Quarkonium production measurements with the ALICE detector at the LHC

In this new energy regime, quarkonium provides a unique probe to study the properties of the high-density, strongly interacting system formed in the early stages of high-energy heavy-ion collisions. In ALICE, quarkonium states are reconstructed down to p_T=0 via their mu+mu- decay channel in the muon spectrometer (2.5<y<4.0) and via their e+e- channel in the central barrel (|y|<0.9). Measurement of the transverse momentum and rapidity distributions of inclusive J/psi production cross section in proton-proton collisions at sqrt{s}=2.76 and 7 TeV will be presented. We will discuss the dependence on charged particle multiplicity of the inclusive J/psi yield in proton-proton collisions at sqrt{s}=7 TeV. Finally, the analysis of the inclusive J/psi production in Pb-Pb collisions at sqrt{s_NN}=2.76 TeV will be described. Preliminary results on the nuclear modification factor (R_AA) and the central to peripheral nuclear modification factor (R_CP) will be discussed.Comment: 8 pages, 3 figures, plenary talk at Quark Matter 2011, May 23rd-28th 2011, Annecy, Franc

Automatic Classification of Chickpea Varieties Using Computer Vision Techniques

There are about 90 different varieties of chickpeas around the world. In Iran, where this study takes place, there are five species that are the most popular (Adel, Arman, Azad, Bevanij and Hashem), with different properties and prices. However, distinguishing them manually is difficult because they have very similar morphological characteristics. In this research, two different computer vision methods for the classification of the variety of chickpeas are proposed and compared. The images were captured with an industrial camera in Kermanshah, Iran. The first method is based on color and texture features extraction, followed by a selection of the most effective features, and classification with a hybrid of artificial neural networks and particle swarm optimization (ANN-PSO). The second method is not based on an explicit extraction of features; instead, image patches (RGB pixel values) are directly used as input for a three-layered backpropagation ANN. The first method achieved a correct classification rate (CCR) of 97.0%, while the second approach achieved a CCR of 99.3%. These results prove that visual classification of fruit varieties in agriculture can be done in a very precise way using a suitable method. Although both techniques are feasible, the second method is generic and more easily applicable to other types of crops, since it is not based on a set of given features.This research was funded by the Spanish MICINN, as well as European Commission FEDER funds, under grant RTI2018-098156-B-C53. It has also been supported by the European Union (EU) under Erasmus + project entitled "Fostering Internationalization in Agricultural Engineering in Iran and Russia [FARmER]" with grant number 585596-EPP-1-2017-1-DE-EPPKA2-CBHE-JP

Antithrombin is incorporated into exosomes produced by antithrombin non-expressing cells

Antithrombin is a serine protease inhibitor that exerts a crucial role in hemostasis as the main inhibitor of the coagulation cascade. It plays also critical roles in other processes, such as inflammation and cancer. Here we show that exosomes released by Madin-Darby canine kidney (MDCK) cells cultured in the presence of heparin incorporate antithrombin from the serum. Exosomal antithrombin is found complexed with the serine protease high temperature requirement A1 (HTRA1), whose cellular levels are increased after serum deprival, the condition used to collect exosomes. Although the biological relevance of the presence of antithrombin in exosomes remains to be investigated, our results suggest a functional interplay between antithrombin and HTRA1.Ginés Luengo-Gil holds a grant from the Spanish Society of Hematology and Hemotherapy (SEHH-FEHH), Irene Martínez-Martínez holds a Miguel Servet contract from the ISCIII. Miguel Quintanilla holds a grant (SAF2017-84183-R) from the Spanish Ministry of Science, Innovation and Universities and Irene Martínez-Martínez holds grants from ISCIII (CP13/00126 & FEDER and PI17/00050 & FEDER)

The course of posterior antebrachial cutaneous nerve: Anatomical and sonographic study with a clinical implication

The course of the posterior antebrachial cutaneous nerve (PACN) was studied via ultrasound (US) and dissection. The aim of this study was to reveal the anatomical relationships of PACN with the surrounding structures along its pathway to identify possible critical points of compression. Nineteen cryopreserved cadaver body donor upper extremities were explored via US and further dissected. During US exploration, two reference points, in relation with the compression of the nerve, were marked using dye injection: (1) the point where the RN pierces the lateral intermuscular septum (LIMS) and (2) the point where the PACN pierces the deep fascia. Anatomical measurements referred to the lateral epicondyle (LE) were taken at these two points. Dissection confirmed the correct site of US-guided dye injection at 100% of points where the RN crossed the LIMS (10.5 cm from the LE) and was correctly injected at 74% of points where the PACN pierce the deep fascia (7.4 cm from the LE). There were variations in the course of the PACN, but it always divided from the RN as an only branch. Either ran close and parallel to the LIMS until the RN crossed the LIMS (84%) or clearly separated from the RN, 1 cm before it crossed the LIMS (16%). In 21% of cases, the PACN crossed the LIMS with the RN, while in the rest of the cases it always followed in the posterior compartment. A close relationship between PACN and LIMS, as well as triceps brachii muscle and deep fascia was observed. The US and anatomical study showed that the course of PACN maintains a close relationship with the LIMS and other connective tissues (such as the fascia and subcutaneous tissue) to be present in its pathology and treatment

Identification of internal defects in potato using spectroscopy and computational intelligence based on majority voting techniques

Producción CientíficaPotatoes are one of the most demanded products due to their richness in nutrients. However, the lack of attention to external and, especially, internal defects greatly reduces its marketability and makes it prone to a variety of diseases. The present study aims to identify healthy-looking potatoes but with internal defects. A visible (Vis), near-infrared (NIR), and short-wavelength infrared (SWIR) spectrometer was used to capture spectral data from the samples. Using a hybrid of artificial neural networks (ANN) and the cultural algorithm (CA), the wavelengths of 861, 883, and 998 nm in Vis/NIR region, and 1539, 1858, and 1896 nm in the SWIR region were selected as optimal. Then, the samples were classified into either healthy or defective class using an ensemble method consisting of four classifiers, namely hybrid ANN and imperialist competitive algorithm (ANN-ICA), hybrid ANN and harmony search algorithm (ANN-HS), linear discriminant analysis (LDA), and k-nearest neighbors (KNN), combined with the majority voting (MV) rule. The performance of the classifier was assessed using only the selected wavelengths and using all the spectral data. The total correct classification rates using all the spectral data were 96.3% and 86.1% in SWIR and Vis/NIR ranges, respectively, and using the optimal wavelengths 94.1% and 83.4% in SWIR and Vis/NIR, respectively. The statistical tests revealed that there are no significant differences between these datasets. Interestingly, the best results were obtained using only LDA, achieving 97.7% accuracy for the selected wavelengths in the SWIR spectral range.Ministerio de Ciencia, Innovación y Universidades; Ministerio de Ciencia e Innovación; Agencia Estatal de Investigación y Fondo Europeo de Desarrollo Regional (FEDER) - (grant RTI2018-098156-B-C53

Estudio y análisis de la accesibilidad para personas con discapacidad física en el acceso a comercios y locales de la ciudad de Murcia

With a worldwide percentage of people with disabilities around 15%, universal accessibility is a fundamental consideration in the habitable design of buildings. Moreover, due to the current aging of the population, especially in Spain, this will be a key factor of sustainability from the human point of view. This paper presents a case study of accessibility in the entrance to shops in the city of Murcia, Spain. First, the applicable accessibility regulations and the criteria of the users obtained from the Regional Federation FAMDIF are exposed, and then the extensive field work carried out is described; more than 650 commercial and service premises have been analyzed in situ by technical personnel. By volume, it is one of the largest studies to date. As a result, it has been obtained that only 1/5 of the premises are accessible in the entrance, while almost 3/4 do not comply with current regulations. We believe that this work will help raise awareness to improve physical accessibility in the future.Con un porcentaje mundial de personas con discapacidad del 15%, la accesibilidad universal resulta una consideración fundamental en el diseño habitable de los edificios. Además, debido al envejecimiento de la población, especialmente en España, este será un factor clave de la sostenibilidad desde el punto de vista humano. Este artículo presenta un caso de estudio de la accesibilidad en el acceso a comercios de la ciudad de Murcia. En primer lugar, se expone la normativa de accesibilidad aplicable y los criterios de los usuarios a través de la Federación Murciana FAMDIF, para después describir el extenso trabajo de campo llevado a cabo, donde se han analizado in situ más de 650 comercios y locales de servicios por personal técnico. Por su volumen, se trata de uno de los mayores estudios realizados hasta la fecha. Como resultado, se ha obtenido que solo 1/5 de los locales son accesibles en la entrada, mientras que casi 3/4 no cumplen las normativas vigentes. Creemos que este trabajo ayudará a concienciar y a mejorar la accesibilidad física en el futuro

Design and Development of a Mobile App for Accessible Beach Tourism Information for People with Disabilities

The global increase in the proportion of the population with disabilities has caused a greater awareness toward guaranteeing their use of public services. In particular, there is emphasis on the accessibility and inclusivity of tourism resources, to improve the enjoyment and well-being for people with motor disabilities. This paper presents a case study on accessibility to beaches in the Region of Murcia, Spain, which is one of the main tourist areas in the country. First, the most important elements that allow for the accessible use of beaches are analyzed and exposed in detail. Then, an extensive field-work in the area of interest has been carried out and its results are evaluated. Finally, the development of a new mobile app is described. The objective of this tool is to provide updated, accurate, and reliable accessibility information regarding the beaches. As a result, more than a third of the beaches analyzed had a high level of accessibility, while almost another third are totally inaccessible. The proposed application is a valuable tool, not only to help people with physical and motor disabilities, but also to raise awareness among local authorities to create and improve accessible services.This work was supported by the Spanish MICINN, as well as European Commission FEDER funds, under grants RTI2018-098156-B-C53 and RTI2018-098309-B-C33. The authors thank Manuel García-Hernández and Salvador Parada-Sarabia for their participation in the collection of data of the study, Khalil Merzouki for the contribution in the software development of the proposed system, and the Federation of Associations of People with Physical and Organic Disability of Murcia (FAMDIF) for the extensive support in carrying out this work

Comparison of Different Classifiers and the Majority Voting Rule for the Detection of Plum Fruits in Garden Conditions

Color segmentation is one of the most thoroughly studied problems in agricultural applications of remote image capture systems, since it is the key step in several different tasks, such as crop harvesting, site specific spraying, and targeted disease control under natural light. This paper studies and compares five methods to segment plum fruit images under ambient conditions at 12 different light intensities, and an ensemble method combining them. In these methods, several color features in different color spaces are first extracted for each pixel, and then the most effective features are selected using a hybrid approach of artificial neural networks and the cultural algorithm (ANN-CA). The features selected among the 38 defined channels were the b* channel of L*a*b*, and the color purity index, C*, from L*C*h. Next, fruit/background segmentation is performed using five classifiers: artificial neural network-imperialist competitive algorithm (ANN-ICA); hybrid artificial neural network-harmony search (ANN-HS); support vector machines (SVM); k nearest neighbors (kNN); and linear discriminant analysis (LDA). In the ensemble method, the final class for each pixel is determined using the majority voting method. The experiments showed that the correct classification rate for the majority voting method excluding LDA was 98.59%, outperforming the results of the constituent methods.This research was funded by the Spanish MICINN, as well as European Commission FEDER funds, under grant RTI2018-098156-B-C53. This project has also been supported by the European Union (EU) under Erasmus+ project entitled "Fostering Internationalization in Agricultural Engineering in Iran and Russia" [FARmER] with grant number 585596-EPP-1-2017-1-DE-EPPKA2-CBHE-JP

P systems simulations on massively parallel architectures

Membrane Computing is an emergent research area studying the behaviour of living cells to de ne bio-inspired computing devices, also called P systems. Such devices provide polynomial time solutions to NP-complete problems by trading time for space. The e cient simulation of P systems poses challenges in three di erent aspects: an intrinsic massively parallelism of P systems, an exponential computational workspace, and a non-intensive oating point nature. In this paper, we analyze the simulation of a family of recognizer P systems with active membranes that solves the Satis ability (SAT) problem in linear time on three di erent architectures: a shared memory system, a distributed memory system, and a set of Graphics Processing Units (GPUs). For an e cient handling of the exponential workspace created by the P systems computation, we enable di erent data policies on those architectures to increase memory bandwidth and exploit data locality through tiling. Parallelism inherent to the target P system is also managed on each architecture to demonstrate that GPUs o er a valid alternative for high-performance computing at a considerably lower cost: Considering the largest problem size we were able to run on the three parallel platforms involving four processors, execution times were 20049.70 ms. using OpenMP on the shared memory multiprocessor, 4954.03 ms. using MPI on the distributed memory multiprocessor and 565.56 ms. using CUDA in our four GPUs, which results in speed factors of 35.44x and 8.75x, respectively.Fundación Séneca 00001/CS/2007Ministerio de Ciencia e Innovación TIN2009–13192European Community CSD2006- 00046Junta de Andalucía P06-TIC-02109Junta de Andalucía P08–TIC-0420

The GPU on the simulation of cellular computing models

Membrane Computing is a discipline aiming to abstract formal computing models, called membrane systems or P systems, from the structure and functioning of the living cells as well as from the cooperation of cells in tissues, organs, and other higher order structures. This framework provides polynomial time solutions to NP-complete problems by trading space for time, and whose efficient simulation poses challenges in three different aspects: an intrinsic massively parallelism of P systems, an exponential computational workspace, and a non-intensive floating point nature. In this paper, we analyze the simulation of a family of recognizer P systems with active membranes that solves the Satisfiability problem in linear time on different instances of Graphics Processing Units (GPUs). For an efficient handling of the exponential workspace created by the P systems computation, we enable different data policies to increase memory bandwidth and exploit data locality through tiling and dynamic queues. Parallelism inherent to the target P system is also managed to demonstrate that GPUs offer a valid alternative for high-performance computing at a considerably lower cost. Furthermore, scalability is demonstrated on the way to the largest problem size we were able to run, and considering the new hardware generation from Nvidia, Fermi, for a total speed-up exceeding four orders of magnitude when running our simulations on the Tesla S2050 server.Agencia Regional de Ciencia y Tecnología - Murcia 00001/CS/2007Ministerio de Ciencia e Innovación TIN2009–13192Ministerio de Ciencia e Innovación TIN2009-14475-C04European Commission Consolider Ingenio-2010 CSD2006-0004