On the Enforcement of a Class of Nonlinear Constraints on Petri Nets

International audienceThis paper focuses on the enforcement of nonlinear constraints in Petri nets. First, a supervisory structure is proposed for a nonlinear constraint. The proposed structure consists of added places and transitions. It controls the transitions in the net to be controlled only but does not change its states since there is no arc between the added transitions and the places in the original net. Second, an integer linear programming model is proposed to transform a nonlinear constraint to a minimal number of conjunc-tive linear constraints that have the same control performance as the nonlinear one. By using a place invariant based method, the obtained linear constraints can be easily enforced by a set of control places. The control places consist to a supervisor that can enforce the given nonlinear constraint. On condition that the admissible markings space of a nonlinear constraint is non-convex, another integer linear programming model is developed to obtain a minimal number of constraints whose disjunctions are equivalent to the nonlinear constraint. Finally, a number of examples are provided to demonstrate the proposed approach

Observation of enhanced visible and infrared emissions in photonic crystal thin-film light-emitting diodes

Photonic crystals, in the form of closed-packed nano-pillar arrays patterned by nanosphere lithography, have been formed on the n-faces of InGaN thin-film vertical light-emitting diodes (LEDs). Through laser lift-off of the sapphire substrate, the thin-film LEDs conduct vertically with reduced dynamic resistances, as well as reduced thermal resistances. The photonic crystal plays a role in enhancing light extraction, not only at visible wavelengths but also at infrared wavelengths boosting heat radiation at high currents, so that heat-induced effects on internal quantum efficiencies are minimized. The observations are consistent with predictions from finite-difference time-domain simulations. © 2014 AIP Publishing LLC.published_or_final_versio

Characterization of soluble microbial products as precursors of disinfection byproducts in drinking water supply

Water pollution by wastewater discharge can cause the problem of disinfection byproducts (DBPs) in drinking water supply. In this study, DBP formation characteristics of soluble microbial products (SMPs) as the main products of wastewater organic biodegradation were investigated. The results show that SMPs can act as DBP precursors in simulated wastewater biodegradation process. Under the experimental conditions, stabilized SMPs had DBPFP (DBP formation potential) yield of around 5.6 mumol mmol(-1)-DOC (dissolved organic carbon) and DBP speciation profile different from that of the conventional precursor, natural organic matter (NOM). SMPs contained polysaccharides, proteins, and humic-like substances, and the latter two groups can act as reactive DBP precursors. SMP fraction with molecular weight of <1 kDa accounted for 85% of the organic carbon and 65% of the DBP formation. As small SMP molecules are more difficult to remove by conventional water treatment processes, more efforts are needed to control wastewater-derived DBP problem in water resource management.postprin

Deep Learning networks with p-norm loss layers for spatial resolution enhancement of 3D medical images

Thurnhofer-Hemsi K., López-Rubio E., Roé-Vellvé N., Molina-Cabello M.A. (2019) Deep Learning Networks with p-norm Loss Layers for Spatial Resolution Enhancement of 3D Medical Images. In: Ferrández Vicente J., Álvarez-Sánchez J., de la Paz López F., Toledo Moreo J., Adeli H. (eds) From Bioinspired Systems and Biomedical Applications to Machine Learning. IWINAC 2019. Lecture Notes in Computer Science, vol 11487. Springer, ChamNowadays, obtaining high-quality magnetic resonance (MR) images is a complex problem due to several acquisition factors, but is crucial in order to perform good diagnostics. The enhancement of the resolution is a typical procedure applied after the image generation. State-of-the-art works gather a large variety of methods for super-resolution (SR), among which deep learning has become very popular during the last years. Most of the SR deep-learning methods are based on the min- imization of the residuals by the use of Euclidean loss layers. In this paper, we propose an SR model based on the use of a p-norm loss layer to improve the learning process and obtain a better high-resolution (HR) image. This method was implemented using a three-dimensional convolutional neural network (CNN), and tested for several norms in order to determine the most robust t. The proposed methodology was trained and tested with sets of MR structural T1-weighted images and showed better outcomes quantitatively, in terms of Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM), and the restored and the calculated residual images showed better CNN outputs.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Left ventricular mechanics in repaired tetralogy of Fallot with and without pulmonary valve replacement: analysis by three-dimensional speckle tracking echocardiography

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Genes encoding Pir51, Beclin 1, RbAp48 and aldolase b are up or down-regulated in human primary hepatocellular carcinoma

Aim: To reveal new tumor markers and target genes from differentially expressed genes of primary tumor samples using cDNA microarray. Methods: The 33P labeled cDNAs were synthesized by reverse transcription of message RNA from the liver cancerous tissue and adjacent non-cancerous liver tissue from the same patient and used to hybridize to LifeGrid 1.0 cDNA microarray blot containing 8400 known and unique human cDNA gene targets, and an expression profile of genes was produced in one paired human liver tumor tissue. After a global analysis of gene expression of 8400 genes, we selected some genes to confirm the differential expression using Northern blot and RT-PCR. Results: Parallel analysis of the hybridized signals enabled us to get an expression profile of genes in which about 500 genes were differentially expressed in the paired liver tumor tissues. We identified 4 genes, the expression of three (Beclin 1, RbAp48 and Pir51) were increased and one (aldolase b) was decreased in liver tumor tissues. In addition, the expression of these genes in 6 hepatoma cell lines was also showed by RT-PCR analysis. Conclusion: cDNA microarray permits a high throughput identification of changes in gene expression. The genes encoding Beclin 1, RbAp48, Pir51 and aldolase b are first reported that may be related with hepatocarcinoma. Copyright © 2004 by The WJG Press ISSN 1007-9327.published_or_final_versio

Cramér-Rao Bound Optimization for Joint Radar-Communication Beamforming

In this paper, we propose multi-input multi-output (MIMO) beamforming designs towards joint radar sensing and multi-user communications. We employ the Cramr-Rao bound (CRB) as a performance metric of target estimation, under both point and extended target scenarios. We then propose minimizing the CRB of radar sensing while guaranteeing a pre-defined level of signal-to-interference-plus-noise ratio (SINR) for each communication user. For the single-user scenario, we derive a closed form for the optimal solution for both cases of point and extended targets. For the multi-user scenario, we show that both problems can be relaxed into semidefinite programming by using the semidefinite relaxation approach, and prove that the global optimum can always be obtained. Finally, we demonstrate numerically that the globally optimal solutions are reachable via the proposed methods, which provide significant gains in target estimation performance over state-of-the-art benchmarks

Performance improvements of a split-off band infra-red detector using a graded barrier

Uncooled split-off band infrared detectors have been demonstrated with an operational device response in the 3–5 μm range. We have shown that it is possible to enhance this device response through reducing the recapture rate by replacing one of the commonly used flat barriers in the device with a graded barrier, which was grown using a “digital alloying” approach. Responsivity of approximately 80 μA/W (D* = 1.4 × 108 Jones) were observed at 78 K under a 1 V applied bias, with a peak response at 2.8 μm. This is an improvement by a factor of ∼25 times compared to an equivalent device with a flat barrier. This enhancement is due to improved carrier transport resulting from the superlattice structure, and a low recapture rate enabled by a reduced distance to the image force potential peak in the graded barrier. The device performance can be further improved by growing a structure with repeats of the single emitter layer reported here

Analysis of investigation of undergraduate nurse's critical thinking

2003-2004 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Left ventricular torsional mechanics and myocardial iron load in beta-thalassaemia major: a potential role of titin degradation

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