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1. DeepSense-V2V: A Vehicle-to-Vehicle Multi-Modal Sensing, Localization, and Communications Dataset

Author

Morais, Joao, Charan, Gouranga, Srinivas, Nikhil, and Alkhateeb, Ahmed

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

High data rate and low-latency vehicle-to-vehicle (V2V) communication are essential for future intelligent transport systems to enable coordination, enhance safety, and support distributed computing and intelligence requirements. Developing effective communication strategies, however, demands realistic test scenarios and datasets. This is important at the high-frequency bands where more spectrum is available, yet harvesting this bandwidth is challenged by the need for direction transmission and the sensitivity of signal propagation to blockages. This work presents the first large-scale multi-modal dataset for studying mmWave vehicle-to-vehicle communications. It presents a two-vehicle testbed that comprises data from a 360-degree camera, four radars, four 60 GHz phased arrays, a 3D lidar, and two precise GPSs. The dataset contains vehicles driving during the day and night for 120 km in intercity and rural settings, with speeds up to 100 km per hour. More than one million objects were detected across all images, from trucks to bicycles. This work further includes detailed dataset statistics that prove the coverage of various situations and highlights how this dataset can enable novel machine-learning applications., Comment: 14 pages, 15 figures, 2 tables. The dataset is available on the DeepSense6G website: https://deepsense6g.net/

Published
2024

2. Safety of the PCSK9 inhibitor alirocumab: insights from 47 296 patient-years of observation

Author

Goodman, Shaun G, Steg, Philippe Gabriel, Szarek, Michael, Bhatt, Deepak L, Bittner, Vera A, Diaz, Rafael, Harrington, Robert A, Jukema, J Wouter, White, Harvey D, Zeiher, Andreas M, Manvelian, Garen, Pordy, Robert, Poulouin, Yann, Stipek, Wanda, Garon, Genevieve, Schwartz, Gregory G, Steg, Ph Gabriel, Tricoci, Pierluigi, Roe, Matthew T, Mahaffey, Kenneth W, Edelberg, Jay M, Hanotin, Corinne, Lecorps, Guillaume, Moryusef, Angèle, Sasiela, William J, Tamby, Jean-François, Aylward, Philip E, Drexel, Heinz, Sinnaeve, Peter, Dilic, Mirza, Lopes, Renato D, Gotcheva, Nina N, Prieto, Juan-Carlos, Yong, Huo, López-Jaramillo, Patricio, Pećin, Ivan, Reiner, Zeljko, Ostadal, Petr, Poulsen, Steen Hvitfeldt, Viigimaa, Margus, Nieminen, Markku S, Danchin, Nicolas, Chumburidze, Vakhtang, Marx, Nikolaus, Liberopoulos, Evangelos, Valdovinos, Pablo Carlos Montenegro, Tse, Hung-Fat, Kiss, Robert Gabor, Xavier, Denis, Zahger, Doron, Valgimigli, Marco, Kimura, Takeshi, Kim, Hyo Soo, Kim, Sang-Hyun, Erglis, Andrejs, Laucevicius, Aleksandras, Kedev, Sasko, Yusoff, Khalid, López, Gabriel Arturo Ramos, Alings, Marco, Halvorsen, Sigrun, Flores, Roger M Correa, Sy, Rody G, Budaj, Andrzej, Morais, Joao, Dorobantu, Maria, Karpov, Yuri, Ristic, Arsen D, Chua, Terrance, Murin, Jan, Fras, Zlatko, Dalby, Anthony J, Tuñón, José, de Silva, H Asita, Hagström, Emil, Landmesser, Ulf, Chiang, Chern-En, Sritara, Piyamitr, Guneri, Sema, Parkhomenko, Alexander, Ray, Kausik K, Moriarty, Patrick M, Chaitman, Bernard, Kelsey, Sheryl F, Olsson, Anders G, and Rouleau, Jean-Lucien

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Clinical Trials and Supportive Activities, Patient Safety, Clinical Research, 6.1 Pharmaceuticals, Good Health and Well Being, Humans, Antibodies, Monoclonal, Humanized, Anticholesteremic Agents, Biomarkers, Cardiovascular Diseases, Cholesterol, LDL, Dyslipidemias, PCSK9 Inhibitors, Proprotein Convertase 9, Randomized Controlled Trials as Topic, Serine Proteinase Inhibitors, Time Factors, Treatment Outcome, ODYSSEY OUTCOMES Investigators, Alirocumab, Cholesterol, PCSK9, Safety, Cardiorespiratory Medicine and Haematology, Pharmacology and Pharmaceutical Sciences, Cardiovascular medicine and haematology, Pharmacology and pharmaceutical sciences
Abstract

The ODYSSEY OUTCOMES trial, comprising over 47 000 patient-years of placebo-controlled observation, demonstrated important reductions in the risk of recurrent ischaemic cardiovascular events with the monoclonal antibody to proprotein convertase subtilisin/kexin type 9 alirocumab, as well as lower all-cause death. These benefits were observed in the context of substantial and persistent lowering of low-density lipoprotein cholesterol with alirocumab compared with that achieved with placebo. The safety profile of alirocumab was indistinguishable from matching placebo except for a ∼1.7% absolute increase in local injection site reactions. Further, the safety of alirocumab compared with placebo was evident in vulnerable groups identified before randomization, such as the elderly and those with diabetes mellitus, previous ischaemic stroke, or chronic kidney disease. The frequency of adverse events and laboratory-based abnormalities was generally similar to that in placebo-treated patients. Thus, alirocumab appears to be a safe and effective lipid-modifying treatment over a duration of at least 5 years.

Published
2024

3. Localization in Digital Twin MIMO Networks: A Case for Massive Fingerprinting

Author

Morais, João and Alkhateeb, Ahmed

Subjects
Computer Science - Information Theory, Electrical Engineering and Systems Science - Signal Processing
Abstract

Localization in outdoor wireless systems typically requires transmitting specific reference signals to estimate distance (trilateration methods) or angle (triangulation methods). These cause overhead on communication, need a LoS link to work well, and require multiple base stations, often imposing synchronization or specific hardware requirements. Fingerprinting has none of these drawbacks, but building its database requires high human effort to collect real-world measurements. For a long time, this issue limited the size of databases and thus their performance. This work proposes significantly reducing human effort in building fingerprinting databases by populating them with \textit{digital twin RF maps}. These RF maps are built from ray-tracing simulations on a digital replica of the environment across several frequency bands and beamforming configurations. Online user fingerprints are then matched against this spatial database. The approach was evaluated with practical simulations using realistic propagation models and user measurements. Our experiments show sub-meter localization errors on a NLoS location 95\% of the time using sensible user measurement report sizes. Results highlight the promising potential of the proposed digital twin approach for ubiquitous wide-area 6G localization., Comment: To appear in ICC 2024. The Dataset and code will be available soon on the DeepMIMO and DeepVerse websites https://www.deepmimo.net/ https://www.deepverse6g.net/

Published
2024

4. Device-Agnostic Millimeter Wave Beam Selection using Machine Learning

Author

Rezaie, Sajad, Morais, João, Alkhateeb, Ahmed, and Manchón, Carles Navarro

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

Most research in the area of machine learning-based user beam selection considers a structure where the model proposes appropriate user beams. However, this design requires a specific model for each user-device beam codebook, where a model learned for a device with a particular codebook can not be reused for another device with a different codebook. Moreover, this design requires training and test samples for each antenna placement configuration/codebook. This paper proposes a device-agnostic beam selection framework that leverages context information to propose appropriate user beams using a generic model and a post processing unit. The generic neural network predicts the potential angles of arrival, and the post processing unit maps these directions to beams based on the specific device's codebook. The proposed beam selection framework works well for user devices with antenna configuration/codebook unseen in the training dataset. Also, the proposed generic network has the option to be trained with a dataset mixed of samples with different antenna configurations/codebooks, which significantly eases the burden of effective model training., Comment: 30 pages, 19 figures. This article was submitted to IEEE Trans. Wirel. Commun. on Nov 14 2022

Published
2022

5. DeepSense 6G: A Large-Scale Real-World Multi-Modal Sensing and Communication Dataset

Author

Alkhateeb, Ahmed, Charan, Gouranga, Osman, Tawfik, Hredzak, Andrew, Morais, João, Demirhan, Umut, and Srinivas, Nikhil

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

This article presents the DeepSense 6G dataset, which is a large-scale dataset based on real-world measurements of co-existing multi-modal sensing and communication data. The DeepSense 6G dataset is built to advance deep learning research in a wide range of applications in the intersection of multi-modal sensing, communication, and positioning. This article provides a detailed overview of the DeepSense dataset structure, adopted testbeds, data collection and processing methodology, deployment scenarios, and example applications, with the objective of facilitating the adoption and reproducibility of multi-modal sensing and communication datasets., Comment: The dataset is available on the DeepSense 6G website http://deepsense6g.net/

Published
2022

6. 'Conversas Made in CO': An Audio Podcast Featuring Alumni, Building a Collective Memory and Contributing to the Brand Identity

Author

Leandro, Alexandra, Morais, João, Silva, Estela, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Rocha, Alvaro, editor, Adeli, Hojjat, editor, Dzemyda, Gintautas, editor, Moreira, Fernando, editor, and Colla, Valentina, editor

Published
2024
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7. Multi-Modal Beam Prediction Challenge 2022: Towards Generalization

Author

Charan, Gouranga, Demirhan, Umut, Morais, João, Behboodi, Arash, Pezeshki, Hamed, and Alkhateeb, Ahmed

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Information Theory
Abstract

Beam management is a challenging task for millimeter wave (mmWave) and sub-terahertz communication systems, especially in scenarios with highly-mobile users. Leveraging external sensing modalities such as vision, LiDAR, radar, position, or a combination of them, to address this beam management challenge has recently attracted increasing interest from both academia and industry. This is mainly motivated by the dependency of the beam direction decision on the user location and the geometry of the surrounding environment -- information that can be acquired from the sensory data. To realize the promised beam management gains, such as the significant reduction in beam alignment overhead, in practice, however, these solutions need to account for important aspects. For example, these multi-modal sensing aided beam selection approaches should be able to generalize their learning to unseen scenarios and should be able to operate in realistic dense deployments. The "Multi-Modal Beam Prediction Challenge 2022: Towards Generalization" competition is offered to provide a platform for investigating these critical questions. In order to facilitate the generalizability study, the competition offers a large-scale multi-modal dataset with co-existing communication and sensing data collected across multiple real-world locations and different times of the day. In this paper, along with the detailed descriptions of the problem statement and the development dataset, we provide a baseline solution that utilizes the user position data to predict the optimal beam indices. The objective of this challenge is to go beyond a simple feasibility study and enable necessary research in this direction, paving the way towards generalizable multi-modal sensing-aided beam management for real-world future communication systems., Comment: The dataset is available on the ML competition page: https://deepsense6g.net/multi-modal-beam-prediction-challenge/

Published
2022

8. Position Aided Beam Prediction in the Real World: How Useful GPS Locations Actually Are?

Author

Morais, João, Behboodi, Arash, Pezeshki, Hamed, and Alkhateeb, Ahmed

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Information Theory, Computer Science - Machine Learning
Abstract

Millimeter-wave (mmWave) communication systems rely on narrow beams for achieving sufficient receive signal power. Adjusting these beams is typically associated with large training overhead, which becomes particularly critical for highly-mobile applications. Intuitively, since optimal beam selection can benefit from the knowledge of the positions of communication terminals, there has been increasing interest in leveraging position data to reduce the overhead in mmWave beam prediction. Prior work, however, studied this problem using only synthetic data that generally does not accurately represent real-world measurements. In this paper, we investigate position-aided beam prediction using a real-world large-scale dataset to derive insights into precisely how much overhead can be saved in practice. Furthermore, we analyze which machine learning algorithms perform best, what factors degrade inference performance in real data, and which machine learning metrics are more meaningful in capturing the actual communication system performance., Comment: Submitted to IEEE. Datasets and code files are available on the DeepSense website: https://deepsense6g.net/

Published
2022

9. Location- and Orientation-aware Millimeter Wave Beam Selection for Multi-Panel Antenna Devices

Author

Rezaie, Sajad, Morais, João, de Carvalho, Elisabeth, Alkhateeb, Ahmed, and Manchón, Carles Navarro

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

While initial beam alignment (BA) in millimeter-wave networks has been thoroughly investigated, most research assumes a simplified terminal model based on uniform linear/planar arrays with isotropic antennas. Devices with non-isotropic antenna elements need multiple panels to provide good spherical coverage, and exhaustive search over all beams of all the panels leads to unacceptable overhead. This paper proposes a location- and orientation-aware solution that manages the initial BA for multi-panel devices. We present three different neural network structures that provide efficient BA with a wide range of training dataset sizes, complexity, and feedback message sizes. Our proposed methods outperform the generalized inverse fingerprinting and hierarchical panel-beam selection methods for two considered edge and edge-face antenna placement designs., Comment: 5 pages, 7 figure. This article was submitted to IEEE SPAWC 2022 on Mar 11 2022

Published
2022

10. Parkour Spot ID: Feature Matching in Satellite and Street view images using Deep Learning

Author

Morais, João, Rathi, Kaushal, Mohan, Bhuvaneshwar, and Rajesh, Shantanu

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

How to find places that are not indexed by Google Maps? We propose an intuitive method and framework to locate places based on their distinctive spatial features. The method uses satellite and street view images in machine vision approaches to classify locations. If we can classify locations, we just need to repeat for non-overlapping locations in our area of interest. We assess the proposed system in finding Parkour spots in the campus of Arizona State University. The results are very satisfactory, having found more than 25 new Parkour spots, with a rate of true positives above 60%.

Published
2022

11. A New Approach for Interpretability and Reliability in Clinical Risk Prediction: Acute Coronary Syndrome Scenario

Author

Valente, Francisco, Henriques, Jorge, Paredes, Simão, Rocha, Teresa, de Carvalho, Paulo, and Morais, João

Subjects
Computer Science - Machine Learning, Statistics - Applications, Statistics - Methodology
Abstract

We intend to create a new risk assessment methodology that combines the best characteristics of both risk score and machine learning models. More specifically, we aim to develop a method that, besides having a good performance, offers a personalized model and outcome for each patient, presents high interpretability, and incorporates an estimation of the prediction reliability which is not usually available. By combining these features in the same approach we expect that it can boost the confidence of physicians to use such a tool in their daily activity. In order to achieve the mentioned goals, a three-step methodology was developed: several rules were created by dichotomizing risk factors; such rules were trained with a machine learning classifier to predict the acceptance degree of each rule (the probability that the rule is correct) for each patient; that information was combined and used to compute the risk of mortality and the reliability of such prediction. The methodology was applied to a dataset of patients admitted with any type of acute coronary syndromes (ACS), to assess the 30-days all-cause mortality risk. The performance was compared with state-of-the-art approaches: logistic regression (LR), artificial neural network (ANN), and clinical risk score model (Global Registry of Acute Coronary Events - GRACE). The proposed approach achieved testing results identical to the standard LR, but offers superior interpretability and personalization; it also significantly outperforms the GRACE risk model and the standard ANN model. The calibration curve also suggests a very good generalization ability of the obtained model as it approaches the ideal curve. Finally, the reliability estimation of individual predictions presented a great correlation with the misclassifications rate. Those properties may have a beneficial application in other clinical scenarios as well. [abridged], Comment: Accepted for publication in the Artificial Intelligence in Medicine journal. Abstract abridged to respect the arXiv's characters limit

Published
2021
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12. Reduced-quaternionic Mathieu functions, time-dependent Moisil-Teodorescu operators, and the imaginary-time wave equation

Author

Morais, João and Porter, R. Michael

Subjects
Mathematics - Complex Variables, Mathematics - Classical Analysis and ODEs, 30G35 (Primary) 33E10, 34B30, 42C30, 35J05, 35Q41 (Secondary)
Abstract

We construct a one-parameter family of generalized Mathieu functions, which are reduced quaternion-valued functions of a pair of real variables lying in an ellipse, and which we call $\lambda$-reduced quaternionic Mathieu functions. We prove that the $\lambda$-RQM functions, which are in the kernel of the Moisil-Teodorescu operator $D+\lambda$ ($D$ is the Dirac operator and $\lambda\in\mathbb{R}\setminus\{0\}$), form a complete orthogonal system in the Hilbert space of square-integrable $\lambda$-metamonogenic functions with respect to the $L^2$-norm over confocal ellipses. Further, we introduce the zero-boundary $\lambda$-RQM-functions, which are $\lambda$-RQM functions whose scalar part vanishes on the boundary of the ellipse. The limiting values of the $\lambda$-RQM functions as the eccentricity of the ellipse tends to zero are expressed in terms of Bessel functions of the first kind and form a complete orthogonal system for $\lambda$-metamonogenic functions with respect to the $L^2$-norm on the unit disk. A connection between the $\lambda$-RQM functions and the time-dependent solutions of the imaginary-time wave equation in the elliptical coordinate system is shown., Comment: 34 pages, 6 figures, 1 table

Published
2021

16. Improving the compromise between accuracy, interpretability and personalization of rule-based machine learning in medical problems

Author

Valente, Francisco, Henriques, Jorge, Paredes, Simão, Rocha, Teresa, de Carvalho, Paulo, and Morais, João

Subjects
Computer Science - Machine Learning
Abstract

One of the key challenges when developing a predictive model is the capability to describe the domain knowledge and the cause-effect relationships in a simple way. Decision rules are a useful and important methodology in this context, justifying their application in several areas, particularly in clinical practice. Several machine-learning classifiers have exploited the advantageous properties of decision rules to build intelligent prediction models, namely decision trees and ensembles of trees (ETs). However, such methodologies usually suffer from a trade-off between interpretability and predictive performance. Some procedures consider a simplification of ETs, using heuristic approaches to select an optimal reduced set of decision rules. In this paper, we introduce a novel step to those methodologies. We create a new component to predict if a given rule will be correct or not for a particular patient, which introduces personalization into the procedure. Furthermore, the validation results using three public clinical datasets suggest that it also allows to increase the predictive performance of the selected set of rules, improving the mentioned trade-off., Comment: Accepted for the IEEE Engineering in Medicine and Biology Society Conference (EMBC 2021)

Published
2021

18. The Meaning of Life (in Video Games)

Author

Mourato, Fausto, Morais, João, de Lima, Edirlei Soares, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ciancarini, Paolo, editor, Di Iorio, Angelo, editor, Hlavacs, Helmut, editor, and Poggi, Francesco, editor

Published
2023
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21. Lipoprotein(a) and the Effect of Alirocumab on Revascularization After Acute Coronary Syndrome

Author

Schwartz, Gregory G., Steg, Ph. Gabriel, Bhatt, Deepak L., Bittner, Vera A., Diaz, Rafael, Goodman, Shaun G., Harrington, Robert A., Jukema, J. Wouter, Szarek, Michael, White, Harvey D., Zeiher, Andreas M., Steg, P. Gabriel, Valgimigli, Marco, Islam, Shahidul, Chiang, Chern-En, Gotcheva, Nina, Kim, Hyo-Soo, Kim, Sang-Hyun, Morais, Joao, Pordy, Robert, and Scemama, Michel

Published
2023
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23. Relations among spheroidal and spherical harmonics

Author

García-Ancona, Raybel, Morais, João, and Porter, R. Michael

Subjects
Mathematics - Complex Variables, 30G35, 30C65, 42C30
Abstract

A contragenic function in a domain $\Omega\subseteq\mathbf{R}^3$ is a reduced-quaternion-valued (i.e. the last coordinate function is zero) harmonic function, which is orthogonal in $L^2(\Omega)$ to all monogenic functions and their conjugates. The notion of contragenicity depends on the domain and thus is not a local property, in contrast to harmonicity and monogenicity. For spheroidal domains of arbitrary eccentricity, we relate standard orthogonal bases of harmonic and contragenic functions for one domain to another via computational formulas. This permits us to show that there exist nontrivial contragenic functions common to the spheroids of all eccentricities.

Published
2019

26. The interacting multiverse and its effect on the cosmic microwave background

Author

Bouhmadi-López, Mariam, Kraemer, Manuel, Morais, João, and Robles-Pérez, Salvador

Subjects
General Relativity and Quantum Cosmology, Astrophysics - Cosmology and Nongalactic Astrophysics, High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract

We study a toy model of a multiverse consisting of canonically quantized universes that interact with each other on a quantum level based on a field-theoretical formulation of the Wheeler-DeWitt equation. This interaction leads to the appearance of a pre-inflationary phase in the evolution of the individual universes. We analyze scalar perturbations within the model and calculate the influence of the pre-inflationary phase onto the power spectrum of these perturbations. The result is that there is a suppression of power on large scales, which can describe well the Planck 2018 data for the cosmic microwave background anisotropies and could thus indicate a possible solution to the observed quadrupole discrepancy., Comment: 28 pages, 8 figures, clarifications and references added, published in the Journal of Cosmology and Astroparticle Physics

Published
2018
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27. Pre-inflation from the multiverse: Can it solve the quadrupole problem in the cosmic microwave background?

Author

Morais, João, Bouhmadi-López, Mariam, Kraemer, Manuel, and Robles-Pérez, Salvador

Subjects
General Relativity and Quantum Cosmology, Astrophysics - Cosmology and Nongalactic Astrophysics, High Energy Physics - Theory
Abstract

We analyze a quantized toy model of a universe undergoing eternal inflation using a quantum-field-theoretical formulation of the Wheeler-DeWitt equation. This so-called third quantization method leads to the picture that the eternally inflating universe is converted to a multiverse in which sub-universes are created and exhibit a distinctive phase in their evolution before reaching an asymptotic de Sitter phase. From the perspective of one of these sub-universes, we can thus analyze the pre-inflationary phase that arises naturally. Assuming that our observable universe is represented by one of those sub-universes, we calculate how this pre-inflationary phase influences the power spectrum of the cosmic microwave background (CMB) anisotropies and analyze whether it can explain the observed discrepancy of the power spectrum on large scales, i.e. the quadrupole issue in the CMB. While the answer to this question is negative in the specific model analyzed here, we point out a possible resolution of this issue., Comment: 15 pages, 9 figures. Correction of typos, one figure added. Accepted for publication in European Physical Journal C

Published
2017
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28. What if? - Exploring the Multiverse through Euclidean wormholes

Author

Bouhmadi-López, Mariam, Kraemer, Manuel, Morais, João, and Robles-Pérez, Salvador

Subjects
General Relativity and Quantum Cosmology, High Energy Physics - Theory
Abstract

We present Euclidean wormhole solutions describing possible bridges within the multiverse. The study is carried out in the framework of the third quantization. The matter content is modelled through a scalar field which supports the existence of a whole collection of universes. The instanton solutions describe Euclidean solutions that connect baby universes with asymptotically de Sitter universes. We compute the tunnelling probability of these processes. Considering the current bounds on the energy scale of inflation and assuming that all the baby universes are nucleated with the same probability, we draw some conclusions about what are the universes more likely to tunnel and therefore undergo a standard inflationary era., Comment: 12 pages, 5 figures. Explanations improved. Version accepted in EPJC

Published
2017
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29. What if gravity becomes really repulsive in the future?

Author

Albarran, Imanol, Bouhmadi-López, Mariam, and Morais, João

Subjects
General Relativity and Quantum Cosmology, Astrophysics - Cosmology and Nongalactic Astrophysics, High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract

The current acceleration of the Universe is one of the most puzzling issues in theoretical physics nowadays. We are far from giving an answer on this letter to its true nature. Yet, with the observations we have at hand, we analyse the different patterns that the gravitational potential can show in the future. Surprisingly, gravity not only can get weaker in the near future, it can even become repulsive; or equivalently, the gravitational potential may become negative. We show this remark by using one of the simplest phenomenological model we can imagine for dark energy. We have as well reviewed the statefinder approach of these models. For completeness, we have also showed the behaviour of the density contrast of dark matter and dark energy for these simple (yet illustrative models). Our results are displayed at present and how they evolve in the future., Comment: 7 pages, 3 figures. Further explanations provided. Version accepted in EPJC

Published
2017
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30. Cosmic infinity: A dynamical system approach

Author

Bouhmadi-López, Mariam, Marto, João, Morais, João, and Silva, César M.

Subjects
General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology, High Energy Physics - Theory, Mathematical Physics
Abstract

Dynamical system techniques are extremely useful to study cosmology. It turns out that in most of the cases, we deal with finite isolated fixed points corresponding to a given cosmological epoch. However, it is equally important to analyse the asymptotic behaviour of the universe. On this paper, we show how this can be carried out for 3-forms model. In fact, we show that there are fixed points at infinity mainly by introducing appropriate compactifications and defining a new time variable that washes away any potential divergence of the system. The richness of 3-form models allows us as well to identify normally hyperbolic non-isolated fixed points., Comment: 19 pages, 9 figures, 3 tables. A new section added. Explanations improved. Version accepted in JCAP

Published
2016
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31. Cosmological perturbations in an effective and genuinely phantom dark energy Universe

Author

Albarran, Imanol, Bouhmadi-López, Mariam, and Morais, João

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract

We carry out an analysis of the cosmological perturbations in general relativity for three different models which are good candidates to describe the current acceleration of the Universe. These three set-ups are described classically by perfect fluids with a phantom nature and represent deviations from the most widely accepted $\Lambda$CDM model. In addition, each of the models under study induce different future singularities or abrupt events known as (i) Big Rip, (ii) Little Rip and (iii) Little Sibling of the Big Rip. Only the first one is regarded as a true singularity since it occurs at a finite cosmic time. For this reason, we refer to the others as abrupt events. With the aim to find possible footprints of this scenario in the Universe matter distribution, we not only obtain the evolution of the cosmological scalar perturbations but also calculate the matter power spectrum for each model. We have carried the perturbations in the absence of any anisotropic stress and within a phenomenological approach for the speed of sound. We constrain observationally these models using several measurements of the growth rate function, more precisely $f\sigma_8$, and compare our results with the observational ones., Comment: 23 pages, 4 figures. Discussion extended further and an appendix added. Version to appear in Physics of the Dark Universe

Published
2016
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32. Identification of Clinically Relevant Rules: An Interpretable Approach for CVD Risk Assessment

Author

Paredes, Simão, Henriques, Jorge, Rocha, Teresa, de Carvalho, Paulo, Morais, João, Magjarevic, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, Jarm, Tomaz, editor, Cvetkoska, Aleksandra, editor, Mahnič-Kalamiza, Samo, editor, and Miklavcic, Damijan, editor

Published
2021
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33. Apolipoprotein B, Residual Cardiovascular Risk After Acute Coronary Syndrome, and Effects of Alirocumab

Author

Hagström, Emil, Steg, P. Gabriel, Szarek, Michael, Bhatt, Deepak L., Bittner, Vera A., Danchin, Nicolas, Diaz, Rafael, Goodman, Shaun G., Harrington, Robert A., Jukema, J. Wouter, Liberopoulos, Evangelos, Marx, Nikolaus, McGinniss, Jennifer, Manvelian, Garen, Pordy, Robert, Scemama, Michel, White, Harvey D., Zeiher, Andreas M., Schwartz, Gregory G., Schwartz, Gregory G., Bhatt, Deepak L., Bittner, Vera A., Diaz, Rafael, Goodman, Shaun G., Harrington, Robert A., Jukema, J. Wouter, Szarek, Michael, White, Harvey D., Zeiher, Andreas M., Tricoci, Pierluigi, Roe, Matthew T., Mahaffey, Kenneth W., Edelberg, Jay M., Hanotin, Corinne, Lecorps, Guillaume, Moryusef, Angèle, Pordy, Robert, Sasiela, William J., Tamby, Jean-François, Diaz, Rafael, Aylward, Philip E, Drexel, Heinz, Sinnaeve, Peter, Dilic, Mirza, Lopes, Renato D., Gotcheva, Nina N, Goodman, Shaun G., Prieto, Juan-Carlos, Yong, Huo, López-Jaramillo, Patricio, Pećin, Ivan, Reiner, Zeljko, Ostadal, Petr, Poulsen, Steen Hvitfeldt, Viigimaa, Margus, Nieminen, Markku S, Danchin, Nicolas, Chumburidze, Vakhtang, Marx, Nikolaus, Liberopoulos, Evangelos, Carlos, Pablo, Valdovinos, Montenegro, Tse, Hung-Fat, Kiss, Robert Gabor, Xavier, Denis, Zahger, Doron, Valgimigli, Marco, Kimura, Takeshi, Kim, Hyo Soo, Kim, Sang-Hyun, Erglis, Andrejs, Laucevicius, Aleksandras, Kedev, Sasko, Yusoff, Khalid, Ramos López, Gabriel Arturo, Alings, Marco, White, Harvey D., Halvorsen, Sigrun, Correa Flores, Roger M, Sy, Rody G., Budaj, Andrzej, Morais, Joao, Dorobantu, Maria, Karpov, Yuri, Ristic, Arsen D., Chua, Terrance, Murin, Jan, Fras, Zlatko, Dalby, Anthony J, Tuñón, José, de Silva, H. 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2022
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35. Lipoprotein(a) and Benefit of PCSK9 Inhibition in Patients With Nominally Controlled LDL Cholesterol

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Schwartz, Gregory G., Gabriel Steg, P.h., Bhatt, Deepak L., Bittner, Vera A., Diaz, Rafael, Goodman, Shaun G., Harrington, Robert A., Jukema, J. Wouter, Szarek, Michael, White, Harvey D., Zeiher, Andreas M., Tricoci, Pierluigi, Roe, Matthew T., Mahaffey, Kenneth W., Edelberg, Jay M., Hanotin, Corinne, Lecorps, Guillaume, Moryusef, Angèle, Pordy, Robert, Sasiela, William J., Tamby, Jean-François, Aylward, Philip E., Drexel, Heinz, Sinnaeve, Peter, Dilic, Mirza, Lopes, Renato D., Gotcheva, Nina N., Prieto, Juan-Carlos, Yong, Huo, López-Jaramillo, Patricio, Pećin, Ivan, Reiner, Zeljko, Ostadal, Petr, Poulsen, Steen Hvitfeldt, Viigimaa, Margus, Nieminen, Markku S., Danchin, Nicolas, Chumburidze, Vakhtang, Marx, Nikolaus, Liberopoulos, Evangelos, Montenegro Valdovinos, Pablo Carlos, Tse, Hung-Fat, Kiss, Robert Gabor, Xavier, Denis, Zahger, Doron, Valgimigli, Marco, Kimura, Takeshi, Kim, Hyo Soo, Kim, Sang-Hyun, Erglis, Andrejs, Laucevicius, Aleksandras, Kedev, Sasko, Yusoff, Khalid, Ramos López, Gabriel Arturo, Alings, Marco, Halvorsen, Sigrun, Correa Flores, Roger M., Sy, Rody G., Budaj, Andrzej, Morais, Joao, Dorobantu, Maria, Karpov, Yuri, Ristic, Arsen D., Chua, Terrance, Murin, Jan, Fras, Zlatko, Dalby, Anthony J., Tuñón, José, Asita de Silva, H., Hagström, Emil, Landmesser, Ulf, Müller, Christian, Chiang, Chern-En, Sritara, Piyamitr, Guneri, Sema, Parkhomenko, Alexander, Ray, Kausik K., Moriarty, Patrick M., Vogel, Robert, Chaitman, Bernard, Kelsey, Sheryl F., Olsson, Anders G., Rouleau, Jean-Lucien, Simoons, Maarten L., Alexander, Karen, Meloni, Chiara, Rosenson, Robert, Sijbrands, Eric J.G., Alexander, John H., Armaganijan, Luciana, Bagai, Akshay, Bahit, Maria Cecilia, Brennan, J. Matthew, Clifton, Shaun, DeVore, Adam D., Deloatch, Shalonda, Dickey, Sheila, Dombrowski, Keith, Ducrocq, Grégory, Eapen, Zubin, Endsley, Patricia, Eppinger, Arleen, Harrison, Robert W., Hess, Connie Ng, Hlatky, Mark A., Jordan, Joseph Dedrick, Knowles, Joshua W., Kolls, Bradley J., Kong, David F., Leonardi, Sergio, Lillis, Linda, Maron, David J., Marcus, Jill, Mathews, Robin, Mehta, Rajendra H., Mentz, Robert J., Moreira, Humberto Graner, Patel, Chetan B., Pereira, Sabrina Bernardez, Perkins, Lynn, Povsic, Thomas J., Puymirat, Etienne, Jones, William Schuyler, Shah, Bimal R., Sherwood, Matthew W., Stringfellow, Kenya, Sujjavanich, Darin, Toma, Mustafa, Trotter, Charlene, van Diepen, Sean F.P., Wilson, Matthew D., Tze-Kay Yan, Andrew, Schiavi, Lilia B., Garrido, Marcelo, Alvarisqueta, Andrés F., Sassone, Sonia A., Bordonava, Anselmo P., Alves De Lima, Alberto E., Schmidberg, Jorge M., Duronto, Ernesto A., Caruso, Orlando C., Novaretto, Leonardo P., Hominal, Miguel Angel, Montaña, Oscar R., Caccavo, Alberto, Gomez Vilamajo, Oscar A., Lorenzatti, Alberto J., Cartasegna, Luis R., Paterlini, Gustavo A., Mackinnon, Ignacio J., Caime, Guillermo D., Amuchastegui, Marcos, Salomone, Oscar, Codutti, Oscar R., Jure, Horacio O., Bono, Julio O.E., Hrabar, Adrian D., Vallejos, Julio A., Ahuad Guerrero, Rodolfo A., Novoa, Federico, Patocchi, Cristian A., Zaidman, Cesar J., Giuliano, Maria E., Dran, Ricardo D., Vico, Marisa L., Carnero, Gabriela S., Guzman, Pablo N., Medrano Allende, Juan C., Garcia Brasca, Daniela F., Bustamante Labarta, Miguel H., Nani, Sebastian, Blumberg, Eduardo D.S., Colombo, Hugo R., Liberman, Alberto, Fuentealba, Victorino, Luciardi, Hector L., Waisman, Gabriel D., Berli, Mario A., Garcia Duran, Ruben O., Cestari, Horacio G., Luquez, Hugo A., Giordano, Jorge A., Saavedra, Silvia S., Zapata, Gerardo, Costamagna, Osvaldo, Llois, Susana, Waites, Jonathon H., Collins, Nicholas, Soward, Allan, Hii, Chris L.S., Shaw, James, Arstall, Margaret A., Horowitz, John, Ninio, Daniel, Rogers, James F., Colquhoun, David, Oqueli Flores, Romulo E., Roberts-Thomson, Philip, Raffel, Owen, Lehman, Sam J., Aroney, Constantine, Coverdale, Steven G.M., Garrahy, Paul J., Starmer, Gregory, Sader, Mark, Carroll, Patrick A., Dick, Ronald, Zweiker, Robert, Hoppe, Uta, Huber, Kurt, Berger, Rudolf, Delle-Karth, Georg, Frey, Bernhard, Faes, Dirk, Hermans, Kurt, Pirenne, Bruno, Leone, Attilio, Hoffer, Etienne, Vrolix, Mathias C.M., De Wolf, Luc, Wollaert, Bart, Castadot, Marc, Dujardin, Karl, Beauloye, Christophe, Vervoort, Geert, Striekwold, Harry, Convens, Carl, Roosen, John, Barbato, Emanuele, Claeys, Marc, Cools, Frank, Terzic, Ibrahim, Barakovic, Fahir, Midzic, Zlatko, Pojskic, Belma, Fazlibegovic, Emir, Durak-Nalbantic, Azra, Kulić, Mehmed, Vulic, Dusko, Muslibegovic, Adis, Goronja, Boris, Reis, Gilmar, Sousa, Luciano, Nicolau, Jose C., Giorgeto, Flavio E., Silva, Ricardo P., Maia, Lilia Nigro, Rech, Rafael, Rossi, Paulo R.F., Cerqueira, Maria José A.G., Duda, 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Senaratne, Manohara, Stone, James, Kornder, Jan, Pearce, Stephen, Dion, Danielle, Savard, Daniel, Pesant, Yves, Pandey, Amritanshu, Robinson, Simon, Gosselin, Gilbert, Vizel, Saul, Hoag, Gordon, Bourgeois, Ronald, Morisset, Anne, Sabbah, Eric, Sussex, Bruce, Kouz, Simon, MacDonald, Paul, Diaz, Ariel, Michaud, Nicolas, Fell, David, Leung, Raymond, Vuurmans, Tycho, Lai, Christopher, Nigro, Frank, Davies, Richard, Nogareda, Gustavo, Vijayaraghavan, Ram, Ducas, John, Lepage, Serge, Mehta, Shamir, Cha, James, Dupuis, Robert, Fong, Peter, Lutchmedial, Sohrab, Rodes-Cabau, Josep, Fadlallah, Hussein, Cleveland, David, Huynh, Thao, Bata, Iqbal, Hameed, Adnan, Pincetti, Cristian, Potthoff, Sergio, Prieto, Juan C., Acevedo, Monica, Aguirre, Arnoldo, Vejar, Margarita, Yañez, Mario, Araneda, Guillermo, Fernandez, Mauricio, Perez, Luis, Varleta, Paola, Florenzano, Fernando, Huidobro, Laura, Raffo, Carlos A., Olivares, Claudia, Nahuelpan, Leonardo, Montecinos, Humberto, Chen, Jiyan, Dong, Yugang, Huang, Weijian, Wang, Jianzhong, Huang, Shi'An, Yao, Zhuhua, Li, Xiang, Cui, Lan, Lin, Wenhua, Sun, Yuemin, Wang, Jingfeng, Li, Jianping, Zhang, Xuelian, Zhu, Hong, Chen, Dandan, Huang, Lan, Dong, Shaohong, Su, Guohai, Xu, Biao, Su, Xi, Cheng, Xiaoshu, Lin, Jinxiu, Zong, Wenxia, Li, Huanming, Feng, Yi, Xu, Dingli, Yang, Xinchun, Ke, Yuannan, Lin, Xuefeng, Zhang, Zheng, Zheng, Zeqi, Luo, Zhurong, Chen, Yundai, Ding, Chunhua, Zhong, Yi, Zheng, Yang, Li, Xiaodong, Peng, Daoquan, Zhao, Shuiping, Li, Ying, Liu, Xuebo, Wei, Meng, Liu, Shaowen, Yu, Yihua, Qu, Baiming, Jiang, Weihong, Zhou, Yujie, Zhao, Xingsheng, Yuan, Zuyi, Guo, Ying, Xu, Xiping, Shi, Xubo, Ge, Junbo, Fu, Guosheng, Bai, Feng, Fang, Weiyi, Shou, Xiling, Yang, Xiangjun, Wang, Jian'An, Xiang, Meixiang, Sun, Yingxian, Lu, Qinghua, Zhang, Ruiyan, Zhu, Jianhua, Xu, Yizhou, Fan, Zhongcai, Li, Tianchang, Wu, Chun, Jaramillo, Nicolas, Vallejo, Gregorio Sanchez, Luna Botia, Diana C., Lopez, Rodrigo Botero, Molina De Salazar, Dora I., Cadena Bonfanti, Alberto J., Aroca, Carlos Cotes, Higuera, Juan Diego, Blanquicett, Marco, Barrera Silva, Sandra I., Garcia Lozada, Henry J., Coronel Arroyo, Julian A., Accini Mendoza, Jose L., Fernandez Ruiz, Ricardo L., Quintero Ossa, Alvaro M., Manzur Jatin, Fernando G., Herazo, Aristides Sotomayor, Parada, Jeffrey Castellanos, Arambula, Rafael Suarez, Urina Triana, Miguel A., Fernandez Trujillo, Angela M., Strozzi, Maja, Car, Siniša, Jerić, Melita, Miličić, Davor, Benčić, Martina Lovrić, Pintarić, Hrvoje, Prvulović, Đeiti, Šikić, Jozica, Peršić, Viktor, Mileta, Dean, Štambuk, Kresimir, Babić, Zdravko, Tomulic, Vjekoslav, Lukenda, Josip, Mejic-Krstulovic, Stanka, Starcevic, Boris, Spinar, Jindrich, Horak, David, Velicka, Zdenek, Stasek, Josef, Alan, David, Machova, Vilma, Linhart, Ales, Novotny, Vojtech, Kaucak, Vladimir, Rokyta, Richard, Naplava, Robert, Coufal, Zdenek, Adamkova, Vera, Podpera, Ivo, Zizka, Jiri, Motovska, Zuzana, Marusincova, Ivana, Svab, Premysl, Heinc, Petr, Kuchar, Jiri, Povolny, Petr, Matuska, Jiri, Poulsen, Steen H., Raungaard, Bent, Clemmensen, Peter, Bang, Lia E., May, Ole, Bøttcher, Morten, Hove, Jens D., Frost, Lars, Gislason, Gunnar, Larsen, John, Johansen, Peter Betton, Hald, Flemming, Johansen, Peter, Jeppesen, Jørgen, Nielsen, Tonny, Kristensen, Kjeld S., Walichiewicz, Piotr Maria, Lomholdt, Jens D., Klausen, Ib C., Nielsen, Peter Kaiser, Davidsen, Flemming, Videbaek, Lars, Soots, Mai, Vahula, Veiko, Hedman, Anu, Soopõld, Üllar, Märtsin, Kaja, Jurgenson, Tiina, Kristjan, Arved, Huikuri, Heikki, Pierre Coste, Juhani Airaksinen, Ferrari, Emile, Morel, Olivier, Montalescot, Gilles, Machecourt, Jacques, Barone-Rochette, Gilles, Mansourati, Jacques, Cottin, Yves, Leclercq, Florence, Belhassane, Abdelkader, Delarche, Nicolas, Boccara, Franck, Paganelli, Franck, Clerc, Jérôme, Schiele, Francois, Aboyans, Victor, Probst, Vincent, Berland, Jacques, Lefèvre, Thierry, Citron, Bernard, Khintibidze, Irakli, Shaburishvili, Tamaz, Pagava, Zurab, Ghlonti, Ramaz, Lominadze, Zaza, Khabeishvili, George, Hemetsberger, Rayyan, Edward, Kemala, Rauch-Kröhnert, Ursula, Stratmann, Matthias, Appel, Karl-Friedrich, Schmidt, Ekkehard, Omran, Heyder, Stellbrink, Christoph, Dorsel, Thomas, Lianopoulos, Emmanouil, Vöhringer, Hans Friedrich, Marx, Roger, Zirlik, Andreas, Schellenberg, Detlev, Heitzer, Thomas, Laufs, Ulrich, Werner, Christian, Gielen, Stephan, Nuding, Sebastian, Winkelmann, Bernhard, Behrens, Steffen, Sydow, Karsten, Karakas, Mahir, Simonis, Gregor, Muenzel, Thomas, Werner, Nikos, Leggewie, Stefan, Böcker, Dirk, Braun-Dullaeus, Rüdiger, Toursarkissian, Nicole, Jeserich, Michael, Weißbrodt, Matthias, Schaeufele, Tim, Weil, Joachim, Völler, Heinz, Waltenberger, Johannes, Natour, Mohammed, Schmitt, Susanne, Müller-Wieland, Dirk, Steiner, Stephan, Heidenreich, Lothar, Offers, Elmar, Gremmler, Uwe, Killat, Holger, Rieker, Werner, Patsilinakos, Sotiris, Kartalis, Athanasios, Manolis, Athanassios, Sionis, Dimitrios, Chachalis, Geargios, Skoumas, Ioannis, Athyros, Vasilios, Vardas, Panagiotis, Parthenakis, Frangkiskos, Lekakis, John, Hatzitolios, Apostolos, Fausto Ovando, Sergio R., Arango Benecke, Juan L., Rodriguez De Leon, Edgar R., Yan, Bryan P.Y., Siu, David C.W., Turi, Tibor, Merkely, Bela, Ungi, Imre, Lupkovics, Geza, Nagy, Lajos, Katona, András, Édes, István, Müller, Gábor, Horvath, Iván, Kapin, Tibor, Szigeti, Zsolt, Faluközy, József, Kumbla, Mukund, Sandhu, Manjinder, Annam, Sharath, Proddutur, Naveen Reddy, Regella, Reddy, Premchand, Rajendra K., Mahajan, Ajaykumar, Pawar, Sudhir, Abhyanakar, Atul D., Kerkar, Prafulla, Govinda, Ravishankar A., Oomman, Abraham, Sinha, Dhurjati, Patil, Sachin N., Kahali, Dhiman, Sawhney, Jitendra, Joshi, Abhijeet B., Chaudhary, Sanjeev, Harkut, Pankaj, Guha, Santanu, Porwal, Sanjay, Jujjuru, Srimannarayana, Pothineni, Ramesh B., Monteiro, Minguel R., Khan, Aziz, Iyengar, Shamanna S., Grewal, Jasprakash Singh, Chopda, Manoj, Fulwani, Mahesh C., Patange, Aparna, Sachin, Patil, Chopra, Vijay K., Goyal, Naresh K., Shinde, Rituparna, Manakshe, Gajendra V., Patki, Nitin, Sethi, Sumeet, Munusamy, Vengatesh, Sunil Thanvi, Sunil Karnaand, Adhyapak, Srilakshmi, Patil, Chandrakant, Pandurangi, Ulhas, Mathur, Rishabh, Gupta, Jugal, Kalashetti, Suhas, Bhagwat, Ajit, Raghuraman, Bagirath, Yerra, Shiv Kumar, Bhansali, Prasant, Borse, Rohidas, Rahul, Patil, Das, Srihari, Kumar, Vinay, Abdullakutty, Jabir, Saathe, Shireesh, Palimkar, Priya, Abdullkutty, Jabir, Sathe, Shireesh, Atar, Shaul, Shechter, Michael, Mosseri, Morris, Arbel, Yaron, Ehud, Chorin, Ofer, Havakuk, Lotan, Chaim, Rosenschein, Uri, Katz, Amos, Henkin, Yaakov, Francis, Adi, Klutstein, Marc, Nikolsky, Eugenia, Zukermann, Robert, Turgeman, Yoav, Halabi, Majdi, Marmor, Alon, Kornowski, Ran, Jonas, Michael, Amir, Offer, Hasin, Yonathan, Rozenman, Yoseph, Fuchs, Shmuel, Zvi, Vered, Hussein, Osamah, Gavish, Dov, Vered, Zvi, Caraco, Yoseph, Elias, Mazen, Tov, Naveh, Wolfovitz, Efrat, Lishner, Michael, Elias, Nizar, Piovaccari, Giancarlo, De Pellegrin, Annamaria, Garbelotto, Raffaella, Guardigli, Gabriele, Marco, Valgimigli, Licciardello, Giovanni, Auguadro, Carla, Scalise, Filippo, Cuccia, Claudio, Salvioni, Alessandro, Musumeci, Giuseppe, Senni, Michelle, Calabrò, Paolo, Novo, Salvatore, Faggiano, Pompilio, Metra, Marco, De Cesare, Nicoletta B., Berti, Sergio, Cavallini, Claudio, Puccioni, Enrico, Galvani, Marcello, Tespili, Maurizio, Piatti, Piermarco, Palvarini, Michela, De Luca, Giuseppe, Violini, Roberto, De Leo, Alessandro, Olivari, Zoran, Filardi, Pasquale Perrone, Ferratini, Maurizio, Racca, Vittorio, Dai, Kazuoki, Shimatani, Yuji, Kamiya, Haruo, Ando, Kenji, Takeda, Yoshihiro, Morino, Yoshihiro, Hata, Yoshiki, Kimura, Kazuo, Kishi, Koichi, Michishita, Ichiro, Uehara, Hiroki, Higashikata, Toshinori, Hirayama, Atsushi, Hirooka, Keiji, Doi, Yasuji, Sakagami, Satoru, Taguchi, Shuichi, Koike, Akihiro, Fujinaga, Hiroyuki, Koba, Shinji, Kozuma, Ken, Kawasaki, Tomohiro, Ono, Yujiro, Shimizu, Masatoshi, Katsuda, Yousuke, Wada, Atsuyuki, Shinke, Toshiro, Ako, Junya, Fujii, Kenshi, Takahashi, Toshiyuki, Sakamoto, Tomohiro, Nakao, Koichi, Furukawa, Yutaka, Sugino, Hiroshi, Tamura, Ritsu, Mano, Toshiaki, Uematsu, Masaaki, Utsu, Noriaki, Ito, Kashima, Haraguchi, Takuya, Sato, Katsuhiko, Ueda, Yasunori, Nishibe, Akira, Fujimoto, Kazuteru, Masutani, Motomaru, Yoon, Jung Han, Kim, Hack-Lyoung, Park, Hun Sik, Chae, In-Ho, Kim, Moo Hyun, Jeong, Myung Ho, Rha, Seungwoon, Kim, Chongjin, Kim, Hae Young, Hong, Taekjong, Tahk, Seung-Jea, Kim, Youngkwon, Busmane, Arija, Pontaga, Natalija, Strelnieks, Aldis, Mintale, Iveta, Sime, Iveta, Petrulioniene, Zaneta, Kavaliauskiene, Roma, Jurgaitiene, Ruta, Sakalyte, Gintare, Slapikas, Rimvydas, Norkiene, Sigute, Misonis, Nerijus, Kibarskis, Aleksandras, Kubilius, Raimondas, Bojovski, Stojko, Lozance, Nensi, Kjovkaroski, Aleksandar, Doncovska, Snezana, Ong, Tiong Kiam, Kasim, Sazzli, Maskon, Oteh, Kandasamy, Balachandran, Liew, Houng B., Izani Wan Mohamed, Wan Mohd, Castillo, Armando García, Calvillo, Jorge Carrillo, Campos, Pedro Fajardo, Núñez Fragoso, Juan Carlos, Bayram Llamas, Edmundo Alfredo, Alcocer Gamba, Marco Antonio, Madrigal, Jaime Carranza, González Salas, Luis Gerardo, Rosas, Enrique López, González Díaz, Belinda, Salcido Vázquez, Eduardo, Nacoud Ackar, Alfredo, Antonio Llamas Esperón, Guillermo, Rodolfo Martínez Sánchez, Carlos, Guerrero De Leon, María, Suarez Otero, Rodrigo, Fanghänel Salmón, Guillermo, Pérez Ríos, Jesús Antonio, Garza Ruíz, José Angel, Breedveld, Robert W., Feenema-Aardema, Margriet, Borger-Van Der Burg, Alida, Hoogslag, Pieter A.M., Suryapranata, Harry, Oomen, Antonius, Van Haelst, Paulus, Feenema-Aradema, Margriet, Wiersma, Jacobijne J., Basart, Dirk, Van Der Wal, Ruud M.A., Zwart, Peter, Monraats, Pascalle, Van Kesteren, Henricus, Karalis, Ioannis, Jukema, Johan, Verdel, Gerardus J.E., Brueren, Bart R.G., Troquay, Roland PTh, Viergever, Eric P., Al-Windy, Nadea Y.Y., Bartels, Gerard L., Cornel, Jan H., Hermans, Walter R.M., Herrman, Johannes P.R., Bos, Robert J., Groutars, Reginald G.E.J., Van Der Zwaan, Coenraad C., Kaplan, Refik, Lionarons, Raymond, Ronner, Eelko, Groenemeijer, Bjorn E., Bronzwaer, Patrick N.A., Liem, Anho A.H., Rensing, Bernard J.W.M., Bokern, Marcel J.J.A., Nijmeijer, Remco, Hersbach, Ferry M.R.J., Willems, Frank F., Gosselink, Antonius T.M., Rasoul, Saman, Elliott, John, Wilkins, Gerard, Fisher, Raewyn, Scott, Douglas, Hart, Hamish, Stewart, Ralph, Harding, Scott, Ternouth, Ian, Fisher, Nicholas, Wilson, Samuel, Aitken, Denise, Anscombe, Russell, Davidson, Laura, Tomala, Tadeusz, Nygård, Ottar, Sparby, Jon Arne, Andersen, Kjell, Gullestad, Lars, Jortveit, Jarle, Munk, Peter S., Singsaas, Erlend gyllensten, Hurtig, Ulf, Calderon Ticona, Jorge R., Durand Velasquez, Julio R., Negron Miguel, Sandra A., Sanabria Perez, Enrique S., Carrion Chambilla, Jesus M., Chavez Ayala, Carlos A., Castillo Leon, Reynaldo P., Vargas Gonzales, Rolando J., Hernandez Zuniga, Jose D., Camacho Cosavalente, Luis A., Bravo Mannucci, Jorge E., Landeo, Javier Heredia, Llerena Navarro, Nassip C., Roldan Concha, Yudy M., Rodriguez Chavez, Víctor E., Anchante Hernandez, Henry A., Zea Nunez, Carlos A., Ramos, Walter Mogrovejo, Ferrolino, Arthur, Sy, Rosa Allyn G., Tirador, Louie, Matiga, Generoso, Coching, Raul Martin, Bernan, Alisa, Rogelio, Gregorio, Morales, Dante D., Tan, Edgar, Sulit, Dennis Jose, Wlodarczak, Adrian, Jaworska, Krystyna, Skonieczny, Grzegorz, Pawlowicz, Lidia, Wojewoda, Pawel, Busz-Papiez, Benita, Bednarski, Janusz, Goch, Aleksander, Staneta, Pawel, Dulak, Elzbieta, Saminski, Krzysztof, Krasowski, Wlodzimierz, Sudnik, Wanda, Zurakowski, Aleksander, Skorski, Marcin, Lysek, Roman, Miklaszewicz, Beata, Kubica, Jacek, Lipko, Jan Andrzej, Kostarska-Srokosz, Edyta, Piepiorka, Marek, Drzewiecka, Anna, Sciborski, Ryszard, Stasiewski, Arkadiusz, Blicharski, Tomasz, Bystryk, Leszek, Szpajer, Michal, Korol, Marek, Czerski, Tomasz, Mirek-Bryniarska, Ewa, Gniot, Jacek, Lubinski, Andrzej, Gorny, Jerzy, Franek, Edward, Raczak, Grzegorz, Szwed, Hanna, Monteiro, Pedro, Bastos, Jose Mesquita, Pereira, Helder H., Martins, Dinis, Seixo, Filipe, Mendonça, Carlos, Botelho, Ana, Caetano, Francisca, Minescu, Bogdan, Istratoaie, Octavian, Tesloianu, Dan N., Cristian, Gabriel, Dumitrescu, Silviu, Podoleanu, Cristian G.C., Constantinescu, Mircea C.A., Bengus, Cristina M., Militaru, Constantin, Rosu, Doina, Parepa, Irinel R., Matei, Adrian V., Alexandru, Tom M., Malis, Mihaela, Coman, Ioan, Stanescu-Cioranu, Rodica, Dimulescu, Doina, Shvarts, Yury, Orlikova, Olga, Kobalava, Zhanna, Barbarash, Olga L., Markov, Valentin, Lyamina, Nadezhda, Gordienko, Alexander, Zrazhevsky, Konstantin, Vishnevsky, Alexander Y., Gurevich, Victor, Stryuk, Raisa, Lomakin, Nikita V., Bokarev, Igor, Khlevchuk, Tatiana, Shalaev, Sergey, Khaisheva, Larisa, Chizhov, Petr, Viktorova, Inna, Osokina, Natalya, Shchekotov, Vladimir, Akatova, Evgenia, Chumakova, Galina, Libov, Igor, Voevoda, Mikhail I., Tretyakova, Tatyana V., Baranov, Evgeny, Shustov, Sergey, Yakushin, Sergey, Gordeev, Ivan, Khasanov, Niiaz, Reshetko, Olga, Sotnikova, Tatiana, Molchanova, Olga, Nikolaev, Konstantin, Gapon, Liudmila, Baranova, Elena, Shogenov, Zaur, Kosmachova, Elena, Karpov, Yuriy, Povzun, Anton, Egorova, Liudmila, Tyrenko, Vadim V., Ivanov, Igor G., Ilya, Masterov, Kanorsky, Sergey, Simic, Dragan, Ivanovic, Nikola, Davidovic, Goran, Tasic, Nebojsa, Asanin, Milika R., Stojic, Stevo, Apostolovic, Svetlana R., Ilic, Stevan, Tosic, Biljana Putnikovic, Stankovic, Aleksandar, Arandjelovic, Aleksandra, Radovanovic, Slavica, Todic, Branislava, Balinovac, Jovan, Dincic, Dragan V., Seferovic, Petar, Karadzic, Ana, Dodic, Slobodan, Dimkovic, Sinisa, Jakimov, Tamara, Poh, Kian-Keong, Ong, Hean Yee, I-Shing, Justin Tang, Micko, Karol, Nociar, Jan, Pella, Daniel, Fulop, Peter, Hranai, Marian, Palka, Juraj, Mazur, Juraj, Majercák, Ivan, Dzupina, Andrej, Fazekas, František, Gonsorcik, Jozef, Bugan, Viliam, Selecky, Juraj, Kamensky, Gabriel, Strbova, Jaroslava, Smik, Rudolf, Dukat, Andrej, Olexa, Peter, Žuran, Ivan, Poklukar, Janez, Šuligoj, Nataša Černič, Cevc, Matija, Cyster, Henry P., Ranjith, Naresh, Corbett, Clive, Bayat, Junaid, Makotoko, Ellen Makoali, du Toit Theron, Hendrik, Kapp, Ilse E., de V Basson, Matthys M., Lottering, Hanlie, Van Aswegen, Dina, Van Zyl, Louis J., Sebastian, Peter J., Pillay, Thayabran, Saaiman, Jan A., Commerford, Patrick J., Cassimjee, Soraya, Riaz, Garda, Ebrahim, Iftikhar O., Sarvan, Mahomed, Mynhardt, Joseph H., Reuter, Helmuth, Moodley, Rajendran, Vida, Manuel, Cequier Fillat, Angel R., Peris, Vicente Bodí, Jimenez, Francisco Fuentes, Marín, Francisco, Cruz Fernández, Jose M., Hidalgo Urbano, Rafael Jesus, Gil-Extremera, Blas, Toledo, Pablo, Diz, Fernando Worner, Garcia-Dorado, David, Iñiguez, Andres, Fernández, José Tuñón, Gonzalez-Juanatey, Jose R., Portales, Javier Fernandez, Murillo, Fernando Civeira, Pericas, Laia Matas, Zamorano, Jose Luis, De Mora Martin, Manuel, Cortada, Jordi Bruguera, Alonso Martin, Joaquin J., Serrano Antolin, Jose Maria, De Berrazueta Fernández, José R., Vázquez de Prada, José Antonio, Díaz Fernández, Jose Francisco, García Lledó, José Alberto, Sales, Juan Cosín, Rodriguez, Javier Botas, Tragant, Gabriel Gusi, Benedicto, Amparo, Gonzalez-Juanatey, Carlos, Potau, Mercedes Camprubí, Perez, Ignacio Plaza, De La Tassa, César Morís, Loma-Osorio Rincon, Pablo, Recena, Javier Balaguer, Escudier, Juan M., Payeras, Antonio Coca, Orcajo, Norberto Alonso, Valdivielso, Pedro, Constantine, Godwin, Haniffa, Ruvaiz, Tissera, Nirmali, Amarasekera, Stanley, Ponnamperuma, Chandrike, Fernando, Nimali, Fernando, Kaputella, Jayawardena, Jayanthimala, Wijeyasingam, Santharaj, Ranasinghe, Gotabhaya, Ekanayaka, Ruvan, Mendis, Sepalika, Senaratne, Vajira, Mayurathan, Gnanamoorthy, Rajapaksha, Ajantha, Sirisena, Thilak, Herath, Jagath I., Amarasena, Naomali, Berglund, Stefan, Rasmanis, Gundars, Vedin, Ola, Witt, Nils, Mourtzinis, Georgios, Nicol, Peter, Hansen, Ole, Romeo, Stefano, Jensen, Steen Agergaard, Torstensson, Ingemar, Ahremark, Ulf, Sundelin, Torbjörn, Moccetti, Tiziano, Mach, Francois, Binde, Ronald, Gämperli, Oliver, Tsai, Wei-Chuan, Ueng, Kwo-Chang, Lai, Wen-Ter, Liu, Ming-En, Hwang, Juey-Jen, Yin, Wei-Hsian, Hsieh, I-Chang, Hsieh, Ming-Jer, Lin, Wei Hsiang, Kuo, Jen-Yuan, Huang, Tsuei-Yuan, Fang, Chih-Yuan, Kaewsuwanna, Pinij, Soonfuang, Wasant, Jintapakorn, Woravut, Sukonthasarn, Apichard, Wongpraparut, Nattawut, Sastravaha, Krisada, Sansanayudh, Nakarin, Kehasukcharoen, Wirash, Piyayotai, Dilok, Chotnoparatpat, Paiboon, Camsari, Ahmet, Kultursay, Hakan, Mutlu, Bulent, Ersanli, Murat, Demirtas, Mustafa, Kirma, Cevat, Ural, Ertan, Koldas, Lale, Karpenko, Oleksandr, Prokhorov, Alexander, Vakaluyk, Ihor, Myshanych, Halyna, Reshotko, Dmytro, Batushkin, Valeriy, Rudenko, Leonid, Kovalskyi, Ihor, Kushnir, Mykola, Tseluyko, Vira, Mostovoy, Yuriy, Stanislavchuk, Mykola, Kyiak, Yulian, Karpenko, Yuriy, Malynovsky, Yaroslav, Klantsa, Andriy, Kutniy, Oles, Amosova, Ekaterina, Tashchuk, Viktor, Leshchuk, Oleh, Rishko, Mykola, Kopytsya, Mykola, Yagensky, Andriy, Vatutin, Mykola, Bagriy, Andriy, Barna, Olga M., Ushakov, Olexiy, Dzyak, Georgiy, Goloborodko, Borys, Rudenko, Anatolii, Zheleznyy, Volodymyr, Trevelyan, Jasper, Zaman, Azfar, Lee, Kaeng, Moriarty, Andrew, Aggarwal, Rajesh K., Clifford, Piers, Wong, Yuk-Ki, Iqbal, Syed M.R., Subkovas, Eduardas, Braganza, Denise, Sarkar, David, Storey, Robert, Griffiths, Huw, Mcclure, Sam, Muthusamy, Rangasamy, Smith, Simon, Kurian, John, Levy, Terry, Barr, Craig, Kadr, Honer, Gerber, Robert, Simaitis, Audrius, Soran, Handrean, Mathur, Anthony, Brodison, Adrian, Ayaz, Mohammad, Cheema, Muhammad, Oliver, Richard, Thackray, Simon, Mudawi, Telal, Rahman, Gohar, Sultan, Ayyaz, Reynolds, Timothy, Sharman, David, david Sprigings, Butler, Rob, Wilkinson, Peter, Lip, Gregory Y.H., Halcox, Julian, Gallagher, Sean, Ossei-Gerning, Nicholas, Vardi, Gil, Baldari, Duccio, Brabham, David, Treasure, Charles, II, Dahl, Charles, Palmer, Bruce, Wiseman, Alan, Khan, Abul, Puri, Sanjeev, Mohart, Ann Elizabeth, Ince, Carlos, Flores, Enrique, Wright, Scott, Cheng, Shi-Chi, Rosenberg, Michael, Rogers, William, Jr., Kosinski, Edward, Forgosh, Les, Waltman, Jonathan, Khan, Misal, Shoukfeh, Mohammad, Dagher, Georges, Cambier, Patrick, Lieber, Ira, Kumar, Priya, East, Cara, Krichmar, Perry, Hasan, Mian, White, Lindsey, Knickelbine, Thomas, Haldis, Thomas, Gillespie, Eve, Amidon, Thomas, Suh, David, Arif, Imran, Abdallah, Mouhamad, Akhter, Faiq, Carlson, Eric, D'Urso, Michael, El-Ahdab, Fadi, Nelson, William, Moriarty, Katie, Harris, Barry, Cohen, Steven, Carter, Luther, Doty, Daniel, Sabatino, Kenneth, Haddad, Tariq, Malik, Amir, Rao, Sunder, Mulkay, Angel, Jovin, Ion, Klancke, Kim, Malhotra, Vinay, Devarapalli, Sai K., Koren, Michael, Chandna, Harish, Dodds, George, III, Goraya, Tauqir, Bengston, James, Janik, Matthew, Moran, Joseph, Sumner, Andrew, Kobayashi, John, Davis, William, Yazdani, Shahram, Pasquini, John, Thakkar, Maitreya, Vedere, Amarnath, Leimbach, Wayne, Rider, James, fenton, Sarah, Singh, Narendra, Shah, Anil V., Janosik, Denise, Pepine, Carl, Berman, Brett, Gelormini, Joseph, Daniels, Christopher, Richard, Kerensky, Keating, Friederike, Kondo, Nicholas I., Shetty, Sanjay, Levite, Howard, Waider, Winfried, Takata, Theodore, Abu-Fadel, Mazen, Shah, Vipul, Aggarwal, Rahul, Izzo, Mark, Kumar, Anil, Hattler, Brack, Do, Rose, Link, Chad, Bortnick, Anna, Kinzfogl, George, III, Ghitis, Arnold, Larry, John, Teufel, Edward, Kuhlman, Peter, Mclaurin, Brent, Zhang, Wenwu, Thew, Stephen, Abbas, Jalal, White, Matthew, Islam, Othman, Subherwal, Sumeet, Ranadive, Nandkishore, Vakili, Babak, Gring, Christian, Henderson, David, Schuchard, Timothy, Farhat, Naim, Kline, Geoffrey, Mahal, Sharan, Whitaker, Jack, Speirs, Shawn, Andersen, Rolf, Daboul, Nizar, Horwitz, Phillip, Zahr, Firas, Ponce, George, Jafar, Zubair, Mcgarvey, Joseph, Jr., Panchal, Vipul, Voyce, Stephen, Blok, Thomas, Sheldon, William, Azizad, Masoud M., Schmalfuss, Carsten, Picone, Mark, Pederson, Robert, Herzog, William, Jr., Friedman, Keith, Lindsey, Jason, Nowins, Rosemary, Timothy, Eichenlaub, Leonard, Parilak, Lepor, Norman, El Shahawy, Mahfouz, Weintraub, Howard, Irimpen, Anand, Alonso, Alvaro, May, Wade, Christopher, Daniels, Galski, Thomas, Chu, Alan, Mody, Freny, Ramin, Ebrahimi, Hodes, Zachary, Rossi, Joseph, Rose, Gregory, Fairlamb, James, Lambert, Charles, Jr., Raisinghani, Ajit, Abbate, Antonio, Vetrovec, George, King, Marilyn, Carey, Charles, Gerber, Jaime, Younis, Liwa, Park, Hyeun, Vidovich, Mladen, Knutson, Thomas, Friedman, Dennis, Chaleff, Fred, Loussararian, Arthur, Rozeman, Phillip, Kimmelstiel, Carey, Kuvin, Jeffrey, Silver, Kevin, Foster, Malcolm, Tonnessen, Glen, Espinoza, Andrey, Amlani, Mohamadali, Wali, Andreas, Malozzi, Christopher, Jong, Geert T., Massey, Clara, Wattanakit, Keattiyoat, O'Donnell, Philip J., Singal, Dinesh, Jaffrani, Naseem, Banuru, Sridhar, Fisher, Daniel, Xenakis, Mark, Perlmutter, Neal, Bhagwat, Ravi, Strader, James, Jr., Blonder, Ronald, Akyea-Djamson, Ayim, Labroo, Ajay, Lee, Kwan, Marais, H. John, Claxton, Edmund, Jr., Weiss, Robert, Kathryn, Rohr, Berk, Martin, Rossi, Peter, Joshi, Parag, Khera, Amit, Khaira, Ajit S., Kumkumian, Greg, Lupovitch, Steven, Purow, Joshua, Welka, Stephen, Hoffman, David, Fischer, Stuart, Soroka, Eugene, Eagerton, Donald, Pancholy, Samir, Ray, Michael, Erenrich, Norman, Farrar, Michael, Pollock, Stewart, French, William J., Diamantis, Steve, Guy, Douglas, Gimple, Lawrence, Neustel, Mark, Schwartz, Steven, Pereira, Edward, Albert, Seals, Spriggs, Douglas, Strain, Janet, Mittal, Suneet, Vo, Anthony, Chane, Majed, Hall, Jason, Vijay, Nampalli, Lotun, Kapildeo, Lester, F. Martin, Nahhas, Ahed, Pope, Theodore, Nager, Paul, Vohra, Rakesh, Sharma, Mukesh, Bashir, Riyaz, Ahmed, Hinan, Berlowitz, Michael, Fishberg, Robert, Barrucco, Robert, Yang, Eric, Radin, Michael, Sporn, Daniel, Stapleton, Dwight, Eisenberg, Steven, Landzberg, Joel, Mcgough, Martin, Turk, Samir, Schwartz, Michael, Sundram, P. Sandy, Jain, Diwakar, Zainea, Mark, Bayron, Carlos, Karlsberg, Ronald, Dohad, Suhail, Lui, Henry, Keen, William, Westerhausen, Donald, Jr., Khurana, Sandeep, Agarwal, Himanshu, Birchem, Jessica, Penny, William, Jr., Chang, Mark, Murphy, Sherrill, Henry, John, Schifferdecker ;John M Gilbert, Branislav, Chalavarya, Gopal, Eaton, Charles, Schmedtje, John F., Jr., Christenson, Stuart, Dotani, Imran, Denham, Douglas, Macdonell, Alexander, Gibson, Paul, Rahman, Aref, Al Joundi, Tammam, Assi, Nizar, Conrad, Gary, Kotha, Purushotham, Love, Michael, Giesler, Gregory, Rubenstein, Howard, Gamil, Dawood, Akright, Laura, Krawczyk, Justine, Cobler, Joanne, Wells, Terry, Welker, James, Foster, Robert, Gilmore, Richard, Anderson, Jay, Jacoby, Douglas, Harris, Bill, Gardner, Geraldine, Dandillaya, Ramprasad, Vora, Kishor, Kostis, John, Hunter, John, Laxson, David, Ball, Eric, Egydio, Flavia, Kawakami, Anelise, Oliveira, Janaina, Wozniak, Julianna, Matthews, Alexander, Ratky, Caroline, Valiris, Janine, Berdan, Lisa, Hepditch, Anita, Quintero, Kirby, Rorick, Tyrus, Westbrook, Melissa, Pascual, Andrea, Rovito, Carla, Bezault, Madeleine, Drouet, Elodie, Simon, Tabassome, Alsweiler, Caroline, Luyten, Anne, Butters, Julie, Griffith, Liddy, Shaw, Michelle, Grunberg, Lena, Islam, Shahidul, Brégeault, Marie-France, Bougon, Nathalie, Faustino, Douglas, Fontecave, Sylvie, Murphy, Judith, Verrier, Melanie, Veronique Agnetti, Andersen, Dorthe, Badreddine, Emmy, Bekkouche, Mhamed, Bouancheau, Cecile, Brigui, Imane, Brocklehurst, Maddy, Cianciarulo, Joseph, Devaul, Dawn, Domokos, Szilvia, Gache, Cecile, Gobillot, Caroline, Guillou, Severine, Healy, Jan, Heath, Megan, Jaiwal, Gayatri, Javierre, Carine, Labeirie, Julien, Monier, Myriam, Morales, Ulises, Mrabti, Asmaa, Mthombeni, Bicky, Okan, Betim, Smith, Lucile, Sheller, Jennifer, Sopena, Sebastien, Pellan, Valerie, Benbernou, Fadela, Bengrait, Nafissa, Lamoureux, Maud, Kralova, Katarina, Scemama, Michel, Bejuit, Raphael, Coulange, Anthony, Berthou, Christelle, Repincay, Jérôme, Lorenzato, Christelle, Etienne, Alexis, Gouet, Valerie, Loizeau, Virginie, Normand, Mickael, Ourliac, Anne, Rondel, Christelle, Adamo, Antony, Beltran, Pascale, Barraud, Pauline, Dubois-Gache, Helene, Halle, Benjamin, Metwally, Lamia, Mourgues, Maxime, Sotty, Marc, Vincendet, Marion, Cotruta, Raluca, Chengyue, Zhu, Fournie-Lloret, Dominique, Morrello, Christine, Perthuis, Aurelie, Picault, Patrick, Zobouyan, Isabelle, Colhoun, Helen M., Dempsey, Michael A., McClanahan, Mark A., Manvelian, Garen, Sinnaeve, Peter R., and Gabriel Steg, Ph

Published
2021
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36. Prolate Spheroidal Wave Functions Associated with the Quaternionic Fourier Transform

Author

Zou, Cuiming, Kou, Kit Ian, and Morais, Joao

Subjects
Mathematics - Classical Analysis and ODEs
Abstract

One of the fundamental problems in communications is finding the energy distribution of signals in time and frequency domains. It should, therefore, be of great interest to find the most energy concentration hypercomplex signal. The present paper finds a new kind of hypercomplex signals whose energy concentration is maximal in both time and frequency under quaternionic Fourier transform. The new signals are a generalization of the prolate spheroidal wave functions (also known as Slepian functions) to quaternionic space, which are called quaternionic prolate spheroidal wave functions. The purpose of this paper is to present the definition and properties of the quaternionic prolate spheroidal wave functions and to show that they can reach the extreme case in energy concentration problem both from the theoretical and experimental description. In particular, these functions are shown as an effective method for bandlimited signals extrapolation problem., Comment: 36 pages, 4 figures

Published
2016

37. Interacting 3-form dark energy models: distinguishing interactions and avoiding the Little Sibling of the Big Rip

Author

Morais, João, Bouhmadi-López, Mariam, Kumar, K. Sravan, Marto, João, and Tavakoli, Yaser

Subjects
General Relativity and Quantum Cosmology, High Energy Physics - Theory
Abstract

In this paper we consider 3-form dark energy (DE) models with interactions in the dark sector. We aim to distinguish the phenomenological interactions that are defined through the dark matter (DM) and the DE energy densities. We do our analysis mainly in two stages. In the first stage, we identify the non-interacting 3-form DE model which generically leads to an abrupt late-time cosmological event which is known as the little sibling of the Big Rip (LSBR). We classify the interactions which can possibly avoid this late-time abrupt event. We also study the parameter space of the model that is consistent with the interaction between DM and DE energy densities at present as indicated by recent studies based on BAO and SDSS data. In the later stage, we observationally distinguish those interactions using the statefinder hierarchy parameters $\{ S_{3}^{(1)}\,,\, S_{4}^{(1)}\} \,,\,\{ S_{3}^{(1)}\,,\, S_{5}^{(1)}\} .$ We also compute the growth factor parameter $\epsilon(z)$ for the various interactions we consider herein and use the composite null diagnostic (CND) $\{ S_{3}^{(1)}\,,\,\epsilon(z)\} $ as a tool to characterise those interactions by measuring their departures from the concordance model. In addition, we make a preliminary analysis of our model in light of the recently released data by SDSS~III on the measurement of the linear growth rate of structure., Comment: 38 pages, 10 figures, 4 tables. Small typos corrected, references added. Paper accepted in Physics of the Dark Universe

Published
2016
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38. $K$-essence model from the mechanical approach point of view: coupled scalar field and the late cosmic acceleration

Author

Bouhmadi-López, Mariam, Kumar, K. Sravan, Marto, João, Morais, João, and Zhuk, Alexander

Subjects
General Relativity and Quantum Cosmology, Astrophysics - Cosmology and Nongalactic Astrophysics, High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract

In this paper, we consider the Universe at the late stage of its evolution and deep inside the cell of uniformity. At these scales, we can consider the Universe to be filled with dust-like matter in the form of discretely distributed galaxies, a $K$-essence scalar field, playing the role of dark energy, and radiation as matter sources. We investigate such a Universe in the mechanical approach. This means that the peculiar velocities of the inhomogeneities (in the form of galaxies) as well as the fluctuations of the other perfect fluids are non-relativistic. Such fluids are designated as coupled because they are concentrated around the inhomogeneities. In the present paper, we investigate the conditions under which the $K$-essence scalar field with the most general form for its action can become coupled. We investigate at the background level three particular examples of the $K$-essence models: (i) the pure kinetic $K$-essence field, (ii) a $K$-essence with a constant speed of sound and (iii) the $K$-essence model with the Lagrangian $bX+cX^2-V(\phi)$. We demonstrate that if the $K$-essence is coupled, all these $K$-essence models take the form of multicomponent perfect fluids where one of the component is the cosmological constant. Therefore, they can provide the late-time cosmic acceleration and be simultaneously compatible with the mechanical approach., Comment: 26 pages, no figures. Conclusions extended and references updated. Version accepted in JCAP

Published
2016
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39. The late Universe with non-linear interaction in the dark sector: the coincidence problem

Author

Bouhmadi-López, Mariam, Morais, João, and Zhuk, Alexander

Subjects
General Relativity and Quantum Cosmology, Astrophysics - Cosmology and Nongalactic Astrophysics, High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract

We study the Universe at the late stage of its evolution and deep inside the cell of uniformity. At such a scale the Universe is highly inhomogeneous and filled with discretely distributed inhomogeneities in the form of galaxies and groups of galaxies. As a matter source, we consider dark matter (DM) and dark energy (DE) with a non-linear interaction $Q = 3\mathcal{H}\gamma \bar\varepsilon_{\mathrm{DE}} \bar\varepsilon_{\mathrm{DM}} / (\bar\varepsilon_{\mathrm{DE}} + \bar\varepsilon_{\mathrm{DM}})$, where $\gamma$ is a constant. We assume that DM is pressureless and DE has a constant equation of state parameter $w$. In the considered model, the energy densities of the dark sector components present a scaling behaviour with $\bar\varepsilon_{\mathrm{DM}} / \bar\varepsilon_{\mathrm{DE}} \sim \left({a_0} / {a} \right)^{-3(w+\gamma)}$. We investigate the possibility that the perturbations of DM and DE, which are interacting among themselves, could be coupled to the galaxies with the former being concentrated around them. To carry our analysis, we consider the theory of scalar perturbations (within the mechanical approach), and obtain the sets of parameters $(w,\gamma)$ which do not contradict it. We conclude that two sets: $(w=-2/3,\gamma=1/3)$ and $(w=-1,\gamma=1/3)$ are of special interest. First, the energy densities of DM and DE on these cases are concentrated around galaxies confirming that they are coupled fluids. Second, we show that for both of them, the coincidence problem is less severe than in the standard $\Lambda$CDM. Third, the set $(w=-1,\gamma=1/3)$ is within the observational constraints. Finally, we also obtain an expression for the gravitational potential in the considered model., Comment: 24 pages, no figures. Conclusions extended and references updated. Version accepted in Physics of the Dark Universe

Published
2016
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40. Coupled scalar fields in the late Universe: The mechanical approach and the late cosmic acceleration

Author

Burgazli, Alvina, Zhuk, Alexander, Morais, João, Bouhmadi-López, Mariam, and Kumar, K. Sravan

Subjects
General Relativity and Quantum Cosmology
Abstract

In this paper, we consider the Universe at the late stage of its evolution and deep inside the cell of uniformity. At these scales, we consider the Universe to be filled with dust-like matter in the form of discretely distributed galaxies, a minimally coupled scalar field and radiation as matter sources. We investigate such a Universe in the mechanical approach. This means that the peculiar velocities of the inhomogeneities (in the form of galaxies) as well as fluctuations of other perfect fluids are non-relativistic. Such fluids are designated as coupled because they are concentrated around inhomogeneities. In the present paper we investigate the conditions under which a scalar field can become coupled, and show that, at the background level, such coupled scalar field behaves as a two component perfect fluid: a network of frustrated cosmic strings with EoS parameter $w=-1/3$ and a cosmological constant. The potential of this scalar field is very flat at the present time. Hence, the coupled scalar field can provide the late cosmic acceleration. The fluctuations of the energy density and pressure of this field are concentrated around the galaxies screening their gravitational potentials. Therefore, such scalar fields can be regarded as coupled to the inhomogeneities., Comment: 14pages, 1 figure

Published
2015
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41. Abstract 10470: Projected Lifetime Benefits of Alirocumab in Patients After Acute Coronary Syndrome

Author

Budaj, Andrzej, Elbez, Yedid, Schwartz, Gregory G, Bhatt, Deepak L, Bittner, Vera A, Chua, Terrance Sing Jin, Diaz, Rafael, Goodman, Shaun G, Harrington, Robert A, Jukema, J Wouter, Kedev, Sasko, Laucevicius, Alexander, MORAIS, JOAO, MURIN, Jan, Parkhomenko, Alexander, Pordy, Robert, Scemama, Michel, Szarek, Michael, White, Harvey D, and Steg, Philippe G

Published
2022
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43. Os custos da aterosclerose em Portugal

Author

Costa, João, Alarcão, Joana, Amaral‐Silva, Alexandre, Araújo, Francisco, Ascenção, Raquel, Caldeira, Daniel, Cardoso, Marta Ferreira, Correia, Manuel, Fiorentino, Francesca, Gavina, Cristina, Gil, Victor, Gouveia, Miguel, Lourenço, Francisco, Mello e Silva, Alberto, Mendes Pedro, Luís, Morais, João, Vaz‐Carneiro, António, Teixeira Veríssimo, Manuel, and Borges, Margarida

Published
2021
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44. Atherosclerosis: The cost of illness in Portugal

Author

Costa, João, Alarcão, Joana, Amaral‐Silva, Alexandre, Araújo, Francisco, Ascenção, Raquel, Caldeira, Daniel, Cardoso, Marta Ferreira, Correia, Manuel, Fiorentino, Francesca, Gavina, Cristina, Gil, Victor, Gouveia, Miguel, Lourenço, Francisco, Mello e Silva, Alberto, Mendes Pedro, Luís, Morais, João, Vaz‐Carneiro, António, Veríssimo, Manuel Teixeira, and Borges, Margarida

Published
2021
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46. Five years of Stent for Life in Portugal

Author

Pereira, Hélder, Calé, Rita, Pereira, Ernesto, Mello, Sofia, Vitorino, Sílvia, Jerónimo de Sousa, Pedro, Monteiro, Sílvia, Pinto, Fausto J., Ramos, Raquel, Coelho dos Santos, Pedro, Ferreira, João, Silveira, João, and Morais, João

Published
2021
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47. Scalar perturbations in the late Universe: viability of the Chaplygin gas models

Author

Bouhmadi-López, Mariam, Brilenkov, Maxim, Brilenkov, Ruslan, Morais, João, and Zhuk, Alexander

Subjects
General Relativity and Quantum Cosmology, Astrophysics - Cosmology and Nongalactic Astrophysics, High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract

We study the late-time evolution of the Universe where dark energy (DE) is parametrized by a modified generalized Chaplygin gas (mGCG) on top of cold dark matter (CDM). We also take into account the radiation content of the Universe. In this context, the late stage of the evolution of the universe refers to the epoch where CDM is already clustered into inhomogeneously distributed discrete structures (galaxies, groups and clusters of galaxies). Under these conditions, the mechanical approach is an adequate tool to study the Universe deep inside the cell of uniformity. To be more accurate, we study scalar perturbations of the Friedmann-Lema\^itre-Robertson-Walker metric due to inhomogeneities of CDM as well as fluctuations of radiation and mGCG, the later driving the late-time acceleration of the universe. Our analysis applies as well to the case where mGCG plays the role of DM and DE. We select the sets of parameters of the mGCG that are compatible with the mechanical approach. These sets define prospective mGCG models. By comparing the selected sets of models with some of the latest observational data results, we conclude that the mGCG is in tight agreement with those observations particularly for a mGCG playing the role of DE and DM., Comment: 18 pages, no figures. Discussion improved. Version accepted in JCAP

Published
2015
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48. Can f(R) gravity contribute to (dark) radiation?

Author

Morais, Joao, Bouhmadi-Lopez, Mariam, and Capozziello, Salvatore

Subjects
General Relativity and Quantum Cosmology, Astrophysics - Cosmology and Nongalactic Astrophysics, High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract

We discuss the possibility that suitable modifications of gravity could account for some amount of the radiation we observe today, in addition to the possibility of explaining the present speed up of the universe. We start introducing and reviewing cosmological reconstruction methods for metric $f(R)$ theories of gravity that can be considered as one of the straightforward modifications of Einstein's gravity as soon as $f(R)\neq R$. We then take into account two possible $f(R)$ models which could give rise to (dark) radiation. Constraints on the models are found by using the Planck Collaboration 2015 data within a cosmographic approach and by obtaining the matter power spectrum of those models. The conclusion is that $f(R)$ gravity can only contribute minimally to the (dark) radiation to avoid departures from the observed matter power spectrum at the smallest scales (of the order of $0.01$Mpc$^{-1}$), i.e., precisely those scales that exited the horizon at the radiation dominated epoch. This result could strongly contribute to select reliable $f(R)$ models., Comment: 29 pages, 10 figures, RevTex4. Discussion improved. Version accepted in JCAP

Published
2015
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