Optimized Duration of Clopidogrel Therapy Following Treatment with the Endeavor Zotarolimus-Eluting Stent in Real-World Clinical Practice (OPTIMIZE) Trial: Rationale and design of a large-scale, randomized, multicenter study

Background Current recommendations for antithrombotic therapy after drug-eluting stent (DES) implantation include prolonged dual antiplatelet therapy (DAPT) with aspirin and clopidogrel >= 12 months. However, the impact of such a regimen for all patients receiving any DES system remains unclear based on scientific evidence available to date. Also, several other shortcomings have been identified with prolonged DAPT, including bleeding complications, compliance, and cost. The second-generation Endeavor zotarolimus-eluting stent (E-ZES) has demonstrated efficacy and safety, despite short duration DAPT (3 months) in the majority of studies. Still, the safety and clinical impact of short-term DAPT with E-ZES in the real world is yet to be determined. Methods The OPTIMIZE trial is a large, prospective, multicenter, randomized (1: 1) non-inferiority clinical evaluation of short-term (3 months) vs long-term (12-months) DAPT in patients undergoing E-ZES implantation in daily clinical practice. Overall, 3,120 patients were enrolled at 33 clinical sites in Brazil. The primary composite endpoint is death (any cause), myocardial infarction, cerebral vascular accident, and major bleeding at 12-month clinical follow-up post-index procedure. Conclusions The OPTIMIZE clinical trial will determine the clinical implications of DAPT duration with the second generation E-ZES in real-world patients undergoing percutaneous coronary intervention. (Am Heart J 2012;164:810-816.e3.)

Design and implementation of bioinformatics tools for large scale genome annotation

The continuous increase of genome sequencing projects produced a huge amount of data in the last 10 years: currently more than 600 prokaryotic and 80 eukaryotic genomes are fully sequenced and publically available. However the sole sequencing process of a genome is able to determine just raw nucleotide sequences. This is only the first step of the genome annotation process that will deal with the issue of assigning biological information to each sequence. The annotation process is done at each different level of the biological information processing mechanism, from DNA to protein, and cannot be accomplished only by in vitro analysis procedures resulting extremely expensive and time consuming when applied at a this large scale level. Thus, in silico methods need to be used to accomplish the task. The aim of this work was the implementation of predictive computational methods to allow a fast, reliable, and automated annotation of genomes and proteins starting from aminoacidic sequences. The first part of the work was focused on the implementation of a new machine learning based method for the prediction of the subcellular localization of soluble eukaryotic proteins. The method is called BaCelLo, and was developed in 2006. The main peculiarity of the method is to be independent from biases present in the training dataset, which causes the over‐prediction of the most represented examples in all the other available predictors developed so far. This important result was achieved by a modification, made by myself, to the standard Support Vector Machine (SVM) algorithm with the creation of the so called Balanced SVM. BaCelLo is able to predict the most important subcellular localizations in eukaryotic cells and three, kingdom‐specific, predictors were implemented. In two extensive comparisons, carried out in 2006 and 2008, BaCelLo reported to outperform all the currently available state‐of‐the‐art methods for this prediction task. BaCelLo was subsequently used to completely annotate 5 eukaryotic genomes, by integrating it in a pipeline of predictors developed at the Bologna Biocomputing group by Dr. Pier Luigi Martelli and Dr. Piero Fariselli. An online database, called eSLDB, was developed by integrating, for each aminoacidic sequence extracted from the genome, the predicted subcellular localization merged with experimental and similarity‐based annotations. In the second part of the work a new, machine learning based, method was implemented for the prediction of GPI‐anchored proteins. Basically the method is able to efficiently predict from the raw aminoacidic sequence both the presence of the GPI‐anchor (by means of an SVM), and the position in the sequence of the post‐translational modification event, the so called ω‐site (by means of an Hidden Markov Model (HMM)). The method is called GPIPE and reported to greatly enhance the prediction performances of GPI‐anchored proteins over all the previously developed methods. GPIPE was able to predict up to 88% of the experimentally annotated GPI‐anchored proteins by maintaining a rate of false positive prediction as low as 0.1%. GPIPE was used to completely annotate 81 eukaryotic genomes, and more than 15000 putative GPI‐anchored proteins were predicted, 561 of which are found in H. sapiens. In average 1% of a proteome is predicted as GPI‐anchored. A statistical analysis was performed onto the composition of the regions surrounding the ω‐site that allowed the definition of specific aminoacidic abundances in the different considered regions. Furthermore the hypothesis that compositional biases are present among the four major eukaryotic kingdoms, proposed in literature, was tested and rejected. All the developed predictors and databases are freely available at: BaCelLo http://gpcr.biocomp.unibo.it/bacello eSLDB http://gpcr.biocomp.unibo.it/esldb GPIPE http://gpcr.biocomp.unibo.it/gpipe

Models and methods for power monolithic microwave integrated circuits

Computer aided design of Monolithic Microwave Integrated Circuits (MMICs) depends critically on active device models that are accurate, computationally efficient, and easily extracted from measurements or device simulators. Empirical models of active electron devices, which are based on actual device measurements, do not provide a detailed description of the electron device physics. However they are numerically efficient and quite accurate. These characteristics make them very suitable for MMIC design in the framework of commercially available CAD tools. In the empirical model formulation it is very important to separate linear memory effects (parasitic effects) from the nonlinear effects (intrinsic effects). Thus an empirical active device model is generally described by an extrinsic linear part which accounts for the parasitic passive structures connecting the nonlinear intrinsic electron device to the external world. An important task circuit designers deal with is evaluating the ultimate potential of a device for specific applications. In fact once the technology has been selected, the designer would choose the best device for the particular application and the best device for the different blocks composing the overall MMIC. Thus in order to accurately reproducing the behaviour of different-in-size devices, good scalability properties of the model are necessarily required. Another important aspect of empirical modelling of electron devices is the mathematical (or equivalent circuit) description of the nonlinearities inherently associated with the intrinsic device. Once the model has been defined, the proper measurements for the characterization of the device are performed in order to identify the model. Hence, the correct measurement of the device nonlinear characteristics (in the device characterization phase) and their reconstruction (in the identification or even simulation phase) are two of the more important aspects of empirical modelling. This thesis presents an original contribution to nonlinear electron device empirical modelling treating the issues of model scalability and reconstruction of the device nonlinear characteristics. The scalability of an empirical model strictly depends on the scalability of the linear extrinsic parasitic network, which should possibly maintain the link between technological process parameters and the corresponding device electrical response. Since lumped parasitic networks, together with simple linear scaling rules, cannot provide accurate scalable models, either complicate technology-dependent scaling rules or computationally inefficient distributed models are available in literature. This thesis shows how the above mentioned problems can be avoided through the use of commercially available electromagnetic (EM) simulators. They enable the actual device geometry and material stratification, as well as losses in the dielectrics and electrodes, to be taken into account for any given device structure and size, providing an accurate description of the parasitic effects which occur in the device passive structure. It is shown how the electron device behaviour can be described as an equivalent two-port intrinsic nonlinear block connected to a linear distributed four-port passive parasitic network, which is identified by means of the EM simulation of the device layout, allowing for better frequency extrapolation and scalability properties than conventional empirical models. Concerning the issue of the reconstruction of the nonlinear electron device characteristics, a data approximation algorithm has been developed for the exploitation in the framework of empirical table look-up nonlinear models. Such an approach is based on the strong analogy between timedomain signal reconstruction from a set of samples and the continuous approximation of device nonlinear characteristics on the basis of a finite grid of measurements. According to this criterion, nonlinear empirical device modelling can be carried out by using, in the sampled voltage domain, typical methods of the time-domain sampling theory.

Design methodologies of microwawe integrated circuits for satellite telecommunications

The running innovation processes of the microwave transistor technologies, used in the implementation of microwave circuits, have to be supported by the study and development of proper design methodologies which, depending on the applications, will fully exploit the technology potentialities. After the choice of the technology to be used in the particular application, the circuit designer has few degrees of freedom when carrying out his design; in the most cases, due to the technological constrains, all the foundries develop and provide customized processes optimized for a specific performance such as power, low-noise, linearity, broadband etc. For these reasons circuit design is always a “compromise”, an investigation for the best solution to reach a trade off between the desired performances. This approach becomes crucial in the design of microwave systems to be used in satellite applications; the tight space constraints impose to reach the best performances under proper electrical and thermal de-rated conditions, respect to the maximum ratings provided by the used technology, in order to ensure adequate levels of reliability. In particular this work is about one of the most critical components in the front-end of a satellite antenna, the High Power Amplifier (HPA). The HPA is the main power dissipation source and so the element which mostly engrave on space, weight and cost of telecommunication apparatus; it is clear from the above reasons that design strategies addressing optimization of power density, efficiency and reliability are of major concern. Many transactions and publications demonstrate different methods for the design of power amplifiers, highlighting the availability to obtain very good levels of output power, efficiency and gain. Starting from existing knowledge, the target of the research activities summarized in this dissertation was to develop a design methodology capable optimize power amplifier performances complying all the constraints imposed by the space applications, tacking into account the thermal behaviour in the same manner of the power and the efficiency. After a reminder of the existing theories about the power amplifier design, in the first section of this work, the effectiveness of the methodology based on the accurate control of the dynamic Load Line and her shaping will be described, explaining all steps in the design of two different kinds of high power amplifiers. Considering the trade-off between the main performances and reliability issues as the target of the design activity, we will demonstrate that the expected results could be obtained working on the characteristics of the Load Line at the intrinsic terminals of the selected active device. The methodology proposed in this first part is based on the assumption that designer has the availability of an accurate electrical model of the device; the variety of publications about this argument demonstrates that it is so difficult to carry out a CAD model capable to taking into account all the non-ideal phenomena which occur when the amplifier operates at such high frequency and power levels. For that, especially for the emerging technology of Gallium Nitride (GaN), in the second section a new approach for power amplifier design will be described, basing on the experimental characterization of the intrinsic Load Line by means of a low frequency high power measurements bench. Thanks to the possibility to develop my Ph.D. in an academic spin-off, MEC – Microwave Electronics for Communications, the results of this activity has been applied to important research programs requested by space agencies, with the aim support the technological transfer from universities to industrial world and to promote a science-based entrepreneurship. For these reasons the proposed design methodology will be explained basing on many experimental results.

Hybrid constraint programming and metaheuristic methods for large scale optimization problems

This work presents hybrid Constraint Programming (CP) and metaheuristic methods for the solution of Large Scale Optimization Problems; it aims at integrating concepts and mechanisms from the metaheuristic methods to a CP-based tree search environment in order to exploit the advantages of both approaches. The modeling and solution of large scale combinatorial optimization problem is a topic which has arisen the interest of many researcherers in the Operations Research field; combinatorial optimization problems are widely spread in everyday life and the need of solving difficult problems is more and more urgent. Metaheuristic techniques have been developed in the last decades to effectively handle the approximate solution of combinatorial optimization problems; we will examine metaheuristics in detail, focusing on the common aspects of different techniques. Each metaheuristic approach possesses its own peculiarities in designing and guiding the solution process; our work aims at recognizing components which can be extracted from metaheuristic methods and re-used in different contexts. In particular we focus on the possibility of porting metaheuristic elements to constraint programming based environments, as constraint programming is able to deal with feasibility issues of optimization problems in a very effective manner. Moreover, CP offers a general paradigm which allows to easily model any type of problem and solve it with a problem-independent framework, differently from local search and metaheuristic methods which are highly problem specific. In this work we describe the implementation of the Local Branching framework, originally developed for Mixed Integer Programming, in a CP-based environment. Constraint programming specific features are used to ease the search process, still mantaining an absolute generality of the approach. We also propose a search strategy called Sliced Neighborhood Search, SNS, that iteratively explores slices of large neighborhoods of an incumbent solution by performing CP-based tree search and encloses concepts from metaheuristic techniques. SNS can be used as a stand alone search strategy, but it can alternatively be embedded in existing strategies as intensification and diversification mechanism. In particular we show its integration within the CP-based local branching. We provide an extensive experimental evaluation of the proposed approaches on instances of the Asymmetric Traveling Salesman Problem and of the Asymmetric Traveling Salesman Problem with Time Windows. The proposed approaches achieve good results on practical size problem, thus demonstrating the benefit of integrating metaheuristic concepts in CP-based frameworks.

A climatological analysis of high-precipitation events in Dronning Maud Land, Antarctica, and associated large-scale atmospheric conditions

The link between high precipitation in Dronning Maud Land (DML), Antarctica, and the large-scale atmospheric circulation is investigated using ERA-Interim data for 1979–2009. High-precipitation events are analyzed at Halvfarryggen situated in the coastal region of DML and at Kohnen Station located in its interior. This study further includes a comprehensive comparison of high precipitation in ERA-Interim with precipitation data from the Antarctic Mesoscale Prediction System (AMPS) and snow accumulation measurements from automatic weather stations (AWSs), with the limitations of such a comparison being discussed. The ERA-Interim and AMPS precipitation data agree very well. However, the correspondence between high precipitation in ERA-Interim and high snow accumulation at the AWSs is relatively weak. High-precipitation events at both Halvfarryggen and Kohnen are typically associated with amplified upper level waves. This large-scale atmospheric flow pattern is preceded by the downstream development of a Rossby wave train from the eastern South Pacific several days before the precipitation event. At the surface, a cyclone located over the Weddell Sea is the main synoptic ingredient for high precipitation both at Halvfarryggen and at Kohnen. A blocking anticyclone downstream is not a requirement for high precipitation per se, but a larger share of blocking occurrences during the highest-precipitation days in DML suggests that these blocks strengthen the vertically integrated water vapor transport (IVT) into DML. A strong link between high precipitation and the IVT perpendicular to the local orography suggests that IVT could be used as a “proxy” for high precipitation, in particular over DML's interior.

Multiple Hashing Integration for Real-Time Large Scale Part-to-Part Video Matching

A real-time large scale part-to-part video matching algorithm, based on the cross correlation of the intensity of motion curves, is proposed with a view to originality recognition, video database cleansing, copyright enforcement, video tagging or video result re-ranking. Moreover, it is suggested how the most representative hashes and distance functions - strada, discrete cosine transformation, Marr-Hildreth and radial - should be integrated in order for the matching algorithm to be invariant against blur, compression and rotation distortions: (R; _) 2 [1; 20]_[1; 8], from 512_512 to 32_32pixels2 and from 10 to 180_. The DCT hash is invariant against blur and compression up to 64x64 pixels2. Nevertheless, although its performance against rotation is the best, with a success up to 70%, it should be combined with the Marr-Hildreth distance function. With the latter, the image selected by the DCT hash should be at a distance lower than 1.15 times the Marr-Hildreth minimum distance.

Standardization, certification, maintenance, and dissemination of large scale engineering software systems : a panel discussion held as a part of the Second National Symposium on Computerized Structural Analysis and Design /

Includes bibliographical references

Design and implementation of a windows-based parallel computing environment for large scale optimization

A parallel computing environment to support optimization of large-scale engineering systems is designed and implemented on Windows-based personal computer networks, using the master-worker model and the Parallel Virtual Machine (PVM). It is involved in decomposition of a large engineering system into a number of smaller subsystems optimized in parallel on worker nodes and coordination of subsystem optimization results on the master node. The environment consists of six functional modules, i.e. the master control, the optimization model generator, the optimizer, the data manager, the monitor, and the post processor. Object-oriented design of these modules is presented. The environment supports steps from the generation of optimization models to the solution and the visualization on networks of computers. User-friendly graphical interfaces make it easy to define the problem, and monitor and steer the optimization process. It has been verified by an example of a large space truss optimization. (C) 2004 Elsevier Ltd. All rights reserved.

Responsive fixture design using dynamic product inspection and monitoring technologies for the precision machining of large-scale aerospace parts

When machining a large-scale aerospace part, the part is normally located and clamped firmly until a set of features are machined. When the part is released, its size and shape may deform beyond the tolerance limits due to stress release. This paper presents the design of a new fixing method and flexible fixtures that would automatically respond to workpiece deformation during machining. Deformation is inspected and monitored on-line, and part location and orientation can be adjusted timely to ensure follow-up operations are carried out under low stress and with respect to the related datum defined in the design models.

A new paradigm in large-scale assembly-research priorities in measurement assisted assembly

This paper presents for the first time the concept of measurement assisted assembly (MAA) and outlines the research priorities of the realisation of this concept in the industry. MAA denotes a paradigm shift in assembly for high value and complex products and encompasses the development and use of novel metrology processes for the holistic integration and capability enhancement of key assembly and ancillary processes. A complete framework for MAA is detailed showing how this can facilitate a step change in assembly process capability and efficiency for large and complex products, such as airframes, where traditional assembly processes exhibit the requirement for rectification and rework, use inflexible tooling and are largely manual, resulting in cost and cycle time pressures. The concept of MAA encompasses a range of innovativemeasurement- assisted processes which enable rapid partto- part assembly, increased use of flexible automation, traceable quality assurance and control, reduced structure weight and improved levels of precision across the dimensional scales. A full scale industrial trial of MAA technologies has been carried out on an experimental aircraft wing demonstrating the viability of the approach while studies within 140 smaller companies have highlighted the need for better adoption of existing process capability and quality control standards. The identified research priorities for MAA include the development of both frameless and tooling embedded automated metrology networks. Other research priorities relate to the development of integrated dimensional variation management, thermal compensation algorithms as well as measurement planning and inspection of algorithms linking design to measurement and process planning. © Springer-Verlag London 2013.

Photonic packaging: transforming silicon photonic integrated circuits into photonic devices

Dedicated multi-project wafer (MPW) runs for photonic integrated circuits (PICs) from Si foundries mean that researchers and small-to-medium enterprises (SMEs) can now afford to design and fabricate Si photonic chips. While these bare Si-PICs are adequate for testing new device and circuit designs on a probe-station, they cannot be developed into prototype devices, or tested outside of the laboratory, without first packaging them into a durable module. Photonic packaging of PICs is significantly more challenging, and currently orders of magnitude more expensive, than electronic packaging, because it calls for robust micron-level alignment of optical components, precise real-time temperature control, and often a high degree of vertical and horizontal electrical integration. Photonic packaging is perhaps the most significant bottleneck in the development of commercially relevant integrated photonic devices. This article describes how the key optical, electrical, and thermal requirements of Si-PIC packaging can be met, and what further progress is needed before industrial scale-up can be achieved.

Large scale underground energy storage for renewables integration: general criteria for reservoir identification and viable technologies.

The increasing integration of renewable energies in the electricity grid contributes considerably to achieve the European Union goals on energy and Greenhouse Gases (GHG) emissions reduction. However, it also brings problems to grid management. Large scale energy storage can provide the means for a better integration of the renewable energy sources, for balancing supply and demand, to increase energy security, to enhance a better management of the grid and also to converge towards a low carbon economy. Geological formations have the potential to store large volumes of fluids with minimal impact to environment and society. One of the ways to ensure a large scale energy storage is to use the storage capacity in geological reservoir. In fact, there are several viable technologies for underground energy storage, as well as several types of underground reservoirs that can be considered. The geological energy storage technologies considered in this research were: Underground Gas Storage (UGS), Hydrogen Storage (HS), Compressed Air Energy Storage (CAES), Underground Pumped Hydro Storage (UPHS) and Thermal Energy Storage (TES). For these different types of underground energy storage technologies there are several types of geological reservoirs that can be suitable, namely: depleted hydrocarbon reservoirs, aquifers, salt formations and caverns, engineered rock caverns and abandoned mines. Specific site screening criteria are applicable to each of these reservoir types and technologies, which determines the viability of the reservoir itself, and of the technology for any particular site. This paper presents a review of the criteria applied in the scope of the Portuguese contribution to the EU funded project ESTMAP – Energy Storage Mapping and Planning.

Node-Depth Encoding and Multiobjective Evolutionary Algorithm Applied to Large-Scale Distribution System Reconfiguration

The power loss reduction in distribution systems (DSs) is a nonlinear and multiobjective problem. Service restoration in DSs is even computationally hard since it additionally requires a solution in real-time. Both DS problems are computationally complex. For large-scale networks, the usual problem formulation has thousands of constraint equations. The node-depth encoding (NDE) enables a modeling of DSs problems that eliminates several constraint equations from the usual formulation, making the problem solution simpler. On the other hand, a multiobjective evolutionary algorithm (EA) based on subpopulation tables adequately models several objectives and constraints, enabling a better exploration of the search space. The combination of the multiobjective EA with NDE (MEAN) results in the proposed approach for solving DSs problems for large-scale networks. Simulation results have shown the MEAN is able to find adequate restoration plans for a real DS with 3860 buses and 632 switches in a running time of 0.68 s. Moreover, the MEAN has shown a sublinear running time in function of the system size. Tests with networks ranging from 632 to 5166 switches indicate that the MEAN can find network configurations corresponding to a power loss reduction of 27.64% for very large networks requiring relatively low running time.

Ultrasound Irradiation Promoted Large-Scale Preparation in Aqueous Media and Antioxidant Activity of Azoles

The scaled-up preparation of 1H-pyrazole, 1-phenylpyrazole and isoxazole via sonocatalysis is reported. The products were isolated in good yields in short time reaction. These compounds had been assayed for antioxidant activity by ORAC and DPPH methodologies. The results showed that only 1-phenylpyrazole presented good antioxidant activity compared with Trolox(R).