Multivariable control of a grid-connected wind energy conversion system with power quality enhancement

This document is the Accepted Manuscript version of the following article: Kaddour Fouad, Houari Merabet Boulouiha, Ahmed Allali, Ali Taibi, and Mouloud Denai, ‘Multivariable control of a grid-connected wind energy conversion system with power quality enhancement’, Energy Systems, Vol. 9 (1): 25-57, February 2018. The final publication is available at Springer via: https://doi.org/10.1007/s12667-016-0223-7This paper proposes the design of a multivariable robust control strategy for a variable-speed WECS based on a SCIG. Optimal speed control of the SCIG is achieved by a conventional PI controller combined with a MPPT strategy. DTC-SVM technique based on a simple Clarke transformation is used to control the generator-side three-level converter in the variable speed WECS. The flow of real and reactive power between the inverter and the grid is controlled via the grid real and reactive currents and the DC link voltage using multivariable H∞ control. The overall WECS and control scheme are developed in Matlab/Simulink and the performance of the proposed control strategy is evaluated via a set of simulation scenarios replicating various operating conditions of the WECS such as variable wind speed and asymmetric single grid faults. The power quality of the WECS system under H∞ control control approach is assessed and the results show a significant improvement in the total harmonic distorsion as compared to that achieved with a classical PI control.Peer reviewedFinal Accepted Versio

Robo2-Slit1 dependent cell-cell interactions mediate assembly of the trigeminal ganglion

Vertebrate cranial sensory ganglia, responsible for sensation of touch, taste and pain in the face and viscera, are composed of both ectodermal placode and neural crest cells. The cellular and molecular interactions allowing generation of complex ganglia remain unknown. Here, we show that proper formation of the trigeminal ganglion, the largest of the cranial ganglia, relies on reciprocal interactions between placode and neural crest cells in chick, as removal of either population resulted in severe defects. We demonstrate that ingressing placode cells express the Robo2 receptor and early migrating cranial neural crest cells express its cognate ligand Slit1. Perturbation of this receptor-ligand interaction by blocking Robo2 function or depleting either Robo2 or Slit1 using RNA interference disrupted proper ganglion formation. The resultant disorganization mimics the effects of neural crest ablation. Thus, our data reveal a novel and essential role for Robo2-Slit1 signaling in mediating neural crest–placode interactions during trigeminal gangliogenesis

Identification of biomolecule mass transport and binding rate parameters in living cells by inverse modeling

BACKGROUND: Quantification of in-vivo biomolecule mass transport and reaction rate parameters from experimental data obtained by Fluorescence Recovery after Photobleaching (FRAP) is becoming more important. METHODS AND RESULTS: The Osborne-Moré extended version of the Levenberg-Marquardt optimization algorithm was coupled with the experimental data obtained by the Fluorescence Recovery after Photobleaching (FRAP) protocol, and the numerical solution of a set of two partial differential equations governing macromolecule mass transport and reaction in living cells, to inversely estimate optimized values of the molecular diffusion coefficient and binding rate parameters of GFP-tagged glucocorticoid receptor. The results indicate that the FRAP protocol provides enough information to estimate one parameter uniquely using a nonlinear optimization technique. Coupling FRAP experimental data with the inverse modeling strategy, one can also uniquely estimate the individual values of the binding rate coefficients if the molecular diffusion coefficient is known. One can also simultaneously estimate the dissociation rate parameter and molecular diffusion coefficient given the pseudo-association rate parameter is known. However, the protocol provides insufficient information for unique simultaneous estimation of three parameters (diffusion coefficient and binding rate parameters) owing to the high intercorrelation between the molecular diffusion coefficient and pseudo-association rate parameter. Attempts to estimate macromolecule mass transport and binding rate parameters simultaneously from FRAP data result in misleading conclusions regarding concentrations of free macromolecule and bound complex inside the cell, average binding time per vacant site, average time for diffusion of macromolecules from one site to the next, and slow or rapid mobility of biomolecules in cells. CONCLUSION: To obtain unique values for molecular diffusion coefficient and binding rate parameters from FRAP data, we propose conducting two FRAP experiments on the same class of macromolecule and cell. One experiment should be used to measure the molecular diffusion coefficient independently of binding in an effective diffusion regime and the other should be conducted in a reaction dominant or reaction-diffusion regime to quantify binding rate parameters. The method described in this paper is likely to be widely used to estimate in-vivo biomolecule mass transport and binding rate parameters

Independent policy learning: Contextual diffusion of active labour market policies

This chapter analyses in which ways diffusion based on interdependent policy learning explains the spread of active labour market policies (ALMP) in the OECD countries. By applying error correction models using multiplicative spatial Prais-Winsten regressions for analyzing the diffusion of ALMPs in 22 OECD countries from 1991–2013, we find evidence of governments adapting labour market policy strategies that have proven successful, that is, perform well in increasing labour market participation in other countries. However, interdependent learning is conditional on the institutional framework: policymakers rather learn from the experience of other countries in the same welfare regime. Even more importantly, the results bear witness to the importance of the European Employment Strategy (EES) as an international coordination framework facilitating policy learning

Stabilization of Dicentric Translocations through Secondary Rearrangements Mediated by Multiple Mechanisms in S. cerevisiae

The gross chromosomal rearrangements (GCRs) observed in S. cerevisiae mutants with increased rates of accumulating GCRs include predicted dicentric GCRs such as translocations, chromosome fusions and isoduplications. These GCRs resemble the genome rearrangements found as mutations underlying inherited diseases as well as in the karyotypes of many cancers exhibiting ongoing genome instabilityThe structures of predicted dicentric GCRs were analyzed using multiple strategies including array-comparative genomic hybridization, pulse field gel electrophoresis, PCR amplification of predicted breakpoints and sequencing. The dicentric GCRs were found to be unstable and to have undergone secondary rearrangements to produce stable monocentric GCRs. The types of secondary rearrangements observed included: non-homologous end joining (NHEJ)-dependent intramolecular deletion of centromeres; chromosome breakage followed by NHEJ-mediated circularization or broken-end fusion to another chromosome telomere; and homologous recombination (HR)-dependent non-reciprocal translocations apparently mediated by break-induced replication. A number of these GCRs appeared to have undergone multiple bridge-fusion-breakage cycles. We also observed examples of chromosomes with extensive ongoing end decay in mec1 tlc1 mutants, suggesting that Mec1 protects chromosome ends from degradation and contributes to telomere maintenance by HR.HR between repeated sequences resulting in secondary rearrangements was the most prevalent pathway for resolution of dicentric GCRs regardless of the structure of the initial dicentric GCR, although at least three other resolution mechanisms were observed. The resolution of dicentric GCRs to stable rearranged chromosomes could in part account for the complex karyotypes seen in some cancers

Massive-Scale RNA-Seq Analysis of Non Ribosomal Transcriptome in Human Trisomy 21

Hybridization- and tag-based technologies have been successfully used in Down syndrome to identify genes involved in various aspects of the pathogenesis. However, these technologies suffer from several limits and drawbacks and, to date, information about rare, even though relevant, RNA species such as long and small non-coding RNAs, is completely missing. Indeed, none of published works has still described the whole transcriptional landscape of Down syndrome. Although the recent advances in high-throughput RNA sequencing have revealed the complexity of transcriptomes, most of them rely on polyA enrichment protocols, able to detect only a small fraction of total RNA content. On the opposite end, massive-scale RNA sequencing on rRNA-depleted samples allows the survey of the complete set of coding and non-coding RNA species, now emerging as novel contributors to pathogenic mechanisms. Hence, in this work we analysed for the first time the complete transcriptome of human trisomic endothelial progenitor cells to an unprecedented level of resolution and sensitivity by RNA-sequencing. Our analysis allowed us to detect differential expression of even low expressed genes crucial for the pathogenesis, to disclose novel regions of active transcription outside yet annotated loci, and to investigate a plethora of non-polyadenilated long as well as short non coding RNAs. Novel splice isoforms for a large subset of crucial genes, and novel extended untranslated regions for known genes—possibly novel miRNA targets or regulatory sites for gene transcription—were also identified in this study. Coupling the rRNA depletion of samples, followed by high-throughput RNA-sequencing, to the easy availability of these cells renders this approach very feasible for transcriptome studies, offering the possibility of investigating in-depth blood-related pathological features of Down syndrome, as well as other genetic disorders

BRCA1 and BRCA2 as molecular targets for phytochemicals indole-3-carbinol and genistein in breast and prostate cancer cells

Indole-3-carbinol (I3C) and genistein are naturally occurring chemicals derived from cruciferous vegetables and soy, respectively, with potential cancer prevention activity for hormone-responsive tumours (e.g., breast and prostate cancers). Previously, we showed that I3C induces BRCA1 expression and that both I3C and BRCA1 inhibit oestrogen (E2)-stimulated oestrogen receptor (ER-α) activity in human breast cancer cells. We now report that both I3C and genistein induce the expression of both breast cancer susceptibility genes (BRCA1 and BRCA2) in breast (MCF-7 and T47D) and prostate (DU-145 and LNCaP) cancer cell types, in a time- and dose-dependent fashion. Induction of the BRCA genes occurred at low doses of I3C (20 μM) and genistein (0.5–1.0 μM), suggesting potential relevance to cancer prevention. A combination of I3C and genistein gave greater than expected induction of BRCA expression. Studies using small interfering RNAs (siRNAs) and BRCA expression vectors suggest that the phytochemical induction of BRCA2 is due, in part, to BRCA1. Functional studies suggest that I3C-mediated cytoxicity is, in part, dependent upon BRCA1 and BRCA2. Inhibition of E2-stimulated ER-α activity by I3C and genistein was dependent upon BRCA1; and inhibition of ligand-inducible androgen receptor (AR) activity by I3C and genistein was partially reversed by BRCA1-siRNA. Finally, we provide evidence suggesting that the phytochemical induction of BRCA1 expression is due, in part, to endoplasmic reticulum stress response signalling. These findings suggest that the BRCA genes are molecular targets for some of the activities of I3C and genistein