190 research outputs found

    Modular Construction of Complete Coalgebraic Logics

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    We present a modular approach to defining logics for a wide variety of state-based systems. The systems are modelled by coalgebras, and we use modal logics to specify their observable properties. We show that the syntax, semantics and proof systems associated to such logics can all be derived in a modular fashion. Moreover, we show that the logics thus obtained inherit soundness, completeness and expressiveness properties from their building blocks. We apply these techniques to derive sound, complete and expressive logics for a wide variety of probabilistic systems, for which no complete axiomatisation has been obtained so far

    A Novel PUF-Based Encryption Protocol for Embedded System On Chip

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    This paper presents a novel security mechanism for sensitive data stored, acquired or processed by a complex electronic circuit implemented as System-on-Chip (SoC) on an FPGA reconfigurable device. Such circuits are increasingly used in embedded or cyber systems employed in civil and military applications. Managing security in the overarching SoC presents a challenge as part of the process of securing such systems. The proposed new method is based on encrypted and authenticated communications between the microprocessor cores, FPGA fabric and peripherals inside the SoC. The encryption resides in a key generated with Physically Unclonable Function (PUF) circuits and a pseudorandom generator. The conceptual design of the security circuit was validated through hardware implementation, testing and analysis of results

    Lazy AC-Pattern Matching for Rewriting

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    We define a lazy pattern-matching mechanism modulo associativity and commutativity. The solutions of a pattern-matching problem are stored in a lazy list composed of a first substitution at the head and a non-evaluated object that encodes the remaining computations. We integrate the lazy AC-matching in a strategy language: rewriting rule and strategy application produce a lazy list of terms.Comment: In Proceedings WRS 2011, arXiv:1204.531

    Measuring movement fluency during the sit-to-walk task

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    Restoring movement fluency is a key focus for physical rehabilitation; it's measurement, however, lacks objectivity. The purpose of this study was to find whether measurable movement fluency variables differed between groups of adults with different movement abilities whilst performing the sit-to-walk (STW) movement. The movement fluency variables were: (1) hesitation during movement (reduction in forward velocity of the centre of mass; CoM), (2) coordination (percentage of temporal overlap of joint rotations) and (3) smoothness (number of inflections in the CoM jerk signal)

    Modular Hybrid Energy Concept Employing a Novel Control Structure Based on a Simple Analog System

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    This paper proposes a novel control topology which enables the setup of a low cost analog system leading to the implementation of a modular energy conversion system. The modular concept is based on hybrid renewable energy (solar and wind) and uses high voltage inverters already available on the market. An important feature of the proposed topology is a permanently active current loop, which assures short circuit protection and simplifies the control loops compensation. The innovative analogue solution of the control structure is based on a dedicated integrated circuit (IC) for power factor correction (PFC) circuits, used in a new configuration, to assure an efficient inverter start-up. The energy conversion system (control structure and maximum power point tracking algorithm) is simulated using a new macromodel-based concept, which reduces the usual computational burden of the simulator and achieves high processing speed. The proposed novel system is presented in this article from concept, through the design and implementation stages, is verified through simulation and is validated by experimental results

    The play's the thing

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    For very understandable reasons phenomenological approaches predominate in the field of sensory urbanism. This paper does not seek to add to that particular discourse. Rather it takes Rorty’s postmodernized Pragmatism as its starting point and develops a position on the role of multi-modal design representation in the design process as a means of admitting many voices and managing multidisciplinary collaboration. This paper will interrogate some of the concepts underpinning the Sensory Urbanism project to help define the scope of interest in multi-modal representations. It will then explore a range of techniques and approaches developed by artists and designers during the past fifty years or so and comment on how they might inform the question of multi-modal representation. In conclusion I will argue that we should develop a heterogeneous tool kit that adopts, adapts and re-invents existing methods because this will better serve our purposes during the exploratory phase(s) of any design project that deals with complexity

    Frequency and impact of glutathione-S-transferase gene polymorphisms on lung function and bronchial asthma susceptibility in Moldovan children

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    Scientific Department of Pediatrics, Research Institute for Maternal and Child Health Care, Congresul III al Medicilor de Familie din Republica Moldova, 17–18 mai, 2012, ChiƟinău, Republica Moldova, ConferinĆŁa NaĆŁională „Maladii bronhoobstructive la copii”, consacrată profesorului universitar, doctor habilitat Victor GheĆŁeul, 27 aprilie, ChiƟinău, Republica MoldovaAsthma is a highly prevalent chronic inflammatory disease of the respiratory tract with genetic predisposition. However, the complex mechanisms of its inheritance, from the genetic predisposition of atopy to allergic diseases, are still not completely understood. Recent data suggest that the pathogenesis of atopic diseases is complex and might be caused by gene-gene and/or gene-environmental interactions. Polymorphisms of the glutathione-S-transferase (GST) genes are known risk factors for some environmentally related diseases. The aim of the present study was to investigate the frequency of polymorphisms in the GSTT1, GSTM1, GSTP1 and NAT2 genes in the population groups of healthy Moldovans and children with asthma, and to analyze their role on lung function. The studied population included 180 subjects – 90 children with asthma, aged 5 to 17 years (mean ± VEM age of 10,9 ± 0,4 years) and 90 healthy controls who showed no signs or history of allergic diseases (mean age 13,5 ± 0,2 years). The asthma group included 51 males and 39 females, who were randomly selected from asthmatic children referred by the Allergy Clinic of the Research Institute for Maternal and Child Healthcare, Chisinau, Moldova, during 2009-2010. Asthma was defined according to the criteria of the Global Initiative for Asthma (GINA). A complete clinical history, physical examination, and pulmonary function test (PFT) were performed for all the subjects in accordance with standards. Forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) were measured using a portable spirometer (Spirobank G, Mir, Italy). Genes coding for the xenobiotic-metabolizing enzymes (GSTT1, GSTM1, GSTP1 and NAT2) were evaluated by polymerase chain reaction (PCR). Analysis of the xenobiotic-metabolizing enzyme genes’ frequency in the studied population showed an equally distributed prevalence of GST genes genotypes in the patient group in comparison with the controls. However, the heterozygous genotype of the GSTP1 341 C>T Ala114Val polymorphism was found significantly more frequent in healthy subjects (14,4±9,7% in patients vs 26,7±9,0% in controls; χ2 = 3,4, gl = 1, p=0,06). The GSTM1 null genotype was overrepresented in asthmatic males in comparison with controls (54,9±9,4% vs 35,3±11,3%; χ2 = 3,21, gl=1, p=0,07). The GSTT1 null genotype was associated with a significant decrease in the FEV1/FVC% ratio when compared with the GSTT1 wild genotype (89,3±3,4 vs 95,8±1,3, respectively, p<0,05) and the homozygous GSTP1 Val105Val genotype was associated with the decrease of FEV1 (64,4±8,2 vs 87,3±2,5 in patients with GSTP1 Ile105/x genotypes, p<0,001) and the FEV1/FVC% ratio (82,6±5,7 vs 95,8±1,2 in patients with GSTP1 Ile105/x genotypes, p<0,01). However, there was no association between GSTM1 polymorphism and lung function tests. Our results suggest that GST gene polymorphisms may play an important role in asthma susceptibility in Moldovan children. Also GST gene polymorphisms may affect asthma pathogenesis as polymorphisms influence lung functioning in asthmatic children. These findings suggest a potentially raised susceptibility to negative environmental influences and predisposition to respiratory morbidity in this particular group

    AT7519, a Novel Small Molecule Multi-Cyclin Dependent Kinase Inhibitor, Induces Apoptosis in Multiple Myeloma VIA GSK3 beta

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    Dysregulated cell cycling is a universal hallmark of cancer and is often mediated by abnormal activation of cyclin-dependent kinases (CDKs) and their cyclin partners. Overexpression of individual complexes are reported in multiple myeloma (MM), making them attractive therapeutic targets. In this study, we investigate the preclinical activity of a novel small-molecule multi-CDK inhibitor, AT7519, in MM. We show the anti-MM activity of AT7519 displaying potent cytotoxicity and apoptosis; associated with in vivo tumor growth inhibition and prolonged survival. At the molecular level, AT7519 inhibited RNA polymerase II (RNA pol II) phosphorylation, a CDK9, 7 substrate, associated with decreased RNA synthesis confirmed by [(3)H] Uridine incorporation. In addition, AT7519 inhibited glycogen synthase kinase 3beta (GSK-3beta) phosphorylation; conversely pretreatment with a selective GSK-3 inhibitor and shRNA GSK-3beta knockdown restored MM survival, suggesting the involvement of GSK-3beta in AT7519-induced apoptosis. GSK-3beta activation was independent of RNA pol II dephosphorylation confirmed by alpha-amanitin, a specific RNA pol II inihibitor, showing potent inhibition of RNA pol II phosphorylation without corresponding effects on GSK-3beta phosphorylation. These results offer new insights into the crucial, yet controversial role of GSK-3beta in MM and show significant anti-MM activity of AT7519, providing the rationale for its clinical evaluation in MM

    Transcription of Spanish Historical Handwritten Documents with Deep Neural Networks

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    [EN] The digitization of historical handwritten document images is important for the preservation of cultural heritage. Moreover, the transcription of text images obtained from digitization is necessary to provide efficient information access to the content of these documents. Handwritten Text Recognition (HTR) has become an important research topic in the areas of image and computational language processing that allows us to obtain transcriptions from text images. State-of-the-art HTR systems are, however, far from perfect. One difficulty is that they have to cope with image noise and handwriting variability. Another difficulty is the presence of a large amount of Out-Of-Vocabulary (OOV) words in ancient historical texts. A solution to this problem is to use external lexical resources, but such resources might be scarce or unavailable given the nature and the age of such documents. This work proposes a solution to avoid this limitation. It consists of associating a powerful optical recognition system that will cope with image noise and variability, with a language model based on sub-lexical units that will model OOV words. Such a language modeling approach reduces the size of the lexicon while increasing the lexicon coverage. Experiments are first conducted on the publicly available Rodrigo dataset, which contains the digitization of an ancient Spanish manuscript, with a recognizer based on Hidden Markov Models (HMMs). They show that sub-lexical units outperform word units in terms of Word Error Rate (WER), Character Error Rate (CER) and OOV word accuracy rate. This approach is then applied to deep net classifiers, namely Bi-directional Long-Short Term Memory (BLSTMs) and Convolutional Recurrent Neural Nets (CRNNs). Results show that CRNNs outperform HMMs and BLSTMs, reaching the lowest WER and CER for this image dataset and significantly improving OOV recognition.Work partially supported by projects READ: Recognition and Enrichment of Archival Documents - 674943 (European Union's H2020) and CoMUN-HaT: Context, Multimodality and User Collaboration in Handwritten Text Processing - TIN2015-70924-C2-1-R (MINECO/FEDER), and a DGA-MRIS (Direction Generale de l'Armement - Mission pour la Recherche et l'Innovation Scientifique) scholarship.Granell, E.; Chammas, E.; Likforman-Sulem, L.; MartĂ­nez-Hinarejos, C.; Mokbel, C.; Cirstea, B. (2018). Transcription of Spanish Historical Handwritten Documents with Deep Neural Networks. Journal of imaging. 4(1). https://doi.org/10.3390/jimaging4010015S154
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