Global transcriptional regulatory network for Escherichia coli robustly connects gene expression to transcription factor activities

Science.gov (United States)

Fang, Xin; Sastry, Anand; Mih, Nathan; Kim, Donghyuk; Tan, Justin; Lloyd, Colton J.; Gao, Ye; Yang, Laurence; Palsson, Bernhard O.

2017-01-01

Transcriptional regulatory networks (TRNs) have been studied intensely for >25 y. Yet, even for the Escherichia coli TRN—probably the best characterized TRN—several questions remain. Here, we address three questions: (i) How complete is our knowledge of the E. coli TRN; (ii) how well can we predict gene expression using this TRN; and (iii) how robust is our understanding of the TRN? First, we reconstructed a high-confidence TRN (hiTRN) consisting of 147 transcription factors (TFs) regulating 1,538 transcription units (TUs) encoding 1,764 genes. The 3,797 high-confidence regulatory interactions were collected from published, validated chromatin immunoprecipitation (ChIP) data and RegulonDB. For 21 different TF knockouts, up to 63% of the differentially expressed genes in the hiTRN were traced to the knocked-out TF through regulatory cascades. Second, we trained supervised machine learning algorithms to predict the expression of 1,364 TUs given TF activities using 441 samples. The algorithms accurately predicted condition-specific expression for 86% (1,174 of 1,364) of the TUs, while 193 TUs (14%) were predicted better than random TRNs. Third, we identified 10 regulatory modules whose definitions were robust against changes to the TRN or expression compendium. Using surrogate variable analysis, we also identified three unmodeled factors that systematically influenced gene expression. Our computational workflow comprehensively characterizes the predictive capabilities and systems-level functions of an organism’s TRN from disparate data types. PMID:28874552

Robust Control of a Cable-Driven Soft Exoskeleton Joint for Intrinsic Human-Robot Interaction.

Science.gov (United States)

Jarrett, C; McDaid, A J

2017-07-01

A novel, cable-driven soft joint is presented for use in robotic rehabilitation exoskeletons to provide intrinsic, comfortable human-robot interaction. The torque-displacement characteristics of the soft elastomeric core contained within the joint are modeled. This knowledge is used in conjunction with a dynamic system model to derive a sliding mode controller (SMC) to implement low-level torque control of the joint. The SMC controller is experimentally compared with a baseline feedback-linearised proportional-derivative controller across a range of conditions and shown to be robust to un-modeled disturbances. The torque controller is then tested with six healthy subjects while they perform a selection of activities of daily living, which has validated its range of performance. Finally, a case study with a participant with spastic cerebral palsy is presented to illustrate the potential of both the joint and controller to be used in a physiotherapy setting to assist clinical populations.

Expression robust 3D face recognition via mesh-based histograms of multiple order surface differential quantities

KAUST Repository

Li, Huibin; Huang, Di; Lemaire, Pierre; Morvan, Jean-Marie; Chen, Liming

2011-01-01

same person than the ones of different persons. Experimental results on the Bosphorus dataset highlight the effectiveness of the proposed method and its robustness to facial expression variations. © 2011 IEEE.

Rapid expression of transgenes driven by seed-specific constructs in leaf tissue: DHA production

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Zhou Xue-Rong

2010-03-01

Full Text Available Abstract Background Metabolic engineering of seed biosynthetic pathways to diversify and improve crop product quality is a highly active research area. The validation of genes driven by seed-specific promoters is time-consuming since the transformed plants must be grown to maturity before the gene function can be analysed. Results In this study we demonstrate that genes driven by seed-specific promoters contained within complex constructs can be transiently-expressed in the Nicotiana benthamiana leaf-assay system by co-infiltrating the Arabidopsis thaliana LEAFY COTYLEDON2 (LEC2 gene. A real-world case study is described in which we first assembled an efficient transgenic DHA synthesis pathway using a traditional N. benthamiana Cauliflower Mosaic Virus (CaMV 35S-driven leaf assay before using the LEC2-extended assay to rapidly validate a complex seed-specific construct containing the same genes before stable transformation in Arabidopsis. Conclusions The LEC2-extended N. benthamiana assay allows the transient activation of seed-specific promoters in leaf tissue. In this study we have used the assay as a rapid preliminary screen of a complex seed-specific transgenic construct prior to stable transformation, a feature that will become increasingly useful as genetic engineering moves from the manipulation of single genes to the engineering of complex pathways. We propose that the assay will prove useful for other applications wherein rapid expression of transgenes driven by seed-specific constructs in leaf tissue are sought.

Dendrimer-driven neurotrophin expression differs in temporal patterns between rodent and human stem cells.

Science.gov (United States)

Shakhbazau, Antos; Shcharbin, Dzmitry; Seviaryn, Ihar; Goncharova, Natalya; Kosmacheva, Svetlana; Potapnev, Mihail; Bryszewska, Maria; Kumar, Ranjan; Biernaskie, Jeffrey; Midha, Rajiv

2012-05-07

This study reports the use of a nonviral expression system based on polyamidoamine dendrimers for time-restricted neurotrophin overproduction in mesenchymal stem cells and skin precursor-derived Schwann cells. The dendrimers were used to deliver plasmids for brain-derived neurotrophic factor (BDNF) or neurotrophin-3 (NT-3) expression in both rodent and human stem cells, and the timelines of expression were studied. We have found that, despite the fact that transfection efficiencies and protein expression levels were comparable, dendrimer-driven expression in human mesenchymal stem cells was characterized by a more rapid decline compared to rodent cells. Transient expression systems can be beneficial for some neurotrophins, which were earlier reported to cause unwanted side effects in virus-based long-term expression models. Nonviral neurotrophin expression is a biologically safe and accessible alternative to increase the therapeutic potential of autologous adult stem cells and stem cell-derived functional differentiated cells.

Adaptive robust trajectory tracking control of a parallel manipulator driven by pneumatic cylinders

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Ce Shang

2016-04-01

Full Text Available Due to the compressibility of air, non-linear characteristics, and parameter uncertainties of pneumatic elements, the position control of a pneumatic cylinder or parallel platform is still very difficult while comparing with the systems driven by electric or hydraulic power. In this article, based on the basic dynamic model and descriptions of thermal processes, a controller integrated with online parameter estimation is proposed to improve the performance of a pneumatic cylinder controlled by a proportional valve. The trajectory tracking error is significantly decreased by applying this method. Moreover, the algorithm is expanded to the problem of posture trajectory tracking for the three-revolute prismatic spherical pneumatic parallel manipulator. Lyapunov’s method is used to give the proof of stability of the controller. Using NI-CompactRio, NI-PXI, and Veristand platform as the realistic controller hardware and data interactive environment, the adaptive robust control algorithm is applied to the physical system successfully. Experimental results and data analysis showed that the posture error of the platform could be about 0.5%–0.7% of the desired trajectory amplitude. By integrating this method to the mechatronic system, the pneumatic servo solutions can be much more competitive in the industrial market of position and posture control.

Neuronal MHC Class I Expression Is Regulated by Activity Driven Calcium Signaling.

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Dan Lv

Full Text Available MHC class I (MHC-I molecules are important components of the immune system. Recently MHC-I have been reported to also play important roles in brain development and synaptic plasticity. In this study, we examine the molecular mechanism(s underlying activity-dependent MHC-I expression using hippocampal neurons. Here we report that neuronal expression level of MHC-I is dynamically regulated during hippocampal development after birth in vivo. Kainic acid (KA treatment significantly increases the expression of MHC-I in cultured hippocampal neurons in vitro, suggesting that MHC-I expression is regulated by neuronal activity. In addition, KA stimulation decreased the expression of pre- and post-synaptic proteins. This down-regulation is prevented by addition of an MHC-I antibody to KA treated neurons. Further studies demonstrate that calcium-dependent protein kinase C (PKC is important in relaying KA simulation activation signals to up-regulated MHC-I expression. This signaling cascade relies on activation of the MAPK pathway, which leads to increased phosphorylation of CREB and NF-κB p65 while also enhancing the expression of IRF-1. Together, these results suggest that expression of MHC-I in hippocampal neurons is driven by Ca2+ regulated activation of the MAPK signaling transduction cascade.

Robust Transgene Expression from Bicistronic mRNA in the Green Alga Chlamydomonas reinhardtii

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Masayuki Onishi

2016-12-01

Full Text Available The unicellular green alga Chlamydomonas reinhardtii is a model organism that provides an opportunity to understand the evolution and functional biology of the lineage that includes the land plants, as well as aspects of the fundamental core biology conserved throughout the eukaryotic phylogeny. Although many tools are available to facilitate genetic, molecular biological, biochemical, and cell biological studies in Chlamydomonas, expression of unselected transgenes of interest (GOIs has been challenging. In most methods used previously, the GOI and a selectable marker are expressed from two separate mRNAs, so that their concomitant expression is not guaranteed. In this study, we developed constructs that allow expression of an upstream GOI and downstream selectable marker from a single bicistronic mRNA. Although this approach in other systems has typically required a translation-enhancing element such as an internal ribosome entry site for the downstream marker, we found that a short stretch of unstructured junction sequence was sufficient to obtain adequate expression of the downstream gene, presumably through post-termination reinitiation. With this system, we obtained robust expression of both endogenous and heterologous GOIs, including fluorescent proteins and tagged fusion proteins, in the vast majority of transformants, thus eliminating the need for tedious secondary screening for GOI-expressing transformants. This improved efficiency should greatly facilitate a variety of genetic and cell-biological studies in Chlamydomonas and also enable new applications such as expression-based screens and large-scale production of foreign proteins.

Super-delta: a new differential gene expression analysis procedure with robust data normalization.

Science.gov (United States)

Liu, Yuhang; Zhang, Jinfeng; Qiu, Xing

2017-12-21

Normalization is an important data preparation step in gene expression analyses, designed to remove various systematic noise. Sample variance is greatly reduced after normalization, hence the power of subsequent statistical analyses is likely to increase. On the other hand, variance reduction is made possible by borrowing information across all genes, including differentially expressed genes (DEGs) and outliers, which will inevitably introduce some bias. This bias typically inflates type I error; and can reduce statistical power in certain situations. In this study we propose a new differential expression analysis pipeline, dubbed as super-delta, that consists of a multivariate extension of the global normalization and a modified t-test. A robust procedure is designed to minimize the bias introduced by DEGs in the normalization step. The modified t-test is derived based on asymptotic theory for hypothesis testing that suitably pairs with the proposed robust normalization. We first compared super-delta with four commonly used normalization methods: global, median-IQR, quantile, and cyclic loess normalization in simulation studies. Super-delta was shown to have better statistical power with tighter control of type I error rate than its competitors. In many cases, the performance of super-delta is close to that of an oracle test in which datasets without technical noise were used. We then applied all methods to a collection of gene expression datasets on breast cancer patients who received neoadjuvant chemotherapy. While there is a substantial overlap of the DEGs identified by all of them, super-delta were able to identify comparatively more DEGs than its competitors. Downstream gene set enrichment analysis confirmed that all these methods selected largely consistent pathways. Detailed investigations on the relatively small differences showed that pathways identified by super-delta have better connections to breast cancer than other methods. As a new pipeline, super

Indirect two-sided relative ranking: a robust similarity measure for gene expression data

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Licamele Louis

2010-03-01

Full Text Available Abstract Background There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunately, these experimental variations have generally prevented researchers from accurately comparing and combining this wealth of data, which still hides many novel insights. Results In this paper we present a new method, which we refer to as indirect two-sided relative ranking, for comparing gene expression profiles that is robust to variations in experimental conditions. This method extends the current best approach, which is based on comparing the correlations of the up and down regulated genes, by introducing a comparison based on the correlations in rankings across the entire database. Because our method is robust to experimental variations, it allows a greater variety of gene expression data to be combined, which, as we show, leads to richer scientific discoveries. Conclusions We demonstrate the benefit of our proposed indirect method on several datasets. We first evaluate the ability of the indirect method to retrieve compounds with similar therapeutic effects across known experimental barriers, namely vehicle and batch effects, on two independent datasets (one private and one public. We show that our indirect method is able to significantly improve upon the previous state-of-the-art method with a substantial improvement in recall at rank 10 of 97.03% and 49.44%, on each dataset, respectively. Next, we demonstrate that our indirect method results in improved accuracy for classification in several additional datasets. These datasets demonstrate the use of our indirect method for classifying cancer subtypes, predicting drug sensitivity/resistance, and classifying (related cell types. Even in the absence of a known (i.e., labeled experimental barrier, the improvement of the indirect method in each of these datasets is statistically significant.

Robust Data-Driven Inference for Density-Weighted Average Derivatives

DEFF Research Database (Denmark)

Cattaneo, Matias D.; Crump, Richard K.; Jansson, Michael

This paper presents a new data-driven bandwidth selector compatible with the small bandwidth asymptotics developed in Cattaneo, Crump, and Jansson (2009) for density- weighted average derivatives. The new bandwidth selector is of the plug-in variety, and is obtained based on a mean squared error...

A zebrafish model of chordoma initiated by notochord-driven expression of HRASV12

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Alexa Burger

2014-07-01

Full Text Available Chordoma is a malignant tumor thought to arise from remnants of the embryonic notochord, with its origin in the bones of the axial skeleton. Surgical resection is the standard treatment, usually in combination with radiation therapy, but neither chemotherapeutic nor targeted therapeutic approaches have demonstrated success. No animal model and only few chordoma cell lines are available for preclinical drug testing, and, although no druggable genetic drivers have been identified, activation of EGFR and downstream AKT-PI3K pathways have been described. Here, we report a zebrafish model of chordoma, based on stable transgene-driven expression of HRASV12 in notochord cells during development. Extensive intra-notochordal tumor formation is evident within days of transgene expression, ultimately leading to larval death. The zebrafish tumors share characteristics of human chordoma as demonstrated by immunohistochemistry and electron microscopy. The mTORC1 inhibitor rapamycin, which has some demonstrated activity in a chordoma cell line, delays the onset of tumor formation in our zebrafish model, and improves survival of tumor-bearing fish. Consequently, the HRASV12-driven zebrafish model of chordoma could enable high-throughput screening of potential therapeutic agents for the treatment of this refractory cancer.

Robust stratification of breast cancer subtypes using differential patterns of transcript isoform expression.

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Thomas P Stricker

2017-03-01

Full Text Available Breast cancer, the second leading cause of cancer death of women worldwide, is a heterogenous disease with multiple different subtypes. These subtypes carry important implications for prognosis and therapy. Interestingly, it is known that these different subtypes not only have different biological behaviors, but also have distinct gene expression profiles. However, it has not been rigorously explored whether particular transcriptional isoforms are also differentially expressed among breast cancer subtypes, or whether transcript isoforms from the same sets of genes can be used to differentiate subtypes. To address these questions, we analyzed the patterns of transcript isoform expression using a small set of RNA-sequencing data for eleven Estrogen Receptor positive (ER+ subtype and fourteen triple negative (TN subtype tumors. We identified specific sets of isoforms that distinguish these tumor subtypes with higher fidelity than standard mRNA expression profiles. We found that alternate promoter usage, alternative splicing, and alternate 3'UTR usage are differentially regulated in breast cancer subtypes. Profiling of isoform expression in a second, independent cohort of 68 tumors confirmed that expression of splice isoforms differentiates breast cancer subtypes. Furthermore, analysis of RNAseq data from 594 cases from the TCGA cohort confirmed the ability of isoform usage to distinguish breast cancer subtypes. Also using our expression data, we identified several RNA processing factors that were differentially expressed between tumor subtypes and/or regulated by estrogen receptor, including YBX1, YBX2, MAGOH, MAGOHB, and PCBP2. RNAi knock-down of these RNA processing factors in MCF7 cells altered isoform expression. These results indicate that global dysregulation of splicing in breast cancer occurs in a subtype-specific and reproducible manner and is driven by specific differentially expressed RNA processing factors.

A zebrafish model of chordoma initiated by notochord-driven expression of HRASV12.

Science.gov (United States)

Burger, Alexa; Vasilyev, Aleksandr; Tomar, Ritu; Selig, Martin K; Nielsen, G Petur; Peterson, Randall T; Drummond, Iain A; Haber, Daniel A

2014-07-01

Chordoma is a malignant tumor thought to arise from remnants of the embryonic notochord, with its origin in the bones of the axial skeleton. Surgical resection is the standard treatment, usually in combination with radiation therapy, but neither chemotherapeutic nor targeted therapeutic approaches have demonstrated success. No animal model and only few chordoma cell lines are available for preclinical drug testing, and, although no druggable genetic drivers have been identified, activation of EGFR and downstream AKT-PI3K pathways have been described. Here, we report a zebrafish model of chordoma, based on stable transgene-driven expression of HRASV12 in notochord cells during development. Extensive intra-notochordal tumor formation is evident within days of transgene expression, ultimately leading to larval death. The zebrafish tumors share characteristics of human chordoma as demonstrated by immunohistochemistry and electron microscopy. The mTORC1 inhibitor rapamycin, which has some demonstrated activity in a chordoma cell line, delays the onset of tumor formation in our zebrafish model, and improves survival of tumor-bearing fish. Consequently, the HRASV12-driven zebrafish model of chordoma could enable high-throughput screening of potential therapeutic agents for the treatment of this refractory cancer. © 2014. Published by The Company of Biologists Ltd.

Differential adenoassociated virus vector-driven expression of a neuropeptide Y gene in primary rat brain astroglial cultures after transfection with Sendai virosomes versus Lipofectin.

Science.gov (United States)

de Fiebre, C M; Wu, P; Notabartolo, D; Millard, W J; Meyer, E M

1994-06-01

The ability of Sendai virosomes or Lipofectin to introduce an AAV vector into primary rat brain astroglial cultures was characterized. The pJDT95npy vector was constructed by inserting rat NPY cDNA downstream from the indigenous AAV p5, p19 and p40 promoters in pJDT95. Lipofectin-mediated transfection with pJDT95npy (10 micrograms) resulted in pronounced expression of several NPY mRNA species: p5-driven (3.3 kb), p19-driven (2.7 kb) and p40-driven (0.6, 0.8, 1.1, and 1.8 kb). Exposure to virosomally encapsulated pJDT95npy (50 or 100 ng) resulted in transient expression of some p40-driven mRNA species (0.8 and 1.8 kb). Neither method produced astroglia cells which synthesized mature NPY immunoreactivity. This demonstrates that an AAV-derived vector can drive gene expression in astroglia, that Sendai virosomes can infuse vectors into astroglia, but that the amount of DNA infused in this manner may limit long term expression.

Suppression of cancer growth in mice by adeno-associated virus vector-mediated IFN-beta expression driven by hTERT promoter.

Science.gov (United States)

He, Ling Feng; Wang, Yi Gang; Xiao, Tian; Zhang, Kang Jiang; Li, Gong Chu; Gu, Jin Fa; Chu, Liang; Tang, Wen Hao; Tan, Wen-Song; Liu, Xin Yuan

2009-12-28

Adeno-associated virus (AAV) has rapidly become a promising gene delivery vehicle for its excellent advantages of non-immunogenic, low pathogenicity and long-term gene expression in vivo. However, a major obstacle in development of effective AAV vector is the lack of tissue specificity, which caused low efficiency of AAV transfer to target cells. The application of human telomerase reverse transcriptase (hTERT) promoter is a prior targeting strategy for AAV in cancer gene therapy as hTERT activity is transcriptionally upregulated in most cancer cells. In the present work, we investigated whether AAV-mediated human interferon beta (IFN-beta) gene driven by hTERT promoter could specifically express in tumor cells and suppress tumor cell growth. Our data demonstrated that hTERT promoter-driven IFN-beta expression was the tumor-specific, decreased the cell viability of tumor cells but not normal cells, and induced tumor cell apoptosis via activation of caspase pathway and release of cytochrome c. AAV-mediated IFN-beta expression driven by hTERT promoter significantly suppressed the growth of colorectal cancer and lung cancer xenograft in mice and resulted in tumor cells death in vivo. These data suggested that AAVs in combination with hTERT-mediated IFN-beta expression could exert potential antitumor activity and provide a novel targeting approach to clinical gene therapy of varieties of cancers.

Robust speaker recognition in noisy environments

CERN Document Server

Rao, K Sreenivasa

2014-01-01

This book discusses speaker recognition methods to deal with realistic variable noisy environments. The text covers authentication systems for; robust noisy background environments, functions in real time and incorporated in mobile devices. The book focuses on different approaches to enhance the accuracy of speaker recognition in presence of varying background environments. The authors examine: (a) Feature compensation using multiple background models, (b) Feature mapping using data-driven stochastic models, (c) Design of super vector- based GMM-SVM framework for robust speaker recognition, (d) Total variability modeling (i-vectors) in a discriminative framework and (e) Boosting method to fuse evidences from multiple SVM models.

Experimental implementation of a robust damped-oscillation control algorithm on a full-sized, two-degree-of-freedom, AC induction motor-driven crane

International Nuclear Information System (INIS)

Kress, R.L.; Jansen, J.F.; Noakes, M.W.

1994-01-01

When suspended payloads are moved with an overhead crane, pendulum like oscillations are naturally introduced. This presents a problem any time a crane is used, especially when expensive and/or delicate objects are moved, when moving in a cluttered an or hazardous environment, and when objects are to be placed in tight locations. Damped-oscillation control algorithms have been demonstrated over the past several years for laboratory-scale robotic systems on dc motor-driven overhead cranes. Most overhead cranes presently in use in industry are driven by ac induction motors; consequently, Oak Ridge National Laboratory has implemented damped-oscillation crane control on one of its existing facility ac induction motor-driven overhead cranes. The purpose of this test was to determine feasibility, to work out control and interfacing specifications, and to establish the capability of newly available ac motor control hardware with respect to use in damped-oscillation-controlled systems. Flux vector inverter drives are used to investigate their acceptability for damped-oscillation crane control. The purpose of this paper is to describe the experimental implementation of a control algorithm on a full-sized, two-degree-of-freedom, industrial crane; describe the experimental evaluation of the controller including robustness to payload length changes; explain the results of experiments designed to determine the hardware required for implementation of the control algorithms; and to provide a theoretical description of the controller

Mutual repression enhances the steepness and precision of gene expression boundaries.

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Thomas R Sokolowski

Full Text Available Embryonic development is driven by spatial patterns of gene expression that determine the fate of each cell in the embryo. While gene expression is often highly erratic, embryonic development is usually exceedingly precise. In particular, gene expression boundaries are robust not only against intra-embryonic fluctuations such as noise in gene expression and protein diffusion, but also against embryo-to-embryo variations in the morphogen gradients, which provide positional information to the differentiating cells. How development is robust against intra- and inter-embryonic variations is not understood. A common motif in the gene regulation networks that control embryonic development is mutual repression between pairs of genes. To assess the role of mutual repression in the robust formation of gene expression patterns, we have performed large-scale stochastic simulations of a minimal model of two mutually repressing gap genes in Drosophila, hunchback (hb and knirps (kni. Our model includes not only mutual repression between hb and kni, but also the stochastic and cooperative activation of hb by the anterior morphogen Bicoid (Bcd and of kni by the posterior morphogen Caudal (Cad, as well as the diffusion of Hb and Kni between neighboring nuclei. Our analysis reveals that mutual repression can markedly increase the steepness and precision of the gap gene expression boundaries. In contrast to other mechanisms such as spatial averaging and cooperative gene activation, mutual repression thus allows for gene-expression boundaries that are both steep and precise. Moreover, mutual repression dramatically enhances their robustness against embryo-to-embryo variations in the morphogen levels. Finally, our simulations reveal that diffusion of the gap proteins plays a critical role not only in reducing the width of the gap gene expression boundaries via the mechanism of spatial averaging, but also in repairing patterning errors that could arise because of the

DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks

Science.gov (United States)

Gerstein, Mark

2016-01-01

Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs), cellular growth factors and microRNAs. A subsystem’s gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally–e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org) for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the “state” and “control” in the model refer to its own (internal) and another subsystem’s (external) gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model’s parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation) representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs), seeing the degree to which these can be accounted for by orthologous (internal) versus species-specific (external) TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with

DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks.

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Daifeng Wang

2016-10-01

Full Text Available Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs, cellular growth factors and microRNAs. A subsystem's gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally-e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the "state" and "control" in the model refer to its own (internal and another subsystem's (external gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model's parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs, seeing the degree to which these can be accounted for by orthologous (internal versus species-specific (external TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with

A simple and robust vector-based shRNA expression system used for RNA interference.

Science.gov (United States)

Wang, Xue-jun; Li, Ying; Huang, Hai; Zhang, Xiu-juan; Xie, Pei-wen; Hu, Wei; Li, Dan-dan; Wang, Sheng-qi

2013-01-01

RNA interference (RNAi) mediated by small interfering RNAs (siRNAs) or short hairpin RNAs (shRNAs) has become a powerful genetic tool for conducting functional studies. Previously, vector-based shRNA-expression strategies capable of inducing RNAi in viable cells have been developed, however, these vector systems have some disadvantages, either because they were error-prone or cost prohibitive. In this report we described the development of a simple, robust shRNA expression system utilizing 1 long oligonucleotide or 2 short oligonucleotides for half the cost of conventional shRNA construction methods and with a >95% cloning success rate. The shRNA loop sequence and stem structure were also compared and carefully selected for better RNAi efficiency. Furthermore, an easier strategy was developed based on isocaudomers which permit rapid combination of the most efficient promoter-shRNA cassettes. Finally, using this method, the conservative target sites for hepatitis B virus (HBV) knockdown were systemically screened and HBV antigen expression shown to be successfully suppressed in the presence of connected multiple shRNAs both in vitro and in vivo. This novel design describes an inexpensive and effective way to clone and express single or multiple shRNAs from the same vector with the capacity for potent and effective silencing of target genes.

Are facial expressions of emotion produced by categorical affect programs or dynamically driven by appraisal?

Science.gov (United States)

Scherer, Klaus R; Ellgring, Heiner

2007-02-01

The different assumptions made by discrete and componential emotion theories about the nature of the facial expression of emotion and the underlying mechanisms are reviewed. Explicit and implicit predictions are derived from each model. It is argued that experimental expression-production paradigms rather than recognition studies are required to critically test these differential predictions. Data from a large-scale actor portrayal study are reported to demonstrate the utility of this approach. The frequencies with which 12 professional actors use major facial muscle actions individually and in combination to express 14 major emotions show little evidence for emotion-specific prototypical affect programs. Rather, the results encourage empirical investigation of componential emotion model predictions of dynamic configurations of appraisal-driven adaptive facial actions. (c) 2007 APA, all rights reserved.

Poinsettia protoplasts - a simple, robust and efficient system for transient gene expression studies

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Pitzschke Andrea

2012-05-01

Full Text Available Abstract Background Transient gene expression systems are indispensable tools in molecular biology. Yet, their routine application is limited to few plant species often requiring substantial equipment and facilities. High chloroplast and chlorophyll content may further impede downstream applications of transformed cells from green plant tissue. Results Here, we describe a fast and simple technique for the high-yield isolation and efficient transformation (>70% of mesophyll-derived protoplasts from red leaves of the perennial plant Poinsettia (Euphorbia pulccherrima. In this method no particular growth facilities or expensive equipments are needed. Poinsettia protoplasts display an astonishing robustness and can be employed in a variety of commonly-used downstream applications, such as subcellular localisation (multi-colour fluorescence or promoter activity studies. Due to low abundance of chloroplasts or chromoplasts, problems encountered in other mesophyll-derived protoplast systems (particularly autofluorescence are alleviated. Furthermore, the transgene expression is detectable within 90 minutes of transformation and lasts for several days. Conclusions The simplicity of the isolation and transformation procedure renders Poinsettia protoplasts an attractive system for transient gene expression experiments, including multi-colour fluorescence, subcellular localisation and promoter activity studies. In addition, they offer hitherto unknown possibilities for anthocyan research and industrial applications.

Allen Brain Atlas-Driven Visualizations: a web-based gene expression energy visualization tool.

Science.gov (United States)

Zaldivar, Andrew; Krichmar, Jeffrey L

2014-01-01

The Allen Brain Atlas-Driven Visualizations (ABADV) is a publicly accessible web-based tool created to retrieve and visualize expression energy data from the Allen Brain Atlas (ABA) across multiple genes and brain structures. Though the ABA offers their own search engine and software for researchers to view their growing collection of online public data sets, including extensive gene expression and neuroanatomical data from human and mouse brain, many of their tools limit the amount of genes and brain structures researchers can view at once. To complement their work, ABADV generates multiple pie charts, bar charts and heat maps of expression energy values for any given set of genes and brain structures. Such a suite of free and easy-to-understand visualizations allows for easy comparison of gene expression across multiple brain areas. In addition, each visualization links back to the ABA so researchers may view a summary of the experimental detail. ABADV is currently supported on modern web browsers and is compatible with expression energy data from the Allen Mouse Brain Atlas in situ hybridization data. By creating this web application, researchers can immediately obtain and survey numerous amounts of expression energy data from the ABA, which they can then use to supplement their work or perform meta-analysis. In the future, we hope to enable ABADV across multiple data resources.

Allen Brain Atlas-Driven Visualizations: A Web-Based Gene Expression Energy Visualization Tool

Directory of Open Access Journals (Sweden)

Andrew eZaldivar

2014-05-01

Full Text Available The Allen Brain Atlas-Driven Visualizations (ABADV is a publicly accessible web-based tool created to retrieve and visualize expression energy data from the Allen Brain Atlas (ABA across multiple genes and brain structures. Though the ABA offers their own search engine and software for researchers to view their growing collection of online public data sets, including extensive gene expression and neuroanatomical data from human and mouse brain, many of their tools limit the amount of genes and brain structures researchers can view at once. To complement their work, ABADV generates multiple pie charts, bar charts and heat maps of expression energy values for any given set of genes and brain structures. Such a suite of free and easy-to-understand visualizations allows for easy comparison of gene expression across multiple brain areas. In addition, each visualization links back to the ABA so researchers may view a summary of the experimental detail. ABADV is currently supported on modern web browsers and is compatible with expression energy data from the Allen Mouse Brain Atlas in situ hybridization data. By creating this web application, researchers can immediately obtain and survey numerous amounts of expression energy data from the ABA, which they can then use to supplement their work or perform meta-analysis. In the future, we hope to enable ABADV across multiple data resources.

Robustness from flexibility in the fungal circadian clock

Directory of Open Access Journals (Sweden)

Akman Ozgur E

2010-06-01

Full Text Available Abstract Background Robustness is a central property of living systems, enabling function to be maintained against environmental perturbations. A key challenge is to identify the structures in biological circuits that confer system-level properties such as robustness. Circadian clocks allow organisms to adapt to the predictable changes of the 24-hour day/night cycle by generating endogenous rhythms that can be entrained to the external cycle. In all organisms, the clock circuits typically comprise multiple interlocked feedback loops controlling the rhythmic expression of key genes. Previously, we showed that such architectures increase the flexibility of the clock's rhythmic behaviour. We now test the relationship between flexibility and robustness, using a mathematical model of the circuit controlling conidiation in the fungus Neurospora crassa. Results The circuit modelled in this work consists of a central negative feedback loop, in which the frequency (frq gene inhibits its transcriptional activator white collar-1 (wc-1, interlocked with a positive feedback loop in which FRQ protein upregulates WC-1 production. Importantly, our model reproduces the observed entrainment of this circuit under light/dark cycles with varying photoperiod and cycle duration. Our simulations show that whilst the level of frq mRNA is driven directly by the light input, the falling phase of FRQ protein, a molecular correlate of conidiation, maintains a constant phase that is uncoupled from the times of dawn and dusk. The model predicts the behaviour of mutants that uncouple WC-1 production from FRQ's positive feedback, and shows that the positive loop enhances the buffering of conidiation phase against seasonal photoperiod changes. This property is quantified using Kitano's measure for the overall robustness of a regulated system output. Further analysis demonstrates that this functional robustness is a consequence of the greater evolutionary flexibility conferred on

Perspective: Evolution and detection of genetic robustness

NARCIS (Netherlands)

Visser, de J.A.G.M.; Hermisson, J.; Wagner, G.P.; Ancel Meyers, L.; Bagheri-Chaichian, H.; Blanchard, J.L.; Chao, L.; Cheverud, J.M.; Elena, S.F.; Fontana, W.; Gibson, G.; Hansen, T.F.; Krakauer, D.; Lewontin, R.C.; Ofria, C.; Rice, S.H.; Dassow, von G.; Wagner, A.; Whitlock, M.C.

2003-01-01

Robustness is the invariance of phenotypes in the face of perturbation. The robustness of phenotypes appears at various levels of biological organization, including gene expression, protein folding, metabolic flux, physiological homeostasis, development, and even organismal fitness. The mechanisms

Robust and Adaptive Control With Aerospace Applications

CERN Document Server

Lavretsky, Eugene

2013-01-01

Robust and Adaptive Control shows the reader how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications the focus of the book is primarily on continuous-dynamical systems.  The text is a three-part treatment, beginning with robust and optimal linear control methods and moving on to a self-contained presentation of the design and analysis of model reference adaptive control (MRAC) for nonlinear uncertain dynamical systems. Recent extensions and modifications to MRAC design are included, as are guidelines for combining robust optimal and MRAC controllers. Features of the text include: ·         case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; ·         detailed background material for each chapter to motivate theoretical developments; ·         realistic examples and simulation data illustrating key features ...

Expression robust 3D face recognition via mesh-based histograms of multiple order surface differential quantities

KAUST Repository

Li, Huibin

2011-09-01

This paper presents a mesh-based approach for 3D face recognition using a novel local shape descriptor and a SIFT-like matching process. Both maximum and minimum curvatures estimated in the 3D Gaussian scale space are employed to detect salient points. To comprehensively characterize 3D facial surfaces and their variations, we calculate weighted statistical distributions of multiple order surface differential quantities, including histogram of mesh gradient (HoG), histogram of shape index (HoS) and histogram of gradient of shape index (HoGS) within a local neighborhood of each salient point. The subsequent matching step then robustly associates corresponding points of two facial surfaces, leading to much more matched points between different scans of a same person than the ones of different persons. Experimental results on the Bosphorus dataset highlight the effectiveness of the proposed method and its robustness to facial expression variations. © 2011 IEEE.

The impact of gene expression variation on the robustness and evolvability of a developmental gene regulatory network.

Directory of Open Access Journals (Sweden)

David A Garfield

2013-10-01

Full Text Available Regulatory interactions buffer development against genetic and environmental perturbations, but adaptation requires phenotypes to change. We investigated the relationship between robustness and evolvability within the gene regulatory network underlying development of the larval skeleton in the sea urchin Strongylocentrotus purpuratus. We find extensive variation in gene expression in this network throughout development in a natural population, some of which has a heritable genetic basis. Switch-like regulatory interactions predominate during early development, buffer expression variation, and may promote the accumulation of cryptic genetic variation affecting early stages. Regulatory interactions during later development are typically more sensitive (linear, allowing variation in expression to affect downstream target genes. Variation in skeletal morphology is associated primarily with expression variation of a few, primarily structural, genes at terminal positions within the network. These results indicate that the position and properties of gene interactions within a network can have important evolutionary consequences independent of their immediate regulatory role.

A simple and robust vector-based shRNA expression system used for RNA interference.

Directory of Open Access Journals (Sweden)

Xue-jun Wang

Full Text Available BACKGROUND: RNA interference (RNAi mediated by small interfering RNAs (siRNAs or short hairpin RNAs (shRNAs has become a powerful genetic tool for conducting functional studies. Previously, vector-based shRNA-expression strategies capable of inducing RNAi in viable cells have been developed, however, these vector systems have some disadvantages, either because they were error-prone or cost prohibitive. RESULTS: In this report we described the development of a simple, robust shRNA expression system utilizing 1 long oligonucleotide or 2 short oligonucleotides for half the cost of conventional shRNA construction methods and with a >95% cloning success rate. The shRNA loop sequence and stem structure were also compared and carefully selected for better RNAi efficiency. Furthermore, an easier strategy was developed based on isocaudomers which permit rapid combination of the most efficient promoter-shRNA cassettes. Finally, using this method, the conservative target sites for hepatitis B virus (HBV knockdown were systemically screened and HBV antigen expression shown to be successfully suppressed in the presence of connected multiple shRNAs both in vitro and in vivo. CONCLUSION: This novel design describes an inexpensive and effective way to clone and express single or multiple shRNAs from the same vector with the capacity for potent and effective silencing of target genes.

Robust performance results for discrete-time systems

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Mahmoud Magdi S.

1997-01-01

Full Text Available The problems of robust performance and feedback control synthesis for a class of linear discrete-time systems with time-varying parametric uncertainties are addressed in this paper. The uncertainties are bound and have a linear matrix fractional form. Based on the concept of strongly robust H ∞ -performance criterion, results of robust stability and performance are developed and expressed in easily computable linear matrix inequalities. Synthesis of robust feedback controllers is carried out for several system models of interest.

Emergence of robust growth laws from optimal regulation of ribosome synthesis.

Science.gov (United States)

Scott, Matthew; Klumpp, Stefan; Mateescu, Eduard M; Hwa, Terence

2014-08-22

Bacteria must constantly adapt their growth to changes in nutrient availability; yet despite large-scale changes in protein expression associated with sensing, adaptation, and processing different environmental nutrients, simple growth laws connect the ribosome abundance and the growth rate. Here, we investigate the origin of these growth laws by analyzing the features of ribosomal regulation that coordinate proteome-wide expression changes with cell growth in a variety of nutrient conditions in the model organism Escherichia coli. We identify supply-driven feedforward activation of ribosomal protein synthesis as the key regulatory motif maximizing amino acid flux, and autonomously guiding a cell to achieve optimal growth in different environments. The growth laws emerge naturally from the robust regulatory strategy underlying growth rate control, irrespective of the details of the molecular implementation. The study highlights the interplay between phenomenological modeling and molecular mechanisms in uncovering fundamental operating constraints, with implications for endogenous and synthetic design of microorganisms. © 2014 The Authors. Published under the terms of the CC BY 4.0 license.

Design and implementation of robust controllers for a gait trainer.

Science.gov (United States)

Wang, F C; Yu, C H; Chou, T Y

2009-08-01

This paper applies robust algorithms to control an active gait trainer for children with walking disabilities. Compared with traditional rehabilitation procedures, in which two or three trainers are required to assist the patient, a motor-driven mechanism was constructed to improve the efficiency of the procedures. First, a six-bar mechanism was designed and constructed to mimic the trajectory of children's ankles in walking. Second, system identification techniques were applied to obtain system transfer functions at different operating points by experiments. Third, robust control algorithms were used to design Hinfinity robust controllers for the system. Finally, the designed controllers were implemented to verify experimentally the system performance. From the results, the proposed robust control strategies are shown to be effective.

Optimal control of quantum systems: Origins of inherent robustness to control field fluctuations

International Nuclear Information System (INIS)

Rabitz, Herschel

2002-01-01

The impact of control field fluctuations on the optimal manipulation of quantum dynamics phenomena is investigated. The quantum system is driven by an optimal control field, with the physical focus on the evolving expectation value of an observable operator. A relationship is shown to exist between the system dynamics and the control field fluctuations, wherein the process of seeking optimal performance assures an inherent degree of system robustness to such fluctuations. The presence of significant field fluctuations breaks down the evolution of the observable expectation value into a sequence of partially coherent robust steps. Robustness occurs because the optimization process reduces sensitivity to noise-driven quantum system fluctuations by taking advantage of the observable expectation value being bilinear in the evolution operator and its adjoint. The consequences of this inherent robustness are discussed in the light of recent experiments and numerical simulations on the optimal control of quantum phenomena. The analysis in this paper bodes well for the future success of closed-loop quantum optimal control experiments, even in the presence of reasonable levels of field fluctuations

Robust variable selection method for nonparametric differential equation models with application to nonlinear dynamic gene regulatory network analysis.

Science.gov (United States)

Lu, Tao

2016-01-01

The gene regulation network (GRN) evaluates the interactions between genes and look for models to describe the gene expression behavior. These models have many applications; for instance, by characterizing the gene expression mechanisms that cause certain disorders, it would be possible to target those genes to block the progress of the disease. Many biological processes are driven by nonlinear dynamic GRN. In this article, we propose a nonparametric differential equation (ODE) to model the nonlinear dynamic GRN. Specially, we address following questions simultaneously: (i) extract information from noisy time course gene expression data; (ii) model the nonlinear ODE through a nonparametric smoothing function; (iii) identify the important regulatory gene(s) through a group smoothly clipped absolute deviation (SCAD) approach; (iv) test the robustness of the model against possible shortening of experimental duration. We illustrate the usefulness of the model and associated statistical methods through a simulation and a real application examples.

An integer optimization algorithm for robust identification of non-linear gene regulatory networks

Directory of Open Access Journals (Sweden)

Chemmangattuvalappil Nishanth

2012-09-01

Full Text Available Abstract Background Reverse engineering gene networks and identifying regulatory interactions are integral to understanding cellular decision making processes. Advancement in high throughput experimental techniques has initiated innovative data driven analysis of gene regulatory networks. However, inherent noise associated with biological systems requires numerous experimental replicates for reliable conclusions. Furthermore, evidence of robust algorithms directly exploiting basic biological traits are few. Such algorithms are expected to be efficient in their performance and robust in their prediction. Results We have developed a network identification algorithm to accurately infer both the topology and strength of regulatory interactions from time series gene expression data in the presence of significant experimental noise and non-linear behavior. In this novel formulism, we have addressed data variability in biological systems by integrating network identification with the bootstrap resampling technique, hence predicting robust interactions from limited experimental replicates subjected to noise. Furthermore, we have incorporated non-linearity in gene dynamics using the S-system formulation. The basic network identification formulation exploits the trait of sparsity of biological interactions. Towards that, the identification algorithm is formulated as an integer-programming problem by introducing binary variables for each network component. The objective function is targeted to minimize the network connections subjected to the constraint of maximal agreement between the experimental and predicted gene dynamics. The developed algorithm is validated using both in silico and experimental data-sets. These studies show that the algorithm can accurately predict the topology and connection strength of the in silico networks, as quantified by high precision and recall, and small discrepancy between the actual and predicted kinetic parameters

microRNA as a potential vector for the propagation of robustness in protein expression and oscillatory dynamics within a ceRNA network.

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Claude Gérard

Full Text Available microRNAs (miRNAs are small noncoding RNAs that are important post-transcriptional regulators of gene expression. miRNAs can induce thresholds in protein synthesis. Such thresholds in protein output can be also achieved by oligomerization of transcription factors (TF for the control of gene expression. First, we propose a minimal model for protein expression regulated by miRNA and by oligomerization of TF. We show that miRNA and oligomerization of TF generate a buffer, which increases the robustness of protein output towards molecular noise as well as towards random variation of kinetics parameters. Next, we extend the model by considering that the same miRNA can bind to multiple messenger RNAs, which accounts for the dynamics of a minimal competing endogenous RNAs (ceRNAs network. The model shows that, through common miRNA regulation, TF can control the expression of all proteins formed by the ceRNA network, even if it drives the expression of only one gene in the network. The model further suggests that the threshold in protein synthesis mediated by the oligomerization of TF can be propagated to the other genes, which can increase the robustness of the expression of all genes in such ceRNA network. Furthermore, we show that a miRNA could increase the time delay of a "Goodwin-like" oscillator model, which may favor the occurrence of oscillations of large amplitude. This result predicts important roles of miRNAs in the control of the molecular mechanisms leading to the emergence of biological rhythms. Moreover, a model for the latter oscillator embedded in a ceRNA network indicates that the oscillatory behavior can be propagated, via the shared miRNA, to all proteins formed by such ceRNA network. Thus, by means of computational models, we show that miRNAs could act as vectors allowing the propagation of robustness in protein synthesis as well as oscillatory behaviors within ceRNA networks.

An Evolutionary Approach for Robust Layout Synthesis of MEMS

DEFF Research Database (Denmark)

Fan, Zhun; Wang, Jiachuan; Goodman, Erik

2005-01-01

The paper introduces a robust design method for layout synthesis of MEM resonators subject to inherent geometric uncertainties such as the fabrication error on the sidewall of the structure. The robust design problem is formulated as a multi-objective constrained optimisation problem after certain...... assumptions and treated with multiobjective genetic algorithm (MOGA), a special type of evolutionary computing approaches. Case study based on layout synthesis of a comb-driven MEM resonator shows that the approach proposed in this paper can lead to design results that meet the target performance and are less...

Robust control of a class of chaotic and hyperchaotic driven systems

Indian Academy of Sciences (India)

2016-12-05

Dec 5, 2016 ... are recently devoted to generate chaos and hyper- chaos dynamics by proposing new PWL systems [6,7]. However, very few results are published on chaos synchronization for such complex systems [8–10]. Over the past ten years, robust chaos synchroniza- tion via state feedback control has been widely ...

Once for All: A Novel Robust System for Co-expression of Multiple Chimeric Fluorescent Fusion Proteins in Plants

Directory of Open Access Journals (Sweden)

Guitao Zhong

2017-06-01

Full Text Available Chimeric fluorescent fusion proteins have been employed as a powerful tool to reveal the subcellular localizations and dynamics of proteins in living cells. Co-expression of a fluorescent fusion protein with well-known organelle markers in the same cell is especially useful in revealing its spatial and temporal functions of the protein in question. However, the conventional methods for co-expressing multiple fluorescent tagged proteins in plants have the drawbacks of low expression efficiency, variations in the expression level and time-consuming genetic crossing. Here, we have developed a novel robust system that allows for high-efficient co-expression of multiple chimeric fluorescent fusion proteins in plants in a time-saving fashion. This system takes advantage of employing a single expression vector which consists of multiple semi-independent expressing cassettes for the protein co-expression thereby overcoming the limitations of using multiple independent expressing plasmids. In addition, it is a highly manipulable DNA assembly system, in which modification and recombination of DNA molecules are easily achieved through an optimized one-step assembly reaction. By employing this effective system, we demonstrated that co-expression of two chimeric fluorescent fusion reporter proteins of vacuolar sorting receptor and secretory carrier membrane protein gave rise to their perspective subcellular localizations in plants via both transient expression and stable transformation. Thus, we believed that this technical advance represents a promising approach for multi-color-protein co-expression in plant cells.

Robust H(∞) positional control of 2-DOF robotic arm driven by electro-hydraulic servo system.

Science.gov (United States)

Guo, Qing; Yu, Tian; Jiang, Dan

2015-11-01

In this paper an H∞ positional feedback controller is developed to improve the robust performance under structural and parametric uncertainty disturbance in electro-hydraulic servo system (EHSS). The robust control model is described as the linear state-space equation by upper linear fractional transformation. According to the solution of H∞ sub-optimal control problem, the robust controller is designed and simplified to lower order linear model which is easily realized in EHSS. The simulation and experimental results can validate the robustness of this proposed method. The comparison result with PI control shows that the robust controller is suitable for this EHSS under the critical condition where the desired system bandwidth is higher and the external load of the hydraulic actuator is closed to its limited capability. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Network statistics of genetically-driven gene co-expression modules in mouse crosses

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Marie-Pier eScott-Boyer

2013-12-01

Full Text Available In biology, networks are used in different contexts as ways to represent relationships between entities, such as for instance interactions between genes, proteins or metabolites. Despite progress in the analysis of such networks and their potential to better understand the collective impact of genes on complex traits, one remaining challenge is to establish the biologic validity of gene co-expression networks and to determine what governs their organization. We used WGCNA to construct and analyze seven gene expression datasets from several tissues of mouse recombinant inbred strains (RIS. For six out of the 7 networks, we found that linkage to module QTLs (mQTLs could be established for 29.3% of gene co-expression modules detected in the several mouse RIS. For about 74.6% of such genetically-linked modules, the mQTL was on the same chromosome as the one contributing most genes to the module, with genes originating from that chromosome showing higher connectivity than other genes in the modules. Such modules (that we considered as genetically-driven had network statistic properties (density, centralization and heterogeneity that set them apart from other modules in the network. Altogether, a sizeable portion of gene co-expression modules detected in mouse RIS panels had genetic determinants as their main organizing principle. In addition to providing a biologic interpretation validation for these modules, these genetic determinants imparted on them particular properties that set them apart from other modules in the network, to the point that they can be predicted to a large extent on the basis of their network statistics.

Facile promoter deletion in Escherichia coli in response to leaky expression of very robust and benign proteins from common expression vectors

Directory of Open Access Journals (Sweden)

Kawe Martin

2009-01-01

Full Text Available Abstract Background Overexpression of proteins in Escherichia coli is considered routine today, at least when the protein is soluble and not otherwise toxic for the host. We report here that the massive overproduction of even such "benign" proteins can cause surprisingly efficient promoter deletions in the expression plasmid, leading to the growth of only non-producers, when expression is not well repressed in the newly transformed bacterial cell. Because deletion is so facile, it might impact on high-throughput protein production, e.g. for structural genomics, where not every expression parameter will be monitored. Results We studied the high-level expression of several robust non-toxic proteins using a T5 promoter under lac operator control. Full induction leads to no significant growth retardation. We compared expression from almost identical plasmids with or without the lacI gene together in strains expressing different levels of LacI. Any combination without net overexpression of LacI led to an efficient promoter deletion in the plasmid, although the number of growing colonies and even the plasmid size – all antibiotic-resistant non-producers – was almost normal, and thus the problem not immediately recognizable. However, by assuring sufficient repression during the initial establishment phase of the plasmid, deletion was completely prevented. Conclusion The deletions in the insufficiently repressed system are caused entirely by the burden of high-level translation. Since the E. coli Dps protein, known to protect DNA against stress in the stationary phase, is accumulated in the deletion mutants, the mutation may have taken place during a transient stationary phase. The cause of the deletion is thus distinct from the well known interference of high-level transcription with plasmid replication. The deletion can be entirely prevented by overexpressing LacI, a useful precaution even without any signs of stress caused by the protein.

Further statistical analysis for genome-wide expression evolution in primate brain/liver/fibroblast tissue

Directory of Open Access Journals (Sweden)

Gu Jianying

2004-05-01

Full Text Available Abstract In spite of only a 1-2 per cent genomic DNA sequence difference, humans and chimpanzees differ considerably in behaviour and cognition. Affymetrix microarray technology provides a novel approach to addressing a long-term debate on whether the difference between humans and chimpanzees results from the alteration of gene expressions. Here, we used several statistical methods (distance method, two-sample t-tests, regularised t-tests, ANOVA and bootstrapping to detect the differential expression pattern between humans and great apes. Our analysis shows that the pattern we observed before is robust against various statistical methods; that is, the pronounced expression changes occurred on the human lineage after the split from chimpanzees, and that the dramatic brain expression alterations in humans may be mainly driven by a set of genes with increased expression (up-regulated rather than decreased expression (down-regulated.

New robust statistical procedures for the polytomous logistic regression models.

Science.gov (United States)

Castilla, Elena; Ghosh, Abhik; Martin, Nirian; Pardo, Leandro

2018-05-17

This article derives a new family of estimators, namely the minimum density power divergence estimators, as a robust generalization of the maximum likelihood estimator for the polytomous logistic regression model. Based on these estimators, a family of Wald-type test statistics for linear hypotheses is introduced. Robustness properties of both the proposed estimators and the test statistics are theoretically studied through the classical influence function analysis. Appropriate real life examples are presented to justify the requirement of suitable robust statistical procedures in place of the likelihood based inference for the polytomous logistic regression model. The validity of the theoretical results established in the article are further confirmed empirically through suitable simulation studies. Finally, an approach for the data-driven selection of the robustness tuning parameter is proposed with empirical justifications. © 2018, The International Biometric Society.

Integrated direct/indirect adaptive robust motion trajectory tracking control of pneumatic cylinders

Science.gov (United States)

Meng, Deyuan; Tao, Guoliang; Zhu, Xiaocong

2013-09-01

This paper studies the precision motion trajectory tracking control of a pneumatic cylinder driven by a proportional-directional control valve. An integrated direct/indirect adaptive robust controller is proposed. The controller employs a physical model based indirect-type parameter estimation to obtain reliable estimates of unknown model parameters, and utilises a robust control method with dynamic compensation type fast adaptation to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. Due to the use of projection mapping, the robust control law and the parameter adaption algorithm can be designed separately. Since the system model uncertainties are unmatched, the recursive backstepping technology is adopted to design the robust control law. Extensive comparative experimental results are presented to illustrate the effectiveness of the proposed controller and its performance robustness to parameter variations and sudden disturbances.

Robustness Analysis of a Timber Structure with Ductile Behaviour in Compression

DEFF Research Database (Denmark)

Čizmar, Dean; Sørensen, John Dalsgaard; Kirkegaard, Poul Henning

2011-01-01

This paper presents a probabilistic approach for structural robustness assessment for a timber structure built a few years ago. The robustness analysis is based on a structural reliability based framework for robustness assessment. The complex timber structure with a large number of failure modes...... material ductility of timber is taken into account. The robustness is expressed and evaluated by a robustness index....

Robust heat-inducible gene expression by two endogenous hsp70-derived promoters in transgenic Aedes aegypti

Science.gov (United States)

Carpenetti, Tiffany L. G.; Aryan, Azadeh; Myles, Kevin M.; Adelman, Zach N.

2011-01-01

Aedes aegypti is an important vector of the viruses that cause dengue fever, dengue hemorrhagic fever, and yellow fever. Reverse genetic approaches to the study of gene function in this mosquito have been limited by the lack of a robust inducible promoter to allow precise temporal control over a protein-encoding or hairpin RNA transgene. Likewise, investigations into the molecular and biochemical basis of vector competence would benefit from the ability to activate an anti-pathogen molecule at specific times during infection. We have characterized the ability of genomic sequences derived from two Ae. aegypti hsp70 genes to drive heat-inducible expression of a reporter in both transient and germline transformation contexts. AaHsp70-luciferase transcripts accumulated specifically after heat shock, and displayed a pattern of rapid induction and decay similar to endogenous AaHsp70 genes. Luciferase expression in transgenic Ae. aegypti increased by ∼25-50 fold in whole adults by four hours after heat-shock, with significant activity (∼20 fold) remaining at 24 hr. Heat-induced expression was even more dramatic in midgut tissues, with one strain showing a ∼2500-fold increase in luciferase activity. The AaHsp70 promoters described could be valuable for gene function studies as well as for the precise timing of the expression of anti-pathogen molecules. PMID:22142225

Reliability-Based Robustness Analysis for a Croatian Sports Hall

DEFF Research Database (Denmark)

Čizmar, Dean; Kirkegaard, Poul Henning; Sørensen, John Dalsgaard

2011-01-01

This paper presents a probabilistic approach for structural robustness assessment for a timber structure built a few years ago. The robustness analysis is based on a structural reliability based framework for robustness and a simplified mechanical system modelling of a timber truss system....... A complex timber structure with a large number of failure modes is modelled with only a few dominant failure modes. First, a component based robustness analysis is performed based on the reliability indices of the remaining elements after the removal of selected critical elements. The robustness...... is expressed and evaluated by a robustness index. Next, the robustness is assessed using system reliability indices where the probabilistic failure model is modelled by a series system of parallel systems....

Reactivity Monitoring of Accelerator-Driven Nuclear Reactor Systems

NARCIS (Netherlands)

Uyttenhove, W.

2016-01-01

This thesis provides a methodology and set-up of a reactivity monitoring tool for Accelerator-Driven Systems (ADS). The reactivity monitoring tool should guarantee the operation of an ADS at a safe margin from criticality. Robustness is assured in different aspects of the monitoring tool: the choice

GOexpress: an R/Bioconductor package for the identification and visualisation of robust gene ontology signatures through supervised learning of gene expression data.

Science.gov (United States)

Rue-Albrecht, Kévin; McGettigan, Paul A; Hernández, Belinda; Nalpas, Nicolas C; Magee, David A; Parnell, Andrew C; Gordon, Stephen V; MacHugh, David E

2016-03-11

Identification of gene expression profiles that differentiate experimental groups is critical for discovery and analysis of key molecular pathways and also for selection of robust diagnostic or prognostic biomarkers. While integration of differential expression statistics has been used to refine gene set enrichment analyses, such approaches are typically limited to single gene lists resulting from simple two-group comparisons or time-series analyses. In contrast, functional class scoring and machine learning approaches provide powerful alternative methods to leverage molecular measurements for pathway analyses, and to compare continuous and multi-level categorical factors. We introduce GOexpress, a software package for scoring and summarising the capacity of gene ontology features to simultaneously classify samples from multiple experimental groups. GOexpress integrates normalised gene expression data (e.g., from microarray and RNA-seq experiments) and phenotypic information of individual samples with gene ontology annotations to derive a ranking of genes and gene ontology terms using a supervised learning approach. The default random forest algorithm allows interactions between all experimental factors, and competitive scoring of expressed genes to evaluate their relative importance in classifying predefined groups of samples. GOexpress enables rapid identification and visualisation of ontology-related gene panels that robustly classify groups of samples and supports both categorical (e.g., infection status, treatment) and continuous (e.g., time-series, drug concentrations) experimental factors. The use of standard Bioconductor extension packages and publicly available gene ontology annotations facilitates straightforward integration of GOexpress within existing computational biology pipelines.

Keratin-6 driven ODC expression to hair follicle keratinocytes enhances stemness and tumorigenesis by negatively regulating Notch

Energy Technology Data Exchange (ETDEWEB)

Arumugam, Aadithya; Weng, Zhiping; Chaudhary, Sandeep C.; Afaq, Farrukh [Department of Dermatology, University of Alabama at Birmingham, Birmingham, AL 35294-0019 (United States); Elmets, Craig A. [Department of Dermatology, University of Alabama at Birmingham, Birmingham, AL 35294-0019 (United States); Skin Diseases Research Center, University of Alabama at Birmingham, Birmingham, AL 35294 (United States); Athar, Mohammad, E-mail: mathar@uab.edu [Department of Dermatology, University of Alabama at Birmingham, Birmingham, AL 35294-0019 (United States); Skin Diseases Research Center, University of Alabama at Birmingham, Birmingham, AL 35294 (United States)

2014-08-29

Highlights: • Targeting ODC to hair follicle augments skin carcinogenesis and invasive SCCs. • Hair follicle ODC expands stem cell compartment carrying CD34{sup +}/K15{sup +}/p63{sup +} keratinocytes. • Negatively regulated Notch1 is associated with expansion of stem cell compartment. - Abstract: Over-expression of ornithine decarboxylase (ODC) is known to be involved in the epidermal carcinogenesis. However, the mechanism by which it enhances skin carcinogenesis remains undefined. Recently, role of stem cells localized in various epidermal compartments has been shown in the pathogenesis of skin cancer. To direct ODC expression in distinct epidermal compartments, we have developed keratin 6 (K6)-ODC/SKH-1 and keratin 14 (K14)-ODC/SKH-1 mice and employed them to investigate the role of ODC directed to these epidermal compartments on UVB-induced carcinogenesis. K6-driven ODC over-expression directed to outer root sheath (ORS) of hair follicle was more effective in augmenting tumorigenesis as compared to mice where K14-driven ODC expression was directed to inter-follicular epidermal keratinocytes. Chronically UVB-irradiated K6-ODC/SKH-1 developed 15 ± 2.5 tumors/mouse whereas K14-ODC/SKH-1 developed only 6.8 ± 1.5 tumors/mouse. K6-ODC/SKH-1 showed augmented UVB-induced proliferation and much higher pro-inflammatory responses than K14-ODC/SKH-1 mice. Tumors induced in K6-ODC/SKH-1 were rapidly growing, invasive and ulcerative squamous cell carcinoma (SCC) showing decreased expression of epidermal polarity marker E-cadherin and enhanced mesenchymal marker, fibronectin. Interestingly, the number of CD34/CK15/p63 positive stem-like cells was significantly higher in chronically UVB-irradiated K6-ODC/SKH-1 as compared to K14-ODC/SKH-1 mice. Reduced Notch1 expression was correlated with the expansion of stem cell compartment in these animals. However, other signaling pathways such as DNA damage response or mTOR signaling pathways were not significantly different in

Keratin-6 driven ODC expression to hair follicle keratinocytes enhances stemness and tumorigenesis by negatively regulating Notch

International Nuclear Information System (INIS)

Arumugam, Aadithya; Weng, Zhiping; Chaudhary, Sandeep C.; Afaq, Farrukh; Elmets, Craig A.; Athar, Mohammad

2014-01-01

Highlights: • Targeting ODC to hair follicle augments skin carcinogenesis and invasive SCCs. • Hair follicle ODC expands stem cell compartment carrying CD34 + /K15 + /p63 + keratinocytes. • Negatively regulated Notch1 is associated with expansion of stem cell compartment. - Abstract: Over-expression of ornithine decarboxylase (ODC) is known to be involved in the epidermal carcinogenesis. However, the mechanism by which it enhances skin carcinogenesis remains undefined. Recently, role of stem cells localized in various epidermal compartments has been shown in the pathogenesis of skin cancer. To direct ODC expression in distinct epidermal compartments, we have developed keratin 6 (K6)-ODC/SKH-1 and keratin 14 (K14)-ODC/SKH-1 mice and employed them to investigate the role of ODC directed to these epidermal compartments on UVB-induced carcinogenesis. K6-driven ODC over-expression directed to outer root sheath (ORS) of hair follicle was more effective in augmenting tumorigenesis as compared to mice where K14-driven ODC expression was directed to inter-follicular epidermal keratinocytes. Chronically UVB-irradiated K6-ODC/SKH-1 developed 15 ± 2.5 tumors/mouse whereas K14-ODC/SKH-1 developed only 6.8 ± 1.5 tumors/mouse. K6-ODC/SKH-1 showed augmented UVB-induced proliferation and much higher pro-inflammatory responses than K14-ODC/SKH-1 mice. Tumors induced in K6-ODC/SKH-1 were rapidly growing, invasive and ulcerative squamous cell carcinoma (SCC) showing decreased expression of epidermal polarity marker E-cadherin and enhanced mesenchymal marker, fibronectin. Interestingly, the number of CD34/CK15/p63 positive stem-like cells was significantly higher in chronically UVB-irradiated K6-ODC/SKH-1 as compared to K14-ODC/SKH-1 mice. Reduced Notch1 expression was correlated with the expansion of stem cell compartment in these animals. However, other signaling pathways such as DNA damage response or mTOR signaling pathways were not significantly different in tumors induced

Synthetic triterpenoid induces 15-PGDH expression and suppresses inflammation-driven colon carcinogenesis.

Science.gov (United States)

Choi, Sung Hee; Kim, Byung-Gyu; Robinson, Janet; Fink, Steve; Yan, Min; Sporn, Michael B; Markowitz, Sanford D; Letterio, John J

2014-06-01

Colitis-associated colon cancer (CAC) develops as a result of inflammation-induced epithelial transformation, which occurs in response to inflammatory cytokine-dependent downregulation of 15-hydroxyprostaglandin dehydrogenase (15-PGDH) and subsequent suppression of prostaglandin metabolism. Agents that both enhance 15-PGDH expression and suppress cyclooxygenase-2 (COX-2) production may more effectively prevent CAC. Synthetic triterpenoids are a class of small molecules that suppress COX-2 as well as inflammatory cytokine signaling. Here, we found that administration of the synthetic triterpenoid 2-cyano-3,12-dioxooleana-1,9(11)-dien-C28-methyl ester (CDDO-Me) suppresses CAC in mice. In a spontaneous, inflammation-driven intestinal neoplasia model, deletion of Smad4 specifically in T cells led to progressive production of inflammatory cytokines, including TNF-α, IFN-γ, iNOS, IL-6, IL-1β; as well as activation of STAT1 and STAT3; along with suppression of 15-PGDH expression. Oral administration of CDDO-Me to mice with SMAD4-deficient T cells increased survival and suppressed intestinal epithelial neoplasia by decreasing production of inflammatory mediators and increasing expression of 15-PGDH. Induction of 15-PGDH by CDDO-Me was dose dependent in epithelial cells and was abrogated following treatment with TGF-β signaling inhibitors in vitro. Furthermore, CDDO-Me-dependent 15-PGDH induction was not observed in Smad3-/- mice. Similarly, CDDO-Me suppressed azoxymethane plus dextran sodium sulfate-induced carcinogenesis in wild-type animals, highlighting the potential of small molecules of the triterpenoid family as effective agents for the chemoprevention of CAC in humans.

Performance-Driven Robust Identification and Control of Uncertain Dynamical Systems

Energy Technology Data Exchange (ETDEWEB)

Basar, Tamer

2001-10-29

The grant DEFG02-97ER13939 from the Department of Energy has supported our research program on robust identification and control of uncertain dynamical systems, initially for the three-year period June 15, 1997-June 14, 2000, which was then extended on a no-cost basis for another year until June 14, 2001. This final report provides an overview of our research conducted during this period, along with a complete list of publications supported by the Grant. Within the scope of this project, we have studied fundamental issues that arise in modeling, identification, filtering, control, stabilization, control-based model reduction, decomposition and aggregation, and optimization of uncertain systems. The mathematical framework we have worked in has allowed the system dynamics to be only partially known (with the uncertainties being of both parametric or structural nature), and further the dynamics to be perturbed by unknown dynamic disturbances. Our research over these four years has generated a substantial body of new knowledge, and has led to new major developments in theory, applications, and computational algorithms. These have all been documented in various journal articles and book chapters, and have been presented at leading conferences, as to be described. A brief description of the results we have obtained within the scope of this project can be found in Section 3. To set the stage for the material of that section, we first provide in the next section (Section 2) a brief description of the issues that arise in the control of uncertain systems, and introduce several criteria under which optimality will lead to robustness and stability. Section 4 contains a list of references cited in these two sections. A list of our publications supported by the DOE Grant (covering the period June 15, 1997-June 14, 2001) comprises Section 5 of the report.

Robust non-local effects of ocean heat uptake on radiative feedback and subtropical cloud cover

Science.gov (United States)

Rose, B. E. J.

2016-02-01

Much recent work has pointed to the limitations of the global mean planetary energy budget as a useful diagnostic tool for understanding transient climate response, because the climate sensitivity (or radiative feedback) governing the relationships between ocean heat content, surface temperature and top-of-atmosphere energy imbalance depends sensitively on timescale, spatial pattern and nature of the climate forcing. Progress has been made by treating the slowly-evolving (and spatially complex) pattern of ocean heat uptake as a quasi-equilibrium forcing on the "fast" components of the climate system: the atmospheric radiative-dynamical processes that link air-sea heat exchange to the top-of-atmosphere energy budget. Differences between these feedbacks and those on CO2 radiative forcing can be expressed as an "efficacy" of ocean heat uptake. We use idealized slab ocean GCMs forced by prescribed steady energy sinks limited to specific latitude bands (representing heat exchange with the deep ocean) to quantify how (and why) the efficacy depends on the spatial pattern of ocean heat uptake. By repeating the experiment across several independent GCMs we identify robust and non-robust aspects of the response. We find that the efficacy of sub-polar heat uptake is 3 to 4 times larger than the efficacy of tropical heat uptake. Radiative kernel analysis allows an accurate partition into feedbacks due to temperature, water vapor and clouds. We find large and robust differences in clear-sky lapse rate feedbacks, associated with robust differences in large-scale atmospheric circulation and stratification driven by ocean heat uptake. A more novel and surprising result is the robustness across several independent GCMs of the differences in subtropical low cloud feedback (positive under high-latitude uptake, strongly negative under tropical uptake). We trace these robust differences to thermodynamic constraints associated with lower-tropospheric stability and boundary layer

Chromatin regulators, phenotypic robustness and autism risk

Directory of Open Access Journals (Sweden)

Reut eSuliman

2014-04-01

Full Text Available Though extensively characterized clinically, the causes of autism spectrum disorder (ASD remain a mystery. ASD is known to have a strong genetic basis, but it is genetically very heterogeneous. Recent studies have estimated that de novo disruptive mutations in hundreds of genes may contribute to ASD. However, it is unclear how it is possible for mutations in so many different genes to contribute to ASD. Recent findings suggest that many of the mutations disrupt genes involved in transcription regulation that are expressed prenatally in the developing brain. De novo disruptive mutations are also more frequent in girls with ASD, despite the fact that ASD is more prevalent in boys. In this paper, we hypothesize that loss of robustness may contribute to ASD. Loss of phenotypic robustness may be caused by mutations that disrupt capacitors that operate in the developing brain. This may lead to the release of cryptic genetic variation that contributes to ASD. Reduced robustness is consistent with the observed variability in expressivity and incomplete penetrance. It is also consistent with the hypothesis that the development of the female brain is more robust, and it may explain the higher rate and severity of disruptive de novo mutations in girls with ASD.

Adjustment of Adaptive Gain with Bounded Linear Stability Analysis to Improve Time-Delay Margin for Metrics-Driven Adaptive Control

Science.gov (United States)

Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje Srinvas

2009-01-01

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a linear damaged twin-engine generic transport model of aircraft. The analysis shows that the system with the adjusted adaptive gain becomes more robust to unmodeled dynamics or time delay.

Feasibility and robustness of dose painting by numbers in proton therapy with contour-driven plan optimization

International Nuclear Information System (INIS)

Barragán, A. M.; Differding, S.; Lee, J. A.; Sterpin, E.; Janssens, G.

2015-01-01

Purpose: To prove the ability of protons to reproduce a dose gradient that matches a dose painting by numbers (DPBN) prescription in the presence of setup and range errors, by using contours and structure-based optimization in a commercial treatment planning system. Methods: For two patients with head and neck cancer, voxel-by-voxel prescription to the target volume (GTV PET ) was calculated from 18 FDG-PET images and approximated with several discrete prescription subcontours. Treatments were planned with proton pencil beam scanning. In order to determine the optimal plan parameters to approach the DPBN prescription, the effects of the scanning pattern, number of fields, number of subcontours, and use of range shifter were separately tested on each patient. Different constant scanning grids (i.e., spot spacing = Δx = Δy = 3.5, 4, and 5 mm) and uniform energy layer separation [4 and 5 mm WED (water equivalent distance)] were analyzed versus a dynamic and automatic selection of the spots grid. The number of subcontours was increased from 3 to 11 while the number of beams was set to 3, 5, or 7. Conventional PTV-based and robust clinical target volumes (CTV)-based optimization strategies were considered and their robustness against range and setup errors assessed. Because of the nonuniform prescription, ensuring robustness for coverage of GTV PET inevitably leads to overdosing, which was compared for both optimization schemes. Results: The optimal number of subcontours ranged from 5 to 7 for both patients. All considered scanning grids achieved accurate dose painting (1% average difference between the prescribed and planned doses). PTV-based plans led to nonrobust target coverage while robust-optimized plans improved it considerably (differences between worst-case CTV dose and the clinical constraint was up to 3 Gy for PTV-based plans and did not exceed 1 Gy for robust CTV-based plans). Also, only 15% of the points in the GTV PET (worst case) were above 5% of DPBN

Parametric uncertainty modeling for robust control

DEFF Research Database (Denmark)

Rasmussen, K.H.; Jørgensen, Sten Bay

1999-01-01

The dynamic behaviour of a non-linear process can often be approximated with a time-varying linear model. In the presented methodology the dynamics is modeled non-conservatively as parametric uncertainty in linear lime invariant models. The obtained uncertainty description makes it possible...... to perform robustness analysis on a control system using the structured singular value. The idea behind the proposed method is to fit a rational function to the parameter variation. The parameter variation can then be expressed as a linear fractional transformation (LFT), It is discussed how the proposed...... point changes. It is shown that a diagonal PI control structure provides robust performance towards variations in feed flow rate or feed concentrations. However including both liquid and vapor flow delays robust performance specifications cannot be satisfied with this simple diagonal control structure...

Robust regularized singular value decomposition with application to mortality data

KAUST Repository

Zhang, Lingsong

2013-09-01

We develop a robust regularized singular value decomposition (RobRSVD) method for analyzing two-way functional data. The research is motivated by the application of modeling human mortality as a smooth two-way function of age group and year. The RobRSVD is formulated as a penalized loss minimization problem where a robust loss function is used to measure the reconstruction error of a low-rank matrix approximation of the data, and an appropriately defined two-way roughness penalty function is used to ensure smoothness along each of the two functional domains. By viewing the minimization problem as two conditional regularized robust regressions, we develop a fast iterative reweighted least squares algorithm to implement the method. Our implementation naturally incorporates missing values. Furthermore, our formulation allows rigorous derivation of leaveone- row/column-out cross-validation and generalized cross-validation criteria, which enable computationally efficient data-driven penalty parameter selection. The advantages of the new robust method over nonrobust ones are shown via extensive simulation studies and the mortality rate application. © Institute of Mathematical Statistics, 2013.

Ensemble Modeling for Robustness Analysis in engineering non-native metabolic pathways.

Science.gov (United States)

Lee, Yun; Lafontaine Rivera, Jimmy G; Liao, James C

2014-09-01

Metabolic pathways in cells must be sufficiently robust to tolerate fluctuations in expression levels and changes in environmental conditions. Perturbations in expression levels may lead to system failure due to the disappearance of a stable steady state. Increasing evidence has suggested that biological networks have evolved such that they are intrinsically robust in their network structure. In this article, we presented Ensemble Modeling for Robustness Analysis (EMRA), which combines a continuation method with the Ensemble Modeling approach, for investigating the robustness issue of non-native pathways. EMRA investigates a large ensemble of reference models with different parameters, and determines the effects of parameter drifting until a bifurcation point, beyond which a stable steady state disappears and system failure occurs. A pathway is considered to have high bifurcational robustness if the probability of system failure is low in the ensemble. To demonstrate the utility of EMRA, we investigate the bifurcational robustness of two synthetic central metabolic pathways that achieve carbon conservation: non-oxidative glycolysis and reverse glyoxylate cycle. With EMRA, we determined the probability of system failure of each design and demonstrated that alternative designs of these pathways indeed display varying degrees of bifurcational robustness. Furthermore, we demonstrated that target selection for flux improvement should consider the trade-offs between robustness and performance. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Multigenic lentiviral vectors for combined and tissue-specific expression of miRNA- and protein-based antiangiogenic factors

Directory of Open Access Journals (Sweden)

Anne Louise Askou

Full Text Available Lentivirus-based gene delivery vectors carrying multiple gene cassettes are powerful tools in gene transfer studies and gene therapy, allowing coexpression of multiple therapeutic factors and, if desired, fluorescent reporters. Current strategies to express transgenes and microRNA (miRNA clusters from a single vector have certain limitations that affect transgene expression levels and/or vector titers. In this study, we describe a novel vector design that facilitates combined expression of therapeutic RNA- and protein-based antiangiogenic factors as well as a fluorescent reporter from back-to-back RNApolII-driven expression cassettes. This configuration allows effective production of intron-embedded miRNAs that are released upon transduction of target cells. Exploiting such multigenic lentiviral vectors, we demonstrate robust miRNA-directed downregulation of vascular endothelial growth factor (VEGF expression, leading to reduced angiogenesis, and parallel impairment of angiogenic pathways by codelivering the gene encoding pigment epithelium-derived factor (PEDF. Notably, subretinal injections of lentiviral vectors reveal efficient retinal pigment epithelium-specific gene expression driven by the VMD2 promoter, verifying that multigenic lentiviral vectors can be produced with high titers sufficient for in vivo applications. Altogether, our results suggest the potential applicability of combined miRNA- and protein-encoding lentiviral vectors in antiangiogenic gene therapy, including new combination therapies for amelioration of age-related macular degeneration.

Topology and robustness in the Drosophila segment polarity network.

Directory of Open Access Journals (Sweden)

Nicholas T Ingolia

2004-06-01

Full Text Available A complex hierarchy of genetic interactions converts a single-celled Drosophila melanogaster egg into a multicellular embryo with 14 segments. Previously, von Dassow et al. reported that a mathematical model of the genetic interactions that defined the polarity of segments (the segment polarity network was robust (von Dassow et al. 2000. As quantitative information about the system was unavailable, parameters were sampled randomly. A surprisingly large fraction of these parameter sets allowed the model to maintain and elaborate on the segment polarity pattern. This robustness is due to the positive feedback of gene products on their own expression, which induces individual cells in a model segment to adopt different stable expression states (bistability corresponding to different cell types in the segment polarity pattern. A positive feedback loop will only yield multiple stable states when the parameters that describe it satisfy a particular inequality. By testing which random parameter sets satisfy these inequalities, I show that bistability is necessary to form the segment polarity pattern and serves as a strong predictor of which parameter sets will succeed in forming the pattern. Although the original model was robust to parameter variation, it could not reproduce the observed effects of cell division on the pattern of gene expression. I present a modified version that incorporates recent experimental evidence and does successfully mimic the consequences of cell division. The behavior of this modified model can also be understood in terms of bistability in positive feedback of gene expression. I discuss how this topological property of networks provides robust pattern formation and how large changes in parameters can change the specific pattern produced by a network.

An empirical likelihood ratio test robust to individual heterogeneity for differential expression analysis of RNA-seq.

Science.gov (United States)

Xu, Maoqi; Chen, Liang

2018-01-01

The individual sample heterogeneity is one of the biggest obstacles in biomarker identification for complex diseases such as cancers. Current statistical models to identify differentially expressed genes between disease and control groups often overlook the substantial human sample heterogeneity. Meanwhile, traditional nonparametric tests lose detailed data information and sacrifice the analysis power, although they are distribution free and robust to heterogeneity. Here, we propose an empirical likelihood ratio test with a mean-variance relationship constraint (ELTSeq) for the differential expression analysis of RNA sequencing (RNA-seq). As a distribution-free nonparametric model, ELTSeq handles individual heterogeneity by estimating an empirical probability for each observation without making any assumption about read-count distribution. It also incorporates a constraint for the read-count overdispersion, which is widely observed in RNA-seq data. ELTSeq demonstrates a significant improvement over existing methods such as edgeR, DESeq, t-tests, Wilcoxon tests and the classic empirical likelihood-ratio test when handling heterogeneous groups. It will significantly advance the transcriptomics studies of cancers and other complex disease. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Novel results for global robust stability of delayed neural networks

International Nuclear Information System (INIS)

Yucel, Eylem; Arik, Sabri

2009-01-01

This paper investigates the global robust convergence properties of continuous-time neural networks with discrete time delays. By employing suitable Lyapunov functionals, some sufficient conditions for the existence, uniqueness and global robust asymptotic stability of the equilibrium point are derived. The conditions can be easily verified as they can be expressed in terms of the network parameters only. Some numerical examples are also given to compare our results with previous robust stability results derived in the literature.

Robust sampled-data control of hydraulic flight control actuators

OpenAIRE

Kliffken, Markus Gustav

1997-01-01

In todays flight-by-wire systems the primary flight control surfaces of modern commercial and transport aircraft are driven by electro hydraulic linear actuators. Changing flight conditions as well as nonlinear actuator dynamics may be interpreted as parameter uncertainties of the linear actuator model. This demands a robust design for the controller. Here the parameter space design is used for the direct sampled-data controller synthesis. Therefore, a static output controller is choosen, the...

NF-κB Signaling Regulates Epstein–Barr Virus BamHI-Q-Driven EBNA1 Expression

Directory of Open Access Journals (Sweden)

Rob J. A. Verhoeven

2018-04-01

Full Text Available Epstein–Barr virus (EBV nuclear antigen 1 (EBNA1 is one of the few viral proteins expressed by EBV in nasopharyngeal carcinoma (NPC, most likely because of its essential role in maintaining the viral genome in EBV-infected cells. In NPC, EBNA1 expression is driven by the BamHI-Q promoter (Qp, which is regulated by both cellular and viral factors. We previously determined that the expression of another group of EBV transcripts, BamHI-A rightward transcripts (BARTs, is associated with constitutively activated nuclear factor-κB (NF-κB signaling in NPC cells. Here, we show that, like the EBV BART promoter, the EBV Qp also responds to NF-κB signaling. NF-κB p65, but not p50, can activate Qp in vitro, and NF-κB signaling regulates Qp-EBNA1 expression in NPC cells, as well as in other EBV-infected epithelial cells. The introduction of mutations in the putative NF-κB site reduced Qp activation by the NF-κB p65 subunit. Binding of p65 to Qp was shown by chromatin immunoprecipitation (ChIP analysis, while electrophoretic mobility shift assays (EMSAs demonstrated that p50 can also bind to Qp. Inhibition of NF-κB signaling by the IκB kinase inhibitor PS-1145 resulted in the downregulation of Qp-EBNA1 expression in C666-1 NPC cells. Since EBNA1 has been reported to block p65 activation by inhibiting IKKα/β through an unknown mechanism, we suggest that, in NPC, NF-κB signaling and EBNA1 may form a regulatory loop which supports EBV latent gene expression, while also limiting NF-κB activity. These findings emphasize the role of NF-κB signaling in the regulation of EBV latency in EBV-associated tumors.

Risk, Robustness and Water Resources Planning Under Uncertainty

Science.gov (United States)

Borgomeo, Edoardo; Mortazavi-Naeini, Mohammad; Hall, Jim W.; Guillod, Benoit P.

2018-03-01

Risk-based water resources planning is based on the premise that water managers should invest up to the point where the marginal benefit of risk reduction equals the marginal cost of achieving that benefit. However, this cost-benefit approach may not guarantee robustness under uncertain future conditions, for instance under climatic changes. In this paper, we expand risk-based decision analysis to explore possible ways of enhancing robustness in engineered water resources systems under different risk attitudes. Risk is measured as the expected annual cost of water use restrictions, while robustness is interpreted in the decision-theoretic sense as the ability of a water resource system to maintain performance—expressed as a tolerable risk of water use restrictions—under a wide range of possible future conditions. Linking risk attitudes with robustness allows stakeholders to explicitly trade-off incremental increases in robustness with investment costs for a given level of risk. We illustrate the framework through a case study of London's water supply system using state-of-the -art regional climate simulations to inform the estimation of risk and robustness.

Adaptive integral robust control and application to electromechanical servo systems.

Science.gov (United States)

Deng, Wenxiang; Yao, Jianyong

2017-03-01

This paper proposes a continuous adaptive integral robust control with robust integral of the sign of the error (RISE) feedback for a class of uncertain nonlinear systems, in which the RISE feedback gain is adapted online to ensure the robustness against disturbances without the prior bound knowledge of the additive disturbances. In addition, an adaptive compensation integrated with the proposed adaptive RISE feedback term is also constructed to further reduce design conservatism when the system also exists parametric uncertainties. Lyapunov analysis reveals the proposed controllers could guarantee the tracking errors are asymptotically converging to zero with continuous control efforts. To illustrate the high performance nature of the developed controllers, numerical simulations are provided. At the end, an application case of an actual electromechanical servo system driven by motor is also studied, with some specific design consideration, and comparative experimental results are obtained to verify the effectiveness of the proposed controllers. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Large Field Visualization with Demand-Driven Calculation

Science.gov (United States)

Moran, Patrick J.; Henze, Chris

1999-01-01

We present a system designed for the interactive definition and visualization of fields derived from large data sets: the Demand-Driven Visualizer (DDV). The system allows the user to write arbitrary expressions to define new fields, and then apply a variety of visualization techniques to the result. Expressions can include differential operators and numerous other built-in functions, ail of which are evaluated at specific field locations completely on demand. The payoff of following a demand-driven design philosophy throughout becomes particularly evident when working with large time-series data, where the costs of eager evaluation alternatives can be prohibitive.

Prolonged Cre expression driven by the α-myosin heavy chain promoter can be cardiotoxic.

Science.gov (United States)

Pugach, Emily K; Richmond, Phillip A; Azofeifa, Joseph G; Dowell, Robin D; Leinwand, Leslie A

2015-09-01

Studying the importance of genetic factors in a desired cell type or tissue necessitates the use of precise genetic tools. With the introduction of bacteriophage Cre recombinase/loxP mediated DNA editing and promoter-specific Cre expression, it is feasible to generate conditional knockout mice in which particular genes are disrupted in a cell type-specific manner in vivo. In cardiac myocytes, this is often achieved through α-myosin heavy chain promoter (αMyHC)-driven Cre expression in conjunction with a loxP-site flanked gene of interest. Recent studies in other cell types demonstrate toxicity of Cre expression through induction of DNA damage. However, it is unclear to what extent the traditionally used αMyHC-Cre line [1] may exhibit cardiotoxicity. Further, the genotype of αMyHC-Cre(+/-) is not often included as a control group in cardiac myocyte-specific knockout studies. Here we present evidence that these αMyHC-Cre(+/-) mice show molecular signs of cardiac toxicity by 3months of age and exhibit decreased cardiac function by 6months of age compared to wild-type littermates. Hearts from αMyHC-Cre(+/-) mice also display evidence of fibrosis, inflammation, and DNA damage. Interestingly, some of the early functional changes observed in αMyHC-Cre(+/-) mice are sexually dimorphic. Given the high level of Cre recombinase expression resulting from expression from the αMyHC promoter, we asked if degenerate loxP-like sites naturally exist in the mouse genome and if so, whether they are affected by Cre in the absence of canonical loxP-sites. Using a novel bioinformatics search tool, we identified 619 loxP-like sites with 4 or less mismatches to the canonical loxP-site. 227 sites overlapped with annotated genes and 55 of these genes were expressed in cardiac muscle. Expression of ~26% of the 27 genes tested was disrupted in αMyHC-Cre(+/-) mice indicating potential targeting by Cre. Taken together, these results highlight both the importance of using αMyHC-Cre mice

Event-triggered decentralized robust model predictive control for constrained large-scale interconnected systems

Directory of Open Access Journals (Sweden)

Ling Lu

2016-12-01

Full Text Available This paper considers the problem of event-triggered decentralized model predictive control (MPC for constrained large-scale linear systems subject to additive bounded disturbances. The constraint tightening method is utilized to formulate the MPC optimization problem. The local predictive control law for each subsystem is determined aperiodically by relevant triggering rule which allows a considerable reduction of the computational load. And then, the robust feasibility and closed-loop stability are proved and it is shown that every subsystem state will be driven into a robust invariant set. Finally, the effectiveness of the proposed approach is illustrated via numerical simulations.

Emergence of robustness in networks of networks

Science.gov (United States)

Roth, Kevin; Morone, Flaviano; Min, Byungjoon; Makse, Hernán A.

2017-06-01

A model of interdependent networks of networks (NONs) was introduced recently [Proc. Natl. Acad. Sci. (USA) 114, 3849 (2017), 10.1073/pnas.1620808114] in the context of brain activation to identify the neural collective influencers in the brain NON. Here we investigate the emergence of robustness in such a model, and we develop an approach to derive an exact expression for the random percolation transition in Erdös-Rényi NONs of this kind. Analytical calculations are in agreement with numerical simulations, and highlight the robustness of the NON against random node failures, which thus presents a new robust universality class of NONs. The key aspect of this robust NON model is that a node can be activated even if it does not belong to the giant mutually connected component, thus allowing the NON to be built from below the percolation threshold, which is not possible in previous models of interdependent networks. Interestingly, the phase diagram of the model unveils particular patterns of interconnectivity for which the NON is most vulnerable, thereby marking the boundary above which the robustness of the system improves with increasing dependency connections.

Robust Linear Models for Cis-eQTL Analysis.

Science.gov (United States)

Rantalainen, Mattias; Lindgren, Cecilia M; Holmes, Christopher C

2015-01-01

Expression Quantitative Trait Loci (eQTL) analysis enables characterisation of functional genetic variation influencing expression levels of individual genes. In outbread populations, including humans, eQTLs are commonly analysed using the conventional linear model, adjusting for relevant covariates, assuming an allelic dosage model and a Gaussian error term. However, gene expression data generally have noise that induces heavy-tailed errors relative to the Gaussian distribution and often include atypical observations, or outliers. Such departures from modelling assumptions can lead to an increased rate of type II errors (false negatives), and to some extent also type I errors (false positives). Careful model checking can reduce the risk of type-I errors but often not type II errors, since it is generally too time-consuming to carefully check all models with a non-significant effect in large-scale and genome-wide studies. Here we propose the application of a robust linear model for eQTL analysis to reduce adverse effects of deviations from the assumption of Gaussian residuals. We present results from a simulation study as well as results from the analysis of real eQTL data sets. Our findings suggest that in many situations robust models have the potential to provide more reliable eQTL results compared to conventional linear models, particularly in respect to reducing type II errors due to non-Gaussian noise. Post-genomic data, such as that generated in genome-wide eQTL studies, are often noisy and frequently contain atypical observations. Robust statistical models have the potential to provide more reliable results and increased statistical power under non-Gaussian conditions. The results presented here suggest that robust models should be considered routinely alongside other commonly used methodologies for eQTL analysis.

Intrinsic and Extrinsic Regulation of PD-L2 Expression in Oncogene-Driven Non-Small Cell Lung Cancer.

Science.gov (United States)

Shibahara, Daisuke; Tanaka, Kentaro; Iwama, Eiji; Kubo, Naoki; Ota, Keiichi; Azuma, Koichi; Harada, Taishi; Fujita, Jiro; Nakanishi, Yoichi; Okamoto, Isamu

2018-03-27

The interaction of programmed cell death ligand 2 (PD-L2) with programmed cell death 1 is implicated in tumor immune escape. The regulation of PD-L2 expression in tumor cells has remained unclear, however. We here examined intrinsic and extrinsic regulation of PD-L2 expression in NSCLC. PD-L2 expression was evaluated by reverse transcription and real-time polymerase chain reaction analysis and by flow cytometry. BEAS-2B cells stably expressing an activated mutant form of EGFR or the echinoderm microtubule associated protein like 4 (EML4)-ALK receptor tyrosine kinase fusion oncoprotein manifested increased expression of PD-L2 at both the mRNA and protein levels. Furthermore, treatment of NSCLC cell lines that harbor such driver oncogenes with corresponding EGFR or ALK tyrosine kinase inhibitors or depletion of EGFR or ALK by small interfering RNA transfection suppressed expression of PD-L2, demonstrating that activating EGFR mutations or echinoderm microtubule associated protein like 4 gene (EML4)-ALK receptor tyrosine kinase gene (ALK) fusion intrinsically induce PD-L2 expression. We also found that interferon gamma (IFN-γ) extrinsically induced expression of PD-L2 through signal transducer and activator of transcription 1 signaling in NSCLC cells. Oncogene-driven expression of PD-L2 in NSCLC cells was inhibited by knockdown of the transcription factors signal transducer and activator of transcription 3 (STAT3) or c-FOS. IFN-γ also activated STAT3 and c-FOS, suggesting that these proteins may also contribute to the extrinsic induction of PD-L2 expression. Expression of PD-L2 is induced intrinsically by activating EGFR mutations or EML4-ALK fusion and extrinsically by IFN-γ, with STAT3 and c-FOS possibly contributing to both intrinsic and extrinsic pathways. Our results thus provide insight into the complexity of tumor immune escape in NSCLC. Copyright © 2018 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Anomalous edge states and the bulk-edge correspondence for periodically-driven two dimensional systems

DEFF Research Database (Denmark)

Rudner, Mark Spencer; Lindner, Netanel; Berg, Erez

2013-01-01

revealed phenomena that cannot be characterized by analogy to the topological classification framework for static systems. In particular, in driven systems in two dimensions (2D), robust chiral edge states can appear even though the Chern numbers of all the bulk Floquet bands are zero. Here, we elucidate...... the crucial distinctions between static and driven 2D systems, and construct a new topological invariant that yields the correct edge-state structure in the driven case. We provide formulations in both the time and frequency domains, which afford additional insight into the origins of the “anomalous” spectra...... that arise in driven systems. Possibilities for realizing these phenomena in solid-state and cold-atomic systems are discussed....

Robustness Metrics: Consolidating the multiple approaches to quantify Robustness

DEFF Research Database (Denmark)

Göhler, Simon Moritz; Eifler, Tobias; Howard, Thomas J.

2016-01-01

robustness metrics; 3) Functional expectancy and dispersion robustness metrics; and 4) Probability of conformance robustness metrics. The goal was to give a comprehensive overview of robustness metrics and guidance to scholars and practitioners to understand the different types of robustness metrics...

A sparse regulatory network of copy-number driven gene expression reveals putative breast cancer oncogenes.

Science.gov (United States)

Yuan, Yinyin; Curtis, Christina; Caldas, Carlos; Markowetz, Florian

2012-01-01

Copy number aberrations are recognized to be important in cancer as they may localize to regions harboring oncogenes or tumor suppressors. Such genomic alterations mediate phenotypic changes through their impact on expression. Both cis- and transacting alterations are important since they may help to elucidate putative cancer genes. However, amidst numerous passenger genes, trans-effects are less well studied due to the computational difficulty in detecting weak and sparse signals in the data, and yet may influence multiple genes on a global scale. We propose an integrative approach to learn a sparse interaction network of DNA copy-number regions with their downstream transcriptional targets in breast cancer. With respect to goodness of fit on both simulated and real data, the performance of sparse network inference is no worse than other state-of-the-art models but with the advantage of simultaneous feature selection and efficiency. The DNA-RNA interaction network helps to distinguish copy-number driven expression alterations from those that are copy-number independent. Further, our approach yields a quantitative copy-number dependency score, which distinguishes cis- versus trans-effects. When applied to a breast cancer data set, numerous expression profiles were impacted by cis-acting copy-number alterations, including several known oncogenes such as GRB7, ERBB2, and LSM1. Several trans-acting alterations were also identified, impacting genes such as ADAM2 and BAGE, which warrant further investigation. An R package named lol is available from www.markowetzlab.org/software/lol.html.

Essential gene disruptions reveal complex relationships between phenotypic robustness, pleiotropy, and fitness

Science.gov (United States)

Bauer, Christopher R; Li, Shuang; Siegal, Mark L

2015-01-01

The concept of robustness in biology has gained much attention recently, but a mechanistic understanding of how genetic networks regulate phenotypic variation has remained elusive. One approach to understand the genetic architecture of variability has been to analyze dispensable gene deletions in model organisms; however, the most important genes cannot be deleted. Here, we have utilized two systems in yeast whereby essential genes have been altered to reduce expression. Using high-throughput microscopy and image analysis, we have characterized a large number of morphological phenotypes, and their associated variation, for the majority of essential genes in yeast. Our results indicate that phenotypic robustness is more highly dependent upon the expression of essential genes than on the presence of dispensable genes. Morphological robustness appears to be a general property of a genotype that is closely related to pleiotropy. While the fitness profile across a range of expression levels is idiosyncratic to each gene, the global pattern indicates that there is a window in which phenotypic variation can be released before fitness effects are observable. PMID:25609648

Modeling stochasticity and robustness in gene regulatory networks.

Science.gov (United States)

Garg, Abhishek; Mohanram, Kartik; Di Cara, Alessandro; De Micheli, Giovanni; Xenarios, Ioannis

2009-06-15

Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.

Newton-Gauss Algorithm of Robust Weighted Total Least Squares Model

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WANG Bin

2015-06-01

Full Text Available Based on the Newton-Gauss iterative algorithm of weighted total least squares (WTLS, a robust WTLS (RWTLS model is presented. The model utilizes the standardized residuals to construct the weight factor function and the square root of the variance component estimator with robustness is obtained by introducing the median method. Therefore, the robustness in both the observation and structure spaces can be simultaneously achieved. To obtain standardized residuals, the linearly approximate cofactor propagation law is employed to derive the expression of the cofactor matrix of WTLS residuals. The iterative calculation steps for RWTLS are also described. The experiment indicates that the model proposed in this paper exhibits satisfactory robustness for gross errors handling problem of WTLS, the obtained parameters have no significant difference with the results of WTLS without gross errors. Therefore, it is superior to the robust weighted total least squares model directly constructed with residuals.

Non-circadian expression masking clock-driven weak transcription rhythms in U2OS cells.

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Julia Hoffmann

Full Text Available U2OS cells harbor a circadian clock but express only a few rhythmic genes in constant conditions. We identified 3040 binding sites of the circadian regulators BMAL1, CLOCK and CRY1 in the U2OS genome. Most binding sites even in promoters do not correlate with detectable rhythmic transcript levels. Luciferase fusions reveal that the circadian clock supports robust but low amplitude transcription rhythms of representative promoters. However, rhythmic transcription of these potentially clock-controlled genes is masked by non-circadian transcription that overwrites the weaker contribution of the clock in constant conditions. Our data suggest that U2OS cells harbor an intrinsically rather weak circadian oscillator. The oscillator has the potential to regulate a large number of genes. The contribution of circadian versus non-circadian transcription is dependent on the metabolic state of the cell and may determine the apparent complexity of the circadian transcriptome.

Noise-driven phenomena in hysteretic systems

CERN Document Server

Dimian, Mihai

2014-01-01

Noise-Driven Phenomena in Hysteretic Systems provides a general approach to nonlinear systems with hysteresis driven by noisy inputs, which leads to a unitary framework for the analysis of various stochastic aspects of hysteresis. This book includes integral, differential and algebraic models that are used to describe scalar and vector hysteretic nonlinearities originating from various areas of science and engineering. The universality of the authors approach is also reflected by the diversity of the models used to portray the input noise, from the classical Gaussian white noise to its impulsive forms, often encountered in economics and biological systems, and pink noise, ubiquitous in multi-stable electronic systems. The book is accompanied by HysterSoft© - a robust simulation environment designed to perform complex hysteresis modeling – that can be used by the reader to reproduce many of the results presented in the book as well as to research both disruptive and constructive effects of noise in hysteret...

Widespread AAV1- and AAV2-mediated transgene expression in the nonhuman primate brain: implications for Huntington's disease

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Piotr Hadaczek

2016-01-01

Full Text Available Huntington's disease (HD is caused by a toxic gain-of-function associated with the expression of the mutant huntingtin (htt protein. Therefore, the use of RNA interference to inhibit Htt expression could represent a disease-modifying therapy. The potential of two recombinant adeno-associated viral vectors (AAV, AAV1 and AAV2, to transduce the cortico-striatal tissues that are predominantly affected in HD was explored. Green fluorescent protein was used as a reporter in each vector to show that both serotypes were broadly distributed in medium spiny neurons in the striatum and cortico-striatal neurons after infusion into the putamen and caudate nucleus of nonhuman primates (NHP, with AAV1-directed expression being slightly more robust than AAV2-driven expression. This study suggests that both serotypes are capable of targeting neurons that degenerate in HD, and it sets the stage for the advanced preclinical evaluation of an RNAi-based therapy for this disease.

BIRC3 is a biomarker of mesenchymal habitat of glioblastoma, and a mediator of survival adaptation in hypoxia-driven glioblastoma habitats.

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Wang, Dapeng; Berglund, Anders E; Kenchappa, Rajappa S; MacAulay, Robert J; Mulé, James J; Etame, Arnold B

2017-08-24

Tumor hypoxia is an established facilitator of survival adaptation and mesenchymal transformation in glioblastoma (GBM). The underlying mechanisms that direct hypoxia-mediated survival in GBM habitats are unclear. We previously identified BIRC3 as a mediator of therapeutic resistance in GBM to standard temozolomide (TMZ) chemotherapy and radiotherapy (RT). Here we report that BIRC3 is a biomarker of the hypoxia-mediated adaptive mesenchymal phenotype of GBM. Specifically, in the TCGA dataset elevated BIRC3 gene expression was identified as a superior and selective biomarker of mesenchymal GBM versus neural, proneural and classical subtypes. Further, BIRC3 protein was highly expressed in the tumor cell niches compared to the perivascular niche across multiple regions in GBM patient tissue microarrays. Tumor hypoxia was found to mechanistically induce BIRC3 expression through HIF1-alpha signaling in GBM cells. Moreover, in human GBM xenografts robust BIRC3 expression was noted within hypoxic regions of the tumor. Importantly, selective inhibition of BIRC3 reversed therapeutic resistance of GBM cells to RT in hypoxic microenvironments through enhanced activation of caspases. Collectively, we have uncovered a novel role for BIRC3 as a targetable biomarker and mediator of hypoxia-driven habitats in GBM.

Transcriptional robustness and protein interactions are associated in yeast

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Conant Gavin C

2011-05-01

Full Text Available Abstract Background Robustness to insults, both external and internal, is a characteristic feature of life. One level of biological organization for which noise and robustness have been extensively studied is gene expression. Cells have a variety of mechanisms for buffering noise in gene expression, but it is not completely clear what rules govern whether or not a given gene uses such tools to maintain appropriate expression. Results Here, we show a general association between the degree to which yeast cells have evolved mechanisms to buffer changes in gene expression and whether they possess protein-protein interactions. We argue that this effect bears an affinity to epistasis, because yeast appears to have evolved regulatory mechanisms such that distant changes in gene copy number for a protein-protein interaction partner gene can alter a gene's expression. This association is not unexpected given recent work linking epistasis and the deleterious effects of changes in gene dosage (i.e., the dosage balance hypothesis. Using gene expression data from artificial aneuploid strains of bakers' yeast, we found that genes coding for proteins that physically interact with other proteins show less expression variation in response to aneuploidy than do other genes. This effect is even more pronounced for genes whose products interact with proteins encoded on aneuploid chromosomes. We further found that genes targeted by transcription factors encoded on aneuploid chromosomes were more likely to change in expression after aneuploidy. Conclusions We suggest that these observations can be best understood as resulting from the higher fitness cost of misexpression in epistatic genes and a commensurate greater regulatory control of them.

A robust sound perception model suitable for neuromorphic implementation.

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Coath, Martin; Sheik, Sadique; Chicca, Elisabetta; Indiveri, Giacomo; Denham, Susan L; Wennekers, Thomas

2013-01-01

We have recently demonstrated the emergence of dynamic feature sensitivity through exposure to formative stimuli in a real-time neuromorphic system implementing a hybrid analog/digital network of spiking neurons. This network, inspired by models of auditory processing in mammals, includes several mutually connected layers with distance-dependent transmission delays and learning in the form of spike timing dependent plasticity, which effects stimulus-driven changes in the network connectivity. Here we present results that demonstrate that the network is robust to a range of variations in the stimulus pattern, such as are found in naturalistic stimuli and neural responses. This robustness is a property critical to the development of realistic, electronic neuromorphic systems. We analyze the variability of the response of the network to "noisy" stimuli which allows us to characterize the acuity in information-theoretic terms. This provides an objective basis for the quantitative comparison of networks, their connectivity patterns, and learning strategies, which can inform future design decisions. We also show, using stimuli derived from speech samples, that the principles are robust to other challenges, such as variable presentation rate, that would have to be met by systems deployed in the real world. Finally we demonstrate the potential applicability of the approach to real sounds.

A Robust Sound Perception Model Suitable for Neuromorphic Implementation

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Martin eCoath

2014-01-01

Full Text Available We have recently demonstrated the emergence of dynamic feature sensitivity through exposure to formative stimuli in a real-time neuromorphic system implementing a hybrid analogue/digital network of spiking neurons. This network, inspired by models of auditory processing in mammals, includes several mutually connected layers with distance-dependent transmission delays and learning in the form of spike timing dependent plasticity, which effects stimulus-driven changes in the network connectivity.Here we present results that demonstrate that the network is robust to a range of variations in the stimulus pattern, such as are found in naturalistic stimuli and neural responses. This robustness is a property critical to the development of realistic, electronic neuromorphic systems.We analyse the variability of the response of the network to `noisy' stimuli which allows us to characterize the acuity in information-theoretic terms. This provides an objective basis for the quantitative comparison of networks, their connectivity patterns, and learning strategies, which can inform future design decisions. We also show, using stimuli derived from speech samples, that the principles are robust to other challenges, such as variable presentation rate, that would have to be met by systems deployed in the real world. Finally we demonstrate the potential applicability of the approach to real sounds.

Robust tissue classification for reproducible wound assessment in telemedicine environments

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Wannous, Hazem; Treuillet, Sylvie; Lucas, Yves

2010-04-01

In telemedicine environments, a standardized and reproducible assessment of wounds, using a simple free-handled digital camera, is an essential requirement. However, to ensure robust tissue classification, particular attention must be paid to the complete design of the color processing chain. We introduce the key steps including color correction, merging of expert labeling, and segmentation-driven classification based on support vector machines. The tool thus developed ensures stability under lighting condition, viewpoint, and camera changes, to achieve accurate and robust classification of skin tissues. Clinical tests demonstrate that such an advanced tool, which forms part of a complete 3-D and color wound assessment system, significantly improves the monitoring of the healing process. It achieves an overlap score of 79.3 against 69.1% for a single expert, after mapping on the medical reference developed from the image labeling by a college of experts.

Robust design optimization using the price of robustness, robust least squares and regularization methods

Science.gov (United States)

Bukhari, Hassan J.

2017-12-01

In this paper a framework for robust optimization of mechanical design problems and process systems that have parametric uncertainty is presented using three different approaches. Robust optimization problems are formulated so that the optimal solution is robust which means it is minimally sensitive to any perturbations in parameters. The first method uses the price of robustness approach which assumes the uncertain parameters to be symmetric and bounded. The robustness for the design can be controlled by limiting the parameters that can perturb.The second method uses the robust least squares method to determine the optimal parameters when data itself is subjected to perturbations instead of the parameters. The last method manages uncertainty by restricting the perturbation on parameters to improve sensitivity similar to Tikhonov regularization. The methods are implemented on two sets of problems; one linear and the other non-linear. This methodology will be compared with a prior method using multiple Monte Carlo simulation runs which shows that the approach being presented in this paper results in better performance.

HDAC Inhibition in Vascular Endothelial Cells Regulates the Expression of ncRNAs

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Haloom Rafehi

2016-05-01

Full Text Available While clinical and pre-clinical trials indicate efficacy of histone deacetylase (HDAC inhibitors in disease mediated by dynamic lysine modification, the impact on the expression of non-coding RNAs (ncRNAs remains poorly understood. In this study, we investigate high throughput RNA sequencing data derived from primary human endothelial cells stimulated with HDAC inhibitors suberanilohydroxamic acid (SAHA and Trichostatin A (TSA. We observe robust regulation of ncRNA expression. Integration of gene expression data with histone 3 lysine 9 and 14 acetylation (H3K9/14ac and histone 3 lysine 4 trimethylation (H3K4me3 datasets identified complex and class-specific expression of ncRNAs. We show that EP300 target genes are subject to histone deacetylation at their promoter following HDAC inhibition. This deacetylation drives suppression of protein-coding genes. However, long intergenic non-coding RNAs (lincRNAs regulated by EP300 are activated following HDAC inhibition, despite histone deacetylation. This increased expression was driven by increased H3K4me3 at the gene promoter. For example, elevated promoter H3K4me3 increased lincRNA MALAT1 expression despite broad EP300-associated histone deacetylation. In conclusion, we show that HDAC inhibitors regulate the expression of ncRNA by complex and class-specific epigenetic mechanisms.

A robust data-driven approach for gene ontology annotation.

Science.gov (United States)

Li, Yanpeng; Yu, Hong

2014-01-01

Gene ontology (GO) and GO annotation are important resources for biological information management and knowledge discovery, but the speed of manual annotation became a major bottleneck of database curation. BioCreative IV GO annotation task aims to evaluate the performance of system that automatically assigns GO terms to genes based on the narrative sentences in biomedical literature. This article presents our work in this task as well as the experimental results after the competition. For the evidence sentence extraction subtask, we built a binary classifier to identify evidence sentences using reference distance estimator (RDE), a recently proposed semi-supervised learning method that learns new features from around 10 million unlabeled sentences, achieving an F1 of 19.3% in exact match and 32.5% in relaxed match. In the post-submission experiment, we obtained 22.1% and 35.7% F1 performance by incorporating bigram features in RDE learning. In both development and test sets, RDE-based method achieved over 20% relative improvement on F1 and AUC performance against classical supervised learning methods, e.g. support vector machine and logistic regression. For the GO term prediction subtask, we developed an information retrieval-based method to retrieve the GO term most relevant to each evidence sentence using a ranking function that combined cosine similarity and the frequency of GO terms in documents, and a filtering method based on high-level GO classes. The best performance of our submitted runs was 7.8% F1 and 22.2% hierarchy F1. We found that the incorporation of frequency information and hierarchy filtering substantially improved the performance. In the post-submission evaluation, we obtained a 10.6% F1 using a simpler setting. Overall, the experimental analysis showed our approaches were robust in both the two tasks. © The Author(s) 2014. Published by Oxford University Press.

ROBUSTNESS OF A FACE-RECOGNITION TECHNIQUE BASED ON SUPPORT VECTOR MACHINES

OpenAIRE

Prashanth Harshangi; Koshy George

2010-01-01

The ever-increasing requirements of security concerns have placed a greater demand for face recognition surveillance systems. However, most current face recognition techniques are not quite robust with respect to factors such as variable illumination, facial expression and detail, and noise in images. In this paper, we demonstrate that face recognition using support vector machines are sufficiently robust to different kinds of noise, does not require image pre-processing, and can be used with...

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology

Science.gov (United States)

Chen, Bor-Sen; Lin, Ying-Po

2013-01-01

Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental

Delivery of a survivin promoter-driven antisense survivin-expressing plasmid DNA as a cancer therapeutic: a proof-of-concept study

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Lin KY

2016-05-01

Full Text Available Kun-Yuan Lin,1 Siao Muk Cheng,2 Shing-Ling Tsai,2 Ju-Ya Tsai,1 Chun-Hui Lin,1 Chun Hei Antonio Cheung1,2 1Department of Pharmacology, College of Medicine, National Cheng Kung University, Tainan, Taiwan, ROC; 2Institute of Basic Medical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan, ROC Abstract: Survivin is a member of the inhibitor-of-apoptosis proteins family. It is overexpressed in many different cancer types but not in the differentiated normal tissue. In addition, overexpression of survivin promotes cancer cell survival and induces chemotherapeutic drug resistance, making it an attractive target for new anticancer interventions. Despite survivin being a promising molecular target for anticancer treatment, it is widely accepted that survivin is only a “semi-druggable” target. Therefore, it is important to develop a new strategy to target survivin for anticancer treatment. In this study, we constructed a novel survivin promoter-driven full-length antisense survivin (pSur/AS-Sur expression plasmid DNA. Promoter activity assay revealed that the activity of the survivin promoter of pSur/AS-Sur correlated with the endogenous expression of survivin at the transcriptional level in the transfected A549, MDA-MB-231, and PANC-1 cancer cells. Western blot analysis showed that liposomal delivery of pSur/AS-Sur successfully downregulated the expression of survivin in A549, MBA-MB-231, and PANC-1 cells in vitro. In addition, delivery of pSur/AS-Sur induced autophagy, caspase-dependent apoptosis, and caspase-independent apoptosis as indicated by the increased LC3B-II conversion, autophagosome formation, caspase-9/-3 and poly(ADP-ribose polymerase-1 cleavage, and apoptosis-inducing factor nuclear translocation in A549, MBA-MB-231, and PANC-1 cells. Importantly, liposomal delivery of pSur/AS-Sur was also capable of decreasing the proliferation of the survivin/MDR1 coexpressing multidrug-resistant KB-TAX50 cancer cells and

A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data.

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Kang, Tianyu; Ding, Wei; Zhang, Luoyan; Ziemek, Daniel; Zarringhalam, Kourosh

2017-12-19

Stratification of patient subpopulations that respond favorably to treatment or experience and adverse reaction is an essential step toward development of new personalized therapies and diagnostics. It is currently feasible to generate omic-scale biological measurements for all patients in a study, providing an opportunity for machine learning models to identify molecular markers for disease diagnosis and progression. However, the high variability of genetic background in human populations hampers the reproducibility of omic-scale markers. In this paper, we develop a biological network-based regularized artificial neural network model for prediction of phenotype from transcriptomic measurements in clinical trials. To improve model sparsity and the overall reproducibility of the model, we incorporate regularization for simultaneous shrinkage of gene sets based on active upstream regulatory mechanisms into the model. We benchmark our method against various regression, support vector machines and artificial neural network models and demonstrate the ability of our method in predicting the clinical outcomes using clinical trial data on acute rejection in kidney transplantation and response to Infliximab in ulcerative colitis. We show that integration of prior biological knowledge into the classification as developed in this paper, significantly improves the robustness and generalizability of predictions to independent datasets. We provide a Java code of our algorithm along with a parsed version of the STRING DB database. In summary, we present a method for prediction of clinical phenotypes using baseline genome-wide expression data that makes use of prior biological knowledge on gene-regulatory interactions in order to increase robustness and reproducibility of omic-scale markers. The integrated group-wise regularization methods increases the interpretability of biological signatures and gives stable performance estimates across independent test sets.

System design and energetic characterization of a four-wheel-driven series–parallel hybrid electric powertrain for heavy-duty applications

International Nuclear Information System (INIS)

Wang, Enhua; Guo, Di; Yang, Fuyuan

2015-01-01

Highlights: • A novel four-wheel-driven series–parallel hybrid powertrain is proposed. • A system model and a rule-based control strategy are designed. • Energetic performance is compared to a rear-wheel-driven hybrid powertrain. • Less torsional oscillation and more robust regenerative braking are achieved. - Abstract: Powertrain topology design is vital for system performance of a hybrid electric vehicle. In this paper, a novel four-wheel-driven series–parallel hybrid electric powertrain is proposed. A motor is connected to the differential of the rear axle. An auxiliary power unit is linked to the differential of the front axle via a clutch. First, a mathematical model was established to evaluate the fuel-saving potential. A rule-based energy management algorithm was subsequently designed, and its working parameters were optimized. The hybrid powertrain system was applied to a transit bus, and the system characteristics were analyzed. Compared to an existing coaxial power-split hybrid powertrain, the fuel economy of the four-wheel-driven series–parallel hybrid powertrain can be at the same level under normal road conditions. However, the proposed four-wheel-driven series–parallel hybrid powertrain can recover braking energy more efficiently under road conditions with a low adhesive coefficient and can alleviate the torsional oscillation occurring at the existing coaxial power-split hybrid powertrain. Therefore, the four-wheel-driven series–parallel hybrid powertrain is a good solution for transit buses toward more robust performance.

A Robust Parallel Algorithm for Combinatorial Compressed Sensing

Science.gov (United States)

Mendoza-Smith, Rodrigo; Tanner, Jared W.; Wechsung, Florian

2018-04-01

In previous work two of the authors have shown that a vector $x \\in \\mathbb{R}^n$ with at most $k Parallel-$\\ell_0$ decoding algorithm, where $\\mathrm{nnz}(A)$ denotes the number of nonzero entries in $A \\in \\mathbb{R}^{m \\times n}$. In this paper we present the Robust-$\\ell_0$ decoding algorithm, which robustifies Parallel-$\\ell_0$ when the sketch $Ax$ is corrupted by additive noise. This robustness is achieved by approximating the asymptotic posterior distribution of values in the sketch given its corrupted measurements. We provide analytic expressions that approximate these posteriors under the assumptions that the nonzero entries in the signal and the noise are drawn from continuous distributions. Numerical experiments presented show that Robust-$\\ell_0$ is superior to existing greedy and combinatorial compressed sensing algorithms in the presence of small to moderate signal-to-noise ratios in the setting of Gaussian signals and Gaussian additive noise.

Perceptual Robust Design

DEFF Research Database (Denmark)

Pedersen, Søren Nygaard

The research presented in this PhD thesis has focused on a perceptual approach to robust design. The results of the research and the original contribution to knowledge is a preliminary framework for understanding, positioning, and applying perceptual robust design. Product quality is a topic...... been presented. Therefore, this study set out to contribute to the understanding and application of perceptual robust design. To achieve this, a state-of-the-art and current practice review was performed. From the review two main research problems were identified. Firstly, a lack of tools...... for perceptual robustness was found to overlap with the optimum for functional robustness and at most approximately 2.2% out of the 14.74% could be ascribed solely to the perceptual robustness optimisation. In conclusion, the thesis have offered a new perspective on robust design by merging robust design...

Environmental Noise, Genetic Diversity and the Evolution of Evolvability and Robustness in Model Gene Networks

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Steiner, Christopher F.

2012-01-01

The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or “evolvability”) can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise) compared to populations in stable or randomly varying (white noise) environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions. PMID:23284934

Neutrality and robustness in evo-devo: emergence of lateral inhibition.

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Andreea Munteanu

2008-11-01

Full Text Available Embryonic development is defined by the hierarchical dynamical process that translates genetic information (genotype into a spatial gene expression pattern (phenotype providing the positional information for the correct unfolding of the organism. The nature and evolutionary implications of genotype-phenotype mapping still remain key topics in evolutionary developmental biology (evo-devo. We have explored here issues of neutrality, robustness, and diversity in evo-devo by means of a simple model of gene regulatory networks. The small size of the system allowed an exhaustive analysis of the entire fitness landscape and the extent of its neutrality. This analysis shows that evolution leads to a class of robust genetic networks with an expression pattern characteristic of lateral inhibition. This class is a repertoire of distinct implementations of this key developmental process, the diversity of which provides valuable clues about its underlying causal principles.

ESTIMATION OF GRASPING TORQUE USING ROBUST REACTION TORQUE OBSERVER FOR ROBOTIC FORCEPS

OpenAIRE

塚本, 祐介

2015-01-01

Abstract— In this paper, the estimation of the grasping torque of robotic forceps without the use of a force/torque sensor is discussed. To estimate the grasping torque when the robotic forceps driven by a rotary motor with a reduction gear grasps an object, a novel robust reaction torque observer is proposed. In the case where a conventional reaction force/torque observer is applied, the estimated torque includes not only the grasping torque, namely the reaction torque, but also t...

The Therapeutic Potential of CRISPR/Cas9 Systems in Oncogene-Addicted Cancer Types: Virally Driven Cancers as a Model System

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Luqman Jubair

2017-09-01

Full Text Available The field of gene editing is undergoing unprecedented growth. The first ex vivo human clinical trial in China started in 2016, more than 1000 US patents have been filed, and there is exponential growth in publications. The ability to edit genes with high fidelity is promising for the development of new treatments for a range of diseases, particularly inherited conditions, infectious diseases, and cancers. For cancer, a major issue is the identification of driver mutations and oncogenes to target for therapeutic effect, and this requires the development of robust models with which to prove their efficacy. The challenge is that there is rarely a single critical gene. However, virally driven cancers, in which cells are addicted to the expression of a single viral oncogene in some cases, may serve as model systems for CRISPR/Cas therapies, as they did for RNAi. These models and systems offer an excellent opportunity to test both preclinical models and clinical conditions to examine the effectiveness of gene editing, and here we review the options and offer a way forward. Keywords: CRISPR/Cas9, virally-driven cancers, cervical cancer, oncogene-addiction

Robust multi-tissue gene panel for cancer detection

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Talantov Dmitri

2010-06-01

Full Text Available Abstract Background We have identified a set of genes whose relative mRNA expression levels in various solid tumors can be used to robustly distinguish cancer from matching normal tissue. Our current feature set consists of 113 gene probes for 104 unique genes, originally identified as differentially expressed in solid primary tumors in microarray data on Affymetrix HG-U133A platform in five tissue types: breast, colon, lung, prostate and ovary. For each dataset, we first identified a set of genes significantly differentially expressed in tumor vs. normal tissue at p-value = 0.05 using an experimentally derived error model. Our common cancer gene panel is the intersection of these sets of significantly dysregulated genes and can distinguish tumors from normal tissue on all these five tissue types. Methods Frozen tumor specimens were obtained from two commercial vendors Clinomics (Pittsfield, MA and Asterand (Detroit, MI. Biotinylated targets were prepared using published methods (Affymetrix, CA and hybridized to Affymetrix U133A GeneChips (Affymetrix, CA. Expression values for each gene were calculated using Affymetrix GeneChip analysis software MAS 5.0. We then used a software package called Genes@Work for differential expression discovery, and SVM light linear kernel for building classification models. Results We validate the predictability of this gene list on several publicly available data sets generated on the same platform. Of note, when analysing the lung cancer data set of Spira et al, using an SVM linear kernel classifier, our gene panel had 94.7% leave-one-out accuracy compared to 87.8% using the gene panel in the original paper. In addition, we performed high-throughput validation on the Dana Farber Cancer Institute GCOD database and several GEO datasets. Conclusions Our result showed the potential for this panel as a robust classification tool for multiple tumor types on the Affymetrix platform, as well as other whole genome arrays

Linear Perturbation Adaptive Control of Hydraulically Driven Manipulators

DEFF Research Database (Denmark)

Andersen, T.O.; Hansen, M.R.; Conrad, Finn

2004-01-01

control.Using the Lyapunov approach, under slowly time-varying assumptions, it is shown that the tracking error and the parameter error remain bounded. This bound is a function of the ideal parameters and a bounded disturbance. The control algorithm decouples and linearizes the manipulator so that each......A method for synthesis of a robust adaptive scheme for a hydraulically driven manipulator, that takes full advantage of any known system dynamics to simplify the adaptive control problem for the unknown portion of the dynamics is presented. The control method is based on adaptive perturbation...

Thy1.2 driven expression of transgenic His₆-SUMO2 in the brain of mice alters a restricted set of genes.

Science.gov (United States)

Rossner, Moritz J; Tirard, Marilyn

2014-08-05

Protein SUMOylation is a post-translational protein modification with a key regulatory role in nerve cell development and function, but its function in mammals in vivo has only been studied cursorily. We generated two new transgenic mouse lines that express His6-tagged SUMO1 and SUMO2 driven by the Thy1.2 promoter. The brains of mice of the two lines express transgenic His6-SUMO peptides and conjugate them to substrates in vivo but cytoarchitecture and synaptic organization of adult transgenic mouse brains are indistinguishable from the wild-type situation. We investigated the impact of transgenic SUMO expression on gene transcription in the hippocampus by performing genome wide analyses using microarrays. Surprisingly, no changes were observed in Thy1.2::His6-SUMO1 transgenic mice and only a restricted set of genes were upregulated in Thy1.2::His6-SUMO2 mice. Among these, Penk1 (Preproenkephalin 1), which encodes Met-enkephalin neuropeptides, showed the highest degree of alteration. Accordingly, a significant increase in Met-enkephalin peptide levels in the hippocampus of Thy1.2::His6-SUMO2 was detected, but the expression levels and cellular localization of Met-enkephalin receptors were not changed. Thus, transgenic neuronal expression of His6-SUMO1 or His6-SUMO2 only induces very minor phenotypical changes in mice. Copyright © 2014 Elsevier B.V. All rights reserved.

Obesity-driven prepartal hepatic lipid accumulation in dairy cows is associated with increased CD36 and SREBP-1 expression.

Science.gov (United States)

Prodanović, Radiša; Korićanac, Goran; Vujanac, Ivan; Djordjević, Ana; Pantelić, Marija; Romić, Snježana; Stanimirović, Zoran; Kirovski, Danijela

2016-08-01

We investigated the hypothesis that obesity in dairy cows enhanced expression of proteins involved in hepatic fatty acid uptake and metabolism. Sixteen Holstein-Friesian close-up cows were divided into 2 equal groups based on their body condition score (BCS) as optimal (3.25≤BCS≤3.5) and high (4.0≤BCS≤4.25). Intravenous glucose tolerance test (GTT) and liver biopsies were carried out at day 10 before calving. Blood samples were collected before (basal) and after glucose infusion, and glucose, insulin and non-esterified fatty acid (NEFA) levels were determined at each sample point. In addition, β-hydroxybutyrate and triglycerides levels were measured in the basal samples. The liver biopsies were analyzed for total lipid content and protein expression of insulin receptor beta (IRβ), fatty acid translocase (FAT/CD36) and sterol regulatory element-binding protein-1 (SREBP-1). Basal glucose and insulin were higher in high-BCS cows, which coincided with higher circulating triglycerides and hepatic lipid content. Clearance rate and AUC for NEFA during GTT were higher in optimal-BCS cows. The development of insulin resistance and fatty liver in obese cows was paralleled by increased hepatic expression of the IRβ, CD36 and SREBP-1. These results suggest that increased expression of hepatic CD36 and SREBP-1 is relevant in the obesity-driven lipid accumulation in the liver of dairy cows during late gestation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Model-driven Service Engineering with SoaML

Science.gov (United States)

Elvesæter, Brian; Carrez, Cyril; Mohagheghi, Parastoo; Berre, Arne-Jørgen; Johnsen, Svein G.; Solberg, Arnor

This chapter presents a model-driven service engineering (MDSE) methodology that uses OMG MDA specifications such as BMM, BPMN and SoaML to identify and specify services within a service-oriented architecture. The methodology takes advantage of business modelling practices and provides a guide to service modelling with SoaML. The presentation is case-driven and illuminated using the telecommunication example. The chapter focuses in particular on the use of the SoaML modelling language as a means for expressing service specifications that are aligned with business models and can be realized in different platform technologies.

Robust multivariate analysis

CERN Document Server

J Olive, David

2017-01-01

This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given.  The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory.   The robust techniques  are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis.  A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with...

Geomagnetic matching navigation algorithm based on robust estimation

Science.gov (United States)

Xie, Weinan; Huang, Liping; Qu, Zhenshen; Wang, Zhenhuan

2017-08-01

The outliers in the geomagnetic survey data seriously affect the precision of the geomagnetic matching navigation and badly disrupt its reliability. A novel algorithm which can eliminate the outliers influence is investigated in this paper. First, the weight function is designed and its principle of the robust estimation is introduced. By combining the relation equation between the matching trajectory and the reference trajectory with the Taylor series expansion for geomagnetic information, a mathematical expression of the longitude, latitude and heading errors is acquired. The robust target function is obtained by the weight function and the mathematical expression. Then the geomagnetic matching problem is converted to the solutions of nonlinear equations. Finally, Newton iteration is applied to implement the novel algorithm. Simulation results show that the matching error of the novel algorithm is decreased to 7.75% compared to the conventional mean square difference (MSD) algorithm, and is decreased to 18.39% to the conventional iterative contour matching algorithm when the outlier is 40nT. Meanwhile, the position error of the novel algorithm is 0.017° while the other two algorithms fail to match when the outlier is 400nT.

A Robust CuCr2O4/SiO2 Composite Photothermal Material with Underwater Black Property and Extremely High Thermal Stability for Solar-Driven Water Evaporation

KAUST Repository

Shi, Yusuf

2017-12-27

The design and fabrication of efficient photothermal materials is the key issue in solar-driven water evaporation. In this work, a robust CuCr2O4/SiO2 composite membrane with outstanding solar-driven water evaporation performance (1.32 kg m−2 h−1) under one sun irradiation is rationally designed and synthesized by using quartz glass fibrous membrane as supporting matrix and stable CuCr2O4 particles as the active light absorber. Instead of coating a separate layer on top of the support, the CuCr2O4 particles are evenly distributed inside the matrix, which endows the membrane with great mechanical strength and excellent wear and abrasion resistance. The highly porous composite survives 6 atm pressure and retains its performance even after 75% of the membrane is removed by sandpaper. This work also looks into a generally overlooked aspect of wet versus dry state of photothermal material and its implications. Interestingly, the composite possesses a gray color with a high reflectance in dry state but turns into deep black with a low reflectance in wet state due to the decreased subsurface scattering and strong NIR light absorbance of water in wet state. This composite material also possesses excellent thermal stability and thermal shock resistance, making it able to be easily recovered by calcination in air or direct burning in fire for contaminants removal. The results demonstrate that this composite is a competitive photothermal material for practical solar distillation and indicate that the optical properties of material in wet state are more relevant to photothermal material screening and optimization for solar distillation.

A simple and robust protocol for high-yield expression of perdeuterated proteins in Escherichia coli grown in shaker flasks

Energy Technology Data Exchange (ETDEWEB)

Cai, Mengli [National Institutes of Health, Laboratories of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States); Huang, Ying; Yang, Renbin; Craigie, Robert, E-mail: robertc@niddk.nih.gov [National Institutes of Health, Laboratories of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases (United States); Clore, G. M., E-mail: mariusc@mail.nih.gov [National Institutes of Health, Laboratories of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States)

2016-10-15

We present a simple, convenient and robust protocol for expressing perdeuterated proteins in E. coli BL21(DE3) cells in shaker flasks that reduces D{sub 2}O usage tenfold and d{sub 7}-glucose usage by 30 %. Using a modified M9 medium and optimized growth conditions, we were able to grow cells in linear log phase to an OD{sub 600} of up to 10. Inducing the cells with isopropyl β-d-1-thiogalactopyranoside at an OD{sub 600} of 10, instead of less than 1, enabled us to increase the cell mass tenfold per unit volume of cell culture. We show that protein expression levels per cell are the same when induced at an OD{sub 600} between 1 and 10 under these growth conditions. Thus, our new protocol can increase protein yield per unit volume of cell culture tenfold. Adaptation of E. coli from H{sub 2}O-based to D{sub 2}O-based medium is also key for ensuring high levels of protein expression in D{sub 2}O. We find that a simple three-step adaptation approach—Luria–Bertani (LB) medium in H{sub 2}O to LB in D{sub 2}O to modified-M9 medium in D{sub 2}O is both simple and reliable. The method increases the yield of perdeuterated proteins by up to tenfold using commonly available air shakers without any requirement for specialized fermentation equipment.

A simple and robust protocol for high-yield expression of perdeuterated proteins in Escherichia coli grown in shaker flasks

International Nuclear Information System (INIS)

Cai, Mengli; Huang, Ying; Yang, Renbin; Craigie, Robert; Clore, G. M.

2016-01-01

We present a simple, convenient and robust protocol for expressing perdeuterated proteins in E. coli BL21(DE3) cells in shaker flasks that reduces D_2O usage tenfold and d_7-glucose usage by 30 %. Using a modified M9 medium and optimized growth conditions, we were able to grow cells in linear log phase to an OD_6_0_0 of up to 10. Inducing the cells with isopropyl β-d-1-thiogalactopyranoside at an OD_6_0_0 of 10, instead of less than 1, enabled us to increase the cell mass tenfold per unit volume of cell culture. We show that protein expression levels per cell are the same when induced at an OD_6_0_0 between 1 and 10 under these growth conditions. Thus, our new protocol can increase protein yield per unit volume of cell culture tenfold. Adaptation of E. coli from H_2O-based to D_2O-based medium is also key for ensuring high levels of protein expression in D_2O. We find that a simple three-step adaptation approach—Luria–Bertani (LB) medium in H_2O to LB in D_2O to modified-M9 medium in D_2O is both simple and reliable. The method increases the yield of perdeuterated proteins by up to tenfold using commonly available air shakers without any requirement for specialized fermentation equipment.

Robust Learning of High-dimensional Biological Networks with Bayesian Networks

Science.gov (United States)

Nägele, Andreas; Dejori, Mathäus; Stetter, Martin

Structure learning of Bayesian networks applied to gene expression data has become a potentially useful method to estimate interactions between genes. However, the NP-hardness of Bayesian network structure learning renders the reconstruction of the full genetic network with thousands of genes unfeasible. Consequently, the maximal network size is usually restricted dramatically to a small set of genes (corresponding with variables in the Bayesian network). Although this feature reduction step makes structure learning computationally tractable, on the downside, the learned structure might be adversely affected due to the introduction of missing genes. Additionally, gene expression data are usually very sparse with respect to the number of samples, i.e., the number of genes is much greater than the number of different observations. Given these problems, learning robust network features from microarray data is a challenging task. This chapter presents several approaches tackling the robustness issue in order to obtain a more reliable estimation of learned network features.

Robustness of Structures

DEFF Research Database (Denmark)

Faber, Michael Havbro; Vrouwenvelder, A.C.W.M.; Sørensen, John Dalsgaard

2011-01-01

In 2005, the Joint Committee on Structural Safety (JCSS) together with Working Commission (WC) 1 of the International Association of Bridge and Structural Engineering (IABSE) organized a workshop on robustness of structures. Two important decisions resulted from this workshop, namely...... ‘COST TU0601: Robustness of Structures’ was initiated in February 2007, aiming to provide a platform for exchanging and promoting research in the area of structural robustness and to provide a basic framework, together with methods, strategies and guidelines enhancing robustness of structures...... the development of a joint European project on structural robustness under the COST (European Cooperation in Science and Technology) programme and the decision to develop a more elaborate document on structural robustness in collaboration between experts from the JCSS and the IABSE. Accordingly, a project titled...

Bulk-viscosity-driven asymmetric inflationary universe

International Nuclear Information System (INIS)

Waga, I.; Lima, J.A.S.; Portugal, R.

1987-01-01

A primordial net bosinic charge is introduced in the context of the bulk-viscosity-driven inflationary models. The analysis is carried through a macroscopic point of view in the framework of the causal thermodynamic theory. The conditions for having exponetial and generalized inflation are obtained. A phenomenological expression for the bulk viscosity coefficient is also derived. (author) [pt

HSV-2-Driven Increase in the Expression of α4β7 Correlates with Increased Susceptibility to Vaginal SHIVSF162P3 Infection

Science.gov (United States)

Goode, Diana; Truong, Rosaline; Villegas, Guillermo; Calenda, Giulia; Guerra-Perez, Natalia; Piatak, Michael; Lifson, Jeffrey D.; Blanchard, James; Gettie, Agegnehu; Robbiani, Melissa; Martinelli, Elena

2014-01-01

The availability of highly susceptible HIV target cells that can rapidly reach the mucosal lymphoid tissues may increase the chances of an otherwise rare transmission event to occur. Expression of α4β7 is required for trafficking of immune cells to gut inductive sites where HIV can expand and it is expressed at high level on cells particularly susceptible to HIV infection. We hypothesized that HSV-2 modulates the expression of α4β7 and other homing receptors in the vaginal tissue and that this correlates with the increased risk of HIV acquisition in HSV-2 positive individuals. To test this hypothesis we used an in vivo rhesus macaque (RM) model of HSV-2 vaginal infection and a new ex vivo model of macaque vaginal explants. In vivo we found that HSV-2 latently infected RMs appeared to be more susceptible to vaginal SHIVSF162P3 infection, had higher frequency of α4β7 high CD4+ T cells in the vaginal tissue and higher expression of α4β7 and CD11c on vaginal DCs. Similarly, ex vivo HSV-2 infection increased the susceptibility of the vaginal tissue to SHIVSF162P3. HSV-2 infection increased the frequencies of α4β7 high CD4+ T cells and this directly correlated with HSV-2 replication. A higher amount of inflammatory cytokines in vaginal fluids of the HSV-2 infected animals was similar to those found in the supernatants of the infected explants. Remarkably, the HSV-2-driven increase in the frequency of α4β7 high CD4+ T cells directly correlated with SHIV replication in the HSV-2 infected tissues. Our results suggest that the HSV-2-driven increase in availability of CD4+ T cells and DCs that express high levels of α4β7 is associated with the increase in susceptibility to SHIV due to HSV-2. This may persists in absence of HSV-2 shedding. Hence, higher availability of α4β7 positive HIV target cells in the vaginal tissue may constitute a risk factor for HIV transmission. PMID:25521298

Robust generation and expansion of skeletal muscle progenitors and myocytes from human pluripotent stem cells.

Science.gov (United States)

Shelton, Michael; Kocharyan, Avetik; Liu, Jun; Skerjanc, Ilona S; Stanford, William L

2016-05-15

Human pluripotent stem cells provide a developmental model to study early embryonic and tissue development, tease apart human disease processes, perform drug screens to identify potential molecular effectors of in situ regeneration, and provide a source for cell and tissue based transplantation. Highly efficient differentiation protocols have been established for many cell types and tissues; however, until very recently robust differentiation into skeletal muscle cells had not been possible unless driven by transgenic expression of master regulators of myogenesis. Nevertheless, several breakthrough protocols have been published in the past two years that efficiently generate cells of the skeletal muscle lineage from pluripotent stem cells. Here, we present an updated version of our recently described 50-day protocol in detail, whereby chemically defined media are used to drive and support muscle lineage development from initial CHIR99021-induced mesoderm through to PAX7-expressing skeletal muscle progenitors and mature skeletal myocytes. Furthermore, we report an optional method to passage and expand differentiating skeletal muscle progenitors approximately 3-fold every 2weeks using Collagenase IV and continued FGF2 supplementation. Both protocols have been optimized using a variety of human pluripotent stem cell lines including patient-derived induced pluripotent stem cells. Taken together, our differentiation and expansion protocols provide sufficient quantities of skeletal muscle progenitors and myocytes that could be used for a variety of studies. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Data-driven process decomposition and robust online distributed modelling for large-scale processes

Science.gov (United States)

Shu, Zhang; Lijuan, Li; Lijuan, Yao; Shipin, Yang; Tao, Zou

2018-02-01

With the increasing attention of networked control, system decomposition and distributed models show significant importance in the implementation of model-based control strategy. In this paper, a data-driven system decomposition and online distributed subsystem modelling algorithm was proposed for large-scale chemical processes. The key controlled variables are first partitioned by affinity propagation clustering algorithm into several clusters. Each cluster can be regarded as a subsystem. Then the inputs of each subsystem are selected by offline canonical correlation analysis between all process variables and its controlled variables. Process decomposition is then realised after the screening of input and output variables. When the system decomposition is finished, the online subsystem modelling can be carried out by recursively block-wise renewing the samples. The proposed algorithm was applied in the Tennessee Eastman process and the validity was verified.

Robust Robot Grasp Detection in Multimodal Fusion

Directory of Open Access Journals (Sweden)

Zhang Qiang

2017-01-01

Full Text Available Accurate robot grasp detection for model free objects plays an important role in robotics. With the development of RGB-D sensors, object perception technology has made great progress. Reach feature expression by the colour and the depth data is a critical problem that needs to be addressed in order to accomplish the grasping task. To solve the problem of data fusion, this paper proposes a convolutional neural networks (CNN based approach combined with regression and classification. In the CNN model, the colour and the depth modal data are deeply fused together to achieve accurate feature expression. Additionally, Welsch function is introduced into the approach to enhance robustness of the training process. Experiment results demonstrates the superiority of the proposed method.

A defect-driven diagnostic method for machine tool spindles.

Science.gov (United States)

Vogl, Gregory W; Donmez, M Alkan

2015-01-01

Simple vibration-based metrics are, in many cases, insufficient to diagnose machine tool spindle condition. These metrics couple defect-based motion with spindle dynamics; diagnostics should be defect-driven. A new method and spindle condition estimation device (SCED) were developed to acquire data and to separate system dynamics from defect geometry. Based on this method, a spindle condition metric relying only on defect geometry is proposed. Application of the SCED on various milling and turning spindles shows that the new approach is robust for diagnosing the machine tool spindle condition.

Defining robustness protocols: a method to include and evaluate robustness in clinical plans

International Nuclear Information System (INIS)

McGowan, S E; Albertini, F; Lomax, A J; Thomas, S J

2015-01-01

We aim to define a site-specific robustness protocol to be used during the clinical plan evaluation process. Plan robustness of 16 skull base IMPT plans to systematic range and random set-up errors have been retrospectively and systematically analysed. This was determined by calculating the error-bar dose distribution (ebDD) for all the plans and by defining some metrics used to define protocols aiding the plan assessment. Additionally, an example of how to clinically use the defined robustness database is given whereby a plan with sub-optimal brainstem robustness was identified. The advantage of using different beam arrangements to improve the plan robustness was analysed. Using the ebDD it was found range errors had a smaller effect on dose distribution than the corresponding set-up error in a single fraction, and that organs at risk were most robust to the range errors, whereas the target was more robust to set-up errors. A database was created to aid planners in terms of plan robustness aims in these volumes. This resulted in the definition of site-specific robustness protocols. The use of robustness constraints allowed for the identification of a specific patient that may have benefited from a treatment of greater individuality. A new beam arrangement showed to be preferential when balancing conformality and robustness for this case. The ebDD and error-bar volume histogram proved effective in analysing plan robustness. The process of retrospective analysis could be used to establish site-specific robustness planning protocols in proton therapy. These protocols allow the planner to determine plans that, although delivering a dosimetrically adequate dose distribution, have resulted in sub-optimal robustness to these uncertainties. For these cases the use of different beam start conditions may improve the plan robustness to set-up and range uncertainties. (paper)

Defining robustness protocols: a method to include and evaluate robustness in clinical plans

Science.gov (United States)

McGowan, S. E.; Albertini, F.; Thomas, S. J.; Lomax, A. J.

2015-04-01

We aim to define a site-specific robustness protocol to be used during the clinical plan evaluation process. Plan robustness of 16 skull base IMPT plans to systematic range and random set-up errors have been retrospectively and systematically analysed. This was determined by calculating the error-bar dose distribution (ebDD) for all the plans and by defining some metrics used to define protocols aiding the plan assessment. Additionally, an example of how to clinically use the defined robustness database is given whereby a plan with sub-optimal brainstem robustness was identified. The advantage of using different beam arrangements to improve the plan robustness was analysed. Using the ebDD it was found range errors had a smaller effect on dose distribution than the corresponding set-up error in a single fraction, and that organs at risk were most robust to the range errors, whereas the target was more robust to set-up errors. A database was created to aid planners in terms of plan robustness aims in these volumes. This resulted in the definition of site-specific robustness protocols. The use of robustness constraints allowed for the identification of a specific patient that may have benefited from a treatment of greater individuality. A new beam arrangement showed to be preferential when balancing conformality and robustness for this case. The ebDD and error-bar volume histogram proved effective in analysing plan robustness. The process of retrospective analysis could be used to establish site-specific robustness planning protocols in proton therapy. These protocols allow the planner to determine plans that, although delivering a dosimetrically adequate dose distribution, have resulted in sub-optimal robustness to these uncertainties. For these cases the use of different beam start conditions may improve the plan robustness to set-up and range uncertainties.

Ectopic expression of human mTOR increases viability, robustness, cell size, proliferation, and antibody production of chinese hamster ovary cells.

Science.gov (United States)

Dreesen, Imke A J; Fussenegger, Martin

2011-04-01

Engineering of mammalian production cell lines to improve titer and quality of biopharmaceuticals is a top priority of the biopharmaceutical manufacturing industry providing protein therapeutics to patients worldwide. While many engineering strategies have been successful in the past decade they were often based on the over-expression of a single transgene and therefore limited to addressing a single bottleneck in the cell's production capacity. We provide evidence that ectopic expression of the global metabolic sensor and processing protein mammalian target of rapamycin (mTOR), simultaneously improves key bioprocess-relevant characteristics of Chinese hamster ovary (CHO) cell-derived production cell lines such as cell growth (increased cell size and protein content), proliferation (increased cell-cycle progression), viability (decreased apoptosis), robustness (decreased sensitivity to sub-optimal growth factor and oxygen supplies) and specific productivity of secreted human glycoproteins. Cultivation of mTOR-transgenic CHO-derived cell lines engineered for secretion of a therapeutic IgG resulted in antibody titers of up to 50 pg/cell/day, which represents a four-fold increase compared to the parental production cell line. mTOR-based engineering of mammalian production cell lines may therefore have a promising future in biopharmaceutical manufacturing of human therapeutic proteins. Copyright © 2010 Wiley Periodicals, Inc.

Robust expression of a bioactive mammalian protein in chlamydomonas chloroplast

Science.gov (United States)

Mayfield, Stephen P.

2010-03-16

Methods and compositions are disclosed to engineer chloroplast comprising heterologous mammalian genes via a direct replacement of chloroplast Photosystem II (PSII) reaction center protein coding regions to achieve expression of recombinant protein above 5% of total protein. When algae is used, algal expressed protein is produced predominantly as a soluble protein where the functional activity of the peptide is intact. As the host algae is edible, production of biologics in this organism for oral delivery or proteins/peptides, especially gut active proteins, without purification is disclosed.

Direct visualization of membrane architecture of myelinating cells in transgenic mice expressing membrane-anchored EGFP.

Science.gov (United States)

Deng, Yaqi; Kim, BongWoo; He, Xuelian; Kim, Sunja; Lu, Changqing; Wang, Haibo; Cho, Ssang-Goo; Hou, Yiping; Li, Jianrong; Zhao, Xianghui; Lu, Q Richard

2014-04-01

Myelinogenesis is a complex process that involves substantial and dynamic changes in plasma membrane architecture and myelin interaction with axons. Highly ramified processes of oligodendrocytes in the central nervous system (CNS) make axonal contact and then extrapolate to wrap around axons and form multilayer compact myelin sheathes. Currently, the mechanisms governing myelin sheath assembly and axon selection by myelinating cells are not fully understood. Here, we generated a transgenic mouse line expressing the membrane-anchored green fluorescent protein (mEGFP) in myelinating cells, which allow live imaging of details of myelinogenesis and cellular behaviors in the nervous systems. mEGFP expression is driven by the promoter of 2'-3'-cyclic nucleotide 3'-phosphodiesterase (CNP) that is expressed in the myelinating cell lineage. Robust mEGFP signals appear in the membrane processes of oligodendrocytes in the CNS and Schwann cells in the peripheral nervous system (PNS), wherein mEGFP expression defines the inner layers of myelin sheaths and Schmidt-Lanterman incisures in adult sciatic nerves. In addition, mEGFP expression can be used to track the extent of remyelination after demyelinating injury in a toxin-induced demyelination animal model. Taken together, the membrane-anchored mEGFP expression in the new transgenic line would facilitate direct visualization of dynamic myelin membrane formation and assembly during development and process remodeling during remyelination after various demyelinating injuries.

Self-Adaptive Event-Driven Simulation of Multi-Scale Plasma Systems

Science.gov (United States)

Omelchenko, Yuri; Karimabadi, Homayoun

2005-10-01

Multi-scale plasmas pose a formidable computational challenge. The explicit time-stepping models suffer from the global CFL restriction. Efficient application of adaptive mesh refinement (AMR) to systems with irregular dynamics (e.g. turbulence, diffusion-convection-reaction, particle acceleration etc.) may be problematic. To address these issues, we developed an alternative approach to time stepping: self-adaptive discrete-event simulation (DES). DES has origin in operations research, war games and telecommunications. We combine finite-difference and particle-in-cell techniques with this methodology by assuming two caveats: (1) a local time increment, dt for a discrete quantity f can be expressed in terms of a physically meaningful quantum value, df; (2) f is considered to be modified only when its change exceeds df. Event-driven time integration is self-adaptive as it makes use of causality rules rather than parametric time dependencies. This technique enables asynchronous flux-conservative update of solution in accordance with local temporal scales, removes the curse of the global CFL condition, eliminates unnecessary computation in inactive spatial regions and results in robust and fast parallelizable codes. It can be naturally combined with various mesh refinement techniques. We discuss applications of this novel technology to diffusion-convection-reaction systems and hybrid simulations of magnetosonic shocks.

Methods for robustness programming

NARCIS (Netherlands)

Olieman, N.J.

2008-01-01

Robustness of an object is defined as the probability that an object will have properties as required. Robustness Programming (RP) is a mathematical approach for Robustness estimation and Robustness optimisation. An example in the context of designing a food product, is finding the best composition

Data-driven strategies for robust forecast of continuous glucose monitoring time-series.

Science.gov (United States)

Fiorini, Samuele; Martini, Chiara; Malpassi, Davide; Cordera, Renzo; Maggi, Davide; Verri, Alessandro; Barla, Annalisa

2017-07-01

Over the past decade, continuous glucose monitoring (CGM) has proven to be a very resourceful tool for diabetes management. To date, CGM devices are employed for both retrospective and online applications. Their use allows to better describe the patients' pathology as well as to achieve a better control of patients' level of glycemia. The analysis of CGM sensor data makes possible to observe a wide range of metrics, such as the glycemic variability during the day or the amount of time spent below or above certain glycemic thresholds. However, due to the high variability of the glycemic signals among sensors and individuals, CGM data analysis is a non-trivial task. Standard signal filtering solutions fall short when an appropriate model personalization is not applied. State-of-the-art data-driven strategies for online CGM forecasting rely upon the use of recursive filters. Each time a new sample is collected, such models need to adjust their parameters in order to predict the next glycemic level. In this paper we aim at demonstrating that the problem of online CGM forecasting can be successfully tackled by personalized machine learning models, that do not need to recursively update their parameters.

HIFU Transducer Characterization Using a Robust Needle Hydrophone

Science.gov (United States)

Howard, Samuel M.; Zanelli, Claudio I.

2007-05-01

A robust needle hydrophone has been developed for HIFU transducer characterization and reported on earlier. After a brief review of the hydrophone design and performance, we demonstrate its use to characterize a 1.5 MHz, 10 cm diameter, F-number 1.5 spherically focused source driven to exceed an intensity of 1400 W/cm2at its focus. Quantitative characterization of this source at high powers is assisted by deconvolving the hydrophone's calibrated frequency response in order to accurately reflect the contribution of harmonics generated by nonlinear propagation in the water testing environment. Results are compared to measurements with a membrane hydrophone at 0.3% duty cycle and to theoretical calculations, using measurements of the field at the source's radiating surface as input to a numerical solution of the KZK equation.

Tradeoff between robustness and elaboration in carotenoid networks produces cycles of avian color diversification.

Science.gov (United States)

Badyaev, Alexander V; Morrison, Erin S; Belloni, Virginia; Sanderson, Michael J

2015-08-20

Resolution of the link between micro- and macroevolution calls for comparing both processes on the same deterministic landscape, such as genomic, metabolic or fitness networks. We apply this perspective to the evolution of carotenoid pigmentation that produces spectacular diversity in avian colors and show that basic structural properties of the underlying carotenoid metabolic network are reflected in global patterns of elaboration and diversification in color displays. Birds color themselves by consuming and metabolizing several dietary carotenoids from the environment. Such fundamental dependency on the most upstream external compounds should intrinsically constrain sustained evolutionary elongation of multi-step metabolic pathways needed for color elaboration unless the metabolic network gains robustness - the ability to synthesize the same carotenoid from an additional dietary starting point. We found that gains and losses of metabolic robustness were associated with evolutionary cycles of elaboration and stasis in expressed carotenoids in birds. Lack of metabolic robustness constrained lineage's metabolic explorations to the immediate biochemical vicinity of their ecologically distinct dietary carotenoids, whereas gains of robustness repeatedly resulted in sustained elongation of metabolic pathways on evolutionary time scales and corresponding color elaboration. The structural link between length and robustness in metabolic pathways may explain periodic convergence of phylogenetically distant and ecologically distinct species in expressed carotenoid pigmentation; account for stasis in carotenoid colors in some ecological lineages; and show how the connectivity of the underlying metabolic network provides a mechanistic link between microevolutionary elaboration and macroevolutionary diversification.

Robustness of Structural Systems

DEFF Research Database (Denmark)

Canisius, T.D.G.; Sørensen, John Dalsgaard; Baker, J.W.

2007-01-01

The importance of robustness as a property of structural systems has been recognised following several structural failures, such as that at Ronan Point in 1968,where the consequenceswere deemed unacceptable relative to the initiating damage. A variety of research efforts in the past decades have...... attempted to quantify aspects of robustness such as redundancy and identify design principles that can improve robustness. This paper outlines the progress of recent work by the Joint Committee on Structural Safety (JCSS) to develop comprehensive guidance on assessing and providing robustness in structural...... systems. Guidance is provided regarding the assessment of robustness in a framework that considers potential hazards to the system, vulnerability of system components, and failure consequences. Several proposed methods for quantifying robustness are reviewed, and guidelines for robust design...

HSV-2-driven increase in the expression of α4β7 correlates with increased susceptibility to vaginal SHIV(SF162P3) infection.

Science.gov (United States)

Goode, Diana; Truong, Rosaline; Villegas, Guillermo; Calenda, Giulia; Guerra-Perez, Natalia; Piatak, Michael; Lifson, Jeffrey D; Blanchard, James; Gettie, Agegnehu; Robbiani, Melissa; Martinelli, Elena

2014-12-01

The availability of highly susceptible HIV target cells that can rapidly reach the mucosal lymphoid tissues may increase the chances of an otherwise rare transmission event to occur. Expression of α4β7 is required for trafficking of immune cells to gut inductive sites where HIV can expand and it is expressed at high level on cells particularly susceptible to HIV infection. We hypothesized that HSV-2 modulates the expression of α4β7 and other homing receptors in the vaginal tissue and that this correlates with the increased risk of HIV acquisition in HSV-2 positive individuals. To test this hypothesis we used an in vivo rhesus macaque (RM) model of HSV-2 vaginal infection and a new ex vivo model of macaque vaginal explants. In vivo we found that HSV-2 latently infected RMs appeared to be more susceptible to vaginal SHIVSF162P3 infection, had higher frequency of α4β7high CD4+ T cells in the vaginal tissue and higher expression of α4β7 and CD11c on vaginal DCs. Similarly, ex vivo HSV-2 infection increased the susceptibility of the vaginal tissue to SHIVSF162P3. HSV-2 infection increased the frequencies of α4β7high CD4+ T cells and this directly correlated with HSV-2 replication. A higher amount of inflammatory cytokines in vaginal fluids of the HSV-2 infected animals was similar to those found in the supernatants of the infected explants. Remarkably, the HSV-2-driven increase in the frequency of α4β7high CD4+ T cells directly correlated with SHIV replication in the HSV-2 infected tissues. Our results suggest that the HSV-2-driven increase in availability of CD4+ T cells and DCs that express high levels of α4β7 is associated with the increase in susceptibility to SHIV due to HSV-2. This may persists in absence of HSV-2 shedding. Hence, higher availability of α4β7 positive HIV target cells in the vaginal tissue may constitute a risk factor for HIV transmission.

HSV-2-driven increase in the expression of α4β7 correlates with increased susceptibility to vaginal SHIV(SF162P3 infection.

Directory of Open Access Journals (Sweden)

Diana Goode

2014-12-01

Full Text Available The availability of highly susceptible HIV target cells that can rapidly reach the mucosal lymphoid tissues may increase the chances of an otherwise rare transmission event to occur. Expression of α4β7 is required for trafficking of immune cells to gut inductive sites where HIV can expand and it is expressed at high level on cells particularly susceptible to HIV infection. We hypothesized that HSV-2 modulates the expression of α4β7 and other homing receptors in the vaginal tissue and that this correlates with the increased risk of HIV acquisition in HSV-2 positive individuals. To test this hypothesis we used an in vivo rhesus macaque (RM model of HSV-2 vaginal infection and a new ex vivo model of macaque vaginal explants. In vivo we found that HSV-2 latently infected RMs appeared to be more susceptible to vaginal SHIVSF162P3 infection, had higher frequency of α4β7high CD4+ T cells in the vaginal tissue and higher expression of α4β7 and CD11c on vaginal DCs. Similarly, ex vivo HSV-2 infection increased the susceptibility of the vaginal tissue to SHIVSF162P3. HSV-2 infection increased the frequencies of α4β7high CD4+ T cells and this directly correlated with HSV-2 replication. A higher amount of inflammatory cytokines in vaginal fluids of the HSV-2 infected animals was similar to those found in the supernatants of the infected explants. Remarkably, the HSV-2-driven increase in the frequency of α4β7high CD4+ T cells directly correlated with SHIV replication in the HSV-2 infected tissues. Our results suggest that the HSV-2-driven increase in availability of CD4+ T cells and DCs that express high levels of α4β7 is associated with the increase in susceptibility to SHIV due to HSV-2. This may persists in absence of HSV-2 shedding. Hence, higher availability of α4β7 positive HIV target cells in the vaginal tissue may constitute a risk factor for HIV transmission.

Robustness in laying hens

NARCIS (Netherlands)

Star, L.

2008-01-01

The aim of the project ‘The genetics of robustness in laying hens’ was to investigate nature and regulation of robustness in laying hens under sub-optimal conditions and the possibility to increase robustness by using animal breeding without loss of production. At the start of the project, a robust

A systematic review of fantasy driven vs. contact driven internet-initiated sexual offences: Discrete or overlapping typologies?

Science.gov (United States)

Broome, Laura Jayne; Izura, Cristina; Lorenzo-Dus, Nuria

2018-05-01

Within the literature individuals who use the internet to facilitate the sexual abuse of a minor are generally classified as being fantasy or contact driven. Classification is based upon the intended location for sexual climax: fantasy driven individuals aim to reach sexual climax online, whereas contact driven individuals target minors to achieve physical sex offline. This review systematically investigates whether there is an empirical basis for the distinction between these two proposed discrete types. Comparison of tactics and behaviour are considered to examine whether the contact vs. fantasy distinction is useful. A two-stage literature selection process, considered against pre-determined inclusion criteria, identified a total of twenty-two studies. As methodological heterogeneity limited the ability to conduct pooled analysis, a narrative synthesis of data employing an interpretive approach was conducted. This showed that the contact and fantasy distinction is ambiguous, given that both groups engage in online behaviours that provide them with online sexual gratification that can also lead to offline contact. Furthermore, no clear pattern of behaviour was found to define contact and fantasy individuals idiosyncratically. The European Online Grooming Project typology is thus proposed as a better representation of this behaviour; intimacy seeking, adaptable and hypersexualized groups. The distinction between these groups focuses primarily on the intensity of the relationship, acknowledging that sexual abuse can occur with or without offline contact. This review also highlights the need for larger, methodologically robust studies that examine the behaviour of online child sexual offenders. Copyright © 2018 Elsevier Ltd. All rights reserved.

Bmi1 Is Required for Hedgehog Pathway-Driven Medulloblastoma Expansion

Directory of Open Access Journals (Sweden)

Lowell Evan Michael

2008-12-01

Full Text Available Inappropriate Hedgehog (Hh signaling underlies development of a subset of medulloblastomas, and tumors with elevated HH signaling activity express the stem cell self-renewal gene BMI1. To test whether Bmi1 is required for Hh-driven medulloblastoma development, we varied Bmi1 gene dosage in transgenic mice expressing an oncogenic Hh effector, SmoA1, driven by a glial fibrillary acidic protein (GFAP promoter. Whereas 100% of SmoA1; Bmi1+/+ or SmoA1;Bmi1+/- mice examined between postnatal (P days 14 and 26 had typical medulloblastomas (N = 29, tumors were not detected in any of the SmoA1;Bmi1-/- animals examined (N = 6. Instead, small ectopic collections of cells were present in the region of greatest tumor load in SmoA1 animals, suggesting that medulloblastomas were initiated but failed to undergo expansion into frank tumors. Cells within these Bmi1-/- lesions expressed SmoA1 but were largely nonproliferative, in contrast to cells in Bmi1+/+ tumors (6.2% vs 81.9% PCNA-positive, respectively. Ectopic cells were negative for the progenitor marker nestin, strongly GFAP-positive, and highly apoptotic, relative to Bmi1+/+ tumor cells (29.6% vs 6.3% TUNEL-positive. The alterations in proliferation and apoptosis in SmoA1;Bmi1-/- ectopic cells are associated with reduced levels of Cyclin D1 and elevated expression of cyclin-dependent kinase inhibitor p19Arf, two inversely regulated downstream targets of Bmi1. These data provide the first demonstration that Bmi1 is required for spontaneous de novo development of a solid tumor arising in the brain, suggest a crucial role for Bmi1-dependent, nestin-expressing progenitor cells in medulloblastoma expansion, and implicate Bmi1 as a key factor required for Hh pathway-driven tumorigenesis.

A Robust Shape Reconstruction Method for Facial Feature Point Detection

Directory of Open Access Journals (Sweden)

Shuqiu Tan

2017-01-01

Full Text Available Facial feature point detection has been receiving great research advances in recent years. Numerous methods have been developed and applied in practical face analysis systems. However, it is still a quite challenging task because of the large variability in expression and gestures and the existence of occlusions in real-world photo shoot. In this paper, we present a robust sparse reconstruction method for the face alignment problems. Instead of a direct regression between the feature space and the shape space, the concept of shape increment reconstruction is introduced. Moreover, a set of coupled overcomplete dictionaries termed the shape increment dictionary and the local appearance dictionary are learned in a regressive manner to select robust features and fit shape increments. Additionally, to make the learned model more generalized, we select the best matched parameter set through extensive validation tests. Experimental results on three public datasets demonstrate that the proposed method achieves a better robustness over the state-of-the-art methods.

Semiconductor lasers driven by self-sustained chaotic electronic oscillators and applications to optical chaos cryptography.

Science.gov (United States)

Kingni, Sifeu Takougang; Mbé, Jimmi Hervé Talla; Woafo, Paul

2012-09-01

In this work, we numerically study the dynamics of vertical cavity surface emitting laser (VCSEL) firstly when it is driven by Chua's oscillator, secondly in case where it is driven by a broad frequency spectral bandwidth chaotic oscillator developed by Nana et al. [Commun. Nonlinear Sci. Numer. Simul. 14, 2266 (2009)]. We demonstrated that the VCSEL generated robust chaotic dynamics compared to the ones found in VCSEL subject to a sinusoidally modulated current and therefore it is more suitable for chaos encryption techniques. The synchronization characteristics and the communication performances of unidirectional coupled VCSEL driven by the broad frequency spectral bandwidth chaotic oscillators are investigated numerically. The results show that high-quality synchronization and transmission of messages can be realized for suitable system parameters. Chaos shift keying method is successfully applied to encrypt a message at a high bitrate.

Global robust exponential stability analysis for interval recurrent neural networks

International Nuclear Information System (INIS)

Xu Shengyuan; Lam, James; Ho, Daniel W.C.; Zou Yun

2004-01-01

This Letter investigates the problem of robust global exponential stability analysis for interval recurrent neural networks (RNNs) via the linear matrix inequality (LMI) approach. The values of the time-invariant uncertain parameters are assumed to be bounded within given compact sets. An improved condition for the existence of a unique equilibrium point and its global exponential stability of RNNs with known parameters is proposed. Based on this, a sufficient condition for the global robust exponential stability for interval RNNs is obtained. Both of the conditions are expressed in terms of LMIs, which can be checked easily by various recently developed convex optimization algorithms. Examples are provided to demonstrate the reduced conservatism of the proposed exponential stability condition

Magnon-driven quantum dot refrigerators

Energy Technology Data Exchange (ETDEWEB)

Wang, Yuan; Huang, Chuankun; Liao, Tianjun; Chen, Jincan, E-mail: jcchen@xmu.edu.cn

2015-12-18

Highlights: • A three-terminal quantum dot refrigerator is proposed. • The effects of magnetic field, applied voltage, and polarization are considered. • The region that the system can work as a refrigerator is determined. • Two different magnon-driven quantum dot refrigerators are compared. - Abstract: A new model of refrigerator consisting of a spin-splitting quantum dot coupled with two ferromagnetic reservoirs and a ferromagnetic insulator is proposed. The rate equation is used to calculate the occupation probabilities of the quantum dot. The expressions of the electron and magnon currents are obtained. The region that the system can work in as a refrigerator is determined. The cooling power and coefficient of performance (COP) of the refrigerator are derived. The influences of the magnetic field, applied voltage, and polarization of two leads on the performance are discussed. The performances of two different magnon-driven quantum dot refrigerators are compared.

FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression data

DEFF Research Database (Denmark)

Manijak, Mieszko P.; Nielsen, Henrik Bjørn

2011-01-01

circumvented by instead matching gene expression signatures to signatures of other experiments. FINDINGS: To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700...... Arabidopsis microarray experiments. CONCLUSIONS: Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/....

Spike propagation in driven chain networks with dominant global inhibition

International Nuclear Information System (INIS)

Chang Wonil; Jin, Dezhe Z.

2009-01-01

Spike propagation in chain networks is usually studied in the synfire regime, in which successive groups of neurons are synaptically activated sequentially through the unidirectional excitatory connections. Here we study the dynamics of chain networks with dominant global feedback inhibition that prevents the synfire activity. Neural activity is driven by suprathreshold external inputs. We analytically and numerically demonstrate that spike propagation along the chain is a unique dynamical attractor in a wide parameter regime. The strong inhibition permits a robust winner-take-all propagation in the case of multiple chains competing via the inhibition.

Robust and sparse correlation matrix estimation for the analysis of high-dimensional genomics data.

Science.gov (United States)

Serra, Angela; Coretto, Pietro; Fratello, Michele; Tagliaferri, Roberto; Stegle, Oliver

2018-02-15

Microarray technology can be used to study the expression of thousands of genes across a number of different experimental conditions, usually hundreds. The underlying principle is that genes sharing similar expression patterns, across different samples, can be part of the same co-expression system, or they may share the same biological functions. Groups of genes are usually identified based on cluster analysis. Clustering methods rely on the similarity matrix between genes. A common choice to measure similarity is to compute the sample correlation matrix. Dimensionality reduction is another popular data analysis task which is also based on covariance/correlation matrix estimates. Unfortunately, covariance/correlation matrix estimation suffers from the intrinsic noise present in high-dimensional data. Sources of noise are: sampling variations, presents of outlying sample units, and the fact that in most cases the number of units is much larger than the number of genes. In this paper, we propose a robust correlation matrix estimator that is regularized based on adaptive thresholding. The resulting method jointly tames the effects of the high-dimensionality, and data contamination. Computations are easy to implement and do not require hand tunings. Both simulated and real data are analyzed. A Monte Carlo experiment shows that the proposed method is capable of remarkable performances. Our correlation metric is more robust to outliers compared with the existing alternatives in two gene expression datasets. It is also shown how the regularization allows to automatically detect and filter spurious correlations. The same regularization is also extended to other less robust correlation measures. Finally, we apply the ARACNE algorithm on the SyNTreN gene expression data. Sensitivity and specificity of the reconstructed network is compared with the gold standard. We show that ARACNE performs better when it takes the proposed correlation matrix estimator as input. The R

Robust facial landmark detection based on initializing multiple poses

Directory of Open Access Journals (Sweden)

Xin Chai

2016-10-01

Full Text Available For robot systems, robust facial landmark detection is the first and critical step for face-based human identification and facial expression recognition. In recent years, the cascaded-regression-based method has achieved excellent performance in facial landmark detection. Nevertheless, it still has certain weakness, such as high sensitivity to the initialization. To address this problem, regression based on multiple initializations is established in a unified model; face shapes are then estimated independently according to these initializations. With a ranking strategy, the best estimate is selected as the final output. Moreover, a face shape model based on restricted Boltzmann machines is built as a constraint to improve the robustness of ranking. Experiments on three challenging datasets demonstrate the effectiveness of the proposed facial landmark detection method against state-of-the-art methods.

Real-time speech-driven animation of expressive talking faces

Science.gov (United States)

Liu, Jia; You, Mingyu; Chen, Chun; Song, Mingli

2011-05-01

In this paper, we present a real-time facial animation system in which speech drives mouth movements and facial expressions synchronously. Considering five basic emotions, a hierarchical structure with an upper layer of emotion classification is established. Based on the recognized emotion label, the under-layer classification at sub-phonemic level has been modelled on the relationship between acoustic features of frames and audio labels in phonemes. Using certain constraint, the predicted emotion labels of speech are adjusted to gain the facial expression labels which are combined with sub-phonemic labels. The combinations are mapped into facial action units (FAUs), and audio-visual synchronized animation with mouth movements and facial expressions is generated by morphing between FAUs. The experimental results demonstrate that the two-layer structure succeeds in both emotion and sub-phonemic classifications, and the synthesized facial sequences reach a comparative convincing quality.

Event-driven simulation of neural population synchronization facilitated by electrical coupling.

Science.gov (United States)

Carrillo, Richard R; Ros, Eduardo; Barbour, Boris; Boucheny, Christian; Coenen, Olivier

2007-02-01

Most neural communication and processing tasks are driven by spikes. This has enabled the application of the event-driven simulation schemes. However the simulation of spiking neural networks based on complex models that cannot be simplified to analytical expressions (requiring numerical calculation) is very time consuming. Here we describe briefly an event-driven simulation scheme that uses pre-calculated table-based neuron characterizations to avoid numerical calculations during a network simulation, allowing the simulation of large-scale neural systems. More concretely we explain how electrical coupling can be simulated efficiently within this computation scheme, reproducing synchronization processes observed in detailed simulations of neural populations.

Full-Angle Quaternions for Robustly Matching Vectors of 3D Rotations

NARCIS (Netherlands)

Liwicki, Stephan; Pham, Minh-Tri; Zafeiriou, Stefanos; Pantic, Maja; Stenger, Björn

In this paper we introduce a new distance for robustly matching vectors of 3D rotations. A special representation of 3D rotations, which we coin full-angle quaternion (FAQ), allows us to express this distance as Euclidean. We apply the distance to the problems of 3D shape recognition from point

RNA-ID, a highly sensitive and robust method to identify cis-regulatory sequences using superfolder GFP and a fluorescence-based assay.

Science.gov (United States)

Dean, Kimberly M; Grayhack, Elizabeth J

2012-12-01

We have developed a robust and sensitive method, called RNA-ID, to screen for cis-regulatory sequences in RNA using fluorescence-activated cell sorting (FACS) of yeast cells bearing a reporter in which expression of both superfolder green fluorescent protein (GFP) and yeast codon-optimized mCherry red fluorescent protein (RFP) is driven by the bidirectional GAL1,10 promoter. This method recapitulates previously reported progressive inhibition of translation mediated by increasing numbers of CGA codon pairs, and restoration of expression by introduction of a tRNA with an anticodon that base pairs exactly with the CGA codon. This method also reproduces effects of paromomycin and context on stop codon read-through. Five key features of this method contribute to its effectiveness as a selection for regulatory sequences: The system exhibits greater than a 250-fold dynamic range, a quantitative and dose-dependent response to known inhibitory sequences, exquisite resolution that allows nearly complete physical separation of distinct populations, and a reproducible signal between different cells transformed with the identical reporter, all of which are coupled with simple methods involving ligation-independent cloning, to create large libraries. Moreover, we provide evidence that there are sequences within a 9-nt library that cause reduced GFP fluorescence, suggesting that there are novel cis-regulatory sequences to be found even in this short sequence space. This method is widely applicable to the study of both RNA-mediated and codon-mediated effects on expression.

Gap-metric-based robustness analysis of nonlinear systems with full and partial feedback linearisation

Science.gov (United States)

Al-Gburi, A.; Freeman, C. T.; French, M. C.

2018-06-01

This paper uses gap metric analysis to derive robustness and performance margins for feedback linearising controllers. Distinct from previous robustness analysis, it incorporates the case of output unstructured uncertainties, and is shown to yield general stability conditions which can be applied to both stable and unstable plants. It then expands on existing feedback linearising control schemes by introducing a more general robust feedback linearising control design which classifies the system nonlinearity into stable and unstable components and cancels only the unstable plant nonlinearities. This is done in order to preserve the stabilising action of the inherently stabilising nonlinearities. Robustness and performance margins are derived for this control scheme, and are expressed in terms of bounds on the plant nonlinearities and the accuracy of the cancellation of the unstable plant nonlinearity by the controller. Case studies then confirm reduced conservatism compared with standard methods.

Robust Growth Determinants

OpenAIRE

Doppelhofer, Gernot; Weeks, Melvyn

2011-01-01

This paper investigates the robustness of determinants of economic growth in the presence of model uncertainty, parameter heterogeneity and outliers. The robust model averaging approach introduced in the paper uses a flexible and parsi- monious mixture modeling that allows for fat-tailed errors compared to the normal benchmark case. Applying robust model averaging to growth determinants, the paper finds that eight out of eighteen variables found to be significantly related to economic growth ...

ErbB2-Driven Breast Cancer Cell Invasion Depends on a Complex Signaling Network Activating Myeloid Zinc Finger-1-Dependent Cathepsin B Expression

DEFF Research Database (Denmark)

Rafn, Bo; Nielsen, Christian Thomas Friberg; Andersen, Sofie Hagel

2012-01-01

Aberrant ErbB2 receptor tyrosine kinase activation in breast cancer is strongly linked to an invasive disease. The molecular basis of ErbB2-driven invasion is largely unknown. We show that cysteine cathepsins B and L are elevated in ErbB2 positive primary human breast cancer and function...... as effectors of ErbB2-induced invasion in vitro. We identify Cdc42-binding protein kinase beta, extracellular regulated kinase 2, p21-activated protein kinase 4, and protein kinase C alpha as essential mediators of ErbB2-induced cysteine cathepsin expression and breast cancer cell invasiveness. The identified...

Quasienergy spectrum and tunneling current in ac-driven triple quantum dot shuttles

Energy Technology Data Exchange (ETDEWEB)

Villavicencio, J [Facultad de Ciencias, Universidad Autonoma de Baja California, Ensenada (Mexico); Maldonado, I [Centro de Investigacion Cientifica y de Educacion Superior de Ensenada (Mexico); Cota, E [Centro de Nanociencias y Nanotecnologia, Universidad Nacional Autonoma de Mexico, Ensenada (Mexico); Platero, G, E-mail: villavics@uabc.edu.mx [Instituto de Ciencia de Materiales de Madrid (CSIC), Cantoblanco, 28049 Madrid (Spain)

2011-02-15

The dynamics of electrons in ac-driven double quantum dots have been extensively analyzed by means of Floquet theory. In these systems, coherent destruction of tunneling has been shown to occur for certain ac field parameters. In this work we analyze, by means of Floquet theory, the electron dynamics of a triple quantum dot in series attached to electric contacts, where the central dot position oscillates. In particular, we analyze the quasienergy spectrum of this ac-driven nanoelectromechanical system as a function of the intensity and frequency of the ac field and of external dc voltages. For strong driving fields, we derive, by means of perturbation theory, analytical expressions for the quasienergies of the driven oscillator system. From this analysis, we discuss the conditions for coherent destruction of tunneling (CDT) to occur as a function of detuning and field parameters. For zero detuning, and from the invariance of the Floquet Hamiltonian under a generalized parity transformation, we find analytical expressions describing the symmetry properties of the Fourier components of the Floquet states under such a transformation. By using these expressions, we show that in the vicinity of the CDT condition, the quasienergy spectrum exhibits exact crossings which can be characterized by the parity properties of the corresponding eigenvectors.

Optimizing the robustness of electrical power systems against cascading failures.

Science.gov (United States)

Zhang, Yingrui; Yağan, Osman

2016-06-21

Electrical power systems are one of the most important infrastructures that support our society. However, their vulnerabilities have raised great concern recently due to several large-scale blackouts around the world. In this paper, we investigate the robustness of power systems against cascading failures initiated by a random attack. This is done under a simple yet useful model based on global and equal redistribution of load upon failures. We provide a comprehensive understanding of system robustness under this model by (i) deriving an expression for the final system size as a function of the size of initial attacks; (ii) deriving the critical attack size after which system breaks down completely; (iii) showing that complete system breakdown takes place through a first-order (i.e., discontinuous) transition in terms of the attack size; and (iv) establishing the optimal load-capacity distribution that maximizes robustness. In particular, we show that robustness is maximized when the difference between the capacity and initial load is the same for all lines; i.e., when all lines have the same redundant space regardless of their initial load. This is in contrast with the intuitive and commonly used setting where capacity of a line is a fixed factor of its initial load.

A biology-driven approach identifies the hypoxia gene signature as a predictor of the outcome of neuroblastoma patients

Directory of Open Access Journals (Sweden)

Fardin Paolo

2010-07-01

Full Text Available Abstract Background Hypoxia is a condition of low oxygen tension occurring in the tumor microenvironment and it is related to poor prognosis in human cancer. To examine the relationship between hypoxia and neuroblastoma, we generated and tested an in vitro derived hypoxia gene signature for its ability to predict patients' outcome. Results We obtained the gene expression profile of 11 hypoxic neuroblastoma cell lines and we derived a robust 62 probesets signature (NB-hypo taking advantage of the strong discriminating power of the l1-l2 feature selection technique combined with the analysis of differential gene expression. We profiled gene expression of the tumors of 88 neuroblastoma patients and divided them according to the NB-hypo expression values by K-means clustering. The NB-hypo successfully stratifies the neuroblastoma patients into good and poor prognosis groups. Multivariate Cox analysis revealed that the NB-hypo is a significant independent predictor after controlling for commonly used risk factors including the amplification of MYCN oncogene. NB-hypo increases the resolution of the MYCN stratification by dividing patients with MYCN not amplified tumors in good and poor outcome suggesting that hypoxia is associated with the aggressiveness of neuroblastoma tumor independently from MYCN amplification. Conclusions Our results demonstrate that the NB-hypo is a novel and independent prognostic factor for neuroblastoma and support the view that hypoxia is negatively correlated with tumors' outcome. We show the power of the biology-driven approach in defining hypoxia as a critical molecular program in neuroblastoma and the potential for improvement in the current criteria for risk stratification.

A Denoising Based Autoassociative Model for Robust Sensor Monitoring in Nuclear Power Plants

Directory of Open Access Journals (Sweden)

Ahmad Shaheryar

2016-01-01

Full Text Available Sensors health monitoring is essentially important for reliable functioning of safety-critical chemical and nuclear power plants. Autoassociative neural network (AANN based empirical sensor models have widely been reported for sensor calibration monitoring. However, such ill-posed data driven models may result in poor generalization and robustness. To address above-mentioned issues, several regularization heuristics such as training with jitter, weight decay, and cross-validation are suggested in literature. Apart from these regularization heuristics, traditional error gradient based supervised learning algorithms for multilayered AANN models are highly susceptible of being trapped in local optimum. In order to address poor regularization and robust learning issues, here, we propose a denoised autoassociative sensor model (DAASM based on deep learning framework. Proposed DAASM model comprises multiple hidden layers which are pretrained greedily in an unsupervised fashion under denoising autoencoder architecture. In order to improve robustness, dropout heuristic and domain specific data corruption processes are exercised during unsupervised pretraining phase. The proposed sensor model is trained and tested on sensor data from a PWR type nuclear power plant. Accuracy, autosensitivity, spillover, and sequential probability ratio test (SPRT based fault detectability metrics are used for performance assessment and comparison with extensively reported five-layer AANN model by Kramer.

A high level of liver-specific expression of oncogenic KrasV12 drives robust liver tumorigenesis in transgenic zebrafish

Directory of Open Access Journals (Sweden)

Anh Tuan Nguyen

2011-11-01

Human liver cancer is one of the deadliest cancers worldwide, with hepatocellular carcinoma (HCC being the most common type. Aberrant Ras signaling has been implicated in the development and progression of human HCC, but a complete understanding of the molecular mechanisms of this protein in hepatocarcinogenesis remains elusive. In this study, a stable in vivo liver cancer model using transgenic zebrafish was generated to elucidate Ras-driven tumorigenesis in HCC. Using the liver-specific fabp10 (fatty acid binding protein 10 promoter, we overexpressed oncogenic krasV12 specifically in the transgenic zebrafish liver. Only a high level of krasV12 expression initiated liver tumorigenesis, which progressed from hyperplasia to benign and malignant tumors with activation of the Ras-Raf-MEK-ERK and Wnt–β-catenin pathways. Histological diagnosis of zebrafish tumors identified HCC as the main lesion. The tumors were invasive and transplantable, indicating malignancy of these HCC cells. Oncogenic krasV12 was also found to trigger p53-dependent senescence as a tumor suppressive barrier in the pre-neoplastic stage. Microarray analysis of zebrafish liver hyperplasia and HCC uncovered the deregulation of several stage-specific and common biological processes and signaling pathways responsible for krasV12-driven liver tumorigenesis that recapitulated the molecular hallmarks of human liver cancer. Cross-species comparisons of cancer transcriptomes further defined a HCC-specific gene signature as well as a liver cancer progression gene signature that are evolutionarily conserved between human and zebrafish. Collectively, our study presents a comprehensive portrait of molecular mechanisms during progressive Ras-induced HCC. These observations indicate the validity of our transgenic zebrafish to model human liver cancer, and this model might act as a useful platform for drug screening and identifying new therapeutic targets.

An adenoviral vector expressing lipoprotein A, a major antigen of Mycoplasma mycoides subspecies mycoides, elicits robust immune responses in mice.

Science.gov (United States)

Carozza, Marlène; Rodrigues, Valérie; Unterfinger, Yves; Galea, Sandra; Coulpier, Muriel; Klonjkowski, Bernard; Thiaucourt, François; Totté, Philippe; Richardson, Jennifer

2015-01-01

Contagious bovine pleuropneumonia (CBPP), caused by Mycoplasma mycoides subsp. mycoides small colony type (MmmSC), is a devastating respiratory disease of cattle. In sub-Saharan Africa, where CBPP is enzootic, live attenuated vaccines are deployed but afford only short-lived protection. In cattle, recovery from experimental MmmSC infection has been associated with the presence of CD4(+) T lymphocytes that secrete interferon gamma in response to MmmSC, and in particular to the lipoprotein A (LppA) antigen. In an effort to develop a better vaccine against CBPP, a viral vector (Ad5-LppA) that expressed LppA was generated from human adenovirus type 5. The LppA-specific immune responses elicited by the Ad5-LppA vector were evaluated in mice, and compared to those elicited by recombinant LppA formulated with a potent adjuvant. Notably, a single administration of Ad5-LppA, but not recombinant protein, sufficed to elicit a robust LppA-specific humoral response. After a booster administration, both vector and recombinant protein elicited strong LppA-specific humoral and cell-mediated responses. Ex vivo stimulation of splenocytes induced extensive proliferation of CD4(+) T cells for mice immunized with vector or protein, and secretion of T helper 1-associated and proinflammatory cytokines for mice immunized with Ad5-LppA. Our study - by demonstrating the potential of a viral-vectored prototypic vaccine to elicit prompt and robust immune responses against a major antigen of MmmSC - represents a first step in developing a recombinant vaccine against CBPP. Copyright © 2014 Elsevier Ltd. All rights reserved.

Robustness of structures

DEFF Research Database (Denmark)

Vrouwenvelder, T.; Sørensen, John Dalsgaard

2009-01-01

After the collapse of the World Trade Centre towers in 2001 and a number of collapses of structural systems in the beginning of the century, robustness of structural systems has gained renewed interest. Despite many significant theoretical, methodical and technological advances, structural...... of robustness for structural design such requirements are not substantiated in more detail, nor have the engineering profession been able to agree on an interpretation of robustness which facilitates for its uantification. A European COST action TU 601 on ‘Robustness of structures' has started in 2007...... by a group of members of the CSS. This paper describes the ongoing work in this action, with emphasis on the development of a theoretical and risk based quantification and optimization procedure on the one side and a practical pre-normative guideline on the other....

LASNEX simulations of the classical and laser-driven Rayleigh-Taylor instability

International Nuclear Information System (INIS)

Mikaelian, K.O.

1990-01-01

We present the results of two-dimensional LASNEX simulations of the classical and laser-driven Rayleigh-Taylor instability. Our growth rates and eigenmodes for classical two- and three-fluid problems agree closely with the exact analytic expressions. We illustrate in several examples how perturbations feed through from one interface to another. For targets driven by a 1/4-μm laser at I=2x10 14 W/cm 2 our growth rates are 40--80 % of the classical case rates for wavelengths between 5 and 100 μm. We find that radiation transport has a stabilizing effect on the Rayleigh-Taylor instability, particularly at high intensities. A brief comparison with a laser-driven experiment is also presented

Robust Identification of Developmentally Active Endothelial Enhancers in Zebrafish Using FANS-Assisted ATAC-Seq.

Science.gov (United States)

Quillien, Aurelie; Abdalla, Mary; Yu, Jun; Ou, Jianhong; Zhu, Lihua Julie; Lawson, Nathan D

2017-07-18

Identification of tissue-specific and developmentally active enhancers provides insights into mechanisms that control gene expression during embryogenesis. However, robust detection of these regulatory elements remains challenging, especially in vertebrate genomes. Here, we apply fluorescent-activated nuclei sorting (FANS) followed by Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) to identify developmentally active endothelial enhancers in the zebrafish genome. ATAC-seq of nuclei from Tg(fli1a:egfp) y1 transgenic embryos revealed expected patterns of nucleosomal positioning at transcriptional start sites throughout the genome and association with active histone modifications. Comparison of ATAC-seq from GFP-positive and -negative nuclei identified more than 5,000 open elements specific to endothelial cells. These elements flanked genes functionally important for vascular development and that displayed endothelial-specific gene expression. Importantly, a majority of tested elements drove endothelial gene expression in zebrafish embryos. Thus, FANS-assisted ATAC-seq using transgenic zebrafish embryos provides a robust approach for genome-wide identification of active tissue-specific enhancer elements. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Generation of anti-TLR2 intrabody mediating inhibition of macrophage surface TLR2 expression and TLR2-driven cell activation.

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Kirschning, Carsten J; Dreher, Stefan; Maass, Björn; Fichte, Sylvia; Schade, Jutta; Köster, Mario; Noack, Andreas; Lindenmaier, Werner; Wagner, Hermann; Böldicke, Thomas

2010-04-13

Toll-like receptor (TLR) 2 is a component of the innate immune system and senses specific pathogen associated molecular patterns (PAMPs) of both microbial and viral origin. Cell activation via TLR2 and other pattern recognition receptors (PRRs) contributes to sepsis pathology and chronic inflammation both relying on overamplification of an immune response. Intracellular antibodies expressed and retained inside the endoplasmatic reticulum (ER-intrabodies) are applied to block translocation of secreted and cell surface molecules from the ER to the cell surface resulting in functional inhibition of the target protein. Here we describe generation and application of a functional anti-TLR2 ER intrabody (alphaT2ib) which was generated from an antagonistic monoclonal antibody (mAb) towards human and murine TLR2 (T2.5) to inhibit the function of TLR2. alphaT2ib is a scFv fragment comprising the variable domain of the heavy chain and the variable domain of the light chain of mAb T2.5 linked together by a synthetic (Gly4Ser)3 amino acid sequence. Coexpression of alphaT2ib and mouse TLR2 in HEK293 cells led to efficient retention and accumulation of TLR2 inside the ER compartment. Co-immunoprecipitation of human TLR2 with alphaT2ib indicated interaction of alphaT2ib with its cognate antigen within cells. alphaT2ib inhibited NF-kappaB driven reporter gene activation via TLR2 but not through TLR3, TLR4, or TLR9 if coexpressed in HEK293 cells. Co-transfection of human TLR2 with increasing amounts of the expression plasmid encoding alphaT2ib into HEK293 cells demonstrated high efficiency of the TLR2-alphaT2ib interaction. The alphaT2ib open reading frame was integrated into an adenoviral cosmid vector for production of recombinant adenovirus (AdV)-alphaT2ib. Transduction with AdValphaT2ib specifically inhibited TLR2 surface expression of murine RAW264.7 and primary macrophages derived from bone marrow (BMM). Furthermore, TLR2 activation dependent TNFalpha mRNA accumulation, as

Data-Driven Anomaly Detection Performance for the Ares I-X Ground Diagnostic Prototype

Science.gov (United States)

Martin, Rodney A.; Schwabacher, Mark A.; Matthews, Bryan L.

2010-01-01

In this paper, we will assess the performance of a data-driven anomaly detection algorithm, the Inductive Monitoring System (IMS), which can be used to detect simulated Thrust Vector Control (TVC) system failures. However, the ability of IMS to detect these failures in a true operational setting may be related to the realistic nature of how they are simulated. As such, we will investigate both a low fidelity and high fidelity approach to simulating such failures, with the latter based upon the underlying physics. Furthermore, the ability of IMS to detect anomalies that were previously unknown and not previously simulated will be studied in earnest, as well as apparent deficiencies or misapplications that result from using the data-driven paradigm. Our conclusions indicate that robust detection performance of simulated failures using IMS is not appreciably affected by the use of a high fidelity simulation. However, we have found that the inclusion of a data-driven algorithm such as IMS into a suite of deployable health management technologies does add significant value.

Robustness of Structures

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

2008-01-01

This paper describes the background of the robustness requirements implemented in the Danish Code of Practice for Safety of Structures and in the Danish National Annex to the Eurocode 0, see (DS-INF 146, 2003), (DS 409, 2006), (EN 1990 DK NA, 2007) and (Sørensen and Christensen, 2006). More...... frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of new structures essential....... According to Danish design rules robustness shall be documented for all structures in high consequence class. The design procedure to document sufficient robustness consists of: 1) Review of loads and possible failure modes / scenarios and determination of acceptable collapse extent; 2) Review...

Dynamics robustness of cascading systems.

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Jonathan T Young

2017-03-01

Full Text Available A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade's kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1 Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2 Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it

A study on facial expressions recognition

Science.gov (United States)

Xu, Jingjing

2017-09-01

In terms of communication, postures and facial expressions of such feelings like happiness, anger and sadness play important roles in conveying information. With the development of the technology, recently a number of algorithms dealing with face alignment, face landmark detection, classification, facial landmark localization and pose estimation have been put forward. However, there are a lot of challenges and problems need to be fixed. In this paper, a few technologies have been concluded and analyzed, and they all relate to handling facial expressions recognition and poses like pose-indexed based multi-view method for face alignment, robust facial landmark detection under significant head pose and occlusion, partitioning the input domain for classification, robust statistics face formalization.

Robust and distributed hypothesis testing

CERN Document Server

Gül, Gökhan

2017-01-01

This book generalizes and extends the available theory in robust and decentralized hypothesis testing. In particular, it presents a robust test for modeling errors which is independent from the assumptions that a sufficiently large number of samples is available, and that the distance is the KL-divergence. Here, the distance can be chosen from a much general model, which includes the KL-divergence as a very special case. This is then extended by various means. A minimax robust test that is robust against both outliers as well as modeling errors is presented. Minimax robustness properties of the given tests are also explicitly proven for fixed sample size and sequential probability ratio tests. The theory of robust detection is extended to robust estimation and the theory of robust distributed detection is extended to classes of distributions, which are not necessarily stochastically bounded. It is shown that the quantization functions for the decision rules can also be chosen as non-monotone. Finally, the boo...

Robustness Property of Robust-BD Wald-Type Test for Varying-Dimensional General Linear Models

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Xiao Guo

2018-03-01

Full Text Available An important issue for robust inference is to examine the stability of the asymptotic level and power of the test statistic in the presence of contaminated data. Most existing results are derived in finite-dimensional settings with some particular choices of loss functions. This paper re-examines this issue by allowing for a diverging number of parameters combined with a broader array of robust error measures, called “robust- BD ”, for the class of “general linear models”. Under regularity conditions, we derive the influence function of the robust- BD parameter estimator and demonstrate that the robust- BD Wald-type test enjoys the robustness of validity and efficiency asymptotically. Specifically, the asymptotic level of the test is stable under a small amount of contamination of the null hypothesis, whereas the asymptotic power is large enough under a contaminated distribution in a neighborhood of the contiguous alternatives, thus lending supports to the utility of the proposed robust- BD Wald-type test.

Robust Least-Squares Support Vector Machine With Minimization of Mean and Variance of Modeling Error.

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Lu, Xinjiang; Liu, Wenbo; Zhou, Chuang; Huang, Minghui

2017-06-13

The least-squares support vector machine (LS-SVM) is a popular data-driven modeling method and has been successfully applied to a wide range of applications. However, it has some disadvantages, including being ineffective at handling non-Gaussian noise as well as being sensitive to outliers. In this paper, a robust LS-SVM method is proposed and is shown to have more reliable performance when modeling a nonlinear system under conditions where Gaussian or non-Gaussian noise is present. The construction of a new objective function allows for a reduction of the mean of the modeling error as well as the minimization of its variance, and it does not constrain the mean of the modeling error to zero. This differs from the traditional LS-SVM, which uses a worst-case scenario approach in order to minimize the modeling error and constrains the mean of the modeling error to zero. In doing so, the proposed method takes the modeling error distribution information into consideration and is thus less conservative and more robust in regards to random noise. A solving method is then developed in order to determine the optimal parameters for the proposed robust LS-SVM. An additional analysis indicates that the proposed LS-SVM gives a smaller weight to a large-error training sample and a larger weight to a small-error training sample, and is thus more robust than the traditional LS-SVM. The effectiveness of the proposed robust LS-SVM is demonstrated using both artificial and real life cases.

Robust Fuzzy Control for Fractional-Order Uncertain Hydroturbine Regulating System with Random Disturbances

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Fengjiao Wu

2016-01-01

Full Text Available The robust fuzzy control for fractional-order hydroturbine regulating system is studied in this paper. First, the more practical fractional-order hydroturbine regulating system with uncertain parameters and random disturbances is presented. Then, on the basis of interval matrix theory and fractional-order stability theorem, a fuzzy control method is proposed for fractional-order hydroturbine regulating system, and the stability condition is expressed as a group of linear matrix inequalities. Furthermore, the proposed method has good robustness which can process external random disturbances and uncertain parameters. Finally, the validity and superiority are proved by the numerical simulations.

Affordable non-traditional source data mining for context assessment to improve distributed fusion system robustness

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Bowman, Christopher; Haith, Gary; Steinberg, Alan; Morefield, Charles; Morefield, Michael

2013-05-01

This paper describes methods to affordably improve the robustness of distributed fusion systems by opportunistically leveraging non-traditional data sources. Adaptive methods help find relevant data, create models, and characterize the model quality. These methods also can measure the conformity of this non-traditional data with fusion system products including situation modeling and mission impact prediction. Non-traditional data can improve the quantity, quality, availability, timeliness, and diversity of the baseline fusion system sources and therefore can improve prediction and estimation accuracy and robustness at all levels of fusion. Techniques are described that automatically learn to characterize and search non-traditional contextual data to enable operators integrate the data with the high-level fusion systems and ontologies. These techniques apply the extension of the Data Fusion & Resource Management Dual Node Network (DNN) technical architecture at Level 4. The DNN architecture supports effectively assessment and management of the expanded portfolio of data sources, entities of interest, models, and algorithms including data pattern discovery and context conformity. Affordable model-driven and data-driven data mining methods to discover unknown models from non-traditional and `big data' sources are used to automatically learn entity behaviors and correlations with fusion products, [14 and 15]. This paper describes our context assessment software development, and the demonstration of context assessment of non-traditional data to compare to an intelligence surveillance and reconnaissance fusion product based upon an IED POIs workflow.

Uncovering robust patterns of microRNA co-expression across cancers using Bayesian Relevance Networks.

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Parameswaran Ramachandran

Full Text Available Co-expression networks have long been used as a tool for investigating the molecular circuitry governing biological systems. However, most algorithms for constructing co-expression networks were developed in the microarray era, before high-throughput sequencing-with its unique statistical properties-became the norm for expression measurement. Here we develop Bayesian Relevance Networks, an algorithm that uses Bayesian reasoning about expression levels to account for the differing levels of uncertainty in expression measurements between highly- and lowly-expressed entities, and between samples with different sequencing depths. It combines data from groups of samples (e.g., replicates to estimate group expression levels and confidence ranges. It then computes uncertainty-moderated estimates of cross-group correlations between entities, and uses permutation testing to assess their statistical significance. Using large scale miRNA data from The Cancer Genome Atlas, we show that our Bayesian update of the classical Relevance Networks algorithm provides improved reproducibility in co-expression estimates and lower false discovery rates in the resulting co-expression networks. Software is available at www.perkinslab.ca.

Boundedness and global robust stability analysis of delayed complex-valued neural networks with interval parameter uncertainties.

Science.gov (United States)

Song, Qiankun; Yu, Qinqin; Zhao, Zhenjiang; Liu, Yurong; Alsaadi, Fuad E

2018-07-01

In this paper, the boundedness and robust stability for a class of delayed complex-valued neural networks with interval parameter uncertainties are investigated. By using Homomorphic mapping theorem, Lyapunov method and inequality techniques, sufficient condition to guarantee the boundedness of networks and the existence, uniqueness and global robust stability of equilibrium point is derived for the considered uncertain neural networks. The obtained robust stability criterion is expressed in complex-valued LMI, which can be calculated numerically using YALMIP with solver of SDPT3 in MATLAB. An example with simulations is supplied to show the applicability and advantages of the acquired result. Copyright © 2018 Elsevier Ltd. All rights reserved.

Robust Operation of Tendon-Driven Robot Fingers Using Force and Position-Based Control Laws

Science.gov (United States)

Abdallah, Muhammad E (Inventor); Platt, Jr., Robert J. (Inventor); Reiland, Matthew J (Inventor); Hargrave, Brian (Inventor); Diftler, Myron A (Inventor); Strawser, Philip A (Inventor); Ihrke, Chris A. (Inventor)

2013-01-01

A robotic system includes a tendon-driven finger and a control system. The system controls the finger via a force-based control law when a tension sensor is available, and via a position-based control law when a sensor is not available. Multiple tendons may each have a corresponding sensor. The system selectively injects a compliance value into the position-based control law when only some sensors are available. A control system includes a host machine and a non-transitory computer-readable medium having a control process, which is executed by the host machine to control the finger via the force- or position-based control law. A method for controlling the finger includes determining the availability of a tension sensor(s), and selectively controlling the finger, using the control system, via the force or position-based control law. The position control law allows the control system to resist disturbances while nominally maintaining the initial state of internal tendon tensions.

Robustness Beamforming Algorithms

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Sajad Dehghani

2014-04-01

Full Text Available Adaptive beamforming methods are known to degrade in the presence of steering vector and covariance matrix uncertinity. In this paper, a new approach is presented to robust adaptive minimum variance distortionless response beamforming make robust against both uncertainties in steering vector and covariance matrix. This method minimize a optimization problem that contains a quadratic objective function and a quadratic constraint. The optimization problem is nonconvex but is converted to a convex optimization problem in this paper. It is solved by the interior-point method and optimum weight vector to robust beamforming is achieved.

An inexact two-stage stochastic robust programming for residential micro-grid management-based on random demand

International Nuclear Information System (INIS)

Ji, L.; Niu, D.X.; Huang, G.H.

2014-01-01

In this paper a stochastic robust optimization problem of residential micro-grid energy management is presented. Combined cooling, heating and electricity technology (CCHP) is introduced to satisfy various energy demands. Two-stage programming is utilized to find the optimal installed capacity investment and operation control of CCHP (combined cooling heating and power). Moreover, interval programming and robust stochastic optimization methods are exploited to gain interval robust solutions under different robustness levels which are feasible for uncertain data. The obtained results can help micro-grid managers minimizing the investment and operation cost with lower system failure risk when facing fluctuant energy market and uncertain technology parameters. The different robustness levels reflect the risk preference of micro-grid manager. The proposed approach is applied to residential area energy management in North China. Detailed computational results under different robustness level are presented and analyzed for providing investment decision and operation strategies. - Highlights: • An inexact two-stage stochastic robust programming model for CCHP management. • The energy market and technical parameters uncertainties were considered. • Investment decision, operation cost, and system safety were analyzed. • Uncertainties expressed as discrete intervals and probability distributions

Robust continuous clustering.

Science.gov (United States)

Shah, Sohil Atul; Koltun, Vladlen

2017-09-12

Clustering is a fundamental procedure in the analysis of scientific data. It is used ubiquitously across the sciences. Despite decades of research, existing clustering algorithms have limited effectiveness in high dimensions and often require tuning parameters for different domains and datasets. We present a clustering algorithm that achieves high accuracy across multiple domains and scales efficiently to high dimensions and large datasets. The presented algorithm optimizes a smooth continuous objective, which is based on robust statistics and allows heavily mixed clusters to be untangled. The continuous nature of the objective also allows clustering to be integrated as a module in end-to-end feature learning pipelines. We demonstrate this by extending the algorithm to perform joint clustering and dimensionality reduction by efficiently optimizing a continuous global objective. The presented approach is evaluated on large datasets of faces, hand-written digits, objects, newswire articles, sensor readings from the Space Shuttle, and protein expression levels. Our method achieves high accuracy across all datasets, outperforming the best prior algorithm by a factor of 3 in average rank.

Robust prediction of anti-cancer drug sensitivity and sensitivity-specific biomarker.

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Heewon Park

Full Text Available The personal genomics era has attracted a large amount of attention for anti-cancer therapy by patient-specific analysis. Patient-specific analysis enables discovery of individual genomic characteristics for each patient, and thus we can effectively predict individual genetic risk of disease and perform personalized anti-cancer therapy. Although the existing methods for patient-specific analysis have successfully uncovered crucial biomarkers, their performance takes a sudden turn for the worst in the presence of outliers, since the methods are based on non-robust manners. In practice, clinical and genomic alterations datasets usually contain outliers from various sources (e.g., experiment error, coding error, etc. and the outliers may significantly affect the result of patient-specific analysis. We propose a robust methodology for patient-specific analysis in line with the NetwrokProfiler. In the proposed method, outliers in high dimensional gene expression levels and drug response datasets are simultaneously controlled by robust Mahalanobis distance in robust principal component space. Thus, we can effectively perform for predicting anti-cancer drug sensitivity and identifying sensitivity-specific biomarkers for individual patients. We observe through Monte Carlo simulations that the proposed robust method produces outstanding performances for predicting response variable in the presence of outliers. We also apply the proposed methodology to the Sanger dataset in order to uncover cancer biomarkers and predict anti-cancer drug sensitivity, and show the effectiveness of our method.

Bmi1 is required for hedgehog pathway-driven medulloblastoma expansion

NARCIS (Netherlands)

Michael, Lowell Evan; Westerman, Bart A.; Ermilov, Alexandre N.; Wang, Aiqin; Ferris, Jennifer; Liu, Jianhong; Blom, Marleen; Ellison, David W.; van Lohuizen, Maarten; Dlugosz, Andrzej A.

2008-01-01

Inappropriate Hedgehog (Hh) signaling underlies development of a subset of medulloblastomas, and tumors with elevated HH signaling activity express the stem cell self-renewal gene BMI1. To test whether Bmi1 is required for Hh-driven medulloblastoma development, we varied Bmi1 gene dosage in

The change of expression configuration affects identity-dependent expression aftereffect but not identity-independent expression aftereffect

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Miao eSong

2015-12-01

Full Text Available The present study examined the influence of expression configuration on cross-identity expression aftereffect. The expression configuration refers to the spatial arrangement of facial features in a face for conveying an emotion, e.g., an open-mouth smile versus a closed-mouth smile. In the first of two experiments, the expression aftereffect is measured using across-identity/cross-expression configuration factorial design. The facial identities of test faces were the same or different from the adaptor, while orthogonally, the expression configurations of those facial identities were also the same or different. The result shows that the change of expression configuration impaired the expression aftereffect when the facial identities of adaptor and tests were the same; however, the impairment effect disappears when facial identities were different, indicating the identity-independent expression representation is more robust to the change of the expression configuration in comparison with the identity-dependent expression representation. In the second experiment, we used schematic line faces as adaptors and real faces as tests to minimize the similarity between the adaptor and tests, which is expected to exclude the contribution from the identity-dependent expression representation to expression aftereffect. The second experiment yields a similar result as the identity-independent expression aftereffect observed in Experiment 1. The findings indicate the different neural sensitivities to expression configuration for identity-dependent and identity-independent expression systems.

Thy-1 attenuates TNF-alpha-activated gene expression in mouse embryonic fibroblasts via Src family kinase.

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Bin Shan

Full Text Available Heterogeneous surface expression of Thy-1 in fibroblasts modulates inflammation and may thereby modulate injury and repair. As a paradigm, patients with idiopathic pulmonary fibrosis, a disease with pathologic features of chronic inflammation, demonstrate an absence of Thy-1 immunoreactivity within areas of fibrotic activity (fibroblast foci in contrast to the predominant Thy-1 expressing fibroblasts in the normal lung. Likewise, Thy-1 deficient mice display more severe lung fibrosis in response to an inflammatory injury than wildtype littermates. We investigated the role of Thy-1 in the response of fibroblasts to the pro-inflammatory cytokine TNF-alpha. Our study demonstrates distinct profiles of TNF-alpha-activated gene expression in Thy-1 positive (Thy-1+ and negative (Thy-1- subsets of mouse embryonic fibroblasts (MEF. TNF-alpha induced a robust activation of MMP-9, ICAM-1, and the IL-8 promoter driven reporter in Thy-1- MEFs, in contrast to only a modest increase in Thy-1+ counterparts. Consistently, ectopic expression of Thy-1 in Thy-1- MEFs significantly attenuated TNF-alpha-activated gene expression. Mechanistically, TNF-alpha activated Src family kinase (SFK only in Thy-1- MEFs. Blockade of SFK activation abrogated TNF-alpha-activated gene expression in Thy-1- MEFs, whereas restoration of SFK activation rescued the TNF-alpha response in Thy-1+ MEFs. Our findings suggest that Thy-1 down-regulates TNF-alpha-activated gene expression via interfering with SFK- and NF-kappaB-mediated transactivation. The current study provides a novel mechanistic insight to the distinct roles of fibroblast Thy-1 subsets in inflammation.

A laser pointer driven microheater for precise local heating and conditional gene regulation in vivo. Microheater driven gene regulation in zebrafish

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Achermann Marc

2009-12-01

Full Text Available Abstract Background Tissue heating has been employed to study a variety of biological processes, including the study of genes that control embryonic development. Conditional regulation of gene expression is a particularly powerful approach for understanding gene function. One popular method for mis-expressing a gene of interest employs heat-inducible heat shock protein (hsp promoters. Global heat shock of hsp-promoter-containing transgenic animals induces gene expression throughout all tissues, but does not allow for spatial control. Local heating allows for spatial control of hsp-promoter-driven transgenes, but methods for local heating are cumbersome and variably effective. Results We describe a simple, highly controllable, and versatile apparatus for heating biological tissue and other materials on the micron-scale. This microheater employs micron-scale fiber optics and uses an inexpensive laser-pointer as a power source. Optical fibers can be pulled on a standard electrode puller to produce tips of varying sizes that can then be used to reliably heat 20-100 μm targets. We demonstrate precise spatiotemporal control of hsp70l:GFP transgene expression in a variety of tissue types in zebrafish embryos and larvae. We also show how this system can be employed as part of a new method for lineage tracing that would greatly facilitate the study of organogenesis and tissue regulation at any time in the life cycle. Conclusion This versatile and simple local heater has broad utility for the study of gene function and for lineage tracing. This system could be used to control hsp-driven gene expression in any organism simply by bringing the fiber optic tip in contact with the tissue of interest. Beyond these uses for the study of gene function, this device has wide-ranging utility in materials science and could easily be adapted for therapeutic purposes in humans.

Robustness Analyses of Timber Structures

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Hald, Frederik

2013-01-01

The robustness of structural systems has obtained a renewed interest arising from a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures, many mo...... with respect to robustness of timber structures and will discuss the consequences of such robustness issues related to the future development of timber structures.......The robustness of structural systems has obtained a renewed interest arising from a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures, many...... modern building codes consider the need for the robustness of structures and provide strategies and methods to obtain robustness. Therefore, a structural engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper summaries issues...

Robust output synchronization of heterogeneous nonlinear agents in uncertain networks.

Science.gov (United States)

Yang, Xi; Wan, Fuhua; Tu, Mengchuan; Shen, Guojiang

2017-11-01

This paper investigates the global robust output synchronization problem for a class of nonlinear multi-agent systems. In the considered setup, the controlled agents are heterogeneous and with both dynamic and parametric uncertainties, the controllers are incapable of exchanging their internal states with the neighbors, and the communication network among agents is defined by an uncertain simple digraph. The problem is pursued via nonlinear output regulation theory and internal model based design. For each agent, the input-driven filter and the internal model compose the controller, and the decentralized dynamic output feedback control law is derived by using backstepping method and the modified dynamic high-gain technique. The theoretical result is applied to output synchronization problem for uncertain network of Lorenz-type agents. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Automated robust registration of grossly misregistered whole-slide images with varying stains

Science.gov (United States)

Litjens, G.; Safferling, K.; Grabe, N.

2016-03-01

Cancer diagnosis and pharmaceutical research increasingly depend on the accurate quantification of cancer biomarkers. Identification of biomarkers is usually performed through immunohistochemical staining of cancer sections on glass slides. However, combination of multiple biomarkers from a wide variety of immunohistochemically stained slides is a tedious process in traditional histopathology due to the switching of glass slides and re-identification of regions of interest by pathologists. Digital pathology now allows us to apply image registration algorithms to digitized whole-slides to align the differing immunohistochemical stains automatically. However, registration algorithms need to be robust to changes in color due to differing stains and severe changes in tissue content between slides. In this work we developed a robust registration methodology to allow for fast coarse alignment of multiple immunohistochemical stains to the base hematyoxylin and eosin stained image. We applied HSD color model conversion to obtain a less stain color dependent representation of the whole-slide images. Subsequently, optical density thresholding and connected component analysis were used to identify the relevant regions for registration. Template matching using normalized mutual information was applied to provide initial translation and rotation parameters, after which a cost function-driven affine registration was performed. The algorithm was validated using 40 slides from 10 prostate cancer patients, with landmark registration error as a metric. Median landmark registration error was around 180 microns, which indicates performance is adequate for practical application. None of the registrations failed, indicating the robustness of the algorithm.

Experiments with a pressure-driven Stirling refrigerator with flexible chambers

Science.gov (United States)

McFarlane, Patrick; Suire, Jonathan; Sen, Mihir; Semperlotti, Fabio

2014-06-01

We report on the design and experimental testing of a Stirling refrigerator that uses air as the working fluid, and where the conventional piston-cylinder assemblies are replaced by pressure-driven flexible chambers. The two chambers are periodically compressed by pneumatic actuators resulting in airflow through the regenerator and in a net temperature difference between the chambers. An experimental setup is used to investigate the performance of the refrigerator under different operating conditions with particular attention to actuation frequencies, driving pressure differences, and phase angles between the two inputs. The time constant of the temperature difference between the two chambers is determined, and the temperature difference is measured as a function of the system parameters. The results of several tests conducted under different operating conditions show that the refrigerating effect is very robust and allows good performance even for modulated inputs. The frequency response is radically different from that of a traditional motion-driven device. This work suggests that mechanical to thermal energy conversion devices based on this principle can be successfully powered by human motion.

0-d energetics scaling models for Z-pinch-driven hohlraums

International Nuclear Information System (INIS)

CUNEO, MICHAEL E.; VESEY, ROGER A.; HAMMER, J.H.; PORTER, JOHN L.

2000-01-01

Wire array Z-pinches on the Z accelerator provide the most intense laboratory source of soft x-rays in the world. The unique combination of a highly-Planckian radiation source with high x-ray production efficiency (15% wall plug), large x-ray powers and energies ( >150 TW, ge1 MJ in 7 ns), large characteristic hohlraum volumes (0.5 to >10 cm 3 ), and long pulse-lengths (5 to 20 ns) may make Z-pinches a good match to the requirements for driving high-yield scale ICF capsules with adequate radiation symmetry and margin. The Z-pinch driven hohlraum approach of Hammer and Porter [Phys.Plasmas, 6, 2129(1999)] may provide a conservative and robust solution to the requirements for high yield, and is currently being studied on the Z accelerator. This paper describes a multiple region, 0-d hohlraum energetic model for Z-pinch driven hohlraums in four configurations. The authors observe consistency between the models and the measured x-ray powers and hohlraum wall temperatures to within ±20% in flux, for the four configurations

Robust assignment of cancer subtypes from expression data using a uni-variate gene expression average as classifier

International Nuclear Information System (INIS)

Lauss, Martin; Frigyesi, Attila; Ryden, Tobias; Höglund, Mattias

2010-01-01

Genome wide gene expression data is a rich source for the identification of gene signatures suitable for clinical purposes and a number of statistical algorithms have been described for both identification and evaluation of such signatures. Some employed algorithms are fairly complex and hence sensitive to over-fitting whereas others are more simple and straight forward. Here we present a new type of simple algorithm based on ROC analysis and the use of metagenes that we believe will be a good complement to existing algorithms. The basis for the proposed approach is the use of metagenes, instead of collections of individual genes, and a feature selection using AUC values obtained by ROC analysis. Each gene in a data set is assigned an AUC value relative to the tumor class under investigation and the genes are ranked according to these values. Metagenes are then formed by calculating the mean expression level for an increasing number of ranked genes, and the metagene expression value that optimally discriminates tumor classes in the training set is used for classification of new samples. The performance of the metagene is then evaluated using LOOCV and balanced accuracies. We show that the simple uni-variate gene expression average algorithm performs as well as several alternative algorithms such as discriminant analysis and the more complex approaches such as SVM and neural networks. The R package rocc is freely available at http://cran.r-project.org/web/packages/rocc/index.html

Generation of anti-TLR2 intrabody mediating inhibition of macrophage surface TLR2 expression and TLR2-driven cell activation

Directory of Open Access Journals (Sweden)

Lindenmaier Werner

2010-04-01

Full Text Available Abstract Background Toll-like receptor (TLR 2 is a component of the innate immune system and senses specific pathogen associated molecular patterns (PAMPs of both microbial and viral origin. Cell activation via TLR2 and other pattern recognition receptors (PRRs contributes to sepsis pathology and chronic inflammation both relying on overamplification of an immune response. Intracellular antibodies expressed and retained inside the endoplasmatic reticulum (ER-intrabodies are applied to block translocation of secreted and cell surface molecules from the ER to the cell surface resulting in functional inhibition of the target protein. Here we describe generation and application of a functional anti-TLR2 ER intrabody (αT2ib which was generated from an antagonistic monoclonal antibody (mAb towards human and murine TLR2 (T2.5 to inhibit the function of TLR2. αT2ib is a scFv fragment comprising the variable domain of the heavy chain and the variable domain of the light chain of mAb T2.5 linked together by a synthetic (Gly4Ser3 amino acid sequence. Results Coexpression of αT2ib and mouse TLR2 in HEK293 cells led to efficient retention and accumulation of TLR2 inside the ER compartment. Co-immunoprecipitation of human TLR2 with αT2ib indicated interaction of αT2ib with its cognate antigen within cells. αT2ib inhibited NF-κB driven reporter gene activation via TLR2 but not through TLR3, TLR4, or TLR9 if coexpressed in HEK293 cells. Co-transfection of human TLR2 with increasing amounts of the expression plasmid encoding αT2ib into HEK293 cells demonstrated high efficiency of the TLR2-αT2ib interaction. The αT2ib open reading frame was integrated into an adenoviral cosmid vector for production of recombinant adenovirus (AdV-αT2ib. Transduction with AdVαT2ib specifically inhibited TLR2 surface expression of murine RAW264.7 and primary macrophages derived from bone marrow (BMM. Furthermore, TLR2 activation dependent TNFα mRNA accumulation, as well

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

Science.gov (United States)

Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

2015-01-01

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

Robust and accurate vectorization of line drawings.

Science.gov (United States)

Hilaire, Xavier; Tombre, Karl

2006-06-01

This paper presents a method for vectorizing the graphical parts of paper-based line drawings. The method consists of separating the input binary image into layers of homogeneous thickness, skeletonizing each layer, segmenting the skeleton by a method based on random sampling, and simplifying the result. The segmentation method is robust with a best bound of 50 percent noise reached for indefinitely long primitives. Accurate estimation of the recognized vector's parameters is enabled by explicitly computing their feasibility domains. Theoretical performance analysis and expression of the complexity of the segmentation method are derived. Experimental results and comparisons with other vectorization systems are also provided.

International Conference on Robust Statistics

CERN Document Server

Filzmoser, Peter; Gather, Ursula; Rousseeuw, Peter

2003-01-01

Aspects of Robust Statistics are important in many areas. Based on the International Conference on Robust Statistics 2001 (ICORS 2001) in Vorau, Austria, this volume discusses future directions of the discipline, bringing together leading scientists, experienced researchers and practitioners, as well as younger researchers. The papers cover a multitude of different aspects of Robust Statistics. For instance, the fundamental problem of data summary (weights of evidence) is considered and its robustness properties are studied. Further theoretical subjects include e.g.: robust methods for skewness, time series, longitudinal data, multivariate methods, and tests. Some papers deal with computational aspects and algorithms. Finally, the aspects of application and programming tools complete the volume.

Data-driven robust control of the plasma rotational transform profile and normalized beta dynamics for advanced tokamak scenarios in DIII-D

Energy Technology Data Exchange (ETDEWEB)

Shi, W.; Wehner, W.P.; Barton, J.E.; Boyer, M.D. [Mechanical Engineering and Mechanics, Lehigh University, Bethlehem, PA 18015 (United States); Schuster, E., E-mail: schuster@lehigh.edu [Mechanical Engineering and Mechanics, Lehigh University, Bethlehem, PA 18015 (United States); Moreau, D. [CEA, IRFM, F-13018 St Paul lez Durance (France); Walker, M.L.; Ferron, J.R.; Luce, T.C.; Humphreys, D.A.; Penaflor, B.G.; Johnson, R.D. [General Atomics, San Diego, CA 92121 (United States)

2017-04-15

A control-oriented, two-timescale, linear, dynamic, response model of the rotational transform ι profile and the normalized beta β{sub N} is proposed based on experimental data from the DIII-D tokamak. Dedicated system-identification experiments without feedback control have been carried out to generate data for the development of this model. The data-driven dynamic model, which is both device-specific and scenario-specific, represents the response of the ι profile and β{sub N} to the electric field due to induction as well as to the heating and current drive (H&CD) systems during the flat-top phase of an H-mode discharge in DIII-D. The control goal is to use both induction and the H&CD systems to locally regulate the plasma ι profile and β{sub N} around particular target values close to the reference state used for system identification. A singular value decomposition (SVD) of the plasma model at steady state is carried out to decouple the system and identify the most relevant control channels. A mixed-sensitivity robust control design problem is formulated based on the dynamic model to synthesize a stabilizing feedback controller without input constraints that minimizes the reference tracking error and rejects external disturbances with minimal control energy. The feedback controller is then augmented with an anti-windup compensator, which keeps the given controller well-behaved in the presence of magnitude constraints in the actuators and leaves the nominal closed-loop system unmodified when no saturation is present. The proposed controller represents one of the first feedback profile controllers integrating magnetic and kinetic variables ever implemented and experimentally tested in DIII-D. The preliminary experimental results presented in this work, although limited in number and constrained by actuator problems and design limitations, as it will be reported, show good progress towards routine current profile control in DIII-D and leave valuable lessons

Robust Scientists

DEFF Research Database (Denmark)

Gorm Hansen, Birgitte

their core i nterests, 2) developing a selfsupply of industry interests by becoming entrepreneurs and thus creating their own compliant industry partner and 3) balancing resources within a larger collective of researchers, thus countering changes in the influx of funding caused by shifts in political...... knowledge", Danish research policy seems to have helped develop politically and economically "robust scientists". Scientific robustness is acquired by way of three strategies: 1) tasting and discriminating between resources so as to avoid funding that erodes academic profiles and push scientists away from...

Early warning of climate tipping points from critical slowing down: comparing methods to improve robustness

Science.gov (United States)

Lenton, T. M.; Livina, V. N.; Dakos, V.; Van Nes, E. H.; Scheffer, M.

2012-01-01

We address whether robust early warning signals can, in principle, be provided before a climate tipping point is reached, focusing on methods that seek to detect critical slowing down as a precursor of bifurcation. As a test bed, six previously analysed datasets are reconsidered, three palaeoclimate records approaching abrupt transitions at the end of the last ice age and three models of varying complexity forced through a collapse of the Atlantic thermohaline circulation. Approaches based on examining the lag-1 autocorrelation function or on detrended fluctuation analysis are applied together and compared. The effects of aggregating the data, detrending method, sliding window length and filtering bandwidth are examined. Robust indicators of critical slowing down are found prior to the abrupt warming event at the end of the Younger Dryas, but the indicators are less clear prior to the Bølling-Allerød warming, or glacial termination in Antarctica. Early warnings of thermohaline circulation collapse can be masked by inter-annual variability driven by atmospheric dynamics. However, rapidly decaying modes can be successfully filtered out by using a long bandwidth or by aggregating data. The two methods have complementary strengths and weaknesses and we recommend applying them together to improve the robustness of early warnings. PMID:22291229

Robust Trust in Expert Testimony

Directory of Open Access Journals (Sweden)

Christian Dahlman

2015-05-01

Full Text Available The standard of proof in criminal trials should require that the evidence presented by the prosecution is robust. This requirement of robustness says that it must be unlikely that additional information would change the probability that the defendant is guilty. Robustness is difficult for a judge to estimate, as it requires the judge to assess the possible effect of information that the he or she does not have. This article is concerned with expert witnesses and proposes a method for reviewing the robustness of expert testimony. According to the proposed method, the robustness of expert testimony is estimated with regard to competence, motivation, external strength, internal strength and relevance. The danger of trusting non-robust expert testimony is illustrated with an analysis of the Thomas Quick Case, a Swedish legal scandal where a patient at a mental institution was wrongfully convicted for eight murders.

Robustness Analysis of Timber Truss Structure

DEFF Research Database (Denmark)

Rajčić, Vlatka; Čizmar, Dean; Kirkegaard, Poul Henning

2010-01-01

The present paper discusses robustness of structures in general and the robustness requirements given in the codes. Robustness of timber structures is also an issues as this is closely related to Working group 3 (Robustness of systems) of the COST E55 project. Finally, an example of a robustness...... evaluation of a widespan timber truss structure is presented. This structure was built few years ago near Zagreb and has a span of 45m. Reliability analysis of the main members and the system is conducted and based on this a robustness analysis is preformed....

Qualitative Robustness in Estimation

Directory of Open Access Journals (Sweden)

Mohammed Nasser

2012-07-01

Full Text Available Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Times New Roman","serif";} Qualitative robustness, influence function, and breakdown point are three main concepts to judge an estimator from the viewpoint of robust estimation. It is important as well as interesting to study relation among them. This article attempts to present the concept of qualitative robustness as forwarded by first proponents and its later development. It illustrates intricacies of qualitative robustness and its relation with consistency, and also tries to remove commonly believed misunderstandings about relation between influence function and qualitative robustness citing some examples from literature and providing a new counter-example. At the end it places a useful finite and a simulated version of   qualitative robustness index (QRI. In order to assess the performance of the proposed measures, we have compared fifteen estimators of correlation coefficient using simulated as well as real data sets.

Robustness in econometrics

CERN Document Server

Sriboonchitta, Songsak; Huynh, Van-Nam

2017-01-01

This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.

Robust Programming by Example

OpenAIRE

Bishop , Matt; Elliott , Chip

2011-01-01

Part 2: WISE 7; International audience; Robust programming lies at the heart of the type of coding called “secure programming”. Yet it is rarely taught in academia. More commonly, the focus is on how to avoid creating well-known vulnerabilities. While important, that misses the point: a well-structured, robust program should anticipate where problems might arise and compensate for them. This paper discusses one view of robust programming and gives an example of how it may be taught.

Robust Reliability or reliable robustness? - Integrated consideration of robustness and reliability aspects

DEFF Research Database (Denmark)

Kemmler, S.; Eifler, Tobias; Bertsche, B.

2015-01-01

products are and vice versa. For a comprehensive understanding and to use existing synergies between both domains, this paper discusses the basic principles of Reliability- and Robust Design theory. The development of a comprehensive model will enable an integrated consideration of both domains...

Augmenting Bag-of-Words: Data-Driven Discovery of Temporal and Structural Information for Activity Recognition

OpenAIRE

Bettadapura, Vinay; Schindler, Grant; Plotz, Thomaz; Essa, Irfan

2015-01-01

We present data-driven techniques to augment Bag of Words (BoW) models, which allow for more robust modeling and recognition of complex long-term activities, especially when the structure and topology of the activities are not known a priori. Our approach specifically addresses the limitations of standard BoW approaches, which fail to represent the underlying temporal and causal information that is inherent in activity streams. In addition, we also propose the use of randomly sampled regular ...

Expression-robust 3D face recognition via weighted sparse representation of multi-scale and multi-component local normal patterns

KAUST Repository

Li, Huibin

2014-06-01

In the theory of differential geometry, surface normal, as a first order surface differential quantity, determines the orientation of a surface at each point and contains informative local surface shape information. To fully exploit this kind of information for 3D face recognition (FR), this paper proposes a novel highly discriminative facial shape descriptor, namely multi-scale and multi-component local normal patterns (MSMC-LNP). Given a normalized facial range image, three components of normal vectors are first estimated, leading to three normal component images. Then, each normal component image is encoded locally to local normal patterns (LNP) on different scales. To utilize spatial information of facial shape, each normal component image is divided into several patches, and their LNP histograms are computed and concatenated according to the facial configuration. Finally, each original facial surface is represented by a set of LNP histograms including both global and local cues. Moreover, to make the proposed solution robust to the variations of facial expressions, we propose to learn the weight of each local patch on a given encoding scale and normal component image. Based on the learned weights and the weighted LNP histograms, we formulate a weighted sparse representation-based classifier (W-SRC). In contrast to the overwhelming majority of 3D FR approaches which were only benchmarked on the FRGC v2.0 database, we carried out extensive experiments on the FRGC v2.0, Bosphorus, BU-3DFE and 3D-TEC databases, thus including 3D face data captured in different scenarios through various sensors and depicting in particular different challenges with respect to facial expressions. The experimental results show that the proposed approach consistently achieves competitive rank-one recognition rates on these databases despite their heterogeneous nature, and thereby demonstrates its effectiveness and its generalizability. © 2014 Elsevier B.V.

Robust PLS approach for KPI-related prediction and diagnosis against outliers and missing data

Science.gov (United States)

Yin, Shen; Wang, Guang; Yang, Xu

2014-07-01

In practical industrial applications, the key performance indicator (KPI)-related prediction and diagnosis are quite important for the product quality and economic benefits. To meet these requirements, many advanced prediction and monitoring approaches have been developed which can be classified into model-based or data-driven techniques. Among these approaches, partial least squares (PLS) is one of the most popular data-driven methods due to its simplicity and easy implementation in large-scale industrial process. As PLS is totally based on the measured process data, the characteristics of the process data are critical for the success of PLS. Outliers and missing values are two common characteristics of the measured data which can severely affect the effectiveness of PLS. To ensure the applicability of PLS in practical industrial applications, this paper introduces a robust version of PLS to deal with outliers and missing values, simultaneously. The effectiveness of the proposed method is finally demonstrated by the application results of the KPI-related prediction and diagnosis on an industrial benchmark of Tennessee Eastman process.

Differential protein expression using proteomics from a crustacean brine shrimp (Artemia sinica) under CO2-driven seawater acidification.

Science.gov (United States)

Chang, Xue-Jiao; Zheng, Chao-Qun; Wang, Yu-Wei; Meng, Chuang; Xie, Xiao-Lu; Liu, Hai-Peng

2016-11-01

Gradually increasing atmospheric CO 2 partial pressure (pCO 2 ) has caused an imbalance in carbonate chemistry and resulted in decreased seawater pH in marine ecosystems, termed seawater acidification. Anthropogenic seawater acidification is postulated to affect the physiology of many marine calcifying organisms. To understand the possible effects of seawater acidification on the proteomic responses of a marine crustacean brine shrimp (Artemia sinica) three groups of cysts were hatched and further raised in seawater at different pH levels (8.2 as control and 7.8 and 7.6 as acidification stress levels according to the predicted levels at the end of this century and next century, respectively) for 1, 7 and 14 days followed by examination of the protein expression changes via two-dimensional gel electrophoresis. Searches of protein databases revealed that 67 differential protein spots were altered due to lower pH level (7.6 and 7.8) stress in comparison to control groups (pH 8.2) by mass spectrometry. Generally, these differentially expressed proteins included the following: 1) metabolic process-related proteins involved in glycolysis and glucogenesis, nucleotide/amino acid/fatty acid metabolism, protein biosynthesis, DNA replication and apoptosis; 2) stress response-related proteins, such as peroxiredoxin, thioredoxin peroxidase, 70-kDa heat shock protein, Na/K ATPase, and ubiquinol-cytochrome c reductase; 3) immune defence-related proteins, such as prophenoloxidase and ferritin; 4) cytoskeletal-related proteins, such as myosin light chain, TCP1 subunit 2, tropomyosin and tubulin alpha chain; and 5) signal transduction-related proteins, such as phospholipase C-like protein, 14-3-3 zeta, translationally controlled tumour protein and RNA binding motif protein. Taken together, these data support the idea that CO 2 -driven seawater acidification may affect protein expression in the crustacean A. sinica and possibly also in other species that feed on brine shrimp in the

V3 spinal neurons establish a robust and balanced locomotor rhythm during walking.

Science.gov (United States)

Zhang, Ying; Narayan, Sujatha; Geiman, Eric; Lanuza, Guillermo M; Velasquez, Tomoko; Shanks, Bayle; Akay, Turgay; Dyck, Jason; Pearson, Keir; Gosgnach, Simon; Fan, Chen-Ming; Goulding, Martyn

2008-10-09

A robust and well-organized rhythm is a key feature of many neuronal networks, including those that regulate essential behaviors such as circadian rhythmogenesis, breathing, and locomotion. Here we show that excitatory V3-derived neurons are necessary for a robust and organized locomotor rhythm during walking. When V3-mediated neurotransmission is selectively blocked by the expression of the tetanus toxin light chain subunit (TeNT), the regularity and robustness of the locomotor rhythm is severely perturbed. A similar degeneration in the locomotor rhythm occurs when the excitability of V3-derived neurons is reduced acutely by ligand-induced activation of the allatostatin receptor. The V3-derived neurons additionally function to balance the locomotor output between both halves of the spinal cord, thereby ensuring a symmetrical pattern of locomotor activity during walking. We propose that the V3 neurons establish a regular and balanced motor rhythm by distributing excitatory drive between both halves of the spinal cord.

Fault diagnosis of locomotive electro-pneumatic brake through uncertain bond graph modeling and robust online monitoring

Science.gov (United States)

Niu, Gang; Zhao, Yajun; Defoort, Michael; Pecht, Michael

2015-01-01

To improve reliability, safety and efficiency, advanced methods of fault detection and diagnosis become increasingly important for many technical fields, especially for safety related complex systems like aircraft, trains, automobiles, power plants and chemical plants. This paper presents a robust fault detection and diagnostic scheme for a multi-energy domain system that integrates a model-based strategy for system fault modeling and a data-driven approach for online anomaly monitoring. The developed scheme uses LFT (linear fractional transformations)-based bond graph for physical parameter uncertainty modeling and fault simulation, and employs AAKR (auto-associative kernel regression)-based empirical estimation followed by SPRT (sequential probability ratio test)-based threshold monitoring to improve the accuracy of fault detection. Moreover, pre- and post-denoising processes are applied to eliminate the cumulative influence of parameter uncertainty and measurement uncertainty. The scheme is demonstrated on the main unit of a locomotive electro-pneumatic brake in a simulated experiment. The results show robust fault detection and diagnostic performance.

Self-driven particles in linear flows and trapped in a harmonic potential

Science.gov (United States)

Sandoval, Mario; Hidalgo-Gonzalez, Julio C.; Jimenez-Aquino, Jose I.

2018-03-01

We present analytical expressions for the mean-square displacement of self-driven particles in general linear flows and trapped in a harmonic potential. The general expressions are applied to three types of linear flows, namely, shear flow, solid-body rotation flow, and extensional flow. By using Brownian dynamics simulations, the effect of trapping and external linear flows on the particles' distribution is also elucidated. These simulations also enabled us to validate our theoretical results.

Robust

DEFF Research Database (Denmark)

2017-01-01

‘Robust – Reflections on Resilient Architecture’, is a scientific publication following the conference of the same name in November of 2017. Researches and PhD-Fellows, associated with the Masters programme: Cultural Heritage, Transformation and Restoration (Transformation), at The Royal Danish...

Electron heating of voltage-driven and matched dual frequency discharges

International Nuclear Information System (INIS)

Lieberman, M A; Lichtenberg, A J

2010-01-01

In a dual frequency capacitive sheath, a high frequency uniform sheath motion is coupled with a low frequency Child law sheath motion. For current-driven high and low frequency sheaths, the high frequency sheath motion generates most of the ohmic and stochastic heating of the discharge electrons. The low frequency motion, in addition to its primary purpose of establishing the ion bombarding energy, also increases the heating by widening the sheath width and transporting the oscillating electrons to regions of lower plasma density, and hence higher sheath velocity. In this work, we show that for voltage-driven high and low frequency sheaths, increasing the low frequency voltage reduces the heating, due to the reduced high frequency current that flows through the sheath under voltage-driven conditions. We determine the dependence of the heating on various parameters and compare the results with the current-driven case. Particle-in-cell simulations are used to confirm this result. Discharges generally employ a matching network to maximize the power transmitted to the plasma. We obtain analytic expressions for the effect of the low frequency source under matched conditions and, again, find that the low frequency source reduces the heating.

Robust extended Kalman filter of discrete-time Markovian jump nonlinear system under uncertain noise

International Nuclear Information System (INIS)

Zhu, Jin; Park, Jun Hong; Lee, Kwan Soo; Spiryagin, Maksym

2008-01-01

This paper examines the problem of robust extended Kalman filter design for discrete -time Markovian jump nonlinear systems with noise uncertainty. Because of the existence of stochastic Markovian switching, the state and measurement equations of underlying system are subject to uncertain noise whose covariance matrices are time-varying or un-measurable instead of stationary. First, based on the expression of filtering performance deviation, admissible uncertainty of noise covariance matrix is given. Secondly, two forms of noise uncertainty are taken into account: Non- Structural and Structural. It is proved by applying game theory that this filter design is a robust mini-max filter. A numerical example shows the validity of the method

Robustness in Railway Operations (RobustRailS)

DEFF Research Database (Denmark)

Jensen, Jens Parbo; Nielsen, Otto Anker

This study considers the problem of enhancing railway timetable robustness without adding slack time, hence increasing the travel time. The approach integrates a transit assignment model to assess how passengers adapt their behaviour whenever operations are changed. First, the approach considers...

Robust statistical methods with R

CERN Document Server

Jureckova, Jana

2005-01-01

Robust statistical methods were developed to supplement the classical procedures when the data violate classical assumptions. They are ideally suited to applied research across a broad spectrum of study, yet most books on the subject are narrowly focused, overly theoretical, or simply outdated. Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on practical application.The authors work from underlying mathematical tools to implementation, paying special attention to the computational aspects. They cover the whole range of robust methods, including differentiable statistical functions, distance of measures, influence functions, and asymptotic distributions, in a rigorous yet approachable manner. Highlighting hands-on problem solving, many examples and computational algorithms using the R software supplement the discussion. The book examines the characteristics of robustness, estimators of real parameter, large sample properties, and goodness-of-fit tests. It...

A robust and rapid method of producing soluble, stable, and functional G-protein coupled receptors.

Directory of Open Access Journals (Sweden)

Karolina Corin

Full Text Available Membrane proteins, particularly G-protein coupled receptors (GPCRs, are notoriously difficult to express. Using commercial E. coli cell-free systems with the detergent Brij-35, we could rapidly produce milligram quantities of 13 unique GPCRs. Immunoaffinity purification yielded receptors at >90% purity. Secondary structure analysis using circular dichroism indicated that the purified receptors were properly folded. Microscale thermophoresis, a novel label-free and surface-free detection technique that uses thermal gradients, showed that these receptors bound their ligands. The secondary structure and ligand-binding results from cell-free produced proteins were comparable to those expressed and purified from HEK293 cells. Our study demonstrates that cell-free protein production using commercially available kits and optimal detergents is a robust technology that can be used to produce sufficient GPCRs for biochemical, structural, and functional analyses. This robust and simple method may further stimulate others to study the structure and function of membrane proteins.

Optimal placement and decentralized robust vibration control for spacecraft smart solar panel structures

International Nuclear Information System (INIS)

Jiang, Jian-ping; Li, Dong-xu

2010-01-01

The decentralized robust vibration control with collocated piezoelectric actuator and strain sensor pairs is considered in this paper for spacecraft solar panel structures. Each actuator is driven individually by the output of the corresponding sensor so that only local feedback control is implemented, with each actuator, sensor and controller operating independently. Firstly, an optimal placement method for the location of the collocated piezoelectric actuator and strain gauge sensor pairs is developed based on the degree of observability and controllability indices for solar panel structures. Secondly, a decentralized robust H ∞ controller is designed to suppress the vibration induced by external disturbance. Finally, a numerical comparison between centralized and decentralized control systems is performed in order to investigate their effectiveness to suppress vibration of the smart solar panel. The simulation results show that the vibration can be significantly suppressed with permitted actuator voltages by the controllers. The decentralized control system almost has the same disturbance attenuation level as the centralized control system with a bit higher control voltages. More importantly, the decentralized controller composed of four three-order systems is a better practical implementation than a high-order centralized controller is

Robust Manufacturing Control

CERN Document Server

2013-01-01

This contributed volume collects research papers, presented at the CIRP Sponsored Conference Robust Manufacturing Control: Innovative and Interdisciplinary Approaches for Global Networks (RoMaC 2012, Jacobs University, Bremen, Germany, June 18th-20th 2012). These research papers present the latest developments and new ideas focusing on robust manufacturing control for global networks. Today, Global Production Networks (i.e. the nexus of interconnected material and information flows through which products and services are manufactured, assembled and distributed) are confronted with and expected to adapt to: sudden and unpredictable large-scale changes of important parameters which are occurring more and more frequently, event propagation in networks with high degree of interconnectivity which leads to unforeseen fluctuations, and non-equilibrium states which increasingly characterize daily business. These multi-scale changes deeply influence logistic target achievement and call for robust planning and control ...

Critique of the use of ICRP-29's 'Robustness Index' in evaluating uncertainties associated with radiological assessment models

Energy Technology Data Exchange (ETDEWEB)

Hoffman, F O; Schwarz, G; Killough, G G [Oak Ridge National Lab., TN (USA)

1980-08-01

Concern is expressed regarding the use of the robustness index, as proposed in ICRP 29, to characterise the uncertainties associated with a model's predictions. Results of a Monte Carlo simulation employing a model of the grass-cow-milk-infant pathway for /sup 131/I are used to elucidate the author's criticisms. It is recommended that the robustness index should be carefully examined to appraise its possible usefulness and potential dangers. Alternate methods for analysis of uncertainty are proposed.

Quantum work distribution for a driven diatomic molecule

International Nuclear Information System (INIS)

Leonard, Alison; Deffner, Sebastian

2015-01-01

Highlights: • A method for calculating the time-dependent solution for a driven system is proposed. • These solutions are used to compute the quantum work distribution. • This distribution is calculated for the Morse potential mimicking a diatomic molecule. • Due to bound and scattering states distribution exhibits continuous and discrete part. • Result is compared with that of a harmonic approximation. - Abstract: We compute the quantum work distribution for a driven Morse oscillator. To this end, we solve the time-dependent dynamics for a scale-invariant process, from which the exact expressions for the transition probabilities are found. Special emphasis is put on the contributions to the work distribution from discrete (bound) and continuous (scattering) parts of the spectrum. The analysis is concluded by comparing the work distribution for the exact Morse potential and the one resulting from a harmonic approximation

Robustness - theoretical framework

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Rizzuto, Enrico; Faber, Michael H.

2010-01-01

More frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of new struct...... of this fact sheet is to describe a theoretical and risk based framework to form the basis for quantification of robustness and for pre-normative guidelines....

Pipe break prediction based on evolutionary data-driven methods with brief recorded data

International Nuclear Information System (INIS)

Xu Qiang; Chen Qiuwen; Li Weifeng; Ma Jinfeng

2011-01-01

Pipe breaks often occur in water distribution networks, imposing great pressure on utility managers to secure stable water supply. However, pipe breaks are hard to detect by the conventional method. It is therefore necessary to develop reliable and robust pipe break models to assess the pipe's probability to fail and then to optimize the pipe break detection scheme. In the absence of deterministic physical models for pipe break, data-driven techniques provide a promising approach to investigate the principles underlying pipe break. In this paper, two data-driven techniques, namely Genetic Programming (GP) and Evolutionary Polynomial Regression (EPR) are applied to develop pipe break models for the water distribution system of Beijing City. The comparison with the recorded pipe break data from 1987 to 2005 showed that the models have great capability to obtain reliable predictions. The models can be used to prioritize pipes for break inspection and then improve detection efficiency.

Robustness Assessment of Spatial Timber Structures

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning

2012-01-01

Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures many modern buildi...... to robustness of spatial timber structures and will discuss the consequences of such robustness issues related to the future development of timber structures.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures many modern building...... codes consider the need for robustness of structures and provide strategies and methods to obtain robustness. Therefore a structural engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper summaries issues with respect...

Improving robustness and computational efficiency using modern C++

International Nuclear Information System (INIS)

Paterno, M; Kowalkowski, J; Green, C

2014-01-01

For nearly two decades, the C++ programming language has been the dominant programming language for experimental HEP. The publication of ISO/IEC 14882:2011, the current version of the international standard for the C++ programming language, makes available a variety of language and library facilities for improving the robustness, expressiveness, and computational efficiency of C++ code. However, much of the C++ written by the experimental HEP community does not take advantage of the features of the language to obtain these benefits, either due to lack of familiarity with these features or concern that these features must somehow be computationally inefficient. In this paper, we address some of the features of modern C+-+, and show how they can be used to make programs that are both robust and computationally efficient. We compare and contrast simple yet realistic examples of some common implementation patterns in C, currently-typical C++, and modern C++, and show (when necessary, down to the level of generated assembly language code) the quality of the executable code produced by recent C++ compilers, with the aim of allowing the HEP community to make informed decisions on the costs and benefits of the use of modern C++.

The Impact of CO2-Driven Vegetation Changes on Wildfire Risk

Science.gov (United States)

Skinner, C. B.; Poulsen, C. J.

2017-12-01

While wildfires are a key component of natural ecological restoration and succession, they also pose tremendous risks to human life, health, and property. Wildfire frequency is expected to increase in many regions as the radiative effects of elevated CO2 drive warmer surface air temperatures, earlier spring snow melt, and more frequent meteorological drought. However, high CO2 concentrations will also directly impact vegetation growth and physiology, potentially altering wildfire characteristics through changes in fuel amount and surface hydrology. Depending on the biome and time of year, these vegetation-driven responses may mitigate or enhance radiative-driven wildfire changes. In this study, we use a suite of earth system models from the Coupled Model Intercomparison Project 5 with active biogeophysics and biogeochemistry to understand how the vegetation response to high CO2 (CO2 quadrupling) contributes to future changes in wildfire risk across the globe. Across the models, projected CO2 fertilization enhances aboveground biomass (about a 30% leaf area index (LAI) increase averaged across the globe) during the spring and summer months, increasing the availability of wildfire fuel across all biomes. Despite greater LAI, models robustly project widespread reductions in summer season transpiration (about -15% averaged across the globe) in response to reduced stomatal conductance from CO2 physiological forcing. Reduced transpiration warms summer season near surface temperatures and lowers relative humidity across vegetated regions of the mid-to-high latitudes, heightening the risk of wildfire occurrence. However, as transpiration goes down in response to greater plant water use efficiency, a larger fraction of soil water remains in the soil, potentially halting the spread of wildfires in some regions. Given the myriad ways in which the vegetation response to CO2 may alter wildfire risk, and the robustness of the responses across models, an explicit simulation of

Robust Face Recognition Via Gabor Feature and Sparse Representation

Directory of Open Access Journals (Sweden)

Hao Yu-Juan

2016-01-01

Full Text Available Sparse representation based on compressed sensing theory has been widely used in the field of face recognition, and has achieved good recognition results. but the face feature extraction based on sparse representation is too simple, and the sparse coefficient is not sparse. In this paper, we improve the classification algorithm based on the fusion of sparse representation and Gabor feature, and then improved algorithm for Gabor feature which overcomes the problem of large dimension of the vector dimension, reduces the computation and storage cost, and enhances the robustness of the algorithm to the changes of the environment.The classification efficiency of sparse representation is determined by the collaborative representation,we simplify the sparse constraint based on L1 norm to the least square constraint, which makes the sparse coefficients both positive and reduce the complexity of the algorithm. Experimental results show that the proposed method is robust to illumination, facial expression and pose variations of face recognition, and the recognition rate of the algorithm is improved.

A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: I. Robust Linear Optimization and Robust Mixed Integer Linear Optimization

Science.gov (United States)

Li, Zukui; Ding, Ran; Floudas, Christodoulos A.

2011-01-01

Robust counterpart optimization techniques for linear optimization and mixed integer linear optimization problems are studied in this paper. Different uncertainty sets, including those studied in literature (i.e., interval set; combined interval and ellipsoidal set; combined interval and polyhedral set) and new ones (i.e., adjustable box; pure ellipsoidal; pure polyhedral; combined interval, ellipsoidal, and polyhedral set) are studied in this work and their geometric relationship is discussed. For uncertainty in the left hand side, right hand side, and objective function of the optimization problems, robust counterpart optimization formulations induced by those different uncertainty sets are derived. Numerical studies are performed to compare the solutions of the robust counterpart optimization models and applications in refinery production planning and batch process scheduling problem are presented. PMID:21935263

Posed versus spontaneous facial expressions are modulated by opposite cerebral hemispheres.

Science.gov (United States)

Ross, Elliott D; Pulusu, Vinay K

2013-05-01

Clinical research has indicated that the left face is more expressive than the right face, suggesting that modulation of facial expressions is lateralized to the right hemisphere. The findings, however, are controversial because the results explain, on average, approximately 4% of the data variance. Using high-speed videography, we sought to determine if movement-onset asymmetry was a more powerful research paradigm than terminal movement asymmetry. The results were very robust, explaining up to 70% of the data variance. Posed expressions began overwhelmingly on the right face whereas spontaneous expressions began overwhelmingly on the left face. This dichotomy was most robust for upper facial expressions. In addition, movement-onset asymmetries did not predict terminal movement asymmetries, which were not significantly lateralized. The results support recent neuroanatomic observations that upper versus lower facial movements have different forebrain motor representations and recent behavioral constructs that posed versus spontaneous facial expressions are modulated preferentially by opposite cerebral hemispheres and that spontaneous facial expressions are graded rather than non-graded movements. Published by Elsevier Ltd.

Robust procedures in chemometrics

DEFF Research Database (Denmark)

Kotwa, Ewelina

properties of the analysed data. The broad theoretical background of robust procedures was given as a very useful supplement to the classical methods, and a new tool, based on robust PCA, aiming at identifying Rayleigh and Raman scatters in excitation-mission (EEM) data was developed. The results show...

Robust canonical correlations: A comparative study

OpenAIRE

Branco, JA; Croux, Christophe; Filzmoser, P; Oliveira, MR

2005-01-01

Several approaches for robust canonical correlation analysis will be presented and discussed. A first method is based on the definition of canonical correlation analysis as looking for linear combinations of two sets of variables having maximal (robust) correlation. A second method is based on alternating robust regressions. These methods axe discussed in detail and compared with the more traditional approach to robust canonical correlation via covariance matrix estimates. A simulation study ...

Stimulus fear relevance and the speed, magnitude, and robustness of vicariously learned fear.

Science.gov (United States)

Dunne, Güler; Reynolds, Gemma; Askew, Chris

2017-08-01

Superior learning for fear-relevant stimuli is typically indicated in the laboratory by faster acquisition of fear responses, greater learned fear, and enhanced resistance to extinction. Three experiments investigated the speed, magnitude, and robustness of UK children's (6-10 years; N = 290; 122 boys, 168 girls) vicariously learned fear responses for three types of stimuli. In two experiments, children were presented with pictures of novel animals (Australian marsupials) and flowers (fear-irrelevant stimuli) alone (control) or together with faces expressing fear or happiness. To determine learning speed the number of stimulus-face pairings seen by children was varied (1, 10, or 30 trials). Robustness of learning was examined via repeated extinction procedures over 3 weeks. A third experiment compared the magnitude and robustness of vicarious fear learning for snakes and marsupials. Significant increases in fear responses were found for snakes, marsupials and flowers. There was no indication that vicarious learning for marsupials was faster than for flowers. Moreover, vicariously learned fear was neither greater nor more robust for snakes compared to marsupials, or for marsupials compared to flowers. These findings suggest that for this age group stimulus fear relevance may have little influence on vicarious fear learning. Copyright © 2017 Elsevier Ltd. All rights reserved.

Robust diagnosis of Ewing sarcoma by immunohistochemical detection of super-enhancer-driven EWSR1-ETS targets

Science.gov (United States)

Marchetto, Aruna; Gerke, Julia S.; Rubio, Rebeca Alba; Kiran, Merve M.; Musa, Julian; Knott, Maximilian M. L.; Ohmura, Shunya; Li, Jing; Akpolat, Nusret; Akatli, Ayse N.; Özen, Özlem; Dirksen, Uta; Hartmann, Wolfgang; de Alava, Enrique; Baumhoer, Daniel; Sannino, Giuseppina; Kirchner, Thomas; Grünewald, Thomas G. P.

2018-01-01

Ewing sarcoma is an undifferentiated small-round-cell sarcoma. Although molecular detection of pathognomonic EWSR1-ETS fusions such as EWSR1-FLI1 enables definitive diagnosis, substantial confusion can arise if molecular diagnostics are unavailable. Diagnosis based on the conventional immunohistochemical marker CD99 is unreliable due to its abundant expression in morphological mimics. To identify novel diagnostic immunohistochemical markers for Ewing sarcoma, we performed comparative expression analyses in 768 tumors representing 21 entities including Ewing-like sarcomas, which confirmed that CIC-DUX4-, BCOR-CCNB3-, EWSR1-NFATc2-, and EWSR1-ETS-translocated sarcomas are distinct entities, and revealed that ATP1A1, BCL11B, and GLG1 constitute specific markers for Ewing sarcoma. Their high expression was validated by immunohistochemistry and proved to depend on EWSR1-FLI1-binding to highly active proximal super-enhancers. Automated cut-off-finding and combination-testing in a tissue-microarray comprising 174 samples demonstrated that detection of high BCL11B and/or GLG1 expression is sufficient to reach 96% specificity for Ewing sarcoma. While 88% of tested Ewing-like sarcomas displayed strong CD99-immunoreactivity, none displayed combined strong BCL11B- and GLG1-immunoreactivity. Collectively, we show that ATP1A1, BCL11B, and GLG1 are EWSR1-FLI1 targets, of which BCL11B and GLG1 offer a fast, simple, and cost-efficient way to diagnose Ewing sarcoma by immunohistochemistry. These markers may significantly reduce the number of misdiagnosed patients, and thus improve patient care. PMID:29416716

Achieving Robustness to Uncertainty for Financial Decision-making

Energy Technology Data Exchange (ETDEWEB)

Barnum, George M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Van Buren, Kendra L. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hemez, Francois M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Song, Peter [Univ. of Pennsylvania, Philadelphia, PA (United States)

2014-01-10

This report investigates the concept of robustness analysis to support financial decision-making. Financial models, that forecast future stock returns or market conditions, depend on assumptions that might be unwarranted and variables that might exhibit large fluctuations from their last-known values. The analysis of robustness explores these sources of uncertainty, and recommends model settings such that the forecasts used for decision-making are as insensitive as possible to the uncertainty. A proof-of-concept is presented with the Capital Asset Pricing Model. The robustness of model predictions is assessed using info-gap decision theory. Info-gaps are models of uncertainty that express the “distance,” or gap of information, between what is known and what needs to be known in order to support the decision. The analysis yields a description of worst-case stock returns as a function of increasing gaps in our knowledge. The analyst can then decide on the best course of action by trading-off worst-case performance with “risk”, which is how much uncertainty they think needs to be accommodated in the future. The report also discusses the Graphical User Interface, developed using the MATLAB® programming environment, such that the user can control the analysis through an easy-to-navigate interface. Three directions of future work are identified to enhance the present software. First, the code should be re-written using the Python scientific programming software. This change will achieve greater cross-platform compatibility, better portability, allow for a more professional appearance, and render it independent from a commercial license, which MATLAB® requires. Second, a capability should be developed to allow users to quickly implement and analyze their own models. This will facilitate application of the software to the evaluation of proprietary financial models. The third enhancement proposed is to add the ability to evaluate multiple models simultaneously

Neutral face classification using personalized appearance models for fast and robust emotion detection.

Science.gov (United States)

Chiranjeevi, Pojala; Gopalakrishnan, Viswanath; Moogi, Pratibha

2015-09-01

Facial expression recognition is one of the open problems in computer vision. Robust neutral face recognition in real time is a major challenge for various supervised learning-based facial expression recognition methods. This is due to the fact that supervised methods cannot accommodate all appearance variability across the faces with respect to race, pose, lighting, facial biases, and so on, in the limited amount of training data. Moreover, processing each and every frame to classify emotions is not required, as user stays neutral for majority of the time in usual applications like video chat or photo album/web browsing. Detecting neutral state at an early stage, thereby bypassing those frames from emotion classification would save the computational power. In this paper, we propose a light-weight neutral versus emotion classification engine, which acts as a pre-processer to the traditional supervised emotion classification approaches. It dynamically learns neutral appearance at key emotion (KE) points using a statistical texture model, constructed by a set of reference neutral frames for each user. The proposed method is made robust to various types of user head motions by accounting for affine distortions based on a statistical texture model. Robustness to dynamic shift of KE points is achieved by evaluating the similarities on a subset of neighborhood patches around each KE point using the prior information regarding the directionality of specific facial action units acting on the respective KE point. The proposed method, as a result, improves emotion recognition (ER) accuracy and simultaneously reduces computational complexity of the ER system, as validated on multiple databases.

Enhanced echolocation via robust statistics and super-resolution of sonar images

Science.gov (United States)

Kim, Kio

Echolocation is a process in which an animal uses acoustic signals to exchange information with environments. In a recent study, Neretti et al. have shown that the use of robust statistics can significantly improve the resiliency of echolocation against noise and enhance its accuracy by suppressing the development of sidelobes in the processing of an echo signal. In this research, the use of robust statistics is extended to problems in underwater explorations. The dissertation consists of two parts. Part I describes how robust statistics can enhance the identification of target objects, which in this case are cylindrical containers filled with four different liquids. Particularly, this work employs a variation of an existing robust estimator called an L-estimator, which was first suggested by Koenker and Bassett. As pointed out by Au et al.; a 'highlight interval' is an important feature, and it is closely related with many other important features that are known to be crucial for dolphin echolocation. A varied L-estimator described in this text is used to enhance the detection of highlight intervals, which eventually leads to a successful classification of echo signals. Part II extends the problem into 2 dimensions. Thanks to the advances in material and computer technology, various sonar imaging modalities are available on the market. By registering acoustic images from such video sequences, one can extract more information on the region of interest. Computer vision and image processing allowed application of robust statistics to the acoustic images produced by forward looking sonar systems, such as Dual-frequency Identification Sonar and ProViewer. The first use of robust statistics for sonar image enhancement in this text is in image registration. Random Sampling Consensus (RANSAC) is widely used for image registration. The registration algorithm using RANSAC is optimized for sonar image registration, and the performance is studied. The second use of robust

Robust H∞ Filtering for Uncertain Neutral Stochastic Systems with Markovian Jumping Parameters and Time Delay

Directory of Open Access Journals (Sweden)

Yajun Li

2015-01-01

Full Text Available This paper deals with the robust H∞ filter design problem for a class of uncertain neutral stochastic systems with Markovian jumping parameters and time delay. Based on the Lyapunov-Krasovskii theory and generalized Finsler Lemma, a delay-dependent stability condition is proposed to ensure not only that the filter error system is robustly stochastically stable but also that a prescribed H∞ performance level is satisfied for all admissible uncertainties. All obtained results are expressed in terms of linear matrix inequalities which can be easily solved by MATLAB LMI toolbox. Numerical examples are given to show that the results obtained are both less conservative and less complicated in computation.

Alpha-fetoprotein-targeted reporter gene expression imaging in hepatocellular carcinoma.

Science.gov (United States)

Kim, Kwang Il; Chung, Hye Kyung; Park, Ju Hui; Lee, Yong Jin; Kang, Joo Hyun

2016-07-21

Hepatocellular carcinoma (HCC) is one of the most common cancers in Eastern Asia, and its incidence is increasing globally. Numerous experimental models have been developed to better our understanding of the pathogenic mechanism of HCC and to evaluate novel therapeutic approaches. Molecular imaging is a convenient and up-to-date biomedical tool that enables the visualization, characterization and quantification of biologic processes in a living subject. Molecular imaging based on reporter gene expression, in particular, can elucidate tumor-specific events or processes by acquiring images of a reporter gene's expression driven by tumor-specific enhancers/promoters. In this review, we discuss the advantages and disadvantages of various experimental HCC mouse models and we present in vivo images of tumor-specific reporter gene expression driven by an alpha-fetoprotein (AFP) enhancer/promoter system in a mouse model of HCC. The current mouse models of HCC development are established by xenograft, carcinogen induction and genetic engineering, representing the spectrum of tumor-inducing factors and tumor locations. The imaging analysis approach of reporter genes driven by AFP enhancer/promoter is presented for these different HCC mouse models. Such molecular imaging can provide longitudinal information about carcinogenesis and tumor progression. We expect that clinical application of AFP-targeted reporter gene expression imaging systems will be useful for the detection of AFP-expressing HCC tumors and screening of increased/decreased AFP levels due to disease or drug treatment.

Arbitrary-step randomly delayed robust filter with application to boost phase tracking

Science.gov (United States)

Qin, Wutao; Wang, Xiaogang; Bai, Yuliang; Cui, Naigang

2018-04-01

The conventional filters such as extended Kalman filter, unscented Kalman filter and cubature Kalman filter assume that the measurement is available in real-time and the measurement noise is Gaussian white noise. But in practice, both two assumptions are invalid. To solve this problem, a novel algorithm is proposed by taking the following four steps. At first, the measurement model is modified by the Bernoulli random variables to describe the random delay. Then, the expression of predicted measurement and covariance are reformulated, which could get rid of the restriction that the maximum number of delay must be one or two and the assumption that probabilities of Bernoulli random variables taking the value one are equal. Next, the arbitrary-step randomly delayed high-degree cubature Kalman filter is derived based on the 5th-degree spherical-radial rule and the reformulated expressions. Finally, the arbitrary-step randomly delayed high-degree cubature Kalman filter is modified to the arbitrary-step randomly delayed high-degree cubature Huber-based filter based on the Huber technique, which is essentially an M-estimator. Therefore, the proposed filter is not only robust to the randomly delayed measurements, but robust to the glint noise. The application to the boost phase tracking example demonstrate the superiority of the proposed algorithms.

FocusHeuristics - expression-data-driven network optimization and disease gene prediction.

Science.gov (United States)

Ernst, Mathias; Du, Yang; Warsow, Gregor; Hamed, Mohamed; Endlich, Nicole; Endlich, Karlhans; Murua Escobar, Hugo; Sklarz, Lisa-Madeleine; Sender, Sina; Junghanß, Christian; Möller, Steffen; Fuellen, Georg; Struckmann, Stephan

2017-02-16

To identify genes contributing to disease phenotypes remains a challenge for bioinformatics. Static knowledge on biological networks is often combined with the dynamics observed in gene expression levels over disease development, to find markers for diagnostics and therapy, and also putative disease-modulatory drug targets and drugs. The basis of current methods ranges from a focus on expression-levels (Limma) to concentrating on network characteristics (PageRank, HITS/Authority Score), and both (DeMAND, Local Radiality). We present an integrative approach (the FocusHeuristics) that is thoroughly evaluated based on public expression data and molecular disease characteristics provided by DisGeNet. The FocusHeuristics combines three scores, i.e. the log fold change and another two, based on the sum and difference of log fold changes of genes/proteins linked in a network. A gene is kept when one of the scores to which it contributes is above a threshold. Our FocusHeuristics is both, a predictor for gene-disease-association and a bioinformatics method to reduce biological networks to their disease-relevant parts, by highlighting the dynamics observed in expression data. The FocusHeuristics is slightly, but significantly better than other methods by its more successful identification of disease-associated genes measured by AUC, and it delivers mechanistic explanations for its choice of genes.

Robust identification of noncoding RNA from transcriptomes requires phylogenetically-informed sampling.

Directory of Open Access Journals (Sweden)

Stinus Lindgreen

2014-10-01

Full Text Available Noncoding RNAs are integral to a wide range of biological processes, including translation, gene regulation, host-pathogen interactions and environmental sensing. While genomics is now a mature field, our capacity to identify noncoding RNA elements in bacterial and archaeal genomes is hampered by the difficulty of de novo identification. The emergence of new technologies for characterizing transcriptome outputs, notably RNA-seq, are improving noncoding RNA identification and expression quantification. However, a major challenge is to robustly distinguish functional outputs from transcriptional noise. To establish whether annotation of existing transcriptome data has effectively captured all functional outputs, we analysed over 400 publicly available RNA-seq datasets spanning 37 different Archaea and Bacteria. Using comparative tools, we identify close to a thousand highly-expressed candidate noncoding RNAs. However, our analyses reveal that capacity to identify noncoding RNA outputs is strongly dependent on phylogenetic sampling. Surprisingly, and in stark contrast to protein-coding genes, the phylogenetic window for effective use of comparative methods is perversely narrow: aggregating public datasets only produced one phylogenetic cluster where these tools could be used to robustly separate unannotated noncoding RNAs from a null hypothesis of transcriptional noise. Our results show that for the full potential of transcriptomics data to be realized, a change in experimental design is paramount: effective transcriptomics requires phylogeny-aware sampling.

Histone Variant HTZ1 Shows Extensive Epistasis with, but Does Not Increase Robustness to, New Mutations

Science.gov (United States)

Richardson, Joshua B.; Uppendahl, Locke D.; Traficante, Maria K.; Levy, Sasha F.; Siegal, Mark L.

2013-01-01

Biological systems produce phenotypes that appear to be robust to perturbation by mutations and environmental variation. Prior studies identified genes that, when impaired, reveal previously cryptic genetic variation. This result is typically interpreted as evidence that the disrupted gene normally increases robustness to mutations, as such robustness would allow cryptic variants to accumulate. However, revelation of cryptic genetic variation is not necessarily evidence that a mutationally robust state has been made less robust. Demonstrating a difference in robustness requires comparing the ability of each state (with the gene perturbed or intact) to suppress the effects of new mutations. Previous studies used strains in which the existing genetic variation had been filtered by selection. Here, we use mutation accumulation (MA) lines that have experienced minimal selection, to test the ability of histone H2A.Z (HTZ1) to increase robustness to mutations in the yeast Saccharomyces cerevisiae. HTZ1, a regulator of chromatin structure and gene expression, represents a class of genes implicated in mutational robustness. It had previously been shown to increase robustness of yeast cell morphology to fluctuations in the external or internal microenvironment. We measured morphological variation within and among 79 MA lines with and without HTZ1. Analysis of within-line variation confirms that HTZ1 increases microenvironmental robustness. Analysis of between-line variation shows the morphological effects of eliminating HTZ1 to be highly dependent on the line, which implies that HTZ1 interacts with mutations that have accumulated in the lines. However, lines without HTZ1 are, as a group, not more phenotypically diverse than lines with HTZ1 present. The presence of HTZ1, therefore, does not confer greater robustness to mutations than its absence. Our results provide experimental evidence that revelation of cryptic genetic variation cannot be assumed to be caused by loss of

Histone variant HTZ1 shows extensive epistasis with, but does not increase robustness to, new mutations.

Directory of Open Access Journals (Sweden)

Joshua B Richardson

Full Text Available Biological systems produce phenotypes that appear to be robust to perturbation by mutations and environmental variation. Prior studies identified genes that, when impaired, reveal previously cryptic genetic variation. This result is typically interpreted as evidence that the disrupted gene normally increases robustness to mutations, as such robustness would allow cryptic variants to accumulate. However, revelation of cryptic genetic variation is not necessarily evidence that a mutationally robust state has been made less robust. Demonstrating a difference in robustness requires comparing the ability of each state (with the gene perturbed or intact to suppress the effects of new mutations. Previous studies used strains in which the existing genetic variation had been filtered by selection. Here, we use mutation accumulation (MA lines that have experienced minimal selection, to test the ability of histone H2A.Z (HTZ1 to increase robustness to mutations in the yeast Saccharomyces cerevisiae. HTZ1, a regulator of chromatin structure and gene expression, represents a class of genes implicated in mutational robustness. It had previously been shown to increase robustness of yeast cell morphology to fluctuations in the external or internal microenvironment. We measured morphological variation within and among 79 MA lines with and without HTZ1. Analysis of within-line variation confirms that HTZ1 increases microenvironmental robustness. Analysis of between-line variation shows the morphological effects of eliminating HTZ1 to be highly dependent on the line, which implies that HTZ1 interacts with mutations that have accumulated in the lines. However, lines without HTZ1 are, as a group, not more phenotypically diverse than lines with HTZ1 present. The presence of HTZ1, therefore, does not confer greater robustness to mutations than its absence. Our results provide experimental evidence that revelation of cryptic genetic variation cannot be assumed to be

Robust plasmonic substrates

DEFF Research Database (Denmark)

Kostiučenko, Oksana; Fiutowski, Jacek; Tamulevicius, Tomas

2014-01-01

Robustness is a key issue for the applications of plasmonic substrates such as tip-enhanced Raman spectroscopy, surface-enhanced spectroscopies, enhanced optical biosensing, optical and optoelectronic plasmonic nanosensors and others. A novel approach for the fabrication of robust plasmonic...... substrates is presented, which relies on the coverage of gold nanostructures with diamond-like carbon (DLC) thin films of thicknesses 25, 55 and 105 nm. DLC thin films were grown by direct hydrocarbon ion beam deposition. In order to find the optimum balance between optical and mechanical properties...

A robust standard deviation control chart

NARCIS (Netherlands)

Schoonhoven, M.; Does, R.J.M.M.

2012-01-01

This article studies the robustness of Phase I estimators for the standard deviation control chart. A Phase I estimator should be efficient in the absence of contaminations and resistant to disturbances. Most of the robust estimators proposed in the literature are robust against either diffuse

Model-Driven Engineering of Machine Executable Code

Science.gov (United States)

Eichberg, Michael; Monperrus, Martin; Kloppenburg, Sven; Mezini, Mira

Implementing static analyses of machine-level executable code is labor intensive and complex. We show how to leverage model-driven engineering to facilitate the design and implementation of programs doing static analyses. Further, we report on important lessons learned on the benefits and drawbacks while using the following technologies: using the Scala programming language as target of code generation, using XML-Schema to express a metamodel, and using XSLT to implement (a) transformations and (b) a lint like tool. Finally, we report on the use of Prolog for writing model transformations.

Combining multiple hypothesis testing and affinity propagation clustering leads to accurate, robust and sample size independent classification on gene expression data

Directory of Open Access Journals (Sweden)

Sakellariou Argiris

2012-10-01

Full Text Available Abstract Background A feature selection method in microarray gene expression data should be independent of platform, disease and dataset size. Our hypothesis is that among the statistically significant ranked genes in a gene list, there should be clusters of genes that share similar biological functions related to the investigated disease. Thus, instead of keeping N top ranked genes, it would be more appropriate to define and keep a number of gene cluster exemplars. Results We propose a hybrid FS method (mAP-KL, which combines multiple hypothesis testing and affinity propagation (AP-clustering algorithm along with the Krzanowski & Lai cluster quality index, to select a small yet informative subset of genes. We applied mAP-KL on real microarray data, as well as on simulated data, and compared its performance against 13 other feature selection approaches. Across a variety of diseases and number of samples, mAP-KL presents competitive classification results, particularly in neuromuscular diseases, where its overall AUC score was 0.91. Furthermore, mAP-KL generates concise yet biologically relevant and informative N-gene expression signatures, which can serve as a valuable tool for diagnostic and prognostic purposes, as well as a source of potential disease biomarkers in a broad range of diseases. Conclusions mAP-KL is a data-driven and classifier-independent hybrid feature selection method, which applies to any disease classification problem based on microarray data, regardless of the available samples. Combining multiple hypothesis testing and AP leads to subsets of genes, which classify unknown samples from both, small and large patient cohorts with high accuracy.

System driven technology selection for future European launch systems

Science.gov (United States)

Baiocco, P.; Ramusat, G.; Sirbi, A.; Bouilly, Th.; Lavelle, F.; Cardone, T.; Fischer, H.; Appel, S.

2015-02-01

In the framework of the next generation launcher activity at ESA, a top-down approach and a bottom-up approach have been performed for the identification of promising technologies and alternative conception of future European launch vehicles. The top-down approach consists in looking for system-driven design solutions and the bottom-up approach features design solutions leading to substantial advantages for the system. The main investigations have been focused on the future launch vehicle technologies. Preliminary specifications have been used in order to permit sub-system design to find the major benefit for the overall launch system. The development cost, non-recurring and recurring cost, industrialization and operational aspects have been considered as competitiveness factors for the identification and down-selection of the most interesting technologies. The recurring cost per unit payload mass has been evaluated. The TRL/IRL has been assessed and a preliminary development plan has been traced for the most promising technologies. The potentially applicable launch systems are Ariane and VEGA evolution. The main FLPP technologies aim at reducing overall structural mass, increasing structural margins for robustness, metallic and composite containment of cryogenic hydrogen and oxygen propellants, propellant management subsystems, elements significantly reducing fabrication and operational costs, avionics, pyrotechnics, etc. to derive performing upper and booster stages. Application of the system driven approach allows creating performing technology demonstrators in terms of need, demonstration objective, size and cost. This paper outlines the process of technology down selection using a system driven approach, the accomplishments already achieved in the various technology fields up to now, as well as the potential associated benefit in terms of competitiveness factors.

Simian Immunodeficiency Virus Targeting of CXCR3+ CD4+ T Cells in Secondary Lymphoid Organs Is Associated with Robust CXCL10 Expression in Monocyte/Macrophage Subsets.

Science.gov (United States)

Fujino, Masayuki; Sato, Hirotaka; Okamura, Tomotaka; Uda, Akihiko; Takeda, Satoshi; Ahmed, Nursarat; Shichino, Shigeyuki; Shiino, Teiichiro; Saito, Yohei; Watanabe, Satoru; Sugimoto, Chie; Kuroda, Marcelo J; Ato, Manabu; Nagai, Yoshiyuki; Izumo, Shuji; Matsushima, Kouji; Miyazawa, Masaaki; Ansari, Aftab A; Villinger, Francois; Mori, Kazuyasu

2017-07-01

Glycosylation of Env defines pathogenic properties of simian immunodeficiency virus (SIV). We previously demonstrated that pathogenic SIVmac239 and a live-attenuated, quintuple deglycosylated Env mutant (Δ5G) virus target CD4 + T cells residing in different tissues during acute infection. SIVmac239 and Δ5G preferentially infected distinct CD4 + T cells in secondary lymphoid organs (SLOs) and within the lamina propria of the small intestine, respectively (C. Sugimoto et al., J Virol 86:9323-9336, 2012, https://doi.org/10.1128/JVI.00948-12). Here, we studied the host responses relevant to SIV targeting of CXCR3 + CCR5 + CD4 + T cells in SLOs. Genome-wide transcriptome analyses revealed that Th1-polarized inflammatory responses, defined by expression of CXCR3 chemokines, were distinctly induced in the SIVmac239-infected animals. Consistent with robust expression of CXCL10, CXCR3 + T cells were depleted from blood in the SIVmac239-infected animals. We also discovered that elevation of CXCL10 expression in blood and SLOs was secondary to the induction of CD14 + CD16 + monocytes and MAC387 + macrophages, respectively. Since the significantly higher levels of SIV infection in SLOs occurred with a massive accumulation of infiltrated MAC387 + macrophages, T cells, dendritic cells (DCs), and residential macrophages near high endothelial venules, the results highlight critical roles of innate/inflammatory responses in SIVmac239 infection. Restricted infection in SLOs by Δ5G also suggests that glycosylation of Env modulates innate/inflammatory responses elicited by cells of monocyte/macrophage/DC lineages. IMPORTANCE We previously demonstrated that a pathogenic SIVmac239 virus and a live-attenuated, deglycosylated mutant Δ5G virus infected distinct CD4 + T cell subsets in SLOs and the small intestine, respectively (C. Sugimoto et al., J Virol 86:9323-9336, 2012, https://doi.org/10.1128/JVI.00948-12). Accordingly, infections with SIVmac239, but not with Δ5G, deplete CXCR3

Half of the world’s population experience robust changes in the water cycle for a 2 °C warmer world

International Nuclear Information System (INIS)

Sedláček, Jan; Knutti, Reto

2014-01-01

Fresh water is a critical resource on Earth, yet projections of changes in the water cycle resulting from anthropogenic warming are challenging. It is important to not only know the best estimate of change, but also how robust these projections are, where changes occur, which variables will change, and how many people are affected by it. Here we synthesize the changes in the water cycle, based on results of the latest climate model intercomparison (CMIP5). Several variables of the water cycle, such as evaporation and relative humidity, show robust changes over more than 50% of the land area already with an anthropogenic global warming of 1 °C. A warming of 2 °C shows more than half of the world’s population to be directly affected by robust local changes in the water cycle, and everybody experiences a robust change in at least one variable of the water cycle. While the physical changes are widespread, the affected people are concentrated in a few hot-spots mainly in Asia and Central Africa. The occurrence of these hot-spots is driven by population density, as well as by the early emergence of the anthropogenic signal from variability in these areas. Large uncertainties remain in projections of soil moisture and runoff changes. (paper)

Abstract knowledge versus direct experience in processing of binomial expressions.

Science.gov (United States)

Morgan, Emily; Levy, Roger

2016-12-01

We ask whether word order preferences for binomial expressions of the form A and B (e.g. bread and butter) are driven by abstract linguistic knowledge of ordering constraints referencing the semantic, phonological, and lexical properties of the constituent words, or by prior direct experience with the specific items in questions. Using forced-choice and self-paced reading tasks, we demonstrate that online processing of never-before-seen binomials is influenced by abstract knowledge of ordering constraints, which we estimate with a probabilistic model. In contrast, online processing of highly frequent binomials is primarily driven by direct experience, which we estimate from corpus frequency counts. We propose a trade-off wherein processing of novel expressions relies upon abstract knowledge, while reliance upon direct experience increases with increased exposure to an expression. Our findings support theories of language processing in which both compositional generation and direct, holistic reuse of multi-word expressions play crucial roles. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

P01.29 Mutant (R132H) IDH1-driven cellular transformation makes cells dependent on continued wild type IDH1 expression in a model of in vitro gliomagenesis

Science.gov (United States)

Johannessen, T.; Mukherjee, J.; Wood, M.; Viswanath, P.; Ohba, S.; Ronen, S.; Berkvig, R.; Pieper, R.

2017-01-01

Abstract Introduction: Missense R132H mutations in the active site of isocitrate dehydrogenase 1 (IDH1) biologically and diagnostically distinguish low-grade gliomas and secondary glioblastomas from primary glioblastomas. IDH1 mutations lead to the formation of the oncometabolite 2-hydroxyglutarate (2-HG) from the reduction of α-ketoglutarate (α-KG), which in turn facilitates tumorigenesis by modifying DNA and histone methylation as well blocking differentiation processes. We recently showed (Mol Cancer Res 14: 976–983, 2016) that although mutant IDH1 expression in hTERT-immortalized, p53/pRb-deficient astrocytes can drive cellular transformation and gliomagenesis, selective pharmacologic inhibition and elimination of 2-HG by the mutant IDH1 inhibitor AGI-5198 has little effect on the growth or clonagenicity of these transformed cells. To address the possible role of WT IDH1 in the growth of mutant IDH-driven tumor cells, we used a slightly different gliomagenesis model in which the transformation of TERT-deficient, p53/pRb-deficient astrocytes (pre-crisis cells) occurs only after prolonged expression of mutant IDH and passage through cellular crisis (post-crisis cells, Cancer Res 76:6680–6689, 2016). METHODS AND MATERIALS: Using this system we introduced AGI-5198, or siRNA targeting both WT and mutant forms of IDH1 into p53/pRb-deficient, mutant IDH1-expressing human astrocytes prior to or following their transformation, and compared the effects on cell growth and clonagenicity. Results: AGI-5198 exposure decreased levels of 2HG by greater than 90%, and as previously reported had no effect on the growth of either the pre-or post-crisis cell populations. A one-day exposure to a pan IDH1 siRNA resulted in a similar, prolonged (greater than 6 day), 80% inhibition of both WT and mutant IDH1 protein levels and 2HG in both cell groups. While the growth of the mutant IDH-expressing, non-transformed cells was similar to that of scramble siRNA controls, the growth

Differential Gene Expression and Aging

Directory of Open Access Journals (Sweden)

Laurent Seroude

2002-01-01

Full Text Available It has been established that an intricate program of gene expression controls progression through the different stages in development. The equally complex biological phenomenon known as aging is genetically determined and environmentally modulated. This review focuses on the genetic component of aging, with a special emphasis on differential gene expression. At least two genetic pathways regulating organism longevity act by modifying gene expression. Many genes are also subjected to age-dependent transcriptional regulation. Some age-related gene expression changes are prevented by caloric restriction, the most robust intervention that slows down the aging process. Manipulating the expression of some age-regulated genes can extend an organism's life span. Remarkably, the activity of many transcription regulatory elements is linked to physiological age as opposed to chronological age, indicating that orderly and tightly controlled regulatory pathways are active during aging.

Robustness: confronting lessons from physics and biology.

Science.gov (United States)

Lesne, Annick

2008-11-01

The term robustness is encountered in very different scientific fields, from engineering and control theory to dynamical systems to biology. The main question addressed herein is whether the notion of robustness and its correlates (stability, resilience, self-organisation) developed in physics are relevant to biology, or whether specific extensions and novel frameworks are required to account for the robustness properties of living systems. To clarify this issue, the different meanings covered by this unique term are discussed; it is argued that they crucially depend on the kind of perturbations that a robust system should by definition withstand. Possible mechanisms underlying robust behaviours are examined, either encountered in all natural systems (symmetries, conservation laws, dynamic stability) or specific to biological systems (feedbacks and regulatory networks). Special attention is devoted to the (sometimes counterintuitive) interrelations between robustness and noise. A distinction between dynamic selection and natural selection in the establishment of a robust behaviour is underlined. It is finally argued that nested notions of robustness, relevant to different time scales and different levels of organisation, allow one to reconcile the seemingly contradictory requirements for robustness and adaptability in living systems.

Behavior-driven arc expression is reduced in all ventral hippocampal subfields compared to CA1, CA3, and dentate gyrus in rat dorsal hippocampus.

Science.gov (United States)

Chawla, M K; Sutherland, V L; Olson, K; McNaughton, B L; Barnes, C A

2018-02-01

Anatomical connectivity and lesion studies reveal distinct functional heterogeneity along the dorsal-ventral axis of the hippocampus. The immediate early gene Arc is known to be involved in neural plasticity and memory and can be used as a marker for cell activity that occurs, for example, when hippocampal place cells fire. We report here, that Arc is expressed in a greater proportion of cells in dorsal CA1, CA3, and dentate gyrus (DG), following spatial behavioral experiences compared to ventral hippocampal subregions (dorsal CA1 = 33%; ventral CA1 = 13%; dorsal CA3 = 23%; ventral CA3 = 8%; and dorsal DG = 2.5%; ventral DG = 1.2%). The technique used here to obtain estimates of numbers of behavior-driven cells across the dorsal-ventral axis, however, corresponds quite well with samples from available single unit recording studies. Several explanations for the two- to-threefold reduction in spatial behavior-driven cell activity in the ventral hippocampus can be offered. These include anatomical connectivity differences, differential gain of the self-motion signals that appear to alter the scale of place fields and the proportion of active cells, and possibly variations in the neuronal responses to non-spatial information within the hippocampus along its dorso-ventral axis. © 2017 Wiley Periodicals, Inc.

Driven-Dissipative Supersolid in a Ring Cavity

Science.gov (United States)

Mivehvar, Farokh; Ostermann, Stefan; Piazza, Francesco; Ritsch, Helmut

2018-03-01

Supersolids are characterized by the counterintuitive coexistence of superfluid and crystalline order. Here we study a supersolid phase emerging in the steady state of a driven-dissipative system. We consider a transversely pumped Bose-Einstein condensate trapped along the axis of a ring cavity and coherently coupled to a pair of degenerate counterpropagating cavity modes. Above a threshold pump strength the interference of photons scattered into the two cavity modes results in an emergent superradiant lattice, which spontaneously breaks the continuous translational symmetry towards a periodic atomic pattern. The crystalline steady state inherits the superfluidity of the Bose-Einstein condensate, thus exhibiting genuine properties of a supersolid. A gapless collective Goldstone mode correspondingly appears in the superradiant phase, which can be nondestructively monitored via the relative phase of the two cavity modes on the cavity output. Despite cavity-photon losses the Goldstone mode remains undamped, indicating the robustness of the supersolid phase.

Transfer functions of double- and multiple-cavity Fabry-Perot filters driven by Lorentzian sources.

Science.gov (United States)

Marti, J; Capmany, J

1996-12-20

We derive expressions for the transfer functions of double- and multiple-cavity Fabry-Perot filters driven by laser sources with Lorentzian spectrum. These are of interest because of their applications in sensing and channel filtering in optical frequency-division multiplexing networks.

The receptive-expressive gap in the vocabulary of young second-language learners: Robustness and possible mechanisms

OpenAIRE

Gibson, Todd A.; Oller, D. Kimbrough; Jarmulowicz, Linda; Ethington, Corinna A.

2012-01-01

Adults and children learning a second language show difficulty accessing expressive vocabulary that appears accessible receptively in their first language (L1). We call this discrepancy the receptive-expressive gap. Kindergarten Spanish (L1) - English (L2) sequential bilinguals were given standardized tests of receptive and expressive vocabulary in both Spanish and English. We found a small receptive-expressive gap in English but a large receptive-expressive gap in Spanish. We categorized chi...

Shock ignition targets: gain and robustness vs ignition threshold factor

Science.gov (United States)

Atzeni, Stefano; Antonelli, Luca; Schiavi, Angelo; Picone, Silvia; Volponi, Gian Marco; Marocchino, Alberto

2017-10-01

Shock ignition is a laser direct-drive inertial confinement fusion scheme, in which the stages of compression and hot spot formation are partly separated. The hot spot is created at the end of the implosion by a converging shock driven by a final ``spike'' of the laser pulse. Several shock-ignition target concepts have been proposed and relevant gain curves computed (see, e.g.). Here, we consider both pure-DT targets and more facility-relevant targets with plastic ablator. The investigation is conducted with 1D and 2D hydrodynamic simulations. We determine ignition threshold factors ITF's (and their dependence on laser pulse parameters) by means of 1D simulations. 2D simulations indicate that robustness to long-scale perturbations increases with ITF. Gain curves (gain vs laser energy), for different ITF's, are generated using 1D simulations. Work partially supported by Sapienza Project C26A15YTMA, Sapienza 2016 (n. 257584), Eurofusion Project AWP17-ENR-IFE-CEA-01.

A Robust Response of the Hadley Circulation to Global Warming

Science.gov (United States)

Lau, William K M.; Kim, Kyu-Myong

2014-01-01

Tropical rainfall is expected to increase in a warmer climate. Yet, recent studies have inferred that the Hadley Circulation (HC), which is primarily driven by latent heating from tropical rainfall, is weakened under global warming. Here, we show evidence of a robust intensification of the HC from analyses of 33 CMIP5 model projections under a scenario of 1 per year CO2 emission increase. The intensification is manifested in a deep-tropics squeeze, characterized by a pronounced increase in the zonal mean ascending motion in the mid and upper troposphere, a deepening and narrowing of the convective zone and enhanced rainfall in the deep tropics. These changes occur in conjunction with a rise in the region of maximum outflow of the HC, with accelerated meridional mass outflow in the uppermost branch of the HC away from the equator, coupled to a weakened inflow in the return branches of the HC in the lower troposphere.

Cre recombinase expression can result in phenotypic aberrations in plants

NARCIS (Netherlands)

Coppoolse, E.; Vroomen, de M.J.; Roelofs, D.; Smit, J.; Gennip, van F.; Hersmus, B.J.M.; Nijkamp, H.J.J.; Haaren, van M.J.

2003-01-01

The cre recombinase gene was stably introduced and expressed in tomato, petunia and Nicotiana tabacum. Some plants expressing the cre gene driven by a CaMV 35S promoter displayed growth retardation and a distinct pattern of chlorosis in their leaves. Although no direct relation can be proven between

Cre recombinase expression can result in phenotypic aberrations in plants

NARCIS (Netherlands)

Coppoolse, Eric R; de Vroomen, Marianne J; Roelofs, Dick; Smit, Jaap; van Gennip, Femke; Hersmus, Bart J M; Nijkamp, H John J; van Haaren, Mark J J

The cre recombinase gene was stably introduced and expressed in tomato, petunia and Nicotiana tabacum. Some plants expressing the cre gene driven by a CaMV 35S promoter displayed growth retardation and a distinct pattern of chlorosis in their leaves. Although no direct relation can be proven between

Robust AIC with High Breakdown Scale Estimate

Directory of Open Access Journals (Sweden)

Shokrya Saleh

2014-01-01

Full Text Available Akaike Information Criterion (AIC based on least squares (LS regression minimizes the sum of the squared residuals; LS is sensitive to outlier observations. Alternative criterion, which is less sensitive to outlying observation, has been proposed; examples are robust AIC (RAIC, robust Mallows Cp (RCp, and robust Bayesian information criterion (RBIC. In this paper, we propose a robust AIC by replacing the scale estimate with a high breakdown point estimate of scale. The robustness of the proposed methods is studied through its influence function. We show that, the proposed robust AIC is effective in selecting accurate models in the presence of outliers and high leverage points, through simulated and real data examples.

Modeling Diffusion and Buoyancy-Driven Convection with Application to Geological CO2 Storage

KAUST Repository

Allen, Rebecca

2015-04-01

ABSTRACT Modeling Diffusion and Buoyancy-Driven Convection with Application to Geological CO2 Storage Rebecca Allen Geological CO2 storage is an engineering feat that has been undertaken around the world for more than two decades, thus accurate modeling of flow and transport behavior is of practical importance. Diffusive and convective transport are relevant processes for buoyancy-driven convection of CO2 into underlying fluid, a scenario that has received the attention of numerous modeling studies. While most studies focus on Darcy-scale modeling of this scenario, relatively little work exists at the pore-scale. In this work, properties evaluated at the pore-scale are used to investigate the transport behavior modeled at the Darcy-scale. We compute permeability and two different forms of tortuosity, namely hydraulic and diffusive. By generating various pore ge- ometries, we find hydraulic and diffusive tortuosity can be quantitatively different in the same pore geometry by up to a factor of ten. As such, we emphasize that these tortuosities should not be used interchangeably. We find pore geometries that are characterized by anisotropic permeability can also exhibit anisotropic diffusive tortuosity. This finding has important implications for buoyancy-driven convection modeling; when representing the geological formation with an anisotropic permeabil- ity, it is more realistic to also account for an anisotropic diffusivity. By implementing a non-dimensional model that includes both a vertically and horizontally orientated 5 Rayleigh number, we interpret our findings according to the combined effect of the anisotropy from permeability and diffusive tortuosity. In particular, we observe the Rayleigh ratio may either dampen or enhance the diffusing front, and our simulation data is used to express the time of convective onset as a function of the Rayleigh ratio. Also, we implement a lattice Boltzmann model for thermal convective flows, which we treat as an analog for

Methodology in robust and nonparametric statistics

CERN Document Server

Jurecková, Jana; Picek, Jan

2012-01-01

Introduction and SynopsisIntroductionSynopsisPreliminariesIntroductionInference in Linear ModelsRobustness ConceptsRobust and Minimax Estimation of LocationClippings from Probability and Asymptotic TheoryProblemsRobust Estimation of Location and RegressionIntroductionM-EstimatorsL-EstimatorsR-EstimatorsMinimum Distance and Pitman EstimatorsDifferentiable Statistical FunctionsProblemsAsymptotic Representations for L-Estimators

Reflection of a Year Long Model-Driven Business and UI Modeling Development Project

Science.gov (United States)

Sukaviriya, Noi; Mani, Senthil; Sinha, Vibha

Model-driven software development enables users to specify an application at a high level - a level that better matches problem domain. It also promises the users with better analysis and automation. Our work embarks on two collaborating domains - business process and human interactions - to build an application. Business modeling expresses business operations and flows then creates business flow implementation. Human interaction modeling expresses a UI design, its relationship with business data, logic, and flow, and can generate working UI. This double modeling approach automates the production of a working system with UI and business logic connected. This paper discusses the human aspects of this modeling approach after a year long of building a procurement outsourcing contract application using the approach - the result of which was deployed in December 2008. The paper discusses in multiple areas the happy endings and some heartache. We end with insights on how a model-driven approach could do better for humans in the process.

A Novel Data-Driven Fast Capacity Estimation of Spent Electric Vehicle Lithium-ion Batteries

Directory of Open Access Journals (Sweden)

Caiping Zhang

2014-12-01

Full Text Available Fast capacity estimation is a key enabling technique for second-life of lithium-ion batteries due to the hard work involved in determining the capacity of a large number of used electric vehicle (EV batteries. This paper tries to make three contributions to the existing literature through a robust and advanced algorithm: (1 a three layer back propagation artificial neural network (BP ANN model is developed to estimate the battery capacity. The model employs internal resistance expressing the battery’s kinetics as the model input, which can realize fast capacity estimation; (2 an estimation error model is established to investigate the relationship between the robustness coefficient and regression coefficient. It is revealed that commonly used ANN capacity estimation algorithm is flawed in providing robustness of parameter measurement uncertainties; (3 the law of large numbers is used as the basis for a proposed robust estimation approach, which optimally balances the relationship between estimation accuracy and disturbance rejection. An optimal range of the threshold for robustness coefficient is also discussed and proposed. Experimental results demonstrate the efficacy and the robustness of the BP ANN model together with the proposed identification approach, which can provide an important basis for large scale applications of second-life of batteries.

Mechanochemically Driven Syntheses of Boride Nanomaterials

Science.gov (United States)

Blair, Richard G.

Solid state metathesis reactions have proven to be a viable route to the production of unfunctionalized nanomaterials. However, current implementations of this approach are limited to self-propagating reactions. We have been investigating mechanically driven metathesis reactions. The use of high-energy ball mills allows control of crystallite sizes without the use of a capping group. Reinforcement materials with crystallite sizes on the order of 5-30 nm can be produced in such a manner. Borides are of particular interest due to their strength, high melting point, and electrical conductivity. The ultimate goal of this work is to prepare oxide and capping group-free nanoparticles suitable for incorporation in thermoelectric, polymer, and ceramic composites. Ultimately this work will facilitate the production of improved thermoelectric materials that will provide robust, deployable, power generation modules to supplement or replace fuel cell, Stirling, and battery-derived power sources. It will also result in scalable, bulk syntheses of tough, refractory, conductive nanomaterials for polymer composites with improved electrical properties, ceramic composites with enhanced fracture toughness, and composites with enhanced neutron reflectance and/or absorbance.

Robust Fuzzy Control for Fractional-Order Uncertain Hydroturbine Regulating System with Random Disturbances

OpenAIRE

Fengjiao Wu; Guitao Zhang; Zhengzhong Wang

2016-01-01

The robust fuzzy control for fractional-order hydroturbine regulating system is studied in this paper. First, the more practical fractional-order hydroturbine regulating system with uncertain parameters and random disturbances is presented. Then, on the basis of interval matrix theory and fractional-order stability theorem, a fuzzy control method is proposed for fractional-order hydroturbine regulating system, and the stability condition is expressed as a group of linear matrix inequalities. ...

Robust Approaches to Forecasting

OpenAIRE

Jennifer Castle; David Hendry; Michael P. Clements

2014-01-01

We investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium correction models. Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, implulses, omitted variables, unanticipated location shifts and incorrectly included variables that experience a shift. We derive the resulting forecast biases and error variances, and indicate when the methods ar...

Facial expression recognition based on improved deep belief networks

Science.gov (United States)

Wu, Yao; Qiu, Weigen

2017-08-01

In order to improve the robustness of facial expression recognition, a method of face expression recognition based on Local Binary Pattern (LBP) combined with improved deep belief networks (DBNs) is proposed. This method uses LBP to extract the feature, and then uses the improved deep belief networks as the detector and classifier to extract the LBP feature. The combination of LBP and improved deep belief networks is realized in facial expression recognition. In the JAFFE (Japanese Female Facial Expression) database on the recognition rate has improved significantly.

A Generalized Cauchy Distribution Framework for Problems Requiring Robust Behavior

Directory of Open Access Journals (Sweden)

Carrillo RafaelE

2010-01-01

Full Text Available Statistical modeling is at the heart of many engineering problems. The importance of statistical modeling emanates not only from the desire to accurately characterize stochastic events, but also from the fact that distributions are the central models utilized to derive sample processing theories and methods. The generalized Cauchy distribution (GCD family has a closed-form pdf expression across the whole family as well as algebraic tails, which makes it suitable for modeling many real-life impulsive processes. This paper develops a GCD theory-based approach that allows challenging problems to be formulated in a robust fashion. Notably, the proposed framework subsumes generalized Gaussian distribution (GGD family-based developments, thereby guaranteeing performance improvements over traditional GCD-based problem formulation techniques. This robust framework can be adapted to a variety of applications in signal processing. As examples, we formulate four practical applications under this framework: (1 filtering for power line communications, (2 estimation in sensor networks with noisy channels, (3 reconstruction methods for compressed sensing, and (4 fuzzy clustering.

Theoretical Framework for Robustness Evaluation

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

2011-01-01

This paper presents a theoretical framework for evaluation of robustness of structural systems, incl. bridges and buildings. Typically modern structural design codes require that ‘the consequence of damages to structures should not be disproportional to the causes of the damages’. However, although...... the importance of robustness for structural design is widely recognized the code requirements are not specified in detail, which makes the practical use difficult. This paper describes a theoretical and risk based framework to form the basis for quantification of robustness and for pre-normative guidelines...

Modular design of metabolic network for robust production of n-butanol from galactose-glucose mixtures.

Science.gov (United States)

Lim, Hyun Gyu; Lim, Jae Hyung; Jung, Gyoo Yeol

2015-01-01

Refactoring microorganisms for efficient production of advanced biofuel such as n-butanol from a mixture of sugars in the cheap feedstock is a prerequisite to achieve economic feasibility in biorefinery. However, production of biofuel from inedible and cheap feedstock is highly challenging due to the slower utilization of biomass-driven sugars, arising from complex assimilation pathway, difficulties in amplification of biosynthetic pathways for heterologous metabolite, and redox imbalance caused by consuming intracellular reducing power to produce quite reduced biofuel. Even with these problems, the microorganisms should show robust production of biofuel to obtain industrial feasibility. Thus, refactoring microorganisms for efficient conversion is highly desirable in biofuel production. In this study, we engineered robust Escherichia coli to accomplish high production of n-butanol from galactose-glucose mixtures via the design of modular pathway, an efficient and systematic way, to reconstruct the entire metabolic pathway with many target genes. Three modular pathways designed using the predictable genetic elements were assembled for efficient galactose utilization, n-butanol production, and redox re-balancing to robustly produce n-butanol from a sugar mixture of galactose and glucose. Specifically, the engineered strain showed dramatically increased n-butanol production (3.3-fold increased to 6.2 g/L after 48-h fermentation) compared to the parental strain (1.9 g/L) in galactose-supplemented medium. Moreover, fermentation with mixtures of galactose and glucose at various ratios from 2:1 to 1:2 confirmed that our engineered strain was able to robustly produce n-butanol regardless of sugar composition with simultaneous utilization of galactose and glucose. Collectively, modular pathway engineering of metabolic network can be an effective approach in strain development for optimal biofuel production with cost-effective fermentable sugars. To the best of our

Robust portfolio selection under norm uncertainty

Directory of Open Access Journals (Sweden)

Lei Wang

2016-06-01

Full Text Available Abstract In this paper, we consider the robust portfolio selection problem which has a data uncertainty described by the ( p , w $(p,w$ -norm in the objective function. We show that the robust formulation of this problem is equivalent to a linear optimization problem. Moreover, we present some numerical results concerning our robust portfolio selection problem.

A 310-bp minimal promoter mediates smooth muscle cell-specific expression of telokin.

Science.gov (United States)

Smith, A F; Bigsby, R M; Word, R A; Herring, B P

1998-05-01

A cell-specific promoter located in an intron of the smooth muscle myosin light chain kinase gene directs transcription of telokin exclusively in smooth muscle cells. Transgenic mice were generated in which a 310-bp rabbit telokin promoter fragment, extending from -163 to +147, was used to drive expression of simian virus 40 large T antigen. Smooth muscle-specific expression of the T-antigen transgene paralleled that of the endogenous telokin gene in all smooth muscle tissues except uterus. The 310-bp promoter fragment resulted in very low levels of transgene expression in uterus; in contrast, a transgene driven by a 2.4-kb fragment (-2250 to +147) resulted in high levels of transgene expression in uterine smooth muscle. Telokin expression levels correlate with the estrogen status of human myometrial tissues, suggesting that deletion of an estrogen response element (ERE) may account for the low levels of transgene expression driven by the 310-bp rabbit telokin promoter in uterine smooth muscle. Experiments in A10 smooth muscle cells directly showed that reporter gene expression driven by the 2.4-kb, but not 310-bp, promoter fragment could be stimulated two- to threefold by estrogen. This stimulation was mediated through an ERE located between -1447 and -1474. Addition of the ERE to the 310-bp fragment restored estrogen responsiveness in A10 cells. These data demonstrate that in addition to a minimal 310-bp proximal promoter at least one distal cis-acting regulatory element is required for telokin expression in uterine smooth muscle. The distal element may include an ERE between -1447 and -1474.

Robustness and structure of complex networks

Science.gov (United States)

Shao, Shuai

This dissertation covers the two major parts of my PhD research on statistical physics and complex networks: i) modeling a new type of attack -- localized attack, and investigating robustness of complex networks under this type of attack; ii) discovering the clustering structure in complex networks and its influence on the robustness of coupled networks. Complex networks appear in every aspect of our daily life and are widely studied in Physics, Mathematics, Biology, and Computer Science. One important property of complex networks is their robustness under attacks, which depends crucially on the nature of attacks and the structure of the networks themselves. Previous studies have focused on two types of attack: random attack and targeted attack, which, however, are insufficient to describe many real-world damages. Here we propose a new type of attack -- localized attack, and study the robustness of complex networks under this type of attack, both analytically and via simulation. On the other hand, we also study the clustering structure in the network, and its influence on the robustness of a complex network system. In the first part, we propose a theoretical framework to study the robustness of complex networks under localized attack based on percolation theory and generating function method. We investigate the percolation properties, including the critical threshold of the phase transition pc and the size of the giant component Pinfinity. We compare localized attack with random attack and find that while random regular (RR) networks are more robust against localized attack, Erdoḧs-Renyi (ER) networks are equally robust under both types of attacks. As for scale-free (SF) networks, their robustness depends crucially on the degree exponent lambda. The simulation results show perfect agreement with theoretical predictions. We also test our model on two real-world networks: a peer-to-peer computer network and an airline network, and find that the real-world networks

Three gene expression vector sets for concurrently expressing multiple genes in Saccharomyces cerevisiae.

Science.gov (United States)

Ishii, Jun; Kondo, Takashi; Makino, Harumi; Ogura, Akira; Matsuda, Fumio; Kondo, Akihiko

2014-05-01

Yeast has the potential to be used in bulk-scale fermentative production of fuels and chemicals due to its tolerance for low pH and robustness for autolysis. However, expression of multiple external genes in one host yeast strain is considerably labor-intensive due to the lack of polycistronic transcription. To promote the metabolic engineering of yeast, we generated systematic and convenient genetic engineering tools to express multiple genes in Saccharomyces cerevisiae. We constructed a series of multi-copy and integration vector sets for concurrently expressing two or three genes in S. cerevisiae by embedding three classical promoters. The comparative expression capabilities of the constructed vectors were monitored with green fluorescent protein, and the concurrent expression of genes was monitored with three different fluorescent proteins. Our multiple gene expression tool will be helpful to the advanced construction of genetically engineered yeast strains in a variety of research fields other than metabolic engineering. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Robustness Recipes for Minimax Robust Optimization in Intensity Modulated Proton Therapy for Oropharyngeal Cancer Patients

Energy Technology Data Exchange (ETDEWEB)

Voort, Sebastian van der [Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam (Netherlands); Section of Nuclear Energy and Radiation Applications, Department of Radiation, Science and Technology, Delft University of Technology, Delft (Netherlands); Water, Steven van de [Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam (Netherlands); Perkó, Zoltán [Section of Nuclear Energy and Radiation Applications, Department of Radiation, Science and Technology, Delft University of Technology, Delft (Netherlands); Heijmen, Ben [Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam (Netherlands); Lathouwers, Danny [Section of Nuclear Energy and Radiation Applications, Department of Radiation, Science and Technology, Delft University of Technology, Delft (Netherlands); Hoogeman, Mischa, E-mail: m.hoogeman@erasmusmc.nl [Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam (Netherlands)

2016-05-01

Purpose: We aimed to derive a “robustness recipe” giving the range robustness (RR) and setup robustness (SR) settings (ie, the error values) that ensure adequate clinical target volume (CTV) coverage in oropharyngeal cancer patients for given gaussian distributions of systematic setup, random setup, and range errors (characterized by standard deviations of Σ, σ, and ρ, respectively) when used in minimax worst-case robust intensity modulated proton therapy (IMPT) optimization. Methods and Materials: For the analysis, contoured computed tomography (CT) scans of 9 unilateral and 9 bilateral patients were used. An IMPT plan was considered robust if, for at least 98% of the simulated fractionated treatments, 98% of the CTV received 95% or more of the prescribed dose. For fast assessment of the CTV coverage for given error distributions (ie, different values of Σ, σ, and ρ), polynomial chaos methods were used. Separate recipes were derived for the unilateral and bilateral cases using one patient from each group, and all 18 patients were included in the validation of the recipes. Results: Treatment plans for bilateral cases are intrinsically more robust than those for unilateral cases. The required RR only depends on the ρ, and SR can be fitted by second-order polynomials in Σ and σ. The formulas for the derived robustness recipes are as follows: Unilateral patients need SR = −0.15Σ{sup 2} + 0.27σ{sup 2} + 1.85Σ − 0.06σ + 1.22 and RR=3% for ρ = 1% and ρ = 2%; bilateral patients need SR = −0.07Σ{sup 2} + 0.19σ{sup 2} + 1.34Σ − 0.07σ + 1.17 and RR=3% and 4% for ρ = 1% and 2%, respectively. For the recipe validation, 2 plans were generated for each of the 18 patients corresponding to Σ = σ = 1.5 mm and ρ = 0% and 2%. Thirty-four plans had adequate CTV coverage in 98% or more of the simulated fractionated treatments; the remaining 2 had adequate coverage in 97.8% and 97.9%. Conclusions: Robustness recipes were derived that can

Minimizing cache misses in an event-driven network server: A case study of TUX

DEFF Research Database (Denmark)

Bhatia, Sapan; Consel, Charles; Lawall, Julia Laetitia

2006-01-01

We analyze the performance of CPU-bound network servers and demonstrate experimentally that the degradation in the performance of these servers under high-concurrency workloads is largely due to inefficient use of the hardware caches. We then describe an approach to speeding up event-driven network...... servers by optimizing their use of the L2 CPU cache in the context of the TUX Web server, known for its robustness to heavy load. Our approach is based on a novel cache-aware memory allocator and a specific scheduling strategy that together ensure that the total working data set of the server stays...

Heterogeneous Bimetallic Phosphide/Sulfide Nanocomposite for Efficient Solar-Energy-Driven Overall Water Splitting.

Science.gov (United States)

Xin, Yanmei; Kan, Xiang; Gan, Li-Yong; Zhang, Zhonghai

2017-10-24

Solar-driven overall water splitting is highly desirable for hydrogen generation with sustainable energy sources, which need efficient, earth-abundant, robust, and bifunctional electrocatalysts for both oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). Herein, we propose a heterogeneous bimetallic phosphide/sulfide nanocomposite electrocatalyst of NiFeSP on nickel foam (NiFeSP/NF), which shows superior electrocatalytic activity of low overpotentials of 91 mV at -10 mA cm -2 for HER and of 240 mV at 50 mA cm -2 for OER in 1 M KOH solution. In addition, the NiFeSP/NF presents excellent overall water splitting performance with a cell voltage as low as 1.58 V at a current density of 10 mA cm -2 . Combining with a photovoltaic device of a Si solar cell or integrating into photoelectrochemical (PEC) systems, the bifunctional NiFeSP/NF electrocatalyst implements unassisted solar-driven water splitting with a solar-to-hydrogen conversion efficiency of ∼9.2% and significantly enhanced PEC performance, respectively.

Interleukin-6-driven progranulin expression increases cholangiocarcinoma growth by an Akt-dependent mechanism.

Science.gov (United States)

Frampton, Gabriel; Invernizzi, Pietro; Bernuzzi, Francesca; Pae, Hae Yong; Quinn, Matthew; Horvat, Darijana; Galindo, Cheryl; Huang, Li; McMillin, Matthew; Cooper, Brandon; Rimassa, Lorenza; DeMorrow, Sharon

2012-02-01

Cholangiocarcinoma is a devastating cancer of biliary origin with limited treatment options. The growth factor, progranulin, is overexpressed in a number of tumours. The study aims were to assess the expression of progranulin in cholangiocarcinoma and to determine its effects on tumour growth. The expression and secretion of progranulin were evaluated in multiple cholangiocarcinoma cell lines and in clinical samples from patients with cholangiocarcinoma. The role of interleukin 6 (IL-6)-mediated signalling in the expression of progranulin was assessed using a combination of specific inhibitors and shRNA knockdown techniques. The effect of progranulin on proliferation and Akt activation and subsequent effects of FOXO1 phosphorylation were assessed in vitro. Progranulin knockdown cell lines were established, and the effects on cholangiocarcinoma growth were determined. Progranulin expression and secretion were upregulated in cholangiocarcinoma cell lines and tissue, which were in part via IL-6-mediated activation of the ERK1/2/RSK1/C/EBPβ pathway. Blocking any of these signalling molecules, by either pharmacological inhibitors or shRNA, prevented the IL-6-dependent activation of progranulin expression. Treatment of cholangiocarcinoma cells with recombinant progranulin increased cell proliferation in vitro by a mechanism involving Akt phosphorylation leading to phosphorylation and nuclear extrusion of FOXO1. Knockdown of progranulin expression in cholangiocarcinoma cells decreased the expression of proliferating cellular nuclear antigen, a marker of proliferative capacity, and slowed tumour growth in vivo. Evidence is presented for a role for progranulin as a novel growth factor regulating cholangiocarcinoma growth. Specific targeting of progranulin may represent an alternative for the development of therapeutic strategies.

Comparative Study on Photovoltaic Pumping Systems Driven by Different Motors Optimized with Sliding Mode Control

Directory of Open Access Journals (Sweden)

Abdelhak Bouchakour

2017-06-01

Full Text Available This study investigates the performance of three different photovoltaic (PV water pumping systems driven by three types of motors, namely a separately excited DC motor (DCM, an asynchronous motor (ASM, and a permanent magnet synchronous motor (PMSM, via a DC/DC buck-boost converter coupled to a centrifugal pump. The purpose of this study is to implement a fast and robust control for this type of a nonlinear system, controlled by sliding mode (SM. This paper presents an SM control technique for controlling a DC/DC buck-boost converter to transfer the maximum power delivered by the PV generator. Each component is studied and analyzed to simulate the global system in MATLAB/SIMULINK. The three systems are then compared to determine the overall effectiveness of the proposed command. The study concludes that the ASM-driven PV system yields highly favorable results and requires less maintenance compared with other systems.

Sex-Dependent Gene Expression in Human Pluripotent Stem Cells

Directory of Open Access Journals (Sweden)

Daniel Ronen

2014-08-01

Full Text Available Males and females have a variety of sexually dimorphic traits, most of which result from hormonal differences. However, differences between male and female embryos initiate very early in development, before hormonal influence begins, suggesting the presence of genetically driven sexual dimorphisms. By comparing the gene expression profiles of male and X-inactivated female human pluripotent stem cells, we detected Y-chromosome-driven effects. We discovered that the sex-determining gene SRY is expressed in human male pluripotent stem cells and is induced by reprogramming. In addition, we detected more than 200 differentially expressed autosomal genes in male and female embryonic stem cells. Some of these genes are involved in steroid metabolism pathways and lead to sex-dependent differentiation in response to the estrogen precursor estrone. Thus, we propose that the presence of the Y chromosome and specifically SRY may drive sex-specific differences in the growth and differentiation of pluripotent stem cells.

Robust Building Energy Load Forecasting Using Physically-Based Kernel Models

Directory of Open Access Journals (Sweden)

Anand Krishnan Prakash

2018-04-01

Full Text Available Robust and accurate building energy load forecasting is important for helping building managers and utilities to plan, budget, and strategize energy resources in advance. With recent prevalent adoption of smart-meters in buildings, a significant amount of building energy consumption data became available. Many studies have developed physics-based white box models and data-driven black box models to predict building energy consumption; however, they require extensive prior knowledge about building system, need a large set of training data, or lack robustness to different forecasting scenarios. In this paper, we introduce a new building energy forecasting method based on Gaussian Process Regression (GPR that incorporates physical insights about load data characteristics to improve accuracy while reducing training requirements. The GPR is a non-parametric regression method that models the data as a joint Gaussian distribution with mean and covariance functions and forecast using the Bayesian updating. We model the covariance function of the GPR to reflect the data patterns in different forecasting horizon scenarios, as prior knowledge. Our method takes advantage of the modeling flexibility and computational efficiency of the GPR while benefiting from the physical insights to further improve the training efficiency and accuracy. We evaluate our method with three field datasets from two university campuses (Carnegie Mellon University and Stanford University for both short- and long-term load forecasting. The results show that our method performs more accurately, especially when the training dataset is small, compared to other state-of-the-art forecasting models (up to 2.95 times smaller prediction error.

A synergy-driven approach to a myoelectric hand.

Science.gov (United States)

Godfrey, S B; Ajoudani, A; Catalano, M; Grioli, G; Bicchi, A

2013-06-01

In this paper, we present the Pisa/IIT SoftHand with myoelectric control as a synergy-driven approach for a prosthetic hand. Commercially available myoelectric hands are more expensive, heavier, and less robust than their body-powered counterparts; however, they can offer greater freedom of motion and a more aesthetically pleasing appearance. The Pisa/IIT SoftHand is built on the motor control principle of synergies through which the immense complexity of the hand is simplified into distinct motor patterns. As the SoftHand grasps, it follows a synergistic path with built-in flexibility to allow grasping of a wide variety of objects with a single motor. Here we test, as a proof-of-concept, 4 myoelectric controllers: a standard controller in which the EMG signal is used only as a position reference, an impedance controller that determines both position and stiffness references from the EMG input, a standard controller with vibrotactile force feedback, and finally a combined vibrotactile-impedance (VI) controller. Four healthy subjects tested the control algorithms by grasping various objects. All controllers were sufficient for basic grasping, however the impedance and vibrotactile controllers reduced the physical and cognitive load on the user, while the combined VI mode was the easiest to use of the four. While these results need to be validated with amputees, they suggest a low-cost, robust hand employing hardware-based synergies is a viable alternative to traditional myoelectric prostheses.

Quantification of differential gene expression by multiplexed targeted resequencing of cDNA

Science.gov (United States)

Arts, Peer; van der Raadt, Jori; van Gestel, Sebastianus H.C.; Steehouwer, Marloes; Shendure, Jay; Hoischen, Alexander; Albers, Cornelis A.

2017-01-01

Whole-transcriptome or RNA sequencing (RNA-Seq) is a powerful and versatile tool for functional analysis of different types of RNA molecules, but sample reagent and sequencing cost can be prohibitive for hypothesis-driven studies where the aim is to quantify differential expression of a limited number of genes. Here we present an approach for quantification of differential mRNA expression by targeted resequencing of complementary DNA using single-molecule molecular inversion probes (cDNA-smMIPs) that enable highly multiplexed resequencing of cDNA target regions of ∼100 nucleotides and counting of individual molecules. We show that accurate estimates of differential expression can be obtained from molecule counts for hundreds of smMIPs per reaction and that smMIPs are also suitable for quantification of relative gene expression and allele-specific expression. Compared with low-coverage RNA-Seq and a hybridization-based targeted RNA-Seq method, cDNA-smMIPs are a cost-effective high-throughput tool for hypothesis-driven expression analysis in large numbers of genes (10 to 500) and samples (hundreds to thousands). PMID:28474677

Cardiac-specific expression of the tetracycline transactivator confers increased heart function and survival following ischemia reperfusion injury.

Directory of Open Access Journals (Sweden)

Laila Elsherif

Full Text Available Mice expressing the tetracycline transactivator (tTA transcription factor driven by the rat α-myosin heavy chain promoter (α-MHC-tTA are widely used to dissect the molecular mechanisms involved in cardiac development and disease. However, these α-MHC-tTA mice exhibit a gain-of-function phenotype consisting of robust protection against ischemia/reperfusion injury in both in vitro and in vivo models in the absence of associated cardiac hypertrophy or remodeling. Cardiac function, as assessed by echocardiography, did not differ between α-MHC-tTA and control animals, and there were no noticeable differences observed between the two groups in HW/TL ratio or LV end-diastolic and end-systolic dimensions. Protection against ischemia/reperfusion injury was assessed using isolated perfused hearts where α-MHC-tTA mice had robust protection against ischemia/reperfusion injury which was not blocked by pharmacological inhibition of PI3Ks with LY294002. Furthermore, α-MHC-tTA mice subjected to coronary artery ligation exhibited significantly reduced infarct size compared to control animals. Our findings reveal that α-MHC-tTA transgenic mice exhibit a gain-of-function phenotype consisting of robust protection against ischemia/reperfusion injury similar to cardiac pre- and post-conditioning effects. However, in contrast to classical pre- and post-conditioning, the α-MHC-tTA phenotype is not inhibited by the classic preconditioning inhibitor LY294002 suggesting involvement of a non-PI3K-AKT signaling pathway in this phenotype. Thus, further study of the α-MHC-tTA model may reveal novel molecular targets for therapeutic intervention during ischemic injury.

Age-Related Gene Expression in the Frontal Cortex Suggests Synaptic Function Changes in Specific Inhibitory Neuron Subtypes

Directory of Open Access Journals (Sweden)

Leon French

2017-05-01

Full Text Available Genome-wide expression profiling of the human brain has revealed genes that are differentially expressed across the lifespan. Characterizing these genes adds to our understanding of both normal functions and pathological conditions. Additionally, the specific cell-types that contribute to the motor, sensory and cognitive declines during aging are unclear. Here we test if age-related genes show higher expression in specific neural cell types. Our study leverages data from two sources of murine single-cell expression data and two sources of age-associations from large gene expression studies of postmortem human brain. We used nonparametric gene set analysis to test for age-related enrichment of genes associated with specific cell-types; we also restricted our analyses to specific gene ontology groups. Our analyses focused on a primary pair of single-cell expression data from the mouse visual cortex and age-related human post-mortem gene expression information from the orbitofrontal cortex. Additional pairings that used data from the hippocampus, prefrontal cortex, somatosensory cortex and blood were used to validate and test specificity of our findings. We found robust age-related up-regulation of genes that are highly expressed in oligodendrocytes and astrocytes, while genes highly expressed in layer 2/3 glutamatergic neurons were down-regulated across age. Genes not specific to any neural cell type were also down-regulated, possibly due to the bulk tissue source of the age-related genes. A gene ontology-driven dissection of the cell-type enriched genes highlighted the strong down-regulation of genes involved in synaptic transmission and cell-cell signaling in the Somatostatin (Sst neuron subtype that expresses the cyclin dependent kinase 6 (Cdk6 and in the vasoactive intestinal peptide (Vip neuron subtype expressing myosin binding protein C, slow type (Mybpc1. These findings provide new insights into cell specific susceptibility to normal aging

Visualization-based decision support for value-driven system design

Science.gov (United States)

Tibor, Elliott

In the past 50 years, the military, communication, and transportation systems that permeate our world, have grown exponentially in size and complexity. The development and production of these systems has seen ballooning costs and increased risk. This is particularly critical for the aerospace industry. The inability to deal with growing system complexity is a crippling force in the advancement of engineered systems. Value-Driven Design represents a paradigm shift in the field of design engineering that has potential to help counteract this trend. The philosophy of Value-Driven Design places the desires of the stakeholder at the forefront of the design process to capture true preferences and reveal system alternatives that were never previously thought possible. Modern aerospace engineering design problems are large, complex, and involve multiple levels of decision-making. To find the best design, the decision-maker is often required to analyze hundreds or thousands of combinations of design variables and attributes. Visualization can be used to support these decisions, by communicating large amounts of data in a meaningful way. Understanding the design space, the subsystem relationships, and the design uncertainties is vital to the advancement of Value-Driven Design as an accepted process for the development of more effective, efficient, robust, and elegant aerospace systems. This research investigates the use of multi-dimensional data visualization tools to support decision-making under uncertainty during the Value-Driven Design process. A satellite design system comprising a satellite, ground station, and launch vehicle is used to demonstrate effectiveness of new visualization methods to aid in decision support during complex aerospace system design. These methods are used to facilitate the exploration of the feasible design space by representing the value impact of system attribute changes and comparing the results of multi-objective optimization formulations

A theoretical and practical contribution to supply chain robustness:developing a schema for robustness in dyads

OpenAIRE

Durach, Christian F.

2016-01-01

Published in print by Universitätsverlag der TU Berlin, ISBN 978-3-7983-2812-9 (ISSN 1865-3170) This doctoral thesis develops four individual research studies on supply chain robustness. The overall goal of these studies is to develop a conceptual framework of supply chain robustness by consolidating current literature in the field, and, drawing on that framework, to construct a schema of determinants that facilitate robustness in buyer-supplier relationships. This research is motivated by...

Enhancing cytochrome P450-mediated conversions in P. pastoris through RAD52 over-expression and optimizing the cultivation conditions.

Science.gov (United States)

Wriessnegger, Tamara; Moser, Sandra; Emmerstorfer-Augustin, Anita; Leitner, Erich; Müller, Monika; Kaluzna, Iwona; Schürmann, Martin; Mink, Daniel; Pichler, Harald

2016-04-01

Cytochrome P450 enzymes (CYPs) play an essential role in the biosynthesis of various natural compounds by catalyzing regio- and stereospecific hydroxylation reactions. Thus, CYP activities are of great interest in the production of fine chemicals, pharmaceutical compounds or flavors and fragrances. Industrial applicability of CYPs has driven extensive research efforts aimed at improving the performance of these enzymes to generate robust biocatalysts. Recently, our group has identified CYP-mediated hydroxylation of (+)-valencene as a major bottleneck in the biosynthesis of trans-nootkatol and (+)-nootkatone in Pichia pastoris. In the current study, we aimed at enhancing CYP-mediated (+)-valencene hydroxylation by over-expressing target genes identified through transcriptome analysis in P. pastoris. Strikingly, over-expression of the DNA repair and recombination gene RAD52 had a distinctly positive effect on trans-nootkatol formation. Combining RAD52 over-expression with optimization of whole-cell biotransformation conditions, i.e. optimized media composition and cultivation at higher pH value, enhanced trans-nootkatol production 5-fold compared to the initial strain and condition. These engineering approaches appear to be generally applicable for enhanced hydroxylation of hydrophobic compounds in P. pastoris as confirmed here for two additional membrane-attached CYPs, namely the limonene-3-hydroxylase from Mentha piperita and the human CYP2D6. Copyright © 2016 Elsevier Inc. All rights reserved.

Combining shallow and deep processing for a robust, fast, deep-linguistic dependency parser

OpenAIRE

Schneider, G

2004-01-01

This paper describes Pro3Gres, a fast, robust, broad-coverage parser that delivers deep-linguistic grammatical relation structures as output, which are closer to predicate-argument structures and more informative than pure constituency structures. The parser stays as shallow as is possible for each task, combining shallow and deep-linguistic methods by integrating chunking and by expressing the majority of long-distance dependencies in a context-free way. It combines statistical and rule-base...

Effects-Driven IT Development

DEFF Research Database (Denmark)

Hertzum, Morten; Simonsen, Jesper

2010-01-01

We present effects-driven IT development as an instrument for pursuing and reinforcing Participatory Design (PD) when it is applied in commercial information technology (IT) projects. Effects-driven IT development supports the management of a sustained PD process throughout design and organizatio......We present effects-driven IT development as an instrument for pursuing and reinforcing Participatory Design (PD) when it is applied in commercial information technology (IT) projects. Effects-driven IT development supports the management of a sustained PD process throughout design...

A robust state-space kinetics-guided framework for dynamic PET image reconstruction

International Nuclear Information System (INIS)

Tong, S; Alessio, A M; Kinahan, P E; Liu, H; Shi, P

2011-01-01

Dynamic PET image reconstruction is a challenging issue due to the low SNR and the large quantity of spatio-temporal data. We propose a robust state-space image reconstruction (SSIR) framework for activity reconstruction in dynamic PET. Unlike statistically-based frame-by-frame methods, tracer kinetic modeling is incorporated to provide physiological guidance for the reconstruction, harnessing the temporal information of the dynamic data. Dynamic reconstruction is formulated in a state-space representation, where a compartmental model describes the kinetic processes in a continuous-time system equation, and the imaging data are expressed in a discrete measurement equation. Tracer activity concentrations are treated as the state variables, and are estimated from the dynamic data. Sampled-data H ∞ filtering is adopted for robust estimation. H ∞ filtering makes no assumptions on the system and measurement statistics, and guarantees bounded estimation error for finite-energy disturbances, leading to robust performance for dynamic data with low SNR and/or errors. This alternative reconstruction approach could help us to deal with unpredictable situations in imaging (e.g. data corruption from failed detector blocks) or inaccurate noise models. Experiments on synthetic phantom and patient PET data are performed to demonstrate feasibility of the SSIR framework, and to explore its potential advantages over frame-by-frame statistical reconstruction approaches.

A robust methodology for kinetic model parameter estimation for biocatalytic reactions

DEFF Research Database (Denmark)

Al-Haque, Naweed; Andrade Santacoloma, Paloma de Gracia; Lima Afonso Neto, Watson

2012-01-01

lead to globally optimized parameter values. In this article, a robust methodology to estimate parameters for biocatalytic reaction kinetic expressions is proposed. The methodology determines the parameters in a systematic manner by exploiting the best features of several of the current approaches...... parameters, which are strongly correlated with each other. State-of-the-art methodologies such as nonlinear regression (using progress curves) or graphical analysis (using initial rate data, for example, the Lineweaver-Burke plot, Hanes plot or Dixon plot) often incorporate errors in the estimates and rarely...

Robust control design with MATLAB

CERN Document Server

Gu, Da-Wei; Konstantinov, Mihail M

2013-01-01

Robust Control Design with MATLAB® (second edition) helps the student to learn how to use well-developed advanced robust control design methods in practical cases. To this end, several realistic control design examples from teaching-laboratory experiments, such as a two-wheeled, self-balancing robot, to complex systems like a flexible-link manipulator are given detailed presentation. All of these exercises are conducted using MATLAB® Robust Control Toolbox 3, Control System Toolbox and Simulink®. By sharing their experiences in industrial cases with minimum recourse to complicated theories and formulae, the authors convey essential ideas and useful insights into robust industrial control systems design using major H-infinity optimization and related methods allowing readers quickly to move on with their own challenges. The hands-on tutorial style of this text rests on an abundance of examples and features for the second edition: ·        rewritten and simplified presentation of theoretical and meth...

Robust Portfolio Optimization Using Pseudodistances

Science.gov (United States)

2015-01-01

The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature. PMID:26468948

Robust Portfolio Optimization Using Pseudodistances.

Science.gov (United States)

Toma, Aida; Leoni-Aubin, Samuela

2015-01-01

The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature.

Threat driven modeling framework using petri nets for e-learning system.

Science.gov (United States)

Khamparia, Aditya; Pandey, Babita

2016-01-01

Vulnerabilities at various levels are main cause of security risks in e-learning system. This paper presents a modified threat driven modeling framework, to identify the threats after risk assessment which requires mitigation and how to mitigate those threats. To model those threat mitigations aspects oriented stochastic petri nets are used. This paper included security metrics based on vulnerabilities present in e-learning system. The Common Vulnerability Scoring System designed to provide a normalized method for rating vulnerabilities which will be used as basis in metric definitions and calculations. A case study has been also proposed which shows the need and feasibility of using aspect oriented stochastic petri net models for threat modeling which improves reliability, consistency and robustness of the e-learning system.

How Robust is Your System Resilience?

Science.gov (United States)

Homayounfar, M.; Muneepeerakul, R.

2017-12-01

Robustness and resilience are concepts in system thinking that have grown in importance and popularity. For many complex social-ecological systems, however, robustness and resilience are difficult to quantify and the connections and trade-offs between them difficult to study. Most studies have either focused on qualitative approaches to discuss their connections or considered only one of them under particular classes of disturbances. In this study, we present an analytical framework to address the linkage between robustness and resilience more systematically. Our analysis is based on a stylized dynamical model that operationalizes a widely used concept framework for social-ecological systems. The model enables us to rigorously define robustness and resilience and consequently investigate their connections. The results reveal the tradeoffs among performance, robustness, and resilience. They also show how the nature of the such tradeoffs varies with the choices of certain policies (e.g., taxation and investment in public infrastructure), internal stresses and external disturbances.

International Conference on Robust Statistics 2015

CERN Document Server

Basu, Ayanendranath; Filzmoser, Peter; Mukherjee, Diganta

2016-01-01

This book offers a collection of recent contributions and emerging ideas in the areas of robust statistics presented at the International Conference on Robust Statistics 2015 (ICORS 2015) held in Kolkata during 12–16 January, 2015. The book explores the applicability of robust methods in other non-traditional areas which includes the use of new techniques such as skew and mixture of skew distributions, scaled Bregman divergences, and multilevel functional data methods; application areas being circular data models and prediction of mortality and life expectancy. The contributions are of both theoretical as well as applied in nature. Robust statistics is a relatively young branch of statistical sciences that is rapidly emerging as the bedrock of statistical analysis in the 21st century due to its flexible nature and wide scope. Robust statistics supports the application of parametric and other inference techniques over a broader domain than the strictly interpreted model scenarios employed in classical statis...

Parental Expressiveness as a Moderator of Coparenting and Marital Relationship Quality

Science.gov (United States)

Kolak, Amy M.; Volling, Brenda L.

2007-01-01

Driven by theory and extant research on the communication of emotions within the family, the current investigation examined marital quality and parents' emotional expressiveness as determinants of coparenting in a sample of 57 couples with young children. Specifically, mothers' and fathers' expressiveness was examined as moderators of the…

Robustness of IPTV business models

NARCIS (Netherlands)

Bouwman, H.; Zhengjia, M.; Duin, P. van der; Limonard, S.

2008-01-01

The final stage in the STOF method is an evaluation of the robustness of the design, for which the method provides some guidelines. For many innovative services, the future holds numerous uncertainties, which makes evaluating the robustness of a business model a difficult task. In this chapter, we

Robust Design Impact Metrics: Measuring the effect of implementing and using Robust Design

DEFF Research Database (Denmark)

Ebro, Martin; Olesen, Jesper; Howard, Thomas J.

2014-01-01

Measuring the performance of an organisation’s product development process can be challenging due to the limited use of metrics in R&D. An organisation considering whether to use Robust Design as an integrated part of their development process may find it difficult to define whether it is relevant......, and afterwards measure the effect of having implemented it. This publication identifies and evaluates Robust Design-related metrics and finds that 2 metrics are especially useful: 1) Relative amount of R&D Resources spent after Design Verification and 2) Number of ‘change notes’ after Design Verification....... The metrics have been applied in a case company to test the assumptions made during the evaluation. It is concluded that the metrics are useful and relevant, but further work is necessary to make a proper overview and categorisation of different types of robustness related metrics....

Modeling the dynamics of the lead bismuth eutectic experimental accelerator driven system by an infinite impulse response locally recurrent neural network

International Nuclear Information System (INIS)

Zio, Enrico; Pedroni, Nicola; Broggi, Matteo; Golea, Lucia Roxana

2009-01-01

In this paper, an infinite impulse response locally recurrent neural network (IIR-LRNN) is employed for modelling the dynamics of the Lead Bismuth Eutectic eXperimental Accelerator Driven System (LBE-XADS). The network is trained by recursive back-propagation (RBP) and its ability in estimating transients is tested under various conditions. The results demonstrate the robustness of the locally recurrent scheme in the reconstruction of complex nonlinear dynamic relationships

Differential transcriptome analysis between Populus and its synthesized allotriploids driven by second-division restitution.

Science.gov (United States)

Cheng, Shiping; Huang, Zhen; Li, Yun; Liao, Ting; Suo, Yujing; Zhang, Pingdong; Wang, Jun; Kang, Xiangyang

2015-12-01

In this report, we compared transcriptomic differences between a synthetic Populus section Tacamahaca triploid driven by second-division restitution and its parents using a high-throughput RNA-seq method. A total of 4,080 genes were differentially expressed between the high-growth vigor allotriploids (SDR-H) and their parents, and 719 genes were non-additively expressed in SDR-H. Differences in gene expression between the allotriploid and male parent were more significant than those between the allotriploid and female parent, which may be caused by maternal effects. We observed 3,559 differentially expressed genes (DEGs) between the SDR-H and male parent. Notably, the genes were mainly involved in metabolic process, cell proliferation, DNA methylation, cell division, and meristem and developmental growth. Among the 1,056 DEGs between SDR-H and female parent, many genes were associated with metabolic process and carbon utilization. In addition, 1,789 DEGs between high- and low-growth vigor allotriploid were mainly associated with metabolic process, auxin poplar transport, and regulation of meristem growth. Our results indicated that the higher poplar ploidy level can generate extensive transcriptomic diversity compared with its parents. Overall, these results increased our understanding of the driving force for phenotypic variation and adaptation in allopolyploids driven by second-division restitution. © 2015 Institute of Botany, Chinese Academy of Sciences.

Robust loss functions for boosting.

Science.gov (United States)

Kanamori, Takafumi; Takenouchi, Takashi; Eguchi, Shinto; Murata, Noboru

2007-08-01

Boosting is known as a gradient descent algorithm over loss functions. It is often pointed out that the typical boosting algorithm, Adaboost, is highly affected by outliers. In this letter, loss functions for robust boosting are studied. Based on the concept of robust statistics, we propose a transformation of loss functions that makes boosting algorithms robust against extreme outliers. Next, the truncation of loss functions is applied to contamination models that describe the occurrence of mislabels near decision boundaries. Numerical experiments illustrate that the proposed loss functions derived from the contamination models are useful for handling highly noisy data in comparison with other loss functions.

Robustness of airline route networks

Science.gov (United States)

Lordan, Oriol; Sallan, Jose M.; Escorihuela, Nuria; Gonzalez-Prieto, David

2016-03-01

Airlines shape their route network by defining their routes through supply and demand considerations, paying little attention to network performance indicators, such as network robustness. However, the collapse of an airline network can produce high financial costs for the airline and all its geographical area of influence. The aim of this study is to analyze the topology and robustness of the network route of airlines following Low Cost Carriers (LCCs) and Full Service Carriers (FSCs) business models. Results show that FSC hubs are more central than LCC bases in their route network. As a result, LCC route networks are more robust than FSC networks.

Expression-dependent susceptibility to face distortions in processing of facial expressions of emotion.

Science.gov (United States)

Guo, Kun; Soornack, Yoshi; Settle, Rebecca

2018-03-05

Our capability of recognizing facial expressions of emotion under different viewing conditions implies the existence of an invariant expression representation. As natural visual signals are often distorted and our perceptual strategy changes with external noise level, it is essential to understand how expression perception is susceptible to face distortion and whether the same facial cues are used to process high- and low-quality face images. We systematically manipulated face image resolution (experiment 1) and blur (experiment 2), and measured participants' expression categorization accuracy, perceived expression intensity and associated gaze patterns. Our analysis revealed a reasonable tolerance to face distortion in expression perception. Reducing image resolution up to 48 × 64 pixels or increasing image blur up to 15 cycles/image had little impact on expression assessment and associated gaze behaviour. Further distortion led to decreased expression categorization accuracy and intensity rating, increased reaction time and fixation duration, and stronger central fixation bias which was not driven by distortion-induced changes in local image saliency. Interestingly, the observed distortion effects were expression-dependent with less deterioration impact on happy and surprise expressions, suggesting this distortion-invariant facial expression perception might be achieved through the categorical model involving a non-linear configural combination of local facial features. Copyright © 2018 Elsevier Ltd. All rights reserved.

Nigrostriatal and Mesolimbic D2/3 Receptor Expression in Parkinson's Disease Patients with Compulsive Reward-Driven Behaviors.

Science.gov (United States)

Stark, Adam J; Smith, Christopher T; Lin, Ya-Chen; Petersen, Kalen J; Trujillo, Paula; van Wouwe, Nelleke C; Kang, Hakmook; Donahue, Manus J; Kessler, Robert M; Zald, David H; Claassen, Daniel O

2018-03-28

The nigrostriatal and mesocorticolimbic dopamine networks regulate reward-driven behavior. Regional alterations to mesolimbic dopamine D 2/3 receptor expression are described in drug-seeking and addiction disorders. Parkinson's disease (PD) patients are frequently prescribed D 2 -like dopamine agonist (DAgonist) therapy for motor symptoms, yet a proportion develop clinically significant behavioral addictions characterized by impulsive and compulsive behaviors (ICBs). Until now, changes in D 2/3 receptor binding in both striatal and extrastriatal regions have not been concurrently quantified in this population. We identified 35 human PD patients (both male and female) receiving DAgonist therapy, with ( n = 17) and without ( n = 18) ICBs, matched for age, disease duration, disease severity, and dose of dopamine therapy. In the off-dopamine state, all completed PET imaging with [ 18 F]fallypride, a high affinity D 2 -like receptor ligand that can measure striatal and extrastriatal D 2/3 nondisplaceable binding potential (BP ND ). Striatal differences between ICB+/ICB- patients localized to the ventral striatum and putamen, where ICB+ subjects had reduced BP ND In this group, self-reported severity of ICB symptoms positively correlated with midbrain D 2/3 receptor BP ND Group differences in regional D 2/3 BP ND relationships were also notable: ICB+ (but not ICB-) patients expressed positive correlations between midbrain and caudate, putamen, globus pallidus, and amygdala BP ND s. These findings support the hypothesis that compulsive behaviors in PD are associated with reduced ventral and dorsal striatal D 2/3 expression, similar to changes in comparable behavioral disorders. The data also suggest that relatively preserved ventral midbrain dopaminergic projections throughout nigrostriatal and mesolimbic networks are characteristic of ICB+ patients, and may account for differential DAgonist therapeutic response. SIGNIFICANCE STATEMENT The biologic determinants of

Lack of promoter IV-driven BDNF transcription results in depression-like behavior.

Science.gov (United States)

Sakata, K; Jin, L; Jha, S

2010-10-01

Transcription of Bdnf is controlled by multiple promoters, in which promoter IV contributes significantly to activity-dependent Bdnf transcription. We have generated promoter IV mutant mice [brain-derived neurotrophic factor (BDNF)-KIV] in which promoter IV-driven expression of BDNF is selectively disrupted by inserting a green fluorescent protein (GFP)-STOP cassette within the Bdnf exon IV locus. BDNF-KIV animals exhibited depression-like behavior as shown by the tail suspension test (TST), sucrose preference test (SPT) and learned helplessness test (LHT). In addition, BDNF-KIV mice showed reduced activity in the open field test (OFT) and reduced food intake in the novelty-suppressed feeding test (NSFT). The mutant mice did not display anxiety-like behavior in the light and dark box test and elevated plus maze tests. Interestingly, the mutant mice showed defective response inhibition in the passive avoidance test (PAT) even though their learning ability was intact when measured with the active avoidance test (AAT). These results suggest that promoter IV-dependent BDNF expression plays a critical role in the control of mood-related behaviors. This is the first study that directly addressed the effects of endogenous promoter-driven expression of BDNF in depression-like behavior. © 2010 The Authors. Genes, Brain and Behavior © 2010 Blackwell Publishing Ltd and International Behavioural and Neural Genetics Society.

Metric-driven Robust Design – Robustness Quantification of Complex Engineering Systems

DEFF Research Database (Denmark)

Göhler, Simon Moritz

2017-01-01

by the Danish Council for Strategic Research. Other supporters of the project have been MAN Diesel & Turbo A/S, DTU Mechanical Engineering, DTU Chemical Engineering, Sandia National Laboratories USA, Norwegian University of Science & Technology (NTNU) and University of Nottingham, Malaysia Campus......This PhD dissertation was carried out at the Technical University of Denmark in the Department of Mechanical Engineering and has been supervised by Associate Professor Anders Ivarsson and co-supervised by Professor Jesper Schramm. The project has been a part of the RADIADE project funded....... The continuing stringency of emission regulations for marine diesel engines forces a deeper understanding of the complex physical processes occurring inside the engine cylinder. A deeper understanding can lead to higher accuracy of predictive numerical models, thereby enabling evaluation of multiple engine...

Multimodel Robust Control for Hydraulic Turbine

OpenAIRE

Osuský, Jakub; Števo, Stanislav

2014-01-01

The paper deals with the multimodel and robust control system design and their combination based on M-Δ structure. Controller design will be done in the frequency domain with nominal performance specified by phase margin. Hydraulic turbine model is analyzed as system with unstructured uncertainty, and robust stability condition is included in controller design. Multimodel and robust control approaches are presented in detail on hydraulic turbine model. Control design approaches are compared a...

The Receptive-Expressive Gap in the Vocabulary of Young Second-Language Learners: Robustness and Possible Mechanisms

Science.gov (United States)

Gibson, Todd A.; Oller, D. Kimbrough; Jarmulowicz, Linda; Ethington, Corinna A.

2012-01-01

Adults and children learning a second language show difficulty accessing expressive vocabulary that appears accessible receptively in their first language (L1). We call this discrepancy the receptive-expressive gap. Kindergarten Spanish (L1)-English (L2) sequential bilinguals were given standardized tests of receptive and expressive vocabulary in…

Robustness of Linear Systems towards Multi-Dissipative Pertubations

DEFF Research Database (Denmark)

Thygesen, Uffe Høgsbro; Poulsen, Niels Kjølstad

1997-01-01

We consider the question of robust stability of a linear time invariant plant subject to dynamic perturbations, which are dissipative in the sense of Willems with respect to several quadratic supply rates. For instance, parasitic dynamics are often both small gain and passive. We reduce several...... robustness analysis questions to linear matrix inequalities: robust stability, robust H2 performance and robust performance in presence of disturbances with finite signal-to-noise ratios...

Troponin T isoform expression is modulated during Atlantic Halibut metamorphosis

Directory of Open Access Journals (Sweden)

Llewellyn Lynda

2007-06-01

Full Text Available Abstract Background Flatfish metamorphosis is a thyroid hormone (TH driven process which leads to a dramatic change from a symmetrical larva to an asymmetrical juvenile. The effect of THs on muscle and in particular muscle sarcomer protein genes is largely unexplored in fish. The change in Troponin T (TnT, a pivotal protein in the assembly of skeletal muscles sarcomeres and a modulator of calcium driven muscle contraction, during flatfish metamophosis is studied. Results In the present study five cDNAs for halibut TnT genes were cloned; three were splice variants arising from a single fast TnT (fTnT gene; a fourth encoded a novel teleost specific fTnT-like cDNA (AfTnT expressed exclusively in slow muscle and the fifth encoded the teleost specific sTnT2. THs modified the expression of halibut fTnT isoforms which changed from predominantly basic to acidic isoforms during natural and T4 induced metamorphosis. In contrast, expression of red muscle specific genes, AfTnT and sTnT2, did not change during natural metamorphosis or after T4 treatment. Prior to and after metamorphosis no change in the dorso-ventral symmetry or temporal-spatial expression pattern of TnT genes and muscle fibre organization occurred in halibut musculature. Conclusion Muscle organisation in halibut remains symmetrical even after metamorphosis suggesting TH driven changes are associated with molecular adaptations. We hypothesize that species specific differences in TnT gene expression in teleosts underlies different larval muscle developmental programs which better adapts them to the specific ecological constraints.

TMPRSS2- driven ERG expression in vivo increases self-renewal and maintains expression in a castration resistant subpopulation.

Directory of Open Access Journals (Sweden)

Orla M Casey

Full Text Available Genomic rearrangements commonly occur in many types of cancers and often initiate or alter the progression of disease. Here we describe an in vivo mouse model that recapitulates the most frequent rearrangement in prostate cancer, the fusion of the promoter region of TMPRSS2 with the coding region of the transcription factor, ERG. A recombinant bacterial artificial chromosome including an extended TMPRSS2 promoter driving genomic ERG was constructed and used for transgenesis in mice. TMPRSS2-ERG expression was evaluated in tissue sections and FACS-fractionated prostate cell populations. In addition to the anticipated expression in luminal cells, TMPRSS2-ERG was similarly expressed in the Sca-1(hi/EpCAM(+ basal/progenitor fraction, where expanded numbers of clonogenic self-renewing progenitors were found, as assayed by in vitro sphere formation. These clonogenic cells increased intrinsic self renewal in subsequent generations. In addition, ERG dependent self-renewal and invasion in vitro was demonstrated in prostate cell lines derived from the model. Clinical studies have suggested that the TMPRSS2-ERG translocation occurs early in prostate cancer development. In the model described here, the presence of the TMPRSS2-ERG fusion alone was not transforming but synergized with heterozygous Pten deletion to promote PIN. Taken together, these data suggest that one function of TMPRSS2-ERG is the expansion of self-renewing cells, which may serve as targets for subsequent mutations. Primary prostate epithelial cells demonstrated increased post transcriptional turnover of ERG compared to the TMPRSS2-ERG positive VCaP cell line, originally isolated from a prostate cancer metastasis. Finally, we determined that TMPRSS2-ERG expression occurred in both castration-sensitive and resistant prostate epithelial subpopulations, suggesting the existence of androgen-independent mechanisms of TMPRSS2 expression in prostate epithelium.

Robust adaptive synchronization of general dynamical networks ...

Indian Academy of Sciences (India)

Home; Journals; Pramana – Journal of Physics; Volume 86; Issue 6. Robust ... A robust adaptive synchronization scheme for these general complex networks with multiple delays and uncertainties is established and raised by employing the robust adaptive control principle and the Lyapunov stability theory. We choose ...

Robust synthesis for real-time systems

DEFF Research Database (Denmark)

Larsen, Kim Guldstrand; Legay, Axel; Traonouez, Luois-Marie

2014-01-01

Specification theories for real-time systems allow reasoning about interfaces and their implementation models, using a set of operators that includes satisfaction, refinement, logical and parallel composition. To make such theories applicable throughout the entire design process from an abstract...... of introducing small perturbations into formal models. We address this problem of robust implementations in timed specification theories. We first consider a fixed perturbation and study the robustness of timed specifications with respect to the operators of the theory. To this end we synthesize robust...... specification to an implementation, we need to reason about the possibility to effectively implement the theoretical specifications on physical systems, despite their limited precision. In the literature, this implementation problem has been linked to the robustness problem that analyzes the consequences...

Comparison between two braking control methods integrating energy recovery for a two-wheel front driven electric vehicle

International Nuclear Information System (INIS)

Itani, Khaled; De Bernardinis, Alexandre; Khatir, Zoubir; Jammal, Ahmad

2016-01-01

Highlights: • Comparison between two braking methods for an EV maximizing the energy recovery. • Wheels slip ratio control based on robust sliding mode and ECE R13 control methods. • Regenerative braking control strategy. • Energy recovery of a HESS with respect to road surface type and road condition. - Abstract: This paper presents the comparison between two braking methods for a two-wheel front driven Electric Vehicle maximizing the energy recovery on the Hybrid Energy Storage System. The first method consists in controlling the wheels slip ratio while braking using a robust sliding mode controller. The second method will be based on ECE R13H constraints for an M1 passenger vehicle. The vehicle model used for simulation is a simplified five degrees of freedom model. It is driven by two 30 kW permanent magnet synchronous motor (PMSM) recovering energy during braking phases. Several simulation results for extreme braking conditions will be performed and compared on various road type surfaces using Matlab/Simulink®. For an initial speed of 80 km/h, simulation results demonstrate that the difference of energy recovery efficiency between the two control braking methods is beneficial to the ECE constraints control method and it can vary from 3.7% for high friction road type to 11.2% for medium friction road type. At low friction road type, the difference attains 6.6% due to different reasons treated in the paper. The stability deceleration is also discussed and detailed.

Hybrid lattice Boltzmann finite difference simulation of mixed convection flows in a lid-driven square cavity

Energy Technology Data Exchange (ETDEWEB)

Bettaibi, Soufiene, E-mail: Bettaibisoufiene@gmail.com [UR: Rayonnement Thermique, Faculté des Sciences de Tunis, Université de Tunis El Manar, 2092 Tunis (Tunisia); Kuznik, Frédéric [INSA-Lyon, CETHIL, F-69621 Villeurbanne (France); Université de Lyon, CNRS, UMR5008, F-69622 Villeurbanne (France); Sediki, Ezeddine [UR: Rayonnement Thermique, Faculté des Sciences de Tunis, Université de Tunis El Manar, 2092 Tunis (Tunisia)

2014-06-27

Highlights: • Mixed convection heat transfer in 2D lid-driven cavity is studied numerically. • Hybrid scheme with multiple relaxation time lattice Boltzmann method is used to obtain the velocity field. • Finite difference method is used to compute the temperature. • Effect of both Richardson and Reynolds numbers for mixed convection is studied. - Abstract: Mixed convection heat transfer in two-dimensional lid-driven rectangular cavity filled with air (Pr=0.71) is studied numerically. A hybrid scheme with multiple relaxation time lattice Boltzmann method (MRT-LBM) is used to obtain the velocity field while the temperature field is deduced from energy balance equation by using the finite difference method (FDM). The main objective of this work is to investigate the model effectiveness for mixed convection flow simulation. Results are presented in terms of streamlines, isotherms and Nusselt numbers. Excellent agreement is obtained between our results and previous works. The different comparisons demonstrate the robustness and the accuracy of our proposed approach.

A Novel Evolutionary Algorithm for Designing Robust Analog Filters

Directory of Open Access Journals (Sweden)

Shaobo Li

2018-03-01

Full Text Available Designing robust circuits that withstand environmental perturbation and device degradation is critical for many applications. Traditional robust circuit design is mainly done by tuning parameters to improve system robustness. However, the topological structure of a system may set a limit on the robustness achievable through parameter tuning. This paper proposes a new evolutionary algorithm for robust design that exploits the open-ended topological search capability of genetic programming (GP coupled with bond graph modeling. We applied our GP-based robust design (GPRD algorithm to evolve robust lowpass and highpass analog filters. Compared with a traditional robust design approach based on a state-of-the-art real-parameter genetic algorithm (GA, our GPRD algorithm with a fitness criterion rewarding robustness, with respect to parameter perturbations, can evolve more robust filters than what was achieved through parameter tuning alone. We also find that inappropriate GA tuning may mislead the search process and that multiple-simulation and perturbed fitness evaluation methods for evolving robustness have complementary behaviors with no absolute advantage of one over the other.

DDB1-Mediated CRY1 Degradation Promotes FOXO1-Driven Gluconeogenesis in Liver.

Science.gov (United States)

Tong, Xin; Zhang, Deqiang; Charney, Nicholas; Jin, Ethan; VanDommelen, Kyle; Stamper, Kenneth; Gupta, Neil; Saldate, Johnny; Yin, Lei

2017-10-01

Targeted protein degradation through ubiquitination is an important step in the regulation of glucose metabolism. Here, we present evidence that the DDB1-CUL4A ubiquitin E3 ligase functions as a novel metabolic regulator that promotes FOXO1-driven hepatic gluconeogenesis. In vivo, hepatocyte-specific Ddb1 deletion leads to impaired hepatic gluconeogenesis in the mouse liver but protects mice from high-fat diet-induced hyperglycemia. Lack of Ddb1 downregulates FOXO1 protein expression and impairs FOXO1-driven gluconeogenic response. Mechanistically, we discovered that DDB1 enhances FOXO1 protein stability via degrading the circadian protein cryptochrome 1 (CRY1), a known target of DDB1 E3 ligase. In the Cry1 depletion condition, insulin fails to reduce the nuclear FOXO1 abundance and suppress gluconeogenic gene expression. Chronic depletion of Cry1 in the mouse liver not only increases FOXO1 protein but also enhances hepatic gluconeogenesis. Thus, we have identified the DDB1-mediated CRY1 degradation as an important target of insulin action on glucose homeostasis. © 2017 by the American Diabetes Association.

REINA at CLEF 2007 Robust Task

OpenAIRE

Zazo Rodríguez, Ángel Francisco; Figuerola, Carlos G.; Alonso Berrocal, José Luis

2007-01-01

This paper describes our work at CLEF 2007 Robust Task. We have participated in the monolingual (English, French and Portuguese) and the bilingual (English to French) subtask. At CLEF 2006 our research group obtained very good results applying local query expansion using windows of terms in the robust task. This year we have used the same expansion technique, but taking into account some criteria of robustness: MAP, GMAP, MMR, GS@10, P@10, number of failed topics, number of topics bellow 0.1 ...

Elimination of proliferating cells from CNS grafts using a Ki67 promoter-driven thymidine kinase

Directory of Open Access Journals (Sweden)

Vannary Tieng

2016-01-01

Full Text Available Pluripotent stem cell (PSC-based cell therapy is an attractive concept for neurodegenerative diseases, but can lead to tumor formation. This is particularly relevant as proliferating neural precursors rather than postmitotic mature neurons need to be transplanted. Thus, safety mechanisms to eliminate proliferating cells are needed. Here, we propose a suicide gene approach, based on cell cycle-dependent promoter Ki67-driven expression of herpes simplex virus thymidine kinase (HSV-TK. We generated a PSC line expressing this construct and induced neural differentiation. In vitro, proliferating PSC and early neural precursor cells (NPC were killed by exposure to ganciclovir. In vivo, transplantation of PSC led to tumor formation, which was prevented by early ganciclovir treatment. Transplanted NPC did not lead to tumor formation and their survival and neural maturation were not affected by ganciclovir. In conclusion, the cell cycle promoter-driven suicide gene approach described in this study allows killing of proliferating undifferentiated precursor cells without expression of the suicide gene in mature neurons. This approach could also be of use for other stem cell-based therapies where the final target consists of postmitotic cells.

Decisional tool to assess current and future process robustness in an antibody purification facility.

Science.gov (United States)

Stonier, Adam; Simaria, Ana Sofia; Smith, Martin; Farid, Suzanne S

2012-07-01

Increases in cell culture titers in existing facilities have prompted efforts to identify strategies that alleviate purification bottlenecks while controlling costs. This article describes the application of a database-driven dynamic simulation tool to identify optimal purification sizing strategies and visualize their robustness to future titer increases. The tool harnessed the benefits of MySQL to capture the process, business, and risk features of multiple purification options and better manage the large datasets required for uncertainty analysis and optimization. The database was linked to a discrete-event simulation engine so as to model the dynamic features of biopharmaceutical manufacture and impact of resource constraints. For a given titer, the tool performed brute force optimization so as to identify optimal purification sizing strategies that minimized the batch material cost while maintaining the schedule. The tool was applied to industrial case studies based on a platform monoclonal antibody purification process in a multisuite clinical scale manufacturing facility. The case studies assessed the robustness of optimal strategies to batch-to-batch titer variability and extended this to assess the long-term fit of the platform process as titers increase from 1 to 10 g/L, given a range of equipment sizes available to enable scale intensification efforts. Novel visualization plots consisting of multiple Pareto frontiers with tie-lines connecting the position of optimal configurations over a given titer range were constructed. These enabled rapid identification of robust purification configurations given titer fluctuations and the facility limit that the purification suites could handle in terms of the maximum titer and hence harvest load. Copyright © 2012 American Institute of Chemical Engineers (AIChE).

A Robust Longitudinal Control Strategy of Platoons under Model Uncertainties and Time Delays

Directory of Open Access Journals (Sweden)

Na Chen

2018-01-01

Full Text Available Automated vehicles are designed to free drivers from driving tasks and are expected to improve traffic safety and efficiency when connected via vehicle-to-vehicle communication, that is, connected automated vehicles (CAVs. The time delays and model uncertainties in vehicle control systems pose challenges for automated driving in real world. Ignoring them may render the performance of cooperative driving systems unsatisfactory or even unstable. This paper aims to design a robust and flexible platooning control strategy for CAVs. A centralized control method is presented, where the leader of a CAV platoon collects information from followers, computes the desired accelerations of all controlled vehicles, and broadcasts the desired accelerations to followers. The robust platooning is formulated as a Min-Max Model Predictive Control (MM-MPC problem, where optimal accelerations are generated to minimize the cost function under the worst case, where the worst case is taken over the possible models. The proposed method is flexible in such a way that it can be applied to both homogeneous platoon and heterogeneous platoon with mixed human-driven and automated controlled vehicles. A third-order linear vehicle model with fixed feedback delay and stochastic actuator lag is used to predict the platoon behavior. Actuator lag is assumed to vary randomly with unknown distributions but a known upper bound. The controller regulates platoon accelerations over a time horizon to minimize a cost function representing driving safety, efficiency, and ride comfort, subject to speed limits, plausible acceleration range, and minimal net spacing. The designed strategy is tested by simulating homogeneous and heterogeneous platoons in a number of typical and extreme scenarios to assess the system stability and performance. The test results demonstrate that the designed control strategy for CAV can ensure the robustness of stability and performance against model uncertainties

The Variation Management Framework (VMF) for Robust Design

DEFF Research Database (Denmark)

Howard, Thomas J.; Ebro, Martin; Eifler, Tobias

2014-01-01

Robust Design is an approach to reduce the effects of variation. There are numerous tools,methods and models associated with robust design, however, there is both a lack of a processmodel formalising the step of a robust design process and a framework tying the models together.In this paper we pr...... in the market place and identifies areaswhere action can be taken against variation. An additional benefit of the framework is that itmakes the link between visual/sensory/perceptual robustness, product robustness, and productionvariation (Six Sigma)....

Robust reflective ghost imaging against different partially polarized thermal light

Science.gov (United States)

Li, Hong-Guo; Wang, Yan; Zhang, Rui-Xue; Zhang, De-Jian; Liu, Hong-Chao; Li, Zong-Guo; Xiong, Jun

2018-03-01

We theoretically study the influence of degree of polarization (DOP) of thermal light on the contrast-to-noise ratio (CNR) of the reflective ghost imaging (RGI), which is a novel and indirect imaging modality. An expression for the CNR of RGI with partially polarized thermal light is carefully derived, which suggests a weak dependence of CNR on the DOP, especially when the ratio of the object size to the speckle size of thermal light has a large value. Different from conventional imaging approaches, our work reveals that RGI is much more robust against the DOP of the light source, which thereby has advantages in practical applications, such as remote sensing.

Light-Driven Alignment

CERN Document Server

Antonyuk, Boris P

2009-01-01

This book deals with influencing the properties of solids by light-driven electron transport. The theoretical basis of these effects, light-driven ordering and self-organisation, as well as optical motors are presented. With light as a tool, new ways to produce materials are opened.

Measure of robustness for complex networks

Science.gov (United States)

Youssef, Mina Nabil

Critical infrastructures are repeatedly attacked by external triggers causing tremendous amount of damages. Any infrastructure can be studied using the powerful theory of complex networks. A complex network is composed of extremely large number of different elements that exchange commodities providing significant services. The main functions of complex networks can be damaged by different types of attacks and failures that degrade the network performance. These attacks and failures are considered as disturbing dynamics, such as the spread of viruses in computer networks, the spread of epidemics in social networks, and the cascading failures in power grids. Depending on the network structure and the attack strength, every network differently suffers damages and performance degradation. Hence, quantifying the robustness of complex networks becomes an essential task. In this dissertation, new metrics are introduced to measure the robustness of technological and social networks with respect to the spread of epidemics, and the robustness of power grids with respect to cascading failures. First, we introduce a new metric called the Viral Conductance (VCSIS ) to assess the robustness of networks with respect to the spread of epidemics that are modeled through the susceptible/infected/susceptible (SIS) epidemic approach. In contrast to assessing the robustness of networks based on a classical metric, the epidemic threshold, the new metric integrates the fraction of infected nodes at steady state for all possible effective infection strengths. Through examples, VCSIS provides more insights about the robustness of networks than the epidemic threshold. In addition, both the paradoxical robustness of Barabasi-Albert preferential attachment networks and the effect of the topology on the steady state infection are studied, to show the importance of quantifying the robustness of networks. Second, a new metric VCSIR is introduced to assess the robustness of networks with respect

Model Driven Engineering

Science.gov (United States)

Gaševic, Dragan; Djuric, Dragan; Devedžic, Vladan

A relevant initiative from the software engineering community called Model Driven Engineering (MDE) is being developed in parallel with the Semantic Web (Mellor et al. 2003a). The MDE approach to software development suggests that one should first develop a model of the system under study, which is then transformed into the real thing (i.e., an executable software entity). The most important research initiative in this area is the Model Driven Architecture (MDA), which is Model Driven Architecture being developed under the umbrella of the Object Management Group (OMG). This chapter describes the basic concepts of this software engineering effort.

Context-dependent adaptation improves robustness of myoelectric control for upper-limb prostheses

Science.gov (United States)

Patel, Gauravkumar K.; Hahne, Janne M.; Castellini, Claudio; Farina, Dario; Dosen, Strahinja

2017-10-01

Objective. Dexterous upper-limb prostheses are available today to restore grasping, but an effective and reliable feed-forward control is still missing. The aim of this work was to improve the robustness and reliability of myoelectric control by using context information from sensors embedded within the prosthesis. Approach. We developed a context-driven myoelectric control scheme (cxMYO) that incorporates the inference of context information from proprioception (inertial measurement unit) and exteroception (force and grip aperture) sensors to modulate the outputs of myoelectric control. Further, a realistic evaluation of the cxMYO was performed online in able-bodied subjects using three functional tasks, during which the cxMYO was compared to a purely machine-learning-based myoelectric control (MYO). Main results. The results demonstrated that utilizing context information decreased the number of unwanted commands, improving the performance (success rate and dropped objects) in all three functional tasks. Specifically, the median number of objects dropped per round with cxMYO was zero in all three tasks and a significant increase in the number of successful transfers was seen in two out of three functional tasks. Additionally, the subjects reported better user experience. Significance. This is the first online evaluation of a method integrating information from multiple on-board prosthesis sensors to modulate the output of a machine-learning-based myoelectric controller. The proposed scheme is general and presents a simple, non-invasive and cost-effective approach for improving the robustness of myoelectric control.

Facial expression recognition based on weber local descriptor and sparse representation

Science.gov (United States)

Ouyang, Yan

2018-03-01

Automatic facial expression recognition has been one of the research hotspots in the area of computer vision for nearly ten years. During the decade, many state-of-the-art methods have been proposed which perform very high accurate rate based on the face images without any interference. Nowadays, many researchers begin to challenge the task of classifying the facial expression images with corruptions and occlusions and the Sparse Representation based Classification framework has been wildly used because it can robust to the corruptions and occlusions. Therefore, this paper proposed a novel facial expression recognition method based on Weber local descriptor (WLD) and Sparse representation. The method includes three parts: firstly the face images are divided into many local patches, and then the WLD histograms of each patch are extracted, finally all the WLD histograms features are composed into a vector and combined with SRC to classify the facial expressions. The experiment results on the Cohn-Kanade database show that the proposed method is robust to occlusions and corruptions.

Robust, functional nanocrystal solids by infilling with atomic layer deposition

Energy Technology Data Exchange (ETDEWEB)

Liu, Yao; Gibbs, Markelle; Perkins, Craig L.; Tolentino, Jason; Zarghami, Mohammad H.; Bustamante, Jr., J.; Law, Matt

2011-12-14

Thin films of colloidal semiconductor nanocrystals (NCs) are inherently metatstable materials prone to oxidative and photothermal degradation driven by their large surface-to-volume ratios and high surface energies. The fabrication of practical electronic devices based on NC solids hinges on preventing oxidation, surface diffusion, ripening, sintering, and other unwanted physicochemical changes that can plague these materials. Here we use low-temperature atomic layer deposition (ALD) to infill conductive PbSe NC solids with metal oxides to produce inorganic nanocomposites in which the NCs are locked in place and protected against oxidative and photothermal damage. Infilling NC field-effect transistors and solar cells with amorphous alumina yields devices that operate with enhanced and stable performance for at least months in air. Furthermore, ALD infilling with ZnO lowers the height of the inter-NC tunnel barrier for electron transport, yielding PbSe NC films with electron mobilities of 1 cm² V^-1 s^-1. Our ALD technique is a versatile means to fabricate robust NC solids for optoelectronic devices.

Clogging and transport of driven particles in asymmetric funnel arrays

Science.gov (United States)

Reichhardt, C. J. O.; Reichhardt, C.

2018-06-01

We numerically examine the flow and clogging of particles driven through asymmetric funnel arrays when the commensurability ratio of the number of particles per plaquette is varied. The particle–particle interactions are modeled with a soft repulsive potential that could represent vortex flow in type-II superconductors or driven charged colloids. The velocity-force curves for driving in the easy flow direction of the funnels exhibit a single depinning threshold; however, for driving in the hard flow direction, we find that there can be both negative mobility where the velocity decreases with increasing driving force as well as a reentrant pinning effect in which the particles flow at low drives but become pinned at intermediate drives. This reentrant pinning is associated with a transition from smooth 1D flow at low drives to a clogged state at higher drives that occurs when the particles cluster in a small number of plaquettes and block the flow. When the drive is further increased, particle rearrangements occur that cause the clog to break apart. We map out the regimes in which the pinned, flowing, and clogged states appear as a function of plaquette filling and drive. The clogged states remain robust at finite temperatures but develop intermittent bursts of flow in which a clog temporarily breaks apart but quickly reforms.

Robust recognition via information theoretic learning

CERN Document Server

He, Ran; Yuan, Xiaotong; Wang, Liang

2014-01-01

This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy.The?authors?resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency,?the brief?introduces the additive and multip

Robust methods for multivariate data analysis A1

DEFF Research Database (Denmark)

Frosch, Stina; Von Frese, J.; Bro, Rasmus

2005-01-01

Outliers may hamper proper classical multivariate analysis, and lead to incorrect conclusions. To remedy the problem of outliers, robust methods are developed in statistics and chemometrics. Robust methods reduce or remove the effect of outlying data points and allow the ?good? data to primarily...... determine the result. This article reviews the most commonly used robust multivariate regression and exploratory methods that have appeared since 1996 in the field of chemometrics. Special emphasis is put on the robust versions of chemometric standard tools like PCA and PLS and the corresponding robust...

Collision-model approach to steering of an open driven qubit

Science.gov (United States)

Beyer, Konstantin; Luoma, Kimmo; Strunz, Walter T.

2018-03-01

We investigate quantum steering of an open quantum system by measurements on its environment in the framework of collision models. As an example we consider a coherently driven qubit dissipatively coupled to a bath. We construct local nonadaptive and adaptive as well as nonlocal measurement scenarios specifying explicitly the measured observable on the environment. Our approach shows transparently how the conditional evolution of the open system depends on the type of the measurement scenario and the measured observables. These can then be optimized for steering. The nonlocal measurement scenario leads to maximal violation of the used steering inequality at zero temperature. Further, we investigate the robustness of the constructed scenarios against thermal noise. We find generally that steering becomes harder at higher temperatures. Surprisingly, the system can be steered even when bipartite entanglement between the system and individual subenvironments vanishes.

Data-driven outbreak forecasting with a simple nonlinear growth model.

Science.gov (United States)

Lega, Joceline; Brown, Heidi E

2016-12-01

Recent events have thrown the spotlight on infectious disease outbreak response. We developed a data-driven method, EpiGro, which can be applied to cumulative case reports to estimate the order of magnitude of the duration, peak and ultimate size of an ongoing outbreak. It is based on a surprisingly simple mathematical property of many epidemiological data sets, does not require knowledge or estimation of disease transmission parameters, is robust to noise and to small data sets, and runs quickly due to its mathematical simplicity. Using data from historic and ongoing epidemics, we present the model. We also provide modeling considerations that justify this approach and discuss its limitations. In the absence of other information or in conjunction with other models, EpiGro may be useful to public health responders. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Robustness Evaluation of Timber Structures

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Sørensen, John Dalsgaard

2009-01-01

Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure....

Ins-Robust Primitive Words

OpenAIRE

Srivastava, Amit Kumar; Kapoor, Kalpesh

2017-01-01

Let Q be the set of primitive words over a finite alphabet with at least two symbols. We characterize a class of primitive words, Q_I, referred to as ins-robust primitive words, which remain primitive on insertion of any letter from the alphabet and present some properties that characterizes words in the set Q_I. It is shown that the language Q_I is dense. We prove that the language of primitive words that are not ins-robust is not context-free. We also present a linear time algorithm to reco...

Dynamic modelling and robust current control of wind-turbine driven DFIG during external AC voltage dip

Institute of Scientific and Technical Information of China (English)

HU Jia-bing; HE Yi-kang

2006-01-01

Doubly-FedInduction Generator (DFIG), with vector control applied, is widely used in Variable-Speed ConstantFrequency (VSCF) windenergy generation system and shows good performance in maximum wind energy capture. But in two traditional vector control schemes, the equivalent stator magnetizing current is considered invariant in order to simplify the rotor current inner-loop controller. The two schemes can perform very well when the grid is in normal condition. However, when grid disturbance such as grid voltage dip or swell fault occurs, the control performance worsens, the rotor over current occurs and the Fault Ride-Through (FRT) capability of the DFIG wind energy generation system gets seriously deteriorated. An accurate DFIG model was used to deeply investigate the deficiency of the traditional vector control. The improved control schemes of two typical traditional vector control schemes used in DFIG were proposed, and simulation study of the proposed and traditional control schemes, with robust rotor current control using Internal Model Control (IMC) method, was carried out. The validity of the proposed modified schemes to control the rotor current and to improve the FRT capability of the DFIG wind energy generation system was proved by the comparison study.

Expression and Purification of Sperm Whale Myoglobin

Science.gov (United States)

Miller, Stephen; Indivero, Virginia; Burkhard, Caroline

2010-01-01

We present a multiweek laboratory exercise that exposes students to the fundamental techniques of bacterial expression and protein purification through the preparation of sperm whale myoglobin. Myoglobin, a robust oxygen-binding protein, contains a single heme that gives the protein a reddish color, making it an ideal subject for the teaching…

Small regulatory RNAs may sharpen spatial expression patterns.

Directory of Open Access Journals (Sweden)

Erel Levine

2007-11-01

Full Text Available The precise establishment of gene expression patterns is a crucial step in development. Formation of a sharp boundary between high and low spatial expression domains requires a genetic mechanism that exhibits sensitivity, yet is robust to fluctuations, a demand that may not be easily achieved by morphogens alone. Recently, it has been demonstrated that small RNAs (and, in particular, microRNAs play many roles in embryonic development. Whereas some RNAs are essential for embryogenesis, others are limited to fine-tuning a predetermined gene expression pattern. Here, we explore the possibility that small RNAs participate in sharpening a gene expression profile that was crudely established by a morphogen. To this end, we study a model in which small RNAs interact with a target gene and diffusively move from cell to cell. Though diffusion generally smoothens spatial expression patterns, we find that intercellular mobility of small RNAs is actually critical in sharpening the interface between target expression domains in a robust manner. This sharpening occurs as small RNAs diffuse into regions of low mRNA expression and eliminate target molecules therein, but cannot affect regions of high mRNA levels. We discuss the applicability of our results, as examples, to the case of leaf polarity establishment in maize and Hox patterning in the early Drosophila embryo. Our findings point out the functional significance of some mechanistic properties, such as mobility of small RNAs and the irreversibility of their interactions. These properties are yet to be established directly for most classes of small RNAs. An indirect yet simple experimental test of the proposed mechanism is suggested in some detail.

Semi-supervised consensus clustering for gene expression data analysis

OpenAIRE

Wang, Yunli; Pan, Youlian

2014-01-01

Background Simple clustering methods such as hierarchical clustering and k-means are widely used for gene expression data analysis; but they are unable to deal with noise and high dimensionality associated with the microarray gene expression data. Consensus clustering appears to improve the robustness and quality of clustering results. Incorporating prior knowledge in clustering process (semi-supervised clustering) has been shown to improve the consistency between the data partitioning and do...

SIGNATURES OF MRI-DRIVEN TURBULENCE IN PROTOPLANETARY DISKS: PREDICTIONS FOR ALMA OBSERVATIONS

Energy Technology Data Exchange (ETDEWEB)

Simon, Jacob B. [Department of Space Studies, Southwest Research Institute, Boulder, CO 80302 (United States); Hughes, A. Meredith; Flaherty, Kevin M. [Astronomy Department, Van Vleck Observatory, Wesleyan University, 96 Foss Hill Dr., Middletown, CT 06459 (United States); Bai, Xue-Ning [Harvard-Smithsonian Center for Astrophysics, 60 Garden St., MS-51, Cambridge, MA 02138 (United States); Armitage, Philip J., E-mail: jbsimon.astro@gmail.com [JILA, University of Colorado and NIST, 440 UCB, Boulder, CO 80309-0440 (United States)

2015-08-01

Spatially resolved observations of molecular line emission have the potential to yield unique constraints on the nature of turbulence within protoplanetary disks. Using a combination of local non-ideal magnetohydrodynamics (MHD) simulations and radiative transfer calculations, tailored to properties of the disk around HD 163296, we assess the ability of ALMA to detect turbulence driven by the magnetorotational instability (MRI). Our local simulations show that the MRI produces small-scale turbulent velocity fluctuations that increase in strength with height above the mid-plane. For a set of simulations at different disk radii, we fit a Maxwell–Boltzmann distribution to the turbulent velocity and construct a turbulent broadening parameter as a function of radius and height. We input this broadening into radiative transfer calculations to quantify observational signatures of MRI-driven disk turbulence. We find that the ratio of the peak line flux to the flux at line center is a robust diagnostic of turbulence that is only mildly degenerate with systematic uncertainties in disk temperature. For the CO(3–2) line, which we expect to probe the most magnetically active slice of the disk column, variations in the predicted peak-to-trough ratio between our most and least turbulent models span a range of approximately 15%. Additional independent constraints can be derived from the morphology of spatially resolved line profiles, and we estimate the resolution required to detect turbulence on different spatial scales. We discuss the role of lower optical depth molecular tracers, which trace regions closer to the disk mid-plane where velocities in MRI-driven models are systematically lower.

Light-regulated promoters for tunable, temporal, and affordable control of fungal gene expression.

Science.gov (United States)

Fuller, Kevin K; Dunlap, Jay C; Loros, Jennifer J

2018-05-01

Regulatable promoters are important genetic tools, particularly for assigning function to essential and redundant genes. They can also be used to control the expression of enzymes that influence metabolic flux or protein secretion, thereby optimizing product yield in bioindustry. This review will focus on regulatable systems for use in filamentous fungi, an important group of organisms whose members include key research models, devastating pathogens of plants and animals, and exploitable cell factories. Though we will begin by cataloging those promoters that are controlled by nutritional or chemical means, our primary focus will rest on those who can be controlled by a literal flip-of-the-switch: promoters of light-regulated genes. The vvd promoter of Neurospora will first serve as a paradigm for how light-driven systems can provide tight, robust, tunable, and temporal control of either autologous or heterologous fungal proteins. We will then discuss a theoretical approach to, and practical considerations for, the development of such promoters in other species. To this end, we have compiled genes from six previously published light-regulated transcriptomic studies to guide the search for suitable photoregulatable promoters in your fungus of interest.

Optically driven self-oscillations of a silica nanospike at low gas pressures

Science.gov (United States)

Xie, Shangran; Pennetta, Riccardo; Noskov, Roman E.; Russell, Philip St. J.

2016-09-01

We report light-driven instability and optomechanical self-oscillation of a fused silica "nanospike" at low gas pressures. The nanospike (tip diameter 400 nm), fabricated by thermally tapering and HF-etching a single mode fiber (SMF), was set pointing at the endface of a hollow-core photonic crystal fiber (HC-PCF) into the field created by the fundamental optical mode emerging from the HC-PCF. At low pressures, the nanospike became unstable and began to self-oscillate for optical powers above a certain threshold, acting like a phonon laser or "phaser". Because the nanospike is robustly connected to the base, direct measurement of the temporal dynamics of the instability is possible. The experiment sheds light on why particles escape from optical traps at low pressures.

Data-Driven and Expectation-Driven Discovery of Empirical Laws.

Science.gov (United States)

1982-10-10

occurred in small integer proportions to each other. In 1809, Joseph Gay- Lussac found evidence for his law of combining volumes, which stated that a...of Empirical Laws Patrick W. Langley Gary L. Bradshaw Herbert A. Simon T1he Robotics Institute Carnegie-Mellon University Pittsburgh, Pennsylvania...Subtitle) S. TYPE OF REPORT & PERIOD COVERED Data-Driven and Expectation-Driven Discovery Interim Report 2/82-10/82 of Empirical Laws S. PERFORMING ORG

A Survey on Robustness in Railway Planning

DEFF Research Database (Denmark)

Lusby, Richard Martin; Larsen, Jesper; Bull, Simon Henry

2018-01-01

Planning problems in passenger railway range from long term strategic decision making to the detailed planning of operations.Operations research methods have played an increasing role in this planning process. However, recently more attention has been given to considerations of robustness...... in the quality of solutions to individual planning problems, and of operations in general. Robustness in general is the capacity for some system to absorb or resist changes. In the context of railway robustness it is often taken to be the capacity for operations to continue at some level when faced...... with a disruption such as delay or failure. This has resulted in more attention given to the inclusion of robustness measures and objectives in individual planning problems, and to the providing of tools to ensure operations continue under disrupted situations. In this paper we survey the literature on robustness...

A robust interpretation of duration calculus

DEFF Research Database (Denmark)

Franzle, M.; Hansen, Michael Reichhardt

2005-01-01

We transfer the concept of robust interpretation from arithmetic first-order theories to metric-time temporal logics. The idea is that the interpretation of a formula is robust iff its truth value does not change under small variation of the constants in the formula. Exemplifying this on Duration...... Calculus (DC), our findings are that the robust interpretation of DC is equivalent to a multi-valued interpretation that uses the real numbers as semantic domain and assigns Lipschitz-continuous interpretations to all operators of DC. Furthermore, this continuity permits approximation between discrete...

Design Robust Controller for Rotary Kiln

Directory of Open Access Journals (Sweden)

Omar D. Hernández-Arboleda

2013-11-01

Full Text Available This paper presents the design of a robust controller for a rotary kiln. The designed controller is a combination of a fractional PID and linear quadratic regulator (LQR, these are not used to control the kiln until now, in addition robustness criteria are evaluated (gain margin, phase margin, strength gain, rejecting high frequency noise and sensitivity applied to the entire model (controller-plant, obtaining good results with a frequency range of 0.020 to 90 rad/s, which contributes to the robustness of the system.

Danish Requirements for Robustness of Structures

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Christensen, H. H.

2006-01-01

. This paper describes the background of the revised robustness requirements implemented in the Danish Code of Practice for Safety of Structures in 2003 [1, 2, 3]. According to the Danish design rules robustness shall be documented for all structures where consequences of failure are serious. This paper...... describes the background of the design procedure in the Danish codes, which shall be followed in order to document sufficient robustness in the following steps: Step 1: review of loads and possible failure modes/scenarios and determination of acceptable collapse extent. Step 2: review of the structural...

Robust lyapunov controller for uncertain systems

KAUST Repository

Laleg-Kirati, Taous-Meriem; Elmetennani, Shahrazed

2017-01-01

Various examples of systems and methods are provided for Lyapunov control for uncertain systems. In one example, a system includes a process plant and a robust Lyapunov controller configured to control an input of the process plant. The robust

Modeling the Pineapple Express phenomenon via Multivariate Extreme Value Theory

Science.gov (United States)

Weller, G.; Cooley, D. S.

2011-12-01

The pineapple express (PE) phenomenon is responsible for producing extreme winter precipitation events in the coastal and mountainous regions of the western United States. Because the PE phenomenon is also associated with warm temperatures, the heavy precipitation and associated snowmelt can cause destructive flooding. In order to study impacts, it is important that regional climate models from NARCCAP are able to reproduce extreme precipitation events produced by PE. We define a daily precipitation quantity which captures the spatial extent and intensity of precipitation events produced by the PE phenomenon. We then use statistical extreme value theory to model the tail dependence of this quantity as seen in an observational data set and each of the six NARCCAP regional models driven by NCEP reanalysis. We find that most NCEP-driven NARCCAP models do exhibit tail dependence between daily model output and observations. Furthermore, we find that not all extreme precipitation events are pineapple express events, as identified by Dettinger et al. (2011). The synoptic-scale atmospheric processes that drive extreme precipitation events produced by PE have only recently begun to be examined. Much of the current work has focused on pattern recognition, rather than quantitative analysis. We use daily mean sea-level pressure (MSLP) fields from NCEP to develop a "pineapple express index" for extreme precipitation, which exhibits tail dependence with our observed precipitation quantity for pineapple express events. We build a statistical model that connects daily precipitation output from the WRFG model, daily MSLP fields from NCEP, and daily observed precipitation in the western US. Finally, we use this model to simulate future observed precipitation based on WRFG output driven by the CCSM model, and our pineapple express index derived from future CCSM output. Our aim is to use this model to develop a better understanding of the frequency and intensity of extreme

Robust mitotic entry is ensured by a latching switch

Directory of Open Access Journals (Sweden)

Chloe Tuck

2013-07-01

Cell cycle events are driven by Cyclin dependent kinases (CDKs and by their counter-acting phosphatases. Activation of the Cdk1:Cyclin B complex during mitotic entry is controlled by the Wee1/Myt1 inhibitory kinases and by Cdc25 activatory phosphatase, which are themselves regulated by Cdk1:Cyclin B within two positive circuits. Impairing these two feedbacks with chemical inhibitors induces a transient entry into M phase referred to as mitotic collapse. The pathology of mitotic collapse reveals that the positive circuits play a significant role in maintaining the M phase state. To better understand the function of these feedback loops during G2/M transition, we propose a simple model for mitotic entry in mammalian cells including spatial control over Greatwall kinase phosphorylation. After parameter calibration, the model is able to recapture the complex and non-intuitive molecular dynamics reported by Potapova et al. (Potapova et al., 2011. Moreover, it predicts the temporal patterns of other mitotic regulators which have not yet been experimentally tested and suggests a general design principle of cell cycle control: latching switches buffer the cellular stresses which accompany cell cycle processes to ensure that the transitions are smooth and robust.

Robust mitotic entry is ensured by a latching switch.

Science.gov (United States)

Tuck, Chloe; Zhang, Tongli; Potapova, Tamara; Malumbres, Marcos; Novák, Béla

2013-01-01

Cell cycle events are driven by Cyclin dependent kinases (CDKs) and by their counter-acting phosphatases. Activation of the Cdk1:Cyclin B complex during mitotic entry is controlled by the Wee1/Myt1 inhibitory kinases and by Cdc25 activatory phosphatase, which are themselves regulated by Cdk1:Cyclin B within two positive circuits. Impairing these two feedbacks with chemical inhibitors induces a transient entry into M phase referred to as mitotic collapse. The pathology of mitotic collapse reveals that the positive circuits play a significant role in maintaining the M phase state. To better understand the function of these feedback loops during G2/M transition, we propose a simple model for mitotic entry in mammalian cells including spatial control over Greatwall kinase phosphorylation. After parameter calibration, the model is able to recapture the complex and non-intuitive molecular dynamics reported by Potapova et al. (Potapova et al., 2011). Moreover, it predicts the temporal patterns of other mitotic regulators which have not yet been experimentally tested and suggests a general design principle of cell cycle control: latching switches buffer the cellular stresses which accompany cell cycle processes to ensure that the transitions are smooth and robust.

Heterologous gene expression driven by carbonic anhydrase gene promoter in Dunaliella salina

Science.gov (United States)

Yurong, Chai; Yumin, Lu; Tianyun, Wang; Weihong, Hou; Lexun, Xue

2006-12-01

Dunaliella salina, a halotolerant unicellular green alga without a rigid cell wall, can live in salinities ranging from 0.05 to 5 mol/L NaCl. These features of D. salina make it an ideal host for the production of antibodies, oral vaccine, and commercially valuable polypeptides. To produce high level of heterologous proteins from D. salina, highly efficient promoters are required to drive expression of target genes under controlled condition. In the present study, we cloned a 5' franking region of 1.4 kb from the carbonic anhydrase ( CAH) gene of D. salina by genomic walking and PCR. The fragment was ligated to the pMD18-T vector and characterized. Sequence analysis indicated that this region contained conserved motifs, including a TATA- like box and CAAT-box. Tandem (GT)n repeats that had a potential role of transcriptional control, were also found in this region. The transcription start site (TSS) of the CAH gene was determined by 5' RACE and nested PCR method. Transformation assays showed that the 1.4 kb fragment was able to drive expression of the selectable bar (bialaphos resistance) gene when the fusion was transformed into D. salina by biolistics. Northern blotting hybridizations showed that the bar transcript was most abundant in cells grown in 2 mol/L NaCl, and less abundant in 0.5 mol/L NaCl, indicating that expression of the bar gene was induced at high salinity. These results suggest the potential use of the CAH gene promoter to induce the expression of heterologous genes in D. salina under varied salt condition.

Emotion-driven level generation

OpenAIRE

Togelius, Julian; Yannakakis, Georgios N.

2016-01-01

This chapter examines the relationship between emotions and level generation. Grounded in the experience-driven procedural content generation framework we focus on levels and introduce a taxonomy of approaches for emotion-driven level generation. We then review four characteristic level generators of our earlier work that exemplify each one of the approaches introduced. We conclude the chapter with our vision on the future of emotion-driven level generation.

Advanced express web application development

CERN Document Server

Keig, Andrew

2013-01-01

A practical book, guiding the reader through the development of a single page application using a feature-driven approach.If you are an experienced JavaScript developer who wants to build highly scalable, real-world applications using Express, this book is ideal for you. This book is an advanced title and assumes that the reader has some experience with node, Javascript MVC web development frameworks, and has heard of Express before, or is familiar with it. You should also have a basic understanding of Redis and MongoDB. This book is not a tutorial on Node, but aims to explore some of the more

Survivin as a therapeutic target in Sonic hedgehog-driven medulloblastoma.

Science.gov (United States)

Brun, S N; Markant, S L; Esparza, L A; Garcia, G; Terry, D; Huang, J-M; Pavlyukov, M S; Li, X-N; Grant, G A; Crawford, J R; Levy, M L; Conway, E M; Smith, L H; Nakano, I; Berezov, A; Greene, M I; Wang, Q; Wechsler-Reya, R J

2015-07-01

Medulloblastoma (MB) is a highly malignant brain tumor that occurs primarily in children. Although surgery, radiation and high-dose chemotherapy have led to increased survival, many MB patients still die from their disease, and patients who survive suffer severe long-term side effects as a consequence of treatment. Thus, more effective and less toxic therapies for MB are critically important. Development of such therapies depends in part on identification of genes that are necessary for growth and survival of tumor cells. Survivin is an inhibitor of apoptosis protein that regulates cell cycle progression and resistance to apoptosis, is frequently expressed in human MB and when expressed at high levels predicts poor clinical outcome. Therefore, we hypothesized that Survivin may have a critical role in growth and survival of MB cells and that targeting it may enhance MB therapy. Here we show that Survivin is overexpressed in tumors from patched (Ptch) mutant mice, a model of Sonic hedgehog (SHH)-driven MB. Genetic deletion of survivin in Ptch mutant tumor cells significantly inhibits proliferation and causes cell cycle arrest. Treatment with small-molecule antagonists of Survivin impairs proliferation and survival of both murine and human MB cells. Finally, Survivin antagonists impede growth of MB cells in vivo. These studies highlight the importance of Survivin in SHH-driven MB, and suggest that it may represent a novel therapeutic target in patients with this disease.

Women process multisensory emotion expressions more efficiently than men.

Science.gov (United States)

Collignon, O; Girard, S; Gosselin, F; Saint-Amour, D; Lepore, F; Lassonde, M

2010-01-01

Despite claims in the popular press, experiments investigating whether female are more efficient than male observers at processing expression of emotions produced inconsistent findings. In the present study, participants were asked to categorize fear and disgust expressions displayed auditorily, visually, or audio-visually. Results revealed an advantage of women in all the conditions of stimulus presentation. We also observed more nonlinear probabilistic summation in the bimodal conditions in female than male observers, indicating greater neural integration of different sensory-emotional informations. These findings indicate robust differences between genders in the multisensory perception of emotion expression.

Robustness Analysis of Typologies of Reciprocal Timber Structures

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Parigi, Dario

2013-01-01

to the future development of typologies of reciprocal timber structures. The paper concludes that these kinds of structures can have a potential as long span timber structures in real projects if they are carefully designed with respect to the overall robustness strategies.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures many modern building...... codes consider the need for robustness in structures and provides strategies and methods to obtain robustness. Therefore a structural engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper outlines robustness issues related...

Adaptive Evolution of Gene Expression in Drosophila.

Science.gov (United States)

Nourmohammad, Armita; Rambeau, Joachim; Held, Torsten; Kovacova, Viera; Berg, Johannes; Lässig, Michael

2017-08-08

Gene expression levels are important quantitative traits that link genotypes to molecular functions and fitness. In Drosophila, population-genetic studies have revealed substantial adaptive evolution at the genomic level, but the evolutionary modes of gene expression remain controversial. Here, we present evidence that adaptation dominates the evolution of gene expression levels in flies. We show that 64% of the observed expression divergence across seven Drosophila species are adaptive changes driven by directional selection. Our results are derived from time-resolved data of gene expression divergence across a family of related species, using a probabilistic inference method for gene-specific selection. Adaptive gene expression is stronger in specific functional classes, including regulation, sensory perception, sexual behavior, and morphology. Moreover, we identify a large group of genes with sex-specific adaptation of expression, which predominantly occurs in males. Our analysis opens an avenue to map system-wide selection on molecular quantitative traits independently of their genetic basis. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Adaptive Evolution of Gene Expression in Drosophila

Directory of Open Access Journals (Sweden)

Armita Nourmohammad

2017-08-01

Full Text Available Gene expression levels are important quantitative traits that link genotypes to molecular functions and fitness. In Drosophila, population-genetic studies have revealed substantial adaptive evolution at the genomic level, but the evolutionary modes of gene expression remain controversial. Here, we present evidence that adaptation dominates the evolution of gene expression levels in flies. We show that 64% of the observed expression divergence across seven Drosophila species are adaptive changes driven by directional selection. Our results are derived from time-resolved data of gene expression divergence across a family of related species, using a probabilistic inference method for gene-specific selection. Adaptive gene expression is stronger in specific functional classes, including regulation, sensory perception, sexual behavior, and morphology. Moreover, we identify a large group of genes with sex-specific adaptation of expression, which predominantly occurs in males. Our analysis opens an avenue to map system-wide selection on molecular quantitative traits independently of their genetic basis.

Robust, accurate, and non-contacting vibration measurement systems: Summary of comparison measurements of the robust laser interferometer and typical accelerometer systems. Volume 1

International Nuclear Information System (INIS)

Goodenow, T.C.; Shipman, R.L.; Holland, H.M.

1995-06-01

Epoch Engineering, Incorporated (EEI) has completed a series of vibration measurements comparing their newly-developed Robust Laser Interferometer (RLI) with accelerometer-based instrumentation systems. EEI has successfully demonstrated, on several pieces of commonplace machinery, that non-contact, line-of-sight measurements are practical and yield results equal to or, in some cases, better than customary field implementations of accelerometers. The demonstration included analysis and comparison of such phenomena as nonlinearity, transverse sensitivity, harmonics, and signal-to-noise ratio. Fast Fourier Transformations were performed on the accelerometer and the laser system outputs to provide a comparison basis. The RLI was demonstrated, within the limits of the task, to be a viable, line-of-sight, non-contact alternative to accelerometer systems. Several different kinds of machinery were instrumented and compared, including a small pump, a gear-driven cement mixer, a rotor kit, and two small fans. Known machinery vibration sources were verified and RLI system output file formats were verified to be compatible with commercial computer programs used for vibration monitoring and trend analysis. The RLI was also observed to be less subject to electromagnetic interference (EMI) and more capable at very low frequencies

Analogy between optically driven injection-locked laser diodes and driven damped linear oscillators

International Nuclear Information System (INIS)

Murakami, Atsushi; Shore, K. Alan

2006-01-01

An analytical study of optically driven laser diodes (LDs) has been undertaken to meet the requirement for a theoretical treatment for chaotic drive and synchronization occurring in the injection-locked LDs with strong injection. A small-signal analysis is performed for the sets of rate equations for the injection-locked LDs driven by a sinusoidal optical signal. In particular, as a model of chaotic driving signals from LD dynamics, an optical signal caused by direct modulation to the master LD is assumed, oscillating both in field amplitude and phase as is the case with chaotic driving signals. Consequently, we find conditions that allow reduction in the degrees of freedom of the driven LD. Under these conditions, the driven response is approximated to a simple form which is found to be equivalent to driven damped linear oscillators. The validity of the application of this theory to previous work on the synchronization of chaos and related phenomena occurring in the injection-locked LDs is demonstrated

Robustness of Long Span Reciprocal Timber Structures

DEFF Research Database (Denmark)

Balfroid, Nathalie; Kirkegaard, Poul Henning

2011-01-01

engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper makes a discussion of such robustness issues related to the future development of reciprocal timber structures. The paper concludes that these kind of structures can have...... a potential as long span timber structures in real projects if they are carefully designed with respect to the overall robustness strategies.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. The interest has also been facilitated due to recently severe structural failures...

Evaluation of Respondent-Driven Sampling

Science.gov (United States)

McCreesh, Nicky; Frost, Simon; Seeley, Janet; Katongole, Joseph; Tarsh, Matilda Ndagire; Ndunguse, Richard; Jichi, Fatima; Lunel, Natasha L; Maher, Dermot; Johnston, Lisa G; Sonnenberg, Pam; Copas, Andrew J; Hayes, Richard J; White, Richard G

2012-01-01

Background Respondent-driven sampling is a novel variant of link-tracing sampling for estimating the characteristics of hard-to-reach groups, such as HIV prevalence in sex-workers. Despite its use by leading health organizations, the performance of this method in realistic situations is still largely unknown. We evaluated respondent-driven sampling by comparing estimates from a respondent-driven sampling survey with total-population data. Methods Total-population data on age, tribe, religion, socioeconomic status, sexual activity and HIV status were available on a population of 2402 male household-heads from an open cohort in rural Uganda. A respondent-driven sampling (RDS) survey was carried out in this population, employing current methods of sampling (RDS sample) and statistical inference (RDS estimates). Analyses were carried out for the full RDS sample and then repeated for the first 250 recruits (small sample). Results We recruited 927 household-heads. Full and small RDS samples were largely representative of the total population, but both samples under-represented men who were younger, of higher socioeconomic status, and with unknown sexual activity and HIV status. Respondent-driven-sampling statistical-inference methods failed to reduce these biases. Only 31%-37% (depending on method and sample size) of RDS estimates were closer to the true population proportions than the RDS sample proportions. Only 50%-74% of respondent-driven-sampling bootstrap 95% confidence intervals included the population proportion. Conclusions Respondent-driven sampling produced a generally representative sample of this well-connected non-hidden population. However, current respondent-driven-sampling inference methods failed to reduce bias when it occurred. Whether the data required to remove bias and measure precision can be collected in a respondent-driven sampling survey is unresolved. Respondent-driven sampling should be regarded as a (potentially superior) form of convenience

Evaluation of respondent-driven sampling.

Science.gov (United States)

McCreesh, Nicky; Frost, Simon D W; Seeley, Janet; Katongole, Joseph; Tarsh, Matilda N; Ndunguse, Richard; Jichi, Fatima; Lunel, Natasha L; Maher, Dermot; Johnston, Lisa G; Sonnenberg, Pam; Copas, Andrew J; Hayes, Richard J; White, Richard G

2012-01-01

Respondent-driven sampling is a novel variant of link-tracing sampling for estimating the characteristics of hard-to-reach groups, such as HIV prevalence in sex workers. Despite its use by leading health organizations, the performance of this method in realistic situations is still largely unknown. We evaluated respondent-driven sampling by comparing estimates from a respondent-driven sampling survey with total population data. Total population data on age, tribe, religion, socioeconomic status, sexual activity, and HIV status were available on a population of 2402 male household heads from an open cohort in rural Uganda. A respondent-driven sampling (RDS) survey was carried out in this population, using current methods of sampling (RDS sample) and statistical inference (RDS estimates). Analyses were carried out for the full RDS sample and then repeated for the first 250 recruits (small sample). We recruited 927 household heads. Full and small RDS samples were largely representative of the total population, but both samples underrepresented men who were younger, of higher socioeconomic status, and with unknown sexual activity and HIV status. Respondent-driven sampling statistical inference methods failed to reduce these biases. Only 31%-37% (depending on method and sample size) of RDS estimates were closer to the true population proportions than the RDS sample proportions. Only 50%-74% of respondent-driven sampling bootstrap 95% confidence intervals included the population proportion. Respondent-driven sampling produced a generally representative sample of this well-connected nonhidden population. However, current respondent-driven sampling inference methods failed to reduce bias when it occurred. Whether the data required to remove bias and measure precision can be collected in a respondent-driven sampling survey is unresolved. Respondent-driven sampling should be regarded as a (potentially superior) form of convenience sampling method, and caution is required

iGC-an integrated analysis package of gene expression and copy number alteration.

Science.gov (United States)

Lai, Yi-Pin; Wang, Liang-Bo; Wang, Wei-An; Lai, Liang-Chuan; Tsai, Mong-Hsun; Lu, Tzu-Pin; Chuang, Eric Y

2017-01-14

With the advancement in high-throughput technologies, researchers can simultaneously investigate gene expression and copy number alteration (CNA) data from individual patients at a lower cost. Traditional analysis methods analyze each type of data individually and integrate their results using Venn diagrams. Challenges arise, however, when the results are irreproducible and inconsistent across multiple platforms. To address these issues, one possible approach is to concurrently analyze both gene expression profiling and CNAs in the same individual. We have developed an open-source R/Bioconductor package (iGC). Multiple input formats are supported and users can define their own criteria for identifying differentially expressed genes driven by CNAs. The analysis of two real microarray datasets demonstrated that the CNA-driven genes identified by the iGC package showed significantly higher Pearson correlation coefficients with their gene expression levels and copy numbers than those genes located in a genomic region with CNA. Compared with the Venn diagram approach, the iGC package showed better performance. The iGC package is effective and useful for identifying CNA-driven genes. By simultaneously considering both comparative genomic and transcriptomic data, it can provide better understanding of biological and medical questions. The iGC package's source code and manual are freely available at https://www.bioconductor.org/packages/release/bioc/html/iGC.html .

Nonlinear robust hierarchical control for nonlinear uncertain systems

Directory of Open Access Journals (Sweden)

Leonessa Alexander

1999-01-01

Full Text Available A nonlinear robust control-system design framework predicated on a hierarchical switching controller architecture parameterized over a set of moving nominal system equilibria is developed. Specifically, using equilibria-dependent Lyapunov functions, a hierarchical nonlinear robust control strategy is developed that robustly stabilizes a given nonlinear system over a prescribed range of system uncertainty by robustly stabilizing a collection of nonlinear controlled uncertain subsystems. The robust switching nonlinear controller architecture is designed based on a generalized (lower semicontinuous Lyapunov function obtained by minimizing a potential function over a given switching set induced by the parameterized nominal system equilibria. The proposed framework robustly stabilizes a compact positively invariant set of a given nonlinear uncertain dynamical system with structured parametric uncertainty. Finally, the efficacy of the proposed approach is demonstrated on a jet engine propulsion control problem with uncertain pressure-flow map data.

Robust recurrent neural network modeling for software fault detection and correction prediction

International Nuclear Information System (INIS)

Hu, Q.P.; Xie, M.; Ng, S.H.; Levitin, G.

2007-01-01

Software fault detection and correction processes are related although different, and they should be studied together. A practical approach is to apply software reliability growth models to model fault detection, and fault correction process is assumed to be a delayed process. On the other hand, the artificial neural networks model, as a data-driven approach, tries to model these two processes together with no assumptions. Specifically, feedforward backpropagation networks have shown their advantages over analytical models in fault number predictions. In this paper, the following approach is explored. First, recurrent neural networks are applied to model these two processes together. Within this framework, a systematic networks configuration approach is developed with genetic algorithm according to the prediction performance. In order to provide robust predictions, an extra factor characterizing the dispersion of prediction repetitions is incorporated into the performance function. Comparisons with feedforward neural networks and analytical models are developed with respect to a real data set

The importance of robust design methodology

DEFF Research Database (Denmark)

Eifler, Tobias; Howard, Thomas J.

2018-01-01

infamous recalls in automotive history, that of the GM ignition switch, from the perspective of Robust Design. It is investigated if available Robust Design methods such as sensitivity analysis, tolerance stack-ups, design clarity, etc. would have been suitable to account for the performance variation...

Security and robustness for collaborative monitors

NARCIS (Netherlands)

Testerink, Bas; Bulling, Nils; Dastani, Mehdi

2016-01-01

Decentralized monitors can be subject to robustness and security risks. Robustness risks include attacks on the monitor’s infrastructure in order to disable parts of its functionality. Security risks include attacks that try to extract information from the monitor and thereby possibly leak sensitive

Robust statistics and geochemical data analysis

International Nuclear Information System (INIS)

Di, Z.

1987-01-01

Advantages of robust procedures over ordinary least-squares procedures in geochemical data analysis is demonstrated using NURE data from the Hot Springs Quadrangle, South Dakota, USA. Robust principal components analysis with 5% multivariate trimming successfully guarded the analysis against perturbations by outliers and increased the number of interpretable factors. Regression with SINE estimates significantly increased the goodness-of-fit of the regression and improved the correspondence of delineated anomalies with known uranium prospects. Because of the ubiquitous existence of outliers in geochemical data, robust statistical procedures are suggested as routine procedures to replace ordinary least-squares procedures

Towards distortion-free robust image authentication

International Nuclear Information System (INIS)

Coltuc, D

2007-01-01

This paper investigates a general framework for distortion-free robust image authentication by multiple marking. First, by robust watermarking a subsampled version of image edges is embedded. Then, by reversible watermarking the information needed to recover the original image is inserted, too. The hiding capacity of the reversible watermarking is the essential requirement for this approach. Thus in case of no attacks not only image is authenticated but also the original is exactly recovered. In case of attacks, reversibility is lost, but image can still be authenticated. Preliminary results providing very good robustness against JPEG compression are presented

On the robustness of Herlihy's hierarchy

Science.gov (United States)

Jayanti, Prasad

1993-01-01

A wait-free hierarchy maps object types to levels in Z(+) U (infinity) and has the following property: if a type T is at level N, and T' is an arbitrary type, then there is a wait-free implementation of an object of type T', for N processes, using only registers and objects of type T. The infinite hierarchy defined by Herlihy is an example of a wait-free hierarchy. A wait-free hierarchy is robust if it has the following property: if T is at level N, and S is a finite set of types belonging to levels N - 1 or lower, then there is no wait-free implementation of an object of type T, for N processes, using any number and any combination of objects belonging to the types in S. Robustness implies that there are no clever ways of combining weak shared objects to obtain stronger ones. Contrary to what many researchers believe, we prove that Herlihy's hierarchy is not robust. We then define some natural variants of Herlihy's hierarchy, which are also infinite wait-free hierarchies. With the exception of one, which is still open, these are not robust either. We conclude with the open question of whether non-trivial robust wait-free hierarchies exist.

Information theory perspective on network robustness

International Nuclear Information System (INIS)

Schieber, Tiago A.; Carpi, Laura; Frery, Alejandro C.; Rosso, Osvaldo A.; Pardalos, Panos M.; Ravetti, Martín G.

2016-01-01

A crucial challenge in network theory is the study of the robustness of a network when facing a sequence of failures. In this work, we propose a dynamical definition of network robustness based on Information Theory, that considers measurements of the structural changes caused by failures of the network's components. Failures are defined here as a temporal process defined in a sequence. Robustness is then evaluated by measuring dissimilarities between topologies after each time step of the sequence, providing a dynamical information about the topological damage. We thoroughly analyze the efficiency of the method in capturing small perturbations by considering different probability distributions on networks. In particular, we find that distributions based on distances are more consistent in capturing network structural deviations, as better reflect the consequences of the failures. Theoretical examples and real networks are used to study the performance of this methodology. - Highlights: • A novel methodology to measure the robustness of a network to component failure or targeted attacks is proposed. • The use of the network's distance PDF allows a precise analysis. • The method provides a dynamic robustness profile showing the response of the topology to each failure event. • The measure is capable to detect network's critical elements.

Replication and robustness in developmental research.

Science.gov (United States)

Duncan, Greg J; Engel, Mimi; Claessens, Amy; Dowsett, Chantelle J

2014-11-01

Replications and robustness checks are key elements of the scientific method and a staple in many disciplines. However, leading journals in developmental psychology rarely include explicit replications of prior research conducted by different investigators, and few require authors to establish in their articles or online appendices that their key results are robust across estimation methods, data sets, and demographic subgroups. This article makes the case for prioritizing both explicit replications and, especially, within-study robustness checks in developmental psychology. It provides evidence on variation in effect sizes in developmental studies and documents strikingly different replication and robustness-checking practices in a sample of journals in developmental psychology and a sister behavioral science-applied economics. Our goal is not to show that any one behavioral science has a monopoly on best practices, but rather to show how journals from a related discipline address vital concerns of replication and generalizability shared by all social and behavioral sciences. We provide recommendations for promoting graduate training in replication and robustness-checking methods and for editorial policies that encourage these practices. Although some of our recommendations may shift the form and substance of developmental research articles, we argue that they would generate considerable scientific benefits for the field. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Primal and dual approaches to adjustable robust optimization

NARCIS (Netherlands)

de Ruiter, Frans

2018-01-01

Robust optimization has become an important paradigm to deal with optimization under uncertainty. Adjustable robust optimization is an extension that deals with multistage problems. This thesis starts with a short but comprehensive introduction to adjustable robust optimization. Then the two

From current-driven to neoclassically driven tearing modes.

Science.gov (United States)

Reimerdes, H; Sauter, O; Goodman, T; Pochelon, A

2002-03-11

In the TCV tokamak, the m/n = 2/1 island is observed in low-density discharges with central electron-cyclotron current drive. The evolution of its width has two distinct growth phases, one of which can be linked to a "conventional" tearing mode driven unstable by the current profile and the other to a neoclassical tearing mode driven by a perturbation of the bootstrap current. The TCV results provide the first clear observation of such a destabilization mechanism and reconcile the theory of conventional and neoclassical tearing modes, which differ only in the dominant driving term.

IDBA-tran: a more robust de novo de Bruijn graph assembler for transcriptomes with uneven expression levels.

Science.gov (United States)

Peng, Yu; Leung, Henry C M; Yiu, Siu-Ming; Lv, Ming-Ju; Zhu, Xin-Guang; Chin, Francis Y L

2013-07-01

RNA sequencing based on next-generation sequencing technology is effective for analyzing transcriptomes. Like de novo genome assembly, de novo transcriptome assembly does not rely on any reference genome or additional annotation information, but is more difficult. In particular, isoforms can have very uneven expression levels (e.g. 1:100), which make it very difficult to identify low-expressed isoforms. One challenge is to remove erroneous vertices/edges with high multiplicity (produced by high-expressed isoforms) in the de Bruijn graph without removing correct ones with not-so-high multiplicity from low-expressed isoforms. Failing to do so will result in the loss of low-expressed isoforms or having complicated subgraphs with transcripts of different genes mixed together due to erroneous vertices/edges. Contributions: Unlike existing tools, which remove erroneous vertices/edges with multiplicities lower than a global threshold, we use a probabilistic progressive approach to iteratively remove them with local thresholds. This enables us to decompose the graph into disconnected components, each containing a few genes, if not a single gene, while retaining many correct vertices/edges of low-expressed isoforms. Combined with existing techniques, IDBA-Tran is able to assemble both high-expressed and low-expressed transcripts and outperform existing assemblers in terms of sensitivity and specificity for both simulated and real data. http://www.cs.hku.hk/~alse/idba_tran. Supplementary data are available at Bioinformatics online.

Connectivity diagnostics in the Mediterranean obtained from Lagrangian Flow Networks; global patterns, sensitivity and robustness

Science.gov (United States)

Monroy, Pedro; Rossi, Vincent; Ser-Giacomi, Enrico; López, Cristóbal; Hernández-García, Emilio

2017-04-01

Lagrangian Flow Network (LFN) is a modeling framework in which geographical sub-areas of the ocean are represented as nodes in a network and are interconnected by links representing the transport of water, substances or propagules (eggs and larvae) by currents. Here we compute for the surface of the whole Mediterranean basin four connectivity metrics derived from LFN that measure retention and exchange processes, thus providing a systematic characterization of propagule dispersal driven by the ocean circulation. Then we assess the sensitivity and robustness of the results with respect to the most relevant parameters: the density of released particles, the node size (spatial-scales of discretization), the Pelagic Larval Duration (PLD) and the modality of spawning. We find a threshold for the number of particles per node that guarantees reliable values for most of the metrics examined, independently of node size. For our setup, this threshold is 100 particles per node. We also find that the size of network nodes has a non-trivial influence on the spatial variability of both exchange and retention metrics. Although the spatio-temporal fluctuations of the circulation affect larval transport in a complex and unpredictable manner, our analyses evidence how specific biological parametrization impact the robustness of connectivity diagnostics. Connectivity estimates for long PLDs are more robust against biological uncertainties (PLD and spawning date) than for short PLDs. Furthermore, our model suggests that for mass-spawners that release propagules over short periods (≃ 2 to 10 days), daily release must be simulated to properly consider connectivity fluctuations. In contrast, average connectivity estimates for species that spawn repeatedly over longer duration (a few weeks to a few months) remain robust even using longer periodicity (5 to 10 days). Our results give a global view of the surface connectivity of the Mediterranean Sea and have implications for the design of

Beam-driven currents in the 1/ν regime in a helical system

International Nuclear Information System (INIS)

Nakajima, Noriyoshi; Okamoto, Masao.

1990-04-01

Beam currents driven by a neutral particle injection in a helical system (stellarator, heliotron/torsatron) are studied in the 1/ν collisionality regime. The general expression for the beam-driven current is obtained for arbitrary magnetic field configurations by solving the drift kinetic equation for electrons. It is found that F = J(net)/J(b) (J(net) is the net current and J(b) is the fast ion beam current) increases as f(t) and Zeff where f(t) is the fraction of trapped electrons and Zeff is the effective ionic charge number. Especially, for Zeff ≅ 1 the effect of trapped electrons is large and F is roughly proportional to f(t). On the other hand, if Zeff > or approx 3 the effect of trapped electrons becomes small. (author)

Schema-driven facilitation of new hierarchy learning in the transitive inference paradigm

Science.gov (United States)

Kumaran, Dharshan

2013-01-01

Prior knowledge, in the form of a mental schema or framework, is viewed to facilitate the learning of new information in a range of experimental and everyday scenarios. Despite rising interest in the cognitive and neural mechanisms underlying schema-driven facilitation of new learning, few paradigms have been developed to examine this issue in humans. Here we develop a multiphase experimental scenario aimed at characterizing schema-based effects in the context of a paradigm that has been very widely used across species, the transitive inference task. We show that an associative schema, comprised of prior knowledge of the rank positions of familiar items in the hierarchy, has a marked effect on transitivity performance and the development of relational knowledge of the hierarchy that cannot be accounted for by more general changes in task strategy. Further, we show that participants are capable of deploying prior knowledge to successful effect under surprising conditions (i.e., when corrective feedback is totally absent), but only when the associative schema is robust. Finally, our results provide insights into the cognitive mechanisms underlying such schema-driven effects, and suggest that new hierarchy learning in the transitive inference task can occur through a contextual transfer mechanism that exploits the structure of associative experiences. PMID:23782509

Schema-driven facilitation of new hierarchy learning in the transitive inference paradigm.

Science.gov (United States)

Kumaran, Dharshan

2013-06-19

Prior knowledge, in the form of a mental schema or framework, is viewed to facilitate the learning of new information in a range of experimental and everyday scenarios. Despite rising interest in the cognitive and neural mechanisms underlying schema-driven facilitation of new learning, few paradigms have been developed to examine this issue in humans. Here we develop a multiphase experimental scenario aimed at characterizing schema-based effects in the context of a paradigm that has been very widely used across species, the transitive inference task. We show that an associative schema, comprised of prior knowledge of the rank positions of familiar items in the hierarchy, has a marked effect on transitivity performance and the development of relational knowledge of the hierarchy that cannot be accounted for by more general changes in task strategy. Further, we show that participants are capable of deploying prior knowledge to successful effect under surprising conditions (i.e., when corrective feedback is totally absent), but only when the associative schema is robust. Finally, our results provide insights into the cognitive mechanisms underlying such schema-driven effects, and suggest that new hierarchy learning in the transitive inference task can occur through a contextual transfer mechanism that exploits the structure of associative experiences.

Towards Robust Face Recognition from Video

International Nuclear Information System (INIS)

Price, JR

2001-01-01

A novel, template-based method for face recognition is presented. The goals of the proposed method are to integrate multiple observations for improved robustness and to provide auxiliary confidence data for subsequent use in an automated video surveillance system. The proposed framework consists of a parallel system of classifiers, referred to as observers, where each observer is trained on one face region. The observer outputs are combined to yield the final recognition result. Three of the four confounding factors-expression, illumination, and decoration-are specifically addressed in this paper. The extension of the proposed approach to address the fourth confounding factor-pose-is straightforward and well supported in previous work. A further contribution of the proposed approach is the computation of a revealing confidence measure. This confidence measure will aid the subsequent application of the proposed method to video surveillance scenarios. Results are reported for a database comprising 676 images of 160 subjects under a variety of challenging circumstances. These results indicate significant performance improvements over previous methods and demonstrate the usefulness of the confidence data

Design principles for robust oscillatory behavior.

Science.gov (United States)

Castillo-Hair, Sebastian M; Villota, Elizabeth R; Coronado, Alberto M

2015-09-01

Oscillatory responses are ubiquitous in regulatory networks of living organisms, a fact that has led to extensive efforts to study and replicate the circuits involved. However, to date, design principles that underlie the robustness of natural oscillators are not completely known. Here we study a three-component enzymatic network model in order to determine the topological requirements for robust oscillation. First, by simulating every possible topological arrangement and varying their parameter values, we demonstrate that robust oscillators can be obtained by augmenting the number of both negative feedback loops and positive autoregulations while maintaining an appropriate balance of positive and negative interactions. We then identify network motifs, whose presence in more complex topologies is a necessary condition for obtaining oscillatory responses. Finally, we pinpoint a series of simple architectural patterns that progressively render more robust oscillators. Together, these findings can help in the design of more reliable synthetic biomolecular networks and may also have implications in the understanding of other oscillatory systems.

A Simple and Robust Method for Culturing Human-Induced Pluripotent Stem Cells in an Undifferentiated State Using Botulinum Hemagglutinin.

Science.gov (United States)

Kim, Mee-Hae; Matsubara, Yoshifumi; Fujinaga, Yukako; Kino-Oka, Masahiro

2018-02-01

Clinical and industrial applications of human-induced pluripotent stem cells (hiPSCs) is hindered by the lack of robust culture strategies capable of sustaining a culture in an undifferentiated state. Here, a simple and robust hiPSC-culture-propagation strategy incorporating botulinum hemagglutinin (HA)-mediated selective removal of cells deviating from an undifferentiated state is developed. After HA treatment, cell-cell adhesion is disrupted, and deviated cells detached from the central region of the colony to subsequently form tight monolayer colonies following prolonged incubation. The authors find that the temporal and dose-dependent activity of HA regulated deviated-cell removal and recoverability after disruption of cell-cell adhesion in hiPSC colonies. The effects of HA are confirmed under all culture conditions examined, regardless of hiPSC line and feeder-dependent or -free culture conditions. After routine application of our HA-treatment paradigm for serial passages, hiPSCs maintains expression of pluripotent markers and readily forms embryoid bodies expressing markers for all three germ-cell layers. This method enables highly efficient culturing of hiPSCs and use of entire undifferentiated portions without having to pick deviated cells manually. This simple and readily reproducible culture strategy is a potentially useful tool for improving the robust and scalable maintenance of undifferentiated hiPSC cultures. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Robustness of Distance-to-Default

DEFF Research Database (Denmark)

Jessen, Cathrine; Lando, David

2013-01-01

Distance-to-default is a remarkably robust measure for ranking firms according to their risk of default. The ranking seems to work despite the fact that the Merton model from which the measure is derived produces default probabilities that are far too small when applied to real data. We use...... simulations to investigate the robustness of the distance-to-default measure to different model specifications. Overall we find distance-to-default to be robust to a number of deviations from the simple Merton model that involve different asset value dynamics and different default triggering mechanisms....... A notable exception is a model with stochastic volatility of assets. In this case both the ranking of firms and the estimated default probabilities using distance-to-default perform significantly worse. We therefore propose a volatility adjustment of the distance-to-default measure, that significantly...

Robustness of digital artist authentication

DEFF Research Database (Denmark)

Jacobsen, Robert; Nielsen, Morten

In many cases it is possible to determine the authenticity of a painting from digital reproductions of the paintings; this has been demonstrated for a variety of artists and with different approaches. Common to all these methods in digital artist authentication is that the potential of the method...... is in focus, while the robustness has not been considered, i.e. the degree to which the data collection process influences the decision of the method. However, in order for an authentication method to be successful in practice, it needs to be robust to plausible error sources from the data collection....... In this paper we investigate the robustness of the newly proposed authenticity method introduced by the authors based on second generation multiresolution analysis. This is done by modelling a number of realistic factors that can occur in the data collection....

Adaptive robust polynomial regression for power curve modeling with application to wind power forecasting

DEFF Research Database (Denmark)

Xu, Man; Pinson, Pierre; Lu, Zongxiang

2016-01-01

of the lack of time adaptivity. In this paper, a refined local polynomial regression algorithm is proposed to yield an adaptive robust model of the time-varying scattered power curve for forecasting applications. The time adaptivity of the algorithm is considered with a new data-driven bandwidth selection......Wind farm power curve modeling, which characterizes the relationship between meteorological variables and power production, is a crucial procedure for wind power forecasting. In many cases, power curve modeling is more impacted by the limited quality of input data rather than the stochastic nature...... of the energy conversion process. Such nature may be due the varying wind conditions, aging and state of the turbines, etc. And, an equivalent steady-state power curve, estimated under normal operating conditions with the intention to filter abnormal data, is not sufficient to solve the problem because...

Thermophilic enzymes and their applications in biocatalysis: a robust aldo-keto reductase.

Science.gov (United States)

Willies, Simon; Isupov, Misha; Littlechild, Jennifer

2010-09-01

Extremophiles are providing a good source of novel robust enzymes for use in biocatalysis for the synthesis of new drugs. This is particularly true for the enzymes from thermophilic organisms which are more robust than their mesophilic counterparts to the conditions required for industrial bio-processes. This paper describes a new aldo-keto reductase enzyme from a thermophilic eubacteria, Thermotoga maritima which can be used for the production of primary alcohols. The enzyme has been cloned and over-expressed in Escherichia coli and has been purified and subjected to full biochemical characterization. The aldo-keto reductase can be used for production of primary alcohols using substrates including benzaldehyde, 1,2,3,6-tetrahydrobenzaldehyde and para-anisaldehyde. It is stable up to 80 degrees C, retaining over 60% activity for 5 hours at this temperature. The enzyme at pH 6.5 showed a preference for the forward, carbonyl reduction. The enzyme showed moderate stability with organic solvents, and retained 70% activity in 20% (v/v) isopropanol or DMSO. These properties are favourable for its potential industrial applications.

Adaptive Critic Nonlinear Robust Control: A Survey.

Science.gov (United States)

Wang, Ding; He, Haibo; Liu, Derong

2017-10-01

Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.

A Robust Controller Structure for Pico-Satellite Applications

DEFF Research Database (Denmark)

Kragelund, Martin Nygaard; Green, Martin; Kristensen, Mads

This paper describes the development of a robust controller structure for use in pico-satellite missions. The structure relies on unknown disturbance estimation and use of robust control theory to implement a system that is robust to both unmodeled disturbances and parameter uncertainties. As one...

Genetic and Environmental Control of Neurodevelopmental Robustness in Drosophila.

Directory of Open Access Journals (Sweden)

David J Mellert

Full Text Available Interindividual differences in neuronal wiring may contribute to behavioral individuality and affect susceptibility to neurological disorders. To investigate the causes and potential consequences of wiring variation in Drosophila melanogaster, we focused on a hemilineage of ventral nerve cord interneurons that exhibits morphological variability. We find that late-born subclasses of the 12A hemilineage are highly sensitive to genetic and environmental variation. Neurons in the second thoracic segment are particularly variable with regard to two developmental decisions, whereas its segmental homologs are more robust. This variability "hotspot" depends on Ultrabithorax expression in the 12A neurons, indicating variability is cell-intrinsic and under genetic control. 12A development is more variable and sensitive to temperature in long-established laboratory strains than in strains recently derived from the wild. Strains with a high frequency of one of the 12A variants also showed a high frequency of animals with delayed spontaneous flight initiation, whereas other wing-related behaviors did not show such a correlation and were thus not overtly affected by 12A variation. These results show that neurodevelopmental robustness is variable and under genetic control in Drosophila and suggest that the fly may serve as a model for identifying conserved gene pathways that stabilize wiring in stressful developmental environments. Moreover, some neuronal lineages are variation hotspots and thus may be more amenable to evolutionary change.

DC Algorithm for Extended Robust Support Vector Machine.

Science.gov (United States)

Fujiwara, Shuhei; Takeda, Akiko; Kanamori, Takafumi

2017-05-01

Nonconvex variants of support vector machines (SVMs) have been developed for various purposes. For example, robust SVMs attain robustness to outliers by using a nonconvex loss function, while extended [Formula: see text]-SVM (E[Formula: see text]-SVM) extends the range of the hyperparameter by introducing a nonconvex constraint. Here, we consider an extended robust support vector machine (ER-SVM), a robust variant of E[Formula: see text]-SVM. ER-SVM combines two types of nonconvexity from robust SVMs and E[Formula: see text]-SVM. Because of the two nonconvexities, the existing algorithm we proposed needs to be divided into two parts depending on whether the hyperparameter value is in the extended range or not. The algorithm also heuristically solves the nonconvex problem in the extended range. In this letter, we propose a new, efficient algorithm for ER-SVM. The algorithm deals with two types of nonconvexity while never entailing more computations than either E[Formula: see text]-SVM or robust SVM, and it finds a critical point of ER-SVM. Furthermore, we show that ER-SVM includes the existing robust SVMs as special cases. Numerical experiments confirm the effectiveness of integrating the two nonconvexities.

Identification of a robust subpathway-based signature for acute myeloid leukemia prognosis using an miRNA integrated strategy.

Science.gov (United States)

Chang, Huijuan; Gao, Qiuying; Ding, Wei; Qing, Xueqin

2018-01-01

Acute myeloid leukemia (AML) is a heterogeneous disease, and survival signatures are urgently needed to better monitor treatment. MiRNAs displayed vital regulatory roles on target genes, which was necessary involved in the complex disease. We therefore examined the expression levels of miRNAs and genes to identify robust signatures for survival benefit analyses. First, we reconstructed subpathway graphs by embedding miRNA components that were derived from low-throughput miRNA-gene interactions. Then, we randomly divided the data sets from The Cancer Genome Atlas (TCGA) into training and testing sets, and further formed 100 subsets based on the training set. Using each subset, we identified survival-related miRNAs and genes, and identified survival subpathways based on the reconstructed subpathway graphs. After statistical analyses of these survival subpathways, the most robust subpathways with the top three ranks were identified, and risk scores were calculated based on these robust subpathways for AML patient prognoses. Among these robust subpathways, three representative subpathways, path: 05200_10 from Pathways in cancer, path: 04110_20 from Cell cycle, and path: 04510_8 from Focal adhesion, were significantly associated with patient survival in the TCGA training and testing sets based on subpathway risk scores. In conclusion, we performed integrated analyses of miRNAs and genes to identify robust prognostic subpathways, and calculated subpathway risk scores to characterize AML patient survival.

Decentralized control of large-scale systems: Fixed modes, sensitivity and parametric robustness. Ph.D. Thesis - Universite Paul Sabatier, 1985

Science.gov (United States)

Tarras, A.

1987-01-01

The problem of stabilization/pole placement under structural constraints of large scale linear systems is discussed. The existence of a solution to this problem is expressed in terms of fixed modes. The aim is to provide a bibliographic survey of the available results concerning the fixed modes (characterization, elimination, control structure selection to avoid them, control design in their absence) and to present the author's contribution to this problem which can be summarized by the use of the mode sensitivity concept to detect or to avoid them, the use of vibrational control to stabilize them, and the addition of parametric robustness considerations to design an optimal decentralized robust control.

A Global User-Driven Model for Tile Prefetching in Web Geographical Information Systems.

Science.gov (United States)

Pan, Shaoming; Chong, Yanwen; Zhang, Hang; Tan, Xicheng

2017-01-01

A web geographical information system is a typical service-intensive application. Tile prefetching and cache replacement can improve cache hit ratios by proactively fetching tiles from storage and replacing the appropriate tiles from the high-speed cache buffer without waiting for a client's requests, which reduces disk latency and improves system access performance. Most popular prefetching strategies consider only the relative tile popularities to predict which tile should be prefetched or consider only a single individual user's access behavior to determine which neighbor tiles need to be prefetched. Some studies show that comprehensively considering all users' access behaviors and all tiles' relationships in the prediction process can achieve more significant improvements. Thus, this work proposes a new global user-driven model for tile prefetching and cache replacement. First, based on all users' access behaviors, a type of expression method for tile correlation is designed and implemented. Then, a conditional prefetching probability can be computed based on the proposed correlation expression mode. Thus, some tiles to be prefetched can be found by computing and comparing the conditional prefetching probability from the uncached tiles set and, similarly, some replacement tiles can be found in the cache buffer according to multi-step prefetching. Finally, some experiments are provided comparing the proposed model with other global user-driven models, other single user-driven models, and other client-side prefetching strategies. The results show that the proposed model can achieve a prefetching hit rate in approximately 10.6% ~ 110.5% higher than the compared methods.

Robustness-related issues in speaker recognition

CERN Document Server

Zheng, Thomas Fang

2017-01-01

This book presents an overview of speaker recognition technologies with an emphasis on dealing with robustness issues. Firstly, the book gives an overview of speaker recognition, such as the basic system framework, categories under different criteria, performance evaluation and its development history. Secondly, with regard to robustness issues, the book presents three categories, including environment-related issues, speaker-related issues and application-oriented issues. For each category, the book describes the current hot topics, existing technologies, and potential research focuses in the future. The book is a useful reference book and self-learning guide for early researchers working in the field of robust speech recognition.

An expression tag toolbox for microbial production of membrane bound plant cytochromes P450

DEFF Research Database (Denmark)

Vazquez Albacete, Dario; Cavaleiro, Mafalda; Christensen, Ulla

2017-01-01

of the intermediate and the final product of the pathway. Finally, the effect of a robustly performing expression tag was explored with a library of 49 different P450s from medicinal plants and nearly half of these were improved in expression by more than 2-fold. The developed toolbox serves as platform to tune P450...... tag chimeras of the model plant P450 CYP79A1 in different Escherichia coli strains. Using a high-throughput screening platform based on C-terminal GFP fusions, we identify several highly expressing and robustly performing chimeric designs. Analysis of long-term cultures by flow cytometry showed...... homogeneous populations for some of the conditions. Three chimeric designs were chosen for a more complex combinatorial assembly of a multigene pathway consisting of two P450s and a redox partner. Cells expressing these recombinant enzymes catalysed the conversion of the substrate to highly different ratios...

Robust Self Tuning Controllers

DEFF Research Database (Denmark)

Poulsen, Niels Kjølstad

1985-01-01

The present thesis concerns robustness properties of adaptive controllers. It is addressed to methods for robustifying self tuning controllers with respect to abrupt changes in the plant parameters. In the thesis an algorithm for estimating abruptly changing parameters is presented. The estimator...... has several operation modes and a detector for controlling the mode. A special self tuning controller has been developed to regulate plant with changing time delay.......The present thesis concerns robustness properties of adaptive controllers. It is addressed to methods for robustifying self tuning controllers with respect to abrupt changes in the plant parameters. In the thesis an algorithm for estimating abruptly changing parameters is presented. The estimator...

Discovery Driven Growth

DEFF Research Database (Denmark)

Bukh, Per Nikolaj

2009-01-01

Anmeldelse af Discovery Driven Growh : A breakthrough process to reduce risk and seize opportunity, af Rita G. McGrath & Ian C. MacMillan, Boston: Harvard Business Press. Udgivelsesdato: 14 august......Anmeldelse af Discovery Driven Growh : A breakthrough process to reduce risk and seize opportunity, af Rita G. McGrath & Ian C. MacMillan, Boston: Harvard Business Press. Udgivelsesdato: 14 august...

ESBWR - Robust design for natural circulation and stability performance effectiveness

Energy Technology Data Exchange (ETDEWEB)

Alamgir, M. D.; Marquino, W.; Yang, J.; Saha, P.; Fennern, L.; Colby, M. [GE-Hitachi Nuclear Energy, M/C A65, 3901Castle Hayne Road, Wilmington, NC 28401 (United States)

2012-07-01

ESBWR is a 4500 MWt Generation III+ natural circulation reactor with an array of robust design features and passive safety systems to deliver highly effective plant performance during normal operation and to keep the reactor safe during postulated transients and accidents. With the submittal of the latest revision of the Design Control Document (DCD) to US Nuclear Regulatory Commission, ESBWR is nearing the completion of the US design certification process. This paper focuses on the natural circulation-driven plant performance aspects during normal operation, and stability evaluation of the robust ESBWR design. The TRACG computer code is used for the analysis of ESBWR plant performance, safety analysis, and stability margins. The paper describes the evaluation of ESBWR stability performance during normal power operation including operation in the Core Power-Feed Water Temperature Operating Domain. For ESBWR the normal power operation condition has the highest power/flow ratio and is limiting from the perspective of stability. The paper includes results from detailed evaluation of the most limiting decay ratio for out-of-phase regional oscillations calculated by perturbing the core inlet flow rate in this out-of-phase mode about the line of symmetry for the azimuthal harmonic mode. The paper also summarizes the ESBWR regional mode stability evaluations during a limiting transient (Loss of Feedwater Heating), and during ATWS (Anticipated Transient without Scram). Nominal decay ratios of limiting Channel oscillation, Core wide oscillation and Regional oscillation are within the maximum acceptance criterion of 0.8, at 95% content and 95% confidence. These stability evaluation results indicate decay ratio is within design limits. The paper also describes the evaluation of ESBWR stability performance during plant startup, and summarizes the defense-in-depth stability solution for ESBWR. (authors)

ESBWR - Robust design for natural circulation and stability performance effectiveness

International Nuclear Information System (INIS)

Alamgir, M. D.; Marquino, W.; Yang, J.; Saha, P.; Fennern, L.; Colby, M.

2012-01-01

ESBWR is a 4500 MWt Generation III+ natural circulation reactor with an array of robust design features and passive safety systems to deliver highly effective plant performance during normal operation and to keep the reactor safe during postulated transients and accidents. With the submittal of the latest revision of the Design Control Document (DCD) to US Nuclear Regulatory Commission, ESBWR is nearing the completion of the US design certification process. This paper focuses on the natural circulation-driven plant performance aspects during normal operation, and stability evaluation of the robust ESBWR design. The TRACG computer code is used for the analysis of ESBWR plant performance, safety analysis, and stability margins. The paper describes the evaluation of ESBWR stability performance during normal power operation including operation in the Core Power-Feed Water Temperature Operating Domain. For ESBWR the normal power operation condition has the highest power/flow ratio and is limiting from the perspective of stability. The paper includes results from detailed evaluation of the most limiting decay ratio for out-of-phase regional oscillations calculated by perturbing the core inlet flow rate in this out-of-phase mode about the line of symmetry for the azimuthal harmonic mode. The paper also summarizes the ESBWR regional mode stability evaluations during a limiting transient (Loss of Feedwater Heating), and during ATWS (Anticipated Transient without Scram). Nominal decay ratios of limiting Channel oscillation, Core wide oscillation and Regional oscillation are within the maximum acceptance criterion of 0.8, at 95% content and 95% confidence. These stability evaluation results indicate decay ratio is within design limits. The paper also describes the evaluation of ESBWR stability performance during plant startup, and summarizes the defense-in-depth stability solution for ESBWR. (authors)

Interface for Light-Driven Electron Transfer by Photosynthetic Complexes Across Block Copolymer Membranes.

Science.gov (United States)

Kuang, Liangju; Olson, Tien L; Lin, Su; Flores, Marco; Jiang, Yunjiang; Zheng, Wan; Williams, JoAnn C; Allen, James P; Liang, Hongjun

2014-03-06

Incorporation of membrane proteins into nanodevices to mediate recognition and transport in a collective and scalable fashion remains a challenging problem. We demonstrate how nanoscale photovoltaics could be designed using robust synthetic nanomembranes with incorporated photosynthetic reaction centers (RCs). Specifically, RCs from Rhodobacter sphaeroides are reconstituted spontaneously into rationally designed polybutadiene membranes to form hierarchically organized proteopolymer membrane arrays via a charge-interaction-directed reconstitution mechanism. Once incorporated, the RCs are fully active for prolonged periods based upon a variety of spectroscopic measurements, underscoring preservation of their 3D pigment configuration critical for light-driven charge transfer. This result provides a strategy to construct solar conversion devices using structurally versatile proteopolymer membranes with integrated RC functions to harvest broad regions of the solar spectrum.

Robustness analysis of chiller sequencing control

International Nuclear Information System (INIS)

Liao, Yundan; Sun, Yongjun; Huang, Gongsheng

2015-01-01

Highlights: • Uncertainties with chiller sequencing control were systematically quantified. • Robustness of chiller sequencing control was systematically analyzed. • Different sequencing control strategies were sensitive to different uncertainties. • A numerical method was developed for easy selection of chiller sequencing control. - Abstract: Multiple-chiller plant is commonly employed in the heating, ventilating and air-conditioning system to increase operational feasibility and energy-efficiency under part load condition. In a multiple-chiller plant, chiller sequencing control plays a key role in achieving overall energy efficiency while not sacrifices the cooling sufficiency for indoor thermal comfort. Various sequencing control strategies have been developed and implemented in practice. Based on the observation that (i) uncertainty, which cannot be avoided in chiller sequencing control, has a significant impact on the control performance and may cause the control fail to achieve the expected control and/or energy performance; and (ii) in current literature few studies have systematically addressed this issue, this paper therefore presents a study on robustness analysis of chiller sequencing control in order to understand the robustness of various chiller sequencing control strategies under different types of uncertainty. Based on the robustness analysis, a simple and applicable method is developed to select the most robust control strategy for a given chiller plant in the presence of uncertainties, which will be verified using case studies

Adaptive GSA-based optimal tuning of PI controlled servo systems with reduced process parametric sensitivity, robust stability and controller robustness.

Science.gov (United States)

Precup, Radu-Emil; David, Radu-Codrut; Petriu, Emil M; Radac, Mircea-Bogdan; Preitl, Stefan

2014-11-01

This paper suggests a new generation of optimal PI controllers for a class of servo systems characterized by saturation and dead zone static nonlinearities and second-order models with an integral component. The objective functions are expressed as the integral of time multiplied by absolute error plus the weighted sum of the integrals of output sensitivity functions of the state sensitivity models with respect to two process parametric variations. The PI controller tuning conditions applied to a simplified linear process model involve a single design parameter specific to the extended symmetrical optimum (ESO) method which offers the desired tradeoff to several control system performance indices. An original back-calculation and tracking anti-windup scheme is proposed in order to prevent the integrator wind-up and to compensate for the dead zone nonlinearity of the process. The minimization of the objective functions is carried out in the framework of optimization problems with inequality constraints which guarantee the robust stability with respect to the process parametric variations and the controller robustness. An adaptive gravitational search algorithm (GSA) solves the optimization problems focused on the optimal tuning of the design parameter specific to the ESO method and of the anti-windup tracking gain. A tuning method for PI controllers is proposed as an efficient approach to the design of resilient control systems. The tuning method and the PI controllers are experimentally validated by the adaptive GSA-based tuning of PI controllers for the angular position control of a laboratory servo system.

Implosion of multilayered cylindrical targets driven by intense heavy ion beams.

Science.gov (United States)

Piriz, A R; Portugues, R F; Tahir, N A; Hoffmann, D H H

2002-11-01

An analytical model for the implosion of a multilayered cylindrical target driven by an intense heavy ion beam has been developed. The target is composed of a cylinder of frozen hydrogen or deuterium, which is enclosed in a thick shell of solid lead. This target has been designed for future high-energy-density matter experiments to be carried out at the Gesellschaft für Schwerionenforschung, Darmstadt. The model describes the implosion dynamics including the motion of the incident shock and the first reflected shock and allows for calculation of the physical conditions of the hydrogen at stagnation. The model predicts that the conditions of the compressed hydrogen are not sensitive to significant variations in target and beam parameters. These predictions are confirmed by one-dimensional numerical simulations and thus allow for a robust target design.

GUS gene expression driven by a citrus promoter in transgenic tobacco and 'Valencia' sweet orange Expressão do gene GUS controlado por promotor de citros em plantas transgênicas de tabaco e laranja 'Valência'

Directory of Open Access Journals (Sweden)

Fernando Alves de Azevedo

2006-11-01

Full Text Available The objective of this work was the transformation of tobacco and 'Valencia' sweet orange with the GUS gene driven by the citrus phenylalanine ammonia-lyase (PAL gene promoter (CsPP. Transformation was accomplished by co-cultivation of tobacco and 'Valência' sweet orange explants with Agrobacterium tumefaciens containing the binary vector CsPP-GUS/2201. After plant transformation and regeneration, histochemical analyses using GUS staining revealed that CsPP promoter preferentially, but not exclusively, conferred gene expression in xylem tissues of tobacco. Weaker GUS staining was also detected throughout the petiole region in tobacco and citrus CsPP transgenic plants.O objetivo deste trabalho foi realizar a transformação de plantas de tabaco e laranja 'Valência' com o gene GUS controlado pelo promotor do gene da fenilalanina amônia-liase (PAL de citros (CsPP. Foi realizada transformação genética por meio do co-cultivo de explantes de tabaco e laranja 'Valência' com Agrobacterium tumefaciens que continha o vetor binário CsPP-GUS/2201. Após a transformação e a regeneração, a detecção da atividade de GUS por ensaios histoquímicos revelou que o promotor CsPP, preferencialmente, mas não exclusivamente, confere expressão gênica em tecidos do xilema de tabaco. Expressão mais baixa de GUS também foi detectada na região de tecido de pecíolo, em plantas transgênicas (CsPP de tabaco e laranja 'Valência'.

Attractive ellipsoids in robust control

CERN Document Server

Poznyak, Alexander; Azhmyakov, Vadim

2014-01-01

This monograph introduces a newly developed robust-control design technique for a wide class of continuous-time dynamical systems called the “attractive ellipsoid method.” Along with a coherent introduction to the proposed control design and related topics, the monograph studies nonlinear affine control systems in the presence of uncertainty and presents a constructive and easily implementable control strategy that guarantees certain stability properties. The authors discuss linear-style feedback control synthesis in the context of the above-mentioned systems. The development and physical implementation of high-performance robust-feedback controllers that work in the absence of complete information is addressed, with numerous examples to illustrate how to apply the attractive ellipsoid method to mechanical and electromechanical systems. While theorems are proved systematically, the emphasis is on understanding and applying the theory to real-world situations. Attractive Ellipsoids in Robust Control will a...

Advances in robust fractional control

CERN Document Server

Padula, Fabrizio

2015-01-01

This monograph presents design methodologies for (robust) fractional control systems. It shows the reader how to take advantage of the superior flexibility of fractional control systems compared with integer-order systems in achieving more challenging control requirements. There is a high degree of current interest in fractional systems and fractional control arising from both academia and industry and readers from both milieux are catered to in the text. Different design approaches having in common a trade-off between robustness and performance of the control system are considered explicitly. The text generalizes methodologies, techniques and theoretical results that have been successfully applied in classical (integer) control to the fractional case. The first part of Advances in Robust Fractional Control is the more industrially-oriented. It focuses on the design of fractional controllers for integer processes. In particular, it considers fractional-order proportional-integral-derivative controllers, becau...

Incentive-Compatible Robust Line Planning

Science.gov (United States)

Bessas, Apostolos; Kontogiannis, Spyros; Zaroliagis, Christos

The problem of robust line planning requests for a set of origin-destination paths (lines) along with their frequencies in an underlying railway network infrastructure, which are robust to fluctuations of real-time parameters of the solution. In this work, we investigate a variant of robust line planning stemming from recent regulations in the railway sector that introduce competition and free railway markets, and set up a new application scenario: there is a (potentially large) number of line operators that have their lines fixed and operate as competing entities issuing frequency requests, while the management of the infrastructure itself remains the responsibility of a single entity, the network operator. The line operators are typically unwilling to reveal their true incentives, while the network operator strives to ensure a fair (or socially optimal) usage of the infrastructure, e.g., by maximizing the (unknown to him) aggregate incentives of the line operators.

Forecasting exchange rates: a robust regression approach

OpenAIRE

Preminger, Arie; Franck, Raphael

2005-01-01

The least squares estimation method as well as other ordinary estimation method for regression models can be severely affected by a small number of outliers, thus providing poor out-of-sample forecasts. This paper suggests a robust regression approach, based on the S-estimation method, to construct forecasting models that are less sensitive to data contamination by outliers. A robust linear autoregressive (RAR) and a robust neural network (RNN) models are estimated to study the predictabil...

Hypoxia-driven angiogenesis: role of tip cells and extracellular matrix scaffolding.

Science.gov (United States)

Germain, Stéphane; Monnot, Catherine; Muller, Laurent; Eichmann, Anne

2010-05-01

Angiogenesis is a highly coordinated tissue remodeling process leading to blood vessel formation. Hypoxia triggers angiogenesis via induction of expression of growth factors such as vascular endothelial growth factor (VEGF). VEGF instructs endothelial cells to form tip cells, which lead outgrowing capillary sprouts, whereas Notch signaling inhibits sprout formation. Basement membrane deposition and mechanical cues from the extracellular matrix (ECM) induced by hypoxia may participate to coordinated vessel sprouting in conjunction with the VEGF and Notch signaling pathways. Hypoxia regulates ECM composition, deposition, posttranslational modifications and rearrangement. In particular, hypoxia-driven vascular remodeling is dynamically regulated through modulation of ECM-modifying enzyme activities that eventually affect both matricellular proteins and growth factor availability. Better understanding of the complex interplay between endothelial cells and soluble growth factors and mechanical factors from the ECM will certainly have significant implications for understanding the regulation of developmental and pathological angiogenesis driven by hypoxia.

Robust-yet-fragile nature of interdependent networks

Science.gov (United States)

Tan, Fei; Xia, Yongxiang; Wei, Zhi

2015-05-01

Interdependent networks have been shown to be extremely vulnerable based on the percolation model. Parshani et al. [Europhys. Lett. 92, 68002 (2010), 10.1209/0295-5075/92/68002] further indicated that the more intersimilar networks are, the more robust they are to random failures. When traffic load is considered, how do the coupling patterns impact cascading failures in interdependent networks? This question has been largely unexplored until now. In this paper, we address this question by investigating the robustness of interdependent Erdös-Rényi random graphs and Barabási-Albert scale-free networks under either random failures or intentional attacks. It is found that interdependent Erdös-Rényi random graphs are robust yet fragile under either random failures or intentional attacks. Interdependent Barabási-Albert scale-free networks, however, are only robust yet fragile under random failures but fragile under intentional attacks. We further analyze the interdependent communication network and power grid and achieve similar results. These results advance our understanding of how interdependency shapes network robustness.

Theta coordinated error-driven learning in the hippocampus.

Directory of Open Access Journals (Sweden)

Nicholas Ketz

Full Text Available The learning mechanism in the hippocampus has almost universally been assumed to be Hebbian in nature, where individual neurons in an engram join together with synaptic weight increases to support facilitated recall of memories later. However, it is also widely known that Hebbian learning mechanisms impose significant capacity constraints, and are generally less computationally powerful than learning mechanisms that take advantage of error signals. We show that the differential phase relationships of hippocampal subfields within the overall theta rhythm enable a powerful form of error-driven learning, which results in significantly greater capacity, as shown in computer simulations. In one phase of the theta cycle, the bidirectional connectivity between CA1 and entorhinal cortex can be trained in an error-driven fashion to learn to effectively encode the cortical inputs in a compact and sparse form over CA1. In a subsequent portion of the theta cycle, the system attempts to recall an existing memory, via the pathway from entorhinal cortex to CA3 and CA1. Finally the full theta cycle completes when a strong target encoding representation of the current input is imposed onto the CA1 via direct projections from entorhinal cortex. The difference between this target encoding and the attempted recall of the same representation on CA1 constitutes an error signal that can drive the learning of CA3 to CA1 synapses. This CA3 to CA1 pathway is critical for enabling full reinstatement of recalled hippocampal memories out in cortex. Taken together, these new learning dynamics enable a much more robust, high-capacity model of hippocampal learning than was available previously under the classical Hebbian model.

Robust Selectivity for Faces in the Human Amygdala in the Absence of Expressions

Science.gov (United States)

Mende-Siedlecki, Peter; Verosky, Sara C.; Turk-Browne, Nicholas B.; Todorov, Alexander

2014-01-01

There is a well-established posterior network of cortical regions that plays a central role in face processing and that has been investigated extensively. In contrast, although responsive to faces, the amygdala is not considered a core face-selective region, and its face selectivity has never been a topic of systematic research in human neuroimaging studies. Here, we conducted a large-scale group analysis of fMRI data from 215 participants. We replicated the posterior network observed in prior studies but found equally robust and reliable responses to faces in the amygdala. These responses were detectable in most individual participants, but they were also highly sensitive to the initial statistical threshold and habituated more rapidly than the responses in posterior face-selective regions. A multivariate analysis showed that the pattern of responses to faces across voxels in the amygdala had high reliability over time. Finally, functional connectivity analyses showed stronger coupling between the amygdala and posterior face-selective regions during the perception of faces than during the perception of control visual categories. These findings suggest that the amygdala should be considered a core face-selective region. PMID:23984945

A robust classic.

Science.gov (United States)

Kutzner, Florian; Vogel, Tobias; Freytag, Peter; Fiedler, Klaus

2011-01-01

In the present research, we argue for the robustness of illusory correlations (ICs, Hamilton & Gifford, 1976) regarding two boundary conditions suggested in previous research. First, we argue that ICs are maintained under extended experience. Using simulations, we derive conflicting predictions. Whereas noise-based accounts predict ICs to be maintained (Fielder, 2000; Smith, 1991), a prominent account based on discrepancy-reducing feedback learning predicts ICs to disappear (Van Rooy et al., 2003). An experiment involving 320 observations with majority and minority members supports the claim that ICs are maintained. Second, we show that actively using the stereotype to make predictions that are met with reward and punishment does not eliminate the bias. In addition, participants' operant reactions afford a novel online measure of ICs. In sum, our findings highlight the robustness of ICs that can be explained as a result of unbiased but noisy learning.

Scan-based volume animation driven by locally adaptive articulated registrations.

Science.gov (United States)

Rhee, Taehyun; Lewis, J P; Neumann, Ulrich; Nayak, Krishna S

2011-03-01

This paper describes a complete system to create anatomically accurate example-based volume deformation and animation of articulated body regions, starting from multiple in vivo volume scans of a specific individual. In order to solve the correspondence problem across volume scans, a template volume is registered to each sample. The wide range of pose variations is first approximated by volume blend deformation (VBD), providing proper initialization of the articulated subject in different poses. A novel registration method is presented to efficiently reduce the computation cost while avoiding strong local minima inherent in complex articulated body volume registration. The algorithm highly constrains the degrees of freedom and search space involved in the nonlinear optimization, using hierarchical volume structures and locally constrained deformation based on the biharmonic clamped spline. Our registration step establishes a correspondence across scans, allowing a data-driven deformation approach in the volume domain. The results provide an occlusion-free person-specific 3D human body model, asymptotically accurate inner tissue deformations, and realistic volume animation of articulated movements driven by standard joint control estimated from the actual skeleton. Our approach also addresses the practical issues arising in using scans from living subjects. The robustness of our algorithms is tested by their applications on the hand, probably the most complex articulated region in the body, and the knee, a frequent subject area for medical imaging due to injuries. © 2011 IEEE

What we learn from surveillance testing of standby turbine driven and motor driven pumps

International Nuclear Information System (INIS)

Christie, B.

1996-01-01

This paper describes a comparison of the performance information collected by the author and the respective system engineers from five standby turbine driven pumps at four commercial nuclear electric generating units in the United States and from two standby motor driven pumps at two of these generating units. Information was collected from surveillance testing and from Non-Test actuations. Most of the performance information (97%) came from surveillance testing. open-quotes Conditional Probabilitiesclose quotes of the pumps ability to respond to a random demand were calculated for each of the seven standby pumps and compared to the historical record of the Non-Test actuations. It appears that the Conditional Probabilities are comparable to the rate of success for Non-Test actuations. The Conditional Probabilities of the standby motor driven pumps (approximately 99%) are better than the Conditional Probabilities of the standby turbine driven pumps (82%-96% range). Recommendations were made to improve the Conditional Probabilities of the standby turbine driven pumps

What we learn from surveillance testing of standby turbine driven and motor driven pumps

Energy Technology Data Exchange (ETDEWEB)

Christie, B.

1996-12-01

This paper describes a comparison of the performance information collected by the author and the respective system engineers from five standby turbine driven pumps at four commercial nuclear electric generating units in the United States and from two standby motor driven pumps at two of these generating units. Information was collected from surveillance testing and from Non-Test actuations. Most of the performance information (97%) came from surveillance testing. {open_quotes}Conditional Probabilities{close_quotes} of the pumps ability to respond to a random demand were calculated for each of the seven standby pumps and compared to the historical record of the Non-Test actuations. It appears that the Conditional Probabilities are comparable to the rate of success for Non-Test actuations. The Conditional Probabilities of the standby motor driven pumps (approximately 99%) are better than the Conditional Probabilities of the standby turbine driven pumps (82%-96% range). Recommendations were made to improve the Conditional Probabilities of the standby turbine driven pumps.

Comparing Four Instructional Techniques for Promoting Robust Knowledge

Science.gov (United States)

Richey, J. Elizabeth; Nokes-Malach, Timothy J.

2015-01-01

Robust knowledge serves as a common instructional target in academic settings. Past research identifying characteristics of experts' knowledge across many domains can help clarify the features of robust knowledge as well as ways of assessing it. We review the expertise literature and identify three key features of robust knowledge (deep,…

Using Two Different Approaches to Assess Dietary Patterns: Hypothesis-Driven and Data-Driven Analysis

Directory of Open Access Journals (Sweden)

Ágatha Nogueira Previdelli

2016-09-01

Full Text Available The use of dietary patterns to assess dietary intake has become increasingly common in nutritional epidemiology studies due to the complexity and multidimensionality of the diet. Currently, two main approaches have been widely used to assess dietary patterns: data-driven and hypothesis-driven analysis. Since the methods explore different angles of dietary intake, using both approaches simultaneously might yield complementary and useful information; thus, we aimed to use both approaches to gain knowledge of adolescents’ dietary patterns. Food intake from a cross-sectional survey with 295 adolescents was assessed by 24 h dietary recall (24HR. In hypothesis-driven analysis, based on the American National Cancer Institute method, the usual intake of Brazilian Healthy Eating Index Revised components were estimated. In the data-driven approach, the usual intake of foods/food groups was estimated by the Multiple Source Method. In the results, hypothesis-driven analysis showed low scores for Whole grains, Total vegetables, Total fruit and Whole fruits, while, in data-driven analysis, fruits and whole grains were not presented in any pattern. High intakes of sodium, fats and sugars were observed in hypothesis-driven analysis with low total scores for Sodium, Saturated fat and SoFAA (calories from solid fat, alcohol and added sugar components in agreement, while the data-driven approach showed the intake of several foods/food groups rich in these nutrients, such as butter/margarine, cookies, chocolate powder, whole milk, cheese, processed meat/cold cuts and candies. In this study, using both approaches at the same time provided consistent and complementary information with regard to assessing the overall dietary habits that will be important in order to drive public health programs, and improve their efficiency to monitor and evaluate the dietary patterns of populations.

Robust inference in sample selection models

KAUST Repository

Zhelonkin, Mikhail; Genton, Marc G.; Ronchetti, Elvezio

2015-01-01

The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman's two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.

Robust inference in sample selection models

KAUST Repository

Zhelonkin, Mikhail

2015-11-20

The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman\\'s two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.

Input-driven versus turnover-driven controls of simulated changes in soil carbon due to land-use change

Science.gov (United States)

Nyawira, S. S.; Nabel, J. E. M. S.; Brovkin, V.; Pongratz, J.

2017-08-01

Historical changes in soil carbon associated with land-use change (LUC) result mainly from the changes in the quantity of litter inputs to the soil and the turnover of carbon in soils. We use a factor separation technique to assess how the input-driven and turnover-driven controls, as well as their synergies, have contributed to historical changes in soil carbon associated with LUC. We apply this approach to equilibrium simulations of present-day and pre-industrial land use performed using the dynamic global vegetation model JSBACH. Our results show that both the input-driven and turnover-driven changes generally contribute to a gain in soil carbon in afforested regions and a loss in deforested regions. However, in regions where grasslands have been converted to croplands, we find an input-driven loss that is partly offset by a turnover-driven gain, which stems from a decrease in the fire-related carbon losses. Omitting land management through crop and wood harvest substantially reduces the global losses through the input-driven changes. Our study thus suggests that the dominating control of soil carbon losses is via the input-driven changes, which are more directly accessible to human management than the turnover-driven ones.

REINA at CLEF 2007 Robust Track (2007)

OpenAIRE

Zazo, Ángel F.; G.-Figuerola, Carlos; Alonso-Berrocal, José-Luis

2007-01-01

This paper describes our work at CLEF 2007 Robust Task. We have participated in the monolingual (English, French and Portuguese) and the bilingual (English to French) subtask. At CLEF 2006 our research group obtained very good results applying local query expansion using windows of terms in the robust task. This year we have used the same expansion technique, but taking into account some criteria of robustness: MAP, GMAP, MMR, GS@10, P@10, number of failed topics, number of topics bellow 0.1 ...

Robust methods for data reduction

CERN Document Server

Farcomeni, Alessio

2015-01-01

Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis.The first part of the book illustrates how dimension reduction techniques synthesize available information by reducing the dimensionality of the data. The second part focuses on cluster and discriminant analy

Robust surgery loading

NARCIS (Netherlands)

Hans, Elias W.; Wullink, Gerhard; van Houdenhoven, Mark; Kazemier, Geert

2008-01-01

We consider the robust surgery loading problem for a hospital’s operating theatre department, which concerns assigning surgeries and sufficient planned slack to operating room days. The objective is to maximize capacity utilization and minimize the risk of overtime, and thus cancelled patients. This

Robust policy choice under Calvo and Rotemberg pricing

OpenAIRE

Sienknecht, Sebastian

2012-01-01

This paper examines the robustness of welfare-based policy choices across the nonlinear Calvo and Rotemberg pricing assumptions. Comparisons between simple interest rate rules turn out to be robust and independent of the price dispersion inherent in the Calvo setting. This robustness is violated if there is a policy alternative that controls for price dispersion.

Established Models and New Paradigms for Hypoxia-Driven Cancer-Associated Bone Disease

DEFF Research Database (Denmark)

Cox, Thomas R.; Erler, Janine T.; Rumney, Robin M.H.

2018-01-01

-driven effects in the primary tumour are wide ranging including changes in gene expression, dysregulation of signalling pathways, resistance to chemotherapy, neovascularisation, increased tumour cell proliferation and migration. Paget’s seed and soil theory states that for a metastasising tumour cell ‘the seed...... metastases. This review describes the roles of hypoxia in primary tumour progression to metastasis, with a focus on key signalling pathways and treatment options to reduce patient morbidity and increase survival....

Reconstructing 3D Face Model with Associated Expression Deformation from a Single Face Image via Constructing a Low-Dimensional Expression Deformation Manifold.

Science.gov (United States)

Wang, Shu-Fan; Lai, Shang-Hong

2011-10-01

Facial expression modeling is central to facial expression recognition and expression synthesis for facial animation. In this work, we propose a manifold-based 3D face reconstruction approach to estimating the 3D face model and the associated expression deformation from a single face image. With the proposed robust weighted feature map (RWF), we can obtain the dense correspondences between 3D face models and build a nonlinear 3D expression manifold from a large set of 3D facial expression models. Then a Gaussian mixture model in this manifold is learned to represent the distribution of expression deformation. By combining the merits of morphable neutral face model and the low-dimensional expression manifold, a novel algorithm is developed to reconstruct the 3D face geometry as well as the facial deformation from a single face image in an energy minimization framework. Experimental results on simulated and real images are shown to validate the effectiveness and accuracy of the proposed algorithm.

TAO-robust backpropagation learning algorithm.

Science.gov (United States)

Pernía-Espinoza, Alpha V; Ordieres-Meré, Joaquín B; Martínez-de-Pisón, Francisco J; González-Marcos, Ana

2005-03-01

In several fields, as industrial modelling, multilayer feedforward neural networks are often used as universal function approximations. These supervised neural networks are commonly trained by a traditional backpropagation learning format, which minimises the mean squared error (mse) of the training data. However, in the presence of corrupted data (outliers) this training scheme may produce wrong models. We combine the benefits of the non-linear regression model tau-estimates [introduced by Tabatabai, M. A. Argyros, I. K. Robust Estimation and testing for general nonlinear regression models. Applied Mathematics and Computation. 58 (1993) 85-101] with the backpropagation algorithm to produce the TAO-robust learning algorithm, in order to deal with the problems of modelling with outliers. The cost function of this approach has a bounded influence function given by the weighted average of two psi functions, one corresponding to a very robust estimate and the other to a highly efficient estimate. The advantages of the proposed algorithm are studied with an example.

Robustness of holonomic quantum gates

International Nuclear Information System (INIS)

Solinas, P.; Zanardi, P.; Zanghi, N.

2005-01-01

Full text: If the driving field fluctuates during the quantum evolution this produces errors in the applied operator. The holonomic (and geometrical) quantum gates are believed to be robust against some kind of noise. Because of the geometrical dependence of the holonomic operators can be robust against this kind of noise; in fact if the fluctuations are fast enough they cancel out leaving the final operator unchanged. I present the numerical studies of holonomic quantum gates subject to this parametric noise, the fidelity of the noise and ideal evolution is calculated for different noise correlation times. The holonomic quantum gates seem robust not only for fast fluctuating fields but also for slow fluctuating fields. These results can be explained as due to the geometrical feature of the holonomic operator: for fast fluctuating fields the fluctuations are canceled out, for slow fluctuating fields the fluctuations do not perturb the loop in the parameter space. (author)

Robust estimation and hypothesis testing

CERN Document Server

Tiku, Moti L

2004-01-01

In statistical theory and practice, a certain distribution is usually assumed and then optimal solutions sought. Since deviations from an assumed distribution are very common, one cannot feel comfortable with assuming a particular distribution and believing it to be exactly correct. That brings the robustness issue in focus. In this book, we have given statistical procedures which are robust to plausible deviations from an assumed mode. The method of modified maximum likelihood estimation is used in formulating these procedures. The modified maximum likelihood estimators are explicit functions of sample observations and are easy to compute. They are asymptotically fully efficient and are as efficient as the maximum likelihood estimators for small sample sizes. The maximum likelihood estimators have computational problems and are, therefore, elusive. A broad range of topics are covered in this book. Solutions are given which are easy to implement and are efficient. The solutions are also robust to data anomali...

Nonlinear Stimulated Raman Exact Passage by Resonance-Locked Inverse Engineering

Science.gov (United States)

Dorier, V.; Gevorgyan, M.; Ishkhanyan, A.; Leroy, C.; Jauslin, H. R.; Guérin, S.

2017-12-01

We derive an exact and robust stimulated Raman process for nonlinear quantum systems driven by pulsed external fields. The external fields are designed with closed-form expressions from the inverse engineering of a given efficient and stable dynamics. This technique allows one to induce a controlled population inversion which surpasses the usual nonlinear stimulated Raman adiabatic passage efficiency.

An Intercompany Perspective on Biopharmaceutical Drug Product Robustness Studies.

Science.gov (United States)

Morar-Mitrica, Sorina; Adams, Monica L; Crotts, George; Wurth, Christine; Ihnat, Peter M; Tabish, Tanvir; Antochshuk, Valentyn; DiLuzio, Willow; Dix, Daniel B; Fernandez, Jason E; Gupta, Kapil; Fleming, Michael S; He, Bing; Kranz, James K; Liu, Dingjiang; Narasimhan, Chakravarthy; Routhier, Eric; Taylor, Katherine D; Truong, Nobel; Stokes, Elaine S E

2018-02-01

The Biophorum Development Group (BPDG) is an industry-wide consortium enabling networking and sharing of best practices for the development of biopharmaceuticals. To gain a better understanding of current industry approaches for establishing biopharmaceutical drug product (DP) robustness, the BPDG-Formulation Point Share group conducted an intercompany collaboration exercise, which included a bench-marking survey and extensive group discussions around the scope, design, and execution of robustness studies. The results of this industry collaboration revealed several key common themes: (1) overall DP robustness is defined by both the formulation and the manufacturing process robustness; (2) robustness integrates the principles of quality by design (QbD); (3) DP robustness is an important factor in setting critical quality attribute control strategies and commercial specifications; (4) most companies employ robustness studies, along with prior knowledge, risk assessments, and statistics, to develop the DP design space; (5) studies are tailored to commercial development needs and the practices of each company. Three case studies further illustrate how a robustness study design for a biopharmaceutical DP balances experimental complexity, statistical power, scientific understanding, and risk assessment to provide the desired product and process knowledge. The BPDG-Formulation Point Share discusses identified industry challenges with regard to biopharmaceutical DP robustness and presents some recommendations for best practices. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Robust Structured Control Design via LMI Optimization

DEFF Research Database (Denmark)

Adegas, Fabiano Daher; Stoustrup, Jakob

2011-01-01

This paper presents a new procedure for discrete-time robust structured control design. Parameter-dependent nonconvex conditions for stabilizable and induced L2-norm performance controllers are solved by an iterative linear matrix inequalities (LMI) optimization. A wide class of controller...... structures including decentralized of any order, fixed-order dynamic output feedback, static output feedback can be designed robust to polytopic uncertainties. Stability is proven by a parameter-dependent Lyapunov function. Numerical examples on robust stability margins shows that the proposed procedure can...

A Dual-Sensing Receptor Confers Robust Cellular Homeostasis

Directory of Open Access Journals (Sweden)

Hannah Schramke

2016-06-01

Full Text Available Cells have evolved diverse mechanisms that maintain intracellular homeostasis in fluctuating environments. In bacteria, control is often exerted by bifunctional receptors acting as both kinase and phosphatase to regulate gene expression, a design known to provide robustness against noise. Yet how such antagonistic enzymatic activities are balanced as a function of environmental change remains poorly understood. We find that the bifunctional receptor that regulates K+ uptake in Escherichia coli is a dual sensor, which modulates its autokinase and phosphatase activities in response to both extracellular and intracellular K+ concentration. Using mathematical modeling, we show that dual sensing is a superior strategy for ensuring homeostasis when both the supply of and demand for a limiting resource fluctuate. By engineering standards, this molecular control system displays a strikingly high degree of functional integration, providing a reference for the vast numbers of receptors for which the sensing strategy remains elusive.

The Crane Robust Control

Directory of Open Access Journals (Sweden)

Marek Hicar

2004-01-01

Full Text Available The article is about a control design for complete structure of the crane: crab, bridge and crane uplift.The most important unknown parameters for simulations are burden weight and length of hanging rope. We will use robustcontrol for crab and bridge control to ensure adaptivity for burden weight and rope length. Robust control will be designed for current control of the crab and bridge, necessary is to know the range of unknown parameters. Whole robust will be splitto subintervals and after correct identification of unknown parameters the most suitable robust controllers will be chosen.The most important condition at the crab and bridge motion is avoiding from burden swinging in the final position. Crab and bridge drive is designed by asynchronous motor fed from frequency converter. We will use crane uplift with burden weightobserver in combination for uplift, crab and bridge drive with cooperation of their parameters: burden weight, rope length and crab and bridge position. Controllers are designed by state control method. We will use preferably a disturbance observerwhich will identify burden weight as a disturbance. The system will be working in both modes at empty hook as well asat maximum load: burden uplifting and dropping down.

Interrogating the topological robustness of gene regulatory circuits by randomization.

Directory of Open Access Journals (Sweden)

Bin Huang

2017-03-01

Full Text Available One of the most important roles of cells is performing their cellular tasks properly for survival. Cells usually achieve robust functionality, for example, cell-fate decision-making and signal transduction, through multiple layers of regulation involving many genes. Despite the combinatorial complexity of gene regulation, its quantitative behavior has been typically studied on the basis of experimentally verified core gene regulatory circuitry, composed of a small set of important elements. It is still unclear how such a core circuit operates in the presence of many other regulatory molecules and in a crowded and noisy cellular environment. Here we report a new computational method, named random circuit perturbation (RACIPE, for interrogating the robust dynamical behavior of a gene regulatory circuit even without accurate measurements of circuit kinetic parameters. RACIPE generates an ensemble of random kinetic models corresponding to a fixed circuit topology, and utilizes statistical tools to identify generic properties of the circuit. By applying RACIPE to simple toggle-switch-like motifs, we observed that the stable states of all models converge to experimentally observed gene state clusters even when the parameters are strongly perturbed. RACIPE was further applied to a proposed 22-gene network of the Epithelial-to-Mesenchymal Transition (EMT, from which we identified four experimentally observed gene states, including the states that are associated with two different types of hybrid Epithelial/Mesenchymal phenotypes. Our results suggest that dynamics of a gene circuit is mainly determined by its topology, not by detailed circuit parameters. Our work provides a theoretical foundation for circuit-based systems biology modeling. We anticipate RACIPE to be a powerful tool to predict and decode circuit design principles in an unbiased manner, and to quantitatively evaluate the robustness and heterogeneity of gene expression.

Differential gene expression before and after ionizing radiation of subcutaneous fibroblasts identifies breast cancer patients resistant to radiation-induced fibrosis

DEFF Research Database (Denmark)

Alsner, Jan; Rødningen, Olaug K.; Overgaard, Jens

2007-01-01

BACKGROUND AND PURPOSE: Differentially gene expression between patients with either very low or very high risk of radiation-induced fibrosis (RIF) in patient-derived fibroblasts after irradiation has previously been reported. In the present study, we are investigating the robustness of radiation...... and changes in radiation-induced gene expression in fibroblasts. MATERIAL AND METHODS: Gene expression was analysed by quantitative real-time PCR before and after a fractionated scheme with 3x3.5Gy/3 days in fibroblasts derived from 26 patients with breast cancer treated with post-mastectomy radiotherapy....... RESULTS: Robust radiation-induced changes in gene expression were observed, with differential gene expression between low and high risk patients being most pronounced for the fold induction level ('after' value divided by 'before' value for each patient). When including patients with intermediate risk...

Robust structural optimization using Gauss-type quadrature formula

International Nuclear Information System (INIS)

Lee, Sang Hoon; Seo, Ki Seog; Chen, Shikui; Chen, Wei

2009-01-01

In robust design, the mean and variance of design performance are frequently used to measure the design performance and its robustness under uncertainties. In this paper, we present the Gauss-type quadrature formula as a rigorous method for mean and variance estimation involving arbitrary input distributions and further extend its use to robust design optimization. One dimensional Gauss-type quadrature formula are constructed from the input probability distributions and utilized in the construction of multidimensional quadrature formula such as the Tensor Product Quadrature (TPQ) formula and the Univariate Dimension Reduction (UDR) method. To improve the efficiency of using it for robust design optimization, a semi-analytic design sensitivity analysis with respect to the statistical moments is proposed. The proposed approach is applied to a simple bench mark problems and robust topology optimization of structures considering various types of uncertainty.

Robust structural optimization using Gauss-type quadrature formula

Energy Technology Data Exchange (ETDEWEB)

Lee, Sang Hoon; Seo, Ki Seog [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Chen, Shikui; Chen, Wei [Northwestern University, Illinois (United States)

2009-07-01

In robust design, the mean and variance of design performance are frequently used to measure the design performance and its robustness under uncertainties. In this paper, we present the Gauss-type quadrature formula as a rigorous method for mean and variance estimation involving arbitrary input distributions and further extend its use to robust design optimization. One dimensional Gauss-type quadrature formula are constructed from the input probability distributions and utilized in the construction of multidimensional quadrature formula such as the Tensor Product Quadrature (TPQ) formula and the Univariate Dimension Reduction (UDR) method. To improve the efficiency of using it for robust design optimization, a semi-analytic design sensitivity analysis with respect to the statistical moments is proposed. The proposed approach is applied to a simple bench mark problems and robust topology optimization of structures considering various types of uncertainty.

Robust Structural Optimization Using Gauss-type Quadrature Formula

Energy Technology Data Exchange (ETDEWEB)

Lee, Sang Hoon; Seo, Ki Seog; Chen, Shikui; Chen, Wei [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2009-08-15

In robust design, the mean and variance of design performance are frequently used to measure the design performance and its robustness under uncertainties. In this paper, we present the Gauss-type quadrature formula as a rigorous method for mean and variance estimation involving arbitrary input distributions and further extend its use to robust design optimization. One dimensional Gauss-type quadrature formula are constructed from the input probability distributions and utilized in the construction of multidimensional quadrature formula such as the tensor product quadrature (TPQ) formula and the univariate dimension reduction (UDR) method. To improve the efficiency of using it for robust design optimization, a semi-analytic design sensitivity analysis with respect to the statistical moments is proposed. The proposed approach is applied to a simple bench mark problems and robust topology optimization of structures considering various types of uncertainty.

Robust Structural Optimization Using Gauss-type Quadrature Formula

International Nuclear Information System (INIS)