tetraxial textiles assessment of mesoscale mechanical modelling by experimental measurements

Tetraxial technical textiles were recently manufactured by a new loom developed to weave yarns in four directions. The textile has warp, weft, and two diagonal yarns oriented at symmetrical angles (typically ±45°) with respect to the warp direction. The peculiar yarns distribution could enhance the mechanical response of the textile in multiple directions aiming to almost isotropic in-plane behaviour. For the prediction of the mechanical performance of such tetraxial textiles, a reliable and accurate predictive model is of relevant importance. The present investigation aims to adopt the finite element numerical approach at the mesoscopic scale to predict the mechanical response for any in-plane loading of tetraxial textiles. An accurate modelling of the constitutive behaviour of the fibrous yarns was adopted considering a hyperelastic model. The modelling of the tetraxial unit cell allowed to have the mechanical behaviour for uniaxial and biaxial tensile and for shear loading conditions. The assessment of the accuracy of the numerical model was performed considering a huge experimental campaign dedicated to several hybrid tetraxial textiles. The comparison highlights the accuracy of the numerical model to predict the nonlinear behavior of the fabric for any loading condition and to provide the proper mechanical model for further optimization of tetraxial textiles supposed for different industrial applications

Microarrays in cancer research

Microarray technology has presented the scientific community with a compelling approach that allows for simultaneous evaluation of all cellular processes at once. Cancer, being one of the most challenging diseases due to its polygenic nature, presents itself as a perfect candidate for evaluation by this approach. Several recent articles have provided significant insight into the strengths and limitations of microarrays. Nevertheless, there are strong indications that this approach will provide new molecular markers that could be used in diagnosis and prognosis of cancers (1, 2). To achieve these goals it is essential that there is a seamless integration of clinical and molecular biological data that allows us to elucidate genes and pathways involved in various cancers. To this effect we are currently evaluating gene expression profiles in human brain, ovarian, breast and hematopoetic, lung, colorectal, head and neck and biliary tract cancers. To address the issues we have a joint team of scientists, doctors and computer scientists from two Virginia Universities and a major healthcare provider. The study has been divided into several focus groups that include; Tissue Bank Clinical & Pathology Laboratory Data, Chip Fabrication, QA/QC, Tissue Devitalization, Database Design and Data Analysis, using multiple microarray platforms. Currently over 300 consenting patients have been enrolled in the study with the largest number being that of breast cancer patients. Clinical data on each patient is being compiled into a secure and interactive relational database and integration of these data elements will be accomplished by a common programming interface. This clinical database contains several key parameters on each patient including demographic (risk factors, nutrition, co-morbidity, familial history), histopathology (non genetic predictors), tumor, treatment and follow-up information. Gene expression data derived from the tissue samples will be linked to this database, which allows us to query the data at multiple levels. The challenge of tissue acquisition and processing is of paramount importance to the success of this venture. A tissue devitalization timeline protocol was devised to ensure sample and RNA integrity. Stringent protocols are being employed to ascertain accurate tumor homogeneity, by serial dissection of each tumor sample at 10\u3bcM frozen sections followed by histopathological evaluation. The multiple platforms being utilized in this study include Affimetrix, Oligo-Chips and custom-designed cDNA arrays. Selected RNA samples will be evaluated on each platform between the groups. Analysis steps will involve normalization and standardization of gene expression data followed by hierarchical clustering to determine co-regulation profiles. The aim of this conjoint effort is to elucidate pathways and genes involved in various cancers, resistance mechanisms, molecular markers for diagnosis and prognosis

Multicore and FPGA implementations of emotional-based agent architectures

The final publication is available at Springer via http://dx.doi.org/10.1007/s11227-014-1307-6.Control architectures based on Emotions are becoming promising solutions for the implementation of future robotic agents. The basic controllers of the architecture are the emotional processes that decide which behaviors of the robot must activate to fulfill the objectives. The number of emotional processes increases (hundreds of millions/s) with the complexity level of the application, reducing the processing capacity of the main processor to solve complex problems (millions of decisions in a given instant). However, the potential parallelism of the emotional processes permits their execution in parallel on FPGAs or Multicores, thus enabling slack computing in the main processor to tackle more complex dynamic problems. In this paper, an emotional architecture for mobile robotic agents is presented. The workload of the emotional processes is evaluated. Then, the main processor is extended with FPGA co-processors through Ethernet link. The FPGAs will be in charge of the execution of the emotional processes in parallel. Different Stratix FPGAs are compared to analyze their suitability to cope with the proposed mobile robotic agent applications. The applications are set up taking into account different environmental conditions, robot dynamics and emotional states. Moreover, the applications are run also on Multicore processors to compare their performance in relation to the FPGAs. Experimental results show that Stratix IV FPGA increases the performance in about one order of magnitude over the main processor and solves all the considered problems. Quad-Core increases the performance in 3.64 times, allowing to tackle about 89 % of the considered problems. Quad-Core has a lower cost than a Stratix IV, so more adequate solution but not for the most complex application. Stratix III could be applied to solve problems with around the double of the requirements that the main processor could support. Finally, a Dual-Core provides slightly better performance than stratix III and it is relatively cheaper.This work was supported in part under Spanish Grant PAID/2012/325 of "Programa de Apoyo a la Investigacion y Desarrollo. Proyectos multidisciplinares", Universitat Politecnica de Valencia, Spain.Domínguez Montagud, CP.; Hassan Mohamed, H.; Crespo, A.; Albaladejo Meroño, J. (2015). Multicore and FPGA implementations of emotional-based agent architectures. Journal of Supercomputing. 71(2):479-507. https://doi.org/10.1007/s11227-014-1307-6S479507712Malfaz M, Salichs MA (2010) Using MUDs as an experimental platform for testing a decision making system for self-motivated autonomous agents. Artif Intell Simul Behav J 2(1):21–44Damiano L, Cañamero L (2010) Constructing emotions. Epistemological groundings and applications in robotics for a synthetic approach to emotions. In: Proceedings of international symposium on aI-inspired biology, The Society for the Study of Artificial Intelligence, pp 20–28Hawes N, Wyatt J, Sloman A (2009) Exploring design space for an integrated intelligent system. Knowl Based Syst 22(7):509–515Sloman A (2009) Some requirements for human-like robots: why the recent over-emphasis on embodiment has held up progress. Creat Brain Like Intell 2009:248–277Arkin RC, Ulam P, Wagner AR (2012) Moral decision-making in autonomous systems: enforcement, moral emotions, dignity, trust and deception. In: Proceedings of the IEEE, Mar 2012, vol 100, no 3, pp 571–589iRobot industrial robots website. http://www.irobot.com/gi/ground/ . Accessed 22 Sept 2014Moravec H (2009) Rise of the robots: the future of artificial intelligence. Scientific American, March 2009. http://www.scientificamerican.com/article/rise-of-the-robots/ . Accessed 14 Oct 2014.Thu Bui L, Abbass HA, Barlow M, Bender A (2012) Robustness against the decision-maker’s attitude to risk in problems with conflicting objectives. IEEE Trans Evolut Comput 16(1):1–19Pedrycz W, Song M (2011) Analytic hierarchy process (AHP) in group decision making and its optimization with an allocation of information granularity. IEEE Trans Fuzzy Syst 19(3):527–539Lee-Johnson CP, Carnegie DA (2010) Mobile robot navigation modulated by artificial emotions. IEEE Trans Syst Man Cybern Part B 40(2):469–480Daglarli E, Temeltas H, Yesiloglu M (2009) Behavioral task processing for cognitive robots using artificial emotions. Neurocomputing 72(13):2835–2844Ventura R, Pinto-Ferreira C (2009) Responding efficiently to relevant stimuli using an emotion-based agent architecture. Neurocomputing 72(13):2923–2930Arkin RC, Ulam P, Wagner AR (2012) Moral decision-making in autonomous systems: enforcement, moral emotions, dignity, trust and deception. Proc IEEE 100(3):571–589Salichs MA, Malfaz M (2012) A new approach to modeling emotions and their use on a decision-making system for artificial agents. Affect Comput IEEE Trans 3(1):56–68Altera Corporation (2011) Stratix III device handbook, vol 1–2, version 2.2. http://www.altera.com/literature/lit-stx3.jsp . Accessed 14 Oct 2014.Altera Corporation (2014) Stratix IV device handbook, vol 1–4, version 5.9. http://www.altera.com/literature/lit-stratix-iv.jsp . Accessed 14 Oct 2014.Naouar MW, Monmasson E, Naassani AA, Slama-Belkhodja I, Patin N (2007) FPGA-based current controllers for AC machine drives: a review. IEEE Trans Ind Electr 54(4):1907–1925Intel Corporation (2014) Desktop 4th generation Intel Core Processor Family, Desktop Intel Pentium Processor Family, and Desktop Intel Celeron Processor Family, Datasheet, vol 1, 2March JL, Sahuquillo J, Hassan H, Petit S, Duato J (2011) A new energy-aware dynamic task set partitioning algorithm for soft and hard embedded real-time systems. Comput J 54(8):1282–1294Del Campo I, Basterretxea K, Echanobe J, Bosque G, Doctor F (2012) A system-on-chip development of a neuro-fuzzy embedded agent for ambient-intelligence environments. IEEE Trans Syst Man Cybern Part B 42(2):501–512Pedraza C, Castillo J, Martínez JI, Huerta P, Bosque JL, Cano J (2011) Genetic algorithm for Boolean minimization in an FPGA cluster. J Supercomput 58(2):244–252Orlowska-Kowalska T, Kaminski M (2011) FPGA implementation of the multilayer neural network for the speed estimation of the two-mass drive system. IEEE Trans Ind Inf 7(3):436–445Cassidy AS, Merolla P, Arthur JV, Esser SK, Jackson B, Alvarez-icaza R, Datta P, Sawada J, Wong TM, Feldman V, Amir A, Ben-dayan D, Mcquinn E, Risk WP, Modha DS (2013) Cognitive computing building block: a versatile and efficient digital neuron model for neurosynaptic cores. In: Proceedings of international joint conference on neural networks, IEEE (IJCNN’2013)IBM Cognitive Computing and Neurosynaptic chips website. http://www.research.ibm.com/cognitive-computing/neurosynaptic-chips.shtml . Accessed 22 Sept 2014Seo E, Jeong J, Park S, Lee J (2008) Energy efficient scheduling of real-time tasks on multicore processors. IEEE Trans Parallel Distrib Syst 19(11):1540–1552Lehoczky J, Sha L, Ding Y (1989) The rate monotonic scheduling algorithm: exact characterization and average case behavior. In: Proceedings of real time systems symposium, IEEE 1989, pp 166–171Ng-Thow-Hing V, Lim J, Wormer J, Sarvadevabhatla RK, Rocha C, Fujimura K, Sakagami Y (2008) The memory game: creating a human-robot interactive scenario for ASIMO. In: Proceedings of intelligent robots and systems, 2008, IROS 2008, IEEE/RSJ international conference, pp 779–78

Ratio-Based Analysis of Differential mRNA Processing and Expression of a Polyadenylation Factor Mutant pcfs4 Using Arabidopsis Tiling Microarray

US National Institutes of Health [1R15GM07719201A1]; US National Science Foundation [IOS-0817818]; Ohio Plant Biotech Consortium; National Natural Science Foundation of China [60774033]; Specialized Research Fund for the Doctoral Program of Higher EducatiBackground: Alternative polyadenylation as a mechanism in gene expression regulation has been widely recognized in recent years. Arabidopsis polyadenylation factor PCFS4 was shown to function in leaf development and in flowering time control. The function of PCFS4 in controlling flowering time was correlated with the alternative polyadenylation of FCA, a flowering time regulator. However, genetic evidence suggested additional targets of PCFS4 that may mediate its function in both flowering time and leaf development. Methodology/Principal Findings: To identify further targets, we investigated the whole transcriptome of a PCFS4 mutant using Affymetrix Arabidopsis genomic tiling 1.0R array and developed a data analysis pipeline, termed RADPRE (Ratio-based Analysis of Differential mRNA Processing and Expression). In RADPRE, ratios of normalized probe intensities between wild type Columbia and a pcfs4 mutant were first generated. By doing so, one of the major problems of tiling array data-variations caused by differential probe affinity-was significantly alleviated. With the probe ratios as inputs, a hierarchy of statistical tests was carried out to identify differentially processed genes (DPG) and differentially expressed genes (DEG). The false discovery rate (FDR) of this analysis was estimated by using the balanced random combinations of Col/pcfs4 and pcfs4/Col ratios as inputs. Gene Ontology (GO) analysis of the DPGs and DEGs revealed potential new roles of PCFS4 in stress responses besides flowering time regulation. Conclusion/Significance: We identified 68 DPGs and 114 DEGs with FDR at 1% and 2%, respectively. Most of the 68 DPGs were subjected to alternative polyadenylation, splicing or transcription initiation. Quantitative PCR analysis of a set of DPGs confirmed that most of these genes were truly differentially processed in pcfs4 mutant plants. The enriched GO term "regulation of flower development'' among PCFS4 targets further indicated the efficacy of the RADPRE pipeline. This simple but effective program is available upon request

FPGA-based Controllers

International audienc

An enhanced DC-link voltage controller for single phase AC/DC converters

International audienc

FPGA-based Space Vector Delta Modulation Current Controller for Grid connected Converters

International audienc

An improved dc-link voltage control for a three-phase PWM rectifier using an adaptive PI controller combined with load current estimation

International audienc

Experimental measurements and numerical modelling of the mechanical behaviour of a glass plain weave composite reinforcement

The study deals with the mechanical behaviour of a glass plain weave composite reinforcement. The experimental activities were focused mainly on uniaxial and biaxial extension tests. Besides, in-plane shear deformation was measured by bias extension test, and for the sake of completeness out-of-plane bending behaviour. In the numerical study, a hyperelastic constitutive model for the yarn material was adopted and validated for the meso scale prediction of the mechanical behaviour of the glass plain weave reinforcement. The model was validated for biaxial tensile and in-plane shear deformation