nanotubes). The penetration of particles into cells was analysed by transmission electron microscopy. The amount of intracellular reactive oxygen species (ROS), the total antioxidant capacity (TAC) and the production of tumour necrosis factor (TNF)-alpha and interleukin (IL)-8 were quantified. The results of the monocultures were summed with an adjustment for the number of each single cell type in the triple cell co-culture. All three particle types were found in all cell and culture types. The production of ROS was induced by all particle types in all cell cultures except in monocultures of MDDCs. The TAC and the (pro-)inflammatory reactions were not statistically significantly increased by particle exposure in any of the cell cultures. Interestingly, in the triple cell co-cultures, the TAC and IL-8 concentrations were lower and the TNF-alpha concentrations were higher than the expected values calculated from the monocultures. The interplay of different lung cell types seems to substantially modulate the oxidative stress and the inflammatory responses after NP exposure.