Efficient Secure Computation for Real-world Settings and Security Models

Secure computation involves multiple parties computing a common function while keeping their inputs private, and is a growing field of cryptography due to its potential for maintaining privacy guarantees in real-world applications. However, current secure computation protocols are not yet efficient enough to be used in practice. We argue that this is due to much of the research effort being focused on generality rather than specificity. Namely, current research tends to focus on constructing and improving protocols for the strongest notions of security or for an arbitrary number of parties. However, in real-world deployments, these security notions are often too strong, or the number of parties running a protocol would be smaller. In this thesis we make several steps towards bridging the efficiency gap of secure computation by focusing on constructing efficient protocols for specific real-world settings and security models. In particular, we make the following four contributions: - We show an efficient (when amortized over multiple runs) maliciously secure two-party secure computation (2PC) protocol in the multiple-execution setting, where the same function is computed multiple times by the same pair of parties. - We improve the efficiency of 2PC protocols in the publicly verifiable covert security model, where a party can cheat with some probability but if it gets caught then the honest party obtains a certificate proving that the given party cheated. - We show how to optimize existing 2PC protocols when the function to be computed includes predicate checks on its inputs. - We demonstrate an efficient maliciously secure protocol in the three-party setting.

Multiple solutions and numerical analysis to the dynamic and stationary models coupling a delayed energy balance model involving latent heat and discontinuous albedo with a deep ocean

We study a climatologically important interaction of two of the main components of the geophysical system by adding an energy balance model for the averaged atmospheric temperature as dynamic boundary condition to a diagnostic ocean model having an additional spatial dimension. In this work, we give deeper insight than previous papers in the literature, mainly with respect to the 1990 pioneering model by Watts and Morantine. We are taking into consideration the latent heat for the two phase ocean as well as a possible delayed term. Non-uniqueness for the initial boundary value problem, uniqueness under a non-degeneracy condition and the existence of multiple stationary solutions are proved here. These multiplicity results suggest that an S-shaped bifurcation diagram should be expected to occur in this class of models generalizing previous energy balance models. The numerical method applied to the model is based on a finite volume scheme with nonlinear weighted essentially non-oscillatory reconstruction and Runge–Kutta total variation diminishing for time integration.

Development of Planning And Evaluation Models For Superstreets

Despite the extensive implementation of Superstreets on congested arterials, reliable methodologies for such designs remain unavailable. The purpose of this research is to fill the information gap by offering reliable tools to assist traffic professionals in the design of Superstreets with and without signal control. The entire tool developed in this thesis consists of three models. The first model is used to determine the minimum U-turn offset length for an Un-signalized Superstreet, given the arterial headway distribution of the traffic flows and the distribution of critical gaps among drivers. The second model is designed to estimate the queue size and its variation on each critical link in a signalized Superstreet, based on the given signal plan and the range of observed volumes. Recognizing that the operational performance of a Superstreet cannot be achieved without an effective signal plan, the third model is developed to produce a signal optimization method that can generate progression offsets for heavy arterial flows moving into and out of such an intersection design.

Tracheostomy in Pediatric Intensive Care Unit: When and Where?

Background: Tracheostomy was first observed in Egyptian drawings in 3600 BC and performed frequently during the 1800’s diphtheria epidemic. Objectives: The aim of this study was to elucidate the indications, complications, mortality rate, and the effect of pediatric tracheostomy on length of PICU or hospital stay. Materials and Methods: Demographic characteristics, diagnosis at admission, duration of ventilation of 152 patients were analyzed retrospectively. Results: The most common tracheostomy indication was prolonged intubation. The mean duration of mechanical ventilation before tracheostomy was 23.8 days. Forty five percent of the tracheostomy procedures were performed at bedside. Neither the place nor the age had any effect on the development of complications (P = 0.701, P = 0.622). The procedure enabled 62% of the patients to be discharged from hospital. Conclusions: Tracheostomy facilitates discharge and weaning of mechanical ventilation. Although the timing of tracheostomy has to be determined for each individual patient, three weeks of ventilation seems to be a suitable period for tracheostomy. Tracheostomy can be performed at bedside safely but patient selection should be made carefully.

Design, synthesis and antiproliferative activity of hydroxyacetamide derivatives against HeLa cervical carcinoma cell and breast cancer cell line

Purpose: To design and develop a new series of histone deacetylase inhibitors (FP1 - FP12) and evaluate their inhibitory activity against hydroxyacetamide (HDAC) enzyme mixture-derived HeLa cervical carcinoma cell and MCF-7. Methods: The designed molecules (FP1 - FP12) were docked using AUTODOCK 1.4.6. FP3 and FP8 showed higher interaction comparable to the prototypical HDACI. The designed series of 2-[[(3- Phenyl/substituted Phenyl-[4-{(4-(substituted phenyl)ethylidine-2-Phenyl-1,3-Imidazol-5-One}](-4H- 1,2,4-triazol-5-yl)sulfanyl]-N-hydroxyacetamide derivatives (FP1-FP12) was synthesized by merging 2- [(4-amino-3-phenyl-4H- 1, 2, 4-triazol-5-yl) sulfanyl]-N-hydroxyacetamide and 2-{[4-amino-3-(2- hydroxyphenyl)-4H-1,2, 4-triazol-5-yl]sulfanyl}-N hydroxyacetamide derivatives with aromatic substituted oxazolone. The biological activity of the synthesized molecule (FP1-FP12) was evaluated against HDAC enzyme mixture-derived HeLa cervical carcinoma cell and breast cancer cell line (MCF-7). Results: HDAC inhibitory activity of FP10 showed higher IC50 (half-maximal concentration inhibitory activity) of 0.09 μM, whereas standard SAHA molecule showed IC50 of 0.057 μM. On the other hand, FP9 exhibited higher GI50 (50 % of maximal concentration that inhibited cell proliferation) of 22.8 μM against MCF-7 cell line, compared with the standard, adriamycin, with GI50 of (-) 50.2 μM. Conclusion: Synthesis, spectral characterization, and evaluation of HDAC inhibition activity and in vitro anticancer evaluation of novel hydroxyacetamide derivatives against MCF-7 cell line have been achieved. The findings indicate the emergence of potentialanticancer compounds.

Combining multispecies home range and distribution models aids assessment of MPA effectiveness

Marine protected areas (MPAs) are today's most important tools for the spatial management and conservation of marine species. Yet, the true protection that they provide to individual fish is unknown, leading to uncertainty associated with MPA effectiveness. In this study, conducted in a recently established coastal MPA in Portugal, we combined the results of individual home range estimation and population distribution models for 3 species of commercial importance and contrasting life histories to infer (1) the size of suitable areas where they would be fully protected and (2) the vulnerability to fishing mortality of each species. Results show that the relationship between MPA size and effective protection is strongly modulated by both the species' home range and the distribution of suitable habitat inside and outside the MPA. This approach provides a better insight into the true potential of MPAs in effectively protecting marine species, since it can reveal the size and location of the areas where protection is most effective and a clear, quantitative estimation of the vulnerability to fishing throughout an entire MPA.

Occurrence and abundance models of threatened plant species: Applications to mitigate the impact of hydroelectric power dams

Species occurrence and abundance models are important tools that can be used in biodiversity conservation, and can be applied to predict or plan actions needed to mitigate the environmental impacts of hydropower dams. In this study our objectives were: (i) to model the occurrence and abundance of threatened plant species, (ii) to verify the relationship between predicted occurrence and true abundance, and (iii) to assess whether models based on abundance are more effective in predicting species occurrence than those based on presence–absence data. Individual representatives of nine species were counted within 388 randomly georeferenced plots (10 m × 50 m) around the Barra Grande hydropower dam reservoir in southern Brazil. We modelled their relationship with 15 environmental variables using both occurrence (Generalised Linear Models) and abundance data (Hurdle and Zero-Inflated models). Overall, occurrence models were more accurate than abundance models. For all species, observed abundance was significantly, although not strongly, correlated with the probability of occurrence. This correlation lost significance when zero-abundance (absence) sites were excluded from analysis, but only when this entailed a substantial drop in sample size. The same occurred when analysing relationships between abundance and probability of occurrence from previously published studies on a range of different species, suggesting that future studies could potentially use probability of occurrence as an approximate indicator of abundance when the latter is not possible to obtain. This possibility might, however, depend on life history traits of the species in question, with some traits favouring a relationship between occurrence and abundance. Reconstructing species abundance patterns from occurrence could be an important tool for conservation planning and the management of threatened species, allowing scientists to indicate the best areas for collection and reintroduction of plant germplasm or choose conservation areas most likely to maintain viable populations.

Inversion of ambient seismic noise HVSR to evaluate velocity and structural models of the Lower Tagus Basin, Portugal

During its history, several significant earthquakes have shaken the Lower Tagus Valley (Portugal). These earthquakes were destructive; some strong earthquakes were produced by large ruptures in offshore structures located southwest of the Portuguese coastline, and other moderate earthquakes were produced by local faults. In recent years, several studies have successfully obtained strong-ground motion syntheses for the Lower Tagus Valley using the finite difference method. To confirm the velocity model of this sedimentary basin obtained from geophysical and geological data, we analysed the ambient seismic noise measurements by applying the horizontal to vertical spectral ratio (HVSR) method. This study reveals the dependence of the frequency and amplitude of the low-frequency (HVSR) peaks (0.2–2 Hz) on the sediment thickness. We have obtained the depth of the Cenozoic basement along a profile transversal to the basin by the inversion of these ratios, imposing constraints from seismic reflection, boreholes, seismic sounding and gravimetric and magnetic potentials. This technique enables us to improve the existing three-dimensional model of the Lower Tagus Valley structure. The improved model will be decisive for the improvement of strong motion predictions in the earthquake hazard analysis of this highly populated basin. The methodology discussed can be applied to any other sedimentary basin.

The mesophotic zone of the Mediterranean Sea: spatial definition, biodiversity, and predictive models

The mesophotic zone is frequently defined as ranging between 30-40 and 150 m depth. However, these borders are necessarily imprecise due to variations in the penetration of light along the water column related to local factors. Moreover, density of data on mesophotic ecosystems vary along geographical distance, with temperate latitudes largely less explored than tropical situations. This is the case of the Mediterranean Sea, where information on mesophotic ecosystems is largely lower with respect to tropical situations. The lack of a clear definition of the borders of the mesophotic zone may represent a problem when information must be transferred to the policy that requires a coherent spatial definition to plan proper management and conservation measures. The present thesis aims at providing information on the spatial definition of the mesophotic zone in the Mediterranean Sea, its biodiversity and distribution of its ecosystems. The first chapter analyzes information on mesophotic ecosystems in the Mediterranean Sea to identify gaps in the literature and map the mesophotic zone in the Mediterranean Sea using light penetration estimated from satellite data. In the second chapter, different visual techniques to study mesophotic ecosystems are compared to identify the best analytical method to estimate diversity and habitat extension. In the third chapter, a set of Remotely Operated vehicles (ROV) surveys performed on mesophotic assemblages in the Mediterranean Sea are analyzed to describe their taxonomic and functional diversity and environmental factors influencing their structure. A Habitat Suitability Model is run in the fourth chapter to map the distribution of areas suitable for the presence of deep-water oyster reefs in the Adriatic-Ionian area. The fifth chapter explores the mesophotic zone in the northern Gulf of Mexico providing its spatial and vertical extension of the mesophotic zone and information on the diversity associated with mesophotic ecosystems.

Variational and learning models for image and time series inverse problems

Inverse problems are at the core of many challenging applications. Variational and learning models provide estimated solutions of inverse problems as the outcome of specific reconstruction maps. In the variational approach, the result of the reconstruction map is the solution of a regularized minimization problem encoding information on the acquisition process and prior knowledge on the solution. In the learning approach, the reconstruction map is a parametric function whose parameters are identified by solving a minimization problem depending on a large set of data. In this thesis, we go beyond this apparent dichotomy between variational and learning models and we show they can be harmoniously merged in unified hybrid frameworks preserving their main advantages. We develop several highly efficient methods based on both these model-driven and data-driven strategies, for which we provide a detailed convergence analysis. The arising algorithms are applied to solve inverse problems involving images and time series. For each task, we show the proposed schemes improve the performances of many other existing methods in terms of both computational burden and quality of the solution. In the first part, we focus on gradient-based regularized variational models which are shown to be effective for segmentation purposes and thermal and medical image enhancement. We consider gradient sparsity-promoting regularized models for which we develop different strategies to estimate the regularization strength. Furthermore, we introduce a novel gradient-based Plug-and-Play convergent scheme considering a deep learning based denoiser trained on the gradient domain. In the second part, we address the tasks of natural image deblurring, image and video super resolution microscopy and positioning time series prediction, through deep learning based methods. We boost the performances of supervised, such as trained convolutional and recurrent networks, and unsupervised deep learning strategies, such as Deep Image Prior, by penalizing the losses with handcrafted regularization terms.

CERN-MEDICIS: une nouvelle infrastructure pour la production de radioisotopes a usage medical [CERN-MEDICIS (Medical Isotopes Collected from ISOLDE): a new facility].

CERN-MEDICIS (Medical Isotopes Collected from ISOLDE) est une plateforme de recherche destinée à la production de radioisotopes biomédicaux. Inauguré en 2014, il produira progressivement un nombre croissant de radioisotopes grâce au faisceau de protons ISOLDE déjà existant. Ce projet réunit des spécialistes du cancer, des chirurgiens, des experts en médecine nucléaire, en radiochimie et radiopharmacie et les scientifiques du CERN. Les radioisotopes ainsi produits seront destinés à la recherche fondamentale contre le cancer, à des études précliniques ainsi qu'au développement de protocoles d'imagerie et de thérapie destinés aux patients.Le CERN, les HUG, le CHUV, l'ISREC et l'EPFL qui soutiennent ce projet seront les premiers bénéficiaires de ces radioisotopes novateurs dont la distribution sera ensuite étendue à d'autres centres européens. CERN-MEDICIS is a facility dedicated to research and development in life science and medical applications. The research platform was inaugurated in October 2014 and will produce an increasing range of innovative isotopes using the proton beam of ISOLDE for fundamental studies in cancer research, for new imaging and therapy protocols in cell and animal models and for preclinical trials, possibly extended to specific early phase clinical studies (phase 0) up to phase I trials. CERN, the University Hospital of Geneva (HUG), the University Hospital of Lausanne (CHUV), the Swiss Institute for Experimental Cancer (ISREC) at Swiss Federal Institutes of Technology (EPFL) that currently support the project will benefit of the initial production that will then be extended to other centers.

Retention at room temperature of the tetragonal t ``-form in Sc(2)O(3)-doped ZrO(2) nanopowders

Synchrotron X-ray powder diffraction was applied to the study of the effect of crystallite size on the crystal structure of ZrO(2)-10 mol% Sc(2)O(3) nanopowders synthesized by a nitrate-lysine gel-combustion route Nanopowders with different average crystallite sizes were obtained by calcination at several temperatures, ranging from 650 to 1200 degrees C The metastable t""-form of the tetragonal phase, exhibiting a cubic unit cell and tetragonal P4(2)/nmc spatial symmetry, was retained at room temperature in fine nanocrystalline powders, completely avoiding the presence of the stable rhombohedral beta phase. Differently, this phase was identified in samples calcined at high temperatures and its content increased with increasing crystallite size The critical maximum crystallite size for the retention of the mestastable t""-form resulted of about 35 nm (C) 2009 Elsevier B.V All rights reserved

Crystalline structure of mangiferin, a C-glycosyl-substituted 9H-xanthen-9-one isolated from the stem bark of Mangifera indica

The crystalline structure of mangiferin (= 2-beta-D-glucopyranosyl-1,3,6,7-tetrahydroxy-9H-xanthen-9-one; 1), a biologically active xanthenone C-glycoside, isolated from the stem bark of Mangifera indica (Anacardiaceae), was unambiguously determined by single-crystal X-ray diffraction (XRD). The crystal structure is summarized as follows: triclinic, P1, a = 7.6575(5), b = 11.2094(8), c = 11.8749(8) angstrom, alpha = 79.967(5), beta = 87.988(4), gamma = 72.164(4)degrees, V = 955.3(1) angstrom(3), and Z = 2. The structure also shows two molecules in the asymmetric unit cell and five crystallization H2O molecules. The packing is stabilized by several intermolecular H-bonds involving either the two symmetry-independent mangiferin molecules 1a and 1b, or the H2O ones.