Primordial black hole production during preheating in a chaotic inflationary model

In this paper we review the production of primordial black holes (PBHs) during preheating after a chaotic inflationary model. All relevant equations of motion are solved numerically in a modified version of HLattice, and we then calculate the mass variance to determine structure formation during preheating. It is found that production of PBHs can be a generic result of the model, even though the results seem to be sensitive to the values of the smoothing scale. We consider a constraint for overproduction of PBHs that could uncover some stress between inflation-preheating models and observations.Comment: 6 pages, 5 figures. Prepared for the conference proceedings of the 9th Mexican School on Gravitation and Mathematical Physics : Cosmology for the XXI Century: Inflation, Dark Matter and Dark Energ

S4ND: Single-Shot Single-Scale Lung Nodule Detection

The state of the art lung nodule detection studies rely on computationally expensive multi-stage frameworks to detect nodules from CT scans. To address this computational challenge and provide better performance, in this paper we propose S4ND, a new deep learning based method for lung nodule detection. Our approach uses a single feed forward pass of a single network for detection and provides better performance when compared to the current literature. The whole detection pipeline is designed as a single $3D$ Convolutional Neural Network (CNN) with dense connections, trained in an end-to-end manner. S4ND does not require any further post-processing or user guidance to refine detection results. Experimentally, we compared our network with the current state-of-the-art object detection network (SSD) in computer vision as well as the state-of-the-art published method for lung nodule detection (3D DCNN). We used publically available $888$ CT scans from LUNA challenge dataset and showed that the proposed method outperforms the current literature both in terms of efficiency and accuracy by achieving an average FROC-score of $0.897$. We also provide an in-depth analysis of our proposed network to shed light on the unclear paradigms of tiny object detection.Comment: Accepted for publication at MICCAI 2018 (21st International Conference on Medical Image Computing and Computer Assisted Intervention

GPCALMA: a Grid Approach to Mammographic Screening

The next generation of High Energy Physics experiments requires a GRID approach to a distributed computing system and the associated data management: the key concept is the "Virtual Organisation" (VO), a group of geographycally distributed users with a common goal and the will to share their resources. A similar approach is being applied to a group of Hospitals which joined the GPCALMA project (Grid Platform for Computer Assisted Library for MAmmography), which will allow common screening programs for early diagnosis of breast and, in the future, lung cancer. HEP techniques come into play in writing the application code, which makes use of neural networks for the image analysis and shows performances similar to radiologists in the diagnosis. GRID technologies will allow remote image analysis and interactive online diagnosis, with a relevant reduction of the delays presently associated to screening programs.Comment: 4 pages, 3 figures; to appear in the Proceedings of Frontier Detectors For Frontier Physics, 9th Pisa Meeting on Advanced Detectors, 25-31 May 2003, La Biodola, Isola d'Elba, Ital

Multi-objective Optimal Test Suite Computation for Software Product Line Pairwise Testing

Lopez-Herrejon, R. E., Chicano F., Ferrer J., Egyed A., & Alba E. (2013). Multi-objective Optimal Test Suite Computation for Software Product Line Pairwise Testing. 2013 IEEE International Conference on Software Maintenance, Eindhoven, The Netherlands, September 22-28, 2013. 404–407.Software Product Lines (SPLs) are families of related software products, which usually provide a large number of feature combinations, a fact that poses a unique set of challenges for software testing. Recently, many SPL testing approaches have been proposed, among them pair wise combinatorial techniques that aim at selecting products to test based on the pairs of feature combinations such products provide. These approaches regard SPL testing as an optimization problem where either coverage (maximize) or test suite size (minimize) are considered as the main optimization objective. Instead, we take a multi-objective view where the two objectives are equally important. In this exploratory paper we propose a zero-one mathematical linear program for solving the multi-objective problem and present an algorithm to compute the true Pareto front, hence an optimal solution, from the feature model of a SPL. The evaluation with 118 feature models revealed an interesting trade-off between reducing the number of constraints in the linear program and the runtime which opens up several venues for future research.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Austrian Science Fund (FWF) project P21321-N15 and Lise Meitner Fellowship M1421-N15. Spanish Ministry of Economy and Competitiveness and FEDER under contract TIN2011-28194 and fellowship BES-2012-055967

Enzymatic extraction of hydroxycinnamic acids from coffee pulp

Ferulic, caffeic, p-coumaric and chlorogenic acids are classified as hydroxycinnamic acids, presenting anticarcinogenic, anti-inflammatory and antioxidant properties. In this work, enzymatic extraction has been studied in order to extract high value-added products like hydroxycinnamic acids from coffee pulp. A commercial pectinase and enzyme extract produced by Rhizomucor pusillus strain 23aIV in solid-state fermentation using olive oil or coffee pulp (CP) as an inducer of the feruloyl esterase activity were evaluated separately and mixed. The total content (covalently linked and free) of ferulic, caffeic, p-coumaric and chlorogenic acids was 5276 mg per kg of coffee pulp. Distribution was as follows (in %): chlorogenic acid 58.7, caffeic acid 37.6, ferulic acid 2.1 and p-coumaric acid 1.5. Most of the hydroxycinnamic acids were covalently bound to the cell wall (in %): p-coumaric acid 97.2, caffeic acid 94.4, chlorogenic acid 76.9 and ferulic acid 73.4. The content of covalently linked hydroxycinnamic acid was used to calculate the enzyme extraction yield. The maximum carbon dioxide rate for the solid-state fermentation using olive oil as an inducer was higher and it was reached in a short cultivation time. Nevertheless, the feruloyl esterase (FAE) activity (units per mg of protein) obtained in the fermentation using CP as an inducer was 31.8 % higher in comparison with that obtained in the fermentation using olive oil as the inducer. To our knowledge, this is the first report indicating the composition of both esterified and free ferulic, caffeic, p-coumaric and chlorogenic acids in coffee pulp. The highest yield of extraction of hydroxycinnamic acids was obtained by mixing the produced enzyme extract using coffee pulp as an inducer and a commercial pectinase. Extraction yields were as follows (in %): chlorogenic acid 54.4, ferulic acid 19.8, p-coumaric acid 7.2 and caffeic acid 2.3. An important increase in the added value of coffee pulp was mainly due to the extraction of chlorogenic acid

A Computer Aided Detection system for mammographic images implemented on a GRID infrastructure

The use of an automatic system for the analysis of mammographic images has proven to be very useful to radiologists in the investigation of breast cancer, especially in the framework of mammographic-screening programs. A breast neoplasia is often marked by the presence of microcalcification clusters and massive lesions in the mammogram: hence the need for tools able to recognize such lesions at an early stage. In the framework of the GPCALMA (GRID Platform for Computer Assisted Library for MAmmography) project, the co-working of italian physicists and radiologists built a large distributed database of digitized mammographic images (about 5500 images corresponding to 1650 patients) and developed a CAD (Computer Aided Detection) system, able to make an automatic search of massive lesions and microcalcification clusters. The CAD is implemented in the GPCALMA integrated station, which can be used also for digitization, as archive and to perform statistical analyses. Some GPCALMA integrated stations have already been implemented and are currently on clinical trial in some italian hospitals. The emerging GRID technology can been used to connect the GPCALMA integrated stations operating in different medical centers. The GRID approach will support an effective tele- and co-working between radiologists, cancer specialists and epidemiology experts by allowing remote image analysis and interactive online diagnosis.Comment: 5 pages, 5 figures, to appear in the Proceedings of the 13th IEEE-NPSS Real Time Conference 2003, Montreal, Canada, May 18-23 200

Comparative analysis of classical multi-objective evolutionary algorithms and seeding strategies for pairwise testing of Software Product Lines

Lopez-Herrejon, R. Erick, Ferrer J., Chicano F., Egyed A., & Alba E. (2014). Comparative analysis of classical multi-objective evolutionary algorithms and seeding strategies for pairwise testing of Software Product Lines. Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2014, Beijing, China, July 6-11, 2014. 387–396.Software Product Lines (SPLs) are families of related software products, each with its own set of feature combinations. Their commonly large number of products poses a unique set of challenges for software testing as it might not be technologically or economically feasible to test of all them individually. SPL pairwise testing aims at selecting a set of products to test such that all possible combinations of two features are covered by at least one selected product. Most approaches for SPL pairwise testing have focused on achieving full coverage of all pairwise feature combinations with the minimum number of products to test. Though useful in many contexts, this single-objective perspective does not reflect the prevailing scenario where software engineers do face trade-offs between the objectives of maximizing the coverage or minimizing the number of products to test. In contrast and to address this need, our work is the first to propose a classical multi-objective formalisation where both objectives are equally important. In this paper, we study the application to SPL pairwise testing of four classical multi-objective evolutionary algorithms. We developed three seeding strategies — techniques that leverage problem domain knowledge — and measured their performance impact on a large and diverse corpus of case studies using two well-known multi-objective quality measures. Our study identifies the performance differences among the algorithms and corroborates that the more domain knowledge leveraged the better the search results. Our findings enable software engineers to select not just one solution (as in the case of single-objective techniques) but instead to select from an array of test suite possibilities the one that best matches the economical and technological constraints of their testing context.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Austrian Science Fund (FWF) project P25289- N15 and Lise Meitner Fellowship M1421-N15. Spanish Ministry of Economy and Competitiveness and FEDER under contract TIN2011-28194 and fellowship BES-2012-055967. Project 8.06/5.47.4142 in collaboration with the VSB-Tech. Univ. of Ostrava and Universidad de Málaga, Andalucía Tech