Adaptive integral robust control and application to electromechanical servo systems.

PubMed

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.

Should I Stay or Should I Switch? A Cost-Benefit Analysis of Voluntary Language Switching in Young and Aging Bilinguals

ERIC Educational Resources Information Center

Gollan, Tamar H.; Ferreira, Victor S.

2009-01-01

Bilinguals spontaneously switch languages in conversation even though laboratory studies reveal robust cued language switching costs. The authors investigated how voluntary-switching costs might differ when switches are voluntary. Younger (Experiments 1-2) and older (Experiment 3) Spanish-English bilinguals named pictures in 3 conditions: (a)…

Anisotropic convergence of dendritic macromolecules facilitated by a heteroleptic metal-organic polyhedron scaffold.

PubMed

Omoto, Kenichiro; Hosono, Nobuhiko; Gochomori, Mika; Albrecht, Ken; Yamamoto, Kimihisa; Kitagawa, Susumu

2018-05-17

Anisotropic dendrimers with bipolar shapes were systematically obtained using a heteroleptic metal-organic polyhedron (MOP) as a robust core scaffold. The structure of one of these polyhedral shapes was unambiguously determined by single-crystal X-ray analysis, which revealed that the bulky dendrons converge to both axial positions of the heteroleptic MOP core.

A Trans-omics Mathematical Analysis Reveals Novel Functions of the Ornithine Metabolic Pathway in Cancer Stem Cells

NASA Astrophysics Data System (ADS)

Koseki, Jun; Matsui, Hidetoshi; Konno, Masamitsu; Nishida, Naohiro; Kawamoto, Koichi; Kano, Yoshihiro; Mori, Masaki; Doki, Yuichiro; Ishii, Hideshi

2016-02-01

Bioinformatics and computational modelling are expected to offer innovative approaches in human medical science. In the present study, we performed computational analyses and made predictions using transcriptome and metabolome datasets obtained from fluorescence-based visualisations of chemotherapy-resistant cancer stem cells (CSCs) in the human oesophagus. This approach revealed an uncharacterized role for the ornithine metabolic pathway in the survival of chemotherapy-resistant CSCs. The present study fastens this rationale for further characterisation that may lead to the discovery of innovative drugs against robust CSCs.

Potential impacts of robust surface roughness indexes on DTM-based segmentation

NASA Astrophysics Data System (ADS)

Trevisani, Sebastiano; Rocca, Michele

2017-04-01

In this study, we explore the impact of robust surface texture indexes based on MAD (median absolute differences), implemented by Trevisani and Rocca (2015), in the unsupervised morphological segmentation of an alpine basin. The area was already object of a geomorphometric analysis, consisting in the roughness-based segmentation of the landscape (Trevisani et al. 2012); the roughness indexes were calculated on a high resolution DTM derived by means of airborne Lidar using the variogram as estimator. The calculated roughness indexes have been then used for the fuzzy clustering (Odeh et al., 1992; Burrough et al., 2000) of the basin, revealing the high informative geomorphometric content of the roughness-based indexes. However, the fuzzy clustering revealed a high fuzziness and a high degree of mixing between textural classes; this was ascribed both to the morphological complexity of the basin and to the high sensitivity of variogram to non-stationarity and signal-noise. Accordingly, we explore how the new implemented roughness indexes based on MAD affect the morphological segmentation of the studied basin. References Burrough, P.A., Van Gaans, P.F.M., MacMillan, R.A., 2000. High-resolution landform classification using fuzzy k-means. Fuzzy Sets and Systems 113, 37-52. Odeh, I.O.A., McBratney, A.B., Chittleborough, D.J., 1992. Soil pattern recognition with fuzzy-c-means: application to classification and soil-landform interrelationships. Soil Sciences Society of America Journal 56, 505-516. Trevisani, S., Cavalli, M. & Marchi, L. 2012, "Surface texture analysis of a high-resolution DTM: Interpreting an alpine basin", Geomorphology, vol. 161-162, pp. 26-39. Trevisani, S. & Rocca, M. 2015, "MAD: Robust image texture analysis for applications in high resolution geomorphometry", Computers and Geosciences, vol. 81, pp. 78-92.

How Do Astronomers Share Data? Reliability and Persistence of Datasets Linked in AAS Publications and a Qualitative Study of Data Practices among US Astronomers

PubMed Central

Pepe, Alberto; Goodman, Alyssa; Muench, August; Crosas, Merce; Erdmann, Christopher

2014-01-01

We analyze data sharing practices of astronomers over the past fifteen years. An analysis of URL links embedded in papers published by the American Astronomical Society reveals that the total number of links included in the literature rose dramatically from 1997 until 2005, when it leveled off at around 1500 per year. The analysis also shows that the availability of linked material decays with time: in 2011, 44% of links published a decade earlier, in 2001, were broken. A rough analysis of link types reveals that links to data hosted on astronomers' personal websites become unreachable much faster than links to datasets on curated institutional sites. To gauge astronomers' current data sharing practices and preferences further, we performed in-depth interviews with 12 scientists and online surveys with 173 scientists, all at a large astrophysical research institute in the United States: the Harvard-Smithsonian Center for Astrophysics, in Cambridge, MA. Both the in-depth interviews and the online survey indicate that, in principle, there is no philosophical objection to data-sharing among astronomers at this institution. Key reasons that more data are not presently shared more efficiently in astronomy include: the difficulty of sharing large data sets; over reliance on non-robust, non-reproducible mechanisms for sharing data (e.g. emailing it); unfamiliarity with options that make data-sharing easier (faster) and/or more robust; and, lastly, a sense that other researchers would not want the data to be shared. We conclude with a short discussion of a new effort to implement an easy-to-use, robust, system for data sharing in astronomy, at theastrodata.org, and we analyze the uptake of that system to-date. PMID:25165807

How do astronomers share data? Reliability and persistence of datasets linked in AAS publications and a qualitative study of data practices among US astronomers.

PubMed

Pepe, Alberto; Goodman, Alyssa; Muench, August; Crosas, Merce; Erdmann, Christopher

2014-01-01

We analyze data sharing practices of astronomers over the past fifteen years. An analysis of URL links embedded in papers published by the American Astronomical Society reveals that the total number of links included in the literature rose dramatically from 1997 until 2005, when it leveled off at around 1500 per year. The analysis also shows that the availability of linked material decays with time: in 2011, 44% of links published a decade earlier, in 2001, were broken. A rough analysis of link types reveals that links to data hosted on astronomers' personal websites become unreachable much faster than links to datasets on curated institutional sites. To gauge astronomers' current data sharing practices and preferences further, we performed in-depth interviews with 12 scientists and online surveys with 173 scientists, all at a large astrophysical research institute in the United States: the Harvard-Smithsonian Center for Astrophysics, in Cambridge, MA. Both the in-depth interviews and the online survey indicate that, in principle, there is no philosophical objection to data-sharing among astronomers at this institution. Key reasons that more data are not presently shared more efficiently in astronomy include: the difficulty of sharing large data sets; over reliance on non-robust, non-reproducible mechanisms for sharing data (e.g. emailing it); unfamiliarity with options that make data-sharing easier (faster) and/or more robust; and, lastly, a sense that other researchers would not want the data to be shared. We conclude with a short discussion of a new effort to implement an easy-to-use, robust, system for data sharing in astronomy, at theastrodata.org, and we analyze the uptake of that system to-date.

How Do Astronomers Share Data? Reliability and Persistence of Datasets Linked in AAS Publications and a Qualitative Study of Data Practices among US Astronomers

NASA Astrophysics Data System (ADS)

Pepe, Alberto; Goodman, Alyssa; Muench, August; Crosas, Merce; Erdmann, Christopher

2014-08-01

We analyze data sharing practices of astronomers over the past fifteen years. An analysis of URL links embedded in papers published by the American Astronomical Society reveals that the total number of links included in the literature rose dramatically from 1997 until 2005, when it leveled off at around 1500 per year. The analysis also shows that the availability of linked material decays with time: in 2011, 44% of links published a decade earlier, in 2001, were broken. A rough analysis of link types reveals that links to data hosted on astronomers' personal websites become unreachable much faster than links to datasets on curated institutional sites. To gauge astronomers' current data sharing practices and preferences further, we performed in-depth interviews with 12 scientists and online surveys with 173 scientists, all at a large astrophysical research institute in the United States: the Harvard-Smithsonian Center for Astrophysics, in Cambridge, MA. Both the in-depth interviews and the online survey indicate that, in principle, there is no philosophical objection to data-sharing among astronomers at this institution. Key reasons that more data are not presently shared more efficiently in astronomy include: the difficulty of sharing large data sets; over reliance on non-robust, non-reproducible mechanisms for sharing data (e.g. emailing it); unfamiliarity with options that make data-sharing easier (faster) and/or more robust; and, lastly, a sense that other researchers would not want the data to be shared. We conclude with a short discussion of a new effort to implement an easy-to-use, robust, system for data sharing in astronomy, at theastrodata.org, and we analyze the uptake of that system to-date.

Micro-Raman Analysis of Irradiated Diamond Films

NASA Technical Reports Server (NTRS)

Newton, R. L.; Munafo, Paul M. (Technical Monitor)

2002-01-01

Owing to its unique and robust physical properties, diamond is a much sought after material for use in advanced technologies such as Microelectromechanical Systems (MEMS). The volume and weight savings promised by MEMS-based devices are of particular interest to spaceflight applications. However, much basic materials science research remains to be completed in this field. Results of micro-Raman analysis of proton (1015 - 1017 H+/cm2 doses) irradiated chemical vapor deposited (CVD) diamond reveals that the microstructure is retained even after high radiation exposure.

Multifractal Detrended Cross-correlation Analysis of Market Clearing Price of electricity and SENSEX in India

NASA Astrophysics Data System (ADS)

Ghosh, Dipak; Dutta, Srimonti; Chakraborty, Sayantan

2015-09-01

This paper reports a study on the cross-correlation between the electric bid price and SENSEX using Multifractal Detrended Cross-correlation Analysis (MF-DXA). MF-DXA is a very rigorous and robust technique for assessment of cross-correction between two non-linear time series. The study reveals power law cross-correlation between Market Clearing Price (MCP) and SENSEX which suggests that a change in the value of one can create a subjective change in the value of the other.

Quantitative proteomics and network analysis of SSA1 and SSB1 deletion mutants reveals robustness of chaperone HSP70 network in Saccharomyces cerevisiae

PubMed Central

Jarnuczak, Andrew F.; Eyers, Claire E.; Schwartz, Jean‐Marc; Grant, Christopher M.

2015-01-01

Molecular chaperones play an important role in protein homeostasis and the cellular response to stress. In particular, the HSP70 chaperones in yeast mediate a large volume of protein folding through transient associations with their substrates. This chaperone interaction network can be disturbed by various perturbations, such as environmental stress or a gene deletion. Here, we consider deletions of two major chaperone proteins, SSA1 and SSB1, from the chaperone network in Sacchromyces cerevisiae. We employ a SILAC‐based approach to examine changes in global and local protein abundance and rationalise our results via network analysis and graph theoretical approaches. Although the deletions result in an overall increase in intracellular protein content, correlated with an increase in cell size, this is not matched by substantial changes in individual protein concentrations. Despite the phenotypic robustness to deletion of these major hub proteins, it cannot be simply explained by the presence of paralogues. Instead, network analysis and a theoretical consideration of folding workload suggest that the robustness to perturbation is a product of the overall network structure. This highlights how quantitative proteomics and systems modelling can be used to rationalise emergent network properties, and how the HSP70 system can accommodate the loss of major hubs. PMID:25689132

Fourier-Mellin moment-based intertwining map for image encryption

NASA Astrophysics Data System (ADS)

Kaur, Manjit; Kumar, Vijay

2018-03-01

In this paper, a robust image encryption technique that utilizes Fourier-Mellin moments and intertwining logistic map is proposed. Fourier-Mellin moment-based intertwining logistic map has been designed to overcome the issue of low sensitivity of an input image. Multi-objective Non-Dominated Sorting Genetic Algorithm (NSGA-II) based on Reinforcement Learning (MNSGA-RL) has been used to optimize the required parameters of intertwining logistic map. Fourier-Mellin moments are used to make the secret keys more secure. Thereafter, permutation and diffusion operations are carried out on input image using secret keys. The performance of proposed image encryption technique has been evaluated on five well-known benchmark images and also compared with seven well-known existing encryption techniques. The experimental results reveal that the proposed technique outperforms others in terms of entropy, correlation analysis, a unified average changing intensity and the number of changing pixel rate. The simulation results reveal that the proposed technique provides high level of security and robustness against various types of attacks.

2-DE analysis indicates that Acinetobacter baumannii displays a robust and versatile metabolism

PubMed Central

Soares, Nelson C; Cabral, Maria P; Parreira, José R; Gayoso, Carmen; Barba, Maria J; Bou, Germán

2009-01-01

Background Acinetobacter baumannii is a nosocomial pathogen that has been associated with outbreak infections in hospitals. Despite increasing awareness about this bacterium, its proteome remains poorly characterised, however recently the complete genome of A. baumannii reference strain ATCC 17978 has been sequenced. Here, we have used 2-DE and MALDI-TOF/TOF approach to characterise the proteome of this strain. Results The membrane and cytoplasmatic protein extracts were analysed separately, these analyses revealed the reproducible presence of 239 and 511 membrane and cytoplamatic protein spots, respectively. MALDI-TOF/TOF characterisation identified a total of 192 protein spots (37 membrane and 155 cytoplasmatic) and revealed that the identified membrane proteins were mainly transport-related proteins, whereas the cytoplasmatic proteins were of diverse nature, although mainly related to metabolic processes. Conclusion This work indicates that A. baumannii has a versatile and robust metabolism and also reveal a number of proteins that may play a key role in the mechanism of drug resistance and virulence. The data obtained complements earlier reports of A. baumannii proteome and provides new tools to increase our knowledge on the protein expression profile of this pathogen. PMID:19785748

Global Gene Expression Analysis in PKCα-/- Mouse Skin Reveals Structural Changes in the Dermis and Defective Wound Granulation Tissue.

PubMed

Cooper, Nichola H; Balachandra, Jeya P; Hardman, Matthew J

2015-12-01

The skin's mechanical integrity is maintained by an organized and robust dermal extracellular matrix (ECM). Resistance to mechanical disruption hinges primarily on homeostasis of the dermal collagen fibril architecture, which is regulated, at least in part, by members of the small leucine-rich proteoglycan (SLRP) family. Here we present data linking protein kinase C alpha (PKCα) to the regulated expression of multiple ECM components including SLRPs. Global microarray profiling reveals deficiencies in ECM gene expression in PKCα-/- skin correlating with abnormal collagen fibril morphology, disorganized dermal architecture, and reduced skin strength. Detailed analysis of the skin and wounds from wild-type and PKCα-/- mice reveals a failure to upregulate collagen and other ECM components in response to injury, resulting in delayed granulation tissue deposition in PKCα-/- wounds. Thus, our data reveal a previously unappreciated role for PKCα in the regulation of ECM structure and deposition during skin wound healing.

Incorporation of support vector machines in the LIBS toolbox for sensitive and robust classification amidst unexpected sample and system variability

PubMed Central

ChariDingari, Narahara; Barman, Ishan; Myakalwar, Ashwin Kumar; Tewari, Surya P.; Kumar, G. Manoj

2012-01-01

Despite the intrinsic elemental analysis capability and lack of sample preparation requirements, laser-induced breakdown spectroscopy (LIBS) has not been extensively used for real world applications, e.g. quality assurance and process monitoring. Specifically, variability in sample, system and experimental parameters in LIBS studies present a substantive hurdle for robust classification, even when standard multivariate chemometric techniques are used for analysis. Considering pharmaceutical sample investigation as an example, we propose the use of support vector machines (SVM) as a non-linear classification method over conventional linear techniques such as soft independent modeling of class analogy (SIMCA) and partial least-squares discriminant analysis (PLS-DA) for discrimination based on LIBS measurements. Using over-the-counter pharmaceutical samples, we demonstrate that application of SVM enables statistically significant improvements in prospective classification accuracy (sensitivity), due to its ability to address variability in LIBS sample ablation and plasma self-absorption behavior. Furthermore, our results reveal that SVM provides nearly 10% improvement in correct allocation rate and a concomitant reduction in misclassification rates of 75% (cf. PLS-DA) and 80% (cf. SIMCA)-when measurements from samples not included in the training set are incorporated in the test data – highlighting its robustness. While further studies on a wider matrix of sample types performed using different LIBS systems is needed to fully characterize the capability of SVM to provide superior predictions, we anticipate that the improved sensitivity and robustness observed here will facilitate application of the proposed LIBS-SVM toolbox for screening drugs and detecting counterfeit samples as well as in related areas of forensic and biological sample analysis. PMID:22292496

Incorporation of support vector machines in the LIBS toolbox for sensitive and robust classification amidst unexpected sample and system variability.

PubMed

Dingari, Narahara Chari; Barman, Ishan; Myakalwar, Ashwin Kumar; Tewari, Surya P; Kumar Gundawar, Manoj

2012-03-20

Despite the intrinsic elemental analysis capability and lack of sample preparation requirements, laser-induced breakdown spectroscopy (LIBS) has not been extensively used for real-world applications, e.g., quality assurance and process monitoring. Specifically, variability in sample, system, and experimental parameters in LIBS studies present a substantive hurdle for robust classification, even when standard multivariate chemometric techniques are used for analysis. Considering pharmaceutical sample investigation as an example, we propose the use of support vector machines (SVM) as a nonlinear classification method over conventional linear techniques such as soft independent modeling of class analogy (SIMCA) and partial least-squares discriminant analysis (PLS-DA) for discrimination based on LIBS measurements. Using over-the-counter pharmaceutical samples, we demonstrate that the application of SVM enables statistically significant improvements in prospective classification accuracy (sensitivity), because of its ability to address variability in LIBS sample ablation and plasma self-absorption behavior. Furthermore, our results reveal that SVM provides nearly 10% improvement in correct allocation rate and a concomitant reduction in misclassification rates of 75% (cf. PLS-DA) and 80% (cf. SIMCA)-when measurements from samples not included in the training set are incorporated in the test data-highlighting its robustness. While further studies on a wider matrix of sample types performed using different LIBS systems is needed to fully characterize the capability of SVM to provide superior predictions, we anticipate that the improved sensitivity and robustness observed here will facilitate application of the proposed LIBS-SVM toolbox for screening drugs and detecting counterfeit samples, as well as in related areas of forensic and biological sample analysis.

Rhabdoid glioblastoma is distinguishable from classical glioblastoma by cytogenetics and molecular genetics.

PubMed

Byeon, Sun-Ju; Cho, Hwa Jin; Baek, Hae Woon; Park, Chul-Kee; Choi, Seung-Hong; Kim, Se-Hoon; Kim, Hee Kyung; Park, Sung-Hye

2014-03-01

The clinicopathologic and molecular genetic features of 5 cases of rhabdoid glioblastoma, an extremely rare variant of glioblastoma that tends to affect patients at a young age, were investigated by immunohistochemical analysis and focused molecular genetic studies including array-based comparative genomic hybridization. All 5 cases had supratentorial tumors that immunohistochemical analysis revealed to be robustly positive for epithelial membrane antigen, vimentin, p53, and PDGFRα (platelet-derived growth factor receptor, alpha polypeptide) but only focally positive for glial fibrillary acidic protein. Although complete retention of SMARCB1 (INI1) was observed in all 5 cases, epidermal growth factor receptor (EGFR) amplification, PTEN (phosphatase and tensin homolog) loss, homozygous deletion of cyclin-dependent kinase inhibitor 2A, 1p/19q codeletion, and isocitrate dehydrogenase 1 R132/IDH2 R172 mutation were not observed in any case, although a high level of EGFR polysomy was detected in 1 recurrent tumor. Although c-MET (MET protein) expression was focal but robustly positive in 3 cases, met proto-oncogene (MET) fluorescence in situ hybridization revealed low polysomy but not MET amplification. MGMT (O-6-methylguanine-DNA methyl-40 transferase) methylation-specific polymerase chain reaction revealed MGMT methylation in only 1 case. Furthermore, array-based comparative genomic hybridization revealed gain of chromosome 7 and loss of 1p, 6, 8p, 11, 13q, and 18q but no deletion of chromosome 22. In contrast to the classical subtype of primary glioblastoma, the cases studied here were characterized by the absence of EGFR amplification, PTEN loss, and 9p homozygous deletion and overexpression of p53, PDGFRα, and c-MET, suggesting that they can be classified as the proneural or mesenchymal subtype of glioblastoma and benefit from intensive therapy that includes temozolomide. Copyright © 2014 Elsevier Inc. All rights reserved.

Strain-Dependent Transcriptome Signatures for Robustness in Lactococcus lactis

PubMed Central

Dijkstra, Annereinou R.; Alkema, Wynand; Starrenburg, Marjo J. C.; van Hijum, Sacha A. F. T.; Bron, Peter A.

2016-01-01

Recently, we demonstrated that fermentation conditions have a strong impact on subsequent survival of Lactococcus lactis strain MG1363 during heat and oxidative stress, two important parameters during spray drying. Moreover, employment of a transcriptome-phenotype matching approach revealed groups of genes associated with robustness towards heat and/or oxidative stress. To investigate if other strains have similar or distinct transcriptome signatures for robustness, we applied an identical transcriptome-robustness phenotype matching approach on the L. lactis strains IL1403, KF147 and SK11, which have previously been demonstrated to display highly diverse robustness phenotypes. These strains were subjected to an identical fermentation regime as was performed earlier for strain MG1363 and consisted of twelve conditions, varying in the level of salt and/or oxygen, as well as fermentation temperature and pH. In the exponential phase of growth, cells were harvested for transcriptome analysis and assessment of heat and oxidative stress survival phenotypes. The variation in fermentation conditions resulted in differences in heat and oxidative stress survival of up to five 10-log units. Effects of the fermentation conditions on stress survival of the L. lactis strains were typically strain-dependent, although the fermentation conditions had mainly similar effects on the growth characteristics of the different strains. By association of the transcriptomes and robustness phenotypes highly strain-specific transcriptome signatures for robustness towards heat and oxidative stress were identified, indicating that multiple mechanisms exist to increase robustness and, as a consequence, robustness of each strain requires individual optimization. However, a relatively small overlap in the transcriptome responses of the strains was also identified and this generic transcriptome signature included genes previously associated with stress (ctsR and lplL) and novel genes, including nanE and genes encoding transport proteins. The transcript levels of these genes can function as indicators of robustness and could aid in selection of fermentation parameters, potentially resulting in more optimal robustness during spray drying. PMID:27973578

Integration of community structure data reveals observable effects below sediment guideline thresholds in a large estuary.

PubMed

Tremblay, Louis A; Clark, Dana; Sinner, Jim; Ellis, Joanne I

2017-09-20

The sustainable management of estuarine and coastal ecosystems requires robust frameworks due to the presence of multiple physical and chemical stressors. In this study, we assessed whether ecological health decline, based on community structure composition changes along a pollution gradient, occurred at levels below guideline threshold values for copper, zinc and lead. Canonical analysis of principal coordinates (CAP) was used to characterise benthic communities along a metal contamination gradient. The analysis revealed changes in benthic community distribution at levels below the individual guideline values for the three metals. These results suggest that field-based measures of ecological health analysed with multivariate tools can provide additional information to single metal guideline threshold values to monitor large systems exposed to multiple stressors.

Distinct molecular cues ensure a robust microtubule-dependent nuclear positioning in the Drosophila oocyte

PubMed Central

Tissot, Nicolas; Lepesant, Jean-Antoine; Bernard, Fred; Legent, Kevin; Bosveld, Floris; Martin, Charlotte; Faklaris, Orestis; Bellaïche, Yohanns; Coppey, Maïté; Guichet, Antoine

2017-01-01

Controlling nucleus localization is crucial for a variety of cellular functions. In the Drosophila oocyte, nuclear asymmetric positioning is essential for the reorganization of the microtubule (MT) network that controls the polarized transport of axis determinants. A combination of quantitative three-dimensional live imaging and laser ablation-mediated force analysis reveal that nuclear positioning is ensured with an unexpected level of robustness. We show that the nucleus is pushed to the oocyte antero-dorsal cortex by MTs and that its migration can proceed through distinct tracks. Centrosome-associated MTs favour one migratory route. In addition, the MT-associated protein Mud/NuMA that is asymmetrically localized in an Asp-dependent manner at the nuclear envelope hemisphere where MT nucleation is higher promotes a separate route. Our results demonstrate that centrosomes do not provide an obligatory driving force for nuclear movement, but together with Mud, contribute to the mechanisms that ensure the robustness of asymmetric nuclear positioning. PMID:28447612

Robust tumor morphometry in multispectral fluorescence microscopy

NASA Astrophysics Data System (ADS)

Tabesh, Ali; Vengrenyuk, Yevgen; Teverovskiy, Mikhail; Khan, Faisal M.; Sapir, Marina; Powell, Douglas; Mesa-Tejada, Ricardo; Donovan, Michael J.; Fernandez, Gerardo

2009-02-01

Morphological and architectural characteristics of primary tissue compartments, such as epithelial nuclei (EN) and cytoplasm, provide important cues for cancer diagnosis, prognosis, and therapeutic response prediction. We propose two feature sets for the robust quantification of these characteristics in multiplex immunofluorescence (IF) microscopy images of prostate biopsy specimens. To enable feature extraction, EN and cytoplasm regions were first segmented from the IF images. Then, feature sets consisting of the characteristics of the minimum spanning tree (MST) connecting the EN and the fractal dimension (FD) of gland boundaries were obtained from the segmented compartments. We demonstrated the utility of the proposed features in prostate cancer recurrence prediction on a multi-institution cohort of 1027 patients. Univariate analysis revealed that both FD and one of the MST features were highly effective for predicting cancer recurrence (p <= 0.0001). In multivariate analysis, an MST feature was selected for a model incorporating clinical and image features. The model achieved a concordance index (CI) of 0.73 on the validation set, which was significantly higher than the CI of 0.69 for the standard multivariate model based solely on clinical features currently used in clinical practice (p < 0.0001). The contributions of this work are twofold. First, it is the first demonstration of the utility of the proposed features in morphometric analysis of IF images. Second, this is the largest scale study of the efficacy and robustness of the proposed features in prostate cancer prognosis.

Quantitative proteomics and network analysis of SSA1 and SSB1 deletion mutants reveals robustness of chaperone HSP70 network in Saccharomyces cerevisiae.

PubMed

Jarnuczak, Andrew F; Eyers, Claire E; Schwartz, Jean-Marc; Grant, Christopher M; Hubbard, Simon J

2015-09-01

Molecular chaperones play an important role in protein homeostasis and the cellular response to stress. In particular, the HSP70 chaperones in yeast mediate a large volume of protein folding through transient associations with their substrates. This chaperone interaction network can be disturbed by various perturbations, such as environmental stress or a gene deletion. Here, we consider deletions of two major chaperone proteins, SSA1 and SSB1, from the chaperone network in Sacchromyces cerevisiae. We employ a SILAC-based approach to examine changes in global and local protein abundance and rationalise our results via network analysis and graph theoretical approaches. Although the deletions result in an overall increase in intracellular protein content, correlated with an increase in cell size, this is not matched by substantial changes in individual protein concentrations. Despite the phenotypic robustness to deletion of these major hub proteins, it cannot be simply explained by the presence of paralogues. Instead, network analysis and a theoretical consideration of folding workload suggest that the robustness to perturbation is a product of the overall network structure. This highlights how quantitative proteomics and systems modelling can be used to rationalise emergent network properties, and how the HSP70 system can accommodate the loss of major hubs. © 2015 The Authors. PROTEOMICS published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mathematical study on robust tissue pattern formation in growing epididymal tubule.

PubMed

Hirashima, Tsuyoshi

2016-10-21

Tissue pattern formation during development is a reproducible morphogenetic process organized by a series of kinetic cellular activities, leading to the building of functional and stable organs. Recent studies focusing on mechanical aspects have revealed physical mechanisms on how the cellular activities contribute to the formation of reproducible tissue patterns; however, the understanding for what factors achieve the reproducibility of such patterning and how it occurs is far from complete. Here, I focus on a tube pattern formation during murine epididymal development, and show that two factors influencing physical design for the patterning, the proliferative zone within the tubule and the viscosity of tissues surrounding to the tubule, control the reproducibility of epididymal tubule pattern, using a mathematical model based on experimental data. Extensive numerical simulation of the simple mathematical model revealed that a spatially localized proliferative zone within the tubule, observed in experiments, results in more reproducible tubule pattern. Moreover, I found that the viscosity of tissues surrounding to the tubule imposes a trade-off regarding pattern reproducibility and spatial accuracy relating to the region where the tubule pattern is formed. This indicates an existence of optimality in material properties of tissues for the robust patterning of epididymal tubule. The results obtained by numerical analysis based on experimental observations provide a general insight on how physical design realizes robust tissue pattern formation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Heat-Passing Framework for Robust Interpretation of Data in Networks

PubMed Central

Fang, Yi; Sun, Mengtian; Ramani, Karthik

2015-01-01

Researchers are regularly interested in interpreting the multipartite structure of data entities according to their functional relationships. Data is often heterogeneous with intricately hidden inner structure. With limited prior knowledge, researchers are likely to confront the problem of transforming this data into knowledge. We develop a new framework, called heat-passing, which exploits intrinsic similarity relationships within noisy and incomplete raw data, and constructs a meaningful map of the data. The proposed framework is able to rank, cluster, and visualize the data all at once. The novelty of this framework is derived from an analogy between the process of data interpretation and that of heat transfer, in which all data points contribute simultaneously and globally to reveal intrinsic similarities between regions of data, meaningful coordinates for embedding the data, and exemplar data points that lie at optimal positions for heat transfer. We demonstrate the effectiveness of the heat-passing framework for robustly partitioning the complex networks, analyzing the globin family of proteins and determining conformational states of macromolecules in the presence of high levels of noise. The results indicate that the methodology is able to reveal functionally consistent relationships in a robust fashion with no reference to prior knowledge. The heat-passing framework is very general and has the potential for applications to a broad range of research fields, for example, biological networks, social networks and semantic analysis of documents. PMID:25668316

Robust Variable Selection with Exponential Squared Loss.

PubMed

Wang, Xueqin; Jiang, Yunlu; Huang, Mian; Zhang, Heping

2013-04-01

Robust variable selection procedures through penalized regression have been gaining increased attention in the literature. They can be used to perform variable selection and are expected to yield robust estimates. However, to the best of our knowledge, the robustness of those penalized regression procedures has not been well characterized. In this paper, we propose a class of penalized robust regression estimators based on exponential squared loss. The motivation for this new procedure is that it enables us to characterize its robustness that has not been done for the existing procedures, while its performance is near optimal and superior to some recently developed methods. Specifically, under defined regularity conditions, our estimators are [Formula: see text] and possess the oracle property. Importantly, we show that our estimators can achieve the highest asymptotic breakdown point of 1/2 and that their influence functions are bounded with respect to the outliers in either the response or the covariate domain. We performed simulation studies to compare our proposed method with some recent methods, using the oracle method as the benchmark. We consider common sources of influential points. Our simulation studies reveal that our proposed method performs similarly to the oracle method in terms of the model error and the positive selection rate even in the presence of influential points. In contrast, other existing procedures have a much lower non-causal selection rate. Furthermore, we re-analyze the Boston Housing Price Dataset and the Plasma Beta-Carotene Level Dataset that are commonly used examples for regression diagnostics of influential points. Our analysis unravels the discrepancies of using our robust method versus the other penalized regression method, underscoring the importance of developing and applying robust penalized regression methods.

Robust Variable Selection with Exponential Squared Loss

PubMed Central

Wang, Xueqin; Jiang, Yunlu; Huang, Mian; Zhang, Heping

2013-01-01

Robust variable selection procedures through penalized regression have been gaining increased attention in the literature. They can be used to perform variable selection and are expected to yield robust estimates. However, to the best of our knowledge, the robustness of those penalized regression procedures has not been well characterized. In this paper, we propose a class of penalized robust regression estimators based on exponential squared loss. The motivation for this new procedure is that it enables us to characterize its robustness that has not been done for the existing procedures, while its performance is near optimal and superior to some recently developed methods. Specifically, under defined regularity conditions, our estimators are n-consistent and possess the oracle property. Importantly, we show that our estimators can achieve the highest asymptotic breakdown point of 1/2 and that their influence functions are bounded with respect to the outliers in either the response or the covariate domain. We performed simulation studies to compare our proposed method with some recent methods, using the oracle method as the benchmark. We consider common sources of influential points. Our simulation studies reveal that our proposed method performs similarly to the oracle method in terms of the model error and the positive selection rate even in the presence of influential points. In contrast, other existing procedures have a much lower non-causal selection rate. Furthermore, we re-analyze the Boston Housing Price Dataset and the Plasma Beta-Carotene Level Dataset that are commonly used examples for regression diagnostics of influential points. Our analysis unravels the discrepancies of using our robust method versus the other penalized regression method, underscoring the importance of developing and applying robust penalized regression methods. PMID:23913996

Knowledge discovery by accuracy maximization

PubMed Central

Cacciatore, Stefano; Luchinat, Claudio; Tenori, Leonardo

2014-01-01

Here we describe KODAMA (knowledge discovery by accuracy maximization), an unsupervised and semisupervised learning algorithm that performs feature extraction from noisy and high-dimensional data. Unlike other data mining methods, the peculiarity of KODAMA is that it is driven by an integrated procedure of cross-validation of the results. The discovery of a local manifold’s topology is led by a classifier through a Monte Carlo procedure of maximization of cross-validated predictive accuracy. Briefly, our approach differs from previous methods in that it has an integrated procedure of validation of the results. In this way, the method ensures the highest robustness of the obtained solution. This robustness is demonstrated on experimental datasets of gene expression and metabolomics, where KODAMA compares favorably with other existing feature extraction methods. KODAMA is then applied to an astronomical dataset, revealing unexpected features. Interesting and not easily predictable features are also found in the analysis of the State of the Union speeches by American presidents: KODAMA reveals an abrupt linguistic transition sharply separating all post-Reagan from all pre-Reagan speeches. The transition occurs during Reagan’s presidency and not from its beginning. PMID:24706821

Influence of socioeconomic status on the whole blood transcriptome in African Americans.

PubMed

Gaye, Amadou; Gibbons, Gary H; Barry, Charles; Quarells, Rakale; Davis, Sharon K

2017-01-01

The correlation between low socioeconomic status (SES) and poor health outcome or higher risk of disease has been consistently reported by many epidemiological studies across various race/ancestry groups. However, the biological mechanisms linking low SES to disease and/or disease risk factors are not well understood and remain relatively under-studied. The analysis of the blood transcriptome is a promising window for elucidating how social and environmental factors influence the molecular networks governing health and disease. To further define the mechanistic pathways between social determinants and health, this study examined the impact of SES on the blood transcriptome in a sample of African-Americans. An integrative approach leveraging three complementary methods (Weighted Gene Co-expression Network Analysis, Random Forest and Differential Expression) was adopted to identify the most predictive and robust transcriptome pathways associated with SES. We analyzed the expression of 15079 genes (RNA-seq) from whole blood across 36 samples. The results revealed a cluster of 141 co-expressed genes over-expressed in the low SES group. Three pro-inflammatory pathways (IL-8 Signaling, NF-κB Signaling and Dendritic Cell Maturation) are activated in this module and over-expressed in low SES. Random Forest analysis revealed 55 of the 141 genes that, collectively, predict SES with an area under the curve of 0.85. One third of the 141 genes are significantly over-expressed in the low SES group. Lower SES has consistently been linked to many social and environmental conditions acting as stressors and known to be correlated with vulnerability to chronic illnesses (e.g. asthma, diabetes) associated with a chronic inflammatory state. Our unbiased analysis of the blood transcriptome in African-Americans revealed evidence of a robust molecular signature of increased inflammation associated with low SES. The results provide a plausible link between the social factors and chronic inflammation.

Robust Bayesian Analysis of Heavy-tailed Stochastic Volatility Models using Scale Mixtures of Normal Distributions

PubMed Central

Abanto-Valle, C. A.; Bandyopadhyay, D.; Lachos, V. H.; Enriquez, I.

2009-01-01

A Bayesian analysis of stochastic volatility (SV) models using the class of symmetric scale mixtures of normal (SMN) distributions is considered. In the face of non-normality, this provides an appealing robust alternative to the routine use of the normal distribution. Specific distributions examined include the normal, student-t, slash and the variance gamma distributions. Using a Bayesian paradigm, an efficient Markov chain Monte Carlo (MCMC) algorithm is introduced for parameter estimation. Moreover, the mixing parameters obtained as a by-product of the scale mixture representation can be used to identify outliers. The methods developed are applied to analyze daily stock returns data on S&P500 index. Bayesian model selection criteria as well as out-of- sample forecasting results reveal that the SV models based on heavy-tailed SMN distributions provide significant improvement in model fit as well as prediction to the S&P500 index data over the usual normal model. PMID:20730043

IARC use of oxidative stress as key mode of action characteristic for facilitating cancer classification: Glyphosate case example illustrating a lack of robustness in interpretative implementation.

PubMed

Bus, James S

2017-06-01

The International Agency for Research on Cancer (IARC) has formulated 10 key characteristics of human carcinogens to incorporate mechanistic data into cancer hazard classifications. The analysis used glyphosate as a case example to examine the robustness of IARC's determination of oxidative stress as "strong" evidence supporting a plausible cancer mechanism in humans. The IARC analysis primarily relied on 14 human/mammalian studies; 19 non-mammalian studies were uninformative of human cancer given the broad spectrum of test species and extensive use of formulations and aquatic testing. The mammalian studies had substantial experimental limitations for informing cancer mechanism including use of: single doses and time points; cytotoxic/toxic test doses; tissues not identified as potential cancer targets; glyphosate formulations or mixtures; technically limited oxidative stress biomarkers. The doses were many orders of magnitude higher than human exposures determined in human biomonitoring studies. The glyphosate case example reveals that the IARC evaluation fell substantially short of "strong" supporting evidence of oxidative stress as a plausible human cancer mechanism, and suggests that other IARC monographs relying on the 10 key characteristics approach should be similarly examined for a lack of robust data integration fundamental to reasonable mode of action evaluations. Copyright © 2017 Elsevier Inc. All rights reserved.

Craniofacial variation and dietary adaptations of African colobines.

PubMed

Koyabu, Daisuke B; Endo, Hideki

2009-06-01

African colobine monkeys show considerable craniofacial variation among species, although the evolutionary causes of this diversity are unclear. In light of growing evidence that diet varies considerably among colobine species, we investigated whether colobine craniofacial morphology varies as a function of their diet. We compared craniofacial morphology among five African species: Colobus angolensis, C. guereza, C. polykomos, Piliocolobus badius, and P. verus. Matrix correlation analysis indicated a significant correlation between species-specific morphological distance and dietary distance matrices. The mechanical advantage of the masseter muscle was higher in seed-eaters (C. angolensis and C. polykomos) and lower in those that eat mainly young leaves (C. guereza, P. badius, and P. verus). Canonical correspondence analysis revealed that the durophagous colobines possess relatively wider bigonial breadths, anteroposteriorly shorter faces, shorter postcanine tooth rows, more medially positioned dental batteries, wider bizygomatic arches, and anteroposteriorly longer zygomatic arches. Under the constrained lever model, these morphological features suggest that durophagous colobines have the capacity to generate relatively greater maximum bite forces. However, no consistent relationship was observed between diet and variation in the mandibular corpus and symphysis, implying that robust mandibles are not necessarily adaptations for stress resistance. Factors that may influence mandibular robusticity include allometry of symphyseal curvature and canine tooth support. Finally, linear measures of mandibular robusticity may suffer from error.

Improving Robustness of Hydrologic Ensemble Predictions Through Probabilistic Pre- and Post-Processing in Sequential Data Assimilation

NASA Astrophysics Data System (ADS)

Wang, S.; Ancell, B. C.; Huang, G. H.; Baetz, B. W.

2018-03-01

Data assimilation using the ensemble Kalman filter (EnKF) has been increasingly recognized as a promising tool for probabilistic hydrologic predictions. However, little effort has been made to conduct the pre- and post-processing of assimilation experiments, posing a significant challenge in achieving the best performance of hydrologic predictions. This paper presents a unified data assimilation framework for improving the robustness of hydrologic ensemble predictions. Statistical pre-processing of assimilation experiments is conducted through the factorial design and analysis to identify the best EnKF settings with maximized performance. After the data assimilation operation, statistical post-processing analysis is also performed through the factorial polynomial chaos expansion to efficiently address uncertainties in hydrologic predictions, as well as to explicitly reveal potential interactions among model parameters and their contributions to the predictive accuracy. In addition, the Gaussian anamorphosis is used to establish a seamless bridge between data assimilation and uncertainty quantification of hydrologic predictions. Both synthetic and real data assimilation experiments are carried out to demonstrate feasibility and applicability of the proposed methodology in the Guadalupe River basin, Texas. Results suggest that statistical pre- and post-processing of data assimilation experiments provide meaningful insights into the dynamic behavior of hydrologic systems and enhance robustness of hydrologic ensemble predictions.

Robust Methods for Moderation Analysis with a Two-Level Regression Model.

PubMed

Yang, Miao; Yuan, Ke-Hai

2016-01-01

Moderation analysis has many applications in social sciences. Most widely used estimation methods for moderation analysis assume that errors are normally distributed and homoscedastic. When these assumptions are not met, the results from a classical moderation analysis can be misleading. For more reliable moderation analysis, this article proposes two robust methods with a two-level regression model when the predictors do not contain measurement error. One method is based on maximum likelihood with Student's t distribution and the other is based on M-estimators with Huber-type weights. An algorithm for obtaining the robust estimators is developed. Consistent estimates of standard errors of the robust estimators are provided. The robust approaches are compared against normal-distribution-based maximum likelihood (NML) with respect to power and accuracy of parameter estimates through a simulation study. Results show that the robust approaches outperform NML under various distributional conditions. Application of the robust methods is illustrated through a real data example. An R program is developed and documented to facilitate the application of the robust methods.

GoIFISH: a system for the quantification of single cell heterogeneity from IFISH images.

PubMed

Trinh, Anne; Rye, Inga H; Almendro, Vanessa; Helland, Aslaug; Russnes, Hege G; Markowetz, Florian

2014-08-26

Molecular analysis has revealed extensive intra-tumor heterogeneity in human cancer samples, but cannot identify cell-to-cell variations within the tissue microenvironment. In contrast, in situ analysis can identify genetic aberrations in phenotypically defined cell subpopulations while preserving tissue-context specificity. GoIFISHGoIFISH is a widely applicable, user-friendly system tailored for the objective and semi-automated visualization, detection and quantification of genomic alterations and protein expression obtained from fluorescence in situ analysis. In a sample set of HER2-positive breast cancers GoIFISHGoIFISH is highly robust in visual analysis and its accuracy compares favorably to other leading image analysis methods. GoIFISHGoIFISH is freely available at www.sourceforge.net/projects/goifish/.

A Sensitivity Analysis of the Nocturnal Boundary-Layer Properties to Atmospheric Emissivity Formulations

NASA Astrophysics Data System (ADS)

Siqueira, Mario B.; Katul, Gabriel G.

2010-02-01

A one-dimensional model for the mean potential temperature within the nocturnal boundary layer (NBL) was used to assess the sensitivity of three NBL properties (height, thermal stratification strength, and near-surface cooling) to three widely used atmospheric emissivity formulations. The calculations revealed that the NBL height is robust to the choice of the emissivity function, though this is not the case for NBL Richardson number and near-surface cooling rate. Rather than endorse one formulation, our analysis highlights the importance of atmospheric emissivity in modelling the radiative properties of the NBL especially for clear-sky conditions.

The mechanism of folding robustness revealed by the crystal structure of extra-superfolder GFP.

PubMed

Choi, Jae Young; Jang, Tae-Ho; Park, Hyun Ho

2017-01-01

Stability of green fluorescent protein (GFP) is sometimes important for a proper practical application of this protein. Random mutagenesis and targeted mutagenesis have been used to create better-folded variants of GFP, including recently reported extra-superfolder GFP. Our aim was to determine the crystal structure of extra-superfolder GFP, which is more robustly folded and stable than GFP and superfolder GFP. The structural and structure-based mutagenesis analyses revealed that some of the mutations that created extra-superfolder GFP (F46L, E126K, N149K, and S208L) contribute to folding robustness by stabilizing extra-superfolder GFP with various noncovalent bonds. © 2016 Federation of European Biochemical Societies.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agnew, Douglas W.; DiMucci, Ida M.; Arroyave, Alejandra

A permanently porous, three-dimensional metal–organic material formed from zero-valent metal nodes is presented. Combination of ditopic m-terphenyl diisocyanide, [CNAr Mes2] 2, and the d 10 Ni(0) precursor Ni(COD) 2, produces a porous metal–organic material featuring tetrahedral [Ni(CNAr Mes2) 4] n structural sites. X-ray absorption spectroscopy provides firm evidence for the presence of Ni(0) centers, whereas gas-sorption and thermogravimetric analysis reveal the characteristics of a robust network with a microdomain N 2-adsorption profile.

A comparison of a novel robust decentralised control strategy and MPC for industrial high purity, high recovery, multicomponent distillation.

PubMed

Udugama, Isuru A; Wolfenstetter, Florian; Kirkpatrick, Robert; Yu, Wei; Young, Brent R

2017-07-01

In this work we have developed a novel, robust practical control structure to regulate an industrial methanol distillation column. This proposed control scheme is based on a override control framework and can manage a non-key trace ethanol product impurity specification while maintaining high product recovery. For comparison purposes, a MPC with a discrete process model (based on step tests) was also developed and tested. The results from process disturbance testing shows that, both the MPC and the proposed controller were capable of maintaining both the trace level ethanol specification in the distillate (X D ) and high product recovery (β). Closer analysis revealed that the MPC controller has a tighter X D control, while the proposed controller was tighter in β control. The tight X D control allowed the MPC to operate at a higher X D set point (closer to the 10ppm AA grade methanol standard), allowing for savings in energy usage. Despite the energy savings of the MPC, the proposed control scheme has lower installation and running costs. An economic analysis revealed a multitude of other external economic and plant design factors, that should be considered when making a decision between the two controllers. In general, we found relatively high energy costs favour MPC. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A comparative study of multivariable robustness analysis methods as applied to integrated flight and propulsion control

NASA Technical Reports Server (NTRS)

Schierman, John D.; Lovell, T. A.; Schmidt, David K.

1993-01-01

Three multivariable robustness analysis methods are compared and contrasted. The focus of the analysis is on system stability and performance robustness to uncertainty in the coupling dynamics between two interacting subsystems. Of particular interest is interacting airframe and engine subsystems, and an example airframe/engine vehicle configuration is utilized in the demonstration of these approaches. The singular value (SV) and structured singular value (SSV) analysis methods are compared to a method especially well suited for analysis of robustness to uncertainties in subsystem interactions. This approach is referred to here as the interacting subsystem (IS) analysis method. This method has been used previously to analyze airframe/engine systems, emphasizing the study of stability robustness. However, performance robustness is also investigated here, and a new measure of allowable uncertainty for acceptable performance robustness is introduced. The IS methodology does not require plant uncertainty models to measure the robustness of the system, and is shown to yield valuable information regarding the effects of subsystem interactions. In contrast, the SV and SSV methods allow for the evaluation of the robustness of the system to particular models of uncertainty, and do not directly indicate how the airframe (engine) subsystem interacts with the engine (airframe) subsystem.

Synaptic activation patterns of the perirhinal-entorhinal inter-connections.

PubMed

de Villers-Sidani, E; Tahvildari, B; Alonso, A

2004-01-01

Ample neuropsychological evidence supports the role of rhinal cortices in memory. The perirhinal cortex (PRC) represents one of the main conduits for the bi-directional flow of information between the entorhinal-hippocampal network and the cortical mantle, a process essential in memory formation. However, despite anatomical evidence for a robust reciprocal connectivity between the perirhinal and entorhinal cortices, neurophysiological understanding of this circuitry is lacking. We now present the results of a series of electrophysiological experiments in rats that demonstrate robust synaptic activation patterns of the perirhinal-entorhinal inter-connections. First, using silicon multi-electrode arrays placed under visual guidance in vivo we performed current source density (CSD) analysis of lateral entorhinal cortex (LEC) responses to PRC stimulation, which demonstrated a current sink in layers II-III of the LEC with a latency consistent with monosynaptic activation. To further substantiate and extend this conclusion, we developed a PRC-LEC slice preparation where CSD analysis also revealed a current sink in superficial LEC layers in response to PRC stimulation. Importantly, intracellular recording of superficial LEC layer neurons confirmed that they receive a major monosynaptic excitatory input from the PRC. Finally, CSD analysis of the LEC to PRC projection in vivo also allowed us to document robust feedback synaptic activation of PRC neurons to deep LEC layer activation. We conclude that a clear bidirectional pattern of synaptic interactions exists between the PRC and LEC that would support a dynamic flow of information subserving memory function in the temporal lobe.

Analysis of Family Structures Reveals Robustness or Sensitivity of Bursting Activity to Parameter Variations in a Half-Center Oscillator (HCO) Model.

PubMed

Doloc-Mihu, Anca; Calabrese, Ronald L

2016-01-01

The underlying mechanisms that support robustness in neuronal networks are as yet unknown. However, recent studies provide evidence that neuronal networks are robust to natural variations, modulation, and environmental perturbations of parameters, such as maximal conductances of intrinsic membrane and synaptic currents. Here we sought a method for assessing robustness, which might easily be applied to large brute-force databases of model instances. Starting with groups of instances with appropriate activity (e.g., tonic spiking), our method classifies instances into much smaller subgroups, called families, in which all members vary only by the one parameter that defines the family. By analyzing the structures of families, we developed measures of robustness for activity type. Then, we applied these measures to our previously developed model database, HCO-db, of a two-neuron half-center oscillator (HCO), a neuronal microcircuit from the leech heartbeat central pattern generator where the appropriate activity type is alternating bursting. In HCO-db, the maximal conductances of five intrinsic and two synaptic currents were varied over eight values (leak reversal potential also varied, five values). We focused on how variations of particular conductance parameters maintain normal alternating bursting activity while still allowing for functional modulation of period and spike frequency. We explored the trade-off between robustness of activity type and desirable change in activity characteristics when intrinsic conductances are altered and identified the hyperpolarization-activated (h) current as an ideal target for modulation. We also identified ensembles of model instances that closely approximate physiological activity and can be used in future modeling studies.

Mean-field analysis of an inductive reasoning game: Application to influenza vaccination

NASA Astrophysics Data System (ADS)

Breban, Romulus; Vardavas, Raffaele; Blower, Sally

2007-09-01

Recently we have introduced an inductive reasoning game of voluntary yearly vaccination to establish whether or not a population of individuals acting in their own self-interest would be able to prevent influenza epidemics. Here, we analyze our model to describe the dynamics of the collective yearly vaccination uptake. We discuss the mean-field equations of our model and first order effects of fluctuations. We explain why our model predicts that severe epidemics are periodically expected even without the introduction of pandemic strains. We find that fluctuations in the collective yearly vaccination uptake induce severe epidemics with an expected periodicity that depends on the number of independent decision makers in the population. The mean-field dynamics also reveal that there are conditions for which the dynamics become robust to the fluctuations. However, the transition between fluctuation-sensitive and fluctuation-robust dynamics occurs for biologically implausible parameters. We also analyze our model when incentive-based vaccination programs are offered. When a family-based incentive is offered, the expected periodicity of severe epidemics is increased. This results from the fact that the number of independent decision makers is reduced, increasing the effect of the fluctuations. However, incentives based on the number of years of prepayment of vaccination may yield fluctuation-robust dynamics where severe epidemics are prevented. In this case, depending on prepayment, the transition between fluctuation-sensitive and fluctuation-robust dynamics may occur for biologically plausible parameters. Our analysis provides a practical method for identifying how many years of free vaccination should be provided in order to successfully ameliorate influenza epidemics.

Mean-field analysis of an inductive reasoning game: application to influenza vaccination.

PubMed

Breban, Romulus; Vardavas, Raffaele; Blower, Sally

2007-09-01

Recently we have introduced an inductive reasoning game of voluntary yearly vaccination to establish whether or not a population of individuals acting in their own self-interest would be able to prevent influenza epidemics. Here, we analyze our model to describe the dynamics of the collective yearly vaccination uptake. We discuss the mean-field equations of our model and first order effects of fluctuations. We explain why our model predicts that severe epidemics are periodically expected even without the introduction of pandemic strains. We find that fluctuations in the collective yearly vaccination uptake induce severe epidemics with an expected periodicity that depends on the number of independent decision makers in the population. The mean-field dynamics also reveal that there are conditions for which the dynamics become robust to the fluctuations. However, the transition between fluctuation-sensitive and fluctuation-robust dynamics occurs for biologically implausible parameters. We also analyze our model when incentive-based vaccination programs are offered. When a family-based incentive is offered, the expected periodicity of severe epidemics is increased. This results from the fact that the number of independent decision makers is reduced, increasing the effect of the fluctuations. However, incentives based on the number of years of prepayment of vaccination may yield fluctuation-robust dynamics where severe epidemics are prevented. In this case, depending on prepayment, the transition between fluctuation-sensitive and fluctuation-robust dynamics may occur for biologically plausible parameters. Our analysis provides a practical method for identifying how many years of free vaccination should be provided in order to successfully ameliorate influenza epidemics.

Robustness of free and pinned spiral waves against breakup by electrical forcing in excitable chemical media.

PubMed

Phantu, Metinee; Sutthiopad, Malee; Luengviriya, Jiraporn; Müller, Stefan C; Luengviriya, Chaiya

2017-04-01

We present an investigation on the breakup of free and pinned spiral waves under an applied electrical current in the Belousov-Zhabotinsky reaction. Spiral fronts propagating towards the negative electrode are decelerated. A breakup of the spiral waves occurs when some segments of the fronts are stopped by a sufficiently strong electrical current. In the absence of obstacles (i.e., free spiral waves), the critical value of the electrical current for the wave breakup increases with the excitability of the medium. For spiral waves pinned to circular obstacles, the critical electrical current increases with the obstacle diameter. Analysis of spiral dynamics shows that the enhancement of the robustness against the breakup of both free and pinned spiral waves is originated by the increment of wave speed when either the excitability is strengthened or the obstacle size is enlarged. The experimental findings are reproduced by numerical simulations using the Oregonator model. In addition, the simulations reveal that the robustness against the forced breakup increases with the activator level in both cases of free and pinned spiral waves.

Functional modules of sigma factor regulons guarantee adaptability and evolvability

PubMed Central

Binder, Sebastian C.; Eckweiler, Denitsa; Schulz, Sebastian; Bielecka, Agata; Nicolai, Tanja; Franke, Raimo; Häussler, Susanne; Meyer-Hermann, Michael

2016-01-01

The focus of modern molecular biology turns from assigning functions to individual genes towards understanding the expression and regulation of complex sets of molecules. Here, we provide evidence that alternative sigma factor regulons in the pathogen Pseudomonas aeruginosa largely represent insulated functional modules which provide a critical level of biological organization involved in general adaptation and survival processes. Analysis of the operational state of the sigma factor network revealed that transcription factors functionally couple the sigma factor regulons and significantly modulate the transcription levels in the face of challenging environments. The threshold quality of newly evolved transcription factors was reached faster and more robustly in in silico testing when the structural organization of sigma factor networks was taken into account. These results indicate that the modular structures of alternative sigma factor regulons provide P. aeruginosa with a robust framework to function adequately in its environment and at the same time facilitate evolutionary change. Our data support the view that widespread modularity guarantees robustness of biological networks and is a key driver of evolvability. PMID:26915971

Robustness of critical points in a complex adaptive system: Effects of hedge behavior

NASA Astrophysics Data System (ADS)

Liang, Yuan; Huang, Ji-Ping

2013-08-01

In our recent papers, we have identified a class of phase transitions in the market-directed resource-allocation game, and found that there exists a critical point at which the phase transitions occur. The critical point is given by a certain resource ratio. Here, by performing computer simulations and theoretical analysis, we report that the critical point is robust against various kinds of human hedge behavior where the numbers of herds and contrarians can be varied widely. This means that the critical point can be independent of the total number of participants composed of normal agents, herds and contrarians, under some conditions. This finding means that the critical points we identified in this complex adaptive system (with adaptive agents) may also be an intensive quantity, similar to those revealed in traditional physical systems (with non-adaptive units).

Revealing how network structure affects accuracy of link prediction

NASA Astrophysics Data System (ADS)

Yang, Jin-Xuan; Zhang, Xiao-Dong

2017-08-01

Link prediction plays an important role in network reconstruction and network evolution. The network structure affects the accuracy of link prediction, which is an interesting problem. In this paper we use common neighbors and the Gini coefficient to reveal the relation between them, which can provide a good reference for the choice of a suitable link prediction algorithm according to the network structure. Moreover, the statistical analysis reveals correlation between the common neighbors index, Gini coefficient index and other indices to describe the network structure, such as Laplacian eigenvalues, clustering coefficient, degree heterogeneity, and assortativity of network. Furthermore, a new method to predict missing links is proposed. The experimental results show that the proposed algorithm yields better prediction accuracy and robustness to the network structure than existing currently used methods for a variety of real-world networks.

Bright discrete solitons in spatially modulated DNLS systems

DOE PAGES

Kevrekidis, P. G.; Horne, R. L.; Whitaker, N.; ...

2015-08-04

In the present work, we revisit the highly active research area of inhomogeneously nonlinear defocusing media and consider the existence, spectral stability and nonlinear dynamics of bright solitary waves in them. We use the anti-continuum limit of vanishing coupling as the starting point of our analysis, enabling in this way a systematic characterization of the branches of solutions. Our stability findings and bifurcation characteristics reveal the enhanced robustness and wider existence intervals of solutions with a broader support, culminating in the 'extended' solution in which all sites are excited. Our eigenvalue predictions are corroborated by numerical linear stability analysis. Inmore » conclusion, the dynamics also reveal a tendency of the solution profiles to broaden, in line with the above findings. These results pave the way for further explorations of such states in discrete systems, including in higher dimensional settings.« less

Uncertainties propagation and global sensitivity analysis of the frequency response function of piezoelectric energy harvesters

NASA Astrophysics Data System (ADS)

Ruiz, Rafael O.; Meruane, Viviana

2017-06-01

The goal of this work is to describe a framework to propagate uncertainties in piezoelectric energy harvesters (PEHs). These uncertainties are related to the incomplete knowledge of the model parameters. The framework presented could be employed to conduct prior robust stochastic predictions. The prior analysis assumes a known probability density function for the uncertain variables and propagates the uncertainties to the output voltage. The framework is particularized to evaluate the behavior of the frequency response functions (FRFs) in PEHs, while its implementation is illustrated by the use of different unimorph and bimorph PEHs subjected to different scenarios: free of uncertainties, common uncertainties, and uncertainties as a product of imperfect clamping. The common variability associated with the PEH parameters are tabulated and reported. A global sensitivity analysis is conducted to identify the Sobol indices. Results indicate that the elastic modulus, density, and thickness of the piezoelectric layer are the most relevant parameters of the output variability. The importance of including the model parameter uncertainties in the estimation of the FRFs is revealed. In this sense, the present framework constitutes a powerful tool in the robust design and prediction of PEH performance.

A New Color Image Encryption Scheme Using CML and a Fractional-Order Chaotic System

PubMed Central

Wu, Xiangjun; Li, Yang; Kurths, Jürgen

2015-01-01

The chaos-based image cryptosystems have been widely investigated in recent years to provide real-time encryption and transmission. In this paper, a novel color image encryption algorithm by using coupled-map lattices (CML) and a fractional-order chaotic system is proposed to enhance the security and robustness of the encryption algorithms with a permutation-diffusion structure. To make the encryption procedure more confusing and complex, an image division-shuffling process is put forward, where the plain-image is first divided into four sub-images, and then the position of the pixels in the whole image is shuffled. In order to generate initial conditions and parameters of two chaotic systems, a 280-bit long external secret key is employed. The key space analysis, various statistical analysis, information entropy analysis, differential analysis and key sensitivity analysis are introduced to test the security of the new image encryption algorithm. The cryptosystem speed is analyzed and tested as well. Experimental results confirm that, in comparison to other image encryption schemes, the new algorithm has higher security and is fast for practical image encryption. Moreover, an extensive tolerance analysis of some common image processing operations such as noise adding, cropping, JPEG compression, rotation, brightening and darkening, has been performed on the proposed image encryption technique. Corresponding results reveal that the proposed image encryption method has good robustness against some image processing operations and geometric attacks. PMID:25826602

Stability and Responsiveness in a Self-Organized Living Architecture

PubMed Central

Garnier, Simon; Murphy, Tucker; Lutz, Matthew; Hurme, Edward; Leblanc, Simon; Couzin, Iain D.

2013-01-01

Robustness and adaptability are central to the functioning of biological systems, from gene networks to animal societies. Yet the mechanisms by which living organisms achieve both stability to perturbations and sensitivity to input are poorly understood. Here, we present an integrated study of a living architecture in which army ants interconnect their bodies to span gaps. We demonstrate that these self-assembled bridges are a highly effective means of maintaining traffic flow over unpredictable terrain. The individual-level rules responsible depend only on locally-estimated traffic intensity and the number of neighbours to which ants are attached within the structure. We employ a parameterized computational model to reveal that bridges are tuned to be maximally stable in the face of regular, periodic fluctuations in traffic. However analysis of the model also suggests that interactions among ants give rise to feedback processes that result in bridges being highly responsive to sudden interruptions in traffic. Subsequent field experiments confirm this prediction and thus the dual nature of stability and flexibility in living bridges. Our study demonstrates the importance of robust and adaptive modular architecture to efficient traffic organisation and reveals general principles regarding the regulation of form in biological self-assemblies. PMID:23555219

Precise calculation of a bond percolation transition and survival rates of nodes in a complex network.

PubMed

Kawamoto, Hirokazu; Takayasu, Hideki; Jensen, Henrik Jeldtoft; Takayasu, Misako

2015-01-01

Through precise numerical analysis, we reveal a new type of universal loopless percolation transition in randomly removed complex networks. As an example of a real-world network, we apply our analysis to a business relation network consisting of approximately 3,000,000 links among 300,000 firms and observe the transition with critical exponents close to the mean-field values taking into account the finite size effect. We focus on the largest cluster at the critical point, and introduce survival probability as a new measure characterizing the robustness of each node. We also discuss the relation between survival probability and k-shell decomposition.

Is Disgust Proneness Associated With Anxiety and Related Disorders? A Qualitative Review and Meta-Analysis of Group Comparison and Correlational Studies.

PubMed

Olatunji, Bunmi O; Armstrong, Thomas; Elwood, Lisa

2017-07-01

Research suggests that disgust may be linked to the etiology of some anxiety-related disorders. The present investigation reviews this literature and employs separate meta-analyses of clinical group comparison and correlational studies to examine the association between disgust proneness and anxiety-related disorder symptoms. Meta-analysis of 43 group comparison studies revealed those high in anxiety disorder symptoms reported significantly more disgust proneness than those low in anxiety symptoms. Although this effect was not moderated by clinical versus analogue studies or type of disorder, larger group differences were observed for those high in anxiety symptoms associated with contagion concerns compared to those high in anxiety symptoms not associated with contagion concerns. Similarly, meta-analysis of correlational data across 83 samples revealed moderate associations between disgust proneness and anxiety-related disorder symptoms. Moderator analysis revealed that the association between disgust proneness and anxiety-related disorder symptoms was especially robust for anxiety symptoms associated with contagion concerns. After controlling for measures of negative affect, disgust proneness continued to be moderately correlated with anxiety-related disorder symptoms. However, negative affect was no longer significantly associated with symptoms of anxiety-related disorders when controlling for disgust proneness. The implications of these findings are discussed in the context of a novel transdiagnostic model.

Steep Delay Discounting and Addictive Behavior: A Meta-Analysis of Continuous Associations

PubMed Central

Amlung, Michael; Vedelago, Lana; Acker, John; Balodis, Iris; MacKillop, James

2016-01-01

Aims To synthesize continuous associations between delayed reward discounting (DRD) and both addiction severity and quantity-frequency (QF); to examine moderators of these relationships; and to investigate publication bias. Methods Meta-analysis of published studies examining continuous associations between DRD and addictive behaviors. Published, peer-reviewed studies on addictive behaviors (alcohol, tobacco, cannabis, stimulants, opiates, and gambling) were identified via PubMed, MEDLINE, and PsycInfo. Studies were restricted to DRD measures of monetary gains. Random effects meta-analysis was conducted using Pearson’s r as the effect size. Publication bias was evaluated using fail-safe N, Begg-Mazumdar and Egger’s tests, meta-regression of publication year and effect size, and imputation of missing studies. Results The primary meta-analysis revealed a small magnitude effect size that was highly significant (r = 0.14, p < 10−14). Significantly larger effect sizes were observed for studies examining severity compared with QF (p = 0.01), but not between the type of addictive behavior (p = 0.30) or DRD assessment (p = 0.90). Indices of publication bias suggested a modest impact of unpublished findings. Conclusions Delayed reward discounting is robustly associated with continuous measures of addiction severity and quantity-frequency. This relation is generally robust across type of addictive behavior and delayed reward discounting assessment modality. PMID:27450931

Robustness Analysis and Optimally Robust Control Design via Sum-of-Squares

NASA Technical Reports Server (NTRS)

Dorobantu, Andrei; Crespo, Luis G.; Seiler, Peter J.

2012-01-01

A control analysis and design framework is proposed for systems subject to parametric uncertainty. The underlying strategies are based on sum-of-squares (SOS) polynomial analysis and nonlinear optimization to design an optimally robust controller. The approach determines a maximum uncertainty range for which the closed-loop system satisfies a set of stability and performance requirements. These requirements, de ned as inequality constraints on several metrics, are restricted to polynomial functions of the uncertainty. To quantify robustness, SOS analysis is used to prove that the closed-loop system complies with the requirements for a given uncertainty range. The maximum uncertainty range, calculated by assessing a sequence of increasingly larger ranges, serves as a robustness metric for the closed-loop system. To optimize the control design, nonlinear optimization is used to enlarge the maximum uncertainty range by tuning the controller gains. Hence, the resulting controller is optimally robust to parametric uncertainty. This approach balances the robustness margins corresponding to each requirement in order to maximize the aggregate system robustness. The proposed framework is applied to a simple linear short-period aircraft model with uncertain aerodynamic coefficients.

Optimizing 4-Dimensional Magnetic Resonance Imaging Data Sampling for Respiratory Motion Analysis of Pancreatic Tumors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stemkens, Bjorn, E-mail: b.stemkens@umcutrecht.nl; Tijssen, Rob H.N.; Senneville, Baudouin D. de

2015-03-01

Purpose: To determine the optimum sampling strategy for retrospective reconstruction of 4-dimensional (4D) MR data for nonrigid motion characterization of tumor and organs at risk for radiation therapy purposes. Methods and Materials: For optimization, we compared 2 surrogate signals (external respiratory bellows and internal MRI navigators) and 2 MR sampling strategies (Cartesian and radial) in terms of image quality and robustness. Using the optimized protocol, 6 pancreatic cancer patients were scanned to calculate the 4D motion. Region of interest analysis was performed to characterize the respiratory-induced motion of the tumor and organs at risk simultaneously. Results: The MRI navigator was foundmore » to be a more reliable surrogate for pancreatic motion than the respiratory bellows signal. Radial sampling is most benign for undersampling artifacts and intraview motion. Motion characterization revealed interorgan and interpatient variation, as well as heterogeneity within the tumor. Conclusions: A robust 4D-MRI method, based on clinically available protocols, is presented and successfully applied to characterize the abdominal motion in a small number of pancreatic cancer patients.« less

Statistical Analysis of Bus Networks in India

PubMed Central

2016-01-01

In this paper, we model the bus networks of six major Indian cities as graphs in L-space, and evaluate their various statistical properties. While airline and railway networks have been extensively studied, a comprehensive study on the structure and growth of bus networks is lacking. In India, where bus transport plays an important role in day-to-day commutation, it is of significant interest to analyze its topological structure and answer basic questions on its evolution, growth, robustness and resiliency. Although the common feature of small-world property is observed, our analysis reveals a wide spectrum of network topologies arising due to significant variation in the degree-distribution patterns in the networks. We also observe that these networks although, robust and resilient to random attacks are particularly degree-sensitive. Unlike real-world networks, such as Internet, WWW and airline, that are virtual, bus networks are physically constrained. Our findings therefore, throw light on the evolution of such geographically and constrained networks that will help us in designing more efficient bus networks in the future. PMID:27992590

Evaluation of Ares-I Control System Robustness to Uncertain Aerodynamics and Flex Dynamics

NASA Technical Reports Server (NTRS)

Jang, Jiann-Woei; VanTassel, Chris; Bedrossian, Nazareth; Hall, Charles; Spanos, Pol

2008-01-01

This paper discusses the application of robust control theory to evaluate robustness of the Ares-I control systems. Three techniques for estimating upper and lower bounds of uncertain parameters which yield stable closed-loop response are used here: (1) Monte Carlo analysis, (2) mu analysis, and (3) characteristic frequency response analysis. All three methods are used to evaluate stability envelopes of the Ares-I control systems with uncertain aerodynamics and flex dynamics. The results show that characteristic frequency response analysis is the most effective of these methods for assessing robustness.

Transcriptome analysis in tardigrade species reveals specific molecular pathways for stress adaptations.

PubMed

Förster, Frank; Beisser, Daniela; Grohme, Markus A; Liang, Chunguang; Mali, Brahim; Siegl, Alexander Matthias; Engelmann, Julia C; Shkumatov, Alexander V; Schokraie, Elham; Müller, Tobias; Schnölzer, Martina; Schill, Ralph O; Frohme, Marcus; Dandekar, Thomas

2012-01-01

Tardigrades have unique stress-adaptations that allow them to survive extremes of cold, heat, radiation and vacuum. To study this, encoded protein clusters and pathways from an ongoing transcriptome study on the tardigrade Milnesium tardigradum were analyzed using bioinformatics tools and compared to expressed sequence tags (ESTs) from Hypsibius dujardini, revealing major pathways involved in resistance against extreme environmental conditions. ESTs are available on the Tardigrade Workbench along with software and databank updates. Our analysis reveals that RNA stability motifs for M. tardigradum are different from typical motifs known from higher animals. M. tardigradum and H. dujardini protein clusters and conserved domains imply metabolic storage pathways for glycogen, glycolipids and specific secondary metabolism as well as stress response pathways (including heat shock proteins, bmh2, and specific repair pathways). Redox-, DNA-, stress- and protein protection pathways complement specific repair capabilities to achieve the strong robustness of M. tardigradum. These pathways are partly conserved in other animals and their manipulation could boost stress adaptation even in human cells. However, the unique combination of resistance and repair pathways make tardigrades and M. tardigradum in particular so highly stress resistant.

Compactness and robustness: Applications in the solution of integral equations for chemical kinetics and electromagnetic scattering

NASA Astrophysics Data System (ADS)

Zhou, Yajun

This thesis employs the topological concept of compactness to deduce robust solutions to two integral equations arising from chemistry and physics: the inverse Laplace problem in chemical kinetics and the vector wave scattering problem in dielectric optics. The inverse Laplace problem occurs in the quantitative understanding of biological processes that exhibit complex kinetic behavior: different subpopulations of transition events from the "reactant" state to the "product" state follow distinct reaction rate constants, which results in a weighted superposition of exponential decay modes. Reconstruction of the rate constant distribution from kinetic data is often critical for mechanistic understandings of chemical reactions related to biological macromolecules. We devise a "phase function approach" to recover the probability distribution of rate constants from decay data in the time domain. The robustness (numerical stability) of this reconstruction algorithm builds upon the continuity of the transformations connecting the relevant function spaces that are compact metric spaces. The robust "phase function approach" not only is useful for the analysis of heterogeneous subpopulations of exponential decays within a single transition step, but also is generalizable to the kinetic analysis of complex chemical reactions that involve multiple intermediate steps. A quantitative characterization of the light scattering is central to many meteoro-logical, optical, and medical applications. We give a rigorous treatment to electromagnetic scattering on arbitrarily shaped dielectric media via the Born equation: an integral equation with a strongly singular convolution kernel that corresponds to a non-compact Green operator. By constructing a quadratic polynomial of the Green operator that cancels out the kernel singularity and satisfies the compactness criterion, we reveal the universality of a real resonance mode in dielectric optics. Meanwhile, exploiting the properties of compact operators, we outline the geometric and physical conditions that guarantee a robust solution to the light scattering problem, and devise an asymptotic solution to the Born equation of electromagnetic scattering for arbitrarily shaped dielectric in a non-perturbative manner.

Interactions of Mitochondria/Metabolism and Calcium Regulation in Alzheimer’s Disease - A Calcinist Point of View

PubMed Central

Gibson, Gary E.; Thakkar, Ankita

2017-01-01

Decades of research suggest that alterations in calcium are central to the pathophysiology of Alzheimer’s Disease (AD). Highly reproducible changes in calcium dynamics occur in cells from patients with both genetic and non-genetic forms of AD relative to controls. The most robust change is an exaggerated release of calcium from internal stores. Detailed analysis of these changes in animal and cell models of the AD-causing presenilin mutations reveal robust changes in ryanodine receptors, inositol tris-phosphate receptors, calcium leak channels and store activated calcium entry. Similar anomalies in calcium result when AD-like changes in mitochondrial enzymes or oxidative stress are induced experimentally. The calcium abnormalities can be directly linked to the altered tau phosphorylation, amyloid precursor protein processing and synaptic dysfunction that are defining features of AD. A better understanding of these changes is required before using calcium abnormalities as therapeutic targets. PMID:28181072

Interactions of Mitochondria/Metabolism and Calcium Regulation in Alzheimer's Disease: A Calcinist Point of View.

PubMed

Gibson, Gary E; Thakkar, Ankita

2017-06-01

Decades of research suggest that alterations in calcium are central to the pathophysiology of Alzheimer's Disease (AD). Highly reproducible changes in calcium dynamics occur in cells from patients with both genetic and non-genetic forms of AD relative to controls. The most robust change is an exaggerated release of calcium from internal stores. Detailed analysis of these changes in animal and cell models of the AD-causing presenilin mutations reveal robust changes in ryanodine receptors, inositol tris-phosphate receptors, calcium leak channels and store activated calcium entry. Similar anomalies in calcium result when AD-like changes in mitochondrial enzymes or oxidative stress are induced experimentally. The calcium abnormalities can be directly linked to the altered tau phosphorylation, amyloid precursor protein processing and synaptic dysfunction that are defining features of AD. A better understanding of these changes is required before using calcium abnormalities as therapeutic targets.

Fostering Student Introspection through Guided Reflection Forms

NASA Astrophysics Data System (ADS)

Wood, Laura; Matheson, Amanda; Franklin, Scott

2017-01-01

Student self-reflection is an important metacognitive skill to developing expert-like habits of mind. This study focuses on student responses to Guided Reflection Forms (GRFs) and individualized instructor feedback to the submissions. Student and instructor entries were hand-coded by an emergent rubric and, separately, analyzed with LIWC (Linguistic Inquiry and Word Count), a computerized text analysis program that extracts affective sentiment. Sentiment analysis supports the development of a stable basis set (rubric) to describe responses that is robust across both introductory and advanced classes. The analysis also reveals the instructor's use of the ``praise sandwich,'' instinctively embedding critiques and suggestions between specific and general encouragements. The study demonstrates the utility of validated, automated, sentiment analysis as a method by which to analyze large corpuses of written text.

Histomorphometry and cortical robusticity of the adult human femur.

PubMed

Miszkiewicz, Justyna Jolanta; Mahoney, Patrick

2018-01-13

Recent quantitative analyses of human bone microanatomy, as well as theoretical models that propose bone microstructure and gross anatomical associations, have started to reveal insights into biological links that may facilitate remodeling processes. However, relationships between bone size and the underlying cortical bone histology remain largely unexplored. The goal of this study is to determine the extent to which static indicators of bone remodeling and vascularity, measured using histomorphometric techniques, relate to femoral midshaft cortical width and robusticity. Using previously published and new quantitative data from 450 adult human male (n = 233) and female (n = 217) femora, we determine if these aspects of femoral size relate to bone microanatomy. Scaling relationships are explored and interpreted within the context of tissue form and function. Analyses revealed that the area and diameter of Haversian canals and secondary osteons, and densities of secondary osteons and osteocyte lacunae from the sub-periosteal region of the posterior midshaft femur cortex were significantly, but not consistently, associated with femoral size. Cortical width and bone robusticity were correlated with osteocyte lacunae density and scaled with positive allometry. Diameter and area of osteons and Haversian canals decreased as the width of cortex and bone robusticity increased, revealing a negative allometric relationship. These results indicate that microscopic products of cortical bone remodeling and vascularity are linked to femur size. Allometric relationships between more robust human femora with thicker cortical bone and histological products of bone remodeling correspond with principles of bone functional adaptation. Future studies may benefit from exploring scaling relationships between bone histomorphometric data and measurements of bone macrostructure.

A Hierarchical Mechanism of RIG-I Ubiquitination Provides Sensitivity, Robustness and Synergy in Antiviral Immune Responses.

PubMed

Sun, Xiaoqiang; Xian, Huifang; Tian, Shuo; Sun, Tingzhe; Qin, Yunfei; Zhang, Shoutao; Cui, Jun

2016-07-08

RIG-I is an essential receptor in the initiation of the type I interferon (IFN) signaling pathway upon viral infection. Although K63-linked ubiquitination plays an important role in RIG-I activation, the optimal modulation of conjugated and unanchored ubiquitination of RIG-I as well as its functional implications remains unclear. In this study, we determined that, in contrast to the RIG-I CARD domain, full-length RIG-I must undergo K63-linked ubiquitination at multiple sites to reach full activity. A systems biology approach was designed based on experiments using full-length RIG-I. Model selection for 7 candidate mechanisms of RIG-I ubiquitination inferred a hierarchical architecture of the RIG-I ubiquitination mode, which was then experimentally validated. Compared with other mechanisms, the selected hierarchical mechanism exhibited superior sensitivity and robustness in RIG-I-induced type I IFN activation. Furthermore, our model analysis and experimental data revealed that TRIM4 and TRIM25 exhibited dose-dependent synergism. These results demonstrated that the hierarchical mechanism of multi-site/type ubiquitination of RIG-I provides an efficient, robust and optimal synergistic regulatory module in antiviral immune responses.

A Hierarchical Mechanism of RIG-I Ubiquitination Provides Sensitivity, Robustness and Synergy in Antiviral Immune Responses

PubMed Central

Sun, Xiaoqiang; Xian, Huifang; Tian, Shuo; Sun, Tingzhe; Qin, Yunfei; Zhang, Shoutao; Cui, Jun

2016-01-01

RIG-I is an essential receptor in the initiation of the type I interferon (IFN) signaling pathway upon viral infection. Although K63-linked ubiquitination plays an important role in RIG-I activation, the optimal modulation of conjugated and unanchored ubiquitination of RIG-I as well as its functional implications remains unclear. In this study, we determined that, in contrast to the RIG-I CARD domain, full-length RIG-I must undergo K63-linked ubiquitination at multiple sites to reach full activity. A systems biology approach was designed based on experiments using full-length RIG-I. Model selection for 7 candidate mechanisms of RIG-I ubiquitination inferred a hierarchical architecture of the RIG-I ubiquitination mode, which was then experimentally validated. Compared with other mechanisms, the selected hierarchical mechanism exhibited superior sensitivity and robustness in RIG-I-induced type I IFN activation. Furthermore, our model analysis and experimental data revealed that TRIM4 and TRIM25 exhibited dose-dependent synergism. These results demonstrated that the hierarchical mechanism of multi-site/type ubiquitination of RIG-I provides an efficient, robust and optimal synergistic regulatory module in antiviral immune responses. PMID:27387525

A Hierarchical Mechanism of RIG-I Ubiquitination Provides Sensitivity, Robustness and Synergy in Antiviral Immune Responses

NASA Astrophysics Data System (ADS)

Sun, Xiaoqiang; Xian, Huifang; Tian, Shuo; Sun, Tingzhe; Qin, Yunfei; Zhang, Shoutao; Cui, Jun

2016-07-01

RIG-I is an essential receptor in the initiation of the type I interferon (IFN) signaling pathway upon viral infection. Although K63-linked ubiquitination plays an important role in RIG-I activation, the optimal modulation of conjugated and unanchored ubiquitination of RIG-I as well as its functional implications remains unclear. In this study, we determined that, in contrast to the RIG-I CARD domain, full-length RIG-I must undergo K63-linked ubiquitination at multiple sites to reach full activity. A systems biology approach was designed based on experiments using full-length RIG-I. Model selection for 7 candidate mechanisms of RIG-I ubiquitination inferred a hierarchical architecture of the RIG-I ubiquitination mode, which was then experimentally validated. Compared with other mechanisms, the selected hierarchical mechanism exhibited superior sensitivity and robustness in RIG-I-induced type I IFN activation. Furthermore, our model analysis and experimental data revealed that TRIM4 and TRIM25 exhibited dose-dependent synergism. These results demonstrated that the hierarchical mechanism of multi-site/type ubiquitination of RIG-I provides an efficient, robust and optimal synergistic regulatory module in antiviral immune responses.

Robust DEA under discrete uncertain data: a case study of Iranian electricity distribution companies

NASA Astrophysics Data System (ADS)

Hafezalkotob, Ashkan; Haji-Sami, Elham; Omrani, Hashem

2015-06-01

Crisp input and output data are fundamentally indispensable in traditional data envelopment analysis (DEA). However, the real-world problems often deal with imprecise or ambiguous data. In this paper, we propose a novel robust data envelopment model (RDEA) to investigate the efficiencies of decision-making units (DMU) when there are discrete uncertain input and output data. The method is based upon the discrete robust optimization approaches proposed by Mulvey et al. (1995) that utilizes probable scenarios to capture the effect of ambiguous data in the case study. Our primary concern in this research is evaluating electricity distribution companies under uncertainty about input/output data. To illustrate the ability of proposed model, a numerical example of 38 Iranian electricity distribution companies is investigated. There are a large amount ambiguous data about these companies. Some electricity distribution companies may not report clear and real statistics to the government. Thus, it is needed to utilize a prominent approach to deal with this uncertainty. The results reveal that the RDEA model is suitable and reliable for target setting based on decision makers (DM's) preferences when there are uncertain input/output data.

Optimization of Robust HPLC Method for Quantitation of Ambroxol Hydrochloride and Roxithromycin Using a DoE Approach.

PubMed

Patel, Rashmin B; Patel, Nilay M; Patel, Mrunali R; Solanki, Ajay B

2017-03-01

The aim of this work was to develop and optimize a robust HPLC method for the separation and quantitation of ambroxol hydrochloride and roxithromycin utilizing Design of Experiment (DoE) approach. The Plackett-Burman design was used to assess the impact of independent variables (concentration of organic phase, mobile phase pH, flow rate and column temperature) on peak resolution, USP tailing and number of plates. A central composite design was utilized to evaluate the main, interaction, and quadratic effects of independent variables on the selected dependent variables. The optimized HPLC method was validated based on ICH Q2R1 guideline and was used to separate and quantify ambroxol hydrochloride and roxithromycin in tablet formulations. The findings showed that DoE approach could be effectively applied to optimize a robust HPLC method for quantification of ambroxol hydrochloride and roxithromycin in tablet formulations. Statistical comparison between results of proposed and reported HPLC method revealed no significant difference; indicating the ability of proposed HPLC method for analysis of ambroxol hydrochloride and roxithromycin in pharmaceutical formulations. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

In-vivo analysis of ankle joint movement for patient-specific kinematic characterization.

PubMed

Ferraresi, Carlo; De Benedictis, Carlo; Franco, Walter; Maffiodo, Daniela; Leardini, Alberto

2017-09-01

In this article, a method for the experimental in-vivo characterization of the ankle kinematics is proposed. The method is meant to improve personalization of various ankle joint treatments, such as surgical decision-making or design and application of an orthosis, possibly to increase their effectiveness. This characterization in fact would make the treatments more compatible with the specific patient's joint physiological conditions. This article describes the experimental procedure and the analytical method adopted, based on the instantaneous and mean helical axis theories. The results obtained in this experimental analysis reveal that more accurate techniques are necessary for a robust in-vivo assessment of the tibio-talar axis of rotation.

Precise Calculation of a Bond Percolation Transition and Survival Rates of Nodes in a Complex Network

PubMed Central

Kawamoto, Hirokazu; Takayasu, Hideki; Jensen, Henrik Jeldtoft; Takayasu, Misako

2015-01-01

Through precise numerical analysis, we reveal a new type of universal loopless percolation transition in randomly removed complex networks. As an example of a real-world network, we apply our analysis to a business relation network consisting of approximately 3,000,000 links among 300,000 firms and observe the transition with critical exponents close to the mean-field values taking into account the finite size effect. We focus on the largest cluster at the critical point, and introduce survival probability as a new measure characterizing the robustness of each node. We also discuss the relation between survival probability and k-shell decomposition. PMID:25885791

Proteomic characterization of EL4 lymphoma-derived tumors upon chemotherapy treatment reveals potential roles for lysosomes and caspase-6 during tumor cell death in vivo.

PubMed

Kramer, David A; Eldeeb, Mohamed A; Wuest, Melinda; Mercer, John; Fahlman, Richard P

2017-06-01

The murine mouse lymphoblastic lymphoma cell line (EL4) tumor model is an established in vivo apoptosis model for the investigation of novel cancer imaging agents and immunological treatments due to the rapid and significant response of the EL4 tumors to cyclophosphamide and etoposide combination chemotherapy. Despite the utility of this model system in cancer research, little is known regarding the molecular details of in vivo tumor cell death. Here, we report the first in-depth quantitative proteomic analysis of the changes that occur in these tumors upon cyclophosphamide and etoposide treatment in vivo. Using a label-free quantitative proteomic approach a total of 5838 proteins were identified in the treated and untreated tumors, of which 875 were determined to change in abundance with statistical significance. Initial analysis of the data reveals changes that may have been predicted, such as the downregulation of ribosomes, but demonstrates the robustness of the dataset. Analysis of the dataset also reveals the unexpected downregulation of caspase-3 and an upregulation of caspase-6 in addition to a global upregulation of lysosomal proteins in the bulk of the tumor. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Determinants of the lethality of climate-related disasters in the Caribbean Community (CARICOM): a cross-country analysis

PubMed Central

Andrewin, Aisha N.; Rodriguez-Llanes, Jose M.; Guha-Sapir, Debarati

2015-01-01

Floods and storms are climate-related hazards posing high mortality risk to Caribbean Community (CARICOM) nations. However risk factors for their lethality remain untested. We conducted an ecological study investigating risk factors for flood and storm lethality in CARICOM nations for the period 1980–2012. Lethality - deaths versus no deaths per disaster event- was the outcome. We examined biophysical and social vulnerability proxies and a decadal effect as predictors. We developed our regression model via multivariate analysis using a generalized logistic regression model with quasi-binomial distribution; removal of multi-collinear variables and backward elimination. Robustness was checked through subset analysis. We found significant positive associations between lethality, percentage of total land dedicated to agriculture (odds ratio [OR] 1.032; 95% CI: 1.013–1.053) and percentage urban population (OR 1.029, 95% CI 1.003–1.057). Deaths were more likely in the 2000–2012 period versus 1980–1989 (OR 3.708, 95% CI 1.615–8.737). Robustness checks revealed similar coefficients and directions of association. Population health in CARICOM nations is being increasingly impacted by climate-related disasters connected to increasing urbanization and land use patterns. Our findings support the evidence base for setting sustainable development goals (SDG). PMID:26153115

Robust volcano plot: identification of differential metabolites in the presence of outliers.

PubMed

Kumar, Nishith; Hoque, Md Aminul; Sugimoto, Masahiro

2018-04-11

The identification of differential metabolites in metabolomics is still a big challenge and plays a prominent role in metabolomics data analyses. Metabolomics datasets often contain outliers because of analytical, experimental, and biological ambiguity, but the currently available differential metabolite identification techniques are sensitive to outliers. We propose a kernel weight based outlier-robust volcano plot for identifying differential metabolites from noisy metabolomics datasets. Two numerical experiments are used to evaluate the performance of the proposed technique against nine existing techniques, including the t-test and the Kruskal-Wallis test. Artificially generated data with outliers reveal that the proposed method results in a lower misclassification error rate and a greater area under the receiver operating characteristic curve compared with existing methods. An experimentally measured breast cancer dataset to which outliers were artificially added reveals that our proposed method produces only two non-overlapping differential metabolites whereas the other nine methods produced between seven and 57 non-overlapping differential metabolites. Our data analyses show that the performance of the proposed differential metabolite identification technique is better than that of existing methods. Thus, the proposed method can contribute to analysis of metabolomics data with outliers. The R package and user manual of the proposed method are available at https://github.com/nishithkumarpaul/Rvolcano .

Steep delay discounting and addictive behavior: a meta-analysis of continuous associations.

PubMed

Amlung, Michael; Vedelago, Lana; Acker, John; Balodis, Iris; MacKillop, James

2017-01-01

To synthesize continuous associations between delayed reward discounting (DRD) and both addiction severity and quantity-frequency (QF); to examine moderators of these relationships; and to investigate publication bias. Meta-analysis of published studies examining continuous associations between DRD and addictive behaviors. Published, peer-reviewed studies on addictive behaviors (alcohol, tobacco, cannabis, stimulants, opiates and gambling) were identified via PubMed, MEDLINE and PsycInfo. Studies were restricted to DRD measures of monetary gains. Random-effects meta-analysis was conducted using Pearson's r as the effect size. Publication bias was evaluated using fail-safe N, Begg-Mazumdar and Egger's tests, meta-regression of publication year and effect size and imputation of missing studies. The primary meta-analysis revealed a small magnitude effect size that was highly significant (r = 0.14, P < 10 -14 ). Significantly larger effect sizes were observed for studies examining severity compared with QF (P = 0.01), but not between the type of addictive behavior (P = 0.30) or DRD assessment (P = 0.90). Indices of publication bias suggested a modest impact of unpublished findings. Delayed reward discounting is associated robustly with continuous measures of addiction severity and quantity-frequency. This relation is generally robust across type of addictive behavior and delayed reward discounting assessment modality. © 2016 Society for the Study of Addiction.

A Baseline for the Multivariate Comparison of Resting-State Networks

PubMed Central

Allen, Elena A.; Erhardt, Erik B.; Damaraju, Eswar; Gruner, William; Segall, Judith M.; Silva, Rogers F.; Havlicek, Martin; Rachakonda, Srinivas; Fries, Jill; Kalyanam, Ravi; Michael, Andrew M.; Caprihan, Arvind; Turner, Jessica A.; Eichele, Tom; Adelsheim, Steven; Bryan, Angela D.; Bustillo, Juan; Clark, Vincent P.; Feldstein Ewing, Sarah W.; Filbey, Francesca; Ford, Corey C.; Hutchison, Kent; Jung, Rex E.; Kiehl, Kent A.; Kodituwakku, Piyadasa; Komesu, Yuko M.; Mayer, Andrew R.; Pearlson, Godfrey D.; Phillips, John P.; Sadek, Joseph R.; Stevens, Michael; Teuscher, Ursina; Thoma, Robert J.; Calhoun, Vince D.

2011-01-01

As the size of functional and structural MRI datasets expands, it becomes increasingly important to establish a baseline from which diagnostic relevance may be determined, a processing strategy that efficiently prepares data for analysis, and a statistical approach that identifies important effects in a manner that is both robust and reproducible. In this paper, we introduce a multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing. We demonstrate the utility of this mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12–71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described here, provide a useful baseline for future investigations of brain networks in health and disease. PMID:21442040

Dealing with the Conflicting Results of Psycholinguistic Experiments: How to Resolve Them with the Help of Statistical Meta-analysis.

PubMed

Rákosi, Csilla

2018-01-22

This paper proposes the use of the tools of statistical meta-analysis as a method of conflict resolution with respect to experiments in cognitive linguistics. With the help of statistical meta-analysis, the effect size of similar experiments can be compared, a well-founded and robust synthesis of the experimental data can be achieved, and possible causes of any divergence(s) in the outcomes can be revealed. This application of statistical meta-analysis offers a novel method of how diverging evidence can be dealt with. The workability of this idea is exemplified by a case study dealing with a series of experiments conducted as non-exact replications of Thibodeau and Boroditsky (PLoS ONE 6(2):e16782, 2011. https://doi.org/10.1371/journal.pone.0016782 ).

Gekko japonicus genome reveals evolution of adhesive toe pads and tail regeneration

PubMed Central

Liu, Yan; Zhou, Qian; Wang, Yongjun; Luo, Longhai; Yang, Jian; Yang, Linfeng; Liu, Mei; Li, Yingrui; Qian, Tianmei; Zheng, Yuan; Li, Meiyuan; Li, Jiang; Gu, Yun; Han, Zujing; Xu, Man; Wang, Yingjie; Zhu, Changlai; Yu, Bin; Yang, Yumin; Ding, Fei; Jiang, Jianping; Yang, Huanming; Gu, Xiaosong

2015-01-01

Reptiles are the most morphologically and physiologically diverse tetrapods, and have undergone 300 million years of adaptive evolution. Within the reptilian tetrapods, geckos possess several interesting features, including the ability to regenerate autotomized tails and to climb on smooth surfaces. Here we sequence the genome of Gekko japonicus (Schlegel's Japanese Gecko) and investigate genetic elements related to its physiology. We obtain a draft G. japonicus genome sequence of 2.55 Gb and annotated 22,487 genes. Comparative genomic analysis reveals specific gene family expansions or reductions that are associated with the formation of adhesive setae, nocturnal vision and tail regeneration, as well as the diversification of olfactory sensation. The obtained genomic data provide robust genetic evidence of adaptive evolution in reptiles. PMID:26598231

Hormone activation induces nucleosome positioning in vivo

PubMed Central

Belikov, Sergey; Gelius, Birgitta; Almouzni, Geneviève; Wrange, Örjan

2000-01-01

The mouse mammary tumor virus (MMTV) promoter is induced by glucocorticoid hormone. A robust hormone- and receptor-dependent activation could be reproduced in Xenopus laevis oocytes. The homogeneous response in this system allowed a detailed analysis of the transition in chromatin structure following hormone activation. This revealed two novel findings: hormone activation led to the establishment of specific translational positioning of nucleosomes despite the lack of significant positioning in the inactive state; and, in the active promoter, a subnucleosomal particle encompassing the glucocorticoid receptor (GR)-binding region was detected. The presence of only a single GR-binding site was sufficient for the structural transition to occur. Both basal promoter elements and ongoing transcription were dispensable. These data reveal a stepwise process in the transcriptional activation by glucocorticoid hormone. PMID:10698943

A protein interaction network analysis for yeast integral membrane protein.

PubMed

Shi, Ming-Guang; Huang, De-Shuang; Li, Xue-Ling

2008-01-01

Although the yeast Saccharomyces cerevisiae is the best exemplified single-celled eukaryote, the vast number of protein-protein interactions of integral membrane proteins of Saccharomyces cerevisiae have not been characterized by experiments. Here, based on the kernel method of Greedy Kernel Principal Component analysis plus Linear Discriminant Analysis, we identify 300 protein-protein interactions involving 189 membrane proteins and get the outcome of a highly connected protein-protein interactions network. Furthermore, we study the global topological features of integral membrane proteins network of Saccharomyces cerevisiae. These results give the comprehensive description of protein-protein interactions of integral membrane proteins and reveal global topological and robustness of the interactome network at a system level. This work represents an important step towards a comprehensive understanding of yeast protein interactions.

Robustness Analysis of Integrated LPV-FDI Filters and LTI-FTC System for a Transport Aircraft

NASA Technical Reports Server (NTRS)

Khong, Thuan H.; Shin, Jong-Yeob

2007-01-01

This paper proposes an analysis framework for robustness analysis of a nonlinear dynamics system that can be represented by a polynomial linear parameter varying (PLPV) system with constant bounded uncertainty. The proposed analysis framework contains three key tools: 1) a function substitution method which can convert a nonlinear system in polynomial form into a PLPV system, 2) a matrix-based linear fractional transformation (LFT) modeling approach, which can convert a PLPV system into an LFT system with the delta block that includes key uncertainty and scheduling parameters, 3) micro-analysis, which is a well known robust analysis tool for linear systems. The proposed analysis framework is applied to evaluating the performance of the LPV-fault detection and isolation (FDI) filters of the closed-loop system of a transport aircraft in the presence of unmodeled actuator dynamics and sensor gain uncertainty. The robustness analysis results are compared with nonlinear time simulations.

Lokiarchaea are close relatives of Euryarchaeota, not bridging the gap between prokaryotes and eukaryotes

PubMed Central

Forterre, Patrick

2017-01-01

The eocyte hypothesis, in which Eukarya emerged from within Archaea, has been boosted by the description of a new candidate archaeal phylum, “Lokiarchaeota”, from metagenomic data. Eukarya branch within Lokiarchaeota in a tree reconstructed from the concatenation of 36 universal proteins. However, individual phylogenies revealed that lokiarchaeal proteins sequences have different evolutionary histories. The individual markers phylogenies revealed at least two subsets of proteins, either supporting the Woese or the Eocyte tree of life. Strikingly, removal of a single protein, the elongation factor EF2, is sufficient to break the Eukaryotes-Lokiarchaea affiliation. Our analysis suggests that the three lokiarchaeal EF2 proteins have a chimeric organization that could be due to contamination and/or homologous recombination with patches of eukaryotic sequences. A robust phylogenetic analysis of RNA polymerases with a new dataset indicates that Lokiarchaeota and related phyla of the Asgard superphylum are sister group to Euryarchaeota, not to Eukarya, and supports the monophyly of Archaea with their rooting in the branch leading to Thaumarchaeota. PMID:28604769

Mapping probabilities of extreme continental water storage changes from space gravimetry

NASA Astrophysics Data System (ADS)

Kusche, J.; Eicker, A.; Forootan, E.; Springer, A.; Longuevergne, L.

2016-08-01

Using data from the Gravity Recovery And Climate Experiment (GRACE) mission, we derive statistically robust "hot spot" regions of high probability of peak anomalous—i.e., with respect to the seasonal cycle—water storage (of up to 0.7 m one-in-five-year return level) and flux (up to 0.14 m/month). Analysis of, and comparison with, up to 32 years of ERA-Interim reanalysis fields reveals generally good agreement of these hot spot regions to GRACE results and that most exceptions are located in the tropics. However, a simulation experiment reveals that differences observed by GRACE are statistically significant, and further error analysis suggests that by around the year 2020, it will be possible to detect temporal changes in the frequency of extreme total fluxes (i.e., combined effects of mainly precipitation and floods) for at least 10-20% of the continental area, assuming that we have a continuation of GRACE by its follow-up GRACE Follow-On (GRACE-FO) mission.

Development and optimization of SPE-HPLC-UV/ELSD for simultaneous determination of nine bioactive components in Shenqi Fuzheng Injection based on Quality by Design principles.

PubMed

Wang, Lu; Qu, Haibin

2016-03-01

A method combining solid phase extraction, high performance liquid chromatography, and ultraviolet/evaporative light scattering detection (SPE-HPLC-UV/ELSD) was developed according to Quality by Design (QbD) principles and used to assay nine bioactive compounds within a botanical drug, Shenqi Fuzheng Injection. Risk assessment and a Plackett-Burman design were utilized to evaluate the impact of 11 factors on the resolutions and signal-to-noise of chromatographic peaks. Multiple regression and Pareto ranking analysis indicated that the sorbent mass, sample volume, flow rate, column temperature, evaporator temperature, and gas flow rate were statistically significant (p < 0.05) in this procedure. Furthermore, a Box-Behnken design combined with response surface analysis was employed to study the relationships between the quality of SPE-HPLC-UV/ELSD analysis and four significant factors, i.e., flow rate, column temperature, evaporator temperature, and gas flow rate. An analytical design space of SPE-HPLC-UV/ELSD was then constructed by calculated Monte Carlo probability. In the presented approach, the operating parameters of sample preparation, chromatographic separation, and compound detection were investigated simultaneously. Eight terms of method validation, i.e., system-suitability tests, method robustness/ruggedness, sensitivity, precision, repeatability, linearity, accuracy, and stability, were accomplished at a selected working point. These results revealed that the QbD principles were suitable in the development of analytical procedures for samples in complex matrices. Meanwhile, the analytical quality and method robustness were validated by the analytical design space. The presented strategy provides a tutorial on the development of a robust QbD-compliant quantitative method for samples in complex matrices.

Inter-laboratory comparison of the in vivo comet assay including three image analysis systems.

PubMed

Plappert-Helbig, Ulla; Guérard, Melanie

2015-12-01

To compare the extent of potential inter-laboratory variability and the influence of different comet image analysis systems, in vivo comet experiments were conducted using the genotoxicants ethyl methanesulfonate and methyl methanesulfonate. Tissue samples from the same animals were processed and analyzed-including independent slide evaluation by image analysis-in two laboratories with extensive experience in performing the comet assay. The analysis revealed low inter-laboratory experimental variability. Neither the use of different image analysis systems, nor the staining procedure of DNA (propidium iodide vs. SYBR® Gold), considerably impacted the results or sensitivity of the assay. In addition, relatively high stability of the staining intensity of propidium iodide-stained slides was found in slides that were refrigerated for over 3 months. In conclusion, following a thoroughly defined protocol and standardized routine procedures ensures that the comet assay is robust and generates comparable results between different laboratories. © 2015 Wiley Periodicals, Inc.

Flexible modulation of network connectivity related to cognition in Alzheimer's disease.

PubMed

McLaren, Donald G; Sperling, Reisa A; Atri, Alireza

2014-10-15

Functional neuroimaging tools, such as fMRI methods, may elucidate the neural correlates of clinical, behavioral, and cognitive performance. Most functional imaging studies focus on regional task-related activity or resting state connectivity rather than how changes in functional connectivity across conditions and tasks are related to cognitive and behavioral performance. To investigate the promise of characterizing context-dependent connectivity-behavior relationships, this study applies the method of generalized psychophysiological interactions (gPPI) to assess the patterns of associative-memory-related fMRI hippocampal functional connectivity in Alzheimer's disease (AD) associated with performance on memory and other cognitively demanding neuropsychological tests and clinical measures. Twenty-four subjects with mild AD dementia (ages 54-82, nine females) participated in a face-name paired-associate encoding memory study. Generalized PPI analysis was used to estimate the connectivity between the hippocampus and the whole brain during encoding. The difference in hippocampal-whole brain connectivity between encoding novel and encoding repeated face-name pairs was used in multiple-regression analyses as an independent predictor for 10 behavioral, neuropsychological and clinical tests. The analysis revealed connectivity-behavior relationships that were distributed, dynamically overlapping, and task-specific within and across intrinsic networks; hippocampal-whole brain connectivity-behavior relationships were not isolated to single networks, but spanned multiple brain networks. Importantly, these spatially distributed performance patterns were unique for each measure. In general, out-of-network behavioral associations with encoding novel greater than repeated face-name pairs hippocampal-connectivity were observed in the default-mode network, while correlations with encoding repeated greater than novel face-name pairs hippocampal-connectivity were observed in the executive control network (p<0.05, cluster corrected). Psychophysiological interactions revealed significantly more extensive and robust associations between paired-associate encoding task-dependent hippocampal-whole brain connectivity and performance on memory and behavioral/clinical measures than previously revealed by standard activity-behavior analysis. Compared to resting state and task-activation methods, gPPI analyses may be more sensitive to reveal additional complementary information regarding subtle within- and between-network relations. The patterns of robust correlations between hippocampal-whole brain connectivity and behavioral measures identified here suggest that there are 'coordinated states' in the brain; that the dynamic range of these states is related to behavior and cognition; and that these states can be observed and quantified, even in individuals with mild AD. Copyright © 2014 Elsevier Inc. All rights reserved.

Up-regulation of DRP-3 long isoform during the induction of neural progenitor cells by glutamate treatment in the ex vivo rat retina

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tokuda, Kazuhiro, E-mail: r502um@yamaguchi-u.ac.jp; Department of Biochemistry and Functional Proteomics, Yamaguchi University Graduate School of Medicine, Ube, Yamaguchi; Kuramitsu, Yasuhiro

Glutamate has been shown to induce neural progenitor cells in the adult vertebrate retina. However, protein dynamics during progenitor cell induction by glutamate are not fully understood. To identify specific proteins involved in the process, we employed two-dimensional electrophoresis-based proteomics on glutamate untreated and treated retinal ex vivo sections. Rat retinal tissues were incubated with 1 mM glutamate for 1 h, followed by incubation in glutamate-free media for a total of 24 h. Consistent with prior reports, it was found that mitotic cells appeared in the outer nuclear layer without any histological damage. Immunohistological evaluations and immunoblotting confirmed the emergence of neuronal progenitor cellsmore » in the mature retina treated with glutamate. Proteomic analysis revealed the up-regulation of dihydropyrimidinase-related protein 3 (DRP-3), DRP-2 and stress-induced-phosphoprotein 1 (STIP1) during neural progenitor cell induction by glutamate. Moreover, mRNA expression of DRP-3, especially, its long isoform, robustly increased in the treated retina compared to that in the untreated retina. These results may indicate that glutamate induces neural progenitor cells in the mature rat retina by up-regulating the proteins which mediate cell mitosis and neurite growth. - Highlights: • Glutamate induced neuronal progenitor cells in the mature rat retina. • Proteomic analysis revealed the up-regulation of DRP-3, DRP-2 and STIP1. • mRNA expression of DRP-3, especially, its long isoform, robustly increased.« less

Robust hierarchical state-space models reveal diel variation in travel rates of migrating leatherback turtles.

PubMed

Jonsen, Ian D; Myers, Ransom A; James, Michael C

2006-09-01

1. Biological and statistical complexity are features common to most ecological data that hinder our ability to extract meaningful patterns using conventional tools. Recent work on implementing modern statistical methods for analysis of such ecological data has focused primarily on population dynamics but other types of data, such as animal movement pathways obtained from satellite telemetry, can also benefit from the application of modern statistical tools. 2. We develop a robust hierarchical state-space approach for analysis of multiple satellite telemetry pathways obtained via the Argos system. State-space models are time-series methods that allow unobserved states and biological parameters to be estimated from data observed with error. We show that the approach can reveal important patterns in complex, noisy data where conventional methods cannot. 3. Using the largest Atlantic satellite telemetry data set for critically endangered leatherback turtles, we show that the diel pattern in travel rates of these turtles changes over different phases of their migratory cycle. While foraging in northern waters the turtles show similar travel rates during day and night, but on their southward migration to tropical waters travel rates are markedly faster during the day. These patterns are generally consistent with diving data, and may be related to changes in foraging behaviour. Interestingly, individuals that migrate southward to breed generally show higher daytime travel rates than individuals that migrate southward in a non-breeding year. 4. Our approach is extremely flexible and can be applied to many ecological analyses that use complex, sequential data.

Improvement of catalytic performance of lignin peroxidase for the enhanced degradation of lignocellulose biomass based on the imbedded electron-relay in long-range electron transfer route.

PubMed

Pham, Le Thanh Mai; Kim, Su Jin; Kim, Yong Hwan

2016-01-01

Although lignin peroxidase is claimed as a key enzyme in enzyme-catalyzed lignin degradation, in vitro enzymatic degradation of lignin was not easily observed in lab-scale experiments. It implies that other factors may hinder the enzymatic degradation of lignin. Irreversible interaction between phenolic compound and lignin peroxidase was hypothesized when active enzyme could not be recovered after the reaction with degradation product (guaiacol) of lignin phenolic dimer. In the study of lignin peroxidase isozyme H8 from white-rot fungi Phanerochaete chrysosporium (LiPH8), W251 site was revealed to make the covalent coupling with one moiety of monolignolic radical (guaiacol radical) by LC-MS/MS analysis. Hypothetical electron-relay containing W251 residue was newly suggested based on the observation of repressed radical coupling and remarkably lower electron transfer rate for W215A mutant. Furthermore, the retardation of the suicidal radical coupling between the W251 residue and the monolignolic radical was attempted by supplementing the acidic microenvironment around the W251 residue to engineer radical-robust LiPH8. Among many mutants, mutant A242D showed exceptional catalytic performances by yielding 21.1- and 4.9-fold higher increases of k cat and k cat /K M values, respectively, in the oxidation of non-phenolic model lignin dimer. A mechanism-based suicide inhibition of LiPH8 by phenolic compounds was firstly revealed and investigated in this work. Radical-robust LiPH8 was also successfully engineered by manipulating the transient radical state of radical-susceptible electron-relay. Radical-robust LiPH8 will play an essential role in degradation of lignin, which will be consequently linked with improved production of sugars from lignocellulose biomass.

Integrated Behavioral Z-Scoring Increases the Sensitivity and Reliability of Behavioral Phenotyping in mice: Relevance to Emotionality and Sex

PubMed Central

Guilloux, Jean-Philippe; Seney, Marianne; Edgar, Nicole; Sibille, Etienne

2011-01-01

Defining anxiety- and depressive-like states in mice (“emotionality”) is best characterized by the use of complementary tests, leading sometimes to puzzling discrepancies and lack of correlation between similar paradigms. To address this issue, we hypothesized that integrating measures along the same behavioral dimensions in different tests would reduce the intrinsic variability of single tests and provide a robust characterization of the underlying “emotionality” of individual mouse, similarly as mood and related syndromes are defined in humans through various related symptoms over time. We describe the use of simple mathematical and integrative tools to help phenotype animals across related behavioral tests (syndrome diagnosis) and experiments (meta-analysis). We applied z-normalization across complementary measures of emotionality in different behavioral tests after unpredictable chronic mild stress (UCMS) or prolonged corticosterone exposure - two approaches to induce anxious-/depressive-like states in mice. Combining z-normalized test values, lowered the variance of emotionality measurement, enhanced the reliability of behavioral phenotyping, and increased analytical opportunities. Comparing integrated emotionality scores across studies revealed a robust sexual dimorphism in the vulnerability to develop high emotionality, manifested as higher UCMS-induced emotionality z-scores, but lower corticosterone-induced scores in females compared to males. Interestingly, the distribution of individual z-scores revealed a pattern of increased baseline emotionality in female mice, reminiscent of what is observed in humans. Together, we show that the z-scoring method yields robust measures of emotionality across complementary tests for individual mice and experimental groups, hence facilitating the comparison across studies and refining the translational applicability of these models. PMID:21277897

Integrated behavioral z-scoring increases the sensitivity and reliability of behavioral phenotyping in mice: relevance to emotionality and sex.

PubMed

Guilloux, Jean-Philippe; Seney, Marianne; Edgar, Nicole; Sibille, Etienne

2011-04-15

Defining anxiety- and depressive-like states in mice (emotionality) is best characterized by the use of complementary tests, leading sometimes to puzzling discrepancies and lack of correlation between similar paradigms. To address this issue, we hypothesized that integrating measures along the same behavioral dimensions in different tests would reduce the intrinsic variability of single tests and provide a robust characterization of the underlying "emotionality" of individual mouse, similarly as mood and related syndromes are defined in humans through various related symptoms over time. We describe the use of simple mathematical and integrative tools to help phenotype animals across related behavioral tests (syndrome diagnosis) and experiments (meta-analysis). We applied z-normalization across complementary measures of emotionality in different behavioral tests after unpredictable chronic mild stress (UCMS) or prolonged corticosterone exposure - two approaches to induce anxious-/depressive-like states in mice. Combining z-normalized test values, lowered the variance of emotionality measurement, enhanced the reliability of behavioral phenotyping, and increased analytical opportunities. Comparing integrated emotionality scores across studies revealed a robust sexual dimorphism in the vulnerability to develop high emotionality, manifested as higher UCMS-induced emotionality z-scores, but lower corticosterone-induced scores in females compared to males. Interestingly, the distribution of individual z-scores revealed a pattern of increased baseline emotionality in female mice, reminiscent of what is observed in humans. Together, we show that the z-scoring method yields robust measures of emotionality across complementary tests for individual mice and experimental groups, hence facilitating the comparison across studies and refining the translational applicability of these models. Copyright © 2011 Elsevier B.V. All rights reserved.

Modern CACSD using the Robust-Control Toolbox

NASA Technical Reports Server (NTRS)

Chiang, Richard Y.; Safonov, Michael G.

1989-01-01

The Robust-Control Toolbox is a collection of 40 M-files which extend the capability of PC/PRO-MATLAB to do modern multivariable robust control system design. Included are robust analysis tools like singular values and structured singular values, robust synthesis tools like continuous/discrete H(exp 2)/H infinity synthesis and Linear Quadratic Gaussian Loop Transfer Recovery methods and a variety of robust model reduction tools such as Hankel approximation, balanced truncation and balanced stochastic truncation, etc. The capabilities of the toolbox are described and illustated with examples to show how easily they can be used in practice. Examples include structured singular value analysis, H infinity loop-shaping and large space structure model reduction.

Computer models and the evidence of anthropogenic climate change: An epistemology of variety-of-evidence inferences and robustness analysis.

PubMed

Vezér, Martin A

2016-04-01

To study climate change, scientists employ computer models, which approximate target systems with various levels of skill. Given the imperfection of climate models, how do scientists use simulations to generate knowledge about the causes of observed climate change? Addressing a similar question in the context of biological modelling, Levins (1966) proposed an account grounded in robustness analysis. Recent philosophical discussions dispute the confirmatory power of robustness, raising the question of how the results of computer modelling studies contribute to the body of evidence supporting hypotheses about climate change. Expanding on Staley's (2004) distinction between evidential strength and security, and Lloyd's (2015) argument connecting variety-of-evidence inferences and robustness analysis, I address this question with respect to recent challenges to the epistemology robustness analysis. Applying this epistemology to case studies of climate change, I argue that, despite imperfections in climate models, and epistemic constraints on variety-of-evidence reasoning and robustness analysis, this framework accounts for the strength and security of evidence supporting climatological inferences, including the finding that global warming is occurring and its primary causes are anthropogenic. Copyright © 2016 Elsevier Ltd. All rights reserved.

Robust Mediation Analysis Based on Median Regression

PubMed Central

Yuan, Ying; MacKinnon, David P.

2014-01-01

Mediation analysis has many applications in psychology and the social sciences. The most prevalent methods typically assume that the error distribution is normal and homoscedastic. However, this assumption may rarely be met in practice, which can affect the validity of the mediation analysis. To address this problem, we propose robust mediation analysis based on median regression. Our approach is robust to various departures from the assumption of homoscedasticity and normality, including heavy-tailed, skewed, contaminated, and heteroscedastic distributions. Simulation studies show that under these circumstances, the proposed method is more efficient and powerful than standard mediation analysis. We further extend the proposed robust method to multilevel mediation analysis, and demonstrate through simulation studies that the new approach outperforms the standard multilevel mediation analysis. We illustrate the proposed method using data from a program designed to increase reemployment and enhance mental health of job seekers. PMID:24079925

Transcriptome Analysis in Tardigrade Species Reveals Specific Molecular Pathways for Stress Adaptations

PubMed Central

Förster, Frank; Beisser, Daniela; Grohme, Markus A.; Liang, Chunguang; Mali, Brahim; Siegl, Alexander Matthias; Engelmann, Julia C.; Shkumatov, Alexander V.; Schokraie, Elham; Müller, Tobias; Schnölzer, Martina; Schill, Ralph O.; Frohme, Marcus; Dandekar, Thomas

2012-01-01

Tardigrades have unique stress-adaptations that allow them to survive extremes of cold, heat, radiation and vacuum. To study this, encoded protein clusters and pathways from an ongoing transcriptome study on the tardigrade Milnesium tardigradum were analyzed using bioinformatics tools and compared to expressed sequence tags (ESTs) from Hypsibius dujardini, revealing major pathways involved in resistance against extreme environmental conditions. ESTs are available on the Tardigrade Workbench along with software and databank updates. Our analysis reveals that RNA stability motifs for M. tardigradum are different from typical motifs known from higher animals. M. tardigradum and H. dujardini protein clusters and conserved domains imply metabolic storage pathways for glycogen, glycolipids and specific secondary metabolism as well as stress response pathways (including heat shock proteins, bmh2, and specific repair pathways). Redox-, DNA-, stress- and protein protection pathways complement specific repair capabilities to achieve the strong robustness of M. tardigradum. These pathways are partly conserved in other animals and their manipulation could boost stress adaptation even in human cells. However, the unique combination of resistance and repair pathways make tardigrades and M. tardigradum in particular so highly stress resistant. PMID:22563243

Genomic reconstruction of the history of extant populations of India reveals five distinct ancestral components and a complex structure

PubMed Central

Basu, Analabha; Sarkar-Roy, Neeta; Majumder, Partha P.

2016-01-01

India, occupying the center stage of Paleolithic and Neolithic migrations, has been underrepresented in genome-wide studies of variation. Systematic analysis of genome-wide data, using multiple robust statistical methods, on (i) 367 unrelated individuals drawn from 18 mainland and 2 island (Andaman and Nicobar Islands) populations selected to represent geographic, linguistic, and ethnic diversities, and (ii) individuals from populations represented in the Human Genome Diversity Panel (HGDP), reveal four major ancestries in mainland India. This contrasts with an earlier inference of two ancestries based on limited population sampling. A distinct ancestry of the populations of Andaman archipelago was identified and found to be coancestral to Oceanic populations. Analysis of ancestral haplotype blocks revealed that extant mainland populations (i) admixed widely irrespective of ancestry, although admixtures between populations was not always symmetric, and (ii) this practice was rapidly replaced by endogamy about 70 generations ago, among upper castes and Indo-European speakers predominantly. This estimated time coincides with the historical period of formulation and adoption of sociocultural norms restricting intermarriage in large social strata. A similar replacement observed among tribal populations was temporally less uniform. PMID:26811443

Integrated multi-cohort transcriptional meta-analysis of neurodegenerative diseases.

PubMed

Li, Matthew D; Burns, Terry C; Morgan, Alexander A; Khatri, Purvesh

2014-09-04

Neurodegenerative diseases share common pathologic features including neuroinflammation, mitochondrial dysfunction and protein aggregation, suggesting common underlying mechanisms of neurodegeneration. We undertook a meta-analysis of public gene expression data for neurodegenerative diseases to identify a common transcriptional signature of neurodegeneration. Using 1,270 post-mortem central nervous system tissue samples from 13 patient cohorts covering four neurodegenerative diseases, we identified 243 differentially expressed genes, which were similarly dysregulated in 15 additional patient cohorts of 205 samples including seven neurodegenerative diseases. This gene signature correlated with histologic disease severity. Metallothioneins featured prominently among differentially expressed genes, and functional pathway analysis identified specific convergent themes of dysregulation. MetaCore network analyses revealed various novel candidate hub genes (e.g. STAU2). Genes associated with M1-polarized macrophages and reactive astrocytes were strongly enriched in the meta-analysis data. Evaluation of genes enriched in neurons revealed 70 down-regulated genes, over half not previously associated with neurodegeneration. Comparison with aging brain data (3 patient cohorts, 221 samples) revealed 53 of these to be unique to neurodegenerative disease, many of which are strong candidates to be important in neuropathogenesis (e.g. NDN, NAP1L2). ENCODE ChIP-seq analysis predicted common upstream transcriptional regulators not associated with normal aging (REST, RBBP5, SIN3A, SP2, YY1, ZNF143, IKZF1). Finally, we removed genes common to neurodegeneration from disease-specific gene signatures, revealing uniquely robust immune response and JAK-STAT signaling in amyotrophic lateral sclerosis. Our results implicate pervasive bioenergetic deficits, M1-type microglial activation and gliosis as unifying themes of neurodegeneration, and identify numerous novel genes associated with neurodegenerative processes.

Bayesian Inference and Application of Robust Growth Curve Models Using Student's "t" Distribution

ERIC Educational Resources Information Center

Zhang, Zhiyong; Lai, Keke; Lu, Zhenqiu; Tong, Xin

2013-01-01

Despite the widespread popularity of growth curve analysis, few studies have investigated robust growth curve models. In this article, the "t" distribution is applied to model heavy-tailed data and contaminated normal data with outliers for growth curve analysis. The derived robust growth curve models are estimated through Bayesian…

Fluorescence recovery after photobleaching reveals regulation and distribution of connexin36 gap junction coupling within mouse islets of Langerhans

PubMed Central

Farnsworth, Nikki L; Hemmati, Alireza; Pozzoli, Marina; Benninger, Richard K P

2014-01-01

The pancreatic islets are central to the maintenance of glucose homeostasis through insulin secretion. Glucose-stimulated insulin secretion is tightly linked to electrical activity in β cells within the islet. Gap junctions, composed of connexin36 (Cx36), form intercellular channels between β cells, synchronizing electrical activity and insulin secretion. Loss of gap junction coupling leads to altered insulin secretion dynamics and disrupted glucose homeostasis. Gap junction coupling is known to be disrupted in mouse models of pre-diabetes. Although approaches to measure gap junction coupling have been devised, they either lack cell specificity, suitable quantification of coupling or spatial resolution, or are invasive. The purpose of this study was to develop fluorescence recovery after photobleaching (FRAP) as a technique to accurately and robustly measure gap junction coupling in the islet. The cationic dye Rhodamine 123 was used with FRAP to quantify dye diffusion between islet β cells as a measure of Cx36 gap junction coupling. Measurements in islets with reduced Cx36 verified the accuracy of this technique in distinguishing between distinct levels of gap junction coupling. Analysis of individual cells revealed that the distribution of coupling across the islet is highly heterogeneous. Analysis of several modulators of gap junction coupling revealed glucose- and cAMP-dependent modulation of gap junction coupling in islets. Finally, FRAP was used to determine cell population specific coupling, where no functional gap junction coupling was observed between α cells and β cells in the islet. The results of this study show FRAP to be a robust technique which provides the cellular resolution to quantify the distribution and regulation of Cx36 gap junction coupling in specific cell populations within the islet. Future studies utilizing this technique may elucidate the role of gap junction coupling in the progression of diabetes and identify mechanisms of gap junction regulation for potential therapies. PMID:25172942

Fluorescence recovery after photobleaching reveals regulation and distribution of connexin36 gap junction coupling within mouse islets of Langerhans.

PubMed

Farnsworth, Nikki L; Hemmati, Alireza; Pozzoli, Marina; Benninger, Richard K P

2014-10-15

The pancreatic islets are central to the maintenance of glucose homeostasis through insulin secretion. Glucose‐stimulated insulin secretion is tightly linked to electrical activity in β cells within the islet. Gap junctions, composed of connexin36 (Cx36), form intercellular channels between β cells, synchronizing electrical activity and insulin secretion. Loss of gap junction coupling leads to altered insulin secretion dynamics and disrupted glucose homeostasis. Gap junction coupling is known to be disrupted in mouse models of pre‐diabetes. Although approaches to measure gap junction coupling have been devised, they either lack cell specificity, suitable quantification of coupling or spatial resolution, or are invasive. The purpose of this study was to develop fluorescence recovery after photobleaching (FRAP) as a technique to accurately and robustly measure gap junction coupling in the islet. The cationic dye Rhodamine 123 was used with FRAP to quantify dye diffusion between islet β cells as a measure of Cx36 gap junction coupling. Measurements in islets with reduced Cx36 verified the accuracy of this technique in distinguishing between distinct levels of gap junction coupling. Analysis of individual cells revealed that the distribution of coupling across the islet is highly heterogeneous. Analysis of several modulators of gap junction coupling revealed glucose‐ and cAMP‐dependent modulation of gap junction coupling in islets. Finally, FRAP was used to determine cell population specific coupling, where no functional gap junction coupling was observed between α cells and β cells in the islet. The results of this study show FRAP to be a robust technique which provides the cellular resolution to quantify the distribution and regulation of Cx36 gap junction coupling in specific cell populations within the islet. Future studies utilizing this technique may elucidate the role of gap junction coupling in the progression of diabetes and identify mechanisms of gap junction regulation for potential therapies.

Robust variance estimation with dependent effect sizes: practical considerations including a software tutorial in Stata and spss.

PubMed

Tanner-Smith, Emily E; Tipton, Elizabeth

2014-03-01

Methodologists have recently proposed robust variance estimation as one way to handle dependent effect sizes in meta-analysis. Software macros for robust variance estimation in meta-analysis are currently available for Stata (StataCorp LP, College Station, TX, USA) and spss (IBM, Armonk, NY, USA), yet there is little guidance for authors regarding the practical application and implementation of those macros. This paper provides a brief tutorial on the implementation of the Stata and spss macros and discusses practical issues meta-analysts should consider when estimating meta-regression models with robust variance estimates. Two example databases are used in the tutorial to illustrate the use of meta-analysis with robust variance estimates. Copyright © 2013 John Wiley & Sons, Ltd.

Aging effects on DNA methylation modules in human brain and blood tissue

PubMed Central

2012-01-01

Background Several recent studies reported aging effects on DNA methylation levels of individual CpG dinucleotides. But it is not yet known whether aging-related consensus modules, in the form of clusters of correlated CpG markers, can be found that are present in multiple human tissues. Such a module could facilitate the understanding of aging effects on multiple tissues. Results We therefore employed weighted correlation network analysis of 2,442 Illumina DNA methylation arrays from brain and blood tissues, which enabled the identification of an age-related co-methylation module. Module preservation analysis confirmed that this module can also be found in diverse independent data sets. Biological evaluation showed that module membership is associated with Polycomb group target occupancy counts, CpG island status and autosomal chromosome location. Functional enrichment analysis revealed that the aging-related consensus module comprises genes that are involved in nervous system development, neuron differentiation and neurogenesis, and that it contains promoter CpGs of genes known to be down-regulated in early Alzheimer's disease. A comparison with a standard, non-module based meta-analysis revealed that selecting CpGs based on module membership leads to significantly increased gene ontology enrichment, thus demonstrating that studying aging effects via consensus network analysis enhances the biological insights gained. Conclusions Overall, our analysis revealed a robustly defined age-related co-methylation module that is present in multiple human tissues, including blood and brain. We conclude that blood is a promising surrogate for brain tissue when studying the effects of age on DNA methylation profiles. PMID:23034122

Correcting systematic inflation in genetic association tests that consider interaction effects: application to a genome-wide association study of posttraumatic stress disorder.

PubMed

Almli, Lynn M; Duncan, Richard; Feng, Hao; Ghosh, Debashis; Binder, Elisabeth B; Bradley, Bekh; Ressler, Kerry J; Conneely, Karen N; Epstein, Michael P

2014-12-01

Genetic association studies of psychiatric outcomes often consider interactions with environmental exposures and, in particular, apply tests that jointly consider gene and gene-environment interaction effects for analysis. Using a genome-wide association study (GWAS) of posttraumatic stress disorder (PTSD), we report that heteroscedasticity (defined as variability in outcome that differs by the value of the environmental exposure) can invalidate traditional joint tests of gene and gene-environment interaction. To identify the cause of bias in traditional joint tests of gene and gene-environment interaction in a PTSD GWAS and determine whether proposed robust joint tests are insensitive to this problem. The PTSD GWAS data set consisted of 3359 individuals (978 men and 2381 women) from the Grady Trauma Project (GTP), a cohort study from Atlanta, Georgia. The GTP performed genome-wide genotyping of participants and collected environmental exposures using the Childhood Trauma Questionnaire and Trauma Experiences Inventory. We performed joint interaction testing of the Beck Depression Inventory and modified PTSD Symptom Scale in the GTP GWAS. We assessed systematic bias in our interaction analyses using quantile-quantile plots and genome-wide inflation factors. Application of the traditional joint interaction test to the GTP GWAS yielded systematic inflation across different outcomes and environmental exposures (inflation-factor estimates ranging from 1.07 to 1.21), whereas application of the robust joint test to the same data set yielded no such inflation (inflation-factor estimates ranging from 1.01 to 1.02). Simulated data further revealed that the robust joint test is valid in different heteroscedasticity models, whereas the traditional joint test is invalid. The robust joint test also has power similar to the traditional joint test when heteroscedasticity is not an issue. We believe the robust joint test should be used in candidate-gene studies and GWASs of psychiatric outcomes that consider environmental interactions. To make the procedure useful for applied investigators, we created a software tool that can be called from the popular PLINK package for analysis.

Correcting Systematic Inflation in Genetic Association Tests That Consider Interaction Effects

PubMed Central

Almli, Lynn M.; Duncan, Richard; Feng, Hao; Ghosh, Debashis; Binder, Elisabeth B.; Bradley, Bekh; Ressler, Kerry J.; Conneely, Karen N.; Epstein, Michael P.

2015-01-01

IMPORTANCE Genetic association studies of psychiatric outcomes often consider interactions with environmental exposures and, in particular, apply tests that jointly consider gene and gene-environment interaction effects for analysis. Using a genome-wide association study (GWAS) of posttraumatic stress disorder (PTSD), we report that heteroscedasticity (defined as variability in outcome that differs by the value of the environmental exposure) can invalidate traditional joint tests of gene and gene-environment interaction. OBJECTIVES To identify the cause of bias in traditional joint tests of gene and gene-environment interaction in a PTSD GWAS and determine whether proposed robust joint tests are insensitive to this problem. DESIGN, SETTING, AND PARTICIPANTS The PTSD GWAS data set consisted of 3359 individuals (978 men and 2381 women) from the Grady Trauma Project (GTP), a cohort study from Atlanta, Georgia. The GTP performed genome-wide genotyping of participants and collected environmental exposures using the Childhood Trauma Questionnaire and Trauma Experiences Inventory. MAIN OUTCOMES AND MEASURES We performed joint interaction testing of the Beck Depression Inventory and modified PTSD Symptom Scale in the GTP GWAS. We assessed systematic bias in our interaction analyses using quantile-quantile plots and genome-wide inflation factors. RESULTS Application of the traditional joint interaction test to the GTP GWAS yielded systematic inflation across different outcomes and environmental exposures (inflation-factor estimates ranging from 1.07 to 1.21), whereas application of the robust joint test to the same data set yielded no such inflation (inflation-factor estimates ranging from 1.01 to 1.02). Simulated data further revealed that the robust joint test is valid in different heteroscedasticity models, whereas the traditional joint test is invalid. The robust joint test also has power similar to the traditional joint test when heteroscedasticity is not an issue. CONCLUSIONS AND RELEVANCE We believe the robust joint test should be used in candidate-gene studies and GWASs of psychiatric outcomes that consider environmental interactions. To make the procedure useful for applied investigators, we created a software tool that can be called from the popular PLINK package for analysis. PMID:25354142

Optical Measurement of Radiocarbon below Unity Fraction Modern by Linear Absorption Spectroscopy.

PubMed

Fleisher, Adam J; Long, David A; Liu, Qingnan; Gameson, Lyn; Hodges, Joseph T

2017-09-21

High-precision measurements of radiocarbon ( 14 C) near or below a fraction modern 14 C of 1 (F 14 C ≤ 1) are challenging and costly. An accurate, ultrasensitive linear absorption approach to detecting 14 C would provide a simple and robust benchtop alternative to off-site accelerator mass spectrometry facilities. Here we report the quantitative measurement of 14 C in gas-phase samples of CO 2 with F 14 C < 1 using cavity ring-down spectroscopy in the linear absorption regime. Repeated analysis of CO 2 derived from the combustion of either biogenic or petrogenic sources revealed a robust ability to differentiate samples with F 14 C < 1. With a combined uncertainty of 14 C/ 12 C = 130 fmol/mol (F 14 C = 0.11), initial performance of the calibration-free instrument is sufficient to investigate a variety of applications in radiocarbon measurement science including the study of biofuels and bioplastics, illicitly traded specimens, bomb dating, and atmospheric transport.

Planck intermediate results. XVI. Profile likelihoods for cosmological parameters

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Battaner, E.; Benabed, K.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bobin, J.; Bonaldi, A.; Bond, J. R.; Bouchet, F. R.; Burigana, C.; Cardoso, J.-F.; Catalano, A.; Chamballu, A.; Chiang, H. C.; Christensen, P. R.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Couchot, F.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Dickinson, C.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Dupac, X.; Enßlin, T. A.; Eriksen, H. K.; Finelli, F.; Forni, O.; Frailis, M.; Franceschi, E.; Galeotta, S.; Galli, S.; Ganga, K.; Giard, M.; Giraud-Héraud, Y.; González-Nuevo, J.; Górski, K. M.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Harrison, D. L.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lawrence, C. R.; Leonardi, R.; Liddle, A.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maffei, B.; Maino, D.; Mandolesi, N.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Massardi, M.; Matarrese, S.; Mazzotta, P.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski∗, S.; Pointecouteau, E.; Polenta, G.; Popa, L.; Pratt, G. W.; Puget, J.-L.; Rachen, J. P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Roudier, G.; Rouillé d'Orfeuil, B.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Savelainen, M.; Savini, G.; Spencer, L. D.; Spinelli, M.; Starck, J.-L.; Sureau, F.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; White, M.; Yvon, D.; Zacchei, A.; Zonca, A.

2014-06-01

We explore the 2013 Planck likelihood function with a high-precision multi-dimensional minimizer (Minuit). This allows a refinement of the ΛCDM best-fit solution with respect to previously-released results, and the construction of frequentist confidence intervals using profile likelihoods. The agreement with the cosmological results from the Bayesian framework is excellent, demonstrating the robustness of the Planck results to the statistical methodology. We investigate the inclusion of neutrino masses, where more significant differences may appear due to the non-Gaussian nature of the posterior mass distribution. By applying the Feldman-Cousins prescription, we again obtain results very similar to those of the Bayesian methodology. However, the profile-likelihood analysis of the cosmic microwave background (CMB) combination (Planck+WP+highL) reveals a minimum well within the unphysical negative-mass region. We show that inclusion of the Planck CMB-lensing information regularizes this issue, and provide a robust frequentist upper limit ∑ mν ≤ 0.26 eV (95% confidence) from the CMB+lensing+BAO data combination.

Distinguishability of stacks in ZnTe/ZnSe quantum dots via spectral analysis of Aharonov-Bohm oscillations

NASA Astrophysics Data System (ADS)

Roy, Bidisha; Ji, Haojie; Dhomkar, Siddharth; Cadieu, Fred J.; Peng, Le; Moug, Richard; Tamargo, Maria C.; Kuskovsky, Igor L.

2013-02-01

A spectral analysis of the Aharonov-Bohm (AB) oscillations in photoluminescence intensity was performed for stacked type-II ZnTe/ZnSe quantum dots (QDs) fabricated within multilayered Zn-Se-Te system with sub-monolayer insertions of Te. Robust AB oscillations allowed for fine probing of distinguishable QDs stacks within the ensemble of QDs. The AB transition magnetic field, B AB , changed from the lower energy side to the higher energy side of the PL spectra revealing the presence of different sets of QDs stacks. The change occurs within the spectral range, where the contributing green and blue bands of the spectra overlapped. "Bundling" in lifetime measurements is seen at transition spectral regions confirming the results.

On Priming Action: Conclusions from a Meta-Analysis of the Behavioral Effects of Incidentally-Presented Words

PubMed Central

Weingarten, Evan; Chen, Qijia; McAdams, Maxwell; Yi, Jessica; Hepler, Justin; Albarracin, Dolores

2016-01-01

This paper presents a summary of the conclusions drawn from a meta-analysis of the behavioral impact of presenting words connected to an action or a goal representation (Weingarten et al., 2016). The average and distribution of 352 effect sizes from 133 studies (84 reports) revealed a small behavioral priming effect (dFE = 0.332, dRE= 0.352), which was robust across methodological procedures and only minimally biased by the publication of positive (vs. negative) results. More valued behavior or goal concepts (e.g., associated with important outcomes or values) were associated with stronger priming effects than were less valued behaviors. In addition, opportunities for goal satisfaction appeared to decrease priming effects. PMID:27957520

Functional genomic analysis of drug sensitivity pathways to guide adjuvant strategies in breast cancer

PubMed Central

Swanton, Charles; Szallasi, Zoltan; Brenton, James D; Downward, Julian

2008-01-01

The widespread introduction of high throughput RNA interference screening technology has revealed tumour drug sensitivity pathways to common cytotoxics such as paclitaxel, doxorubicin and 5-fluorouracil, targeted agents such as trastuzumab and inhibitors of AKT and Poly(ADP-ribose) polymerase (PARP) as well as endocrine therapies such as tamoxifen. Given the limited power of microarray signatures to predict therapeutic response in associative studies of small clinical trial cohorts, the use of functional genomic data combined with expression or sequence analysis of genes and microRNAs implicated in drug response in human tumours may provide a more robust method to guide adjuvant treatment strategies in breast cancer that are transferable across different expression platforms and patient cohorts. PMID:18986507

Crystalline Coordination Networks of Zero-Valent Metal Centers: Formation of a 3-Dimensional Ni(0) Framework with m-Terphenyl Diisocyanides.

PubMed

Agnew, Douglas W; DiMucci, Ida M; Arroyave, Alejandra; Gembicky, Milan; Moore, Curtis E; MacMillan, Samantha N; Rheingold, Arnold L; Lancaster, Kyle M; Figueroa, Joshua S

2017-12-06

A permanently porous, three-dimensional metal-organic material formed from zero-valent metal nodes is presented. Combination of ditopic m-terphenyl diisocyanide, [CNAr Mes2 ] 2 , and the d 10 Ni(0) precursor Ni(COD) 2 , produces a porous metal-organic material featuring tetrahedral [Ni(CNAr Mes2 ) 4 ] n structural sites. X-ray absorption spectroscopy provides firm evidence for the presence of Ni(0) centers, whereas gas-sorption and thermogravimetric analysis reveal the characteristics of a robust network with a microdomain N 2 -adsorption profile.

Crystalline Coordination Networks of Zero-Valent Metal Centers: Formation of a 3-Dimensional Ni(0) Framework with m-Terphenyl Diisocyanides

DOE PAGES

Agnew, Douglas W.; DiMucci, Ida M.; Arroyave, Alejandra; ...

2017-11-13

A permanently porous, three-dimensional metal–organic material formed from zero-valent metal nodes is presented. Combination of ditopic m-terphenyl diisocyanide, [CNAr Mes2] 2, and the d 10 Ni(0) precursor Ni(COD) 2, produces a porous metal–organic material featuring tetrahedral [Ni(CNAr Mes2) 4] n structural sites. X-ray absorption spectroscopy provides firm evidence for the presence of Ni(0) centers, whereas gas-sorption and thermogravimetric analysis reveal the characteristics of a robust network with a microdomain N 2-adsorption profile.

Robust patterning of gene expression based on internal coordinate system of cells.

PubMed

Ogawa, Ken-ichiro; Miyake, Yoshihiro

2015-06-01

Cell-to-cell communication in multicellular organisms is established through the transmission of various kinds of chemical substances such as proteins. It is well known that gene expression triggered by a chemical substance in individuals has stable spatial patterns despite the individual differences in concentration patterns of the chemical substance. This fact reveals an important property of multicellular organisms called "robustness", which allows the organisms to generate their forms while maintaining proportion. Robustness has been conventionally accounted for by the stability of solutions of dynamical equations that represent a specific interaction network of chemical substances. However, any biological system is composed of autonomous elements. In general, an autonomous element does not merely accept information on the chemical substance from the environment; instead, it accepts the information based on its own criteria for reaction. Therefore, this phenomenon needs to be considered from the viewpoint of cells. Such a viewpoint is expected to allow the consideration of the autonomy of cells in multicellular organisms. This study aims to explain theoretically the robust patterning of gene expression from the viewpoint of cells. For this purpose, we introduced a new operator for transforming a state variable of a chemical substance from an external coordinate system to an internal coordinate system of each cell, which describes the observation of the chemical substance by cells. We then applied this operator to the simplest reaction-diffusion model of the chemical substance to investigate observation effects by cells. Our mathematical analysis of this extended model indicates that the robust patterning of gene expression against individual differences in concentration pattern of the chemical substance can be explained from the viewpoint of cells if there is a regulation field that compensates for the difference between cells seen in the observation results. This result provides a new insight into the investigation of the mechanism of robust patterning in biological systems composed of individual elements. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

New Frontiers and Challenges for Single-Cell Electrochemical Analysis.

PubMed

Zhang, Jingjing; Zhou, Junyu; Pan, Rongrong; Jiang, Dechen; Burgess, James D; Chen, Hong-Yuan

2018-02-23

Previous measurements of cell populations might obscure many important cellular differences, and new strategies for single-cell analyses are urgently needed to re-examine these fundamental biological principles for better diagnosis and treatment of diseases. Electrochemistry is a robust technique for the analysis of single living cells that has the advantages of minor interruption of cellular activity and provides the capability of high spatiotemporal resolution. The achievements of the past 30 years have revealed significant information about the exocytotic events of single cells to elucidate the mechanisms of cellular activity. Currently, the rapid developments of micro/nanofabrication and optoelectronic technologies drive the development of multifunctional electrodes and novel electrochemical approaches with higher resolution for single cells. In this Perspective, three new frontiers in this field, namely, electrochemical microscopy, intracellular analysis, and single-cell analysis in a biological system (i.e., neocortex and retina), are reviewed. The unique features and remaining challenges of these techniques are discussed.

Comprehensive machine learning analysis of Hydra behavior reveals a stable basal behavioral repertoire

PubMed Central

Taralova, Ekaterina; Dupre, Christophe; Yuste, Rafael

2018-01-01

Animal behavior has been studied for centuries, but few efficient methods are available to automatically identify and classify it. Quantitative behavioral studies have been hindered by the subjective and imprecise nature of human observation, and the slow speed of annotating behavioral data. Here, we developed an automatic behavior analysis pipeline for the cnidarian Hydra vulgaris using machine learning. We imaged freely behaving Hydra, extracted motion and shape features from the videos, and constructed a dictionary of visual features to classify pre-defined behaviors. We also identified unannotated behaviors with unsupervised methods. Using this analysis pipeline, we quantified 6 basic behaviors and found surprisingly similar behavior statistics across animals within the same species, regardless of experimental conditions. Our analysis indicates that the fundamental behavioral repertoire of Hydra is stable. This robustness could reflect a homeostatic neural control of "housekeeping" behaviors which could have been already present in the earliest nervous systems. PMID:29589829

Confirmatory Factor Analysis of the System for Evaluation of Teaching Qualities (SETQ) in Graduate Medical Training.

PubMed

Boerebach, Benjamin C M; Lombarts, Kiki M J M H; Arah, Onyebuchi A

2016-03-01

The System for Evaluation of Teaching Qualities (SETQ) was developed as a formative system for the continuous evaluation and development of physicians' teaching performance in graduate medical training. It has been seven years since the introduction and initial exploratory psychometric analysis of the SETQ questionnaires. This study investigates the validity and reliability of the SETQ questionnaires across hospitals and medical specialties using confirmatory factor analyses (CFAs), reliability analysis, and generalizability analysis. The SETQ questionnaires were tested in a sample of 3,025 physicians and 2,848 trainees in 46 hospitals. The CFA revealed acceptable fit of the data to the previously identified five-factor model. The high internal consistency estimates suggest satisfactory reliability of the subscales. These results provide robust evidence for the validity and reliability of the SETQ questionnaires for evaluating physicians' teaching performance. © The Author(s) 2014.

Generalized Stability Analysis of Capillary Flow in Slender V-Grooves

NASA Astrophysics Data System (ADS)

White, Nicholas; Troian, Sandra

2017-11-01

Spontaneous capillary flow, an especially rapid process in slender open microchannels resembling V-grooves, is of significant importance to many applications requiring passive robust flow control. Many types of biomedical devices for point-of-care use in developing countries are being designed around this principle. Important fundamental work by Romero and Yost (1996) and Weislogel (1996) elucidated the behavior of Newtonian films in slender V-grooves driven to flow by the streamwise change in capillary pressure due to the change in radius of curvature of the circular arc describing the interface of wetting or non-wetting fluids. Self-similar solutions describing Washburn type dynamics were found but other solutions are possible. Here we extend the Romero and Yost model to include a variety of inlet and outlet boundary conditions and examine the transient growth and generalized stability of perturbations to steady state and self-similar flows. Although most cases examined for wetting fluids exhibit robust stability against small perturbations, some exceptions reveal unstable flow. In total, these results support decades of experimental work which has found this method of flow control to be especially reliable, robust and self-healing. The authors gratefully acknowledge financial support from the 2016 NASA/Jet Propulsion Laboratory President's and Director's Fund as well as a 2017 NASA Space Technology Research Fellowship.

Study on recognition technology of complementary image

NASA Astrophysics Data System (ADS)

Liu, Chengxiang; Hu, Xuejuan; Jian, Yaobo; Zhang, Li

2006-11-01

Complementation image is often used as a guard technology in the trademark and paper currency. The key point of recognizing this kind of images is judging the complementary effect of complementation printing. The perspective images are usually not clear and legible, so it is difficult to recognize them. In this paper, a new method is proposed. Firstly, capture the image by reflex. Secondly, find the same norm to man-made pair printing. Lastly, judge the true and false of paper currency by the complementary effect of complementation printing. This is the purpose of inspecting the false. Theoretic analysis and simulation results reveal that the effect of man-made pair printing is good, the method has advantages such as simplicity, high calculating speed, and good robust to different RMB. The experiment results reveal that the conclusion is reasonable, and demonstrates that this approach is effective.

Identification and Validation of a Diagnostic and Prognostic Multi-Gene Biomarker Panel for Pancreatic Ductal Adenocarcinoma.

PubMed

Klett, Hagen; Fuellgraf, Hannah; Levit-Zerdoun, Ella; Hussung, Saskia; Kowar, Silke; Küsters, Simon; Bronsert, Peter; Werner, Martin; Wittel, Uwe; Fritsch, Ralph; Busch, Hauke; Boerries, Melanie

2018-01-01

Late diagnosis and systemic dissemination essentially contribute to the invariably poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Therefore, the development of diagnostic biomarkers for PDAC are urgently needed to improve patient stratification and outcome in the clinic. By studying the transcriptomes of independent PDAC patient cohorts of tumor and non-tumor tissues, we identified 81 robustly regulated genes, through a novel, generally applicable meta-analysis. Using consensus clustering on co-expression values revealed four distinct clusters with genes originating from exocrine/endocrine pancreas, stromal and tumor cells. Three clusters were strongly associated with survival of PDAC patients based on TCGA database underlining the prognostic potential of the identified genes. With the added information of impact of survival and the robustness within the meta-analysis, we extracted a 17-gene subset for further validation. We show that it did not only discriminate PDAC from non-tumor tissue and stroma in fresh-frozen as well as formalin-fixed paraffin embedded samples, but also detected pancreatic precursor lesions and singled out pancreatitis samples. Moreover, the classifier discriminated PDAC from other cancers in the TCGA database. In addition, we experimentally validated the classifier in PDAC patients on transcript level using qPCR and exemplify the usage on protein level for three proteins (AHNAK2, LAMC2, TFF1) using immunohistochemistry and for two secreted proteins (TFF1, SERPINB5) using ELISA-based protein detection in blood-plasma. In conclusion, we present a novel robust diagnostic and prognostic gene signature for PDAC with future potential applicability in the clinic.

Identification and Validation of a Diagnostic and Prognostic Multi-Gene Biomarker Panel for Pancreatic Ductal Adenocarcinoma

PubMed Central

Klett, Hagen; Fuellgraf, Hannah; Levit-Zerdoun, Ella; Hussung, Saskia; Kowar, Silke; Küsters, Simon; Bronsert, Peter; Werner, Martin; Wittel, Uwe; Fritsch, Ralph; Busch, Hauke; Boerries, Melanie

2018-01-01

Late diagnosis and systemic dissemination essentially contribute to the invariably poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Therefore, the development of diagnostic biomarkers for PDAC are urgently needed to improve patient stratification and outcome in the clinic. By studying the transcriptomes of independent PDAC patient cohorts of tumor and non-tumor tissues, we identified 81 robustly regulated genes, through a novel, generally applicable meta-analysis. Using consensus clustering on co-expression values revealed four distinct clusters with genes originating from exocrine/endocrine pancreas, stromal and tumor cells. Three clusters were strongly associated with survival of PDAC patients based on TCGA database underlining the prognostic potential of the identified genes. With the added information of impact of survival and the robustness within the meta-analysis, we extracted a 17-gene subset for further validation. We show that it did not only discriminate PDAC from non-tumor tissue and stroma in fresh-frozen as well as formalin-fixed paraffin embedded samples, but also detected pancreatic precursor lesions and singled out pancreatitis samples. Moreover, the classifier discriminated PDAC from other cancers in the TCGA database. In addition, we experimentally validated the classifier in PDAC patients on transcript level using qPCR and exemplify the usage on protein level for three proteins (AHNAK2, LAMC2, TFF1) using immunohistochemistry and for two secreted proteins (TFF1, SERPINB5) using ELISA-based protein detection in blood-plasma. In conclusion, we present a novel robust diagnostic and prognostic gene signature for PDAC with future potential applicability in the clinic. PMID:29675033

A Bayesian Multinomial Probit MODEL FOR THE ANALYSIS OF PANEL CHOICE DATA.

PubMed

Fong, Duncan K H; Kim, Sunghoon; Chen, Zhe; DeSarbo, Wayne S

2016-03-01

A new Bayesian multinomial probit model is proposed for the analysis of panel choice data. Using a parameter expansion technique, we are able to devise a Markov Chain Monte Carlo algorithm to compute our Bayesian estimates efficiently. We also show that the proposed procedure enables the estimation of individual level coefficients for the single-period multinomial probit model even when the available prior information is vague. We apply our new procedure to consumer purchase data and reanalyze a well-known scanner panel dataset that reveals new substantive insights. In addition, we delineate a number of advantageous features of our proposed procedure over several benchmark models. Finally, through a simulation analysis employing a fractional factorial design, we demonstrate that the results from our proposed model are quite robust with respect to differing factors across various conditions.

Implicit timing activates the left inferior parietal cortex.

PubMed

Wiener, Martin; Turkeltaub, Peter E; Coslett, H Branch

2010-11-01

Coull and Nobre (2008) suggested that tasks that employ temporal cues might be divided on the basis of whether these cues are explicitly or implicitly processed. Furthermore, they suggested that implicit timing preferentially engages the left cerebral hemisphere. We tested this hypothesis by conducting a quantitative meta-analysis of eleven neuroimaging studies of implicit timing using the activation-likelihood estimation (ALE) algorithm (Turkeltaub, Eden, Jones, & Zeffiro, 2002). Our analysis revealed a single but robust cluster of activation-likelihood in the left inferior parietal cortex (supramarginal gyrus). This result is in accord with the hypothesis that the left hemisphere subserves implicit timing mechanisms. Furthermore, in conjunction with a previously reported meta-analysis of explicit timing tasks, our data support the claim that implicit and explicit timing are supported by at least partially distinct neural structures. Copyright © 2010 Elsevier Ltd. All rights reserved.

Large scale aggregate microarray analysis reveals three distinct molecular subclasses of human preeclampsia.

PubMed

Leavey, Katherine; Bainbridge, Shannon A; Cox, Brian J

2015-01-01

Preeclampsia (PE) is a life-threatening hypertensive pathology of pregnancy affecting 3-5% of all pregnancies. To date, PE has no cure, early detection markers, or effective treatments short of the removal of what is thought to be the causative organ, the placenta, which may necessitate a preterm delivery. Additionally, numerous small placental microarray studies attempting to identify "PE-specific" genes have yielded inconsistent results. We therefore hypothesize that preeclampsia is a multifactorial disease encompassing several pathology subclasses, and that large cohort placental gene expression analysis will reveal these groups. To address our hypothesis, we utilized known bioinformatic methods to aggregate 7 microarray data sets across multiple platforms in order to generate a large data set of 173 patient samples, including 77 with preeclampsia. Unsupervised clustering of these patient samples revealed three distinct molecular subclasses of PE. This included a "canonical" PE subclass demonstrating elevated expression of known PE markers and genes associated with poor oxygenation and increased secretion, as well as two other subclasses potentially representing a poor maternal response to pregnancy and an immunological presentation of preeclampsia. Our analysis sheds new light on the heterogeneity of PE patients, and offers up additional avenues for future investigation. Hopefully, our subclassification of preeclampsia based on molecular diversity will finally lead to the development of robust diagnostics and patient-based treatments for this disorder.

Robust Variance Estimation with Dependent Effect Sizes: Practical Considerations Including a Software Tutorial in Stata and SPSS

ERIC Educational Resources Information Center

Tanner-Smith, Emily E.; Tipton, Elizabeth

2014-01-01

Methodologists have recently proposed robust variance estimation as one way to handle dependent effect sizes in meta-analysis. Software macros for robust variance estimation in meta-analysis are currently available for Stata (StataCorp LP, College Station, TX, USA) and SPSS (IBM, Armonk, NY, USA), yet there is little guidance for authors regarding…

FATSLiM: a fast and robust software to analyze MD simulations of membranes.

PubMed

Buchoux, Sébastien

2017-01-01

When studying biological membranes, Molecular Dynamics (MD) simulations reveal to be quite complementary to experimental techniques. Because the simulated systems keep increasing both in size and complexity, the analysis of MD trajectories need to be computationally efficient while being robust enough to perform analysis on membranes that may be curved or deformed due to their size and/or protein-lipid interactions. This work presents a new software named FATSLiM ('Fast Analysis Toolbox for Simulations of Lipid Membranes') that can extract physical properties from MD simulations of membranes (with or without interacting proteins). Because it relies on the calculation of local normals, FATSLiM does not depend of the bilayer morphology and thus can handle with the same accuracy vesicles for instance. Thanks to an efficiency-driven development, it is also fast and consumes a rather low amount of memory. FATSLiM (http://fatslim.github.io) is a stand-alone software written in Python. Source code is released under the GNU GPLv3 and is freely available at https://github.com/FATSLiM/fatslim A complete online documentation including instructions for platform-independent installation is available at http://pythonhosted.org/fatslim CONTACT: sebastien.buchoux@u-picardie.frSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Eliciting mixed emotions: a meta-analysis comparing models, types, and measures.

PubMed

Berrios, Raul; Totterdell, Peter; Kellett, Stephen

2015-01-01

The idea that people can experience two oppositely valenced emotions has been controversial ever since early attempts to investigate the construct of mixed emotions. This meta-analysis examined the robustness with which mixed emotions have been elicited experimentally. A systematic literature search identified 63 experimental studies that instigated the experience of mixed emotions. Studies were distinguished according to the structure of the underlying affect model-dimensional or discrete-as well as according to the type of mixed emotions studied (e.g., happy-sad, fearful-happy, positive-negative). The meta-analysis using a random-effects model revealed a moderate to high effect size for the elicitation of mixed emotions (d IG+ = 0.77), which remained consistent regardless of the structure of the affect model, and across different types of mixed emotions. Several methodological and design moderators were tested. Studies using the minimum index (i.e., the minimum value between a pair of opposite valenced affects) resulted in smaller effect sizes, whereas subjective measures of mixed emotions increased the effect sizes. The presence of more women in the samples was also associated with larger effect sizes. The current study indicates that mixed emotions are a robust, measurable and non-artifactual experience. The results are discussed in terms of the implications for an affect system that has greater versatility and flexibility than previously thought.

Analysis of a dynamic model of guard cell signaling reveals the stability of signal propagation

NASA Astrophysics Data System (ADS)

Gan, Xiao; Albert, RéKa

Analyzing the long-term behaviors (attractors) of dynamic models of biological systems can provide valuable insight into biological phenotypes and their stability. We identified the long-term behaviors of a multi-level, 70-node discrete dynamic model of the stomatal opening process in plants. We reduce the model's huge state space by reducing unregulated nodes and simple mediator nodes, and by simplifying the regulatory functions of selected nodes while keeping the model consistent with experimental observations. We perform attractor analysis on the resulting 32-node reduced model by two methods: 1. converting it into a Boolean model, then applying two attractor-finding algorithms; 2. theoretical analysis of the regulatory functions. We conclude that all nodes except two in the reduced model have a single attractor; and only two nodes can admit oscillations. The multistability or oscillations do not affect the stomatal opening level in any situation. This conclusion applies to the original model as well in all the biologically meaningful cases. We further demonstrate the robustness of signal propagation by showing that a large percentage of single-node knockouts does not affect the stomatal opening level. Thus, we conclude that the complex structure of this signal transduction network provides multiple information propagation pathways while not allowing extensive multistability or oscillations, resulting in robust signal propagation. Our innovative combination of methods offers a promising way to analyze multi-level models.

Eliciting mixed emotions: a meta-analysis comparing models, types, and measures

PubMed Central

Berrios, Raul; Totterdell, Peter; Kellett, Stephen

2015-01-01

The idea that people can experience two oppositely valenced emotions has been controversial ever since early attempts to investigate the construct of mixed emotions. This meta-analysis examined the robustness with which mixed emotions have been elicited experimentally. A systematic literature search identified 63 experimental studies that instigated the experience of mixed emotions. Studies were distinguished according to the structure of the underlying affect model—dimensional or discrete—as well as according to the type of mixed emotions studied (e.g., happy-sad, fearful-happy, positive-negative). The meta-analysis using a random-effects model revealed a moderate to high effect size for the elicitation of mixed emotions (dIG+ = 0.77), which remained consistent regardless of the structure of the affect model, and across different types of mixed emotions. Several methodological and design moderators were tested. Studies using the minimum index (i.e., the minimum value between a pair of opposite valenced affects) resulted in smaller effect sizes, whereas subjective measures of mixed emotions increased the effect sizes. The presence of more women in the samples was also associated with larger effect sizes. The current study indicates that mixed emotions are a robust, measurable and non-artifactual experience. The results are discussed in terms of the implications for an affect system that has greater versatility and flexibility than previously thought. PMID:25926805

Novel Methods for Analysing Bacterial Tracks Reveal Persistence in Rhodobacter sphaeroides

PubMed Central

Rosser, Gabriel; Fletcher, Alexander G.; Wilkinson, David A.; de Beyer, Jennifer A.; Yates, Christian A.; Armitage, Judith P.; Maini, Philip K.; Baker, Ruth E.

2013-01-01

Tracking bacteria using video microscopy is a powerful experimental approach to probe their motile behaviour. The trajectories obtained contain much information relating to the complex patterns of bacterial motility. However, methods for the quantitative analysis of such data are limited. Most swimming bacteria move in approximately straight lines, interspersed with random reorientation phases. It is therefore necessary to segment observed tracks into swimming and reorientation phases to extract useful statistics. We present novel robust analysis tools to discern these two phases in tracks. Our methods comprise a simple and effective protocol for removing spurious tracks from tracking datasets, followed by analysis based on a two-state hidden Markov model, taking advantage of the availability of mutant strains that exhibit swimming-only or reorientating-only motion to generate an empirical prior distribution. Using simulated tracks with varying levels of added noise, we validate our methods and compare them with an existing heuristic method. To our knowledge this is the first example of a systematic assessment of analysis methods in this field. The new methods are substantially more robust to noise and introduce less systematic bias than the heuristic method. We apply our methods to tracks obtained from the bacterial species Rhodobacter sphaeroides and Escherichia coli. Our results demonstrate that R. sphaeroides exhibits persistence over the course of a tumbling event, which is a novel result with important implications in the study of this and similar species. PMID:24204227

Single Cell Analysis: From Technology to Biology and Medicine.

PubMed

Pan, Xinghua

2014-01-01

Single-cell analysis heralds a new era that allows "omics" analysis, notably genomics, transcriptomics, epigenomics and proteomics at the single-cell level. It enables the identification of the minor subpopulations that may play a critical role in a biological process of a population of cells, which conventionally are regarded as homogeneous. It provides an ultra-sensitive tool to clarify specific molecular mechanisms and pathways and reveal the nature of cell heterogeneity. It also facilitates the clinical investigation of patients when a very low quantity or a single cell is available for analysis, such as noninvasive prenatal diagnosis and cancer screening, and genetic evaluation for in vitro fertilization. Within a few short years, single-cell analysis, especially whole genomic sequencing and transcriptomic sequencing, is becoming robust and broadly accessible, although not yet a routine practice. Here, with single cell RNA-seq emphasized, an overview of the discipline, progresses, and prospects of single-cell analysis and its applications in biology and medicine are given with a series of logic and theoretical considerations.

Lucid dreaming incidence: A quality effects meta-analysis of 50years of research.

PubMed

Saunders, David T; Roe, Chris A; Smith, Graham; Clegg, Helen

2016-07-01

We report a quality effects meta-analysis on studies from the period 1966-2016 measuring either (a) lucid dreaming prevalence (one or more lucid dreams in a lifetime); (b) frequent lucid dreaming (one or more lucid dreams in a month) or both. A quality effects meta-analysis allows for the minimisation of the influence of study methodological quality on overall model estimates. Following sensitivity analysis, a heterogeneous lucid dreaming prevalence data set of 34 studies yielded a mean estimate of 55%, 95% C. I. [49%, 62%] for which moderator analysis showed no systematic bias for suspected sources of variability. A heterogeneous lucid dreaming frequency data set of 25 studies yielded a mean estimate of 23%, 95% C. I. [20%, 25%], moderator analysis revealed no suspected sources of variability. These findings are consistent with earlier estimates of lucid dreaming prevalence and frequent lucid dreaming in the population but are based on more robust evidence. Copyright © 2016 Elsevier Inc. All rights reserved.

Functional cliques in the amygdala and related brain networks driven by fear assessment acquired during movie viewing.

PubMed

Kinreich, Sivan; Intrator, Nathan; Hendler, Talma

2011-01-01

One of the greatest challenges involved in studying the brain mechanisms of fear is capturing the individual's unique instantaneous experience. Brain imaging studies to date commonly sacrifice valuable information regarding the individual real-time conscious experience, especially when focusing on elucidating the amygdala's activity. Here, we assumed that by using a minimally intrusive cue along with applying a robust clustering approach to probe the amygdala, it would be possible to rate fear in real time and to derive the related network of activation. During functional magnetic resonance imaging scanning, healthy volunteers viewed two excerpts from horror movies and were periodically auditory cued to rate their instantaneous experience of "I'm scared." Using graph theory and community mathematical concepts, data-driven clustering of the fear-related functional cliques in the amygdala was performed guided by the individually marked periods of heightened fear. Individually tailored functions derived from these amygdala activation cliques were subsequently applied as general linear model predictors to a whole-brain analysis to reveal the correlated networks. Our results suggest that by using a localized robust clustering approach, it is possible to probe activation in the right dorsal amygdala that is directly related to individual real-time emotional experience. Moreover, this fear-evoked amygdala revealed two opposing networks of co-activation and co-deactivation, which correspond to vigilance and rest-related circuits, respectively.

Human embryonic and induced pluripotent stem cells maintain phenotype but alter their metabolism after exposure to ROCK inhibitor.

PubMed

Vernardis, Spyros I; Terzoudis, Konstantinos; Panoskaltsis, Nicki; Mantalaris, Athanasios

2017-02-06

Human pluripotent stem cells (hPSCs) are adhesion-dependent cells that require cultivation in colonies to maintain growth and pluripotency. Robust differentiation protocols necessitate single cell cultures that are achieved by use of ROCK (Rho kinase) inhibitors. ROCK inhibition enables maintenance of stem cell phenotype; its effects on metabolism are unknown. hPSCs were exposed to 10 μM ROCK inhibitor for varying exposure times. Pluripotency (TRA-1-81, SSEA3, OCT4, NANOG, SOX2) remained unaffected, until after prolonged exposure (96 hrs). Gas chromatography-mass spectrometry metabolomics analysis identified differences between ROCK-treated and untreated cells as early as 12 hrs. Exposure for 48 hours resulted in reduction in glycolysis, glutaminolysis, the citric acid (TCA) cycle as well as the amino acids pools, suggesting the adaptation of the cells to the new culture conditions, which was also reflected by the expression of the metabolic regulators, mTORC1 and tp53 and correlated with cellular proliferation status. While gene expression and protein levels did not reveal any changes in the physiology of the cells, metabolomics revealed the fluctuating state of the metabolism. The above highlight the usefulness of metabolomics in providing accurate and sensitive information on cellular physiological status, which could lead to the development of robust and optimal stem cell bioprocesses.

Robustness analysis of non-ordinary Petri nets for flexible assembly systems

NASA Astrophysics Data System (ADS)

Hsieh, Fu-Shiung

2010-05-01

Non-ordinary controlled Petri nets (NCPNs) have the advantages to model flexible assembly systems in which multiple identical resources may be required to perform an operation. However, existing studies on NCPNs are still limited. For example, the robustness properties of NCPNs have not been studied. This motivates us to develop an analysis method for NCPNs. Robustness analysis concerns the ability for a system to maintain operation in the presence of uncertainties. It provides an alternative way to analyse a perturbed system without reanalysis. In our previous research, we have analysed the robustness properties of several subclasses of ordinary controlled Petri nets. To study the robustness properties of NCPNs, we augment NCPNs with an uncertainty model, which specifies an upper bound on the uncertainties for each reachable marking. The resulting PN models are called non-ordinary controlled Petri nets with uncertainties (NCPNU). Based on NCPNU, the problem is to characterise the maximal tolerable uncertainties for each reachable marking. The computational complexities to characterise maximal tolerable uncertainties for each reachable marking grow exponentially with the size of the nets. Instead of considering general NCPNU, we limit our scope to a subclass of PN models called non-ordinary controlled flexible assembly Petri net with uncertainties (NCFAPNU) for assembly systems and study its robustness. We will extend the robustness analysis to NCFAPNU. We identify two types of uncertainties under which the liveness of NCFAPNU can be maintained.

Automated image analysis reveals the dynamic 3-dimensional organization of multi-ciliary arrays

PubMed Central

Galati, Domenico F.; Abuin, David S.; Tauber, Gabriel A.; Pham, Andrew T.; Pearson, Chad G.

2016-01-01

ABSTRACT Multi-ciliated cells (MCCs) use polarized fields of undulating cilia (ciliary array) to produce fluid flow that is essential for many biological processes. Cilia are positioned by microtubule scaffolds called basal bodies (BBs) that are arranged within a spatially complex 3-dimensional geometry (3D). Here, we develop a robust and automated computational image analysis routine to quantify 3D BB organization in the ciliate, Tetrahymena thermophila. Using this routine, we generate the first morphologically constrained 3D reconstructions of Tetrahymena cells and elucidate rules that govern the kinetics of MCC organization. We demonstrate the interplay between BB duplication and cell size expansion through the cell cycle. In mutant cells, we identify a potential BB surveillance mechanism that balances large gaps in BB spacing by increasing the frequency of closely spaced BBs in other regions of the cell. Finally, by taking advantage of a mutant predisposed to BB disorganization, we locate the spatial domains that are most prone to disorganization by environmental stimuli. Collectively, our analyses reveal the importance of quantitative image analysis to understand the principles that guide the 3D organization of MCCs. PMID:26700722

Intrinsic disruption of white matter microarchitecture in first-episode, drug-naive major depressive disorder: A voxel-based meta-analysis of diffusion tensor imaging.

PubMed

Chen, Guangxiang; Guo, Yi; Zhu, Hongyan; Kuang, Weihong; Bi, Feng; Ai, Hua; Gu, Zhongwei; Huang, Xiaoqi; Lui, Su; Gong, Qiyong

2017-06-02

Previous studies have demonstrated the influences of episodes and antidepressant drugs on white matter (WM) in patients with major depressive disorder (MDD). However, most diffusion tensor imaging (DTI) studies included highly heterogeneous individuals with different numbers of depressive episodes or medication status. To exclude the confounding effects of multiple episodes or medication, we conducted a quantitative voxel-based meta-analysis of fractional anisotropy (FA) in patients with first-episode, drug-naive MDD to identify the intrinsic WM alterations involved in the pathogenesis of MDD. The pooled meta-analysis revealed significant FA reductions in the body of the corpus callosum (CC), bilateral anterior limb of the internal capsule (ALIC), right inferior temporal gyrus (ITG) and right superior frontal gyrus (SFG) in MDD patients relative to healthy controls. Meta-regression analyses revealed that FA reduction in the right ALIC and right SFG was negatively correlated with symptom severity and duration of depression, respectively. Our findings provide robust evidence that the WM impairments in the interhemispheric connections and frontal-subcortical neuronal circuits may play an important role in MDD pathogenesis. Copyright © 2017. Published by Elsevier Inc.

GPS baseline configuration design based on robustness analysis

NASA Astrophysics Data System (ADS)

Yetkin, M.; Berber, M.

2012-11-01

The robustness analysis results obtained from a Global Positioning System (GPS) network are dramatically influenced by the configurationof the observed baselines. The selection of optimal GPS baselines may allow for a cost effective survey campaign and a sufficiently robustnetwork. Furthermore, using the approach described in this paper, the required number of sessions, the baselines to be observed, and thesignificance levels for statistical testing and robustness analysis can be determined even before the GPS campaign starts. In this study, wepropose a robustness criterion for the optimal design of geodetic networks, and present a very simple and efficient algorithm based on thiscriterion for the selection of optimal GPS baselines. We also show the relationship between the number of sessions and the non-centralityparameter. Finally, a numerical example is given to verify the efficacy of the proposed approach.

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

NASA Astrophysics Data System (ADS)

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.

Aerodynamic robustness in owl-inspired leading-edge serrations: a computational wind-gust model.

PubMed

Rao, Chen; Liu, Hao

2018-06-08

Owls are a master to achieve silent flight in gliding and flapping flights under natural turbulent environments owing to their unique wing morphologies. While the leading-edge serrations are recently revealed, as a passive flow control micro-device, to play a crucial role in aerodynamic force production and sound suppression [25], the characteristics of wind-gust rejection associated with leading-edge serrations remain unclear. Here we address a large-eddy simulation (LES)-based study of aerodynamic robustness in owl-inspired leading-edge serrations, which is conducted with clean and serrated wing models through mimicking wind-gusts under a longitudinal fluctuation in free-stream inflow and a lateral fluctuation in pitch angle over a broad range of angles of attack (AoAs) over 0° ≤ Φ ≤ 20°. Our results show that the leading-edge serration-based passive flow control mechanisms associated with laminar-turbulent transition work effectively under fluctuated inflow and wing pitch, indicating that the leading-edge serrations are of potential gust fluctuation rejection or robustness in aerodynamic performance. Moreover, it is revealed that the tradeoff between turbulent flow control (i.e., aero-acoustic suppression) and force production in the serrated model holds independently to the wind-gust environments: poor at lower AoAs but capable of achieving equivalent aerodynamic performance at higher AoAs > 15o compared to the clean model. Our results reveal that the owl-inspired leading-edge serrations can be a robust micro-device for aero-acoustic control coping with unsteady and complex wind environments in biomimetic rotor designs for various fluid machineries. © 2018 IOP Publishing Ltd.

GWAR: robust analysis and meta-analysis of genome-wide association studies.

PubMed

Dimou, Niki L; Tsirigos, Konstantinos D; Elofsson, Arne; Bagos, Pantelis G

2017-05-15

In the context of genome-wide association studies (GWAS), there is a variety of statistical techniques in order to conduct the analysis, but, in most cases, the underlying genetic model is usually unknown. Under these circumstances, the classical Cochran-Armitage trend test (CATT) is suboptimal. Robust procedures that maximize the power and preserve the nominal type I error rate are preferable. Moreover, performing a meta-analysis using robust procedures is of great interest and has never been addressed in the past. The primary goal of this work is to implement several robust methods for analysis and meta-analysis in the statistical package Stata and subsequently to make the software available to the scientific community. The CATT under a recessive, additive and dominant model of inheritance as well as robust methods based on the Maximum Efficiency Robust Test statistic, the MAX statistic and the MIN2 were implemented in Stata. Concerning MAX and MIN2, we calculated their asymptotic null distributions relying on numerical integration resulting in a great gain in computational time without losing accuracy. All the aforementioned approaches were employed in a fixed or a random effects meta-analysis setting using summary data with weights equal to the reciprocal of the combined cases and controls. Overall, this is the first complete effort to implement procedures for analysis and meta-analysis in GWAS using Stata. A Stata program and a web-server are freely available for academic users at http://www.compgen.org/tools/GWAR. pbagos@compgen.org. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Dietary specializations and diversity in feeding ecology of the earliest stem mammals.

PubMed

Gill, Pamela G; Purnell, Mark A; Crumpton, Nick; Brown, Kate Robson; Gostling, Neil J; Stampanoni, M; Rayfield, Emily J

2014-08-21

The origin and radiation of mammals are key events in the history of life, with fossils placing the origin at 220 million years ago, in the Late Triassic period. The earliest mammals, representing the first 50 million years of their evolution and including the most basal taxa, are widely considered to be generalized insectivores. This implies that the first phase of the mammalian radiation--associated with the appearance in the fossil record of important innovations such as heterodont dentition, diphyodonty and the dentary-squamosal jaw joint--was decoupled from ecomorphological diversification. Finds of exceptionally complete specimens of later Mesozoic mammals have revealed greater ecomorphological diversity than previously suspected, including adaptations for swimming, burrowing, digging and even gliding, but such well-preserved fossils of earlier mammals do not exist, and robust analysis of their ecomorphological diversity has previously been lacking. Here we present the results of an integrated analysis, using synchrotron X-ray tomography and analyses of biomechanics, finite element models and tooth microwear textures. We find significant differences in function and dietary ecology between two of the earliest mammaliaform taxa, Morganucodon and Kuehneotherium--taxa that are central to the debate on mammalian evolution. Morganucodon possessed comparatively more forceful and robust jaws and consumed 'harder' prey, comparable to extant small-bodied mammals that eat considerable amounts of coleopterans. Kuehneotherium ingested a diet comparable to extant mixed feeders and specialists on 'soft' prey such as lepidopterans. Our results reveal previously hidden trophic specialization at the base of the mammalian radiation; hence even the earliest mammaliaforms were beginning to diversify--morphologically, functionally and ecologically. In contrast to the prevailing view, this pattern suggests that lineage splitting during the earliest stages of mammalian evolution was associated with ecomorphological specialization and niche partitioning.

Three-dimensional imaging of aquifer and aquitard heterogeneity via transient hydraulic tomography at a highly heterogeneous field site

NASA Astrophysics Data System (ADS)

Zhao, Zhanfeng; Illman, Walter A.

2018-04-01

Previous studies have shown that geostatistics-based transient hydraulic tomography (THT) is robust for subsurface heterogeneity characterization through the joint inverse modeling of multiple pumping tests. However, the hydraulic conductivity (K) and specific storage (Ss) estimates can be smooth or even erroneous for areas where pumping/observation densities are low. This renders the imaging of interlayer and intralayer heterogeneity of highly contrasting materials including their unit boundaries difficult. In this study, we further test the performance of THT by utilizing existing and newly collected pumping test data of longer durations that showed drawdown responses in both aquifer and aquitard units at a field site underlain by a highly heterogeneous glaciofluvial deposit. The robust performance of the THT is highlighted through the comparison of different degrees of model parameterization including: (1) the effective parameter approach; (2) the geological zonation approach relying on borehole logs; and (3) the geostatistical inversion approach considering different prior information (with/without geological data). Results reveal that the simultaneous analysis of eight pumping tests with the geostatistical inverse model yields the best results in terms of model calibration and validation. We also find that the joint interpretation of long-term drawdown data from aquifer and aquitard units is necessary in mapping their full heterogeneous patterns including intralayer variabilities. Moreover, as geological data are included as prior information in the geostatistics-based THT analysis, the estimated K values increasingly reflect the vertical distribution patterns of permeameter-estimated K in both aquifer and aquitard units. Finally, the comparison of various THT approaches reveals that differences in the estimated K and Ss tomograms result in significantly different transient drawdown predictions at observation ports.

Time-Frequency Analysis of Chemosensory Event-Related Potentials to Characterize the Cortical Representation of Odors in Humans

PubMed Central

Huart, Caroline; Legrain, Valéry; Hummel, Thomas; Rombaux, Philippe; Mouraux, André

2012-01-01

Background The recording of olfactory and trigeminal chemosensory event-related potentials (ERPs) has been proposed as an objective and non-invasive technique to study the cortical processing of odors in humans. Until now, the responses have been characterized mainly using across-trial averaging in the time domain. Unfortunately, chemosensory ERPs, in particular, olfactory ERPs, exhibit a relatively low signal-to-noise ratio. Hence, although the technique is increasingly used in basic research as well as in clinical practice to evaluate people suffering from olfactory disorders, its current clinical relevance remains very limited. Here, we used a time-frequency analysis based on the wavelet transform to reveal EEG responses that are not strictly phase-locked to onset of the chemosensory stimulus. We hypothesized that this approach would significantly enhance the signal-to-noise ratio of the EEG responses to chemosensory stimulation because, as compared to conventional time-domain averaging, (1) it is less sensitive to temporal jitter and (2) it can reveal non phase-locked EEG responses such as event-related synchronization and desynchronization. Methodology/Principal Findings EEG responses to selective trigeminal and olfactory stimulation were recorded in 11 normosmic subjects. A Morlet wavelet was used to characterize the elicited responses in the time-frequency domain. We found that this approach markedly improved the signal-to-noise ratio of the obtained EEG responses, in particular, following olfactory stimulation. Furthermore, the approach allowed characterizing non phase-locked components that could not be identified using conventional time-domain averaging. Conclusion/Significance By providing a more robust and complete view of how odors are represented in the human brain, our approach could constitute the basis for a robust tool to study olfaction, both for basic research and clinicians. PMID:22427997

Comparative Analysis of Mouse-Induced Pluripotent Stem Cells and Mesenchymal Stem Cells During Osteogenic Differentiation In Vitro

PubMed Central

Kayashima, Hiroki; Miura, Jiro; Uraguchi, Shinya; Wang, Fangfang; Okawa, Hiroko; Sasaki, Jun-Ichi; Saeki, Makio; Matsumoto, Takuya; Yatani, Hirofumi

2014-01-01

Induced pluripotent stem cells (iPSCs) can differentiate into mineralizing cells and are, therefore, expected to be useful for bone regenerative medicine; however, the characteristics of iPSC-derived osteogenic cells remain unclear. Here, we provide a direct in vitro comparison of the osteogenic differentiation process in mesenchymal stem cells (MSCs) and iPSCs from adult C57BL/6J mice. After 30 days of culture in osteogenic medium, both MSCs and iPSCs produced robustly mineralized bone nodules that contained abundant calcium phosphate with hydroxyapatite crystal formation. Mineral deposition was significantly higher in iPSC cultures than in MSC cultures. Scanning electron microscopy revealed budding matrix vesicles in early osteogenic iPSCs; subsequently, the vesicles propagated to exhibit robust mineralization without rich fibrous structures. Early osteogenic MSCs showed deposition of many matrix vesicles in abundant collagen fibrils that became solid mineralized structures. Both cell types demonstrated increased expression of osteogenic marker genes, such as runx2, osterix, dlx5, bone sialoprotein (BSP), and osteocalcin, during osteogenesis; however, real-time reverse transcription–polymerase chain reaction array analysis revealed that osteogenesis-related genes encoding mineralization-associated molecules, bone morphogenetic proteins, and extracellular matrix collagens were differentially expressed between iPSCs and MSCs. These data suggest that iPSCs are capable of differentiation into mature osteoblasts whose associated hydroxyapatite has a crystal structure similar to that of MSC-associated hydroxyapatite; however, the transcriptional differences between iPSCs and MSCs could result in differences in the mineral and matrix environments of the bone nodules. Determining the biological mechanisms underlying cell-specific differences in mineralization during in vitro iPSC osteogenesis may facilitate the development of clinically effective engineered bone. PMID:24625139

Novel relationships among ten fish model species revealed based on a phylogenomic analysis using ESTs.

PubMed

Steinke, Dirk; Salzburger, Walter; Meyer, Axel

2006-06-01

The power of comparative phylogenomic analyses also depends on the amount of data that are included in such studies. We used expressed sequence tags (ESTs) from fish model species as a proof of principle approach in order to test the reliability of using ESTs for phylogenetic inference. As expected, the robustness increases with the amount of sequences. Although some progress has been made in the elucidation of the phylogeny of teleosts, relationships among the main lineages of the derived fish (Euteleostei) remain poorly defined and are still debated. We performed a phylogenomic analysis of a set of 42 of orthologous genes from 10 available fish model systems from seven different orders (Salmoniformes, Siluriformes, Cypriniformes, Tetraodontiformes, Cyprinodontiformes, Beloniformes, and Perciformes) of euteleostean fish to estimate divergence times and evolutionary relationships among those lineages. All 10 fish species serve as models for developmental, aquaculture, genomic, and comparative genetic studies. The phylogenetic signal and the strength of the contribution of each of the 42 orthologous genes were estimated with randomly chosen data subsets. Our study revealed a molecular phylogeny of higher-level relationships of derived teleosts, which indicates that the use of multiple genes produces robust phylogenies, a finding that is expected to apply to other phylogenetic issues among distantly related taxa. Our phylogenomic analyses confirm that the euteleostean superorders Ostariophysi and Acanthopterygii are monophyletic and the Protacanthopterygii and Ostariophysi are sister clades. In addition, and contrary to the traditional phylogenetic hypothesis, our analyses determine that killifish (Cyprinodontiformes), medaka (Beloniformes), and cichlids (Perciformes) appear to be more closely related to each other than either of them is to pufferfish (Tetraodontiformes). All 10 lineages split before or during the fragmentation of the supercontinent Pangea in the Jurassic.

Robust Classification of Small-Molecule Mechanism of Action Using a Minimalist High-Content Microscopy Screen and Multidimensional Phenotypic Trajectory Analysis

PubMed Central

Twarog, Nathaniel R.; Low, Jonathan A.; Currier, Duane G.; Miller, Greg; Chen, Taosheng; Shelat, Anang A.

2016-01-01

Phenotypic screening through high-content automated microscopy is a powerful tool for evaluating the mechanism of action of candidate therapeutics. Despite more than a decade of development, however, high content assays have yielded mixed results, identifying robust phenotypes in only a small subset of compound classes. This has led to a combinatorial explosion of assay techniques, analyzing cellular phenotypes across dozens of assays with hundreds of measurements. Here, using a minimalist three-stain assay and only 23 basic cellular measurements, we developed an analytical approach that leverages informative dimensions extracted by linear discriminant analysis to evaluate similarity between the phenotypic trajectories of different compounds in response to a range of doses. This method enabled us to visualize biologically-interpretable phenotypic tracks populated by compounds of similar mechanism of action, cluster compounds according to phenotypic similarity, and classify novel compounds by comparing them to phenotypically active exemplars. Hierarchical clustering applied to 154 compounds from over a dozen different mechanistic classes demonstrated tight agreement with published compound mechanism classification. Using 11 phenotypically active mechanism classes, classification was performed on all 154 compounds: 78% were correctly identified as belonging to one of the 11 exemplar classes or to a different unspecified class, with accuracy increasing to 89% when less phenotypically active compounds were excluded. Importantly, several apparent clustering and classification failures, including rigosertib and 5-fluoro-2’-deoxycytidine, instead revealed more complex mechanisms or off-target effects verified by more recent publications. These results show that a simple, easily replicated, minimalist high-content assay can reveal subtle variations in the cellular phenotype induced by compounds and can correctly predict mechanism of action, as long as the appropriate analytical tools are used. PMID:26886014

Robust Classification of Small-Molecule Mechanism of Action Using a Minimalist High-Content Microscopy Screen and Multidimensional Phenotypic Trajectory Analysis.

PubMed

Twarog, Nathaniel R; Low, Jonathan A; Currier, Duane G; Miller, Greg; Chen, Taosheng; Shelat, Anang A

2016-01-01

Phenotypic screening through high-content automated microscopy is a powerful tool for evaluating the mechanism of action of candidate therapeutics. Despite more than a decade of development, however, high content assays have yielded mixed results, identifying robust phenotypes in only a small subset of compound classes. This has led to a combinatorial explosion of assay techniques, analyzing cellular phenotypes across dozens of assays with hundreds of measurements. Here, using a minimalist three-stain assay and only 23 basic cellular measurements, we developed an analytical approach that leverages informative dimensions extracted by linear discriminant analysis to evaluate similarity between the phenotypic trajectories of different compounds in response to a range of doses. This method enabled us to visualize biologically-interpretable phenotypic tracks populated by compounds of similar mechanism of action, cluster compounds according to phenotypic similarity, and classify novel compounds by comparing them to phenotypically active exemplars. Hierarchical clustering applied to 154 compounds from over a dozen different mechanistic classes demonstrated tight agreement with published compound mechanism classification. Using 11 phenotypically active mechanism classes, classification was performed on all 154 compounds: 78% were correctly identified as belonging to one of the 11 exemplar classes or to a different unspecified class, with accuracy increasing to 89% when less phenotypically active compounds were excluded. Importantly, several apparent clustering and classification failures, including rigosertib and 5-fluoro-2'-deoxycytidine, instead revealed more complex mechanisms or off-target effects verified by more recent publications. These results show that a simple, easily replicated, minimalist high-content assay can reveal subtle variations in the cellular phenotype induced by compounds and can correctly predict mechanism of action, as long as the appropriate analytical tools are used.

An Intercompany Perspective on Biopharmaceutical Drug Product Robustness Studies.

PubMed

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 Control Systems.

DTIC Science & Technology

1981-12-01

time control system algorithms that will perform adequately (i.e., at least maintain closed-loop system stability) when ucertain parameters in the...system design models vary significantly. Such a control algorithm is said to have stability robustness-or more simply is said to be "robust". This...cas6s above, the performance is analyzed using a covariance analysis. The development of all the controllers and the performance analysis algorithms is

Leuconostoc strains isolated from dairy products: Response against food stress conditions.

PubMed

D'Angelo, Luisa; Cicotello, Joaquín; Zago, Miriam; Guglielmotti, Daniela; Quiberoni, Andrea; Suárez, Viviana

2017-09-01

A systematic study about the intrinsic resistance of 29 strains (26 autochthonous and 3 commercial ones), belonging to Leuconostoc genus, against diverse stress factors (thermal, acidic, alkaline, osmotic and oxidative) commonly present at industrial or conservation processes were evaluated. Exhaustive result processing was made by applying one-way ANOVA, Student's test (t), multivariate analysis by Principal Component Analysis (PCA) and Matrix Hierarchical Cluster Analysis. In addition, heat adaptation on 4 strains carefully selected based on previous data analysis was assayed. The strains revealed wide diversity of resistance to stress factors and, in general, a clear relationship between resistance and Leuconostoc species was established. In this sense, the highest resistance was shown by Leuconostoc lactis followed by Leuconostoc mesenteroides strains, while Leuconostoc pseudomesenteroides and Leuconostoc citreum strains revealed the lowest resistance to the stress factors applied. Heat adaptation improved thermal cell survival and resulted in a cross-resistance against the acidic factor. However, all adapted cells showed diminished their oxidative resistance. According to our knowledge, this is the first study regarding response of Leuconostoc strains against technological stress factors and could establish the basis for the selection of "more robust" strains and propose the possibility of improving their performance during industrial processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mycobacterial RNA isolation optimized for non-coding RNA: high fidelity isolation of 5S rRNA from Mycobacterium bovis BCG reveals novel post-transcriptional processing and a complete spectrum of modified ribonucleosides.

PubMed

Hia, Fabian; Chionh, Yok Hian; Pang, Yan Ling Joy; DeMott, Michael S; McBee, Megan E; Dedon, Peter C

2015-03-11

A major challenge in the study of mycobacterial RNA biology is the lack of a comprehensive RNA isolation method that overcomes the unusual cell wall to faithfully yield the full spectrum of non-coding RNA (ncRNA) species. Here, we describe a simple and robust procedure optimized for the isolation of total ncRNA, including 5S, 16S and 23S ribosomal RNA (rRNA) and tRNA, from mycobacteria, using Mycobacterium bovis BCG to illustrate the method. Based on a combination of mechanical disruption and liquid and solid-phase technologies, the method produces all major species of ncRNA in high yield and with high integrity, enabling direct chemical and sequence analysis of the ncRNA species. The reproducibility of the method with BCG was evident in bioanalyzer electrophoretic analysis of isolated RNA, which revealed quantitatively significant differences in the ncRNA profiles of exponentially growing and non-replicating hypoxic bacilli. The method also overcame an historical inconsistency in 5S rRNA isolation, with direct sequencing revealing a novel post-transcriptional processing of 5S rRNA to its functional form and with chemical analysis revealing seven post-transcriptional ribonucleoside modifications in the 5S rRNA. This optimized RNA isolation procedure thus provides a means to more rigorously explore the biology of ncRNA species in mycobacteria. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Integration of uniform design and quantum-behaved particle swarm optimization to the robust design for a railway vehicle suspension system under different wheel conicities and wheel rolling radii

NASA Astrophysics Data System (ADS)

Cheng, Yung-Chang; Lee, Cheng-Kang

2017-10-01

This paper proposes a systematic method, integrating the uniform design (UD) of experiments and quantum-behaved particle swarm optimization (QPSO), to solve the problem of a robust design for a railway vehicle suspension system. Based on the new nonlinear creep model derived from combining Hertz contact theory, Kalker's linear theory and a heuristic nonlinear creep model, the modeling and dynamic analysis of a 24 degree-of-freedom railway vehicle system were investigated. The Lyapunov indirect method was used to examine the effects of suspension parameters, wheel conicities and wheel rolling radii on critical hunting speeds. Generally, the critical hunting speeds of a vehicle system resulting from worn wheels with different wheel rolling radii are lower than those of a vehicle system having original wheels without different wheel rolling radii. Because of worn wheels, the critical hunting speed of a running railway vehicle substantially declines over the long term. For safety reasons, it is necessary to design the suspension system parameters to increase the robustness of the system and decrease the sensitive of wheel noises. By applying UD and QPSO, the nominal-the-best signal-to-noise ratio of the system was increased from -48.17 to -34.05 dB. The rate of improvement was 29.31%. This study has demonstrated that the integration of UD and QPSO can successfully reveal the optimal solution of suspension parameters for solving the robust design problem of a railway vehicle suspension system.

Robust Flutter Margin Analysis that Incorporates Flight Data

NASA Technical Reports Server (NTRS)

Lind, Rick; Brenner, Martin J.

1998-01-01

An approach for computing worst-case flutter margins has been formulated in a robust stability framework. Uncertainty operators are included with a linear model to describe modeling errors and flight variations. The structured singular value, mu, computes a stability margin that directly accounts for these uncertainties. This approach introduces a new method of computing flutter margins and an associated new parameter for describing these margins. The mu margins are robust margins that indicate worst-case stability estimates with respect to the defined uncertainty. Worst-case flutter margins are computed for the F/A-18 Systems Research Aircraft using uncertainty sets generated by flight data analysis. The robust margins demonstrate flight conditions for flutter may lie closer to the flight envelope than previously estimated by p-k analysis.

Sensitive luminescent reporter viruses reveal appreciable release of hepatitis C virus NS5A protein into the extracellular environment.

PubMed

Eyre, Nicholas S; Aloia, Amanda L; Joyce, Michael A; Chulanetra, Monrat; Tyrrell, D Lorne; Beard, Michael R

2017-07-01

The HCV NS5A protein is essential for viral RNA replication and virus particle assembly. To study the viral replication cycle and NS5A biology we generated an infectious HCV construct with a NanoLuciferase (NLuc) insertion within NS5A. Surprisingly, beyond its utility as a sensitive reporter of cytoplasmic viral RNA replication, we also observed strong luminescence in cell culture fluids. Further analysis using assembly-defective viruses and subgenomic replicons revealed that infectious virus production was not required for extracellular NS5A-NLuc activity but was associated with enrichment of extracellular NS5A-NLuc in intermediate-density fractions similar to those of exosomes and virus particles. Additionally, BRET analysis indicated that intracellular and extracellular forms of NS5A may adopt differing conformations. Importantly, infection studies using a human liver chimeric mouse model confirmed robust infection in vivo and ready detection of NLuc activity in serum. We hypothesise that the presence of NS5A in extracellular fluids contributes to HCV pathogenesis. Copyright © 2017 Elsevier Inc. All rights reserved.

Mapping probabilities of extreme continental water storage changes from space gravimetry

NASA Astrophysics Data System (ADS)

Kusche, J.; Eicker, A.; Forootan, E.; Springer, A.; Longuevergne, L.

2016-12-01

Using data from the Gravity Recovery and Climate Experiment (GRACE) mission, we derive statistically robust 'hotspot' regions of high probability of peak anomalous - i.e. with respect to the seasonal cycle - water storage (of up to 0.7 m one-in-five-year return level) and flux (up to 0.14 m/mon). Analysis of, and comparison with, up to 32 years of ERA-Interim reanalysis fields reveals generally good agreement of these hotspot regions to GRACE results, and that most exceptions are located in the Tropics. However, a simulation experiment reveals that differences observed by GRACE are statistically significant, and further error analysis suggests that by around the year 2020 it will be possible to detect temporal changes in the frequency of extreme total fluxes (i.e. combined effects of mainly precipitation and floods) for at least 10-20% of the continental area, assuming that we have a continuation of GRACE by its follow-up GRACE-FO. J. Kusche et al. (2016): Mapping probabilities of extreme continental water storage changes from space gravimetry, Geophysical Research Letters, accepted online, doi:10.1002/2016GL069538

T1, diffusion tensor, and quantitative magnetization transfer imaging of the hippocampus in an Alzheimer's disease mouse model.

PubMed

Whittaker, Heather T; Zhu, Shenghua; Di Curzio, Domenico L; Buist, Richard; Li, Xin-Min; Noy, Suzanna; Wiseman, Frances K; Thiessen, Jonathan D; Martin, Melanie

2018-07-01

Alzheimer's disease (AD) pathology causes microstructural changes in the brain. These changes, if quantified with magnetic resonance imaging (MRI), could be studied for use as an early biomarker for AD. The aim of our study was to determine if T 1 relaxation, diffusion tensor imaging (DTI), and quantitative magnetization transfer imaging (qMTI) metrics could reveal changes within the hippocampus and surrounding white matter structures in ex vivo transgenic mouse brains overexpressing human amyloid precursor protein with the Swedish mutation. Delineation of hippocampal cell layers using DTI color maps allows more detailed analysis of T 1 -weighted imaging, DTI, and qMTI metrics, compared with segmentation of gross anatomy based on relaxation images, and with analysis of DTI or qMTI metrics alone. These alterations are observed in the absence of robust intracellular Aβ accumulation or plaque deposition as revealed by histology. This work demonstrates that multiparametric quantitative MRI methods are useful for characterizing changes within the hippocampal substructures and surrounding white matter tracts of mouse models of AD. Copyright © 2018. Published by Elsevier Inc.

Multifractal detrended fluctuation analysis to characterize phase couplings in seahorse (Hippocampus kuda) feeding clicks.

PubMed

Haris, K; Chakraborty, Bishwajit; Menezes, A; Sreepada, R A; Fernandes, W A

2014-10-01

Nonlinear phenomena in animal vocalizations fundamentally includes known features, namely, frequency jump, subharmonics, biphonation, and deterministic chaos. In the present study, the multifractal detrended fluctuation analysis (MFDFA) has been employed to characterize the phase couplings revealed in the feeding clicks of Hippocampus kuda yellow seahorse. The fluctuation function Fq(s), generalized Hurst exponent h(q), multifractal scaling exponent τ(q), and the multifractal spectrum f(α) calculated in the procedure followed were analyzed to comprehend the underlying nonlinearities in the seahorse clicks. The analyses carried out reveal long-range power-law correlation properties in the data, substantiating the multifractal behavior. The resulting h(q) spectrum exhibits a distinct characteristic pattern in relation to the seahorse sex and size, and reveals a spectral blind spot in the data that was not possible to detect by conventional spectral analyses. The corresponding multifractal spectrum related width parameter Δh(q) is well clustered, defining the individual seahorse clicks. The highest degree of multifractality is evident in the 18 cm male seahorse, signifying greater heterogeneity. A further comparison between the seahorse body size and weight (wet) with respect to the width parameter Δh(q) and the second-order Hurst exponent h(q=2) underscores the versatility of MFDFA as a robust statistical tool to analyze bioacoustic observations.

The Neurobiological Grounding of Persistent Stuttering: from Structure to Function.

PubMed

Neef, Nicole E; Anwander, Alfred; Friederici, Angela D

2015-09-01

Neuroimaging and transcranial magnetic stimulation provide insights into the neuronal mechanisms underlying speech disfluencies in chronic persistent stuttering. In the present paper, the goal is not to provide an exhaustive review of existing literature, but rather to highlight robust findings. We, therefore, conducted a meta-analysis of diffusion tensor imaging studies which have recently implicated disrupted white matter connectivity in stuttering. A reduction of fractional anisotropy in persistent stuttering has been reported at several different loci. Our meta-analysis revealed consistent deficits in the left dorsal stream and in the interhemispheric connections between the sensorimotor cortices. In addition, recent fMRI meta-analyses link stuttering to reduced left fronto-parieto-temporal activation while greater fluency is associated with boosted co-activations of right fronto-parieto-temporal areas. However, the physiological foundation of these irregularities is not accessible with MRI. Complementary, transcranial magnetic stimulation (TMS) reveals local excitatory and inhibitory regulation of cortical dynamics. Applied to a speech motor area, TMS revealed reduced speech-planning-related neuronal dynamics at the level of the primary motor cortex in stuttering. Together, this review provides a focused view of the neurobiology of stuttering to date and may guide the rational design of future research. This future needs to account for the perpetual dynamic interactions between auditory, somatosensory, and speech motor circuits that shape fluent speech.

Optimization and quality control of genome-wide Hi-C library preparation.

PubMed

Zhang, Xiang-Yuan; He, Chao; Ye, Bing-Yu; Xie, De-Jian; Shi, Ming-Lei; Zhang, Yan; Shen, Wen-Long; Li, Ping; Zhao, Zhi-Hu

2017-09-20

Highest-throughput chromosome conformation capture (Hi-C) is one of the key assays for genome- wide chromatin interaction studies. It is a time-consuming process that involves many steps and many different kinds of reagents, consumables, and equipments. At present, the reproducibility is unsatisfactory. By optimizing the key steps of the Hi-C experiment, such as crosslinking, pretreatment of digestion, inactivation of restriction enzyme, and in situ ligation etc., we established a robust Hi-C procedure and prepared two biological replicates of Hi-C libraries from the GM12878 cells. After preliminary quality control by Sanger sequencing, the two replicates were high-throughput sequenced. The bioinformatics analysis of the raw sequencing data revealed the mapping-ability and pair-mate rate of the raw data were around 90% and 72%, respectively. Additionally, after removal of self-circular ligations and dangling-end products, more than 96% of the valid pairs were reached. Genome-wide interactome profiling shows clear topological associated domains (TADs), which is consistent with previous reports. Further correlation analysis showed that the two biological replicates strongly correlate with each other in terms of both bin coverage and all bin pairs. All these results indicated that the optimized Hi-C procedure is robust and stable, which will be very helpful for the wide applications of the Hi-C assay.

A low cost mobile phone dark-field microscope for nanoparticle-based quantitative studies.

PubMed

Sun, Dali; Hu, Tony Y

2018-01-15

Dark-field microscope (DFM) analysis of nanoparticle binding signal is highly useful for a variety of research and biomedical applications, but current applications for nanoparticle quantification rely on expensive DFM systems. The cost, size, limited robustness of these DFMs limits their utility for non-laboratory settings. Most nanoparticle analyses use high-magnification DFM images, which are labor intensive to acquire and subject to operator bias. Low-magnification DFM image capture is faster, but is subject to background from surface artifacts and debris, although image processing can partially compensate for background signal. We thus mated an LED light source, a dark-field condenser and a 20× objective lens with a mobile phone camera to create an inexpensive, portable and robust DFM system suitable for use in non-laboratory conditions. This proof-of-concept mobile DFM device weighs less than 400g and costs less than $2000, but analysis of images captured with this device reveal similar nanoparticle quantitation results to those acquired with a much larger and more expensive desktop DFMM system. Our results suggest that similar devices may be useful for quantification of stable, nanoparticle-based activity and quantitation assays in resource-limited areas where conventional assay approaches are not practical. Copyright © 2017 Elsevier B.V. All rights reserved.

Model reference tracking control of an aircraft: a robust adaptive approach

NASA Astrophysics Data System (ADS)

Tanyer, Ilker; Tatlicioglu, Enver; Zergeroglu, Erkan

2017-05-01

This work presents the design and the corresponding analysis of a nonlinear robust adaptive controller for model reference tracking of an aircraft that has parametric uncertainties in its system matrices and additive state- and/or time-dependent nonlinear disturbance-like terms in its dynamics. Specifically, robust integral of the sign of the error feedback term and an adaptive term is fused with a proportional integral controller. Lyapunov-based stability analysis techniques are utilised to prove global asymptotic convergence of the output tracking error. Extensive numerical simulations are presented to illustrate the performance of the proposed robust adaptive controller.

Robust-mode analysis of hydrodynamic flows

NASA Astrophysics Data System (ADS)

Roy, Sukesh; Gord, James R.; Hua, Jia-Chen; Gunaratne, Gemunu H.

2017-04-01

The emergence of techniques to extract high-frequency high-resolution data introduces a new avenue for modal decomposition to assess the underlying dynamics, especially of complex flows. However, this task requires the differentiation of robust, repeatable flow constituents from noise and other irregular features of a flow. Traditional approaches involving low-pass filtering and principle components analysis have shortcomings. The approach outlined here, referred to as robust-mode analysis, is based on Koopman decomposition. Three applications to (a) a counter-rotating cellular flame state, (b) variations in financial markets, and (c) turbulent injector flows are provided.

A versatile pipeline for the multi-scale digital reconstruction and quantitative analysis of 3D tissue architecture

PubMed Central

Morales-Navarrete, Hernán; Segovia-Miranda, Fabián; Klukowski, Piotr; Meyer, Kirstin; Nonaka, Hidenori; Marsico, Giovanni; Chernykh, Mikhail; Kalaidzidis, Alexander; Zerial, Marino; Kalaidzidis, Yannis

2015-01-01

A prerequisite for the systems biology analysis of tissues is an accurate digital three-dimensional reconstruction of tissue structure based on images of markers covering multiple scales. Here, we designed a flexible pipeline for the multi-scale reconstruction and quantitative morphological analysis of tissue architecture from microscopy images. Our pipeline includes newly developed algorithms that address specific challenges of thick dense tissue reconstruction. Our implementation allows for a flexible workflow, scalable to high-throughput analysis and applicable to various mammalian tissues. We applied it to the analysis of liver tissue and extracted quantitative parameters of sinusoids, bile canaliculi and cell shapes, recognizing different liver cell types with high accuracy. Using our platform, we uncovered an unexpected zonation pattern of hepatocytes with different size, nuclei and DNA content, thus revealing new features of liver tissue organization. The pipeline also proved effective to analyse lung and kidney tissue, demonstrating its generality and robustness. DOI: http://dx.doi.org/10.7554/eLife.11214.001 PMID:26673893

HITS-CLIP yields genome-wide insights into brain alternative RNA processing

NASA Astrophysics Data System (ADS)

Licatalosi, Donny D.; Mele, Aldo; Fak, John J.; Ule, Jernej; Kayikci, Melis; Chi, Sung Wook; Clark, Tyson A.; Schweitzer, Anthony C.; Blume, John E.; Wang, Xuning; Darnell, Jennifer C.; Darnell, Robert B.

2008-11-01

Protein-RNA interactions have critical roles in all aspects of gene expression. However, applying biochemical methods to understand such interactions in living tissues has been challenging. Here we develop a genome-wide means of mapping protein-RNA binding sites in vivo, by high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP). HITS-CLIP analysis of the neuron-specific splicing factor Nova revealed extremely reproducible RNA-binding maps in multiple mouse brains. These maps provide genome-wide in vivo biochemical footprints confirming the previous prediction that the position of Nova binding determines the outcome of alternative splicing; moreover, they are sufficiently powerful to predict Nova action de novo. HITS-CLIP revealed a large number of Nova-RNA interactions in 3' untranslated regions, leading to the discovery that Nova regulates alternative polyadenylation in the brain. HITS-CLIP, therefore, provides a robust, unbiased means to identify functional protein-RNA interactions in vivo.

Comprehensive Lipidome-Wide Profiling Reveals Dynamic Changes of Tea Lipids during Manufacturing Process of Black Tea.

PubMed

Li, Jia; Hua, Jinjie; Zhou, Qinghua; Dong, Chunwang; Wang, Jinjin; Deng, Yuliang; Yuan, Haibo; Jiang, Yongwen

2017-11-22

As important biomolecules in Camellia sinensis L., lipids undergo substantial changes during black tea manufacture, which is considered to contribute to tea sensory quality. However, limited by analytical capacity, detailed lipid composition and its dynamic changes during black tea manufacture remain unclear. Herein, we performed tea lipidome profiling using high resolution liquid chromatography coupled to mass spectrometry (LC-MS), which allows simultaneous and robust analysis of 192 individual lipid species in black tea, covering 17 (sub)classes. Furthermore, dynamic changes of tea lipids during black tea manufacture were investigated. Significant alterations of lipid pattern were revealed, involved with chlorophyll degradation, metabolic pathways of glycoglycerolipids, and other extraplastidial membrane lipids. To our knowledge, this report presented most comprehensive coverage of lipid species in black tea. This study provides a global and in-depth metabolic map of tea lipidome during black tea manufacture.

Synergistic adhesion mechanisms of spider capture silk.

PubMed

Guo, Yang; Chang, Zheng; Guo, Hao-Yuan; Fang, Wei; Li, Qunyang; Zhao, Hong-Ping; Feng, Xi-Qiao; Gao, Huajian

2018-03-01

It is well known that capture silk, the main sticky component of the orb web of a spider, plays an important role in the spider's ability to capture prey via adhesion. However, the detailed mechanism with which the spider achieves its unparalleled high-adhesion performance remains elusive. In this work, we combine experiments and theoretical analysis to investigate the adhesion mechanisms of spider silk. In addition to the widely recognized adhesion effect of the sticky glue, we reveal a synergistic enhancement mechanism due to the elasticity of silk fibres. A balance between silk stiffness, strength and glue stickiness is crucial to endow the silk with superior adhesion, as well as outstanding energy absorption capacity and structural robustness. The revealed mechanisms deepen our understanding of the working principles of spider silk and suggest guidelines for biomimetic designs of spider-inspired adhesion and capture devices. © 2018 The Author(s).

Discovery and Characterization of a Thermostable and Highly Halotolerant GH5 Cellulase from an Icelandic Hot Spring Isolate

PubMed Central

Zarafeta, Dimitra; Kissas, Dimitrios; Sayer, Christopher; Gudbergsdottir, Sóley R.; Ladoukakis, Efthymios; Isupov, Michail N.; Chatziioannou, Aristotelis; Peng, Xu; Littlechild, Jennifer A.; Skretas, Georgios; Kolisis, Fragiskos N.

2016-01-01

With the ultimate goal of identifying robust cellulases for industrial biocatalytic conversions, we have isolated and characterized a new thermostable and very halotolerant GH5 cellulase. This new enzyme, termed CelDZ1, was identified by bioinformatic analysis from the genome of a polysaccharide-enrichment culture isolate, initiated from material collected from an Icelandic hot spring. Biochemical characterization of CelDZ1 revealed that it is a glycoside hydrolase with optimal activity at 70°C and pH 5.0 that exhibits good thermostability, high halotolerance at near-saturating salt concentrations, and resistance towards metal ions and other denaturing agents. X-ray crystallography of the new enzyme showed that CelDZ1 is the first reported cellulase structure that lacks the defined sugar-binding 2 subsite and revealed structural features which provide potential explanations of its biochemical characteristics. PMID:26741138

Study on Fuzzy Adaptive Fractional Order PIλDμ Control for Maglev Guiding System

NASA Astrophysics Data System (ADS)

Hu, Qing; Hu, Yuwei

The mathematical model of the linear elevator maglev guiding system is analyzed in this paper. For the linear elevator needs strong stability and robustness to run, the integer order PID was expanded to the fractional order, in order to improve the steady state precision, rapidity and robustness of the system, enhance the accuracy of the parameter in fractional order PIλDμ controller, the fuzzy control is combined with the fractional order PIλDμ control, using the fuzzy logic achieves the parameters online adjustment. The simulations reveal that the system has faster response speed, higher tracking precision, and has stronger robustness to the disturbance.

Transportation Infrastructure Robustness : Joint Engineering and Economic Analysis

DOT National Transportation Integrated Search

2017-11-01

The objectives of this study are to develop a methodology for assessing the robustness of transportation infrastructure facilities and assess the effect of damage to such facilities on travel demand and the facilities users welfare. The robustness...

Enabling Rapid and Robust Structural Analysis During Conceptual Design

NASA Technical Reports Server (NTRS)

Eldred, Lloyd B.; Padula, Sharon L.; Li, Wu

2015-01-01

This paper describes a multi-year effort to add a structural analysis subprocess to a supersonic aircraft conceptual design process. The desired capabilities include parametric geometry, automatic finite element mesh generation, static and aeroelastic analysis, and structural sizing. The paper discusses implementation details of the new subprocess, captures lessons learned, and suggests future improvements. The subprocess quickly compares concepts and robustly handles large changes in wing or fuselage geometry. The subprocess can rank concepts with regard to their structural feasibility and can identify promising regions of the design space. The automated structural analysis subprocess is deemed robust and rapid enough to be included in multidisciplinary conceptual design and optimization studies.

Design of robust flow processing networks with time-programmed responses

NASA Astrophysics Data System (ADS)

Kaluza, P.; Mikhailov, A. S.

2012-04-01

Can artificially designed networks reach the levels of robustness against local damage which are comparable with those of the biochemical networks of a living cell? We consider a simple model where the flow applied to an input node propagates through the network and arrives at different times to the output nodes, thus generating a pattern of coordinated responses. By using evolutionary optimization algorithms, functional networks - with required time-programmed responses - were constructed. Then, continuing the evolution, such networks were additionally optimized for robustness against deletion of individual nodes or links. In this manner, large ensembles of functional networks with different kinds of robustness were obtained, making statistical investigations and comparison of their structural properties possible. We have found that, generally, different architectures are needed for various kinds of robustness. The differences are statistically revealed, for example, in the Laplacian spectra of the respective graphs. On the other hand, motif distributions of robust networks do not differ from those of the merely functional networks; they are found to belong to the first Alon superfamily, the same as that of the gene transcription networks of single-cell organisms.

Constructing Robust Cooperative Networks using a Multi-Objective Evolutionary Algorithm

PubMed Central

Wang, Shuai; Liu, Jing

2017-01-01

The design and construction of network structures oriented towards different applications has attracted much attention recently. The existing studies indicated that structural heterogeneity plays different roles in promoting cooperation and robustness. Compared with rewiring a predefined network, it is more flexible and practical to construct new networks that satisfy the desired properties. Therefore, in this paper, we study a method for constructing robust cooperative networks where the only constraint is that the number of nodes and links is predefined. We model this network construction problem as a multi-objective optimization problem and propose a multi-objective evolutionary algorithm, named MOEA-Netrc, to generate the desired networks from arbitrary initializations. The performance of MOEA-Netrc is validated on several synthetic and real-world networks. The results show that MOEA-Netrc can construct balanced candidates and is insensitive to the initializations. MOEA-Netrc can find the Pareto fronts for networks with different levels of cooperation and robustness. In addition, further investigation of the robustness of the constructed networks revealed the impact on other aspects of robustness during the construction process. PMID:28134314

A Hybrid One-Way ANOVA Approach for the Robust and Efficient Estimation of Differential Gene Expression with Multiple Patterns

PubMed Central

Mollah, Mohammad Manir Hossain; Jamal, Rahman; Mokhtar, Norfilza Mohd; Harun, Roslan; Mollah, Md. Nurul Haque

2015-01-01

Background Identifying genes that are differentially expressed (DE) between two or more conditions with multiple patterns of expression is one of the primary objectives of gene expression data analysis. Several statistical approaches, including one-way analysis of variance (ANOVA), are used to identify DE genes. However, most of these methods provide misleading results for two or more conditions with multiple patterns of expression in the presence of outlying genes. In this paper, an attempt is made to develop a hybrid one-way ANOVA approach that unifies the robustness and efficiency of estimation using the minimum β-divergence method to overcome some problems that arise in the existing robust methods for both small- and large-sample cases with multiple patterns of expression. Results The proposed method relies on a β-weight function, which produces values between 0 and 1. The β-weight function with β = 0.2 is used as a measure of outlier detection. It assigns smaller weights (≥ 0) to outlying expressions and larger weights (≤ 1) to typical expressions. The distribution of the β-weights is used to calculate the cut-off point, which is compared to the observed β-weight of an expression to determine whether that gene expression is an outlier. This weight function plays a key role in unifying the robustness and efficiency of estimation in one-way ANOVA. Conclusion Analyses of simulated gene expression profiles revealed that all eight methods (ANOVA, SAM, LIMMA, EBarrays, eLNN, KW, robust BetaEB and proposed) perform almost identically for m = 2 conditions in the absence of outliers. However, the robust BetaEB method and the proposed method exhibited considerably better performance than the other six methods in the presence of outliers. In this case, the BetaEB method exhibited slightly better performance than the proposed method for the small-sample cases, but the the proposed method exhibited much better performance than the BetaEB method for both the small- and large-sample cases in the presence of more than 50% outlying genes. The proposed method also exhibited better performance than the other methods for m > 2 conditions with multiple patterns of expression, where the BetaEB was not extended for this condition. Therefore, the proposed approach would be more suitable and reliable on average for the identification of DE genes between two or more conditions with multiple patterns of expression. PMID:26413858

Identification of novel and robust internal control genes from Volvariella volvacea that are suitable for RT-qPCR in filamentous fungi.

PubMed

Tao, Yongxin; van Peer, Arend Frans; Huang, Qianhui; Shao, Yanping; Zhang, Lei; Xie, Bin; Jiang, Yuji; Zhu, Jian; Xie, Baogui

2016-07-12

The selection of appropriate internal control genes (ICGs) is a crucial step in the normalization of real-time quantitative PCR (RT-qPCR) data. Housekeeping genes are habitually selected for this purpose, despite accumulating evidence on their instability. We screened for novel, robust ICGs in the mushroom forming fungus Volvariella volvacea. Nine commonly used and five newly selected ICGs were evaluated for expression stability using RT-qPCR data in eight different stages of the life cycle of V. volvacea. Three different algorithms consistently determined that three novel ICGs (SPRYp, Ras and Vps26) exhibited the highest expression stability in V. volvacea. Subsequent analysis of ICGs in twenty-four expression profiles from nine filamentous fungi revealed that Ras was the most stable ICG amongst the Basidiomycetous samples, followed by SPRYp, Vps26 and ACTB. Vps26 was expressed most stably within the analyzed data of Ascomycetes, followed by HH3 and β-TUB. No ICG was universally stable for all fungal species, or for all experimental conditions within a species. Ultimately, the choice of an ICG will depend on a specific set of experiments. This study provides novel, robust ICGs for Basidiomycetes and Ascomycetes. Together with the presented guiding principles, this enables the efficient selection of suitable ICGs for RT-qPCR.

Click-On-Diagram Questions: a New Tool to Study Conceptions Using Classroom Response Systems

NASA Astrophysics Data System (ADS)

LaDue, Nicole D.; Shipley, Thomas F.

2018-06-01

Geoscience instructors depend upon photos, diagrams, and other visualizations to depict geologic structures and processes that occur over a wide range of temporal and spatial scales. This proof-of-concept study tests click-on-diagram (COD) questions, administered using a classroom response system (CRS), as a research tool for identifying spatial misconceptions. First, we propose a categorization of spatial conceptions associated with geoscience concepts. Second, we implemented the COD questions in an undergraduate introductory geology course. Each question was implemented three times: pre-instruction, post-instruction, and at the end of the course to evaluate the stability of students' conceptual understanding. We classified each instance as (1) a false belief that was easily remediated, (2) a flawed mental model that was not fully transformed, or (3) a robust misconception that persisted despite targeted instruction. Geographic Information System (GIS) software facilitated spatial analysis of students' answers. The COD data confirmed known misconceptions about Earth's structure, geologic time, and base level and revealed a novel robust misconception about hot spot formation. Questions with complex spatial attributes were less likely to change following instruction and more likely to be classified as a robust misconception. COD questions provided efficient access to students' conceptual understanding. CRS-administered COD questions present an opportunity to gather spatial conceptions with large groups of students, immediately, building the knowledge base about students' misconceptions and providing feedback to guide instruction.

Robust and Stable Cu Nanowire@Graphene Core-Shell Aerogels for Ultraeffective Electromagnetic Interference Shielding.

PubMed

Wu, Shiting; Zou, Mingchu; Li, Zhencheng; Chen, Daqin; Zhang, Hui; Yuan, Yongjun; Pei, Yongmao; Cao, Anyuan

2018-06-01

Cu nanowires (CuNWs) are considered as a promising candidate to develop high performance metal aerogels, yet the construction of robust and stable 3D porous structures remains challenging which severely limits their practical applications. Here, graphene-hybridized CuNW (CuNW@G) core-shell aerogels are fabricated by introducing a conformal polymeric coating and in situ transforming it into multilayered graphene seamlessly wrapped around individual CuNWs through a mild thermal annealing process. The existence of the outer graphene shell reinforces the 3D bulk structure and significantly slows down the oxidation process of CuNWs, resulting in improved mechanical property and highly stable electrical conductivity. When applied in electromagnetic interference shielding, the CuNW@G core-shell aerogels exhibit an average effectiveness of ≈52.5 dB over a wide range (from 8.2 to 18 GHz) with negligible degradation under ambient conditions for 40 d. Mechanism analysis reveals that the graphene shell with functional groups enables dual reflections on the core-shell and a multiple dielectric relaxation process, leading to enhanced dielectric loss and energy dissipation within the core-shell aerogels. The flexible core-shell-structured CuNW@G aerogels, with superior mechanical robustness and electrical stability, have potential applications in many areas such as advanced energy devices and functional composites. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Breeding Strategy To Generate Robust Yeast Starter Cultures for Cocoa Pulp Fermentations

PubMed Central

Meersman, Esther; Steensels, Jan; Paulus, Tinneke; Struyf, Nore; Saels, Veerle; Mathawan, Melissa; Koffi, Jean; Vrancken, Gino

2015-01-01

Cocoa pulp fermentation is a spontaneous process during which the natural microbiota present at cocoa farms is allowed to ferment the pulp surrounding cocoa beans. Because such spontaneous fermentations are inconsistent and contribute to product variability, there is growing interest in a microbial starter culture that could be used to inoculate cocoa pulp fermentations. Previous studies have revealed that many different fungi are recovered from different batches of spontaneous cocoa pulp fermentations, whereas the variation in the prokaryotic microbiome is much more limited. In this study, therefore, we aimed to develop a suitable yeast starter culture that is able to outcompete wild contaminants and consistently produce high-quality chocolate. Starting from specifically selected Saccharomyces cerevisiae strains, we developed robust hybrids with characteristics that allow them to efficiently ferment cocoa pulp, including improved temperature tolerance and fermentation capacity. We conducted several laboratory and field trials to show that these new hybrids often outperform their parental strains and are able to dominate spontaneous pilot scale fermentations, which results in much more consistent microbial profiles. Moreover, analysis of the resulting chocolate showed that some of the cocoa batches that were fermented with specific starter cultures yielded superior chocolate. Taken together, these results describe the development of robust yeast starter cultures for cocoa pulp fermentations that can contribute to improving the consistency and quality of commercial chocolate production. PMID:26150457

Integrated hot-melt extrusion - injection molding continuous tablet manufacturing platform: Effects of critical process parameters and formulation attributes on product robustness and dimensional stability.

PubMed

Desai, Parind M; Hogan, Rachael C; Brancazio, David; Puri, Vibha; Jensen, Keith D; Chun, Jung-Hoon; Myerson, Allan S; Trout, Bernhardt L

2017-10-05

This study provides a framework for robust tablet development using an integrated hot-melt extrusion-injection molding (IM) continuous manufacturing platform. Griseofulvin, maltodextrin, xylitol and lactose were employed as drug, carrier, plasticizer and reinforcing agent respectively. A pre-blended drug-excipient mixture was fed from a loss-in-weight feeder to a twin-screw extruder. The extrudate was subsequently injected directly into the integrated IM unit and molded into tablets. Tablets were stored in different storage conditions up to 20 weeks to monitor physical stability and were evaluated by polarized light microscopy, DSC, SEM, XRD and dissolution analysis. Optimized injection pressure provided robust tablet formulations. Tablets manufactured at low and high injection pressures exhibited the flaws of sink marks and flashing respectively. Higher solidification temperature during IM process reduced the thermal induced residual stress and prevented chipping and cracking issues. Polarized light microscopy revealed a homogeneous dispersion of crystalline griseofulvin in an amorphous matrix. DSC underpinned the effect of high tablet residual moisture on maltodextrin-xylitol phase separation that resulted in dimensional instability. Tablets with low residual moisture demonstrated long term dimensional stability. This study serves as a model for IM tablet formulations for mechanistic understanding of critical process parameters and formulation attributes required for optimal product performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Contribution of Cell Elongation to the Biofilm Formation of Pseudomonas aeruginosa during Anaerobic Respiration

PubMed Central

Park, Yongjin; Yoon, Sang Sun

2011-01-01

Pseudomonas aeruginosa, a gram-negative bacterium of clinical importance, forms more robust biofilm during anaerobic respiration, a mode of growth presumed to occur in abnormally thickened mucus layer lining the cystic fibrosis (CF) patient airway. However, molecular basis behind this anaerobiosis-triggered robust biofilm formation is not clearly defined yet. Here, we identified a morphological change naturally accompanied by anaerobic respiration in P. aeruginosa and investigated its effect on the biofilm formation in vitro. A standard laboratory strain, PAO1 was highly elongated during anaerobic respiration compared with bacteria grown aerobically. Microscopic analysis demonstrated that cell elongation likely occurred as a consequence of defective cell division. Cell elongation was dependent on the presence of nitrite reductase (NIR) that reduces nitrite (NO2 −) to nitric oxide (NO) and was repressed in PAO1 in the presence of carboxy-PTIO, a NO antagonist, demonstrating that cell elongation involves a process to respond to NO, a spontaneous byproduct of the anaerobic respiration. Importantly, the non-elongated NIR-deficient mutant failed to form biofilm, while a mutant of nitrate reductase (NAR) and wild type PAO1, both of which were highly elongated, formed robust biofilm. Taken together, our data reveal a role of previously undescribed cell biological event in P. aeruginosa biofilm formation and suggest NIR as a key player involved in such process. PMID:21267455

Breeding Strategy To Generate Robust Yeast Starter Cultures for Cocoa Pulp Fermentations.

PubMed

Meersman, Esther; Steensels, Jan; Paulus, Tinneke; Struyf, Nore; Saels, Veerle; Mathawan, Melissa; Koffi, Jean; Vrancken, Gino; Verstrepen, Kevin J

2015-09-01

Cocoa pulp fermentation is a spontaneous process during which the natural microbiota present at cocoa farms is allowed to ferment the pulp surrounding cocoa beans. Because such spontaneous fermentations are inconsistent and contribute to product variability, there is growing interest in a microbial starter culture that could be used to inoculate cocoa pulp fermentations. Previous studies have revealed that many different fungi are recovered from different batches of spontaneous cocoa pulp fermentations, whereas the variation in the prokaryotic microbiome is much more limited. In this study, therefore, we aimed to develop a suitable yeast starter culture that is able to outcompete wild contaminants and consistently produce high-quality chocolate. Starting from specifically selected Saccharomyces cerevisiae strains, we developed robust hybrids with characteristics that allow them to efficiently ferment cocoa pulp, including improved temperature tolerance and fermentation capacity. We conducted several laboratory and field trials to show that these new hybrids often outperform their parental strains and are able to dominate spontaneous pilot scale fermentations, which results in much more consistent microbial profiles. Moreover, analysis of the resulting chocolate showed that some of the cocoa batches that were fermented with specific starter cultures yielded superior chocolate. Taken together, these results describe the development of robust yeast starter cultures for cocoa pulp fermentations that can contribute to improving the consistency and quality of commercial chocolate production. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Osseous Frame Index calculations of the early medieval South-West Germany.

PubMed

Jasch, Isabelle; Langer, Antje; Boley, Moritz; Mumm, Rebekka; Riesenberg, Martin; Mann, Robert; Wahl, Joachim

2018-05-15

The proper description of former populations is one of the most difficult tasks in anthropology. Archaeological material is often limited due to fragmented and sometimes poorly preserved bone material resulting in incomplete data. Published skeletal raw data are available from the past, but much of this data is either unavailable or not used for scientific studies. The authors seek to elicit more information about prehistoric times by using this dataset to introduce a new method. The purpose is to provide an approach to reconstruct a former population in respect to robusticity and health status. For this in the pilot study the Body Mass Index (BMI) and Frame Index (FI) of early medieval South-West Germany have been analysed. The FI, in contrast to the BMI, has not yet been used for robusticity analysis utilizing only skeletal remains. As far as we know, this is the first time that the FI has been calculated using archaeological material. Due to unknown soft-tissue thickness we introduce the Osseous Frame Index (OFI). The measured OFI reveals new insights in (pre-)historic populations and allows comparisons with modern reference samples. Our OFI calculations are relatively similar to modern calculations. Males have a higher robusticity than females, slightly increasing during life-time compared to females. These calculations provide a better historical understanding of human body composition.

Robust PBPK/PD-Based Model Predictive Control of Blood Glucose.

PubMed

Schaller, Stephan; Lippert, Jorg; Schaupp, Lukas; Pieber, Thomas R; Schuppert, Andreas; Eissing, Thomas

2016-07-01

Automated glucose control (AGC) has not yet reached the point where it can be applied clinically [3]. Challenges are accuracy of subcutaneous (SC) glucose sensors, physiological lag times, and both inter- and intraindividual variability. To address above issues, we developed a novel scheme for MPC that can be applied to AGC. An individualizable generic whole-body physiology-based pharmacokinetic and dynamics (PBPK/PD) model of the glucose, insulin, and glucagon metabolism has been used as the predictive kernel. The high level of mechanistic detail represented by the model takes full advantage of the potential of MPC and may make long-term prediction possible as it captures at least some relevant sources of variability [4]. Robustness against uncertainties was increased by a control cascade relying on proportional-integrative derivative-based offset control. The performance of this AGC scheme was evaluated in silico and retrospectively using data from clinical trials. This analysis revealed that our approach handles sensor noise with a MARD of 10%-14%, and model uncertainties and disturbances. The results suggest that PBPK/PD models are well suited for MPC in a glucose control setting, and that their predictive power in combination with the integrated database-driven (a priori individualizable) model framework will help overcome current challenges in the development of AGC systems. This study provides a new, generic, and robust mechanistic approach to AGC using a PBPK platform with extensive a priori (database) knowledge for individualization.

Analysis and improvements of Adaptive Particle Refinement (APR) through CPU time, accuracy and robustness considerations

NASA Astrophysics Data System (ADS)

Chiron, L.; Oger, G.; de Leffe, M.; Le Touzé, D.

2018-02-01

While smoothed-particle hydrodynamics (SPH) simulations are usually performed using uniform particle distributions, local particle refinement techniques have been developed to concentrate fine spatial resolutions in identified areas of interest. Although the formalism of this method is relatively easy to implement, its robustness at coarse/fine interfaces can be problematic. Analysis performed in [16] shows that the radius of refined particles should be greater than half the radius of unrefined particles to ensure robustness. In this article, the basics of an Adaptive Particle Refinement (APR) technique, inspired by AMR in mesh-based methods, are presented. This approach ensures robustness with alleviated constraints. Simulations applying the new formalism proposed achieve accuracy comparable to fully refined spatial resolutions, together with robustness, low CPU times and maintained parallel efficiency.

Robustness analysis of multirate and periodically time varying systems

NASA Technical Reports Server (NTRS)

Berg, Martin C.; Mason, Gregory S.

1991-01-01

A new method for analyzing the stability and robustness of multirate and periodically time varying systems is presented. It is shown that a multirate or periodically time varying system can be transformed into an equivalent time invariant system. For a SISO system, traditional gain and phase margins can be found by direct application of the Nyquist criterion to this equivalent time invariant system. For a MIMO system, structured and unstructured singular values can be used to determine the system's robustness. The limitations and implications of utilizing this equivalent time invariant system for calculating gain and phase margins, and for estimating robustness via singular value analysis are discussed.

Robust Optimization and Sensitivity Analysis with Multi-Objective Genetic Algorithms: Single- and Multi-Disciplinary Applications

DTIC Science & Technology

2007-01-01

multi-disciplinary optimization with uncertainty. Robust optimization and sensitivity analysis is usually used when an optimization model has...formulation is introduced in Section 2.3. We briefly discuss several definitions used in the sensitivity analysis in Section 2.4. Following in...2.5. 2.4 SENSITIVITY ANALYSIS In this section, we discuss several definitions used in Chapter 5 for Multi-Objective Sensitivity Analysis . Inner

Discontinuous Inter-Granular Separations (DIGS) in the Gas Nitride Layer of ISS Race Rings

NASA Technical Reports Server (NTRS)

Figert, John; Dasgupta, Rajib; Martinez, James

2010-01-01

The starboard solar alpha rotary joint (SARJ) race ring on the International space station (ISS) failed due to severe spalling of the outer diameter, 45 degree (outer canted) nitrided surface. Subsequent analysis at NASA-KSC revealed that almost all of the debris generated due to the failure was nitrided 15-5 stainless steel. Subsequent analysis of the nitride control coupons (NCC) at NASA-JSC revealed the presence of discontinuous inter-granular separations (DIGS) in the gas nitride layer. These DIGS were present in the inter-granular networking located in the top 2 mils of the nitride layer. The manufacturer's specification requires the maximum white structure to be 0.0003 inches and intergranular networking below the allowable white structure depth to be cause for rejection; a requirement that the NCCs did not meet. Subsequent testing and analysis revealed that lower DIGS content significantly lowered the probability of nitride spalling in simulated, dry condition runs. One batch of nitride samples with DIGS content similar to the port SARJ (did not fail on orbit) which exhibited almost no nitride spalling after being run on one test rig. Another batch of nitride samples with DIGS content levels similar to the starboard SARJ exhibited significant nitride spalling on the same test rig with the same load under dry conditions. Although DIGS were not the root cause of starboard race ring failure, testing indicates that increased DIGS reduced the robustness of the gas nitride layer under dry operating conditions.

Evolutionary conservation of the polyproline II conformation surrounding intrinsically disordered phosphorylation sites.

PubMed

Elam, W Austin; Schrank, Travis P; Campagnolo, Andrew J; Hilser, Vincent J

2013-04-01

Intrinsically disordered (ID) proteins function in the absence of a unique stable structure and appear to challenge the classic structure-function paradigm. The extent to which ID proteins take advantage of subtle conformational biases to perform functions, and whether signals for such mechanism can be identified in proteome-wide studies is not well understood. Of particular interest is the polyproline II (PII) conformation, suggested to be highly populated in unfolded proteins. We experimentally determine a complete calorimetric propensity scale for the PII conformation. Projection of the scale into representative eukaryotic proteomes reveals significant PII bias in regions coding for ID proteins. Importantly, enrichment of PII in ID proteins, or protein segments, is also captured by other PII scales, indicating that this enrichment is robustly encoded and universally detectable regardless of the method of PII propensity determination. Gene ontology (GO) terms obtained using our PII scale and other scales demonstrate a consensus for molecular functions performed by high PII proteins across the proteome. Perhaps the most striking result of the GO analysis is conserved enrichment (P < 10(-8) ) of phosphorylation sites in high PII regions found by all PII scales. Subsequent conformational analysis reveals a phosphorylation-dependent modulation of PII, suggestive of a conserved "tunability" within these regions. In summary, the application of an experimentally determined polyproline II (PII) propensity scale to proteome-wide sequence analysis and gene ontology reveals an enrichment of PII bias near disordered phosphorylation sites that is conserved throughout eukaryotes. Copyright © 2013 The Protein Society.

An origin of good electrical conduction in La{sub 4}BaCu{sub 5}O{sub 13+δ}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mori, Daiki; Asai, Shinichiro; Terasaki, Ichiro, E-mail: terra@cc.nagoya-u.ac.jp

2015-07-21

We have prepared a set of polycrystalline samples of the metallic copper oxide La{sub 4}BaCu{sub 5−x}Co{sub x}O{sub 13+δ} (0 ≤ x ≤ 0.35) and have measured the resistivity from 4 to 800 K. All the resistivities show metallic temperature dependence with a small magnitude less than 2 mΩ cm at 800 K, indicating that the metallic conduction is robust against impurities. The robust metallic conduction further suggests that this class of oxide is a promising candidate for electrical leads at high temperature, which might replace platinum. A detailed measurement and analysis on the Hall resistivity have revealed that at least two components are responsible for the electricalmore » conduction, in which a large number of electrons of moderate mobility coexist with a much smaller number of holes of extremely high mobility. This large electron density well screens the impurity potential and retains the metallic conduction against 7% impurity doping.« less

RSRE: RNA structural robustness evaluator

PubMed Central

Shu, Wenjie; Zheng, Zhiqiang; Wang, Shengqi

2007-01-01

Biological robustness, defined as the ability to maintain stable functioning in the face of various perturbations, is an important and fundamental topic in current biology, and has become a focus of numerous studies in recent years. Although structural robustness has been explored in several types of RNA molecules, the origins of robustness are still controversial. Computational analysis results are needed to make up for the lack of evidence of robustness in natural biological systems. The RNA structural robustness evaluator (RSRE) web server presented here provides a freely available online tool to quantitatively evaluate the structural robustness of RNA based on the widely accepted definition of neutrality. Several classical structure comparison methods are employed; five randomization methods are implemented to generate control sequences; sub-optimal predicted structures can be optionally utilized to mitigate the uncertainty of secondary structure prediction. With a user-friendly interface, the web application is easy to use. Intuitive illustrations are provided along with the original computational results to facilitate analysis. The RSRE will be helpful in the wide exploration of RNA structural robustness and will catalyze our understanding of RNA evolution. The RSRE web server is freely available at http://biosrv1.bmi.ac.cn/RSRE/ or http://biotech.bmi.ac.cn/RSRE/. PMID:17567615

Software development for the analysis of heartbeat sounds with LabVIEW in diagnosis of cardiovascular disease.

PubMed

Topal, Taner; Polat, Hüseyin; Güler, Inan

2008-10-01

In this paper, a time-frequency spectral analysis software (Heart Sound Analyzer) for the computer-aided analysis of cardiac sounds has been developed with LabVIEW. Software modules reveal important information for cardiovascular disorders, it can also assist to general physicians to come up with more accurate and reliable diagnosis at early stages. Heart sound analyzer (HSA) software can overcome the deficiency of expert doctors and help them in rural as well as urban clinics and hospitals. HSA has two main blocks: data acquisition and preprocessing, time-frequency spectral analyses. The heart sounds are first acquired using a modified stethoscope which has an electret microphone in it. Then, the signals are analysed using the time-frequency/scale spectral analysis techniques such as STFT, Wigner-Ville distribution and wavelet transforms. HSA modules have been tested with real heart sounds from 35 volunteers and proved to be quite efficient and robust while dealing with a large variety of pathological conditions.

Comprehensive machine learning analysis of Hydra behavior reveals a stable basal behavioral repertoire.

PubMed

Han, Shuting; Taralova, Ekaterina; Dupre, Christophe; Yuste, Rafael

2018-03-28

Animal behavior has been studied for centuries, but few efficient methods are available to automatically identify and classify it. Quantitative behavioral studies have been hindered by the subjective and imprecise nature of human observation, and the slow speed of annotating behavioral data. Here, we developed an automatic behavior analysis pipeline for the cnidarian Hydra vulgaris using machine learning. We imaged freely behaving Hydra , extracted motion and shape features from the videos, and constructed a dictionary of visual features to classify pre-defined behaviors. We also identified unannotated behaviors with unsupervised methods. Using this analysis pipeline, we quantified 6 basic behaviors and found surprisingly similar behavior statistics across animals within the same species, regardless of experimental conditions. Our analysis indicates that the fundamental behavioral repertoire of Hydra is stable. This robustness could reflect a homeostatic neural control of "housekeeping" behaviors which could have been already present in the earliest nervous systems. © 2018, Han et al.

Genetic Diversity and Association Studies in US Hispanic/Latino Populations: Applications in the Hispanic Community Health Study/Study of Latinos

PubMed Central

Conomos, Matthew P.; Laurie, Cecelia A.; Stilp, Adrienne M.; Gogarten, Stephanie M.; McHugh, Caitlin P.; Nelson, Sarah C.; Sofer, Tamar; Fernández-Rhodes, Lindsay; Justice, Anne E.; Graff, Mariaelisa; Young, Kristin L.; Seyerle, Amanda A.; Avery, Christy L.; Taylor, Kent D.; Rotter, Jerome I.; Talavera, Gregory A.; Daviglus, Martha L.; Wassertheil-Smoller, Sylvia; Schneiderman, Neil; Heiss, Gerardo; Kaplan, Robert C.; Franceschini, Nora; Reiner, Alex P.; Shaffer, John R.; Barr, R. Graham; Kerr, Kathleen F.; Browning, Sharon R.; Browning, Brian L.; Weir, Bruce S.; Avilés-Santa, M. Larissa; Papanicolaou, George J.; Lumley, Thomas; Szpiro, Adam A.; North, Kari E.; Rice, Ken; Thornton, Timothy A.; Laurie, Cathy C.

2016-01-01

US Hispanic/Latino individuals are diverse in genetic ancestry, culture, and environmental exposures. Here, we characterized and controlled for this diversity in genome-wide association studies (GWASs) for the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We simultaneously estimated population-structure principal components (PCs) robust to familial relatedness and pairwise kinship coefficients (KCs) robust to population structure, admixture, and Hardy-Weinberg departures. The PCs revealed substantial genetic differentiation within and among six self-identified background groups (Cuban, Dominican, Puerto Rican, Mexican, and Central and South American). To control for variation among groups, we developed a multi-dimensional clustering method to define a “genetic-analysis group” variable that retains many properties of self-identified background while achieving substantially greater genetic homogeneity within groups and including participants with non-specific self-identification. In GWASs of 22 biomedical traits, we used a linear mixed model (LMM) including pairwise empirical KCs to account for familial relatedness, PCs for ancestry, and genetic-analysis groups for additional group-associated effects. Including the genetic-analysis group as a covariate accounted for significant trait variation in 8 of 22 traits, even after we fit 20 PCs. Additionally, genetic-analysis groups had significant heterogeneity of residual variance for 20 of 22 traits, and modeling this heteroscedasticity within the LMM reduced genomic inflation for 19 traits. Furthermore, fitting an LMM that utilized a genetic-analysis group rather than a self-identified background group achieved higher power to detect previously reported associations. We expect that the methods applied here will be useful in other studies with multiple ethnic groups, admixture, and relatedness. PMID:26748518

Artificial Neural Networks for differential diagnosis of breast lesions in MR-Mammography: a systematic approach addressing the influence of network architecture on diagnostic performance using a large clinical database.

PubMed

Dietzel, Matthias; Baltzer, Pascal A T; Dietzel, Andreas; Zoubi, Ramy; Gröschel, Tobias; Burmeister, Hartmut P; Bogdan, Martin; Kaiser, Werner A

2012-07-01

Differential diagnosis of lesions in MR-Mammography (MRM) remains a complex task. The aim of this MRM study was to design and to test robustness of Artificial Neural Network architectures to predict malignancy using a large clinical database. For this IRB-approved investigation standardized protocols and study design were applied (T1w-FLASH; 0.1 mmol/kgBW Gd-DTPA; T2w-TSE; histological verification after MRM). All lesions were evaluated by two experienced (>500 MRM) radiologists in consensus. In every lesion, 18 previously published descriptors were assessed and documented in the database. An Artificial Neural Network (ANN) was developed to process this database (The-MathWorks/Inc., feed-forward-architecture/resilient back-propagation-algorithm). All 18 descriptors were set as input variables, whereas histological results (malignant vs. benign) was defined as classification variable. Initially, the ANN was optimized in terms of "Training Epochs" (TE), "Hidden Layers" (HL), "Learning Rate" (LR) and "Neurons" (N). Robustness of the ANN was addressed by repeated evaluation cycles (n: 9) with receiver operating characteristics (ROC) analysis of the results applying 4-fold Cross Validation. The best network architecture was identified comparing the corresponding Area under the ROC curve (AUC). Histopathology revealed 436 benign and 648 malignant lesions. Enhancing the level of complexity could not increase diagnostic accuracy of the network (P: n.s.). The optimized ANN architecture (TE: 20, HL: 1, N: 5, LR: 1.2) was accurate (mean-AUC 0.888; P: <0.001) and robust (CI: 0.885-0.892; range: 0.880-0.898). The optimized neural network showed robust performance and high diagnostic accuracy for prediction of malignancy on unknown data. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Development of a Comprehensive Digital Avionics Curriculum for the Aeronautical Engineer

DTIC Science & Technology

2006-03-01

able to analyze and design aircraft and missile guidance and control systems, including feedback stabilization schemes and stochastic processes, using ...Uncertainty modeling for robust control; Robust closed-loop stability and performance; Robust H- infinity control; Robustness check using mu-analysis...Controlled feedback (reduces noise) 3. Statistical group response (reduce pressure toward conformity) When used as a tool to study a complex problem

Fertility treatment in women with polycystic ovary syndrome: a decision analysis of different oral ovulation induction agents

PubMed Central

Jungheim, Emily S.; Odibo, Anthony O.

2010-01-01

Study objective To compare different oral ovulation induction agents in treating infertile women with polycystic ovary syndrome Design Decision-analytic model comparing three treatment strategies using probability estimates derived from literature review and sensitivity analyses performed on the baseline assumptions Setting Outpatient reproductive medicine and gynecology practices Patients Infertile women with polycystic ovary syndrome Interventions Metformin, clomiphene citrate, or metformin with clomiphene citrate Main Outcome Measures Live birth Results Within the baseline assumptions, combination therapy with metformin and clomiphene citrate was the preferred therapy for achieving live birth in women with polycystic ovary syndrome. Sensitivity analysis revealed the model to be robust over a wide range of probabilities. Conclusions Combination therapy with metformin and clomiphene citrate should be considered as first-line treatment for infertile women with polycystic ovary syndrome PMID:20451181

A multiagent filovirus DNA vaccine delivered by intramuscular electroporation completely protects mice from ebola and Marburg virus challenge.

PubMed

Grant-Klein, Rebecca J; Van Deusen, Nicole M; Badger, Catherine V; Hannaman, Drew; Dupuy, Lesley C; Schmaljohn, Connie S

2012-11-01

We evaluated the immunogenicity and protective efficacy of DNA vaccines expressing the codon-optimized envelope glycoprotein genes of Zaire ebolavirus, Sudan ebolavirus, and Marburg marburgvirus (Musoke and Ravn). Intramuscular or intradermal delivery of the vaccines in BALB/c mice was performed using the TriGrid™ electroporation device. Mice that received DNA vaccines against the individual viruses developed robust glycoprotein-specific antibody titers as determined by ELISA and survived lethal viral challenge with no display of clinical signs of infection. Survival curve analysis revealed there was a statistically significant increase in survival compared to the control groups for both the Ebola and Ravn virus challenges. These data suggest that further analysis of the immune responses generated in the mice and additional protection studies in nonhuman primates are warranted.

Aberrant AKT activation drives well-differentiated liposarcoma

PubMed Central

Gutierrez, Alejandro; Snyder, Eric L.; Marino-Enriquez, Adrian; Zhang, Yi-Xiang; Sioletic, Stefano; Kozakewich, Elena; Grebliunaite, Ruta; Ou, Wen-bin; Sicinska, Ewa; Raut, Chandrajit P.; Demetri, George D.; Perez-Atayde, Antonio R.; Wagner, Andrew J.; Fletcher, Jonathan A.; Fletcher, Christopher D. M.; Look, A. Thomas

2011-01-01

Well-differentiated liposarcoma (WDLPS), one of the most common human sarcomas, is poorly responsive to radiation and chemotherapy, and the lack of animal models suitable for experimental analysis has seriously impeded functional investigation of its pathobiology and development of effective targeted therapies. Here, we show that zebrafish expressing constitutively active Akt2 in mesenchymal progenitors develop WDLPS that closely resembles the human disease. Tumor incidence rates were 8% in p53 wild-type zebrafish, 6% in p53 heterozygotes, and 29% in p53-homozygous mutant zebrafish (P = 0.013), indicating that aberrant Akt activation collaborates with p53 mutation in WDLPS pathogenesis. Analysis of primary clinical specimens of WDLPS, and of the closely related dedifferentiated liposarcoma (DDLPS) subtype, revealed immunohistochemical evidence of AKT activation in 27% of cases. Western blot analysis of a panel of cell lines derived from patients with WDLPS or DDLPS revealed robust AKT phosphorylation in all cell lines examined, even when these cells were cultured in serum-free media. Moreover, BEZ235, a small molecule inhibitor of PI3K and mammalian target of rapamycin that effectively inhibits AKT activation in these cells, impaired viability at nanomolar concentrations. Our findings are unique in providing an animal model to decipher the molecular pathogenesis of WDLPS, and implicate AKT as a previously unexplored therapeutic target in this chemoresistant sarcoma. PMID:21930930

Evaluation of PCR and high-resolution melt curve analysis for differentiation of Salmonella isolates.

PubMed

Saeidabadi, Mohammad Sadegh; Nili, Hassan; Dadras, Habibollah; Sharifiyazdi, Hassan; Connolly, Joanne; Valcanis, Mary; Raidal, Shane; Ghorashi, Seyed Ali

2017-06-01

Consumption of poultry products contaminated with Salmonella is one of the major causes of foodborne diseases worldwide and therefore detection and differentiation of Salmonella spp. in poultry is important. In this study, oligonucleotide primers were designed from hemD gene and a PCR followed by high-resolution melt (HRM) curve analysis was developed for rapid differentiation of Salmonella isolates. Amplicons of 228 bp were generated from 16 different Salmonella reference strains and from 65 clinical field isolates mainly from poultry farms. HRM curve analysis of the amplicons differentiated Salmonella isolates and analysis of the nucleotide sequence of the amplicons from selected isolates revealed that each melting curve profile was related to a unique DNA sequence. The relationship between reference strains and tested specimens was also evaluated using a mathematical model without visual interpretation of HRM curves. In addition, the potential of the PCR-HRM curve analysis was evaluated for genotyping of additional Salmonella isolates from different avian species. The findings indicate that PCR followed by HRM curve analysis provides a rapid and robust technique for genotyping of Salmonella isolates to determine the serovar/serotype.

Wavelet Filtering to Reduce Conservatism in Aeroservoelastic Robust Stability Margins

NASA Technical Reports Server (NTRS)

Brenner, Marty; Lind, Rick

1998-01-01

Wavelet analysis for filtering and system identification was used to improve the estimation of aeroservoelastic stability margins. The conservatism of the robust stability margins was reduced with parametric and nonparametric time-frequency analysis of flight data in the model validation process. Nonparametric wavelet processing of data was used to reduce the effects of external desirableness and unmodeled dynamics. Parametric estimates of modal stability were also extracted using the wavelet transform. Computation of robust stability margins for stability boundary prediction depends on uncertainty descriptions derived from the data for model validation. F-18 high Alpha Research Vehicle aeroservoelastic flight test data demonstrated improved robust stability prediction by extension of the stability boundary beyond the flight regime.

Differential Network Analysis Reveals Evolutionary Complexity in Secondary Metabolism of Rauvolfia serpentina over Catharanthus roseus

PubMed Central

Pathania, Shivalika; Bagler, Ganesh; Ahuja, Paramvir S.

2016-01-01

Comparative co-expression analysis of multiple species using high-throughput data is an integrative approach to determine the uniformity as well as diversification in biological processes. Rauvolfia serpentina and Catharanthus roseus, both members of Apocyanacae family, are reported to have remedial properties against multiple diseases. Despite of sharing upstream of terpenoid indole alkaloid pathway, there is significant diversity in tissue-specific synthesis and accumulation of specialized metabolites in these plants. This led us to implement comparative co-expression network analysis to investigate the modules and genes responsible for differential tissue-specific expression as well as species-specific synthesis of metabolites. Toward these goals differential network analysis was implemented to identify candidate genes responsible for diversification of metabolites profile. Three genes were identified with significant difference in connectivity leading to differential regulatory behavior between these plants. These genes may be responsible for diversification of secondary metabolism, and thereby for species-specific metabolite synthesis. The network robustness of R. serpentina, determined based on topological properties, was also complemented by comparison of gene-metabolite networks of both plants, and may have evolved to have complex metabolic mechanisms as compared to C. roseus under the influence of various stimuli. This study reveals evolution of complexity in secondary metabolism of R. serpentina, and key genes that contribute toward diversification of specific metabolites. PMID:27588023

Differential Network Analysis Reveals Evolutionary Complexity in Secondary Metabolism of Rauvolfia serpentina over Catharanthus roseus.

PubMed

Pathania, Shivalika; Bagler, Ganesh; Ahuja, Paramvir S

2016-01-01

Comparative co-expression analysis of multiple species using high-throughput data is an integrative approach to determine the uniformity as well as diversification in biological processes. Rauvolfia serpentina and Catharanthus roseus, both members of Apocyanacae family, are reported to have remedial properties against multiple diseases. Despite of sharing upstream of terpenoid indole alkaloid pathway, there is significant diversity in tissue-specific synthesis and accumulation of specialized metabolites in these plants. This led us to implement comparative co-expression network analysis to investigate the modules and genes responsible for differential tissue-specific expression as well as species-specific synthesis of metabolites. Toward these goals differential network analysis was implemented to identify candidate genes responsible for diversification of metabolites profile. Three genes were identified with significant difference in connectivity leading to differential regulatory behavior between these plants. These genes may be responsible for diversification of secondary metabolism, and thereby for species-specific metabolite synthesis. The network robustness of R. serpentina, determined based on topological properties, was also complemented by comparison of gene-metabolite networks of both plants, and may have evolved to have complex metabolic mechanisms as compared to C. roseus under the influence of various stimuli. This study reveals evolution of complexity in secondary metabolism of R. serpentina, and key genes that contribute toward diversification of specific metabolites.

Using Colaizzi's method of data analysis to explore the experiences of nurse academics teaching on satellite campuses.

PubMed

Wirihana, Lisa; Welch, Anthony; Williamson, Moira; Christensen, Martin; Bakon, Shannon; Craft, Judy

2018-03-16

Phenomenology is a useful methodological approach in qualitative nursing research. It enables researchers to put aside their perceptions of a phenomenon and give meaning to a participant's experiences. Exploring the experiences of others enables previously unavailable insights to be discovered. To delineate the implementation of Colaizzi's ( 1978 ) method of data analysis in descriptive phenomenological nursing research. The use of Colaizzi's method of data analysis enabled new knowledge to be revealed and provided insights into the experiences of nurse academics teaching on satellite campuses. Local adaptation of the nursing curriculum and additional unnoticed responsibilities had not been identified previously and warrant further research. Colaizzi's ( 1978 ) method of data analysis is rigorous and robust, and therefore a qualitative method that ensures the credibility and reliability of its results. It allows researchers to reveal emergent themes and their interwoven relationships. Researchers using a descriptive phenomenological approach should consider using this method as a clear and logical process through which the fundamental structure of an experience can be explored. Colaizzi's phenomenological methodology can be used reliably to understand people's experiences. This may prove beneficial in the development of therapeutic policy and the provision of patient-centred care. ©2018 RCN Publishing Company Ltd. All rights reserved. Not to be copied, transmitted or recorded in any way, in whole or part, without prior permission of the publishers.

Multiple Method Analysis of TiO2 Nanoparticle Uptake in Rice (Oryza sativa L.) Plants.

PubMed

Deng, Yingqing; Petersen, Elijah J; Challis, Katie E; Rabb, Savelas A; Holbrook, R David; Ranville, James F; Nelson, Bryant C; Xing, Baoshan

2017-09-19

Understanding the translocation of nanoparticles (NPs) into plants is challenging because qualitative and quantitative methods are still being developed and the comparability of results among different methods is unclear. In this study, uptake of titanium dioxide NPs and larger bulk particles (BPs) in rice plant (Oryza sativa L.) tissues was evaluated using three orthogonal techniques: electron microscopy, single-particle inductively coupled plasma mass spectroscopy (spICP-MS) with two different plant digestion approaches, and total elemental analysis using ICP optical emission spectroscopy. In agreement with electron microscopy results, total elemental analysis of plants exposed to TiO 2 NPs and BPs at 5 and 50 mg/L concentrations revealed that TiO 2 NPs penetrated into the plant root and resulted in Ti accumulation in above ground tissues at a higher level compared to BPs. spICP-MS analyses revealed that the size distributions of internalized particles differed between the NPs and BPs with the NPs showing a distribution with smaller particles. Acid digestion resulted in higher particle numbers and the detection of a broader range of particle sizes than the enzymatic digestion approach, highlighting the need for development of robust plant digestion procedures for NP analysis. Overall, there was agreement among the three techniques regarding NP and BP penetration into rice plant roots and spICP-MS showed its unique contribution to provide size distribution information.

Non-Convex Sparse and Low-Rank Based Robust Subspace Segmentation for Data Mining.

PubMed

Cheng, Wenlong; Zhao, Mingbo; Xiong, Naixue; Chui, Kwok Tai

2017-07-15

Parsimony, including sparsity and low-rank, has shown great importance for data mining in social networks, particularly in tasks such as segmentation and recognition. Traditionally, such modeling approaches rely on an iterative algorithm that minimizes an objective function with convex l ₁-norm or nuclear norm constraints. However, the obtained results by convex optimization are usually suboptimal to solutions of original sparse or low-rank problems. In this paper, a novel robust subspace segmentation algorithm has been proposed by integrating l p -norm and Schatten p -norm constraints. Our so-obtained affinity graph can better capture local geometrical structure and the global information of the data. As a consequence, our algorithm is more generative, discriminative and robust. An efficient linearized alternating direction method is derived to realize our model. Extensive segmentation experiments are conducted on public datasets. The proposed algorithm is revealed to be more effective and robust compared to five existing algorithms.

Assessing the Robustness of Complete Bacterial Genome Segmentations

NASA Astrophysics Data System (ADS)

Devillers, Hugo; Chiapello, Hélène; Schbath, Sophie; El Karoui, Meriem

Comparison of closely related bacterial genomes has revealed the presence of highly conserved sequences forming a "backbone" that is interrupted by numerous, less conserved, DNA fragments. Segmentation of bacterial genomes into backbone and variable regions is particularly useful to investigate bacterial genome evolution. Several software tools have been designed to compare complete bacterial chromosomes and a few online databases store pre-computed genome comparisons. However, very few statistical methods are available to evaluate the reliability of these software tools and to compare the results obtained with them. To fill this gap, we have developed two local scores to measure the robustness of bacterial genome segmentations. Our method uses a simulation procedure based on random perturbations of the compared genomes. The scores presented in this paper are simple to implement and our results show that they allow to discriminate easily between robust and non-robust bacterial genome segmentations when using aligners such as MAUVE and MGA.

Incentive-Compatible Robust Line Planning

NASA Astrophysics Data System (ADS)

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.

Fractional Control of An Active Four-wheel-steering Vehicle

NASA Astrophysics Data System (ADS)

Wang, Tianting; Tong, Jun; Chen, Ning; Tian, Jie

2018-03-01

A four-wheel-steering (4WS) vehicle model and reference model with a drop filter are constructed. The decoupling of 4WS vehicle model is carried out. And a fractional PIλDμ controller is introduced into the decoupling strategy to reduce the effects of the uncertainty of the vehicle parameters as well as the unmodelled dynamics on the system performance. Based on optimization techniques, the design of fractional controller are obtained to ensure the robustness of 4WS vehicle during the special range of frequencies through proper choice of the constraints. In order to compare with fractional robust controller, an optimal controller for the same vehicle is also designed. The simulations of the two control systems are carried out and it reveals that the decoupling and fractional robust controller is able to make vehicle model trace the reference model very well with better robustness.

MicroRNA function in Drosophila melanogaster.

PubMed

Carthew, Richard W; Agbu, Pamela; Giri, Ritika

2017-05-01

Over the last decade, microRNAs have emerged as critical regulators in the expression and function of animal genomes. This review article discusses the relationship between microRNA-mediated regulation and the biology of the fruit fly Drosophila melanogaster. We focus on the roles that microRNAs play in tissue growth, germ cell development, hormone action, and the development and activity of the central nervous system. We also discuss the ways in which microRNAs affect robustness. Many gene regulatory networks are robust; they are relatively insensitive to the precise values of reaction constants and concentrations of molecules acting within the networks. MicroRNAs involved in robustness appear to be nonessential under uniform conditions used in conventional laboratory experiments. However, the robust functions of microRNAs can be revealed when environmental or genetic variation otherwise has an impact on developmental outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Statistical Approach Reveals Designs for the Most Robust Stochastic Gene Oscillators

PubMed Central

2016-01-01

The engineering of transcriptional networks presents many challenges due to the inherent uncertainty in the system structure, changing cellular context, and stochasticity in the governing dynamics. One approach to address these problems is to design and build systems that can function across a range of conditions; that is they are robust to uncertainty in their constituent components. Here we examine the parametric robustness landscape of transcriptional oscillators, which underlie many important processes such as circadian rhythms and the cell cycle, plus also serve as a model for the engineering of complex and emergent phenomena. The central questions that we address are: Can we build genetic oscillators that are more robust than those already constructed? Can we make genetic oscillators arbitrarily robust? These questions are technically challenging due to the large model and parameter spaces that must be efficiently explored. Here we use a measure of robustness that coincides with the Bayesian model evidence, combined with an efficient Monte Carlo method to traverse model space and concentrate on regions of high robustness, which enables the accurate evaluation of the relative robustness of gene network models governed by stochastic dynamics. We report the most robust two and three gene oscillator systems, plus examine how the number of interactions, the presence of autoregulation, and degradation of mRNA and protein affects the frequency, amplitude, and robustness of transcriptional oscillators. We also find that there is a limit to parametric robustness, beyond which there is nothing to be gained by adding additional feedback. Importantly, we provide predictions on new oscillator systems that can be constructed to verify the theory and advance design and modeling approaches to systems and synthetic biology. PMID:26835539

Robust Mean and Covariance Structure Analysis through Iteratively Reweighted Least Squares.

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Bentler, Peter M.

2000-01-01

Adapts robust schemes to mean and covariance structures, providing an iteratively reweighted least squares approach to robust structural equation modeling. Each case is weighted according to its distance, based on first and second order moments. Test statistics and standard error estimators are given. (SLD)

What Is Robustness?: Problem Framing Challenges for Water Systems Planning Under Change

NASA Astrophysics Data System (ADS)

Herman, J. D.; Reed, P. M.; Zeff, H. B.; Characklis, G. W.

2014-12-01

Water systems planners have long recognized the need for robust solutions capable of withstanding deviations from the conditions for which they were designed. Faced with a set of alternatives to choose from—for example, resulting from a multi-objective optimization—existing analysis frameworks offer competing definitions of robustness under change. Robustness analyses have moved from expected utility to exploratory "bottom-up" approaches in which vulnerable scenarios are identified prior to assigning likelihoods; examples include Robust Decision Making (RDM), Decision Scaling, Info-Gap, and Many-Objective Robust Decision Making (MORDM). We propose a taxonomy of robustness frameworks to compare and contrast these approaches, based on their methods of (1) alternative selection, (2) sampling of states of the world, (3) quantification of robustness measures, and (4) identification of key uncertainties using sensitivity analysis. Using model simulations from recent work in multi-objective urban water supply portfolio planning, we illustrate the decision-relevant consequences that emerge from each of these choices. Results indicate that the methodological choices in the taxonomy lead to substantially different planning alternatives, underscoring the importance of an informed definition of robustness. We conclude with a set of recommendations for problem framing: that alternatives should be searched rather than prespecified; dominant uncertainties should be discovered rather than assumed; and that a multivariate satisficing measure of robustness allows stakeholders to achieve their problem-specific performance requirements. This work highlights the importance of careful problem formulation, and provides a common vocabulary to link the robustness frameworks widely used in the field of water systems planning.

Robust extrema features for time-series data analysis.

PubMed

Vemulapalli, Pramod K; Monga, Vishal; Brennan, Sean N

2013-06-01

The extraction of robust features for comparing and analyzing time series is a fundamentally important problem. Research efforts in this area encompass dimensionality reduction using popular signal analysis tools such as the discrete Fourier and wavelet transforms, various distance metrics, and the extraction of interest points from time series. Recently, extrema features for analysis of time-series data have assumed increasing significance because of their natural robustness under a variety of practical distortions, their economy of representation, and their computational benefits. Invariably, the process of encoding extrema features is preceded by filtering of the time series with an intuitively motivated filter (e.g., for smoothing), and subsequent thresholding to identify robust extrema. We define the properties of robustness, uniqueness, and cardinality as a means to identify the design choices available in each step of the feature generation process. Unlike existing methods, which utilize filters "inspired" from either domain knowledge or intuition, we explicitly optimize the filter based on training time series to optimize robustness of the extracted extrema features. We demonstrate further that the underlying filter optimization problem reduces to an eigenvalue problem and has a tractable solution. An encoding technique that enhances control over cardinality and uniqueness is also presented. Experimental results obtained for the problem of time series subsequence matching establish the merits of the proposed algorithm.

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

PubMed

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.

Metabolomics and In-Silico Analysis Reveal Critical Energy Deregulations in Animal Models of Parkinson’s Disease

PubMed Central

Poliquin, Pierre O.; Chen, Jingkui; Cloutier, Mathieu; Trudeau, Louis-Éric; Jolicoeur, Mario

2013-01-01

Parkinson’s disease (PD) is a multifactorial disease known to result from a variety of factors. Although age is the principal risk factor, other etiological mechanisms have been identified, including gene mutations and exposure to toxins. Deregulation of energy metabolism, mostly through the loss of complex I efficiency, is involved in disease progression in both the genetic and sporadic forms of the disease. In this study, we investigated energy deregulation in the cerebral tissue of animal models (genetic and toxin induced) of PD using an approach that combines metabolomics and mathematical modelling. In a first step, quantitative measurements of energy-related metabolites in mouse brain slices revealed most affected pathways. A genetic model of PD, the Park2 knockout, was compared to the effect of CCCP, a complex I blocker. Model simulated and experimental results revealed a significant and sustained decrease in ATP after CCCP exposure, but not in the genetic mice model. In support to data analysis, a mathematical model of the relevant metabolic pathways was developed and calibrated onto experimental data. In this work, we show that a short-term stress response in nucleotide scavenging is most probably induced by the toxin exposure. In turn, the robustness of energy-related pathways in the model explains how genetic perturbations, at least in young animals, are not sufficient to induce significant changes at the metabolite level. PMID:23935941

Robustness properties of discrete time regulators, LOG regulators and hybrid systems

NASA Technical Reports Server (NTRS)

Stein, G.; Athans, M.

1979-01-01

Robustness properites of sample-data LQ regulators are derived which show that these regulators have fundamentally inferior uncertainty tolerances when compared to their continuous-time counterparts. Results are also presented in stability theory, multivariable frequency domain analysis, LQG robustness, and mathematical representations of hybrid systems.

An Effective Collaborative Mobile Weighted Clustering Schemes for Energy Balancing in Wireless Sensor Networks.

PubMed

Tang, Chengpei; Shokla, Sanesy Kumcr; Modhawar, George; Wang, Qiang

2016-02-19

Collaborative strategies for mobile sensor nodes ensure the efficiency and the robustness of data processing, while limiting the required communication bandwidth. In order to solve the problem of pipeline inspection and oil leakage monitoring, a collaborative weighted mobile sensing scheme is proposed. By adopting a weighted mobile sensing scheme, the adaptive collaborative clustering protocol can realize an even distribution of energy load among the mobile sensor nodes in each round, and make the best use of battery energy. A detailed theoretical analysis and experimental results revealed that the proposed protocol is an energy efficient collaborative strategy such that the sensor nodes can communicate with a fusion center and produce high power gain.

New generation of elastic network models.

PubMed

López-Blanco, José Ramón; Chacón, Pablo

2016-04-01

The intrinsic flexibility of proteins and nucleic acids can be grasped from remarkably simple mechanical models of particles connected by springs. In recent decades, Elastic Network Models (ENMs) combined with Normal Model Analysis widely confirmed their ability to predict biologically relevant motions of biomolecules and soon became a popular methodology to reveal large-scale dynamics in multiple structural biology scenarios. The simplicity, robustness, low computational cost, and relatively high accuracy are the reasons behind the success of ENMs. This review focuses on recent advances in the development and application of ENMs, paying particular attention to combinations with experimental data. Successful application scenarios include large macromolecular machines, structural refinement, docking, and evolutionary conservation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Structure of turbulent non-premixed flames modeled with two-step chemistry

NASA Technical Reports Server (NTRS)

Chen, J. H.; Mahalingam, S.; Puri, I. K.; Vervisch, L.

1992-01-01

Direct numerical simulations of turbulent diffusion flames modeled with finite-rate, two-step chemistry, A + B yields I, A + I yields P, were carried out. A detailed analysis of the turbulent flame structure reveals the complex nature of the penetration of various reactive species across two reaction zones in mixture fraction space. Due to this two zone structure, these flames were found to be robust, resisting extinction over the parameter ranges investigated. As in single-step computations, mixture fraction dissipation rate and the mixture fraction were found to be statistically correlated. Simulations involving unequal molecular diffusivities suggest that the small scale mixing process and, hence, the turbulent flame structure is sensitive to the Schmidt number.

Community Perspectives on Drug/Alcohol Use, Concerns, Needs and Resources In Four Washington State Tribal Communities

PubMed Central

Radin, Sandra M.; Kutz, Stephen H.; LaMarr, June; Vendiola, Diane; Vendiola, Michael; Wilbur, Brian; Thomas, Lisa Rey; Donovan, Dennis M.

2016-01-01

Community-university teams investigated substance use, abuse, and dependence (SUAD) and related concerns, needs, strengths, and resources in four Washington State Tribal communities. 153 key community members shared their perspectives through 43 semi-structured interviews and 19 semi-structured focus groups. Qualitative data analysis revealed robust themes: prescription medications and alcohol were perceived as most prevalent and concerning; family and peer influences and emotional distress were prominent perceived risk factors; and SUAD intervention resources varied across communities. Findings may guide future research and the development of much needed strength-based, culturally appropriate, and effective SUAD interventions for American Indians, Alaska Natives, and their communities. PMID:25560464

Molecular Classifiers for Acute Kidney Transplant Rejection in Peripheral Blood by Whole Genome Gene Expression Profiling

PubMed Central

Kurian, S. M.; Williams, A. N.; Gelbart, T.; Campbell, D.; Mondala, T. S.; Head, S. R.; Horvath, S.; Gaber, L.; Thompson, R.; Whisenant, T.; Lin, W.; Langfelder, P.; Robison, E. H.; Schaffer, R. L.; Fisher, J. S.; Friedewald, J.; Flechner, S. M.; Chan, L. K.; Wiseman, A. C.; Shidban, H.; Mendez, R.; Heilman, R.; Abecassis, M. M.; Marsh, C. L.; Salomon, D. R.

2015-01-01

There are no minimally invasive diagnostic metrics for acute kidney transplant rejection (AR), especially in the setting of the common confounding diagnosis, acute dysfunction with no rejection (ADNR). Thus, though kidney transplant biopsies remain the gold standard, they are invasive, have substantial risks, sampling error issues and significant costs and are not suitable for serial monitoring. Global gene expression profiles of 148 peripheral blood samples from transplant patients with excellent function and normal histology (TX; n = 46), AR (n = 63) and ADNR (n = 39), from two independent cohorts were analyzed with DNA microarrays. We applied a new normalization tool, frozen robust multi-array analysis, particularly suitable for clinical diagnostics, multiple prediction tools to discover, refine and validate robust molecular classifiers and we tested a novel one-by-one analysis strategy to model the real clinical application of this test. Multiple three-way classifier tools identified 200 highest value probesets with sensitivity, specificity, positive predictive value, negative predictive value and area under the curve for the validation cohort ranging from 82% to 100%, 76% to 95%, 76% to 95%, 79% to 100%, 84% to 100% and 0.817 to 0.968, respectively. We conclude that peripheral blood gene expression profiling can be used as a minimally invasive tool to accurately reveal TX, AR and ADNR in the setting of acute kidney transplant dysfunction. PMID:24725967

Benchmarking of a treatment planning system for spot scanning proton therapy: Comparison and analysis of robustness to setup errors of photon IMRT and proton SFUD treatment plans of base of skull meningioma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harding, R., E-mail: ruth.harding2@wales.nhs.uk; Trnková, P.; Lomax, A. J.

Purpose: Base of skull meningioma can be treated with both intensity modulated radiation therapy (IMRT) and spot scanned proton therapy (PT). One of the main benefits of PT is better sparing of organs at risk, but due to the physical and dosimetric characteristics of protons, spot scanned PT can be more sensitive to the uncertainties encountered in the treatment process compared with photon treatment. Therefore, robustness analysis should be part of a comprehensive comparison between these two treatment methods in order to quantify and understand the sensitivity of the treatment techniques to uncertainties. The aim of this work was tomore » benchmark a spot scanning treatment planning system for planning of base of skull meningioma and to compare the created plans and analyze their robustness to setup errors against the IMRT technique. Methods: Plans were produced for three base of skull meningioma cases: IMRT planned with a commercial TPS [Monaco (Elekta AB, Sweden)]; single field uniform dose (SFUD) spot scanning PT produced with an in-house TPS (PSI-plan); and SFUD spot scanning PT plan created with a commercial TPS [XiO (Elekta AB, Sweden)]. A tool for evaluating robustness to random setup errors was created and, for each plan, both a dosimetric evaluation and a robustness analysis to setup errors were performed. Results: It was possible to create clinically acceptable treatment plans for spot scanning proton therapy of meningioma with a commercially available TPS. However, since each treatment planning system uses different methods, this comparison showed different dosimetric results as well as different sensitivities to setup uncertainties. The results confirmed the necessity of an analysis tool for assessing plan robustness to provide a fair comparison of photon and proton plans. Conclusions: Robustness analysis is a critical part of plan evaluation when comparing IMRT plans with spot scanned proton therapy plans.« less

Robust, Causal, and Incremental Approaches to Investigating Linguistic Adaptation

PubMed Central

Roberts, Seán G.

2018-01-01

This paper discusses the maximum robustness approach for studying cases of adaptation in language. We live in an age where we have more data on more languages than ever before, and more data to link it with from other domains. This should make it easier to test hypotheses involving adaptation, and also to spot new patterns that might be explained by adaptation. However, there is not much discussion of the overall approach to research in this area. There are outstanding questions about how to formalize theories, what the criteria are for directing research and how to integrate results from different methods into a clear assessment of a hypothesis. This paper addresses some of those issues by suggesting an approach which is causal, incremental and robust. It illustrates the approach with reference to a recent claim that dry environments select against the use of precise contrasts in pitch. Study 1 replicates a previous analysis of the link between humidity and lexical tone with an alternative dataset and finds that it is not robust. Study 2 performs an analysis with a continuous measure of tone and finds no significant correlation. Study 3 addresses a more recent analysis of the link between humidity and vowel use and finds that it is robust, though the effect size is small and the robustness of the measurement of vowel use is low. Methodological robustness of the general theory is addressed by suggesting additional approaches including iterated learning, a historical case study, corpus studies, and studying individual speech. PMID:29515487

Robustness analysis of a green chemistry-based model for the classification of silver nanoparticles synthesis processes

EPA Science Inventory

This paper proposes a robustness analysis based on Multiple Criteria Decision Aiding (MCDA). The ensuing model was used to assess the implementation of green chemistry principles in the synthesis of silver nanoparticles. Its recommendations were also compared to an earlier develo...

Robustness of Type I Error and Power in Set Correlation Analysis of Contingency Tables.

ERIC Educational Resources Information Center

Cohen, Jacob; Nee, John C. M.

1990-01-01

The analysis of contingency tables via set correlation allows the assessment of subhypotheses involving contrast functions of the categories of the nominal scales. The robustness of such methods with regard to Type I error and statistical power was studied via a Monte Carlo experiment. (TJH)

Allosteric mechanism of quinoline inhibitors for HIV RT-associated RNase with MD simulation and dynamics fluctuation network.

PubMed

Cai, Yi; Liu, Hao; Chen, Haifeng

2018-03-01

The human immunodeficiency virus (HIV) is a retrovirus which infects T lymphocyte of human body and causes immunodeficiency. Reverse transcriptase inhibitors (RTIs) can inhibit some functions of RT, preventing virus synthesis (double-stranded DNA), so that HIV virus replication can be reduced. Experimental results indicate a series of benzimidazole-based inhibitors which target HIV RT-associated RNase to inhibit the reverse transcription of HIV virus. However, the allosteric mechanism is still unclear. Here, molecular dynamics simulations and dynamics fluctuation network analysis were used to reveal the binding mode between the inhibitors and RT-associated RNase. The most active molecule has more hydrophobic and electrostatic interactions than the less active inhibitor. Dynamics correlation network analysis indicates that the most active inhibitor perturbs the network of RT-associated RNase and decreases the correlation of nodes. 3D-QSAR model suggests that two robust and reliable models were constructed and validated by independent test set. 3D-QSAR model also shows that bulky negatively charged or hydrophilic substituent is favorable to bioactivity. These results reveal the allosteric mechanism of quinoline inhibitors and help to improve the bioactivity. © 2017 John Wiley & Sons A/S.

Genome-wide analyses of the bZIP family reveal their involvement in the development, ripening and abiotic stress response in banana

PubMed Central

Hu, Wei; Wang, Lianzhe; Tie, Weiwei; Yan, Yan; Ding, Zehong; Liu, Juhua; Li, Meiying; Peng, Ming; Xu, Biyu; Jin, Zhiqiang

2016-01-01

The leucine zipper (bZIP) transcription factors play important roles in multiple biological processes. However, less information is available regarding the bZIP family in the important fruit crop banana. In this study, 121 bZIP transcription factor genes were identified in the banana genome. Phylogenetic analysis showed that MabZIPs were classified into 11 subfamilies. The majority of MabZIP genes in the same subfamily shared similar gene structures and conserved motifs. The comprehensive transcriptome analysis of two banana genotypes revealed the differential expression patterns of MabZIP genes in different organs, in various stages of fruit development and ripening, and in responses to abiotic stresses, including drought, cold, and salt. Interaction networks and co-expression assays showed that group A MabZIP-mediated networks participated in various stress signaling, which was strongly activated in Musa ABB Pisang Awak. This study provided new insights into the complicated transcriptional control of MabZIP genes and provided robust tissue-specific, development-dependent, and abiotic stress-responsive candidate MabZIP genes for potential applications in the genetic improvement of banana cultivars. PMID:27445085

Optimization of Friction and Wear Properties of Electroless Ni-P Coatings Under Lubrication Using Grey Fuzzy Logic

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Arkadeb; Duari, Santanu; Barman, Tapan Kumar; Sahoo, Prasanta

2017-10-01

The present study aims to evaluate the friction and wear behaviour of electroless Ni-P coatings sliding against hardened chromium coated steel under lubrication. Tribological tests are carried out on a block-on-roller configuration multi tribotester. The effect of variation of applied normal load, rotation speed of the counterface roller and test duration on the coefficient of friction and wear depth is analyzed using Taguchi's robust design philosophy and design of experiments. Optimal setting of the tribo-testing parameters is evaluated using a hybrid grey fuzzy reasoning analysis in a quest to achieve optimal tribological performance of the coatings under lubrication. Analysis of variance reveals the highest contribution by applied normal load in controlling the tribological behaviour under lubrication. Whereas the interaction effect of load and time is also seen to cast a significant effect. Surface morphology studies reveal a typical nodular structure of the deposits. The coatings are seen to be amorphous in its as-deposited condition which becomes crystalline on heat treatment. Further, the synergistic effects of test parameters, microstructure of the coatings, lubrication, etc. on the tribological behaviour are assessed.

Influencing Mechanism of Ocean Acidification on Byssus Performance in the Pearl Oyster Pinctada fucata.

PubMed

Li, Shiguo; Liu, Chuang; Zhan, Aibin; Xie, Liping; Zhang, Rongqing

2017-07-05

The byssus is an important adhesive structure by which bivalves robustly adhere to underwater substrates. It is susceptible to carbon dioxide-driven ocean acidification (OA). Previous investigations have documented significant adverse effects of OA on the performance of byssal threads, but the mechanisms remain largely unknown. In this study, multiple approaches were employed to reveal the underlying mechanisms for the effects of OA on byssus production and mechanical properties in the pearl oyster Pinctada fucata. The results showed that OA altered the abundance and secondary structure of byssal proteins and affected the contents of metal ions in distal threads, which together reduced the byssus diameter and amplified byssus nanocavity, causing reductions in mechanical properties (strength and extensibility). Expression analysis of key foot protein genes further confirmed changes in byssal protein abundance. Moreover, comparative transcriptome analysis revealed enrichment of ion transportation- and apoptosis-related categories, up-regulation of apoptosis-related pathways, and down-regulation of the "extracellular matrix-receptor interaction" pathway, which may influence foot locomotion physiology, leading to a decrease in byssus production. This study provides mechanistic insight into the effects of OA on pearl oyster byssus, which should broaden our overall understanding of the impacts of OA on marine ecosystem.

Community analysis of pigment patterns from 37 microalgae strains reveals new carotenoids and porphyrins characteristic of distinct strains and taxonomic groups

PubMed Central

Bérard, Jean-Baptiste; Kaas, Raymond; Pasquet, Virginie; Picot, Laurent; Cadoret, Jean-Paul

2017-01-01

Phytoplankton, with an estimated 30 000 to 1 000 000 species clustered in 12 phyla, presents a high taxonomic and ecophysiological diversity, reflected by the complex distribution of pigments among the different algal classes. High performance liquid chromatography is the gold standard method for qualitative and quantitative analysis of phytoplankton pigments in seawater and culture samples, but only a few pigments can be used as robust chemotaxonomic markers. A major challenge is thus to identify new ones, characteristic of a strain, species, class or taxon that cannot be currently identified on the basis of its pigment signature. Using an optimized extraction process coupled to a HPLC de-replication strategy, we examined the pigment composition of 37 microalgae strains, representative of the broad taxonomic diversity of marine and freshwater species (excluding cyanobacteria). For each species, the major pigments already described were unambiguously identified. We also observed the presence of several minor unidentified pigments in each chromatogram. The global analysis of pigment compositions revealed a total of 124 pigments, including 98 pigments or derivatives unidentified using the standards. Absorption spectra indicated that 35 corresponded to chlorophyll/porphyrin derivatives, 57 to carotenoids and six to derivatives having both spectral signatures. Sixty-one of these unidentified or new carotenoids and porphyrin derivatives were characteristic of particular strains or species, indicating their possible use as highly specific chemotaxonomic markers capable of identifying one strain out of the 37 selected. We developed a graphical analysis using Gephi software to give a clear representation of pigment communities among the various phytoplankton strains, and to reveal strain-characteristic and shared pigments. This made it possible to reconstruct the taxonomic evolution of microalgae classes, on the basis of the conservation, loss, and/or appearance of pigments. PMID:28231253

MO-F-16A-01: Implementation of MPPG TPS Verification Tests On Various Accelerators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smilowitz, J; Bredfeldt, J; Geurts, M

2014-06-15

Purpose: To demonstrate the implementation of the Medical Physics Practice Guideline (MPPG) for dose calculation and beam parameters verification of treatment planning systems (TPS). Methods: We implemented the draft TPS MPPG for three linacs: Varian Trilogy, TomoHDA and Elekta Infinity. Static and modulated test plans were created. The static fields are different than used in commissioning. Data was collected using ion chambers and diodes in a scanning water tank, Delta4 phantom and a custom phantom. MatLab and Microsoft Excel were used to create analysis tools to compare reference DICOM dose with scan data. This custom code allowed for the interpolation,more » registration and gamma analysis of arbitrary dose profiles. It will be provided as open source code. IMRT fields were validated with Delta4 registration and comparison tools. The time for each task was recorded. Results: The tests confirmed the strengths, and revealed some limitations, of our TPS. The agreement between calculated and measured dose was reported for all beams. For static fields, percent depth dose and profiles were analyzed with criteria in the draft MPPG. The results reveal areas of slight mismatch with the model (MLC leaf penumbra, buildup region.) For TomoTherapy, the IMRT plan 2%/2 mm gamma analysis revealed poorest agreement in the low dose regions. For one static test plan for all 10MV Trilogy photon beams, the plan generation, scan queue creation, data collection, data analysis and report took 2 hours, excluding tank setup. Conclusions: We have demonstrated the implementation feasibility of the TPS MPPG. This exercise generated an open source tool for dose comparisons between scan data and DICOM dose data. An easily reproducible and efficient infrastructure with streamlined data collection was created for repeatable robust testing of the TPS. The tests revealed minor discrepancies in our models and areas for improvement that are being investigated.« less

Improvement of endothelial function by pitavastatin: a meta-analysis.

PubMed

Katsiki, Niki; Reiner, Željko; Tedeschi Reiner, Eugenia; Al-Rasadi, Khalid; Pirro, Matteo; Mikhailidis, Dimitri P; Sahebkar, Amirhossein

2018-02-01

Dyslipidemia is commonly associated with endothelial dysfunction and increased cardiovascular risk. Pitavastatin has been shown to reduce total and low-density lipoprotein cholesterol, to increase high-density lipoprotein (HDL)-cholesterol and improve HDL function. Furthermore, several trials explored its effects on flow-mediated dilation (FMD), as an index of endothelial function. The authors evaluated the effect of pitavastatin therapy on FMD. The authors performed a systematic review and meta-analysis of all clinical trials exploring the impact of pitavastatin on FMD. The search included PubMed-Medline, Scopus, ISI Web of Knowledge and Google Scholar databases. Quantitative data synthesis was performed using a random-effects model, with weighted mean difference (WMD) and 95% confidence interval (CI) as summary statistics. Six eligible studies comprising 7 treatment arms were selected for this meta-analysis. Overall, WMD was significant for the effect of pitavastatin on FMD (2.45%, 95% CI: 1.31, 3.60, p < 0.001) and the effect size was robust in the leave-one-out sensitivity analysis. This meta-analysis of all available clinical trials revealed a significant increase of FMD induced by pitavastatin.

Robust red-emission spectra and yields in firefly bioluminescence against temperature changes

NASA Astrophysics Data System (ADS)

Mochizuki, Toshimitsu; Wang, Yu; Hiyama, Miyabi; Akiyama, Hidefumi

2014-05-01

We measured the quantitative spectra of firefly (Photinus pyralis) bioluminescence at various temperatures to investigate the temperature dependence of the luciferin-luciferase reaction at 15-34 °C. The quantitative spectra were decomposed very well into red (1.9 eV), orange (2.0 eV), and green (2.2 eV) Gaussian components. The intensity of the green component was the only temperature sensitive quantity that linearly decreased as the temperature increased at pH 7 and 8. We found the quantitative bioluminescence spectra to be robust below 2.0 eV against temperature and other experimental conditions. The revealed robustness of the red emissions should be useful for quantitative applications such as adenosine-5'-triphosphate detection.

Association between the SERPINE1 (PAI-1) 4G/5G insertion/deletion promoter polymorphism (rs1799889) and pre-eclampsia: a systematic review and meta-analysis.

PubMed

Zhao, Linlu; Bracken, Michael B; Dewan, Andrew T; Chen, Suzan

2013-03-01

The SERPINE1 -675 4G/5G promoter region insertion/deletion polymorphism (rs1799889) has been implicated in the pathogenesis of pre-eclampsia (PE), but the genetic association has been inconsistently replicated. To derive a more precise estimate of the association, a systematic review and meta-analysis was conducted. This study conformed to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed (MEDLINE), Scopus and HuGE Literature Finder literature databases were systematically searched for relevant studies. Summary odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for the allelic comparison (4G versus 5G) and genotypic comparisons following the co-dominant (4G/4G versus 5G/5G and 4G/5G versus 5G/5G), dominant (4G/4G+4G/5G versus 5G/5G) and recessive (4G/4G versus 4G/5G+5G/5G) genetic models. Between-study heterogeneity was quantified by I(2) statistics and publication bias was appraised with funnel plots. Sensitivity analysis was conducted to evaluate the robustness of meta-analysis findings. Meta-analysis of 11 studies involving 1297 PE cases and 1791 controls found a significant association between the SERPINE1 -675 4G/5G polymorphism and PE for the recessive genetic model (OR = 1.36, 95% CI: 1.13-1.64, P = 0.001), a robust finding according to sensitivity analysis. A low level of between-study heterogeneity was detected (I(2) = 20%) in this comparison, which may be explained by ethnic differences. Funnel plot inspection did not reveal evidence of publication bias. In conclusion, this study provides a comprehensive examination of the available literature on the association between SERPINE1 -675 4G/5G and PE. Meta-analysis results support this polymorphism as a likely susceptibility variant for PE.

Trace element profiles in modern horse molar enamel as tracers of seasonality: Evidence from micro-XRF, LA-ICP-MS and stable isotope analysis

NASA Astrophysics Data System (ADS)

de Winter, Niels; Goderis, Steven; van Malderen, Stijn; Vanhaecke, Frank; Claeys, Philippe

2016-04-01

A combination of laboratory micro-X-ray Fluorescence (μXRF) and stable carbon and oxygen isotope analysis shows that trace element profiles from modern horse molars reveal a seasonal pattern that co-varies with seasonality in the oxygen isotope records of enamel carbonate from the same teeth. A combination of six cheek teeth (premolars and molars) from the same individual yields a seasonal isotope and trace element record of approximately three years recorded during the growth of the molars. This record shows that reproducible measurements of various trace element ratios (e.g., Sr/Ca, Zn/Ca, Fe/Ca, K/Ca and S/Ca) lag the seasonal pattern in oxygen isotope records by 2-3 months. Laser Ablation-ICP-Mass Spectrometry (LA-ICP-MS) analysis on a cross-section of the first molar of the same individual is compared to the bench-top tube-excitation μXRF results to test the robustness of the measurements and to compare both methods. Furthermore, trace element (e.g. Sr, Zn, Mg & Ba) profiles perpendicular to the growth direction of the same tooth, as well as profiles parallel to the growth direction are measured with LA-ICP-MS and μXRF to study the internal distribution of trace element ratios in two dimensions. Results of this extensive complementary line-scanning procedure shows the robustness of state of the art laboratory micro-XRF scanning for the measurement of trace elements in bioapatite. The comparison highlights the advantages and disadvantages of both methods for trace element analysis and illustrates their complementarity. Results of internal variation within the teeth shed light on the origins of trace elements in mammal teeth and their potential use for paleo-environmental reconstruction.

Percolation analysis for cosmic web with discrete points

NASA Astrophysics Data System (ADS)

Zhang, Jiajun; Cheng, Dalong; Chu, Ming-Chung

2018-01-01

Percolation analysis has long been used to quantify the connectivity of the cosmic web. Most of the previous work is based on density fields on grids. By smoothing into fields, we lose information about galaxy properties like shape or luminosity. The lack of mathematical modeling also limits our understanding for the percolation analysis. To overcome these difficulties, we have studied percolation analysis based on discrete points. Using a friends-of-friends (FoF) algorithm, we generate the S -b b relation, between the fractional mass of the largest connected group (S ) and the FoF linking length (b b ). We propose a new model, the probability cloud cluster expansion theory to relate the S -b b relation with correlation functions. We show that the S -b b relation reflects a combination of all orders of correlation functions. Using N-body simulation, we find that the S -b b relation is robust against redshift distortion and incompleteness in observation. From the Bolshoi simulation, with halo abundance matching (HAM), we have generated a mock galaxy catalog. Good matching of the projected two-point correlation function with observation is confirmed. However, comparing the mock catalog with the latest galaxy catalog from Sloan Digital Sky Survey (SDSS) Data Release (DR)12, we have found significant differences in their S -b b relations. This indicates that the mock galaxy catalog cannot accurately retain higher-order correlation functions than the two-point correlation function, which reveals the limit of the HAM method. As a new measurement, the S -b b relation is applicable to a wide range of data types, fast to compute, and robust against redshift distortion and incompleteness and contains information of all orders of correlation functions.

A simple model for cell type recognition using 2D-correlation analysis of FTIR images from breast cancer tissue

NASA Astrophysics Data System (ADS)

Ali, Mohamed H.; Rakib, Fazle; Al-Saad, Khalid; Al-Saady, Rafif; Lyng, Fiona M.; Goormaghtigh, Erik

2018-07-01

Breast cancer is the second most common cancer after lung cancer. So far, in clinical practice, most cancer parameters originating from histopathology rely on the visualization by a pathologist of microscopic structures observed in stained tissue sections, including immunohistochemistry markers. Fourier transform infrared spectroscopy (FTIR) spectroscopy provides a biochemical fingerprint of a biopsy sample and, together with advanced data analysis techniques, can accurately classify cell types. Yet, one of the challenges when dealing with FTIR imaging is the slow recording of the data. One cm2 tissue section requires several hours of image recording. We show in the present paper that 2D covariance analysis singles out only a few wavenumbers where both variance and covariance are large. Simple models could be built using 4 wavenumbers to identify the 4 main cell types present in breast cancer tissue sections. Decision trees provide particularly simple models to reach discrimination between the 4 cell types. The robustness of these simple decision-tree models were challenged with FTIR spectral data obtained using different recording conditions. One test set was recorded by transflection on tissue sections in the presence of paraffin while the training set was obtained on dewaxed tissue sections by transmission. Furthermore, the test set was collected with a different brand of FTIR microscope and a different pixel size. Despite the different recording conditions, separating extracellular matrix (ECM) from carcinoma spectra was 100% successful, underlying the robustness of this univariate model and the utility of covariance analysis for revealing efficient wavenumbers. We suggest that 2D covariance maps using the full spectral range could be most useful to select the interesting wavenumbers and achieve very fast data acquisition on quantum cascade laser infrared imaging microscopes.

Neural network modeling and prediction of resistivity structures using VES Schlumberger data over a geothermal area

NASA Astrophysics Data System (ADS)

Singh, Upendra K.; Tiwari, R. K.; Singh, S. B.

2013-03-01

This paper presents the effects of several parameters on the artificial neural networks (ANN) inversion of vertical electrical sounding (VES) data. Sensitivity of ANN parameters was examined on the performance of adaptive backpropagation (ABP) and Levenberg-Marquardt algorithms (LMA) to test the robustness to noisy synthetic as well as field geophysical data and resolving capability of these methods for predicting the subsurface resistivity layers. We trained, tested and validated ANN using the synthetic VES data as input to the networks and layer parameters of the models as network output. ANN learning parameters are varied and corresponding observations are recorded. The sensitivity analysis of synthetic data and real model demonstrate that ANN algorithms applied in VES data inversion should be considered well not only in terms of accuracy but also in terms of high computational efforts. Also the analysis suggests that ANN model with its various controlling parameters are largely data dependent and hence no unique architecture can be designed for VES data analysis. ANN based methods are also applied to the actual VES field data obtained from the tectonically vital geothermal areas of Jammu and Kashmir, India. Analysis suggests that both the ABP and LMA are suitable methods for 1-D VES modeling. But the LMA method provides greater degree of robustness than the ABP in case of 2-D VES modeling. Comparison of the inversion results with known lithology correlates well and also reveals the additional significant feature of reconsolidated breccia of about 7.0 m thickness beneath the overburden in some cases like at sounding point RDC-5. We may therefore conclude that ANN based methods are significantly faster and efficient for detection of complex layered resistivity structures with a relatively greater degree of precision and resolution.

Sex beyond the genitalia: The human brain mosaic

PubMed Central

Joel, Daphna; Berman, Zohar; Tavor, Ido; Wexler, Nadav; Gaber, Olga; Stein, Yaniv; Shefi, Nisan; Pool, Jared; Urchs, Sebastian; Margulies, Daniel S.; Liem, Franziskus; Hänggi, Jürgen; Jäncke, Lutz; Assaf, Yaniv

2015-01-01

Whereas a categorical difference in the genitals has always been acknowledged, the question of how far these categories extend into human biology is still not resolved. Documented sex/gender differences in the brain are often taken as support of a sexually dimorphic view of human brains (“female brain” or “male brain”). However, such a distinction would be possible only if sex/gender differences in brain features were highly dimorphic (i.e., little overlap between the forms of these features in males and females) and internally consistent (i.e., a brain has only “male” or only “female” features). Here, analysis of MRIs of more than 1,400 human brains from four datasets reveals extensive overlap between the distributions of females and males for all gray matter, white matter, and connections assessed. Moreover, analyses of internal consistency reveal that brains with features that are consistently at one end of the “maleness-femaleness” continuum are rare. Rather, most brains are comprised of unique “mosaics” of features, some more common in females compared with males, some more common in males compared with females, and some common in both females and males. Our findings are robust across sample, age, type of MRI, and method of analysis. These findings are corroborated by a similar analysis of personality traits, attitudes, interests, and behaviors of more than 5,500 individuals, which reveals that internal consistency is extremely rare. Our study demonstrates that, although there are sex/gender differences in the brain, human brains do not belong to one of two distinct categories: male brain/female brain. PMID:26621705

Functional Analysis of Dopaminergic Systems in a DYT1 Knock-in Mouse Model of Dystonia

PubMed Central

Song, Chang-Hyun; Fan, Xueliang; Exeter, Cicely J.; Hess, Ellen J.; Jinnah, H. A.

2012-01-01

The dystonias are a group of disorders characterized by involuntary twisting movements and abnormal posturing. The most common of the inherited dystonias is DYT1 dystonia, which is due to deletion of a single GAG codon (ΔE) in the TOR1A gene that encodes torsinA. Since some forms of dystonia have been linked with dysfunction of brain dopamine pathways, the integrity of these pathways was explored in a knock-in mouse model of DYT1 dystonia. In DYT1(ΔE) knock-in mice, neurochemical measures revealed only small changes in the content of dopamine or its metabolites in tissue homogenates from caudoputamen or midbrain, but microdialysis studies revealed robust decreases in baseline and amphetamine-stimulated extracellular dopamine in the caudoputamen. Quantitative stereological methods revealed no evidence for striatal or midbrain atrophy, but substantia nigra neurons immunopositive for tyrosine hydroxylase were slightly reduced in numbers and enlarged in size. Behavioral studies revealed subtle abnormalities in gross motor activity and motor coordination without overt dystonia. Neuropharmacological challenges of dopamine systems revealed normal behavioral responses to amphetamine and a minor increase in sensitivity to haloperidol. These results demonstrate that this DYT1(ΔE) knock-in mouse model of dystonia harbors neurochemical and structural changes of the dopamine pathways, as well as motor abnormalities. PMID:22659308

ER stress-induced protein, VIGG, disturbs plant cation homeostasis, which is correlated with growth retardation and robustness to ER stress

DOE Office of Scientific and Technical Information (OSTI.GOV)

Katoh, Hironori; Fujita, Keiko; Takuhara, Yuki

2011-02-18

Highlights: {yields} VIGG is an ER stress-induced protein in plant. {yields} We examine the characteristics of VIGG-overexpressing Arabidopsis plants. {yields} VIGG-overexpressing plants reveal growth retardation and robustness to ER stress. {yields} VIGG disturbs cation homeostasis in plant. -- Abstract: VIGG is a putative endoplasmic reticulum (ER) resident protein induced by virus infection and ER stress, and is correlated with fruit quality in grapevine. The present study was undertaken to determine the biological function of VIGG in grapevine. Experiments using fluorescent protein-VIGG fusion protein demonstrated that VIGG is localized in ER and the ER targeting sequence is in the N-terminus. Themore » overexpression of VIGG in Arabidopsis plant led to growth retardation. The rosette leaves of VIGG-overexpressing plants were smaller than those of the control plants and rolled at 42 days after seeding. VIGG-overexpressing plants revealed robustness to ER stress as well as the low expression of ER stress marker proteins, such as the luminal binding proteins. These characteristics of VIGG-overexpressing plants were supported by a microarray experiment that demonstrated the disruption of genes related to ER stress response and flowering, as well as cation mobility, in the plants. Finally, cation homeostasis in the plants was disturbed by the overexpression of VIGG. Taken together, these results suggest that VIGG may disturb cation homeostasis in plant, which is correlated with the robustness to ER stress and growth retardation.« less

Model Uncertainty and Robustness: A Computational Framework for Multimodel Analysis

ERIC Educational Resources Information Center

Young, Cristobal; Holsteen, Katherine

2017-01-01

Model uncertainty is pervasive in social science. A key question is how robust empirical results are to sensible changes in model specification. We present a new approach and applied statistical software for computational multimodel analysis. Our approach proceeds in two steps: First, we estimate the modeling distribution of estimates across all…

Complex adaptive behavior and dexterous action

PubMed Central

Harrison, Steven J.; Stergiou, Nicholas

2016-01-01

Dexterous action, as conceptualized by Bernstein in his influential ecological analysis of human behavior, is revealed in the ability to flexibly generate behaviors that are adaptively tailored to the demands of the context in which they are embedded. Conceived as complex adaptive behavior, dexterity depends upon the qualities of robustness and degeneracy, and is supported by the functional complexity of the agent-environment system. Using Bernstein’s and Gibson’s ecological analyses of behavior situated in natural environments as conceptual touchstones, we consider the hypothesis that complex adaptive behavior capitalizes upon general principles of self-organization. Here, we outline a perspective in which the complex interactivity of nervous-system, body, and environment is revealed as an essential resource for adaptive behavior. From this perspective, we consider the implications for interpreting the functionality and dysfunctionality of human behavior. This paper demonstrates that, optimal variability, the topic of this special issue, is a logical consequence of interpreting the functionality of human behavior as complex adaptive behavior. PMID:26375932

How robust are in situ observations for validating satellite-derived albedo over the dark zone of the Greenland Ice Sheet?

NASA Astrophysics Data System (ADS)

Ryan, J. C.; Hubbard, A.; Irvine-Fynn, T. D.; Doyle, S. H.; Cook, J. M.; Stibal, M.; Box, J. E.

2017-06-01

Calibration and validation of satellite-derived ice sheet albedo data require high-quality, in situ measurements commonly acquired by up and down facing pyranometers mounted on automated weather stations (AWS). However, direct comparison between ground and satellite-derived albedo can only be justified when the measured surface is homogeneous at the length-scale of both satellite pixel and in situ footprint. Here we use digital imagery acquired by an unmanned aerial vehicle to evaluate point-to-pixel albedo comparisons across the western, ablating margin of the Greenland Ice Sheet. Our results reveal that in situ measurements overestimate albedo by up to 0.10 at the end of the melt season because the ground footprints of AWS-mounted pyranometers are insufficient to capture the spatial heterogeneity of the ice surface as it progressively ablates and darkens. Statistical analysis of 21 AWS across the entire Greenland Ice Sheet reveals that almost half suffer from this bias, including some AWS located within the wet snow zone.

How robust are in situ observations for validating satellite-derived albedo over the dark zone of the Greenland Ice Sheet?

NASA Astrophysics Data System (ADS)

Ryan, J.; Hubbard, A., II; Irvine-Fynn, T. D.; Doyle, S. H.; Cook, J.; Stibal, M.; Smith, L. C.; Box, J. E.

2017-12-01

Calibration and validation of satellite-derived ice sheet albedo data require high-quality, in situ measurements commonly acquired by up and down facing pyranometers mounted on automated weather stations (AWS). However, direct comparison between ground and satellite-derived albedo can only be justified when the measured surface is homogeneous at the length-scale of both satellite pixel and in situ footprint. We used digital imagery acquired by an unmanned aerial vehicle to evaluate point-to-pixel albedo comparisons across the western, ablating margin of the Greenland Ice Sheet. Our results reveal that in situ measurements overestimate albedo by up to 0.10 at the end of the melt season because the ground footprints of AWS-mounted pyranometers are insufficient to capture the spatial heterogeneity of the ice surface as it progressively ablates and darkens. Statistical analysis of 21 AWS across the entire Greenland Ice Sheet reveals that almost half suffer from this bias, including some AWS located within the wet snow zone.

Characterisation of the Transcriptomes of Genetically Diverse Listeria monocytogenes Exposed to Hyperosmotic and Low Temperature Conditions Reveal Global Stress-Adaptation Mechanisms

PubMed Central

Durack, Juliana; Ross, Tom; Bowman, John P.

2013-01-01

The ability of Listeria monocytogenes to adapt to various food and food- processing environments has been attributed to its robustness, persistence and prevalence in the food supply chain. To improve the present understanding of molecular mechanisms involved in hyperosmotic and low-temperature stress adaptation of L. monocytogenes, we undertook transcriptomics analysis on three strains adapted to sub-lethal levels of these stress stimuli and assessed functional gene response. Adaptation to hyperosmotic and cold-temperature stress has revealed many parallels in terms of gene expression profiles in strains possessing different levels of stress tolerance. Gene sets associated with ribosomes and translation, transcription, cell division as well as fatty acid biosynthesis and peptide transport showed activation in cells adapted to either cold or hyperosmotic stress. Repression of genes associated with carbohydrate metabolism and transport as well as flagella was evident in stressed cells, likely linked to activation of CodY regulon and consequential cellular energy conservation. PMID:24023890

An objective alternative to IUPAC's approach to assign oxidation states.

PubMed

Postils, Verònica; Delgado-Alonso, Carlos; Luis, Josep M; Salvador, Pedro

2018-05-22

The IUPAC has recently clarified the term Oxidation State (OS), and provided algorithms for its determination based on the ionic approximation (IA) of the bonds supported by atomic electronegativities (EN). Unfortunately, there are a number of exceptions and ambiguities in IUPAC's algorithms when it comes to practical applications. Our comprehensive study reveals the critical role of the chemical environment on establishing the OS, which cannot always be properly predicted using fix atomic EN values. By identifying what we define here as subsystems of enhanced stability within the molecular system, OS can be safely assigned in many cases without invoking exceptions. New insights about the effect of local aromaticity upon OS are revealed. Moreover, we prove that there are intrinsic limitations of the IA that cannot be overcome. In this context, the effective oxidation state (EOS) analysis arises as a robust and general scheme to derive OS without any external guidance. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Jamming criticality revealed by removing localized buckling excitations.

PubMed

Charbonneau, Patrick; Corwin, Eric I; Parisi, Giorgio; Zamponi, Francesco

2015-03-27

Recent theoretical advances offer an exact, first-principles theory of jamming criticality in infinite dimension as well as universal scaling relations between critical exponents in all dimensions. For packings of frictionless spheres near the jamming transition, these advances predict that nontrivial power-law exponents characterize the critical distribution of (i) small interparticle gaps and (ii) weak contact forces, both of which are crucial for mechanical stability. The scaling of the interparticle gaps is known to be constant in all spatial dimensions d-including the physically relevant d=2 and 3, but the value of the weak force exponent remains the object of debate and confusion. Here, we resolve this ambiguity by numerical simulations. We construct isostatic jammed packings with extremely high accuracy, and introduce a simple criterion to separate the contribution of particles that give rise to localized buckling excitations, i.e., bucklers, from the others. This analysis reveals the remarkable dimensional robustness of mean-field marginality and its associated criticality.

Mapping the Extracellular and Membrane Proteome Associated with the Vasculature and the Stroma in the Embryo*

PubMed Central

Soulet, Fabienne; Kilarski, Witold W.; Roux-Dalvai, Florence; Herbert, John M. J.; Sacewicz, Izabela; Mouton-Barbosa, Emmanuelle; Bicknell, Roy; Lalor, Patricia; Monsarrat, Bernard; Bikfalvi, Andreas

2013-01-01

In order to map the extracellular or membrane proteome associated with the vasculature and the stroma in an embryonic organism in vivo, we developed a biotinylation technique for chicken embryo and combined it with mass spectrometry and bioinformatic analysis. We also applied this procedure to implanted tumors growing on the chorioallantoic membrane or after the induction of granulation tissue. Membrane and extracellular matrix proteins were the most abundant components identified. Relative quantitative analysis revealed differential protein expression patterns in several tissues. Through a bioinformatic approach, we determined endothelial cell protein expression signatures, which allowed us to identify several proteins not yet reported to be associated with endothelial cells or the vasculature. This is the first study reported so far that applies in vivo biotinylation, in combination with robust label-free quantitative proteomics approaches and bioinformatic analysis, to an embryonic organism. It also provides the first description of the vascular and matrix proteome of the embryo that might constitute the starting point for further developments. PMID:23674615

Group-based QSAR and molecular dynamics mechanistic analysis revealing the mode of action of novel piperidinone derived protein-protein inhibitors of p53-MDM2.

PubMed

Goyal, Sukriti; Grover, Sonam; Dhanjal, Jaspreet Kaur; Tyagi, Chetna; Goyal, Manisha; Grover, Abhinav

2014-06-01

Tumour suppressor p53 is known to play a central role in prevention of tumour development, DNA repair, senescence and apoptosis which is in normal cells maintained by negative feedback regulator MDM2 (Murine Double Minute 2). In case of dysfunctioning of this regulatory loop, tumour development starts thus resulting in cancerous condition. Inhibition of p53-MDM2 binding would result in activation of the tumour suppressor. In this study, a novel robust fragment-based QSAR model has been developed for piperidinone derived compounds experimentally known to inhibit p53-MDM2 interaction. The QSAR model developed showed satisfactory statistical parameters for the experimentally reported dataset (r(2)=0.9415, q(2)=0.8958, pred_r(2)=0.8894 and F-test=112.7314), thus judging the robustness of the model. Low standard error values (r(2)_se=0.3003, q(2)_se=0.4009 and pred_r(2)_se=0.3315) confirmed the accuracy of the developed model. The regression equation obtained constituted three descriptors (R2-DeltaEpsilonA, R1-RotatableBondCount and R2-SssOCount), two of which had positive contribution while third showed negative correlation. Based on the developed QSAR model, a combinatorial library was generated and activities of the compounds were predicted. These compounds were docked with MDM2 and two top scoring compounds with binding affinities of -10.13 and -9.80kcal/mol were selected. The binding modes of actions of these complexes were analyzed using molecular dynamics simulations. Analysis of the developed fragment-based QSAR model revealed that addition of unsaturated electronegative groups at R2 site and groups with more rotatable bonds at R1 improved the inhibitory activity of these potent lead compounds. The detailed analysis carried out in this study provides a considerable basis for the design and development of novel piperidinone-based lead molecules against cancer and also provides mechanistic insights into their mode of actions. Copyright © 2014 Elsevier Inc. All rights reserved.

Engineering diverse changes in beta-turn propensities in the N-terminal beta-hairpin of ubiquitin reveals significant effects on stability and kinetics but a robust folding transition state.

PubMed

Simpson, Emma R; Meldrum, Jill K; Searle, Mark S

2006-04-04

Using the N-terminal 17-residue beta-hairpin of ubiquitin as a "host" for mutational studies, we have investigated the influence of the beta-turn sequence on protein stability and folding kinetics by replacing the native G-bulged turn (TLTGK) with more flexible analogues (TG3K and TG5K) and a series of four-residue type I' beta-turn sequences, commonly found in beta-hairpins. Although a statistical analysis of type I' turns demonstrates residue preferences at specific sites, the frequency of occurrence appears to only broadly correlate with experimentally determined protein stabilities. The subsequent engineering of context-dependent non-native tertiary contacts involving turn residues is shown to produce large changes in stability. Relatively few point mutations have been described that probe secondary structure formation in ubiquitin in a manner that is independent of tertiary contacts. To this end, we have used the more rigorous rate-equilibrium free energy relationship (Leffler analysis), rather than the two-point phi value analysis, to show for a family of engineered beta-turn mutants that stability (range of approximately 20 kJ/mol) and folding kinetics (190-fold variation in refolding rate) are linearly correlated (alpha(f) = 0.74 +/- 0.08). The data are consistent with a transition state that is robust with regard to a wide range of statistically favored and disfavored beta-turn mutations and implicate a loosely assembled beta-hairpin as a key template in transition state stabilization with the beta-turn playing a central role.

Network Analysis of Beliefs About the Scientific Enterprise: A comparison of scientists, middle school science teachers and eighth-grade science students

NASA Astrophysics Data System (ADS)

Peters-Burton, Erin; Baynard, Liz R.

2013-11-01

An understanding of the scientific enterprise is useful because citizens need to make systematic, rational decisions about projects involving scientific endeavors and technology, and a clearer understanding of scientific epistemology is beneficial because it could encourage more public engagement with science. The purpose of this study was to capture beliefs for three groups, scientists, secondary science teachers, and eighth-grade science students, about the ways scientific knowledge is generated and validated. Open-ended questions were framed by formal scientific epistemology and dimensions of epistemology recognized in the field of educational psychology. The resulting statements were placed in a card sort and mapped in a network analysis to communicate interconnections among ideas. Maps analyzed with multidimensional scaling revealed robust connections among students and scientists but not among teachers. Student and teacher maps illustrated the strongest connections among ideas about experiments while scientist maps present more descriptive and well-rounded ideas about the scientific enterprise. The students' map was robust in terms of numbers of ideas, but were lacking in a hierarchical organization of ideas. The teachers' map displayed an alignment with the learning standards of the state, but not a broader view of science. The scientists map displayed a hierarchy of ideas with elaboration of equally valued statements connected to several foundational statements. Network analysis can be helpful in forwarding the study of views of the nature of science because of the technique's ability to capture verbatim statements from participants and to display the strength of connections among the statements.

Bayesian analysis of stochastic volatility-in-mean model with leverage and asymmetrically heavy-tailed error using generalized hyperbolic skew Student’s t-distribution*

PubMed Central

Leão, William L.; Chen, Ming-Hui

2017-01-01

A stochastic volatility-in-mean model with correlated errors using the generalized hyperbolic skew Student-t (GHST) distribution provides a robust alternative to the parameter estimation for daily stock returns in the absence of normality. An efficient Markov chain Monte Carlo (MCMC) sampling algorithm is developed for parameter estimation. The deviance information, the Bayesian predictive information and the log-predictive score criterion are used to assess the fit of the proposed model. The proposed method is applied to an analysis of the daily stock return data from the Standard & Poor’s 500 index (S&P 500). The empirical results reveal that the stochastic volatility-in-mean model with correlated errors and GH-ST distribution leads to a significant improvement in the goodness-of-fit for the S&P 500 index returns dataset over the usual normal model. PMID:29333210

A Normalization-Free and Nonparametric Method Sharpens Large-Scale Transcriptome Analysis and Reveals Common Gene Alteration Patterns in Cancers.

PubMed

Li, Qi-Gang; He, Yong-Han; Wu, Huan; Yang, Cui-Ping; Pu, Shao-Yan; Fan, Song-Qing; Jiang, Li-Ping; Shen, Qiu-Shuo; Wang, Xiao-Xiong; Chen, Xiao-Qiong; Yu, Qin; Li, Ying; Sun, Chang; Wang, Xiangting; Zhou, Jumin; Li, Hai-Peng; Chen, Yong-Bin; Kong, Qing-Peng

2017-01-01

Heterogeneity in transcriptional data hampers the identification of differentially expressed genes (DEGs) and understanding of cancer, essentially because current methods rely on cross-sample normalization and/or distribution assumption-both sensitive to heterogeneous values. Here, we developed a new method, Cross-Value Association Analysis (CVAA), which overcomes the limitation and is more robust to heterogeneous data than the other methods. Applying CVAA to a more complex pan-cancer dataset containing 5,540 transcriptomes discovered numerous new DEGs and many previously rarely explored pathways/processes; some of them were validated, both in vitro and in vivo , to be crucial in tumorigenesis, e.g., alcohol metabolism ( ADH1B ), chromosome remodeling ( NCAPH ) and complement system ( Adipsin ). Together, we present a sharper tool to navigate large-scale expression data and gain new mechanistic insights into tumorigenesis.

Bayesian analysis of stochastic volatility-in-mean model with leverage and asymmetrically heavy-tailed error using generalized hyperbolic skew Student's t-distribution.

PubMed

Leão, William L; Abanto-Valle, Carlos A; Chen, Ming-Hui

2017-01-01

A stochastic volatility-in-mean model with correlated errors using the generalized hyperbolic skew Student-t (GHST) distribution provides a robust alternative to the parameter estimation for daily stock returns in the absence of normality. An efficient Markov chain Monte Carlo (MCMC) sampling algorithm is developed for parameter estimation. The deviance information, the Bayesian predictive information and the log-predictive score criterion are used to assess the fit of the proposed model. The proposed method is applied to an analysis of the daily stock return data from the Standard & Poor's 500 index (S&P 500). The empirical results reveal that the stochastic volatility-in-mean model with correlated errors and GH-ST distribution leads to a significant improvement in the goodness-of-fit for the S&P 500 index returns dataset over the usual normal model.

ENSO controls interannual fire activity in southeast Australia

NASA Astrophysics Data System (ADS)

Mariani, M.; Fletcher, M.-S.; Holz, A.; Nyman, P.

2016-10-01

El Niño-Southern Oscillation (ENSO) is the main mode controlling the variability in the ocean-atmosphere system in the South Pacific. While the ENSO influence on rainfall regimes in the South Pacific is well documented, its role in driving spatiotemporal trends in fire activity in this region has not been rigorously investigated. This is particularly the case for the highly flammable and densely populated southeast Australian sector, where ENSO is a major control over climatic variability. Here we conduct the first region-wide analysis of how ENSO controls fire activity in southeast Australia. We identify a significant relationship between ENSO and both fire frequency and area burnt. Critically, wavelet analyses reveal that despite substantial temporal variability in the ENSO system, ENSO exerts a persistent and significant influence on southeast Australian fire activity. Our analysis has direct application for developing robust predictive capacity for the increasingly important efforts at fire management.

An improved method for bivariate meta-analysis when within-study correlations are unknown.

PubMed

Hong, Chuan; D Riley, Richard; Chen, Yong

2018-03-01

Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference procedures for multivariate meta-analysis require the knowledge of within-study correlations, which are usually unavailable. This limits standard inference approaches in practice. Riley et al proposed a working model and an overall synthesis correlation parameter to account for the marginal correlation between outcomes, where the only data needed are those required for a separate univariate random-effects meta-analysis. As within-study correlations are not required, the Riley method is applicable to a wide variety of evidence synthesis situations. However, the standard variance estimator of the Riley method is not entirely correct under many important settings. As a consequence, the coverage of a function of pooled estimates may not reach the nominal level even when the number of studies in the multivariate meta-analysis is large. In this paper, we improve the Riley method by proposing a robust variance estimator, which is asymptotically correct even when the model is misspecified (ie, when the likelihood function is incorrect). Simulation studies of a bivariate meta-analysis, in a variety of settings, show a function of pooled estimates has improved performance when using the proposed robust variance estimator. In terms of individual pooled estimates themselves, the standard variance estimator and robust variance estimator give similar results to the original method, with appropriate coverage. The proposed robust variance estimator performs well when the number of studies is relatively large. Therefore, we recommend the use of the robust method for meta-analyses with a relatively large number of studies (eg, m≥50). When the sample size is relatively small, we recommend the use of the robust method under the working independence assumption. We illustrate the proposed method through 2 meta-analyses. Copyright © 2017 John Wiley & Sons, Ltd.

How robust is a robust policy? A comparative analysis of alternative robustness metrics for supporting robust decision analysis.

NASA Astrophysics Data System (ADS)

Kwakkel, Jan; Haasnoot, Marjolijn

2015-04-01

In response to climate and socio-economic change, in various policy domains there is increasingly a call for robust plans or policies. That is, plans or policies that performs well in a very large range of plausible futures. In the literature, a wide range of alternative robustness metrics can be found. The relative merit of these alternative conceptualizations of robustness has, however, received less attention. Evidently, different robustness metrics can result in different plans or policies being adopted. This paper investigates the consequences of several robustness metrics on decision making, illustrated here by the design of a flood risk management plan. A fictitious case, inspired by a river reach in the Netherlands is used. The performance of this system in terms of casualties, damages, and costs for flood and damage mitigation actions is explored using a time horizon of 100 years, and accounting for uncertainties pertaining to climate change and land use change. A set of candidate policy options is specified up front. This set of options includes dike raising, dike strengthening, creating more space for the river, and flood proof building and evacuation options. The overarching aim is to design an effective flood risk mitigation strategy that is designed from the outset to be adapted over time in response to how the future actually unfolds. To this end, the plan will be based on the dynamic adaptive policy pathway approach (Haasnoot, Kwakkel et al. 2013) being used in the Dutch Delta Program. The policy problem is formulated as a multi-objective robust optimization problem (Kwakkel, Haasnoot et al. 2014). We solve the multi-objective robust optimization problem using several alternative robustness metrics, including both satisficing robustness metrics and regret based robustness metrics. Satisficing robustness metrics focus on the performance of candidate plans across a large ensemble of plausible futures. Regret based robustness metrics compare the performance of a candidate plan with the performance of other candidate plans across a large ensemble of plausible futures. Initial results suggest that the simplest satisficing metric, inspired by the signal to noise ratio, results in very risk averse solutions. Other satisficing metrics, which handle the average performance and the dispersion around the average separately, provide substantial additional insights into the trade off between the average performance, and the dispersion around this average. In contrast, the regret-based metrics enhance insight into the relative merits of candidate plans, while being less clear on the average performance or the dispersion around this performance. These results suggest that it is beneficial to use multiple robustness metrics when doing a robust decision analysis study. Haasnoot, M., J. H. Kwakkel, W. E. Walker and J. Ter Maat (2013). "Dynamic Adaptive Policy Pathways: A New Method for Crafting Robust Decisions for a Deeply Uncertain World." Global Environmental Change 23(2): 485-498. Kwakkel, J. H., M. Haasnoot and W. E. Walker (2014). "Developing Dynamic Adaptive Policy Pathways: A computer-assisted approach for developing adaptive strategies for a deeply uncertain world." Climatic Change.

Robust tracking control of a magnetically suspended rigid body

NASA Technical Reports Server (NTRS)

Lim, Kyong B.; Cox, David E.

1994-01-01

This study is an application of H-infinity and micro-synthesis for designing robust tracking controllers for the Large Angle Magnetic Suspension Test Facility. The modeling, design, analysis, simulation, and testing of a control law that guarantees tracking performance under external disturbances and model uncertainties is investigated. The type of uncertainties considered and the tracking performance metric used is discussed. This study demonstrates the tradeoff between tracking performance at low frequencies and robustness at high frequencies. Two sets of controllers were designed and tested. The first set emphasized performance over robustness, while the second set traded off performance for robustness. Comparisons of simulation and test results are also included. Current simulation and experimental results indicate that reasonably good robust tracking performance can be attained for this system using multivariable robust control approach.

Carbon and nitrogen isotopic signatures and nitrogen profile to identify adulteration in organic fertilizers.

PubMed

Verenitch, Sergei; Mazumder, Asit

2012-08-29

Recently it has been shown that stable isotopes of nitrogen can be used to discriminate between organic and synthetic fertilizers, but the robustness of the approach is questionable. This work developed a comprehensive method that is far more robust in identifying an adulteration of organic nitrogen fertilizers. Organic fertilizers of various types (manures, composts, blood meal, bone meal, fish meal, products of poultry and plant productions, molasses and seaweed based, and others) available on the North American market were analyzed to reveal the most sensitive criteria as well as their quantitative ranges, which can be used in their authentication. Organic nitrogen fertilizers of known origins with a wide δ(15)N range between -0.55 and 28.85‰ (n = 1258) were characterized for C and N content, δ(13)C, δ(15)N, viscosity, pH, and nitrogen profile (urea, ammonia, organic N, water insoluble N, and NO3). A statistically significant data set of characterized unique organic nitrogen fertilizers (n = 335) of various known origins has been assembled. Deliberately adulterated samples of different types of organic fertilizers mixed with synthetic fertilizers at a wide range of proportions have been used to develop the quantitative critical characteristics of organic fertilizers as the key indicators of their adulteration. Statistical analysis based on the discriminant functions of the quantitative critical characteristics of organic nitrogen fertilizers from 14 different source materials revealed a very high average rate of correct classification. The developed methodology has been successfully used as a source identification tool for numerous commercial nitrogen fertilizers available on the North American market.

New Phosphospecific Antibody Reveals Isoform-Specific Phosphorylation of CPEB3 Protein

PubMed Central

Sehgal, Kapil; Sylvester, Marc; Skubal, Magdalena; Josten, Michele; Steinhäuser, Christian; De Koninck, Paul; Theis, Martin

2016-01-01

Cytoplasmic Polyadenylation Element Binding proteins (CPEBs) are a family of polyadenylation factors interacting with 3’UTRs of mRNA and thereby regulating gene expression. Various functions of CPEBs in development, synaptic plasticity, and cellular senescence have been reported. Four CPEB family members of partially overlapping functions have been described to date, each containing a distinct alternatively spliced region. This region is highly conserved between CPEBs-2-4 and contains a putative phosphorylation consensus, overlapping with the exon seven of CPEB3. We previously found CPEBs-2-4 splice isoforms containing exon seven to be predominantly present in neurons, and the isoform expression pattern to be cell type-specific. Here, focusing on the alternatively spliced region of CPEB3, we determined that putative neuronal isoforms of CPEB3 are phosphorylated. Using a new phosphospecific antibody directed to the phosphorylation consensus we found Protein Kinase A and Calcium/Calmodulin-dependent Protein Kinase II to robustly phosphorylate CPEB3 in vitro and in primary hippocampal neurons. Interestingly, status epilepticus induced by systemic kainate injection in mice led to specific upregulation of the CPEB3 isoforms containing exon seven. Extensive analysis of CPEB3 phosphorylation in vitro revealed two other phosphorylation sites. In addition, we found plethora of potential kinases that might be targeting the alternatively spliced kinase consensus site of CPEB3. As this site is highly conserved between the CPEB family members, we suggest the existence of a splicing-based regulatory mechanism of CPEB function, and describe a robust phosphospecific antibody to study it in future. PMID:26915047

Phylogeography of Australia's king brown snake (Pseudechis australis) reveals Pliocene divergence and Pleistocene dispersal of a top predator.

PubMed

Kuch, Ulrich; Keogh, J Scott; Weigel, John; Smith, Laurie A; Mebs, Dietrich

2005-03-01

King brown snakes or mulga snakes (Pseudechis australis) are the largest and among the most dangerous and wide-ranging venomous snakes in Australia and New Guinea. They occur in diverse habitats, are important predators, and exhibit considerable morphological variation. We infer the relationships and historical biogeography of P. australis based on phylogenetic analysis of 1,249 base pairs from the mitochondrial cytochrome b, NADH dehydrogenase subunit 4 and three adjacent tRNA genes using Bayesian, maximum-likelihood, and maximum-parsimony methods. All methods reveal deep phylogenetic structure with four strongly supported clades comprising snakes from New Guinea (I), localities all over Australia (II), the Kimberleys of Western Australia (III), and north-central Australia (IV), suggesting a much more ancient radiation than previously believed. This conclusion is robust to different molecular clock estimations indicating divergence in Pliocene or Late Miocene, after landbridge dispersal to New Guinea had occurred. While members of clades I, III and IV are medium-sized, slender snakes, those of clade II attain large sizes and a robust build, rendering them top predators in their ecosystems. Genetic differentiation within clade II is low and haplotype distribution largely incongruent with geography or colour morphs, suggesting Pleistocene dispersal and recent ecomorph evolution. Significant haplotype diversity exists in clades III and IV, implying that clade IV comprises two species. Members of clade II are broadly sympatric with members of both northern Australian clades. Thus, our data support the recognition of at least five species from within P. australis (auct.) under various criteria. We discuss biogeographical, ecological and medical implications of our findings.

Phylogeography of Australia's king brown snake (Pseudechis australis) reveals Pliocene divergence and Pleistocene dispersal of a top predator

NASA Astrophysics Data System (ADS)

Kuch, Ulrich; Keogh, J. Scott; Weigel, John; Smith, Laurie A.; Mebs, Dietrich

2005-03-01

King brown snakes or mulga snakes (Pseudechis australis) are the largest and among the most dangerous and wide-ranging venomous snakes in Australia and New Guinea. They occur in diverse habitats, are important predators, and exhibit considerable morphological variation. We infer the relationships and historical biogeography of P. australis based on phylogenetic analysis of 1,249 base pairs from the mitochondrial cytochrome b, NADH dehydrogenase subunit 4 and three adjacent tRNA genes using Bayesian, maximum-likelihood, and maximum-parsimony methods. All methods reveal deep phylogenetic structure with four strongly supported clades comprising snakes from New Guinea (I), localities all over Australia (II), the Kimberleys of Western Australia (III), and north-central Australia (IV), suggesting a much more ancient radiation than previously believed. This conclusion is robust to different molecular clock estimations indicating divergence in Pliocene or Late Miocene, after landbridge dispersal to New Guinea had occurred. While members of clades I, III and IV are medium-sized, slender snakes, those of clade II attain large sizes and a robust build, rendering them top predators in their ecosystems. Genetic differentiation within clade II is low and haplotype distribution largely incongruent with geography or colour morphs, suggesting Pleistocene dispersal and recent ecomorph evolution. Significant haplotype diversity exists in clades III and IV, implying that clade IV comprises two species. Members of clade II are broadly sympatric with members of both northern Australian clades. Thus, our data support the recognition of at least five species from within P. australis (auct.) under various criteria. We discuss biogeographical, ecological and medical implications of our findings.

Association Mapping Reveals Genetic Loci Associated with Important Agronomic Traits in Lentinula edodes, Shiitake Mushroom

PubMed Central

Li, Chuang; Gong, Wenbing; Zhang, Lin; Yang, Zhiquan; Nong, Wenyan; Bian, Yinbing; Kwan, Hoi-Shan; Cheung, Man-Kit; Xiao, Yang

2017-01-01

Association mapping is a robust approach for the detection of quantitative trait loci (QTLs). Here, by genotyping 297 genome-wide molecular markers of 89 Lentinula edodes cultivars in China, the genetic diversity, population structure and genetic loci associated with 11 agronomic traits were examined. A total of 873 alleles were detected in the tested strains with a mean of 2.939 alleles per locus, and the Shannon's information index was 0.734. Population structure analysis revealed two robustly differentiated groups among the Chinese L. edodes cultivars (FST = 0.247). Using the mixed linear model, a total of 43 markers were detected to be significantly associated with four traits. The number of markers associated with traits ranged from 9 to 26, and the phenotypic variations explained by each marker varied from 12.07% to 31.32%. Apart from five previously reported markers, the remaining 38 markers were newly reported here. Twenty-one markers were identified as simultaneously linked to two to four traits, and five markers were associated with the same traits in cultivation tests performed in two consecutive years. The 43 traits-associated markers were related to 97 genes, and 24 of them were related to 10 traits-associated markers detected in both years or identified previously, 13 of which had a >2-fold expression change between the mycelium and primordium stages. Our study has provided candidate markers for marker-assisted selection (MAS) and useful clues for understanding the genetic architecture of agronomic traits in the shiitake mushroom. PMID:28261189

Connectivity-based parcellation reveals distinct cortico-striatal connectivity fingerprints in Autism Spectrum Disorder.

PubMed

Balsters, Joshua H; Mantini, Dante; Wenderoth, Nicole

2018-04-15

Autism Spectrum Disorder (ASD) has been associated with abnormal synaptic development causing a breakdown in functional connectivity. However, when measured at the macro scale using resting state fMRI, these alterations are subtle and often difficult to detect due to the large heterogeneity of the pathology. Recently, we outlined a novel approach for generating robust biomarkers of resting state functional magnetic resonance imaging (RS-fMRI) using connectivity based parcellation of gross morphological structures to improve single-subject reproducibility and generate more robust connectivity fingerprints. Here we apply this novel approach to investigating the organization and connectivity strength of the cortico-striatal system in a large sample of ASD individuals and typically developed (TD) controls (N=130 per group). Our results showed differences in the parcellation of the striatum in ASD. Specifically, the putamen was found to be one single structure in ASD, whereas this was split into anterior and posterior segments in an age, IQ, and head movement matched TD group. An analysis of the connectivity fingerprints revealed that the group differences in clustering were driven by differential connectivity between striatum and the supplementary motor area, posterior cingulate cortex, and posterior insula. Our approach for analysing RS-fMRI in clinical populations has provided clear evidence that cortico-striatal circuits are organized differently in ASD. Based on previous task-based segmentations of the striatum, we believe that the anterior putamen cluster present in TD, but not in ASD, likely contributes to social and language processes. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Posture Detection Based on Smart Cushion for Wheelchair Users

PubMed Central

Ma, Congcong; Li, Wenfeng; Gravina, Raffaele; Fortino, Giancarlo

2017-01-01

The postures of wheelchair users can reveal their sitting habit, mood, and even predict health risks such as pressure ulcers or lower back pain. Mining the hidden information of the postures can reveal their wellness and general health conditions. In this paper, a cushion-based posture recognition system is used to process pressure sensor signals for the detection of user’s posture in the wheelchair. The proposed posture detection method is composed of three main steps: data level classification for posture detection, backward selection of sensor configuration, and recognition results compared with previous literature. Five supervised classification techniques—Decision Tree (J48), Support Vector Machines (SVM), Multilayer Perceptron (MLP), Naive Bayes, and k-Nearest Neighbor (k-NN)—are compared in terms of classification accuracy, precision, recall, and F-measure. Results indicate that the J48 classifier provides the highest accuracy compared to other techniques. The backward selection method was used to determine the best sensor deployment configuration of the wheelchair. Several kinds of pressure sensor deployments are compared and our new method of deployment is shown to better detect postures of the wheelchair users. Performance analysis also took into account the Body Mass Index (BMI), useful for evaluating the robustness of the method across individual physical differences. Results show that our proposed sensor deployment is effective, achieving 99.47% posture recognition accuracy. Our proposed method is very competitive for posture recognition and robust in comparison with other former research. Accurate posture detection represents a fundamental basic block to develop several applications, including fatigue estimation and activity level assessment. PMID:28353684

Scalable Robust Principal Component Analysis Using Grassmann Averages.

PubMed

Hauberg, Sren; Feragen, Aasa; Enficiaud, Raffi; Black, Michael J

2016-11-01

In large datasets, manual data verification is impossible, and we must expect the number of outliers to increase with data size. While principal component analysis (PCA) can reduce data size, and scalable solutions exist, it is well-known that outliers can arbitrarily corrupt the results. Unfortunately, state-of-the-art approaches for robust PCA are not scalable. We note that in a zero-mean dataset, each observation spans a one-dimensional subspace, giving a point on the Grassmann manifold. We show that the average subspace corresponds to the leading principal component for Gaussian data. We provide a simple algorithm for computing this Grassmann Average ( GA), and show that the subspace estimate is less sensitive to outliers than PCA for general distributions. Because averages can be efficiently computed, we immediately gain scalability. We exploit robust averaging to formulate the Robust Grassmann Average (RGA) as a form of robust PCA. The resulting Trimmed Grassmann Average ( TGA) is appropriate for computer vision because it is robust to pixel outliers. The algorithm has linear computational complexity and minimal memory requirements. We demonstrate TGA for background modeling, video restoration, and shadow removal. We show scalability by performing robust PCA on the entire Star Wars IV movie; a task beyond any current method. Source code is available online.

[Heath and political regimes: presidential or parliamentary government for Colombia?].

PubMed

Idrovo, Alvaro J

2007-01-01

Changing the presidential regime for a parliamentarian one is currently be-ing discussed in Colombia. This preliminary study explores the potential effects on health of both presidential and parliamentary regimes by using world-wide data. An ecological study was undertaken using countries from which comparable information concerning life-expectancy at birth, political regime, economic development, inequality in income, social capital (as measured by general-ised trust or Corruption Perceptions Index), political rights, civil freedom and cultural diversity could be obtained. Life-expectancy at birth and macro-determinants were compared between both political regimes. The co-relationship between these macro-determinants was estimated and the relationship between political regimen and life-expectancy at birth was estimated using robust regression. Crude analysis revealed that parliamentary countries have greater life-expectancy at birth than countries having a presidential regime. Significant co-relationships between all macro-determinants were observed. No differential effects were observed between both political regimes regarding life-expectancy at birth in multiple robust regressions. There is no evidence that presidential or parliamentary regimes provide greater levels of health for the population. It is suggested that public health policies be focused on other macro-determinants having more known effects on health, such as income inequality.

Constructing robust selves after brain injury: positive identity work among members of a female self-help group.

PubMed

Gelech, Jan; Bayly, Melanie; Desjardins, Michel

2017-04-10

Despite common experiences of identity damage, decline, and deterioration, many brain injury survivors succeed in reconstructing robust identities in the wake of injury. Yet, while this accomplishment greatly benefits survivors' quality of life, little is known about how positive identity work might be facilitated or enhanced in therapeutic institutions. Drawing on data from a women's self-help group, we argue that an egalitarian, reflective, strength-focused, and gender-segregated environment can provide female ABI (acquired brain injury) survivors with a fertile scene for identity enhancement and offer unique opportunities for collective identity development. Sociolinguistic interactional analysis revealed four types of positive identity work undertaken within the group: constructing competent selves; tempering the threat of loss and impairment; resisting infantilisation and delegitimisation; and asserting a collective gender identity. This identity work was facilitated by specific programme attributes and activities and contributed to the global project of decentring disability and destigmatising impairments and losses. We call for increased attention to identity issues in brain injury rehabilitation and argue that gender-segregated programming can provide a unique space for female survivors to construct empowering individual and collective identities after injury.

A QC approach to the determination of day-to-day reproducibility and robustness of LC-MS methods for global metabolite profiling in metabonomics/metabolomics.

PubMed

Gika, Helen G; Theodoridis, Georgios A; Earll, Mark; Wilson, Ian D

2012-09-01

An approach to the determination of day-to-day analytical robustness of LC-MS-based methods for global metabolic profiling using a pooled QC sample is presented for the evaluation of metabonomic/metabolomic data. A set of 60 urine samples were repeatedly analyzed on five different days and the day-to-day reproducibility of the data obtained was determined. Multivariate statistical analysis was performed with the aim of evaluating variability and selected peaks were assessed and validated in terms of retention time stability, mass accuracy and intensity. The methodology enables the repeatability/reproducibility of extended analytical runs in large-scale studies to be determined, allowing the elimination of analytical (as opposed to biological) variability, in order to discover true patterns and correlations within the data. The day-to-day variability of the data revealed by this process suggested that, for this particular system, 3 days continuous operation was possible without the need for maintenance and cleaning. Variation was generally based on signal intensity changes over the 7-day period of the study, and was mainly a result of source contamination.

Empirical study using network of semantically related associations in bridging the knowledge gap.

PubMed

Abedi, Vida; Yeasin, Mohammed; Zand, Ramin

2014-11-27

The data overload has created a new set of challenges in finding meaningful and relevant information with minimal cognitive effort. However designing robust and scalable knowledge discovery systems remains a challenge. Recent innovations in the (biological) literature mining tools have opened new avenues to understand the confluence of various diseases, genes, risk factors as well as biological processes in bridging the gaps between the massive amounts of scientific data and harvesting useful knowledge. In this paper, we highlight some of the findings using a text analytics tool, called ARIANA--Adaptive Robust and Integrative Analysis for finding Novel Associations. Empirical study using ARIANA reveals knowledge discovery instances that illustrate the efficacy of such tool. For example, ARIANA can capture the connection between the drug hexamethonium and pulmonary inflammation and fibrosis that caused the tragic death of a healthy volunteer in a 2001 John Hopkins asthma study, even though the abstract of the study was not part of the semantic model. An integrated system, such as ARIANA, could assist the human expert in exploratory literature search by bringing forward hidden associations, promoting data reuse and knowledge discovery as well as stimulating interdisciplinary projects by connecting information across the disciplines.

Application of a random walk model to geographic distributions of animal mitochondrial DNA variation.

PubMed

Neigel, J E; Avise, J C

1993-12-01

In rapidly evolving molecules, such as animal mitochondrial DNA, mutations that delineate specific lineages may not be dispersed at sufficient rates to attain an equilibrium between genetic drift and gene flow. Here we predict conditions that lead to nonequilibrium geographic distributions of mtDNA lineages, test the robustness of these predictions and examine mtDNA data sets for consistency with our model. Under a simple isolation by distance model, the variance of an mtDNA lineage's geographic distribution is expected be proportional to its age. Simulation results indicated that this relationship is fairly robust. Analysis of mtDNA data from natural populations revealed three qualitative distributional patterns: (1) significant departure of lineage structure from equilibrium geographic distributions, a pattern exhibited in three rodent species with limited dispersal; (2) nonsignificant departure from equilibrium expectations, exhibited by two avian and two marine fish species with potentials for relatively long-distance dispersal; and (3) a progression from nonequilibrium distributions for younger lineages to equilibrium distributions for older lineages, a condition displayed by one surveyed avian species. These results demonstrate the advantages of considering mutation and genealogy in the interpretation of mtDNA geographic variation.

Bromamine Decomposition Revisited: A Holistic Approach for Analyzing Acid and Base Catalysis Kinetics.

PubMed

Wahman, David G; Speitel, Gerald E; Katz, Lynn E

2017-11-21

Chloramine chemistry is complex, with a variety of reactions occurring in series and parallel and many that are acid or base catalyzed, resulting in numerous rate constants. Bromide presence increases system complexity even further with possible bromamine and bromochloramine formation. Therefore, techniques for parameter estimation must address this complexity through thoughtful experimental design and robust data analysis approaches. The current research outlines a rational basis for constrained data fitting using Brønsted theory, application of the microscopic reversibility principle to reversible acid or base catalyzed reactions, and characterization of the relative significance of parallel reactions using fictive product tracking. This holistic approach was used on a comprehensive and well-documented data set for bromamine decomposition, allowing new interpretations of existing data by revealing that a previously published reaction scheme was not robust; it was not able to describe monobromamine or dibromamine decay outside of the conditions for which it was calibrated. The current research's simplified model (3 reactions, 17 constants) represented the experimental data better than the previously published model (4 reactions, 28 constants). A final model evaluation was conducted based on representative drinking water conditions to determine a minimal model (3 reactions, 8 constants) applicable for drinking water conditions.

Evolutionary relationships in Panicoid grasses based on plastome phylogenomics (Panicoideae; Poaceae).

PubMed

Burke, Sean V; Wysocki, William P; Zuloaga, Fernando O; Craine, Joseph M; Pires, J Chris; Edger, Patrick P; Mayfield-Jones, Dustin; Clark, Lynn G; Kelchner, Scot A; Duvall, Melvin R

2016-06-18

Panicoideae are the second largest subfamily in Poaceae (grass family), with 212 genera and approximately 3316 species. Previous studies have begun to reveal relationships within the subfamily, but largely lack resolution and/or robust support for certain tribal and subtribal groups. This study aims to resolve these relationships, as well as characterize a putative mitochondrial insert in one linage. 35 newly sequenced Panicoideae plastomes were combined in a phylogenomic study with 37 other species: 15 Panicoideae and 22 from outgroups. A robust Panicoideae topology largely congruent with previous studies was obtained, but with some incongruences with previously reported subtribal relationships. A mitochondrial DNA (mtDNA) to plastid DNA (ptDNA) transfer was discovered in the Paspalum lineage. The phylogenomic analysis returned a topology that largely supports previous studies. Five previously recognized subtribes appear on the topology to be non-monophyletic. Additionally, evidence for mtDNA to ptDNA transfer was identified in both Paspalum fimbriatum and P. dilatatum, and suggests a single rare event that took place in a common progenitor. Finally, the framework from this study can guide larger whole plastome sampling to discern the relationships in Cyperochloeae, Steyermarkochloeae, Gynerieae, and other incertae sedis taxa that are weakly supported or unresolved.

Robust 2DPCA with non-greedy l1 -norm maximization for image analysis.

PubMed

Wang, Rong; Nie, Feiping; Yang, Xiaojun; Gao, Feifei; Yao, Minli

2015-05-01

2-D principal component analysis based on l1 -norm (2DPCA-L1) is a recently developed approach for robust dimensionality reduction and feature extraction in image domain. Normally, a greedy strategy is applied due to the difficulty of directly solving the l1 -norm maximization problem, which is, however, easy to get stuck in local solution. In this paper, we propose a robust 2DPCA with non-greedy l1 -norm maximization in which all projection directions are optimized simultaneously. Experimental results on face and other datasets confirm the effectiveness of the proposed approach.

Analysis and Design of Launch Vehicle Flight Control Systems

NASA Technical Reports Server (NTRS)

Wie, Bong; Du, Wei; Whorton, Mark

2008-01-01

This paper describes the fundamental principles of launch vehicle flight control analysis and design. In particular, the classical concept of "drift-minimum" and "load-minimum" control principles is re-examined and its performance and stability robustness with respect to modeling uncertainties and a gimbal angle constraint is discussed. It is shown that an additional feedback of angle-of-attack or lateral acceleration can significantly improve the overall performance and robustness, especially in the presence of unexpected large wind disturbance. Non-minimum-phase structural filtering of "unstably interacting" bending modes of large flexible launch vehicles is also shown to be effective and robust.

Analysis of Infrared Signature Variation and Robust Filter-Based Supersonic Target Detection

PubMed Central

Sun, Sun-Gu; Kim, Kyung-Tae

2014-01-01

The difficulty of small infrared target detection originates from the variations of infrared signatures. This paper presents the fundamental physics of infrared target variations and reports the results of variation analysis of infrared images acquired using a long wave infrared camera over a 24-hour period for different types of backgrounds. The detection parameters, such as signal-to-clutter ratio were compared according to the recording time, temperature and humidity. Through variation analysis, robust target detection methodologies are derived by controlling thresholds and designing a temporal contrast filter to achieve high detection rate and low false alarm rate. Experimental results validate the robustness of the proposed scheme by applying it to the synthetic and real infrared sequences. PMID:24672290

Respiratory motion correction in dynamic MRI using robust data decomposition registration - application to DCE-MRI.

PubMed

Hamy, Valentin; Dikaios, Nikolaos; Punwani, Shonit; Melbourne, Andrew; Latifoltojar, Arash; Makanyanga, Jesica; Chouhan, Manil; Helbren, Emma; Menys, Alex; Taylor, Stuart; Atkinson, David

2014-02-01

Motion correction in Dynamic Contrast Enhanced (DCE-) MRI is challenging because rapid intensity changes can compromise common (intensity based) registration algorithms. In this study we introduce a novel registration technique based on robust principal component analysis (RPCA) to decompose a given time-series into a low rank and a sparse component. This allows robust separation of motion components that can be registered, from intensity variations that are left unchanged. This Robust Data Decomposition Registration (RDDR) is demonstrated on both simulated and a wide range of clinical data. Robustness to different types of motion and breathing choices during acquisition is demonstrated for a variety of imaged organs including liver, small bowel and prostate. The analysis of clinically relevant regions of interest showed both a decrease of error (15-62% reduction following registration) in tissue time-intensity curves and improved areas under the curve (AUC60) at early enhancement. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Investigation on changes of modularity and robustness by edge-removal mutations in signaling networks.

PubMed

Truong, Cong-Doan; Kwon, Yung-Keun

2017-12-21

Biological networks consisting of molecular components and interactions are represented by a graph model. There have been some studies based on that model to analyze a relationship between structural characteristics and dynamical behaviors in signaling network. However, little attention has been paid to changes of modularity and robustness in mutant networks. In this paper, we investigated the changes of modularity and robustness by edge-removal mutations in three signaling networks. We first observed that both the modularity and robustness increased on average in the mutant network by the edge-removal mutations. However, the modularity change was negatively correlated with the robustness change. This implies that it is unlikely that both the modularity and the robustness values simultaneously increase by the edge-removal mutations. Another interesting finding is that the modularity change was positively correlated with the degree, the number of feedback loops, and the edge betweenness of the removed edges whereas the robustness change was negatively correlated with them. We note that these results were consistently observed in randomly structure networks. Additionally, we identified two groups of genes which are incident to the highly-modularity-increasing and the highly-robustness-decreasing edges with respect to the edge-removal mutations, respectively, and observed that they are likely to be central by forming a connected component of a considerably large size. The gene-ontology enrichment of each of these gene groups was significantly different from the rest of genes. Finally, we showed that the highly-robustness-decreasing edges can be promising edgetic drug-targets, which validates the usefulness of our analysis. Taken together, the analysis of changes of robustness and modularity against edge-removal mutations can be useful to unravel novel dynamical characteristics underlying in signaling networks.

A Merged IQC/SOS Theory for Analysis and Synthesis of Nonlinear Control Systems

DTIC Science & Technology

2015-06-23

constraints. As mentioned previously, this enables new applications of IQCs to analyze the robustness of time-varying and nonlinear systems . This...enables new applications of IQCs to analyze the robustness of time-varying and nonlinear systems . This section considers the analysis of nonlinear systems ...AFRL-AFOSR-VA-TR-2016-0008 A Merged IQC/SOS Theory for Analysis and Synthesis of Nonlinear Control Systems Gary Balas REGENTS OF THE UNIVERSITY OF

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sarovar, Mohan; Zhang, Jun; Zeng, Lishan

Analog quantum simulators (AQS) will likely be the first nontrivial application of quantum technology for predictive simulation. However, there remain questions regarding the degree of confidence that can be placed in the results of AQS since they do not naturally incorporate error correction. Specifically, how do we know whether an analog simulation of a quantum model will produce predictions that agree with the ideal model in the presence of inevitable imperfections? At the same time there is a widely held expectation that certain quantum simulation questions will be robust to errors and perturbations in the underlying hardware. Resolving these twomore » points of view is a critical step in making the most of this promising technology. In this paper we formalize the notion of AQS reliability by determining sensitivity of AQS outputs to underlying parameters, and formulate conditions for robust simulation. Our approach naturally reveals the importance of model symmetries in dictating the robust properties. Finally, to demonstrate the approach, we characterize the robust features of a variety of quantum many-body models.« less

Robust control for a biaxial servo with time delay system based on adaptive tuning technique.

PubMed

Chen, Tien-Chi; Yu, Chih-Hsien

2009-07-01

A robust control method for synchronizing a biaxial servo system motion is proposed in this paper. A new network based cross-coupled control and adaptive tuning techniques are used together to cancel out the skew error. The conventional fixed gain PID cross-coupled controller (CCC) is replaced with the adaptive cross-coupled controller (ACCC) in the proposed control scheme to maintain biaxial servo system synchronization motion. Adaptive-tuning PID (APID) position and velocity controllers provide the necessary control actions to maintain synchronization while following a variable command trajectory. A delay-time compensator (DTC) with an adaptive controller was augmented to set the time delay element, effectively moving it outside the closed loop, enhancing the stability of the robust controlled system. This scheme provides strong robustness with respect to uncertain dynamics and disturbances. The simulation and experimental results reveal that the proposed control structure adapts to a wide range of operating conditions and provides promising results under parameter variations and load changes.

Median Robust Extended Local Binary Pattern for Texture Classification.

PubMed

Liu, Li; Lao, Songyang; Fieguth, Paul W; Guo, Yulan; Wang, Xiaogang; Pietikäinen, Matti

2016-03-01

Local binary patterns (LBP) are considered among the most computationally efficient high-performance texture features. However, the LBP method is very sensitive to image noise and is unable to capture macrostructure information. To best address these disadvantages, in this paper, we introduce a novel descriptor for texture classification, the median robust extended LBP (MRELBP). Different from the traditional LBP and many LBP variants, MRELBP compares regional image medians rather than raw image intensities. A multiscale LBP type descriptor is computed by efficiently comparing image medians over a novel sampling scheme, which can capture both microstructure and macrostructure texture information. A comprehensive evaluation on benchmark data sets reveals MRELBP's high performance-robust to gray scale variations, rotation changes and noise-but at a low computational cost. MRELBP produces the best classification scores of 99.82%, 99.38%, and 99.77% on three popular Outex test suites. More importantly, MRELBP is shown to be highly robust to image noise, including Gaussian noise, Gaussian blur, salt-and-pepper noise, and random pixel corruption.

Reliability of analog quantum simulation

DOE PAGES

Sarovar, Mohan; Zhang, Jun; Zeng, Lishan

2017-01-03

Analog quantum simulators (AQS) will likely be the first nontrivial application of quantum technology for predictive simulation. However, there remain questions regarding the degree of confidence that can be placed in the results of AQS since they do not naturally incorporate error correction. Specifically, how do we know whether an analog simulation of a quantum model will produce predictions that agree with the ideal model in the presence of inevitable imperfections? At the same time there is a widely held expectation that certain quantum simulation questions will be robust to errors and perturbations in the underlying hardware. Resolving these twomore » points of view is a critical step in making the most of this promising technology. In this paper we formalize the notion of AQS reliability by determining sensitivity of AQS outputs to underlying parameters, and formulate conditions for robust simulation. Our approach naturally reveals the importance of model symmetries in dictating the robust properties. Finally, to demonstrate the approach, we characterize the robust features of a variety of quantum many-body models.« less

Robust ferromagnetism in the compressed permanent magnet Sm2Co17

NASA Astrophysics Data System (ADS)

Jeffries, J. R.; Veiga, L. S. I.; Fabbris, G.; Haskel, D.; Huang, P.; Butch, N. P.; McCall, S. K.; Holliday, K.; Jenei, Z.; Xiao, Y.; Chow, P.

2014-09-01

The compound Sm2Co17 displays magnetic properties amenable to permanent magnet applications owing to both the 3d electrons of Co and the 4f electrons of Sm. The long-standing description of the magnetic interactions between the Sm and Co ions implies a truly ferromagnetic configuration, but some recent calculations challenge this axiom, suggesting at least a propensity for ferrimagnetic behavior. We have used high-pressure synchrotron x-ray techniques to characterize the magnetic and structural properties of Sm2Co17 to reveal a robust ferromagnetic state. The local Sm moment is at most weakly affected by compression, and the ordered moments show a surprising resilience to volumetric compressions of nearly 20%. Density functional theory calculations echo the magnetic robustness of Sm2Co17.

The Genome-Wide Interaction Network of Nutrient Stress Genes in Escherichia coli.

PubMed

Côté, Jean-Philippe; French, Shawn; Gehrke, Sebastian S; MacNair, Craig R; Mangat, Chand S; Bharat, Amrita; Brown, Eric D

2016-11-22

Conventional efforts to describe essential genes in bacteria have typically emphasized nutrient-rich growth conditions. Of note, however, are the set of genes that become essential when bacteria are grown under nutrient stress. For example, more than 100 genes become indispensable when the model bacterium Escherichia coli is grown on nutrient-limited media, and many of these nutrient stress genes have also been shown to be important for the growth of various bacterial pathogens in vivo To better understand the genetic network that underpins nutrient stress in E. coli, we performed a genome-scale cross of strains harboring deletions in some 82 nutrient stress genes with the entire E. coli gene deletion collection (Keio) to create 315,400 double deletion mutants. An analysis of the growth of the resulting strains on rich microbiological media revealed an average of 23 synthetic sick or lethal genetic interactions for each nutrient stress gene, suggesting that the network defining nutrient stress is surprisingly complex. A vast majority of these interactions involved genes of unknown function or genes of unrelated pathways. The most profound synthetic lethal interactions were between nutrient acquisition and biosynthesis. Further, the interaction map reveals remarkable metabolic robustness in E. coli through pathway redundancies. In all, the genetic interaction network provides a powerful tool to mine and identify missing links in nutrient synthesis and to further characterize genes of unknown function in E. coli Moreover, understanding of bacterial growth under nutrient stress could aid in the development of novel antibiotic discovery platforms. With the rise of antibiotic drug resistance, there is an urgent need for new antibacterial drugs. Here, we studied a group of genes that are essential for the growth of Escherichia coli under nutrient limitation, culture conditions that arguably better represent nutrient availability during an infection than rich microbiological media. Indeed, many such nutrient stress genes are essential for infection in a variety of pathogens. Thus, the respective proteins represent a pool of potential new targets for antibacterial drugs that have been largely unexplored. We have created all possible double deletion mutants through a genetic cross of nutrient stress genes and the E. coli deletion collection. An analysis of the growth of the resulting clones on rich media revealed a robust, dense, and complex network for nutrient acquisition and biosynthesis. Importantly, our data reveal new genetic connections to guide innovative approaches for the development of new antibacterial compounds targeting bacteria under nutrient stress. Copyright © 2016 Côté et al.

The developmental genetics of biological robustness

PubMed Central

Mestek Boukhibar, Lamia; Barkoulas, Michalis

2016-01-01

Background Living organisms are continuously confronted with perturbations, such as environmental changes that include fluctuations in temperature and nutrient availability, or genetic changes such as mutations. While some developmental systems are affected by such challenges and display variation in phenotypic traits, others continue consistently to produce invariable phenotypes despite perturbation. This ability of a living system to maintain an invariable phenotype in the face of perturbations is termed developmental robustness. Biological robustness is a phenomenon observed across phyla, and studying its mechanisms is central to deciphering the genotype–phenotype relationship. Recent work in yeast, animals and plants has shown that robustness is genetically controlled and has started to reveal the underlying mechinisms behind it. Scope and Conclusions Studying biological robustness involves focusing on an important property of developmental traits, which is the phenotypic distribution within a population. This is often neglected because the vast majority of developmental biology studies instead focus on population aggregates, such as trait averages. By drawing on findings in animals and yeast, this Viewpoint considers how studies on plant developmental robustness may benefit from strict definitions of what is the developmental system of choice and what is the relevant perturbation, and also from clear distinctions between gene effects on the trait mean and the trait variance. Recent advances in quantitative developmental biology and high-throughput phenotyping now allow the design of targeted genetic screens to identify genes that amplify or restrict developmental trait variance and to study how variation propagates across different phenotypic levels in biological systems. The molecular characterization of more quantitative trait loci affecting trait variance will provide further insights into the evolution of genes modulating developmental robustness. The study of robustness mechanisms in closely related species will address whether mechanisms of robustness are evolutionarily conserved. PMID:26292993

Designing Flood Management Systems for Joint Economic and Ecological Robustness

NASA Astrophysics Data System (ADS)

Spence, C. M.; Grantham, T.; Brown, C. M.; Poff, N. L.

2015-12-01

Freshwater ecosystems across the United States are threatened by hydrologic change caused by water management operations and non-stationary climate trends. Nonstationary hydrology also threatens flood management systems' performance. Ecosystem managers and flood risk managers need tools to design systems that achieve flood risk reduction objectives while sustaining ecosystem functions and services in an uncertain hydrologic future. Robust optimization is used in water resources engineering to guide system design under climate change uncertainty. Using principles introduced by Eco-Engineering Decision Scaling (EEDS), we extend robust optimization techniques to design flood management systems that meet both economic and ecological goals simultaneously across a broad range of future climate conditions. We use three alternative robustness indices to identify flood risk management solutions that preserve critical ecosystem functions in a case study from the Iowa River, where recent severe flooding has tested the limits of the existing flood management system. We seek design modifications to the system that both reduce expected cost of flood damage while increasing ecologically beneficial inundation of riparian floodplains across a wide range of plausible climate futures. The first robustness index measures robustness as the fraction of potential climate scenarios in which both engineering and ecological performance goals are met, implicitly weighting each climate scenario equally. The second index builds on the first by using climate projections to weight each climate scenario, prioritizing acceptable performance in climate scenarios most consistent with climate projections. The last index measures robustness as mean performance across all climate scenarios, but penalizes scenarios with worse performance than average, rewarding consistency. Results stemming from alternate robustness indices reflect implicit assumptions about attitudes toward risk and reveal the tradeoffs between using structural and non-structural flood management strategies to ensure economic and ecological robustness.

An Integrated Proteomics and Bioinformatics Approach Reveals the Anti-inflammatory Mechanism of Carnosic Acid

PubMed Central

Wang, Li-Chao; Wei, Wen-Hui; Zhang, Xiao-Wen; Liu, Dan; Zeng, Ke-Wu; Tu, Peng-Fei

2018-01-01

Drastic macrophages activation triggered by exogenous infection or endogenous stresses is thought to be implicated in the pathogenesis of various inflammatory diseases. Carnosic acid (CA), a natural phenolic diterpene extracted from Salvia officinalis plant, has been reported to possess anti-inflammatory activity. However, its role in macrophages activation as well as potential molecular mechanism is largely unexplored. In the current study, we sought to elucidate the anti-inflammatory property of CA using an integrated approach based on unbiased proteomics and bioinformatics analysis. CA significantly inhibited the robust increase of nitric oxide and TNF-α, downregulated COX2 protein expression, and lowered the transcriptional level of inflammatory genes including Nos2, Tnfα, Cox2, and Mcp1 in LPS-stimulated RAW264.7 cells, a murine model of peritoneal macrophage cell line. The LC-MS/MS-based shotgun proteomics analysis showed CA negatively regulated 217 LPS-elicited proteins which were involved in multiple inflammatory processes including MAPK, nuclear factor (NF)-κB, and FoxO signaling pathways. A further molecular biology analysis revealed that CA effectually inactivated IKKβ/IκB-α/NF-κB, ERK/JNK/p38 MAPKs, and FoxO1/3 signaling pathways. Collectively, our findings demonstrated the role of CA in regulating inflammation response and provide some insights into the proteomics-guided pharmacological mechanism study of natural products. PMID:29713284

Non-linear Min protein interactions generate harmonics that signal mid-cell division in Escherichia coli

PubMed Central

Walsh, James C.; Angstmann, Christopher N.; Duggin, Iain G.

2017-01-01

The Min protein system creates a dynamic spatial pattern in Escherichia coli cells where the proteins MinD and MinE oscillate from pole to pole. MinD positions MinC, an inhibitor of FtsZ ring formation, contributing to the mid-cell localization of cell division. In this paper, Fourier analysis is used to decompose experimental and model MinD spatial distributions into time-dependent harmonic components. In both experiment and model, the second harmonic component is responsible for producing a mid-cell minimum in MinD concentration. The features of this harmonic are robust in both experiment and model. Fourier analysis reveals a close correspondence between the time-dependent behaviour of the harmonic components in the experimental data and model. Given this, each molecular species in the model was analysed individually. This analysis revealed that membrane-bound MinD dimer shows the mid-cell minimum with the highest contrast when averaged over time, carrying the strongest signal for positioning the cell division ring. This concurs with previous data showing that the MinD dimer binds to MinC inhibiting FtsZ ring formation. These results show that non-linear interactions of Min proteins are essential for producing the mid-cell positioning signal via the generation of second-order harmonic components in the time-dependent spatial protein distribution. PMID:29040283

META-ANALYSIS OF CYP2D6 METABOLIZER PHENOTYPE AND METOPROLOL PHARMACOKINETICS

PubMed Central

Blake, CM; Kharasch, ED; Schwab, M; Nagele, P

2013-01-01

Metoprolol, a commonly prescribed beta-blocker, is primarily metabolized by cytochrome P450 2D6 (CYP2D6), an enzyme with substantial genetic heterogeneity. Several smaller studies have shown that metoprolol pharmacokinetics is influenced by CYP2D6 genotype and metabolizer phenotype. To increase robustness of metoprolol pharmacokinetic estimates, a systematic review and meta-analysis of pharmacokinetic studies that administered a single oral dose of immediate release metoprolol was performed. Pooled analysis (n= 264) demonstrated differences in peak plasma metoprolol concentration, area under the concentration-time curve, elimination half-life, and apparent oral clearance that were 2.3-, 4.9-, 2.3-, and 5.9-fold between extensive and poor metabolizers, respectively, and 5.3-, 13-, 2.6-, and 15-fold between ultra-rapid and poor metabolizers (all p<0.001). Enantiomer-specific analysis revealed genotype-dependent enantio-selective metabolism, with nearly 40% greater R- vs S-metoprolol metabolism in ultra-rapid and extensive metabolizers. This study demonstrates a marked effect of CYP2D6 metabolizer phenotype on metoprolol pharmacokinetics and confirms enantiomer specific metabolism of metoprolol. PMID:23665868

A novel computer algorithm improves antibody epitope prediction using affinity-selected mimotopes: a case study using monoclonal antibodies against the West Nile virus E protein.

PubMed

Denisova, Galina F; Denisov, Dimitri A; Yeung, Jeffrey; Loeb, Mark B; Diamond, Michael S; Bramson, Jonathan L

2008-11-01

Understanding antibody function is often enhanced by knowledge of the specific binding epitope. Here, we describe a computer algorithm that permits epitope prediction based on a collection of random peptide epitopes (mimotopes) isolated by antibody affinity purification. We applied this methodology to the prediction of epitopes for five monoclonal antibodies against the West Nile virus (WNV) E protein, two of which exhibit therapeutic activity in vivo. This strategy was validated by comparison of our results with existing F(ab)-E protein crystal structures and mutational analysis by yeast surface display. We demonstrate that by combining the results of the mimotope method with our data from mutational analysis, epitopes could be predicted with greater certainty. The two methods displayed great complementarity as the mutational analysis facilitated epitope prediction when the results with the mimotope method were equivocal and the mimotope method revealed a broader number of residues within the epitope than the mutational analysis. Our results demonstrate that the combination of these two prediction strategies provides a robust platform for epitope characterization.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wiebenga, J. H.; Atzema, E. H.; Boogaard, A. H. van den

Robust design of forming processes using numerical simulations is gaining attention throughout the industry. In this work, it is demonstrated how robust optimization can assist in further stretching the limits of metal forming processes. A deterministic and a robust optimization study are performed, considering a stretch-drawing process of a hemispherical cup product. For the robust optimization study, both the effect of material and process scatter are taken into account. For quantifying the material scatter, samples of 41 coils of a drawing quality forming steel have been collected. The stochastic material behavior is obtained by a hybrid approach, combining mechanical testingmore » and texture analysis, and efficiently implemented in a metamodel based optimization strategy. The deterministic and robust optimization results are subsequently presented and compared, demonstrating an increased process robustness and decreased number of product rejects by application of the robust optimization approach.« less

The Fundamental Structure and the Reproduction of Spiral Wave in a Two-Dimensional Excitable Lattice.

PubMed

Qian, Yu; Zhang, Zhaoyang

2016-01-01

In this paper we have systematically investigated the fundamental structure and the reproduction of spiral wave in a two-dimensional excitable lattice. A periodically rotating spiral wave is introduced as the model to reproduce spiral wave artificially. Interestingly, by using the dominant phase-advanced driving analysis method, the fundamental structure containing the loop structure and the wave propagation paths has been revealed, which can expose the periodically rotating orbit of spiral tip and the charity of spiral wave clearly. Furthermore, the fundamental structure is utilized as the core for artificial spiral wave. Additionally, the appropriate parameter region, in which the artificial spiral wave can be reproduced, is studied. Finally, we discuss the robustness of artificial spiral wave to defects.

An Effective Collaborative Mobile Weighted Clustering Schemes for Energy Balancing in Wireless Sensor Networks

PubMed Central

Tang, Chengpei; Shokla, Sanesy Kumcr; Modhawar, George; Wang, Qiang

2016-01-01

Collaborative strategies for mobile sensor nodes ensure the efficiency and the robustness of data processing, while limiting the required communication bandwidth. In order to solve the problem of pipeline inspection and oil leakage monitoring, a collaborative weighted mobile sensing scheme is proposed. By adopting a weighted mobile sensing scheme, the adaptive collaborative clustering protocol can realize an even distribution of energy load among the mobile sensor nodes in each round, and make the best use of battery energy. A detailed theoretical analysis and experimental results revealed that the proposed protocol is an energy efficient collaborative strategy such that the sensor nodes can communicate with a fusion center and produce high power gain. PMID:26907285

Exploring Galaxy Formation and Evolution via Structural Decomposition

NASA Astrophysics Data System (ADS)

Kelvin, Lee; Driver, Simon; Robotham, Aaron; Hill, David; Cameron, Ewan

2010-06-01

The Galaxy And Mass Assembly (GAMA) structural decomposition pipeline (GAMA-SIGMA Structural Investigation of Galaxies via Model Analysis) will provide multi-component information for a sample of ~12,000 galaxies across 9 bands ranging from near-UV to near-IR. This will allow the relationship between structural properties and broadband, optical-to-near-IR, spectral energy distributions of bulge, bar, and disk components to be explored, revealing clues as to the history of baryonic mass assembly within a hierarchical clustering framework. Data is initially taken from the SDSS & UKIDSS-LAS surveys to test the robustness of our automated decomposition pipeline. This will eventually be replaced with the forthcoming higher-resolution VST & VISTA surveys data, expanding the sample to ~30,000 galaxies.

QSAR study of curcumine derivatives as HIV-1 integrase inhibitors.

PubMed

Gupta, Pawan; Sharma, Anju; Garg, Prabha; Roy, Nilanjan

2013-03-01

A QSAR study was performed on curcumine derivatives as HIV-1 integrase inhibitors using multiple linear regression. The statistically significant model was developed with squared correlation coefficients (r(2)) 0.891 and cross validated r(2) (r(2) cv) 0.825. The developed model revealed that electronic, shape, size, geometry, substitution's information and hydrophilicity were important atomic properties for determining the inhibitory activity of these molecules. The model was also tested successfully for external validation (r(2) pred = 0.849) as well as Tropsha's test for model predictability. Furthermore, the domain analysis was carried out to evaluate the prediction reliability of external set molecules. The model was statistically robust and had good predictive power which can be successfully utilized for screening of new molecules.

Robustness surfaces of complex networks

NASA Astrophysics Data System (ADS)

Manzano, Marc; Sahneh, Faryad; Scoglio, Caterina; Calle, Eusebi; Marzo, Jose Luis

2014-09-01

Despite the robustness of complex networks has been extensively studied in the last decade, there still lacks a unifying framework able to embrace all the proposed metrics. In the literature there are two open issues related to this gap: (a) how to dimension several metrics to allow their summation and (b) how to weight each of the metrics. In this work we propose a solution for the two aforementioned problems by defining the R*-value and introducing the concept of robustness surface (Ω). The rationale of our proposal is to make use of Principal Component Analysis (PCA). We firstly adjust to 1 the initial robustness of a network. Secondly, we find the most informative robustness metric under a specific failure scenario. Then, we repeat the process for several percentage of failures and different realizations of the failure process. Lastly, we join these values to form the robustness surface, which allows the visual assessment of network robustness variability. Results show that a network presents different robustness surfaces (i.e., dissimilar shapes) depending on the failure scenario and the set of metrics. In addition, the robustness surface allows the robustness of different networks to be compared.

Robustness surfaces of complex networks.

PubMed

Manzano, Marc; Sahneh, Faryad; Scoglio, Caterina; Calle, Eusebi; Marzo, Jose Luis

2014-09-02

Despite the robustness of complex networks has been extensively studied in the last decade, there still lacks a unifying framework able to embrace all the proposed metrics. In the literature there are two open issues related to this gap: (a) how to dimension several metrics to allow their summation and (b) how to weight each of the metrics. In this work we propose a solution for the two aforementioned problems by defining the R*-value and introducing the concept of robustness surface (Ω). The rationale of our proposal is to make use of Principal Component Analysis (PCA). We firstly adjust to 1 the initial robustness of a network. Secondly, we find the most informative robustness metric under a specific failure scenario. Then, we repeat the process for several percentage of failures and different realizations of the failure process. Lastly, we join these values to form the robustness surface, which allows the visual assessment of network robustness variability. Results show that a network presents different robustness surfaces (i.e., dissimilar shapes) depending on the failure scenario and the set of metrics. In addition, the robustness surface allows the robustness of different networks to be compared.

Developing Uncertainty Models for Robust Flutter Analysis Using Ground Vibration Test Data

NASA Technical Reports Server (NTRS)

Potter, Starr; Lind, Rick; Kehoe, Michael W. (Technical Monitor)

2001-01-01

A ground vibration test can be used to obtain information about structural dynamics that is important for flutter analysis. Traditionally, this information#such as natural frequencies of modes#is used to update analytical models used to predict flutter speeds. The ground vibration test can also be used to obtain uncertainty models, such as natural frequencies and their associated variations, that can update analytical models for the purpose of predicting robust flutter speeds. Analyzing test data using the -norm, rather than the traditional 2-norm, is shown to lead to a minimum-size uncertainty description and, consequently, a least-conservative robust flutter speed. This approach is demonstrated using ground vibration test data for the Aerostructures Test Wing. Different norms are used to formulate uncertainty models and their associated robust flutter speeds to evaluate which norm is least conservative.

Membrane Resonance Enables Stable and Robust Gamma Oscillations

PubMed Central

Moca, Vasile V.; Nikolić, Danko; Singer, Wolf; Mureşan, Raul C.

2014-01-01

Neuronal mechanisms underlying beta/gamma oscillations (20–80 Hz) are not completely understood. Here, we show that in vivo beta/gamma oscillations in the cat visual cortex sometimes exhibit remarkably stable frequency even when inputs fluctuate dramatically. Enhanced frequency stability is associated with stronger oscillations measured in individual units and larger power in the local field potential. Simulations of neuronal circuitry demonstrate that membrane properties of inhibitory interneurons strongly determine the characteristics of emergent oscillations. Exploration of networks containing either integrator or resonator inhibitory interneurons revealed that: (i) Resonance, as opposed to integration, promotes robust oscillations with large power and stable frequency via a mechanism called RING (Resonance INduced Gamma); resonance favors synchronization by reducing phase delays between interneurons and imposes bounds on oscillation cycle duration; (ii) Stability of frequency and robustness of the oscillation also depend on the relative timing of excitatory and inhibitory volleys within the oscillation cycle; (iii) RING can reproduce characteristics of both Pyramidal INterneuron Gamma (PING) and INterneuron Gamma (ING), transcending such classifications; (iv) In RING, robust gamma oscillations are promoted by slow but are impaired by fast inputs. Results suggest that interneuronal membrane resonance can be an important ingredient for generation of robust gamma oscillations having stable frequency. PMID:23042733

The Economic Impact of Closed-Incision Negative-Pressure Therapy in High-Risk Abdominal Incisions: A Cost-Utility Analysis.

PubMed

Chopra, Karan; Gowda, Arvind U; Morrow, Chris; Holton, Luther; Singh, Devinder P

2016-04-01

Complex abdominal wall reconstruction is beset by postoperative complications. A recent meta-analysis comparing the use of closed-incision negative-pressure therapy to standard dressings found a statistically significant reduction in surgical-site infection. The use of closed-incision negative-pressure therapy is gaining acceptance in this population; however, the economic impact of this innovative dressing remains unknown. In this study, a cost-utility analysis was performed assessing closed-incision negative-pressure therapy and standard dressings following closure of abdominal incisions in high-risk patients. Cost-utility methodology involved reviewing literature related to closed-incision negative-pressure therapy in abdominal wall surgery, obtaining utility estimates to calculate quality-adjusted life-year scores for successful surgery and surgery complicated by surgical-site infection, summing costs using Medicare Current Procedural Terminology codes, and creating a decision tree illuminating the most cost-effective dressing strategy. One-way sensitivity analysis was performed to assess the robustness of the results. The aforementioned meta-analysis comparing closed-incision negative-pressure therapy to standard dressings included a subset of five studies assessing abdominal wall surgery in 829 patients (260 closed-incision negative-pressure therapy and 569 standard dressings). Decision tree analysis revealed an estimated savings of $1546.52 and a gain of 0.0024 quality-adjusted life-year with closed-incision negative-pressure therapy compared with standard dressings; therefore, closed-incision negative-pressure therapy is a dominant treatment strategy. One-way sensitivity analysis revealed that closed-incision negative-pressure therapy is a cost-effective option when the surgical-site infection rate is greater than 16.39 percent. The use of closed-incision negative-pressure therapy is cost-saving following closure of abdominal incisions in high-risk patients.

Robust Mokken Scale Analysis by Means of the Forward Search Algorithm for Outlier Detection

ERIC Educational Resources Information Center

Zijlstra, Wobbe P.; van der Ark, L. Andries; Sijtsma, Klaas

2011-01-01

Exploratory Mokken scale analysis (MSA) is a popular method for identifying scales from larger sets of items. As with any statistical method, in MSA the presence of outliers in the data may result in biased results and wrong conclusions. The forward search algorithm is a robust diagnostic method for outlier detection, which we adapt here to…

Gradient descent for robust kernel-based regression

NASA Astrophysics Data System (ADS)

Guo, Zheng-Chu; Hu, Ting; Shi, Lei

2018-06-01

In this paper, we study the gradient descent algorithm generated by a robust loss function over a reproducing kernel Hilbert space (RKHS). The loss function is defined by a windowing function G and a scale parameter σ, which can include a wide range of commonly used robust losses for regression. There is still a gap between theoretical analysis and optimization process of empirical risk minimization based on loss: the estimator needs to be global optimal in the theoretical analysis while the optimization method can not ensure the global optimality of its solutions. In this paper, we aim to fill this gap by developing a novel theoretical analysis on the performance of estimators generated by the gradient descent algorithm. We demonstrate that with an appropriately chosen scale parameter σ, the gradient update with early stopping rules can approximate the regression function. Our elegant error analysis can lead to convergence in the standard L 2 norm and the strong RKHS norm, both of which are optimal in the mini-max sense. We show that the scale parameter σ plays an important role in providing robustness as well as fast convergence. The numerical experiments implemented on synthetic examples and real data set also support our theoretical results.

Robustness of meta-analyses in finding gene × environment interactions

PubMed Central

Shi, Gang; Nehorai, Arye

2017-01-01

Meta-analyses that synthesize statistical evidence across studies have become important analytical tools for genetic studies. Inspired by the success of genome-wide association studies of the genetic main effect, researchers are searching for gene × environment interactions. Confounders are routinely included in the genome-wide gene × environment interaction analysis as covariates; however, this does not control for any confounding effects on the results if covariate × environment interactions are present. We carried out simulation studies to evaluate the robustness to the covariate × environment confounder for meta-regression and joint meta-analysis, which are two commonly used meta-analysis methods for testing the gene × environment interaction or the genetic main effect and interaction jointly. Here we show that meta-regression is robust to the covariate × environment confounder while joint meta-analysis is subject to the confounding effect with inflated type I error rates. Given vast sample sizes employed in genome-wide gene × environment interaction studies, non-significant covariate × environment interactions at the study level could substantially elevate the type I error rate at the consortium level. When covariate × environment confounders are present, type I errors can be controlled in joint meta-analysis by including the covariate × environment terms in the analysis at the study level. Alternatively, meta-regression can be applied, which is robust to potential covariate × environment confounders. PMID:28362796

Investigation of progressive failure robustness and alternate load paths for damage tolerant structures

NASA Astrophysics Data System (ADS)

Marhadi, Kun Saptohartyadi

Structural optimization for damage tolerance under various unforeseen damage scenarios is computationally challenging. It couples non-linear progressive failure analysis with sampling-based stochastic analysis of random damage. The goal of this research was to understand the relationship between alternate load paths available in a structure and its damage tolerance, and to use this information to develop computationally efficient methods for designing damage tolerant structures. Progressive failure of a redundant truss structure subjected to small random variability was investigated to identify features that correlate with robustness and predictability of the structure's progressive failure. The identified features were used to develop numerical surrogate measures that permit computationally efficient deterministic optimization to achieve robustness and predictability of progressive failure. Analysis of damage tolerance on designs with robust progressive failure indicated that robustness and predictability of progressive failure do not guarantee damage tolerance. Damage tolerance requires a structure to redistribute its load to alternate load paths. In order to investigate the load distribution characteristics that lead to damage tolerance in structures, designs with varying degrees of damage tolerance were generated using brute force stochastic optimization. A method based on principal component analysis was used to describe load distributions (alternate load paths) in the structures. Results indicate that a structure that can develop alternate paths is not necessarily damage tolerant. The alternate load paths must have a required minimum load capability. Robustness analysis of damage tolerant optimum designs indicates that designs are tailored to specified damage. A design Optimized under one damage specification can be sensitive to other damages not considered. Effectiveness of existing load path definitions and characterizations were investigated for continuum structures. A load path definition using a relative compliance change measure (U* field) was demonstrated to be the most useful measure of load path. This measure provides quantitative information on load path trajectories and qualitative information on the effectiveness of the load path. The use of the U* description of load paths in optimizing structures for effective load paths was investigated.

Network analyses based on comprehensive molecular interaction maps reveal robust control structures in yeast stress response pathways

PubMed Central

Kawakami, Eiryo; Singh, Vivek K; Matsubara, Kazuko; Ishii, Takashi; Matsuoka, Yukiko; Hase, Takeshi; Kulkarni, Priya; Siddiqui, Kenaz; Kodilkar, Janhavi; Danve, Nitisha; Subramanian, Indhupriya; Katoh, Manami; Shimizu-Yoshida, Yuki; Ghosh, Samik; Jere, Abhay; Kitano, Hiroaki

2016-01-01

Cellular stress responses require exquisite coordination between intracellular signaling molecules to integrate multiple stimuli and actuate specific cellular behaviors. Deciphering the web of complex interactions underlying stress responses is a key challenge in understanding robust biological systems and has the potential to lead to the discovery of targeted therapeutics for diseases triggered by dysregulation of stress response pathways. We constructed large-scale molecular interaction maps of six major stress response pathways in Saccharomyces cerevisiae (baker’s or budding yeast). Biological findings from over 900 publications were converted into standardized graphical formats and integrated into a common framework. The maps are posted at http://www.yeast-maps.org/yeast-stress-response/ for browse and curation by the research community. On the basis of these maps, we undertook systematic analyses to unravel the underlying architecture of the networks. A series of network analyses revealed that yeast stress response pathways are organized in bow–tie structures, which have been proposed as universal sub-systems for robust biological regulation. Furthermore, we demonstrated a potential role for complexes in stabilizing the conserved core molecules of bow–tie structures. Specifically, complex-mediated reversible reactions, identified by network motif analyses, appeared to have an important role in buffering the concentration and activity of these core molecules. We propose complex-mediated reactions as a key mechanism mediating robust regulation of the yeast stress response. Thus, our comprehensive molecular interaction maps provide not only an integrated knowledge base, but also a platform for systematic network analyses to elucidate the underlying architecture in complex biological systems. PMID:28725465

Resolving Recent Plant Radiations: Power and Robustness of Genotyping-by-Sequencing.

PubMed

Fernández-Mazuecos, Mario; Mellers, Greg; Vigalondo, Beatriz; Sáez, Llorenç; Vargas, Pablo; Glover, Beverley J

2018-03-01

Disentangling species boundaries and phylogenetic relationships within recent evolutionary radiations is a challenge due to the poor morphological differentiation and low genetic divergence between species, frequently accompanied by phenotypic convergence, interspecific gene flow and incomplete lineage sorting. Here we employed a genotyping-by-sequencing (GBS) approach, in combination with morphometric analyses, to investigate a small western Mediterranean clade in the flowering plant genus Linaria that radiated in the Quaternary. After confirming the morphological and genetic distinctness of eight species, we evaluated the relative performances of concatenation and coalescent methods to resolve phylogenetic relationships. Specifically, we focused on assessing the robustness of both approaches to variations in the parameter used to estimate sequence homology (clustering threshold). Concatenation analyses suffered from strong systematic bias, as revealed by the high statistical support for multiple alternative topologies depending on clustering threshold values. By contrast, topologies produced by two coalescent-based methods (NJ$_{\\mathrm{st}}$, SVDquartets) were robust to variations in the clustering threshold. Reticulate evolution may partly explain incongruences between NJ$_{\\mathrm{st}}$, SVDquartets and concatenated trees. Integration of morphometric and coalescent-based phylogenetic results revealed (i) extensive morphological divergence associated with recent splits between geographically close or sympatric sister species and (ii) morphological convergence in geographically disjunct species. These patterns are particularly true for floral traits related to pollinator specialization, including nectar spur length, tube width and corolla color, suggesting pollinator-driven diversification. Given its relatively simple and inexpensive implementation, GBS is a promising technique for the phylogenetic and systematic study of recent radiations, but care must be taken to evaluate the robustness of results to variation of data assembly parameters.

GO-based functional dissimilarity of gene sets.

PubMed

Díaz-Díaz, Norberto; Aguilar-Ruiz, Jesús S

2011-09-01

The Gene Ontology (GO) provides a controlled vocabulary for describing the functions of genes and can be used to evaluate the functional coherence of gene sets. Many functional coherence measures consider each pair of gene functions in a set and produce an output based on all pairwise distances. A single gene can encode multiple proteins that may differ in function. For each functionality, other proteins that exhibit the same activity may also participate. Therefore, an identification of the most common function for all of the genes involved in a biological process is important in evaluating the functional similarity of groups of genes and a quantification of functional coherence can helps to clarify the role of a group of genes working together. To implement this approach to functional assessment, we present GFD (GO-based Functional Dissimilarity), a novel dissimilarity measure for evaluating groups of genes based on the most relevant functions of the whole set. The measure assigns a numerical value to the gene set for each of the three GO sub-ontologies. Results show that GFD performs robustly when applied to gene set of known functionality (extracted from KEGG). It performs particularly well on randomly generated gene sets. An ROC analysis reveals that the performance of GFD in evaluating the functional dissimilarity of gene sets is very satisfactory. A comparative analysis against other functional measures, such as GS2 and those presented by Resnik and Wang, also demonstrates the robustness of GFD.

A piggyBac-based reporter system for scalable in vitro and in vivo analysis of 3′ untranslated region-mediated gene regulation

PubMed Central

Chaudhury, Arindam; Kongchan, Natee; Gengler, Jon P.; Mohanty, Vakul; Christiansen, Audrey E.; Fachini, Joseph M.; Martin, James F.; Neilson, Joel R.

2014-01-01

Regulation of messenger ribonucleic acid (mRNA) subcellular localization, stability and translation is a central aspect of gene expression. Much of this control is mediated via recognition of mRNA 3′ untranslated regions (UTRs) by microRNAs (miRNAs) and RNA-binding proteins. The gold standard approach to assess the regulation imparted by a transcript's 3′ UTR is to fuse the UTR to a reporter coding sequence and assess the relative expression of this reporter as compared to a control. Yet, transient transfection approaches or the use of highly active viral promoter elements may overwhelm a cell's post-transcriptional regulatory machinery in this context. To circumvent this issue, we have developed and validated a novel, scalable piggyBac-based vector for analysis of 3′ UTR-mediated regulation in vitro and in vivo. The vector delivers three independent transcription units to the target genome—a selection cassette, a turboGFP control reporter and an experimental reporter expressed under the control of a 3′ UTR of interest. The pBUTR (piggyBac-based 3′ UnTranslated Region reporter) vector performs robustly as a siRNA/miRNA sensor, in established in vitro models of post-transcriptional regulation, and in both arrayed and pooled screening approaches. The vector is robustly expressed as a transgene during murine embryogenesis, highlighting its potential usefulness for revealing post-transcriptional regulation in an in vivo setting. PMID:24753411

Robust prediction of individual creative ability from brain functional connectivity.

PubMed

Beaty, Roger E; Kenett, Yoed N; Christensen, Alexander P; Rosenberg, Monica D; Benedek, Mathias; Chen, Qunlin; Fink, Andreas; Qiu, Jiang; Kwapil, Thomas R; Kane, Michael J; Silvia, Paul J

2018-01-30

People's ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis-connectome-based predictive modeling-to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences ( r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems-intrinsic functional networks that tend to work in opposition-suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks.

Linking log files with dosimetric accuracy--A multi-institutional study on quality assurance of volumetric modulated arc therapy.

PubMed

Pasler, Marlies; Kaas, Jochem; Perik, Thijs; Geuze, Job; Dreindl, Ralf; Künzler, Thomas; Wittkamper, Frits; Georg, Dietmar

2015-12-01

To systematically evaluate machine specific quality assurance (QA) for volumetric modulated arc therapy (VMAT) based on log files by applying a dynamic benchmark plan. A VMAT benchmark plan was created and tested on 18 Elekta linacs (13 MLCi or MLCi2, 5 Agility) at 4 different institutions. Linac log files were analyzed and a delivery robustness index was introduced. For dosimetric measurements an ionization chamber array was used. Relative dose deviations were assessed by mean gamma for each control point and compared to the log file evaluation. Fourteen linacs delivered the VMAT benchmark plan, while 4 linacs failed by consistently terminating the delivery. The mean leaf error (±1SD) was 0.3±0.2 mm for all linacs. Large MLC maximum errors up to 6.5 mm were observed at reversal positions. Delivery robustness index accounting for MLC position correction (0.8-1.0) correlated with delivery time (80-128 s) and depended on dose rate performance. Dosimetric evaluation indicated in general accurate plan reproducibility with γ(mean)(±1 SD)=0.4±0.2 for 1 mm/1%. However single control point analysis revealed larger deviations and attributed well to log file analysis. The designed benchmark plan helped identify linac related malfunctions in dynamic mode for VMAT. Log files serve as an important additional QA measure to understand and visualize dynamic linac parameters. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Robust L1-norm two-dimensional linear discriminant analysis.

PubMed

Li, Chun-Na; Shao, Yuan-Hai; Deng, Nai-Yang

2015-05-01

In this paper, we propose an L1-norm two-dimensional linear discriminant analysis (L1-2DLDA) with robust performance. Different from the conventional two-dimensional linear discriminant analysis with L2-norm (L2-2DLDA), where the optimization problem is transferred to a generalized eigenvalue problem, the optimization problem in our L1-2DLDA is solved by a simple justifiable iterative technique, and its convergence is guaranteed. Compared with L2-2DLDA, our L1-2DLDA is more robust to outliers and noises since the L1-norm is used. This is supported by our preliminary experiments on toy example and face datasets, which show the improvement of our L1-2DLDA over L2-2DLDA. Copyright © 2015 Elsevier Ltd. All rights reserved.

Enhanced elastin synthesis and maturation in human vascular smooth muscle tissue derived from induced-pluripotent stem cells.

PubMed

Eoh, Joon H; Shen, Nian; Burke, Jacqueline A; Hinderer, Svenja; Xia, Zhiyong; Schenke-Layland, Katja; Gerecht, Sharon

2017-04-01

Obtaining vascular smooth muscle tissue with mature, functional elastic fibers is a key obstacle in tissue-engineered blood vessels. Poor elastin secretion and organization leads to a loss of specialization in contractile smooth muscle cells, resulting in over proliferation and graft failure. In this study, human induced-pluripotent stem cells (hiPSCs) were differentiated into early smooth muscle cells, seeded onto a hybrid poly(ethylene glycol) dimethacrylate/poly (l-lactide) (PEGdma-PLA) scaffold and cultured in a bioreactor while exposed to pulsatile flow, towards maturation into contractile smooth muscle tissue. We evaluated the effects of pulsatile flow on cellular organization as well as elastin expression and assembly in the engineered tissue compared to a static control through immunohistochemistry, gene expression and functionality assays. We show that culturing under pulsatile flow resulted in organized and functional hiPSC derived smooth muscle tissue. Immunohistochemistry analysis revealed hiPSC-smooth muscle tissue with robust, well-organized cells and elastic fibers and the supporting microfibril proteins necessary for elastic fiber assembly. Through qRT-PCR analysis, we found significantly increased expression of elastin, fibronectin, and collagen I, indicating the synthesis of necessary extracellular matrix components. Functionality assays revealed that hiPSC-smooth muscle tissue cultured in the bioreactor had an increased calcium signaling and contraction in response to a cholinergic agonist, significantly higher mature elastin content and improved mechanical properties in comparison to the static control. The findings presented here detail an effective approach to engineering elastic human vascular smooth muscle tissue with the functionality necessary for tissue engineering and regenerative medicine applications. Obtaining robust, mature elastic fibers is a key obstacle in tissue-engineered blood vessels. Human induced-pluripotent stem cells have become of interest due to their ability to supplement tissue engineered scaffolds. Their ability to differentiate into cells of vascular lineages with defined phenotypes serves as a potential solution to a major cause of graft failure in which phenotypic shifts in smooth muscle cells lead to over proliferation and occlusion of the graft. Herein, we have differentiated human induced-pluripotent stem cells in a pulsatile flow bioreactor, resulting in vascular smooth muscle tissue with robust elastic fibers and enhanced functionality. This study highlights an effective approach to engineering elastic functional vascular smooth muscle tissue for tissue engineering and regenerative medicine applications. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

When Can Categorical Variables Be Treated as Continuous? A Comparison of Robust Continuous and Categorical SEM Estimation Methods under Suboptimal Conditions

ERIC Educational Resources Information Center

Rhemtulla, Mijke; Brosseau-Liard, Patricia E.; Savalei, Victoria

2012-01-01

A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…

Robust dynamic inversion controller design and analysis (using the X-38 vehicle as a case study)

NASA Astrophysics Data System (ADS)

Ito, Daigoro

A new way to approach robust Dynamic Inversion controller synthesis is addressed in this paper. A Linear Quadratic Gaussian outer-loop controller improves the robustness of a Dynamic Inversion inner-loop controller in the presence of uncertainties. Desired dynamics are given by the dynamic compensator, which shapes the loop. The selected dynamics are based on both performance and stability robustness requirements. These requirements are straightforwardly formulated as frequency-dependent singular value bounds during synthesis of the controller. Performance and robustness of the designed controller is tested using a worst case time domain quadratic index, which is a simple but effective way to measure robustness due to parameter variation. Using this approach, a lateral-directional controller for the X-38 vehicle is designed and its robustness to parameter variations and disturbances is analyzed. It is found that if full state measurements are available, the performance of the designed lateral-directional control system, measured by the chosen cost function, improves by approximately a factor of four. Also, it is found that the designed system is stable up to a parametric variation of 1.65 standard deviation with the set of uncertainty considered. The system robustness is determined to be highly sensitive to the dihedral derivative and the roll damping coefficients. The controller analysis is extended to the nonlinear system where both control input displacements and rates are bounded. In this case, the considered nonlinear system is stable up to 48.1° in bank angle and 1.59° in sideslip angle variations, indicating it is more sensitive to variations in sideslip angle than in bank angle. This nonlinear approach is further extended for the actuator failure mode analysis. The results suggest that the designed system maintains a high level of stability in the event of aileron failure. However, only 35% or less of the original stability range is maintained for the rudder failure case. Overall, this combination of controller synthesis and robustness criteria compares well with the mu-synthesis technique. It also is readily accessible to the practicing engineer, in terms of understanding and use.

Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer.

PubMed

Singanamalli, Asha; Rusu, Mirabela; Sparks, Rachel E; Shih, Natalie N C; Ziober, Amy; Wang, Li-Ping; Tomaszewski, John; Rosen, Mark; Feldman, Michael; Madabhushi, Anant

2016-01-01

To identify computer extracted in vivo dynamic contrast enhanced (DCE) MRI markers associated with quantitative histomorphometric (QH) characteristics of microvessels and Gleason scores (GS) in prostate cancer. This study considered retrospective data from 23 biopsy confirmed prostate cancer patients who underwent 3 Tesla multiparametric MRI before radical prostatectomy (RP). Representative slices from RP specimens were stained with vascular marker CD31. Tumor extent was mapped from RP sections onto DCE MRI using nonlinear registration methods. Seventy-seven microvessel QH features and 18 DCE MRI kinetic features were extracted and evaluated for their ability to distinguish low from intermediate and high GS. The effect of temporal sampling on kinetic features was assessed and correlations between those robust to temporal resolution and microvessel features discriminative of GS were examined. A total of 12 microvessel architectural features were discriminative of low and intermediate/high grade tumors with area under the receiver operating characteristic curve (AUC) > 0.7. These features were most highly correlated with mean washout gradient (WG) (max rho = -0.62). Independent analysis revealed WG to be moderately robust to temporal resolution (intraclass correlation coefficient [ICC] = 0.63) and WG variance, which was poorly correlated with microvessel features, to be predictive of low grade tumors (AUC = 0.77). Enhancement ratio was the most robust (ICC = 0.96) and discriminative (AUC = 0.78) kinetic feature but was moderately correlated with microvessel features (max rho = -0.52). Computer extracted features of prostate DCE MRI appear to be correlated with microvessel architecture and may be discriminative of low versus intermediate and high GS. © 2015 Wiley Periodicals, Inc.

Automated Image Registration Using Morphological Region of Interest Feature Extraction

NASA Technical Reports Server (NTRS)

Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

2005-01-01

With the recent explosion in the amount of remotely sensed imagery and the corresponding interest in temporal change detection and modeling, image registration has become increasingly important as a necessary first step in the integration of multi-temporal and multi-sensor data for applications such as the analysis of seasonal and annual global climate changes, as well as land use/cover changes. The task of image registration can be divided into two major components: (1) the extraction of control points or features from images; and (2) the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual control feature extraction can be subjective and extremely time consuming, and often results in few usable points. Automated feature extraction is a solution to this problem, where desired target features are invariant, and represent evenly distributed landmarks such as edges, corners and line intersections. In this paper, we develop a novel automated registration approach based on the following steps. First, a mathematical morphology (MM)-based method is used to obtain a scale-orientation morphological profile at each image pixel. Next, a spectral dissimilarity metric such as the spectral information divergence is applied for automated extraction of landmark chips, followed by an initial approximate matching. This initial condition is then refined using a hierarchical robust feature matching (RFM) procedure. Experimental results reveal that the proposed registration technique offers a robust solution in the presence of seasonal changes and other interfering factors. Keywords-Automated image registration, multi-temporal imagery, mathematical morphology, robust feature matching.

Robustness analysis of elastoplastic structure subjected to double impulse

NASA Astrophysics Data System (ADS)

Kanno, Yoshihiro; Takewaki, Izuru

2016-11-01

The double impulse has extensively been used to evaluate the critical response of an elastoplastic structure against a pulse-type input, including near-fault earthquake ground motions. In this paper, we propose a robustness assessment method for elastoplastic single-degree-of-freedom structures subjected to the double impulse input. Uncertainties in the initial velocity of the input, as well as the natural frequency and the strength of the structure, are considered. As fundamental properties of the structural robustness, we show monotonicity of the robustness measure with respect to the natural frequency. In contrast, we show that robustness is not necessarily improved even if the structural strength is increased. Moreover, the robustness preference between two structures with different values of structural strength can possibly reverse when the performance requirement is changed.

Practical robustness measures in multivariable control system analysis. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Lehtomaki, N. A.

1981-01-01

The robustness of the stability of multivariable linear time invariant feedback control systems with respect to model uncertainty is considered using frequency domain criteria. Available robustness tests are unified under a common framework based on the nature and structure of model errors. These results are derived using a multivariable version of Nyquist's stability theorem in which the minimum singular value of the return difference transfer matrix is shown to be the multivariable generalization of the distance to the critical point on a single input, single output Nyquist diagram. Using the return difference transfer matrix, a very general robustness theorem is presented from which all of the robustness tests dealing with specific model errors may be derived. The robustness tests that explicitly utilized model error structure are able to guarantee feedback system stability in the face of model errors of larger magnitude than those robustness tests that do not. The robustness of linear quadratic Gaussian control systems are analyzed.

Identification of Four Oxidative Stress-Responsive MicroRNAs, miR-34a-5p, miR-1915-3p, miR-638, and miR-150-3p, in Hepatocellular Carcinoma.

PubMed

Wan, Yong; Cui, Ruixia; Gu, Jingxian; Zhang, Xing; Xiang, Xiaohong; Liu, Chang; Qu, Kai; Lin, Ting

2017-01-01

Increasing evidence suggests that oxidative stress plays an essential role during carcinogenesis. However, the underlying mechanism between oxidative stress and carcinogenesis remains unknown. Recently, microRNAs (miRNAs) are revealed to be involved in oxidative stress response and carcinogenesis. This study aims to identify miRNAs in hepatocellular carcinoma (HCC) cells which might involve in oxidative stress response. An integrated analysis of miRNA expression signature was performed by employing robust rank aggregation (RRA) method, and four miRNAs (miR-34a-5p, miR-1915-3p, miR-638, and miR-150-3p) were identified as the oxidative stress-responsive miRNAs. Pathway enrichment analysis suggested that these four miRNAs played an important role in antiapoptosis process. Our data also revealed miR-34a-5p and miR-1915-3p, but not miR-150-3p and miR-638, were regulated by p53 in HCC cell lines under oxidative stress. In addition, clinical investigation revealed that these four miRNAs might be involved in oxidative stress response by targeting oxidative stress-related genes in HCC tissues. Kaplan-Meier analysis showed that these four miRNAs were associated with patients' overall survival. In conclusion, we identified four oxidative stress-responsive miRNAs, which were regulated by p53-dependent (miR-34a-5p and miR-1915-3p) and p53-independent pathway (miR-150-3p and miR-638). These four miRNAs may offer new strategy for HCC diagnosis and prognosis.

Integrated Genomic Characterization Reveals Novel, Therapeutically Relevant Drug Targets in FGFR and EGFR Pathways in Sporadic Intrahepatic Cholangiocarcinoma

PubMed Central

Liang, Winnie S.; Fonseca, Rafael; Bryce, Alan H.; McCullough, Ann E.; Barrett, Michael T.; Hunt, Katherine; Patel, Maitray D.; Young, Scott W.; Collins, Joseph M.; Silva, Alvin C.; Condjella, Rachel M.; Block, Matthew; McWilliams, Robert R.; Lazaridis, Konstantinos N.; Klee, Eric W.; Bible, Keith C.; Harris, Pamela; Oliver, Gavin R.; Bhavsar, Jaysheel D.; Nair, Asha A.; Middha, Sumit; Asmann, Yan; Kocher, Jean-Pierre; Schahl, Kimberly; Kipp, Benjamin R.; Barr Fritcher, Emily G.; Baker, Angela; Aldrich, Jessica; Kurdoglu, Ahmet; Izatt, Tyler; Christoforides, Alexis; Cherni, Irene; Nasser, Sara; Reiman, Rebecca; Phillips, Lori; McDonald, Jackie; Adkins, Jonathan; Mastrian, Stephen D.; Placek, Pamela; Watanabe, Aprill T.; LoBello, Janine; Han, Haiyong; Von Hoff, Daniel; Craig, David W.; Stewart, A. Keith; Carpten, John D.

2014-01-01

Advanced cholangiocarcinoma continues to harbor a difficult prognosis and therapeutic options have been limited. During the course of a clinical trial of whole genomic sequencing seeking druggable targets, we examined six patients with advanced cholangiocarcinoma. Integrated genome-wide and whole transcriptome sequence analyses were performed on tumors from six patients with advanced, sporadic intrahepatic cholangiocarcinoma (SIC) to identify potential therapeutically actionable events. Among the somatic events captured in our analysis, we uncovered two novel therapeutically relevant genomic contexts that when acted upon, resulted in preliminary evidence of anti-tumor activity. Genome-wide structural analysis of sequence data revealed recurrent translocation events involving the FGFR2 locus in three of six assessed patients. These observations and supporting evidence triggered the use of FGFR inhibitors in these patients. In one example, preliminary anti-tumor activity of pazopanib (in vitro FGFR2 IC50≈350 nM) was noted in a patient with an FGFR2-TACC3 fusion. After progression on pazopanib, the same patient also had stable disease on ponatinib, a pan-FGFR inhibitor (in vitro, FGFR2 IC50≈8 nM). In an independent non-FGFR2 translocation patient, exome and transcriptome analysis revealed an allele specific somatic nonsense mutation (E384X) in ERRFI1, a direct negative regulator of EGFR activation. Rapid and robust disease regression was noted in this ERRFI1 inactivated tumor when treated with erlotinib, an EGFR kinase inhibitor. FGFR2 fusions and ERRFI mutations may represent novel targets in sporadic intrahepatic cholangiocarcinoma and trials should be characterized in larger cohorts of patients with these aberrations. PMID:24550739

TU-H-CAMPUS-JeP1-04: Deformable Image Registration Performances in Pelvis Patients: Impact of CBCT Image Quality

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fusella, M; Loi, G; Fiandra, C

Purpose: To investigate the accuracy and robustness, against image noise and artifacts (typical of CBCT images), of a commercial algorithm for deformable image registration (DIR), to propagate regions of interest (ROIs) in computational phantoms based on real prostate patient images. Methods: The Anaconda DIR algorithm, implemented in RayStation was tested. Two specific Deformation Vector Fields (DVFs) were applied to the reference data set (CTref) using the ImSimQA software, obtaining two deformed CTs. For each dataset twenty-four different level of noise and/or capping artifacts were applied to simulate CBCT images. DIR was performed between CTref and each deformed CTs and CBCTs.more » In order to investigate the relationship between image quality parameters and the DIR results (expressed by a logit transform of the Dice Index) a bilinear regression was defined. Results: More than 550 DIR-mapped ROIs were analyzed. The Statistical analysis states that deformation strenght and artifacts were significant prognostic factors of DIR performances, while noise appeared to have a minor role in DIR process as implemented in RayStation as expected by the image similarity metric built in the registration algorithm. Capping artifacts reveals a determinant role for the accuracy of DIR results. Two optimal values for capping artifacts were found to obtain acceptable DIR results (DICE> 075/ 0.85). Various clinical CBCT acquisition protocol were reported to evaluate the significance of the study. Conclusion: This work illustrates the impact of image quality on DIR performance. Clinical issues like Adaptive Radiation Therapy (ART) and Dose Accumulation need accurate and robust DIR software. The RayStation DIR algorithm resulted robust against noise, but sensitive to image artifacts. This result highlights the need of robustness quality assurance against image noise and artifacts in the commissioning of a DIR commercial system and underlines the importance to adopt optimized protocols for CBCT image acquisitions in ART clinical implementation.« less

A meta-analysis of the relationship between rational beliefs and psychological distress.

PubMed

Oltean, Horea-Radu; David, Daniel Ovidiu

2018-06-01

 Rational emotive behavior therapy (REBT) model of psychological health assumes that rational beliefs cause functional emotions and adaptive behavior, but the presumed role of rational beliefs as protective factor against psychological distress/disorders is still in debate. An important step in validating an evidence-based therapy is to investigate the underling theoretical assumptions. Thus, the aim of the present meta-analysis is to investigate the direction and magnitude of the relationship between rational beliefs and psychological distress.  Our search identified 26 studies that met our criteria. We evaluated the effect size using the random-effects model and we tested the moderator role of several variables. The overall results revealed a medium negative association between rational beliefs and psychological distress, r = -0.31. The strongest association was found for unconditional acceptance beliefs (r = -0.41). The results add empirical evidence for the underling theory of REBT and revealed that the strength of the association between rational beliefs and distress is robust for a wide range of emotional problems. Therefore, rational beliefs could be a trans-diagnostic protective factor against distress. Moreover, results emphasized that rational beliefs type is an important factor, suggesting an increased focus in therapy on the developing of unconditional acceptance and self-acceptance beliefs. © 2017 Wiley Periodicals, Inc.

RNAi-Mediated Reverse Genetic Screen Identified Drosophila Chaperones Regulating Eye and Neuromuscular Junction Morphology.

PubMed

Raut, Sandeep; Mallik, Bhagaban; Parichha, Arpan; Amrutha, Valsakumar; Sahi, Chandan; Kumar, Vimlesh

2017-07-05

Accumulation of toxic proteins in neurons has been linked with the onset of neurodegenerative diseases, which in many cases are characterized by altered neuronal function and synapse loss. Molecular chaperones help protein folding and the resolubilization of unfolded proteins, thereby reducing the protein aggregation stress. While most of the chaperones are expressed in neurons, their functional relevance remains largely unknown. Here, using bioinformatics analysis, we identified 95 Drosophila chaperones and classified them into seven different classes. Ubiquitous actin5C -Gal4-mediated RNAi knockdown revealed that ∼50% of the chaperones are essential in Drosophila Knocking down these genes in eyes revealed that ∼30% of the essential chaperones are crucial for eye development. Using neuron-specific knockdown, immunocytochemistry, and robust behavioral assays, we identified a new set of chaperones that play critical roles in the regulation of Drosophila NMJ structural organization. Together, our data present the first classification and comprehensive analysis of Drosophila chaperones. Our screen identified a new set of chaperones that regulate eye and NMJ morphogenesis. The outcome of the screen reported here provides a useful resource for further elucidating the role of individual chaperones in Drosophila eye morphogenesis and synaptic development. Copyright © 2017 Raut et al.

Simultaneous recordings from the primary visual cortex and lateral geniculate nucleus reveal rhythmic interactions and a cortical source for γ-band oscillations.

PubMed

Bastos, Andre M; Briggs, Farran; Alitto, Henry J; Mangun, George R; Usrey, W Martin

2014-05-28

Oscillatory synchronization of neuronal activity has been proposed as a mechanism to modulate effective connectivity between interacting neuronal populations. In the visual system, oscillations in the gamma-frequency range (30-100 Hz) are thought to subserve corticocortical communication. To test whether a similar mechanism might influence subcortical-cortical communication, we recorded local field potential activity from retinotopically aligned regions in the lateral geniculate nucleus (LGN) and primary visual cortex (V1) of alert macaque monkeys viewing stimuli known to produce strong cortical gamma-band oscillations. As predicted, we found robust gamma-band power in V1. In contrast, visual stimulation did not evoke gamma-band activity in the LGN. Interestingly, an analysis of oscillatory phase synchronization of LGN and V1 activity identified synchronization in the alpha (8-14 Hz) and beta (15-30 Hz) frequency bands. Further analysis of directed connectivity revealed that alpha-band interactions mediated corticogeniculate feedback processing, whereas beta-band interactions mediated geniculocortical feedforward processing. These results demonstrate that although the LGN and V1 display functional interactions in the lower frequency bands, gamma-band activity in the alert monkey is largely an emergent property of cortex. Copyright © 2014 the authors 0270-6474/14/347639-06$15.00/0.

Equation-free analysis of agent-based models and systematic parameter determination

NASA Astrophysics Data System (ADS)

Thomas, Spencer A.; Lloyd, David J. B.; Skeldon, Anne C.

2016-12-01

Agent based models (ABM)s are increasingly used in social science, economics, mathematics, biology and computer science to describe time dependent systems in circumstances where a description in terms of equations is difficult. Yet few tools are currently available for the systematic analysis of ABM behaviour. Numerical continuation and bifurcation analysis is a well-established tool for the study of deterministic systems. Recently, equation-free (EF) methods have been developed to extend numerical continuation techniques to systems where the dynamics are described at a microscopic scale and continuation of a macroscopic property of the system is considered. To date, the practical use of EF methods has been limited by; (1) the over-head of application-specific implementation; (2) the laborious configuration of problem-specific parameters; and (3) large ensemble sizes (potentially) leading to computationally restrictive run-times. In this paper we address these issues with our tool for the EF continuation of stochastic systems, which includes algorithms to systematically configuration problem specific parameters and enhance robustness to noise. Our tool is generic and can be applied to any 'black-box' simulator and determines the essential EF parameters prior to EF analysis. Robustness is significantly improved using our convergence-constraint with a corrector-repeat (C3R) method. This algorithm automatically detects outliers based on the dynamics of the underlying system enabling both an order of magnitude reduction in ensemble size and continuation of systems at much higher levels of noise than classical approaches. We demonstrate our method with application to several ABM models, revealing parameter dependence, bifurcation and stability analysis of these complex systems giving a deep understanding of the dynamical behaviour of the models in a way that is not otherwise easily obtainable. In each case we demonstrate our systematic parameter determination stage for configuring the system specific EF parameters.

Validation of Reference Genes for Robust qRT-PCR Gene Expression Analysis in the Rice Blast Fungus Magnaporthe oryzae.

PubMed

Che Omar, Sarena; Bentley, Michael A; Morieri, Giulia; Preston, Gail M; Gurr, Sarah J

2016-01-01

The rice blast fungus causes significant annual harvest losses. It also serves as a genetically-tractable model to study fungal ingress. Whilst pathogenicity determinants have been unmasked and changes in global gene expression described, we know little about Magnaporthe oryzae cell wall remodelling. Our interests, in wall remodelling genes expressed during infection, vegetative growth and under exogenous wall stress, demand robust choice of reference genes for quantitative Real Time-PCR (qRT-PCR) data normalisation. We describe the expression stability of nine candidate reference genes profiled by qRT-PCR with cDNAs derived during asexual germling development, from sexual stage perithecia and from vegetative mycelium grown under various exogenous stressors. Our Minimum Information for Publication of qRT-PCR Experiments (MIQE) compliant analysis reveals a set of robust reference genes used to track changes in the expression of the cell wall remodelling gene MGG_Crh2 (MGG_00592). We ranked nine candidate reference genes by their expression stability (M) and report the best gene combination needed for reliable gene expression normalisation, when assayed in three tissue groups (Infective, Vegetative, and Global) frequently used in M. oryzae expression studies. We found that MGG_Actin (MGG_03982) and the 40S 27a ribosomal subunit MGG_40s (MGG_02872) proved to be robust reference genes for the Infection group and MGG_40s and MGG_Ef1 (Elongation Factor1-α) for both Vegetative and Global groups. Using the above validated reference genes, M. oryzae MGG_Crh2 expression was found to be significantly (p<0.05) elevated three-fold during vegetative growth as compared with dormant spores and two fold higher under cell wall stress (Congo Red) compared to growth under optimal conditions. We recommend the combinatorial use of two reference genes, belonging to the cytoskeleton and ribosomal synthesis functional groups, MGG_Actin, MGG_40s, MGG_S8 (Ribosomal subunit 40S S8) or MGG_Ef1, which demonstrated low M values across heterogeneous tissues. By contrast, metabolic pathway genes MGG_Fad (FAD binding domain-containing protein) and MGG_Gapdh (Glyceraldehyde-3-phosphate dehydrogenase) performed poorly, due to their lack of expression stability across samples.

The Robustness Analysis of Wireless Sensor Networks under Uncertain Interference

PubMed Central

Deng, Changjian

2013-01-01

Based on the complex network theory, robustness analysis of condition monitoring wireless sensor network under uncertain interference is present. In the evolution of the topology of sensor networks, the density weighted algebraic connectivity is taken into account, and the phenomenon of removing and repairing the link and node in the network is discussed. Numerical simulation is conducted to explore algebraic connectivity characteristics and network robustness performance. It is found that nodes density has the effect on algebraic connectivity distribution in the random graph model; high density nodes carry more connections, use more throughputs, and may be more unreliable. Moreover, the results show that, when network should be more error tolerant or robust by repairing nodes or adding new nodes, the network should be better clustered in median and high scale wireless sensor networks and be meshing topology in small scale networks. PMID:24363613

A comparative robustness evaluation of feedforward neurofilters

NASA Technical Reports Server (NTRS)

Troudet, Terry; Merrill, Walter

1993-01-01

A comparative performance and robustness analysis is provided for feedforward neurofilters trained with back propagation to filter additive white noise. The signals used in this analysis are simulated pitch rate responses to typical pilot command inputs for a modern fighter aircraft model. Various configurations of nonlinear and linear neurofilters are trained to estimate exact signal values from input sequences of noisy sampled signal values. In this application, nonlinear neurofiltering is found to be more efficient than linear neurofiltering in removing the noise from responses of the nominal vehicle model, whereas linear neurofiltering is found to be more robust in the presence of changes in the vehicle dynamics. The possibility of enhancing neurofiltering through hybrid architectures based on linear and nonlinear neuroprocessing is therefore suggested as a way of taking advantage of the robustness of linear neurofiltering, while maintaining the nominal performance advantage of nonlinear neurofiltering.

On-Line Robust Modal Stability Prediction using Wavelet Processing

NASA Technical Reports Server (NTRS)

Brenner, Martin J.; Lind, Rick

1998-01-01

Wavelet analysis for filtering and system identification has been used to improve the estimation of aeroservoelastic stability margins. The conservatism of the robust stability margins is reduced with parametric and nonparametric time- frequency analysis of flight data in the model validation process. Nonparametric wavelet processing of data is used to reduce the effects of external disturbances and unmodeled dynamics. Parametric estimates of modal stability are also extracted using the wavelet transform. Computation of robust stability margins for stability boundary prediction depends on uncertainty descriptions derived from the data for model validation. The F-18 High Alpha Research Vehicle aeroservoelastic flight test data demonstrates improved robust stability prediction by extension of the stability boundary beyond the flight regime. Guidelines and computation times are presented to show the efficiency and practical aspects of these procedures for on-line implementation. Feasibility of the method is shown for processing flight data from time- varying nonstationary test points.

Uncertainty analysis and robust trajectory linearization control of a flexible air-breathing hypersonic vehicle

NASA Astrophysics Data System (ADS)

Pu, Zhiqiang; Tan, Xiangmin; Fan, Guoliang; Yi, Jianqiang

2014-08-01

Flexible air-breathing hypersonic vehicles feature significant uncertainties which pose huge challenges to robust controller designs. In this paper, four major categories of uncertainties are analyzed, that is, uncertainties associated with flexible effects, aerodynamic parameter variations, external environmental disturbances, and control-oriented modeling errors. A uniform nonlinear uncertainty model is explored for the first three uncertainties which lumps all uncertainties together and consequently is beneficial for controller synthesis. The fourth uncertainty is additionally considered in stability analysis. Based on these analyses, the starting point of the control design is to decompose the vehicle dynamics into five functional subsystems. Then a robust trajectory linearization control (TLC) scheme consisting of five robust subsystem controllers is proposed. In each subsystem controller, TLC is combined with the extended state observer (ESO) technique for uncertainty compensation. The stability of the overall closed-loop system with the four aforementioned uncertainties and additional singular perturbations is analyzed. Particularly, the stability of nonlinear ESO is also discussed from a Liénard system perspective. At last, simulations demonstrate the great control performance and the uncertainty rejection ability of the robust scheme.

Respiromics - An integrative analysis linking mitochondrial bioenergetics to molecular signatures.

PubMed

Walheim, Ellen; Wiśniewski, Jacek R; Jastroch, Martin

2018-03-01

Energy metabolism is challenged upon nutrient stress, eventually leading to a variety of metabolic diseases that represent a major global health burden. Here, we combine quantitative mitochondrial respirometry (Seahorse technology) and proteomics (LC-MS/MS-based total protein approach) to understand how molecular changes translate to changes in mitochondrial energy transduction during diet-induced obesity (DIO) in the liver. The integrative analysis reveals that significantly increased palmitoyl-carnitine respiration is supported by an array of proteins enriching lipid metabolism pathways. Upstream of the respiratory chain, the increased capacity for ATP synthesis during DIO associates strongest to mitochondrial uptake of pyruvate, which is routed towards carboxylation. At the respiratory chain, robust increases of complex I are uncovered by cumulative analysis of single subunit concentrations. Specifically, nuclear-encoded accessory subunits, but not mitochondrial-encoded or core units, appear to be permissive for enhanced lipid oxidation. Our integrative analysis, that we dubbed "respiromics", represents an effective tool to link molecular changes to functional mechanisms in liver energy metabolism, and, more generally, can be applied for mitochondrial analysis in a variety of metabolic and mitochondrial disease models. Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.

Image velocimetry and spectral analysis enable quantitative characterization of larval zebrafish gut motility.

PubMed

Ganz, J; Baker, R P; Hamilton, M K; Melancon, E; Diba, P; Eisen, J S; Parthasarathy, R

2018-05-02

Normal gut function requires rhythmic and coordinated movements that are affected by developmental processes, physical and chemical stimuli, and many debilitating diseases. The imaging and characterization of gut motility, especially regarding periodic, propagative contractions driving material transport, are therefore critical goals. Previous image analysis approaches have successfully extracted properties related to the temporal frequency of motility modes, but robust measures of contraction magnitude, especially from in vivo image data, remain challenging to obtain. We developed a new image analysis method based on image velocimetry and spectral analysis that reveals temporal characteristics such as frequency and wave propagation speed, while also providing quantitative measures of the amplitude of gut motion. We validate this approach using several challenges to larval zebrafish, imaged with differential interference contrast microscopy. Both acetylcholine exposure and feeding increase frequency and amplitude of motility. Larvae lacking enteric nervous system gut innervation show the same average motility frequency, but reduced and less variable amplitude compared to wild types. Our image analysis approach enables insights into gut dynamics in a wide variety of developmental and physiological contexts and can also be extended to analyze other types of cell movements. © 2018 John Wiley & Sons Ltd.

Different techniques of multispectral data analysis for vegetation fraction retrieval

NASA Astrophysics Data System (ADS)

Kancheva, Rumiana; Georgiev, Georgi

2012-07-01

Vegetation monitoring is one of the most important applications of remote sensing technologies. In respect to farmlands, the assessment of crop condition constitutes the basis of growth, development, and yield processes monitoring. Plant condition is defined by a set of biometric variables, such as density, height, biomass amount, leaf area index, and etc. The canopy cover fraction is closely related to these variables, and is state-indicative of the growth process. At the same time it is a defining factor of the soil-vegetation system spectral signatures. That is why spectral mixtures decomposition is a primary objective in remotely sensed data processing and interpretation, specifically in agricultural applications. The actual usefulness of the applied methods depends on their prediction reliability. The goal of this paper is to present and compare different techniques for quantitative endmember extraction from soil-crop patterns reflectance. These techniques include: linear spectral unmixing, two-dimensional spectra analysis, spectral ratio analysis (vegetation indices), spectral derivative analysis (red edge position), colorimetric analysis (tristimulus values sum, chromaticity coordinates and dominant wavelength). The objective is to reveal their potential, accuracy and robustness for plant fraction estimation from multispectral data. Regression relationships have been established between crop canopy cover and various spectral estimators.

Associations of Quality of Life with Service Satisfaction in Psychotic Patients: A Meta-Analysis

PubMed Central

Petkari, Eleni; Pietschnig, Jakob

2015-01-01

Background Quality of life (QoL) has gained increasing attention as a desired outcome of psychosocial treatments targeting psychotic patients. Yet, the relationship between the patients’ satisfaction with services and QoL has not been clearly established, perhaps due to the multidimensionality of the QoL concept and the variability in its assessment. Aim This is the first systematic meta-analysis of all available evidence assessing the relationship between QoL and service satisfaction. Methods: In all, 19 studies reporting data of 21 independent samples (N = 5,337) were included in the present meta-analysis. In moderator analyses, effects of age, sex, diagnoses (schizophrenia vs. other psychoses), treatment context (inpatients vs. outpatients), study design (cross-sectional vs. longitudinal), and QoL domain (subjective vs. health-related) were examined. Results Analyses revealed a highly significant medium-sized effect (r = .30, p < .001) for the associations of QoL and service satisfaction. Effect sizes were significantly stronger for subjective than health-related quality of life (r = .35 vs. r = .14, respectively). Moreover, associations with subjective QoL remained largely robust when accounting for moderating variables, although there was a trend of stronger associations for outpatients compared to inpatients. In contrast, effect sizes for health-related QoL were small and only observable for samples with longitudinal designs. Conclusion Associations between QoL and service satisfaction appear to be robust but are differentiated in regard to QoL domain. Our findings suggest that agents responsible for service design and implementation need to take the patients’ perception of the service adequacy for achieving QoL enhancement into account. PMID:26275139

Performance of CMIP3 and CMIP5 GCMs to simulate observed rainfall characteristics over the Western Himalayan region

NASA Astrophysics Data System (ADS)

Meher, J. K.; Das, L.

2017-12-01

The Western Himalayan Region (WHR) was subject to a significant negative trend in the annual and monsoon rainfall during 1902-2005. Annual and seasonal rainfall change over WHR of India was estimated using 22 rain gauge station rainfall data from the India Meteorological Department. The performance of 13 global climate models (GCMs) from the coupled model intercomparison project phase 3 (CMIP3) and 42 GCMs from CMIP5 was evaluated through multiple analysis: the evaluation of the mean annual cycle, annual cycles of interannual variability, spatial patterns, trends and signal-to-noise ratio. In general, CMIP5 GCMs were more skillful in terms of simulating the annual cycle of interannual variability compared to CMIP3 GCMs. The CMIP3 GCMs failed to reproduce the observed trend whereas 50% of the CMIP5 GCMs reproduced the statistical distribution of short-term (30-years) trend-estimates than for the longer term (99-years). GCMs from both CMIP3 and CMIP5 were able to simulate the spatial distribution of observed rainfall in pre-monsoon and winter months. Based on performance, each model of CMIP3 and CMIP5 was given an overall rank, which puts the high resolution version of the MIROC3.2 model (MIROC3.2 hires) and MIROC5 at the top in CMIP3 and CMIP5 respectively. Robustness of the ranking was judged through a sensitivity analysis, which indicated that ranks were independent during the process of adding or removing any individual method. It also revealed that trend analysis was not a robust method of judging performances of the model as compared to other methods.

Robustness surfaces of complex networks

PubMed Central

Manzano, Marc; Sahneh, Faryad; Scoglio, Caterina; Calle, Eusebi; Marzo, Jose Luis

2014-01-01

Despite the robustness of complex networks has been extensively studied in the last decade, there still lacks a unifying framework able to embrace all the proposed metrics. In the literature there are two open issues related to this gap: (a) how to dimension several metrics to allow their summation and (b) how to weight each of the metrics. In this work we propose a solution for the two aforementioned problems by defining the R*-value and introducing the concept of robustness surface (Ω). The rationale of our proposal is to make use of Principal Component Analysis (PCA). We firstly adjust to 1 the initial robustness of a network. Secondly, we find the most informative robustness metric under a specific failure scenario. Then, we repeat the process for several percentage of failures and different realizations of the failure process. Lastly, we join these values to form the robustness surface, which allows the visual assessment of network robustness variability. Results show that a network presents different robustness surfaces (i.e., dissimilar shapes) depending on the failure scenario and the set of metrics. In addition, the robustness surface allows the robustness of different networks to be compared. PMID:25178402

Robust Linear Models for Cis-eQTL Analysis.

PubMed

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.

Instantaneous, Simple, and Reversible Revealing of Invisible Patterns Encrypted in Robust Hollow Sphere Colloidal Photonic Crystals.

PubMed

Zhong, Kuo; Li, Jiaqi; Liu, Liwang; Van Cleuvenbergen, Stijn; Song, Kai; Clays, Koen

2018-05-04

The colors of photonic crystals are based on their periodic crystalline structure. They show clear advantages over conventional chromophores for many applications, mainly due to their anti-photobleaching and responsiveness to stimuli. More specifically, combining colloidal photonic crystals and invisible patterns is important in steganography and watermarking for anticounterfeiting applications. Here a convenient way to imprint robust invisible patterns in colloidal crystals of hollow silica spheres is presented. While these patterns remain invisible under static environmental humidity, even up to near 100% relative humidity, they are unveiled immediately (≈100 ms) and fully reversibly by dynamic humid flow, e.g., human breath. They reveal themselves due to the extreme wettability of the patterned (etched) regions, as confirmed by contact angle measurements. The liquid surface tension threshold to induce wetting (revealing the imprinted invisible images) is evaluated by thermodynamic predictions and subsequently verified by exposure to various vapors with different surface tension. The color of the patterned regions is furthermore independently tuned by vapors with different refractive indices. Such a system can play a key role in applications such as anticounterfeiting, identification, and vapor sensing. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

NASA Astrophysics Data System (ADS)

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.

Identification and robust control of an experimental servo motor.

PubMed

Adam, E J; Guestrin, E D

2002-04-01

In this work, the design of a robust controller for an experimental laboratory-scale position control system based on a dc motor drive as well as the corresponding identification and robust stability analysis are presented. In order to carry out the robust design procedure, first, a classic closed-loop identification technique is applied and then, the parametrization by internal model control is used. The model uncertainty is evaluated under both parametric and global representation. For the latter case, an interesting discussion about the conservativeness of this description is presented by means of a comparison between the uncertainty disk and the critical perturbation radius approaches. Finally, conclusions about the performance of the experimental system with the robust controller are discussed using comparative graphics of the controlled variable and the Nyquist stability margin as a robustness measurement.

The Influence Function of Principal Component Analysis by Self-Organizing Rule.

PubMed

Higuchi; Eguchi

1998-07-28

This article is concerned with a neural network approach to principal component analysis (PCA). An algorithm for PCA by the self-organizing rule has been proposed and its robustness observed through the simulation study by Xu and Yuille (1995). In this article, the robustness of the algorithm against outliers is investigated by using the theory of influence function. The influence function of the principal component vector is given in an explicit form. Through this expression, the method is shown to be robust against any directions orthogonal to the principal component vector. In addition, a statistic generated by the self-organizing rule is proposed to assess the influence of data in PCA.

Sample manipulation and data assembly for robust microcrystal synchrotron crystallography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo, Gongrui; Fuchs, Martin R.; Shi, Wuxian

With the recent developments in microcrystal handling, synchrotron microdiffraction beamline instrumentation and data analysis, microcrystal crystallography with crystal sizes of less than 10 µm is appealing at synchrotrons. However, challenges remain in sample manipulation and data assembly for robust microcrystal synchrotron crystallography. Here, the development of micro-sized polyimide well-mounts for the manipulation of microcrystals of a few micrometres in size and the implementation of a robust data-analysis method for the assembly of rotational microdiffraction data sets from many microcrystals are described. Here, the method demonstrates that microcrystals may be routinely utilized for the acquisition and assembly of complete data setsmore » from synchrotron microdiffraction beamlines.« less

Sample manipulation and data assembly for robust microcrystal synchrotron crystallography

DOE PAGES

Guo, Gongrui; Fuchs, Martin R.; Shi, Wuxian; ...

2018-04-19

With the recent developments in microcrystal handling, synchrotron microdiffraction beamline instrumentation and data analysis, microcrystal crystallography with crystal sizes of less than 10 µm is appealing at synchrotrons. However, challenges remain in sample manipulation and data assembly for robust microcrystal synchrotron crystallography. Here, the development of micro-sized polyimide well-mounts for the manipulation of microcrystals of a few micrometres in size and the implementation of a robust data-analysis method for the assembly of rotational microdiffraction data sets from many microcrystals are described. Here, the method demonstrates that microcrystals may be routinely utilized for the acquisition and assembly of complete data setsmore » from synchrotron microdiffraction beamlines.« less

Efficient and robust analysis of complex scattering data under noise in microwave resonators.

PubMed

Probst, S; Song, F B; Bushev, P A; Ustinov, A V; Weides, M

2015-02-01

Superconducting microwave resonators are reliable circuits widely used for detection and as test devices for material research. A reliable determination of their external and internal quality factors is crucial for many modern applications, which either require fast measurements or operate in the single photon regime with small signal to noise ratios. Here, we use the circle fit technique with diameter correction and provide a step by step guide for implementing an algorithm for robust fitting and calibration of complex resonator scattering data in the presence of noise. The speedup and robustness of the analysis are achieved by employing an algebraic rather than an iterative fit technique for the resonance circle.

Rocket Design for the Future

NASA Technical Reports Server (NTRS)

Follett, William W.; Rajagopal, Raj

2001-01-01

The focus of the AA MDO team is to reduce product development cost through the capture and automation of best design and analysis practices and through increasing the availability of low-cost, high-fidelity analysis. Implementation of robust designs reduces costs associated with the Test-Fall-Fix cycle. RD is currently focusing on several technologies to improve the design process, including optimization and robust design, expert and rule-based systems, and collaborative technologies.

Robust control charts in industrial production of olive oil

NASA Astrophysics Data System (ADS)

Grilo, Luís M.; Mateus, Dina M. R.; Alves, Ana C.; Grilo, Helena L.

2014-10-01

Acidity is one of the most important variables in the quality analysis and characterization of olive oil. During the industrial production we use individuals and moving range charts to monitor this variable, which is not always normal distributed. After a brief exploratory data analysis, where we use the bootstrap method, we construct control charts, before and after a Box-Cox transformation, and compare their robustness and performance.

Closed-Loop Evaluation of an Integrated Failure Identification and Fault Tolerant Control System for a Transport Aircraft

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Belcastro, Christine; Khong, thuan

2006-01-01

Formal robustness analysis of aircraft control upset prevention and recovery systems could play an important role in their validation and ultimate certification. Such systems developed for failure detection, identification, and reconfiguration, as well as upset recovery, need to be evaluated over broad regions of the flight envelope or under extreme flight conditions, and should include various sources of uncertainty. To apply formal robustness analysis, formulation of linear fractional transformation (LFT) models of complex parameter-dependent systems is required, which represent system uncertainty due to parameter uncertainty and actuator faults. This paper describes a detailed LFT model formulation procedure from the nonlinear model of a transport aircraft by using a preliminary LFT modeling software tool developed at the NASA Langley Research Center, which utilizes a matrix-based computational approach. The closed-loop system is evaluated over the entire flight envelope based on the generated LFT model which can cover nonlinear dynamics. The robustness analysis results of the closed-loop fault tolerant control system of a transport aircraft are presented. A reliable flight envelope (safe flight regime) is also calculated from the robust performance analysis results, over which the closed-loop system can achieve the desired performance of command tracking and failure detection.

Contour plot assessment of existing meta-analyses confirms robust association of statin use and acute kidney injury risk.

PubMed

Chevance, Aurélie; Schuster, Tibor; Steele, Russell; Ternès, Nils; Platt, Robert W

2015-10-01

Robustness of an existing meta-analysis can justify decisions on whether to conduct an additional study addressing the same research question. We illustrate the graphical assessment of the potential impact of an additional study on an existing meta-analysis using published data on statin use and the risk of acute kidney injury. A previously proposed graphical augmentation approach is used to assess the sensitivity of the current test and heterogeneity statistics extracted from existing meta-analysis data. In addition, we extended the graphical augmentation approach to assess potential changes in the pooled effect estimate after updating a current meta-analysis and applied the three graphical contour definitions to data from meta-analyses on statin use and acute kidney injury risk. In the considered example data, the pooled effect estimates and heterogeneity indices demonstrated to be considerably robust to the addition of a future study. Supportingly, for some previously inconclusive meta-analyses, a study update might yield statistically significant kidney injury risk increase associated with higher statin exposure. The illustrated contour approach should become a standard tool for the assessment of the robustness of meta-analyses. It can guide decisions on whether to conduct additional studies addressing a relevant research question. Copyright © 2015 Elsevier Inc. All rights reserved.

Discontinuities reveal panarchy in socio-ecological system

EPA Science Inventory

Debates on the organization, structure and dynamics of ecosystems across scales of space and time have waxed and waned in the literature for a century. From successional theory to ecosystem theories of resilience and robustness, from hierarchy to ascendency to panarchy theory, e...

Analytical Round Robin for Elastic-Plastic Analysis of Surface Cracked Plates: Phase I Results

NASA Technical Reports Server (NTRS)

Wells, D. N.; Allen, P. A.

2012-01-01

An analytical round robin for the elastic-plastic analysis of surface cracks in flat plates was conducted with 15 participants. Experimental results from a surface crack tension test in 2219-T8 aluminum plate provided the basis for the inter-laboratory study (ILS). The study proceeded in a blind fashion given that the analysis methodology was not specified to the participants, and key experimental results were withheld. This approach allowed the ILS to serve as a current measure of the state of the art for elastic-plastic fracture mechanics analysis. The analytical results and the associated methodologies were collected for comparison, and sources of variability were studied and isolated. The results of the study revealed that the J-integral analysis methodology using the domain integral method is robust, providing reliable J-integral values without being overly sensitive to modeling details. General modeling choices such as analysis code, model size (mesh density), crack tip meshing, or boundary conditions, were not found to be sources of significant variability. For analyses controlled only by far-field boundary conditions, the greatest source of variability in the J-integral assessment is introduced through the constitutive model. This variability can be substantially reduced by using crack mouth opening displacements to anchor the assessment. Conclusions provide recommendations for analysis standardization.

Review of LMIs, Interior Point Methods, Complexity Theory, and Robustness Analysis

NASA Technical Reports Server (NTRS)

Mesbahi, M.

1996-01-01

From end of intro: ...We would like to show that for certain problems in systems and control theory, there exist algorithms for which corresponding (xi) can be viewed as a certain measure of robustness, e.g., stability margin.

The Fundamental Structure and the Reproduction of Spiral Wave in a Two-Dimensional Excitable Lattice

PubMed Central

Qian, Yu; Zhang, Zhaoyang

2016-01-01

In this paper we have systematically investigated the fundamental structure and the reproduction of spiral wave in a two-dimensional excitable lattice. A periodically rotating spiral wave is introduced as the model to reproduce spiral wave artificially. Interestingly, by using the dominant phase-advanced driving analysis method, the fundamental structure containing the loop structure and the wave propagation paths has been revealed, which can expose the periodically rotating orbit of spiral tip and the charity of spiral wave clearly. Furthermore, the fundamental structure is utilized as the core for artificial spiral wave. Additionally, the appropriate parameter region, in which the artificial spiral wave can be reproduced, is studied. Finally, we discuss the robustness of artificial spiral wave to defects. PMID:26900841

QSAR modeling for anti-human African trypanosomiasis activity of substituted 2-Phenylimidazopyridines

NASA Astrophysics Data System (ADS)

Masand, Vijay H.; El-Sayed, Nahed N. E.; Mahajan, Devidas T.; Mercader, Andrew G.; Alafeefy, Ahmed M.; Shibi, I. G.

2017-02-01

In the present work, sixty substituted 2-Phenylimidazopyridines previously reported with potent anti-human African trypanosomiasis (HAT) activity were selected to build genetic algorithm (GA) based QSAR models to determine the structural features that have significant correlation with the activity. Multiple QSAR models were built using easily interpretable descriptors that are directly associated with the presence or the absence of a structural scaffold, or a specific atom. All the QSAR models have been thoroughly validated according to the OECD principles. All the QSAR models are statistically very robust (R2 = 0.80-0.87) with high external predictive ability (CCCex = 0.81-0.92). The QSAR analysis reveals that the HAT activity has good correlation with the presence of five membered rings in the molecule.

Adolescent personality factors in self-ratings and peer nominations and their prediction of peer acceptance and peer rejection.

PubMed

Scholte, R H; van Aken, M A; van Lieshout, C F

1997-12-01

In this study, the robustness of the Big Five personality factors in adolescents' self-ratings and peer nominations was investigated. Data were obtained on 2,001 adolescents attending secondary school (885 girls; 1,116 boys; M age = 14.5 years). Exploratory and confirmatory factor analyses on the self-ratings confirmed the Big Five personality factors. In contrast, exploratory analysis on the peer nominations revealed five different factors: Aggression-Inattentiveness, Achievement-Withdrawal, Self-Confidence, Sociability, and Emotionality-Nervousness. It is suggested that peers evaluate group members not in terms of their personality but in terms of their group reputation. Peer evaluations contributed substantially to the prediction of peer acceptance and rejection; the Big Five personality factors based on self-ratings did not.

3D/4D multiscale imaging in acute lymphoblastic leukemia cells: visualizing dynamics of cell death

NASA Astrophysics Data System (ADS)

Sarangapani, Sreelatha; Mohan, Rosmin Elsa; Patil, Ajeetkumar; Lang, Matthew J.; Asundi, Anand

2017-06-01

Quantitative phase detection is a new methodology that provides quantitative information on cellular morphology to monitor the cell status, drug response and toxicity. In this paper the morphological changes in acute leukemia cells treated with chitosan were detected using d'Bioimager a robust imaging system. Quantitative phase image of the cells was obtained with numerical analysis. Results show that the average area and optical volume of the chitosan treated cells is significantly reduced when compared with the control cells, which reveals the effect of chitosan on the cancer cells. From the results it can be attributed that d'Bioimager can be used as a non-invasive imaging alternative to measure the morphological changes of the living cells in real time.

Multiplex detection of pancreatic cancer biomarkers using a SERS-based immunoassay

NASA Astrophysics Data System (ADS)

Banaei, Nariman; Foley, Anne; Houghton, Jean Marie; Sun, Yubing; Kim, Byung

2017-11-01

Early diagnosis of pancreatic cancer (PC) is critical to reduce the mortality rate of this disease. Current biological analysis approaches cannot robustly detect several low abundance PC biomarkers in sera, limiting the clinical application of these biomarkers. Enzyme linked immunosorbent assay and radioimmunoassay are two common platforms for detection of biomarkers; however, they suffer from some limitation. This study demonstrates a novel system for multiplex detection of pancreatic biomarkers CA19-9, MMP7 and MUC4 in sera samples with high sensitivity using surface enhanced Raman spectroscopy. Measuring the levels of these biomarkers in PC patients, pancreatitis patients, and healthy individuals reveals the unique expression pattern of these markers in PC patients, suggesting the great potential of using this approach for early diagnostics of PCs.

Source apportionment of soil heavy metals using robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR) receptor model.

PubMed

Qu, Mingkai; Wang, Yan; Huang, Biao; Zhao, Yongcun

2018-06-01

The traditional source apportionment models, such as absolute principal component scores-multiple linear regression (APCS-MLR), are usually susceptible to outliers, which may be widely present in the regional geochemical dataset. Furthermore, the models are merely built on variable space instead of geographical space and thus cannot effectively capture the local spatial characteristics of each source contributions. To overcome the limitations, a new receptor model, robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR), was proposed based on the traditional APCS-MLR model. Then, the new method was applied to the source apportionment of soil metal elements in a region of Wuhan City, China as a case study. Evaluations revealed that: (i) RAPCS-RGWR model had better performance than APCS-MLR model in the identification of the major sources of soil metal elements, and (ii) source contributions estimated by RAPCS-RGWR model were more close to the true soil metal concentrations than that estimated by APCS-MLR model. It is shown that the proposed RAPCS-RGWR model is a more effective source apportionment method than APCS-MLR (i.e., non-robust and global model) in dealing with the regional geochemical dataset. Copyright © 2018 Elsevier B.V. All rights reserved.

Identification of robust adaptation gene regulatory network parameters using an improved particle swarm optimization algorithm.

PubMed

Huang, X N; Ren, H P

2016-05-13

Robust adaptation is a critical ability of gene regulatory network (GRN) to survive in a fluctuating environment, which represents the system responding to an input stimulus rapidly and then returning to its pre-stimulus steady state timely. In this paper, the GRN is modeled using the Michaelis-Menten rate equations, which are highly nonlinear differential equations containing 12 undetermined parameters. The robust adaption is quantitatively described by two conflicting indices. To identify the parameter sets in order to confer the GRNs with robust adaptation is a multi-variable, multi-objective, and multi-peak optimization problem, which is difficult to acquire satisfactory solutions especially high-quality solutions. A new best-neighbor particle swarm optimization algorithm is proposed to implement this task. The proposed algorithm employs a Latin hypercube sampling method to generate the initial population. The particle crossover operation and elitist preservation strategy are also used in the proposed algorithm. The simulation results revealed that the proposed algorithm could identify multiple solutions in one time running. Moreover, it demonstrated a superior performance as compared to the previous methods in the sense of detecting more high-quality solutions within an acceptable time. The proposed methodology, owing to its universality and simplicity, is useful for providing the guidance to design GRN with superior robust adaptation.

Prediction of Hexaconazole Concentration in the Top Most Layer of Oil Palm Plantation Soil Using Exploratory Data Analysis (EDA)

PubMed Central

Maznah, Zainol; Halimah, Muhamad; Shitan, Mahendran; Kumar Karmokar, Provash; Najwa, Sulaiman

2017-01-01

Ganoderma boninense is a fungus that can affect oil palm trees and cause a serious disease called the basal stem root (BSR). This disease causes the death of more than 80% of oil palm trees midway through their economic life and hexaconazole is one of the particular fungicides that can control this fungus. Hexaconazole can be applied by the soil drenching method and it will be of interest to know the concentration of the residue in the soil after treatment with respect to time. Hence, a field study was conducted in order to determine the actual concentration of hexaconazole in soil. In the present paper, a new approach that can be used to predict the concentration of pesticides in the soil is proposed. The statistical analysis revealed that the Exploratory Data Analysis (EDA) techniques would be appropriate in this study. The EDA techniques were used to fit a robust resistant model and predict the concentration of the residue in the topmost layer of the soil. PMID:28060816

Prediction of Hexaconazole Concentration in the Top Most Layer of Oil Palm Plantation Soil Using Exploratory Data Analysis (EDA).

PubMed

Maznah, Zainol; Halimah, Muhamad; Shitan, Mahendran; Kumar Karmokar, Provash; Najwa, Sulaiman

2017-01-01

Ganoderma boninense is a fungus that can affect oil palm trees and cause a serious disease called the basal stem root (BSR). This disease causes the death of more than 80% of oil palm trees midway through their economic life and hexaconazole is one of the particular fungicides that can control this fungus. Hexaconazole can be applied by the soil drenching method and it will be of interest to know the concentration of the residue in the soil after treatment with respect to time. Hence, a field study was conducted in order to determine the actual concentration of hexaconazole in soil. In the present paper, a new approach that can be used to predict the concentration of pesticides in the soil is proposed. The statistical analysis revealed that the Exploratory Data Analysis (EDA) techniques would be appropriate in this study. The EDA techniques were used to fit a robust resistant model and predict the concentration of the residue in the topmost layer of the soil.

Scalable and cost-effective NGS genotyping in the cloud.

PubMed

Souilmi, Yassine; Lancaster, Alex K; Jung, Jae-Yoon; Rizzo, Ettore; Hawkins, Jared B; Powles, Ryan; Amzazi, Saaïd; Ghazal, Hassan; Tonellato, Peter J; Wall, Dennis P

2015-10-15

While next-generation sequencing (NGS) costs have plummeted in recent years, cost and complexity of computation remain substantial barriers to the use of NGS in routine clinical care. The clinical potential of NGS will not be realized until robust and routine whole genome sequencing data can be accurately rendered to medically actionable reports within a time window of hours and at scales of economy in the 10's of dollars. We take a step towards addressing this challenge, by using COSMOS, a cloud-enabled workflow management system, to develop GenomeKey, an NGS whole genome analysis workflow. COSMOS implements complex workflows making optimal use of high-performance compute clusters. Here we show that the Amazon Web Service (AWS) implementation of GenomeKey via COSMOS provides a fast, scalable, and cost-effective analysis of both public benchmarking and large-scale heterogeneous clinical NGS datasets. Our systematic benchmarking reveals important new insights and considerations to produce clinical turn-around of whole genome analysis optimization and workflow management including strategic batching of individual genomes and efficient cluster resource configuration.

Single Stem Cell Imaging and Analysis Reveals Telomere Length Differences in Diseased Human and Mouse Skeletal Muscles.

PubMed

Tichy, Elisia D; Sidibe, David K; Tierney, Matthew T; Stec, Michael J; Sharifi-Sanjani, Maryam; Hosalkar, Harish; Mubarak, Scott; Johnson, F Brad; Sacco, Alessandra; Mourkioti, Foteini

2017-10-10

Muscle stem cells (MuSCs) contribute to muscle regeneration following injury. In many muscle disorders, the repeated cycles of damage and repair lead to stem cell dysfunction. While telomere attrition may contribute to aberrant stem cell functions, methods to accurately measure telomere length in stem cells from skeletal muscles have not been demonstrated. Here, we have optimized and validated such a method, named MuQ-FISH, for analyzing telomere length in MuSCs from either mice or humans. Our analysis showed no differences in telomere length between young and aged MuSCs from uninjured wild-type mice, but MuSCs isolated from young dystrophic mice exhibited significantly shortened telomeres. In corroboration, we demonstrated that telomere attrition is present in human dystrophic MuSCs, which underscores its importance in diseased regenerative failure. The robust technique described herein provides analysis at a single-cell resolution and may be utilized for other cell types, especially rare populations of cells. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Independent component analysis applied to long bunch beams in the Los Alamos Proton Storage Ring

NASA Astrophysics Data System (ADS)

Kolski, Jeffrey S.; Macek, Robert J.; McCrady, Rodney C.; Pang, Xiaoying

2012-11-01

Independent component analysis (ICA) is a powerful blind source separation (BSS) method. Compared to the typical BSS method, principal component analysis, ICA is more robust to noise, coupling, and nonlinearity. The conventional ICA application to turn-by-turn position data from multiple beam position monitors (BPMs) yields information about cross-BPM correlations. With this scheme, multi-BPM ICA has been used to measure the transverse betatron phase and amplitude functions, dispersion function, linear coupling, sextupole strength, and nonlinear beam dynamics. We apply ICA in a new way to slices along the bunch revealing correlations of particle motion within the beam bunch. We digitize beam signals of the long bunch at the Los Alamos Proton Storage Ring with a single device (BPM or fast current monitor) for an entire injection-extraction cycle. ICA of the digitized beam signals results in source signals, which we identify to describe varying betatron motion along the bunch, locations of transverse resonances along the bunch, measurement noise, characteristic frequencies of the digitizing oscilloscopes, and longitudinal beam structure.

A robust control scheme for flexible arms with friction in the joints

NASA Technical Reports Server (NTRS)

Rattan, Kuldip S.; Feliu, Vicente; Brown, H. Benjamin, Jr.

1988-01-01

A general control scheme to control flexible arms with friction in the joints is proposed in this paper. This scheme presents the advantage of being robust in the sense that it minimizes the effects of the Coulomb friction existing in the motor and the effects of changes in the dynamic friction coefficient. A justification of the robustness properties of the scheme is given in terms of the sensitivity analysis.

The C-terminal region of the motor protein MCAK controls its structure and activity through a conformational switch

PubMed Central

Talapatra, Sandeep K; Harker, Bethany; Welburn, Julie PI

2015-01-01

The precise regulation of microtubule dynamics is essential during cell division. The kinesin-13 motor protein MCAK is a potent microtubule depolymerase. The divergent non-motor regions flanking the ATPase domain are critical in regulating its targeting and activity. However, the molecular basis for the function of the non-motor regions within the context of full-length MCAK is unknown. Here, we determine the structure of MCAK motor domain bound to its regulatory C-terminus. Our analysis reveals that the MCAK C-terminus binds to two motor domains in solution and is displaced allosterically upon microtubule binding, which allows its robust accumulation at microtubule ends. These results demonstrate that MCAK undergoes long-range conformational changes involving its C-terminus during the soluble to microtubule-bound transition and that the C-terminus-motor interaction represents a structural intermediate in the MCAK catalytic cycle. Together, our work reveals intrinsic molecular mechanisms underlying the regulation of kinesin-13 activity. DOI: http://dx.doi.org/10.7554/eLife.06421.001 PMID:25915621

Galaxy Mass Assembly with VLT & HST and lessons for E-ELT/MOSAIC

NASA Astrophysics Data System (ADS)

Hammer, François; Flores, Hector; Puech, Mathieu

2015-02-01

The fraction of distant disks and mergers is still debated, while 3D-spectroscopy is revolutionizing the field. However its limited spatial resolution imposes a complimentary HST imagery and a robust analysis procedure. When applied to observations of IMAGES galaxies at z = 0.4-0.8, it reveals that half of the spiral progenitors were in a merger phase, 6 billion year ago. The excellent correspondence between methodologically-based classifications of morphologies and kinematics definitively probes a violent origin of disk galaxies as proposed by Hammer et al. (2005). Examination of nearby galaxy outskirts reveals fossil imprints of such ancient merger events, under the form of well organized stellar streams. Perhaps our neighbor, M31, is the best illustration of an ancient merger, which modeling in 2010 leads to predict the gigantic plane of satellites discovered by Ibata et al. (2013). There are still a lot of discoveries to be done until the ELT era, which will open an avenue for detailed and accurate 3D-spectroscopy of galaxies from the earliest epochs to the present.

Vanadium Oxide Thin Films Alloyed with Ti, Zr, Nb, and Mo for Uncooled Infrared Imaging Applications

NASA Astrophysics Data System (ADS)

Ozcelik, Adem; Cabarcos, Orlando; Allara, David L.; Horn, Mark W.

2013-05-01

Microbolometer-grade vanadium oxide (VO x ) thin films with 1.3 < x < 2.0 were prepared by pulsed direct-current (DC) sputtering using substrate bias in a controlled oxygen and argon environment. These films were systematically alloyed with Ti, Nb, Mo, and Zr using a second gun and radiofrequency (RF) reactive co-sputtering to probe the effects of the transition metals on the film charge transport characteristics. The results reveal that the temperature coefficient of resistance (TCR) and resistivity are unexpectedly similar for alloyed and unalloyed films up to alloy compositions in the ˜20 at.% range. Analysis of the film structures for the case of the 17% Nb-alloyed film by glancing-angle x-ray diffraction and transmission electron microscopy shows that the microstructure remains even with the addition of high concentrations of alloy metal, demonstrating the robust character of the VO x films to maintain favorable electrical transport properties for bolometer applications. Postdeposition thermal annealing of the alloyed VO x films further reveals improvement of electrical properties compared with unalloyed films, indicating a direction for further improvements in the materials.

The complexity of the HANG SENG Index and its constituencies during the 2007-2008 Great Recession

NASA Astrophysics Data System (ADS)

Argyroudis, G.; Siokis, F.

2018-04-01

We apply the multifractal detrended moving average (MF-DMA) procedure to the daily data from HANG SENG Index (HSI) and two sub-indices, the Properties Index which consists of 10 Real Estate Companies and the Finance Index with 12 companies respectively. Two major events are considered: the 2007 and the 1997 crises. Based on scaling exponents and the singularity spectrum analysis, we show that both events reveal multiscaling and the results are robust across different indices. Furthermore, by dividing the data into two equal sub-samples for prior and after the crisis periods, we reveal that for the 2007-2008 crisis, the complexity of the HSI and Properties index remain the same between periods, while for the Finance Index, the after crisis period exhibits richer multifractality and higher complexity. Especially for the Properties Index, the results indicate that the Real Estate sector was not affected as much, by the transitory shocks of the Great Recession. As for the 1997 event, the HS Index is impacted greatly in the after period crisis exhibiting higher degree of multifractality and heterogeneity.

In silico serine β-lactamases analysis reveals a huge potential resistome in environmental and pathogenic species.

PubMed

Brandt, Christian; Braun, Sascha D; Stein, Claudia; Slickers, Peter; Ehricht, Ralf; Pletz, Mathias W; Makarewicz, Oliwia

2017-02-24

The secretion of antimicrobial compounds is an ancient mechanism with clear survival benefits for microbes competing with other microorganisms. Consequently, mechanisms that confer resistance are also ancient and may represent an underestimated reservoir in environmental bacteria. In this context, β-lactamases (BLs) are of great interest due to their long-term presence and diversification in the hospital environment, leading to the emergence of Gram-negative pathogens that are resistant to cephalosporins (extended spectrum BLs = ESBLs) and carbapenems (carbapenemases). In the current study, protein sequence databases were used to analyze BLs, and the results revealed a substantial number of unknown and functionally uncharacterized BLs in a multitude of environmental and pathogenic species. Together, these BLs represent an uncharacterized reservoir of potentially transferable resistance genes. Considering all available data, in silico approaches appear to more adequately reflect a given resistome than analyses of limited datasets. This approach leads to a more precise definition of BL clades and conserved motifs. Moreover, it may support the prediction of new resistance determinants and improve the tailored development of robust molecular diagnostics.

Time course of gene expression during mouse skeletal muscle hypertrophy

PubMed Central

Lee, Jonah D.; England, Jonathan H.; Esser, Karyn A.; McCarthy, John J.

2013-01-01

The purpose of this study was to perform a comprehensive transcriptome analysis during skeletal muscle hypertrophy to identify signaling pathways that are operative throughout the hypertrophic response. Global gene expression patterns were determined from microarray results on days 1, 3, 5, 7, 10, and 14 during plantaris muscle hypertrophy induced by synergist ablation in adult mice. Principal component analysis and the number of differentially expressed genes (cutoffs ≥2-fold increase or ≥50% decrease compared with control muscle) revealed three gene expression patterns during overload-induced hypertrophy: early (1 day), intermediate (3, 5, and 7 days), and late (10 and 14 days) patterns. Based on the robust changes in total RNA content and in the number of differentially expressed genes, we focused our attention on the intermediate gene expression pattern. Ingenuity Pathway Analysis revealed a downregulation of genes encoding components of the branched-chain amino acid degradation pathway during hypertrophy. Among these genes, five were predicted by Ingenuity Pathway Analysis or previously shown to be regulated by the transcription factor Kruppel-like factor-15, which was also downregulated during hypertrophy. Moreover, the integrin-linked kinase signaling pathway was activated during hypertrophy, and the downregulation of muscle-specific micro-RNA-1 correlated with the upregulation of five predicted targets associated with the integrin-linked kinase pathway. In conclusion, we identified two novel pathways that may be involved in muscle hypertrophy, as well as two upstream regulators (Kruppel-like factor-15 and micro-RNA-1) that provide targets for future studies investigating the importance of these pathways in muscle hypertrophy. PMID:23869057

Time course of gene expression during mouse skeletal muscle hypertrophy.

PubMed

Chaillou, Thomas; Lee, Jonah D; England, Jonathan H; Esser, Karyn A; McCarthy, John J

2013-10-01

The purpose of this study was to perform a comprehensive transcriptome analysis during skeletal muscle hypertrophy to identify signaling pathways that are operative throughout the hypertrophic response. Global gene expression patterns were determined from microarray results on days 1, 3, 5, 7, 10, and 14 during plantaris muscle hypertrophy induced by synergist ablation in adult mice. Principal component analysis and the number of differentially expressed genes (cutoffs ≥2-fold increase or ≥50% decrease compared with control muscle) revealed three gene expression patterns during overload-induced hypertrophy: early (1 day), intermediate (3, 5, and 7 days), and late (10 and 14 days) patterns. Based on the robust changes in total RNA content and in the number of differentially expressed genes, we focused our attention on the intermediate gene expression pattern. Ingenuity Pathway Analysis revealed a downregulation of genes encoding components of the branched-chain amino acid degradation pathway during hypertrophy. Among these genes, five were predicted by Ingenuity Pathway Analysis or previously shown to be regulated by the transcription factor Kruppel-like factor-15, which was also downregulated during hypertrophy. Moreover, the integrin-linked kinase signaling pathway was activated during hypertrophy, and the downregulation of muscle-specific micro-RNA-1 correlated with the upregulation of five predicted targets associated with the integrin-linked kinase pathway. In conclusion, we identified two novel pathways that may be involved in muscle hypertrophy, as well as two upstream regulators (Kruppel-like factor-15 and micro-RNA-1) that provide targets for future studies investigating the importance of these pathways in muscle hypertrophy.

Genome-wide analysis of drought induced gene expression changes in flax (Linum usitatissimum).

PubMed

Dash, Prasanta K; Cao, Yongguo; Jailani, Abdul K; Gupta, Payal; Venglat, Prakash; Xiang, Daoquan; Rai, Rhitu; Sharma, Rinku; Thirunavukkarasu, Nepolean; Abdin, Malik Z; Yadava, Devendra K; Singh, Nagendra K; Singh, Jas; Selvaraj, Gopalan; Deyholos, Mike; Kumar, Polumetla Ananda; Datla, Raju

2014-01-01

A robust phenotypic plasticity to ward off adverse environmental conditions determines performance and productivity in crop plants. Flax (linseed), is an important cash crop produced for natural textile fiber (linen) or oilseed with many health promoting products. This crop is prone to drought stress and yield losses in many parts of the world. Despite recent advances in drought research in a number of important crops, related progress in flax is very limited. Since, response of this plant to drought stress has not been addressed at the molecular level; we conducted microarray analysis to capture transcriptome associated with induced drought in flax. This study identified 183 differentially expressed genes (DEGs) associated with diverse cellular, biophysical and metabolic programs in flax. The analysis also revealed especially the altered regulation of cellular and metabolic pathways governing photosynthesis. Additionally, comparative transcriptome analysis identified a plethora of genes that displayed differential regulation both spatially and temporally. These results revealed co-regulated expression of 26 genes in both shoot and root tissues with implications for drought stress response. Furthermore, the data also showed that more genes are upregulated in roots compared to shoots, suggesting that roots may play important and additional roles in response to drought in flax. With prolonged drought treatment, the number of DEGs increased in both tissue types. Differential expression of selected genes was confirmed by qRT-PCR, thus supporting the suggested functional association of these intrinsic genes in maintaining growth and homeostasis in response to imminent drought stress in flax. Together the present study has developed foundational and new transcriptome data sets for drought stress in flax.

Empirical analysis of RNA robustness and evolution using high-throughput sequencing of ribozyme reactions.

PubMed

Hayden, Eric J

2016-08-15

RNA molecules provide a realistic but tractable model of a genotype to phenotype relationship. This relationship has been extensively investigated computationally using secondary structure prediction algorithms. Enzymatic RNA molecules, or ribozymes, offer access to genotypic and phenotypic information in the laboratory. Advancements in high-throughput sequencing technologies have enabled the analysis of sequences in the lab that now rivals what can be accomplished computationally. This has motivated a resurgence of in vitro selection experiments and opened new doors for the analysis of the distribution of RNA functions in genotype space. A body of computational experiments has investigated the persistence of specific RNA structures despite changes in the primary sequence, and how this mutational robustness can promote adaptations. This article summarizes recent approaches that were designed to investigate the role of mutational robustness during the evolution of RNA molecules in the laboratory, and presents theoretical motivations, experimental methods and approaches to data analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Robust geostatistical analysis of spatial data

NASA Astrophysics Data System (ADS)

Papritz, Andreas; Künsch, Hans Rudolf; Schwierz, Cornelia; Stahel, Werner A.

2013-04-01

Most of the geostatistical software tools rely on non-robust algorithms. This is unfortunate, because outlying observations are rather the rule than the exception, in particular in environmental data sets. Outliers affect the modelling of the large-scale spatial trend, the estimation of the spatial dependence of the residual variation and the predictions by kriging. Identifying outliers manually is cumbersome and requires expertise because one needs parameter estimates to decide which observation is a potential outlier. Moreover, inference after the rejection of some observations is problematic. A better approach is to use robust algorithms that prevent automatically that outlying observations have undue influence. Former studies on robust geostatistics focused on robust estimation of the sample variogram and ordinary kriging without external drift. Furthermore, Richardson and Welsh (1995) proposed a robustified version of (restricted) maximum likelihood ([RE]ML) estimation for the variance components of a linear mixed model, which was later used by Marchant and Lark (2007) for robust REML estimation of the variogram. We propose here a novel method for robust REML estimation of the variogram of a Gaussian random field that is possibly contaminated by independent errors from a long-tailed distribution. It is based on robustification of estimating equations for the Gaussian REML estimation (Welsh and Richardson, 1997). Besides robust estimates of the parameters of the external drift and of the variogram, the method also provides standard errors for the estimated parameters, robustified kriging predictions at both sampled and non-sampled locations and kriging variances. Apart from presenting our modelling framework, we shall present selected simulation results by which we explored the properties of the new method. This will be complemented by an analysis a data set on heavy metal contamination of the soil in the vicinity of a metal smelter. Marchant, B.P. and Lark, R.M. 2007. Robust estimation of the variogram by residual maximum likelihood. Geoderma 140: 62-72. Richardson, A.M. and Welsh, A.H. 1995. Robust restricted maximum likelihood in mixed linear models. Biometrics 51: 1429-1439. Welsh, A.H. and Richardson, A.M. 1997. Approaches to the robust estimation of mixed models. In: Handbook of Statistics Vol. 15, Elsevier, pp. 343-384.

Robustness and fragility in coupled oscillator networks under targeted attacks.

PubMed

Yuan, Tianyu; Aihara, Kazuyuki; Tanaka, Gouhei

2017-01-01

The dynamical tolerance of coupled oscillator networks against local failures is studied. As the fraction of failed oscillator nodes gradually increases, the mean oscillation amplitude in the entire network decreases and then suddenly vanishes at a critical fraction as a phase transition. This critical fraction, widely used as a measure of the network robustness, was analytically derived for random failures but not for targeted attacks so far. Here we derive the general formula for the critical fraction, which can be applied to both random failures and targeted attacks. We consider the effects of targeting oscillator nodes based on their degrees. First we deal with coupled identical oscillators with homogeneous edge weights. Then our theory is applied to networks with heterogeneous edge weights and to those with nonidentical oscillators. The analytical results are validated by numerical experiments. Our results reveal the key factors governing the robustness and fragility of oscillator networks.

Structural signatures of DRD4 mutants revealed using molecular dynamics simulations: Implications for drug targeting.

PubMed

Jatana, Nidhi; Thukral, Lipi; Latha, N

2016-01-01

Human Dopamine Receptor D4 (DRD4) orchestrates several neurological functions and represents a target for many psychological disorders. Here, we examined two rare variants in DRD4; V194G and R237L, which elicit functional alterations leading to disruption of ligand binding and G protein coupling, respectively. Using atomistic molecular dynamics (MD) simulations, we provide in-depth analysis to reveal structural signatures of wild and mutant complexes with their bound agonist and antagonist ligands. We constructed intra-protein network graphs to discriminate the global conformational changes induced by mutations. The simulations also allowed us to elucidate the local side-chain dynamical variations in ligand-bound mutant receptors. The data suggest that the mutation in transmembrane V (V194G) drastically disrupts the organization of ligand binding site and causes disorder in the native helical arrangement. Interestingly, the R237L mutation leads to significant rewiring of side-chain contacts in the intracellular loop 3 (site of mutation) and also affects the distant transmembrane topology. Additionally, these mutations lead to compact ICL3 region compared to the wild type, indicating that the receptor would be inaccessible for G protein coupling. Our findings thus reveal unreported structural determinants of the mutated DRD4 receptor and provide a robust framework for design of effective novel drugs.

RNA interference of Arabidopsis beta-amylase8 prevents maltose accumulation upon cold shock and increases sensitivity of PSII photochemical efficiency to freezing stress.

PubMed

Kaplan, Fatma; Guy, Charles L

2005-12-01

It has been suggested that beta-amylase (BMY) induction during temperature stress in Arabidopsis could lead to starch-dependent maltose accumulation, and that maltose may contribute to protection of the electron transport chain and proteins in the chloroplast stroma during acute stress. A time-course transcript profiling analysis for cold shock at 4 degrees C revealed that BMY8 (At4g17090) was induced specifically in response to cold shock, while major induction was not observed for any of the other eight beta-amylases. A parallel metabolite-profiling analysis revealed a robust transient maltose accumulation during cold shock. BMY8 RNAi lines with lower BMY8 expression exhibited a starch-excess phenotype, and a dramatic decrease in maltose accumulation during a 6-h cold shock at 4 degrees C. The decreased maltose content was also accompanied by decreased glucose, fructose and sucrose content in the BMY8 RNAi plants, consistent with the roles of beta-amylase and maltose in transitory starch metabolism. BMY8 RNAi lines with reduced soluble sugar content exhibited diminished chlorophyll fluorescence as F(v)/F(m) ratio compared with wild type, suggesting that PSII photochemical efficiency was more sensitive to freezing stress. Together, carbohydrate analysis and freezing stress results of BMY8 RNAi lines indicate that increased maltose content, by itself or together through a maltose-dependent increase in other soluble sugars, contributes to the protection of the photosynthetic electron transport chain during freezing stress.

Cooperativity of anion⋯π and π⋯π interactions regulates the self-assembly of a series of carbene proligands: Towards quantitative analysis of intermolecular interactions with Hirshfeld surface

NASA Astrophysics Data System (ADS)

Samanta, Tapastaru; Dey, Lingaraj; Dinda, Joydev; Chattopadhyay, Shyamal Kumar; Seth, Saikat Kumar

2014-06-01

The cooperative effect of weak non-covalent forces between anions and electron deficient aromatics by π⋯π stacking of a series of carbene proligands (1-3) have been thoroughly explored by crystallographic studies. Structural analysis revealed that the anion⋯π and π⋯π interactions along with intermolecular hydrogen bonding mutually cooperate to facilitate the assembling of the supramolecular framework. The π⋯π and corresponding anion⋯π interactions have been investigated in the title carbene proligands despite their association with counter ions. The presence of the anion in the vicinity of the π-system leads to the formation of anion⋯π/π⋯π/π⋯anion network for an inductive stabilization of the assemblies. To assess the dimensionality of the supramolecular framework consolidated by cooperative anion⋯π/π⋯π interactions and hydrogen bonding, different substituent effects in the carbene backbone have been considered to tune these interactions. These facts show that the supramolecular framework based on these cooperative weak forces may be robust enough for application in molecular recognition. The investigation of close intermolecular interactions between the molecules via Hirshfeld surface analyses is presented in order to reveal subtle differences and similarities in the crystal structures. The decomposition of the fingerprint plot area provides a percentage of each intermolecular interaction, allowing for a quantified analysis of close contacts within each crystal.

Cryptotephras: the revolution in correlation and precision dating1

PubMed Central

DAVIES, SIWAN M

2015-01-01

From its Icelandic origins in the study of visible tephra horizons, tephrochronology took a remarkable step in the late 1980 s with the discovery of a ca. 4300-year-old microscopic ash layer in a Scottish peat bog. Since then, the search for these cryptotephra deposits in distal areas has gone from strength to strength. Indeed, a recent discovery demonstrates how a few fine-grained glass shards from an Alaskan eruption have been dispersed more than 7000 km to northern Europe. Instantaneous deposition of geochemically distinct volcanic ash over such large geographical areas gives rise to a powerful correlation tool with considerable potential for addressing a range of scientific questions. A prerequisite of this work is the establishment of regional tephrochronological frameworks that include well-constrained age estimates and robust geochemical signatures for each deposit. With distal sites revealing a complex record of previously unknown volcanic events, frameworks are regularly revised, and it has become apparent that some closely timed eruptions have similar geochemical signatures. The search for unique and robust geochemical fingerprints thus hinges on rigorous analysis by electron microprobe and laser ablation-inductively coupled plasma-mass spectrometry. Historical developments and significant breakthroughs are presented to chart the revolution in correlation and precision dating over the last 50 years using tephrochronology and cryptotephrochronology. PMID:27512240

Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise.

PubMed

Che-Castaldo, Christian; Jenouvrier, Stephanie; Youngflesh, Casey; Shoemaker, Kevin T; Humphries, Grant; McDowall, Philip; Landrum, Laura; Holland, Marika M; Li, Yun; Ji, Rubao; Lynch, Heather J

2017-10-10

Colonially-breeding seabirds have long served as indicator species for the health of the oceans on which they depend. Abundance and breeding data are repeatedly collected at fixed study sites in the hopes that changes in abundance and productivity may be useful for adaptive management of marine resources, but their suitability for this purpose is often unknown. To address this, we fit a Bayesian population dynamics model that includes process and observation error to all known Adélie penguin abundance data (1982-2015) in the Antarctic, covering >95% of their population globally. We find that process error exceeds observation error in this system, and that continent-wide "year effects" strongly influence population growth rates. Our findings have important implications for the use of Adélie penguins in Southern Ocean feedback management, and suggest that aggregating abundance across space provides the fastest reliable signal of true population change for species whose dynamics are driven by stochastic processes.Adélie penguins are a key Antarctic indicator species, but data patchiness has challenged efforts to link population dynamics to key drivers. Che-Castaldo et al. resolve this issue using a pan-Antarctic Bayesian model to infer missing data, and show that spatial aggregation leads to more robust inference regarding dynamics.

Multi-scale computational study of the mechanical regulation of cell mitotic rounding in epithelia

PubMed Central

Xu, Zhiliang; Zartman, Jeremiah J.; Alber, Mark

2017-01-01

Mitotic rounding during cell division is critical for preventing daughter cells from inheriting an abnormal number of chromosomes, a condition that occurs frequently in cancer cells. Cells must significantly expand their apical area and transition from a polygonal to circular apical shape to achieve robust mitotic rounding in epithelial tissues, which is where most cancers initiate. However, how cells mechanically regulate robust mitotic rounding within packed tissues is unknown. Here, we analyze mitotic rounding using a newly developed multi-scale subcellular element computational model that is calibrated using experimental data. Novel biologically relevant features of the model include separate representations of the sub-cellular components including the apical membrane and cytoplasm of the cell at the tissue scale level as well as detailed description of cell properties during mitotic rounding. Regression analysis of predictive model simulation results reveals the relative contributions of osmotic pressure, cell-cell adhesion and cortical stiffness to mitotic rounding. Mitotic area expansion is largely driven by regulation of cytoplasmic pressure. Surprisingly, mitotic shape roundness within physiological ranges is most sensitive to variation in cell-cell adhesivity and stiffness. An understanding of how perturbed mechanical properties impact mitotic rounding has important potential implications on, amongst others, how tumors progressively become more genetically unstable due to increased chromosomal aneuploidy and more aggressive. PMID:28531187

Blind test of methods for obtaining 2-D near-surface seismic velocity models from first-arrival traveltimes

USGS Publications Warehouse

Zelt, Colin A.; Haines, Seth; Powers, Michael H.; Sheehan, Jacob; Rohdewald, Siegfried; Link, Curtis; Hayashi, Koichi; Zhao, Don; Zhou, Hua-wei; Burton, Bethany L.; Petersen, Uni K.; Bonal, Nedra D.; Doll, William E.

2013-01-01

Seismic refraction methods are used in environmental and engineering studies to image the shallow subsurface. We present a blind test of inversion and tomographic refraction analysis methods using a synthetic first-arrival-time dataset that was made available to the community in 2010. The data are realistic in terms of the near-surface velocity model, shot-receiver geometry and the data's frequency and added noise. Fourteen estimated models were determined by ten participants using eight different inversion algorithms, with the true model unknown to the participants until it was revealed at a session at the 2011 SAGEEP meeting. The estimated models are generally consistent in terms of their large-scale features, demonstrating the robustness of refraction data inversion in general, and the eight inversion algorithms in particular. When compared to the true model, all of the estimated models contain a smooth expression of its two main features: a large offset in the bedrock and the top of a steeply dipping low-velocity fault zone. The estimated models do not contain a subtle low-velocity zone and other fine-scale features, in accord with conventional wisdom. Together, the results support confidence in the reliability and robustness of modern refraction inversion and tomographic methods.

Insights into Atlantic multidecadal variability using the Last Millennium Reanalysis framework

NASA Astrophysics Data System (ADS)

Singh, Hansi K. A.; Hakim, Gregory J.; Tardif, Robert; Emile-Geay, Julien; Noone, David C.

2018-02-01

The Last Millennium Reanalysis (LMR) employs a data assimilation approach to reconstruct climate fields from annually resolved proxy data over years 0-2000 CE. We use the LMR to examine Atlantic multidecadal variability (AMV) over the last 2 millennia and find several robust thermodynamic features associated with a positive Atlantic Multidecadal Oscillation (AMO) index that reveal a dynamically consistent pattern of variability: the Atlantic and most continents warm; sea ice thins over the Arctic and retreats over the Greenland, Iceland, and Norwegian seas; and equatorial precipitation shifts northward. The latter is consistent with anomalous southward energy transport mediated by the atmosphere. Net downward shortwave radiation increases at both the top of the atmosphere and the surface, indicating a decrease in planetary albedo, likely due to a decrease in low clouds. Heat is absorbed by the climate system and the oceans warm. Wavelet analysis of the AMO time series shows a reddening of the frequency spectrum on the 50- to 100-year timescale, but no evidence of a distinct multidecadal or centennial spectral peak. This latter result is insensitive to both the choice of prior model and the calibration dataset used in the data assimilation algorithm, suggesting that the lack of a distinct multidecadal spectral peak is a robust result.

A new genus of proteocephalid tapeworm (Cestoda) from the marbled swamp eel Synbranchus marmoratus Bloch (Synbranchiformes: Synbranchidae) in the River Paraná basin, Argentina.

PubMed

Arredondo, Nathalia J; Alves, Philippe Vieira; Gil de Pertierra, Alicia A

2017-05-05

Synbranchiella gen. n. is proposed to accommodate Synbranchiella mabelae sp. n. (Proteocephalidae: Monticelliinae) from the intestine of the marbled swamp eel Synbranchus marmoratus Bloch, in the River Colastiné, a tributary of the middle River Paraná in Argentina. The new genus is placed in the Monticelliinae because of the cortical position of the genital organs. It differs from all known monticelliine genera by the following combination of characters: (i) scolex robust, with a conical apex, without metascolex; (ii) biloculate suckers with a conspicuous septum separating unequally-sized loculi and a robust non-adherent area, lacking free posterior margin; (iii) vitelline follicles in two narrow lateral bands, extended throughout the nearly entire proglottid length; (iv) vagina always anterior to the cirrus-sac, with an inconspicuous vaginal sphincter; (v) a genital pore pre-equatorial. Scanning electron microscopy revealed three types of microtriches on the tegument surface: acicular and capiliform filitriches and gladiate spinitriches. A phylogenetic analysis of the large subunit nuclear ribosomal RNA gene (lsrDNA, D1-D3 domains) confirms that S. mabelae represents an independent lineage within a large clade comprised mainly from Neotropical taxa parasitising catfishes. This is the second proteocephalidean cestode described from a Neotropical synbranchiform fish host.

Hearing Scenes: A Neuromagnetic Signature of Auditory Source and Reverberant Space Separation

PubMed Central

Oliva, Aude

2017-01-01

Abstract Perceiving the geometry of surrounding space is a multisensory process, crucial to contextualizing object perception and guiding navigation behavior. Humans can make judgments about surrounding spaces from reverberation cues, caused by sounds reflecting off multiple interior surfaces. However, it remains unclear how the brain represents reverberant spaces separately from sound sources. Here, we report separable neural signatures of auditory space and source perception during magnetoencephalography (MEG) recording as subjects listened to brief sounds convolved with monaural room impulse responses (RIRs). The decoding signature of sound sources began at 57 ms after stimulus onset and peaked at 130 ms, while space decoding started at 138 ms and peaked at 386 ms. Importantly, these neuromagnetic responses were readily dissociable in form and time: while sound source decoding exhibited an early and transient response, the neural signature of space was sustained and independent of the original source that produced it. The reverberant space response was robust to variations in sound source, and vice versa, indicating a generalized response not tied to specific source-space combinations. These results provide the first neuromagnetic evidence for robust, dissociable auditory source and reverberant space representations in the human brain and reveal the temporal dynamics of how auditory scene analysis extracts percepts from complex naturalistic auditory signals. PMID:28451630

A robust, efficient and flexible method for staining myelinated axons in blocks of brain tissue.

PubMed

Wahlsten, Douglas; Colbourne, Frederick; Pleus, Richard

2003-03-15

Previous studies have demonstrated the utility of the gold chloride method for en bloc staining of a bisected brain in mice and rats. The present study explores several variations in the method, assesses its reliability, and extends the limits of its application. We conclude that the method is very efficient, highly robust, sufficiently accurate for most purposes, and adaptable to many morphometric measures. We obtained acceptable staining of commissures in every brain, despite a wide variety of fixation methods. One-half could be stained 24 h after the brain was extracted and the other half could be stained months later. When staining failed because of an exhausted solution, the brain could be stained successfully in fresh solution. Relatively small changes were found in the sizes of commissures several weeks after initial fixation or staining. A half brain stained to reveal the mid-sagittal section could then be sectioned coronally and stained again in either gold chloride for myelin or cresyl violet for Nissl substance. Uncertainty, arising from pixelation of digitized images was far less than errors arising from human judgments about the histological limits of major commissures. Useful data for morphometric analysis were obtained by scanning the surface of a gold chloride stained block of brain with an inexpensive flatbed scanner.

Adaptive phase k-means algorithm for waveform classification

NASA Astrophysics Data System (ADS)

Song, Chengyun; Liu, Zhining; Wang, Yaojun; Xu, Feng; Li, Xingming; Hu, Guangmin

2018-01-01

Waveform classification is a powerful technique for seismic facies analysis that describes the heterogeneity and compartments within a reservoir. Horizon interpretation is a critical step in waveform classification. However, the horizon often produces inconsistent waveform phase, and thus results in an unsatisfied classification. To alleviate this problem, an adaptive phase waveform classification method called the adaptive phase k-means is introduced in this paper. Our method improves the traditional k-means algorithm using an adaptive phase distance for waveform similarity measure. The proposed distance is a measure with variable phases as it moves from sample to sample along the traces. Model traces are also updated with the best phase interference in the iterative process. Therefore, our method is robust to phase variations caused by the interpretation horizon. We tested the effectiveness of our algorithm by applying it to synthetic and real data. The satisfactory results reveal that the proposed method tolerates certain waveform phase variation and is a good tool for seismic facies analysis.

The Significance of Breakdown Voltages for Quality Assurance of Low-Voltage BME Ceramic Capacitors

NASA Technical Reports Server (NTRS)

Teverovsky, Alexander A.

2014-01-01

Application of thin dielectric, base metal electrode (BME) ceramic capacitors for high-reliability applications requires development of testing procedures that can assure high quality and reliability of the parts. In this work, distributions of breakdown voltages (VBR) in variety of low-voltage BME multilayer ceramic capacitors (MLCCs) have been measured and analyzed. It has been shown that analysis of the distributions can indicate the proportion of defective parts in the lot and significance of the defects. Variations of the distributions after solder dip testing allow for an assessment of the robustness of capacitors to soldering-related stresses. The drawbacks of the existing screening and qualification methods to reveal defects in high-value, low-voltage MLCCs and the importance of VBR measurements are discussed. Analysis has shown that due to a larger concentration of oxygen vacancies, defect-related degradation of the insulation resistance (IR) and failures are more likely in BME compared to the precious metal electrode (PME) capacitors.

Economic analysis of microaerobic removal of H2S from biogas in full-scale sludge digesters.

PubMed

Díaz, I; Ramos, I; Fdz-Polanco, M

2015-09-01

The application of microaerobic conditions during sludge digestion has been proven to be an efficient method for H2S removal from biogas. In this study, three microaerobic treatments were considered as an alternative to the technique of biogas desulfurization applied (FeCl3 dosing to the digesters) in a WWTP comprising three full-scale anaerobic reactors treating sewage sludge, depending on the reactant: pure O2 from cryogenic tanks, concentrated O2 from PSA generators, and air. These alternatives were compared in terms of net present value (NPV) with a fourth scenario consisting in the utilization of iron-sponge-bed filter inoculated with thiobacteria. The analysis revealed that the most profitable alternative to FeCl3 addition was the injection of concentrated O2 (0.0019 €/m(3) biogas), and this scenario presented the highest robustness towards variations in the price of FeCl3, electricity, and in the H2S concentration. Copyright © 2015 Elsevier Ltd. All rights reserved.

A novel strategy for global analysis of the dynamic thiol redox proteome.

PubMed

Martínez-Acedo, Pablo; Núñez, Estefanía; Gómez, Francisco J Sánchez; Moreno, Margoth; Ramos, Elena; Izquierdo-Álvarez, Alicia; Miró-Casas, Elisabet; Mesa, Raquel; Rodriguez, Patricia; Martínez-Ruiz, Antonio; Dorado, David Garcia; Lamas, Santiago; Vázquez, Jesús

2012-09-01

Nitroxidative stress in cells occurs mainly through the action of reactive nitrogen and oxygen species (RNOS) on protein thiol groups. Reactive nitrogen and oxygen species-mediated protein modifications are associated with pathophysiological states, but can also convey physiological signals. Identification of Cys residues that are modified by oxidative stimuli still poses technical challenges and these changes have never been statistically analyzed from a proteome-wide perspective. Here we show that GELSILOX, a method that combines a robust proteomics protocol with a new computational approach that analyzes variance at the peptide level, allows a simultaneous analysis of dynamic alterations in the redox state of Cys sites and of protein abundance. GELSILOX permits the characterization of the major endothelial redox targets of hydrogen peroxide in endothelial cells and reveals that hypoxia induces a significant increase in the status of oxidized thiols. GELSILOX also detected thiols that are redox-modified by ischemia-reperfusion in heart mitochondria and demonstrated that these alterations are abolished in ischemia-preconditioned animals.

Assessment of existing Sierra/Fuego capabilities related to grid-to-rod-fretting (GTRF).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turner, Daniel Zack; Rodriguez, Salvador B.

2011-06-01

The following report presents an assessment of existing capabilities in Sierra/Fuego applied to modeling several aspects of grid-to-rod-fretting (GTRF) including: fluid dynamics, heat transfer, and fluid-structure interaction. We compare the results of a number of Fuego simulations with relevant sources in the literature to evaluate the accuracy, efficiency, and robustness of using Fuego to model the aforementioned aspects. Comparisons between flow domains that include the full fuel rod length vs. a subsection of the domain near the spacer show that tremendous efficiency gains can be obtained by truncating the domain without loss of accuracy. Thermal analysis reveals the extent tomore » which heat transfer from the fuel rods to the coolant is improved by the swirling flow created by the mixing vanes. Lastly, coupled fluid-structure interaction analysis shows that the vibrational modes of the fuel rods filter out high frequency turbulent pressure fluctuations. In general, these results allude to interesting phenomena for which further investigation could be quite fruitful.« less

Optimization of Gas Metal Arc Welding Process Parameters

NASA Astrophysics Data System (ADS)

Kumar, Amit; Khurana, M. K.; Yadav, Pradeep K.

2016-09-01

This study presents the application of Taguchi method combined with grey relational analysis to optimize the process parameters of gas metal arc welding (GMAW) of AISI 1020 carbon steels for multiple quality characteristics (bead width, bead height, weld penetration and heat affected zone). An orthogonal array of L9 has been implemented to fabrication of joints. The experiments have been conducted according to the combination of voltage (V), current (A) and welding speed (Ws). The results revealed that the welding speed is most significant process parameter. By analyzing the grey relational grades, optimal parameters are obtained and significant factors are known using ANOVA analysis. The welding parameters such as speed, welding current and voltage have been optimized for material AISI 1020 using GMAW process. To fortify the robustness of experimental design, a confirmation test was performed at selected optimal process parameter setting. Observations from this method may be useful for automotive sub-assemblies, shipbuilding and vessel fabricators and operators to obtain optimal welding conditions.

Deep Structure of Northern Apennines Subduction Orogen (Italy) as Revealed by a Joint Interpretation of Passive and Active Seismic Data

NASA Astrophysics Data System (ADS)

Piana Agostinetti, Nicola; Faccenna, Claudio

2018-05-01

The Apennines is a well-studied orogeny formed by the accretion of continental slivers during the subduction of the Adriatic plate, but its deep structure is still a topic of controversy. Here we illuminated the deep structure of the Northern Apennines belt by combining results from the analysis of active seismic (CROP03) and receiver function data. The result from combining these two approaches provides a new robust view of the structure of the deep crust/upper mantle, from the back-arc region to the Adriatic subduction zone. Our analysis confirms the shallow Moho depth beneath the back-arc region and defines the top of the downgoing plate, showing that the two plates separate at depth about 40 km closer to the trench than reported in previous reconstructions. This spatial relationship has profound implications for the geometry of the shallow subduction zone and of the mantle wedge, by the amount of crustal material consumed at trench.

Profiles of Adolescent Religiousness using Latent Profile Analysis: Implications for Psychopathology

PubMed Central

Longo, Gregory S.; Bray, Bethany; Kim-Spoon, Jungmeen

2017-01-01

Prior research has documented robust associations between adolescent religiousness/spirituality (R/S) and psychopathology outcomes including externalizing and internalizing symptomatology, yet no previous studies have examined these associations with adolescent R/S profiles using a person-centered approach. We examined if there are identifiable subgroups characterized by unique multidimensional patterns of R/S experiences and how these experiences may be related to externalizing and internalizing symptomatology. The sample consisted of 220 Appalachian adolescents between 12 and 18 years old who were primarily White and primarily Christian. Latent profile analysis revealed three profiles of adolescent R/S; high religiousness (28.4%), introjectors (47.6%), and low religiousness (24.0%). These profiles were differentially related to internalizing and externalizing symptomatology such that the high religiousness group was significantly lower than the introjectors with respect to internalizing and externalizing symptomatology and lower than the low religiousness group in externalizing symptomatology. Implications and suggestions for future research using person-centered approaches to better understand differential developmental trajectories of religious development are provided. PMID:28220955

Single-neutron orbits near 78Ni: Spectroscopy of the N = 49 isotope 79Zn

DOE PAGES

Orlandi, R.; Mücher, D.; Raabe, R.; ...

2014-12-09

Single-neutron states in the Z=30, N=49 isotope 79Zn have been populated using the 78Zn(d, p) 79Zn transfer reaction at REX-ISOLDE, CERN. The experimental setup allowed the combined detection of protons ejected in the reaction, and of γ rays emitted by 79Zn. The analysis reveals that the lowest excited states populated in the reaction lie at approximately 1 MeV of excitation, and involve neutron orbits above the N=50 shell gap. From the analysis of γ -ray data and of proton angular distributions, characteristic of the amount of angular momentum transferred, a 5/2 + configuration was assigned to a state at 983more » keV. Comparison with large-scale-shell-model calculations supports a robust neutron N=50 shell-closure for 78Ni. Finally, these data constitute an important step towards the understanding of the magicity of 78Ni and of the structure of nuclei in the region.« less

The MACHO Project: Microlensing Results from 5.7 Years of LMC Observations

NASA Astrophysics Data System (ADS)

Becker, A. C.; Alcock, C.; Allsman, R. A.; Alves, D.; Axelrod, T. S.; Bennett, D. P.; Cook, K. H.; Drake, A. J.; Freeman, K. C.; Geha, M.; Griest, K.; Lehner, M. J.; Marshall, S. L.; Minniti, D.; Nelson, C. A.; Peterson, B. A.; Popowski, P.; Pratt, M. R.; Quinn, P. J.; Rodgers, A. W.; Stubbs, C. W.; Sutherland, W.; Tomaney, A. B.; Vandehei, T.; Welch, D. L.; MACHO Collaboration

1999-12-01

We report on our search for microlensing towards the Large Magellanic Cloud (LMC). Analysis of 5.7 years of photometry on 11.9 million stars in the LMC reveals 17 candidate microlensing events. A careful treatment of our detection efficiency shows that this is significantly more than the 2 to 4 events expected from lensing by known stellar populations. The timescales (t) of the events range from 34 to 230 days. The spatial distribution of events is probably inconsistent with LMC/LMC disk self-lensing, but consistent with an extended lens distribution such as a Milky Way or LMC halo. The optical depth results appear consistent with, but are lower than, our previous 2.1 year results. Besides a factor of 3.4 increase in exposure, this new work also includes an improved efficiency determination, improved likelihood analysis, and more thorough testing of robustness and systematic errors, especially in regards to the treatment of potential backgrounds to microlensing, such as supernovae in galaxies behind the LMC.

Dynamic Functional Connectivity States Between the Dorsal and Ventral Sensorimotor Networks Revealed by Dynamic Conditional Correlation Analysis of Resting-State Functional Magnetic Resonance Imaging.

PubMed

Syed, Maleeha F; Lindquist, Martin A; Pillai, Jay J; Agarwal, Shruti; Gujar, Sachin K; Choe, Ann S; Caffo, Brian; Sair, Haris I

2017-12-01

Functional connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) has received substantial attention since the initial findings of Biswal et al. Traditional network correlation metrics assume that the functional connectivity in the brain remains stationary over time. However, recent studies have shown that robust temporal fluctuations of functional connectivity among as well as within functional networks exist, challenging this assumption. In this study, these dynamic correlation differences were investigated between the dorsal and ventral sensorimotor networks by applying the dynamic conditional correlation model to rs-fMRI data of 20 healthy subjects. k-Means clustering was used to determine an optimal number of discrete connectivity states (k = 10) of the sensorimotor system across all subjects. Our analysis confirms the existence of differences in dynamic correlation between the dorsal and ventral networks, with highest connectivity found within the ventral motor network.

Design and analysis issues in quantitative proteomics studies.

PubMed

Karp, Natasha A; Lilley, Kathryn S

2007-09-01

Quantitative proteomics is the comparison of distinct proteomes which enables the identification of protein species which exhibit changes in expression or post-translational state in response to a given stimulus. Many different quantitative techniques are being utilized and generate large datasets. Independent of the technique used, these large datasets need robust data analysis to ensure valid conclusions are drawn from such studies. Approaches to address the problems that arise with large datasets are discussed to give insight into the types of statistical analyses of data appropriate for the various experimental strategies that can be employed by quantitative proteomic studies. This review also highlights the importance of employing a robust experimental design and highlights various issues surrounding the design of experiments. The concepts and examples discussed within will show how robust design and analysis will lead to confident results that will ensure quantitative proteomics delivers.

Proteome analysis reveals that de novo regenerated mucosa over fibula flap-reconstructed mandibles resembles mature keratinized oral mucosa.

PubMed

Kumar, Vinay V; James, Bonney L; Ruß, Manuela; Mikkat, Stefan; Suresh, Amritha; Kämmerer, Peer W; Glocker, Michael O

2018-03-01

The aim of this study was to determine whether intra-oral de novo regenerated mucosa (D) that grew over free fibula flap reconstructed-mandibles resembled the donor tissue i.e. external skin (S) of the lateral leg, or the recipient site tissue, i.e. keratinized oral mucosa (K). Differential proteome analysis was performed with ten tissue samples from each of the three groups: de novo regenerated mucosa (D), external skin (S), and keratinized oral mucosa (K). Expression differences of cornulin and involucrin were validated by Western blot analysis and their spatial distributions in the respective tissues were ascertained by immunohistochemistry. From all three investigated tissue types a total of 1188 proteins were identified, 930 of which were reproducibly and robustly quantified by proteome analysis. The best differentiating proteins were assembled in an oral mucosa proteome signature that encompasses 56 differentially expressed proteins. Principal component analysis of both, the 930 quantifiable proteins and the 56 oral mucosa signature proteins revealed that the de novo regenerated mucosa resembles keratinized oral mucosa much closer than extra-oral skin. Differentially expressed cornification-related proteins comprise proteins from all subclasses of the cornified cell envelope. Prominently expressed in intra-oral mucosa tissues were (i) cornifin-A, cornifin-B, SPRR3, and involucrin from the cornified-cell-envelope precursor group, (ii) S100A9, S100A8 and S100A2 from the S100 group, and (iii) cornulin which belongs to the fused-gene-protein group. According to its proteome signature de novo regenerated mucosa over the free fibula flap not only presents a passive structural surface layer but has adopted active tissue function. Copyright © 2018 Elsevier Ltd. All rights reserved.

Revisiting an old concept: the coupled oscillator model for VCD. Part 2: implications of the generalised coupled oscillator mechanism for the VCD robustness concept.

PubMed

Nicu, Valentin Paul

2016-08-03

Using two illustrative examples it is shown that the generalised coupled oscillator (GCO) mechanism implies that the stability of the VCD sign computed for a given normal mode is not reflected by the magnitude of the ratio ζ between the rotational strength and dipole strength of the respective mode, i.e., the VCD robustness criterium proposed by Góbi and Magyarfalvi. The performed VCD GCO analysis brings further insight into the GCO mechanism and also into the VCD robustness concept. First, it shows that the GCO mechanism can be interpreted as a VCD resonance enhancement mechanism, i.e. very large VCD signals can be observed when the interacting molecular fragments are in favourable orientation. Second, it shows that the uncertainties observed in the computed VCD signs are associated to uncertainties in the relative orientation of the coupled oscillator fragments and/or to uncertainties in the predicted nuclear displacement vectors, i.e. not uncertainties in the computed magnetic dipole transition moments as was originally assumed. Since it is able to identify such situations easily, the VCD GCO analysis can be used as a VCD robustness analysis.

Abnormal Brain Activation During Theory of Mind Tasks in Schizophrenia: A Meta-Analysis.

PubMed

Kronbichler, Lisa; Tschernegg, Melanie; Martin, Anna Isabel; Schurz, Matthias; Kronbichler, Martin

2017-10-21

Social cognition abilities are severely impaired in schizophrenia (SZ). The current meta-analysis used foci of 21 individual studies on functional abnormalities in the schizophrenic brain in order to identify regions that reveal convergent under- or over-activation during theory of mind (TOM) tasks. Studies were included in the analyses when contrasting tasks that require the processing of mental states with tasks which did not. Only studies that investigated patients with an ICD or DSM diagnosis were included. Quantitative voxel-based meta-analyses were done using Seed-based d Mapping software. Common TOM regions like medial-prefrontal cortex and temporo-parietal junction revealed abnormal activation in schizophrenic patients: Under-activation was identified in the medial prefrontal cortex, left orbito-frontal cortex, and in a small section of the left posterior temporo-parietal junction. Remarkably, robust over-activation was identified in a more dorsal, bilateral section of the temporo-parietal junction. Further abnormal activation was identified in medial occipito-parietal cortex, right premotor areas, left cingulate gyrus, and lingual gyrus. The findings of this study suggest that SZ patients simultaneously show over- and under-activation in TOM-related regions. Especially interesting, temporo-parietal junction reveals diverging activation patterns with an under-activating left posterior and an over-activating bilateral dorsal section. In conclusion, SZ patients show less specialized brain activation in regions linked to TOM and increased activation in attention-related networks suggesting compensatory effects. © The Author 2017. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

The Problem of Size in Robust Design

NASA Technical Reports Server (NTRS)

Koch, Patrick N.; Allen, Janet K.; Mistree, Farrokh; Mavris, Dimitri

1997-01-01

To facilitate the effective solution of multidisciplinary, multiobjective complex design problems, a departure from the traditional parametric design analysis and single objective optimization approaches is necessary in the preliminary stages of design. A necessary tradeoff becomes one of efficiency vs. accuracy as approximate models are sought to allow fast analysis and effective exploration of a preliminary design space. In this paper we apply a general robust design approach for efficient and comprehensive preliminary design to a large complex system: a high speed civil transport (HSCT) aircraft. Specifically, we investigate the HSCT wing configuration design, incorporating life cycle economic uncertainties to identify economically robust solutions. The approach is built on the foundation of statistical experimentation and modeling techniques and robust design principles, and is specialized through incorporation of the compromise Decision Support Problem for multiobjective design. For large problems however, as in the HSCT example, this robust design approach developed for efficient and comprehensive design breaks down with the problem of size - combinatorial explosion in experimentation and model building with number of variables -and both efficiency and accuracy are sacrificed. Our focus in this paper is on identifying and discussing the implications and open issues associated with the problem of size for the preliminary design of large complex systems.

Robustness of fit indices to outliers and leverage observations in structural equation modeling.

PubMed

Yuan, Ke-Hai; Zhong, Xiaoling

2013-06-01

Normal-distribution-based maximum likelihood (NML) is the most widely used method in structural equation modeling (SEM), although practical data tend to be nonnormally distributed. The effect of nonnormally distributed data or data contamination on the normal-distribution-based likelihood ratio (LR) statistic is well understood due to many analytical and empirical studies. In SEM, fit indices are used as widely as the LR statistic. In addition to NML, robust procedures have been developed for more efficient and less biased parameter estimates with practical data. This article studies the effect of outliers and leverage observations on fit indices following NML and two robust methods. Analysis and empirical results indicate that good leverage observations following NML and one of the robust methods lead most fit indices to give more support to the substantive model. While outliers tend to make a good model superficially bad according to many fit indices following NML, they have little effect on those following the two robust procedures. Implications of the results to data analysis are discussed, and recommendations are provided regarding the use of estimation methods and interpretation of fit indices. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Integrative analysis of transcriptomic and metabolomic data via sparse canonical correlation analysis with incorporation of biological information.

PubMed

Safo, Sandra E; Li, Shuzhao; Long, Qi

2018-03-01

Integrative analysis of high dimensional omics data is becoming increasingly popular. At the same time, incorporating known functional relationships among variables in analysis of omics data has been shown to help elucidate underlying mechanisms for complex diseases. In this article, our goal is to assess association between transcriptomic and metabolomic data from a Predictive Health Institute (PHI) study that includes healthy adults at a high risk of developing cardiovascular diseases. Adopting a strategy that is both data-driven and knowledge-based, we develop statistical methods for sparse canonical correlation analysis (CCA) with incorporation of known biological information. Our proposed methods use prior network structural information among genes and among metabolites to guide selection of relevant genes and metabolites in sparse CCA, providing insight on the molecular underpinning of cardiovascular disease. Our simulations demonstrate that the structured sparse CCA methods outperform several existing sparse CCA methods in selecting relevant genes and metabolites when structural information is informative and are robust to mis-specified structural information. Our analysis of the PHI study reveals that a number of gene and metabolic pathways including some known to be associated with cardiovascular diseases are enriched in the set of genes and metabolites selected by our proposed approach. © 2017, The International Biometric Society.

Association of Gestational Hypertensive Disorders with Retinopathy of prematurity: A Systematic Review and Meta-analysis.

PubMed

Chan, Priscilla Y L; Tang, Shu-Min; Au, Sunny C L; Rong, Shi-Song; Lau, Henry H W; Ko, Simon T C; Ng, Danny S C; Chen, Li Jia; Yam, Jason C S

2016-08-05

The role of gestational hypertensive disorders, which includes both pre-eclampsia and gestational hypertension, in the development of retinopathy of prematurity (ROP) has been controversial. Therefore, this systematic review and meta-analysis is to evaluate the association between gestational hypertensive disoders and ROP. Eligible studies published up to June 5, 2016 were identified from MEDLINE and EMBASE that evaluated the association between the two conditions. Totally 1142 published records were retrieved for screening, 925 of them eligible for detailed evaluation. Finally 19 studies involving 45281 infants with 5388 cases of ROP met our criteria for meta-analysis. Gestational hypertensive disorders were not associated with ROP (unadjusted OR: 0.89; P = 0.38; adjusted OR: 1.35; P = 0.18). Subgroup analyses also revealed no significant association between ROP with pre-eclampsia (unadjusted OR: 0.85; P = 0.29; adjusted OR:1.29; P = 0.28) or with gestational hypertension (unadjusted OR: 1.10; P = 0.39; adjusted OR: 1.25; P = 0.60) separately. Sensitivity analysis indicated our results were robust. We concluded no significant association between gestational hypertensive disorders and ROP. More large scale well-conducted prospective cohorts on the topic are needed.

Combining self-organizing mapping and supervised affinity propagation clustering approach to investigate functional brain networks involved in motor imagery and execution with fMRI measurements.

PubMed

Zhang, Jiang; Liu, Qi; Chen, Huafu; Yuan, Zhen; Huang, Jin; Deng, Lihua; Lu, Fengmei; Zhang, Junpeng; Wang, Yuqing; Wang, Mingwen; Chen, Liangyin

2015-01-01

Clustering analysis methods have been widely applied to identifying the functional brain networks of a multitask paradigm. However, the previously used clustering analysis techniques are computationally expensive and thus impractical for clinical applications. In this study a novel method, called SOM-SAPC that combines self-organizing mapping (SOM) and supervised affinity propagation clustering (SAPC), is proposed and implemented to identify the motor execution (ME) and motor imagery (MI) networks. In SOM-SAPC, SOM was first performed to process fMRI data and SAPC is further utilized for clustering the patterns of functional networks. As a result, SOM-SAPC is able to significantly reduce the computational cost for brain network analysis. Simulation and clinical tests involving ME and MI were conducted based on SOM-SAPC, and the analysis results indicated that functional brain networks were clearly identified with different response patterns and reduced computational cost. In particular, three activation clusters were clearly revealed, which include parts of the visual, ME and MI functional networks. These findings validated that SOM-SAPC is an effective and robust method to analyze the fMRI data with multitasks.

Robust Global Image Registration Based on a Hybrid Algorithm Combining Fourier and Spatial Domain Techniques

DTIC Science & Technology

2012-09-01

Robust global image registration based on a hybrid algorithm combining Fourier and spatial domain techniques Peter N. Crabtree, Collin Seanor...00-00-2012 to 00-00-2012 4. TITLE AND SUBTITLE Robust global image registration based on a hybrid algorithm combining Fourier and spatial domain...demonstrate performance of a hybrid algorithm . These results are from analysis of a set of images of an ISO 12233 [12] resolution chart captured in the

Efficient Computation of Info-Gap Robustness for Finite Element Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stull, Christopher J.; Hemez, Francois M.; Williams, Brian J.

2012-07-05

A recent research effort at LANL proposed info-gap decision theory as a framework by which to measure the predictive maturity of numerical models. Info-gap theory explores the trade-offs between accuracy, that is, the extent to which predictions reproduce the physical measurements, and robustness, that is, the extent to which predictions are insensitive to modeling assumptions. Both accuracy and robustness are necessary to demonstrate predictive maturity. However, conducting an info-gap analysis can present a formidable challenge, from the standpoint of the required computational resources. This is because a robustness function requires the resolution of multiple optimization problems. This report offers anmore » alternative, adjoint methodology to assess the info-gap robustness of Ax = b-like numerical models solved for a solution x. Two situations that can arise in structural analysis and design are briefly described and contextualized within the info-gap decision theory framework. The treatments of the info-gap problems, using the adjoint methodology are outlined in detail, and the latter problem is solved for four separate finite element models. As compared to statistical sampling, the proposed methodology offers highly accurate approximations of info-gap robustness functions for the finite element models considered in the report, at a small fraction of the computational cost. It is noted that this report considers only linear systems; a natural follow-on study would extend the methodologies described herein to include nonlinear systems.« less

Trading Robustness Requirements in Mars Entry Trajectory Design

NASA Technical Reports Server (NTRS)

Lafleur, Jarret M.

2009-01-01

One of the most important metrics characterizing an atmospheric entry trajectory in preliminary design is the size of its predicted landing ellipse. Often, requirements for this ellipse are set early in design and significantly influence both the expected scientific return from a particular mission and the cost of development. Requirements typically specify a certain probability level (6-level) for the prescribed ellipse, and frequently this latter requirement is taken at 36. However, searches for the justification of 36 as a robustness requirement suggest it is an empirical rule of thumb borrowed from non-aerospace fields. This paper presents an investigation into the sensitivity of trajectory performance to varying robustness (6-level) requirements. The treatment of robustness as a distinct objective is discussed, and an analysis framework is presented involving the manipulation of design variables to effect trades between performance and robustness objectives. The scenario for which this method is illustrated is the ballistic entry of an MSL-class Mars entry vehicle. Here, the design variable is entry flight path angle, and objectives are parachute deploy altitude performance and error ellipse robustness. Resulting plots show the sensitivities between these objectives and trends in the entry flight path angles required to design to these objectives. Relevance to the trajectory designer is discussed, as are potential steps for further development and use of this type of analysis.

Analysis, calculation and utilization of the k-balance attribute in interdependent networks

NASA Astrophysics Data System (ADS)

Liu, Zheng; Li, Qing; Wang, Dan; Xu, Mingwei

2018-05-01

Interdependent networks, where two networks depend on each other, are becoming more and more significant in modern systems. From previous work, it can be concluded that interdependent networks are more vulnerable than a single network. The robustness in interdependent networks deserves special attention. In this paper, we propose a metric of robustness from a new perspective-the balance. First, we define the balance-coefficient of the interdependent system. Based on precise analysis and derivation, we prove some significant theories and provide an efficient algorithm to compute the balance-coefficient. Finally, we propose an optimal solution to reduce the balance-coefficient to enhance the robustness of the given system. Comprehensive experiments confirm the efficiency of our algorithms.

Robustness of statistical tests for multiplicative terms in the additive main effects and multiplicative interaction model for cultivar trials.

PubMed

Piepho, H P

1995-03-01

The additive main effects multiplicative interaction model is frequently used in the analysis of multilocation trials. In the analysis of such data it is of interest to decide how many of the multiplicative interaction terms are significant. Several tests for this task are available, all of which assume that errors are normally distributed with a common variance. This paper investigates the robustness of several tests (Gollob, F GH1, FGH2, FR)to departures from these assumptions. It is concluded that, because of its better robustness, the F Rtest is preferable. If the other tests are to be used, preliminary tests for the validity of assumptions should be performed.

A robust method for RNA extraction and purification from a single adult mouse tendon.

PubMed

Grinstein, Mor; Dingwall, Heather L; Shah, Rishita R; Capellini, Terence D; Galloway, Jenna L

2018-01-01

Mechanistic understanding of tendon molecular and cellular biology is crucial toward furthering our abilities to design new therapies for tendon and ligament injuries and disease. Recent transcriptomic and epigenomic studies in the field have harnessed the power of mouse genetics to reveal new insights into tendon biology. However, many mouse studies pool tendon tissues or use amplification methods to perform RNA analysis, which can significantly increase the experimental costs and limit the ability to detect changes in expression of low copy transcripts. Single Achilles tendons were harvested from uninjured, contralateral injured, and wild type mice between three and five months of age, and RNA was extracted. RNA Integrity Number (RIN) and concentration were determined, and RT-qPCR gene expression analysis was performed. After testing several RNA extraction approaches on single adult mouse Achilles tendons, we developed a protocol that was successful at obtaining high RIN and sufficient concentrations suitable for RNA analysis. We found that the RNA quality was sensitive to the time between tendon harvest and homogenization, and the RNA quality and concentration was dependent on the duration of homogenization. Using this method, we demonstrate that analysis of Scx gene expression in single mouse tendons reduces the biological variation caused by pooling tendons from multiple mice. We also show successful use of this approach to analyze Sox9 and Col1a2 gene expression changes in injured compared with uninjured control tendons. Our work presents a robust, cost-effective, and straightforward method to extract high quality RNA from a single adult mouse Achilles tendon at sufficient amounts for RT-qPCR as well as RNA-seq. We show this can reduce variation and decrease the overall costs associated with experiments. This approach can also be applied to other skeletal tissues, as well as precious human samples.

Impact of self-healing capability on network robustness

NASA Astrophysics Data System (ADS)

Shang, Yilun

2015-04-01

A wide spectrum of real-life systems ranging from neurons to botnets display spontaneous recovery ability. Using the generating function formalism applied to static uncorrelated random networks with arbitrary degree distributions, the microscopic mechanism underlying the depreciation-recovery process is characterized and the effect of varying self-healing capability on network robustness is revealed. It is found that the self-healing capability of nodes has a profound impact on the phase transition in the emergence of percolating clusters, and that salient difference exists in upholding network integrity under random failures and intentional attacks. The results provide a theoretical framework for quantitatively understanding the self-healing phenomenon in varied complex systems.

Impact of self-healing capability on network robustness.

PubMed

Shang, Yilun

2015-04-01

A wide spectrum of real-life systems ranging from neurons to botnets display spontaneous recovery ability. Using the generating function formalism applied to static uncorrelated random networks with arbitrary degree distributions, the microscopic mechanism underlying the depreciation-recovery process is characterized and the effect of varying self-healing capability on network robustness is revealed. It is found that the self-healing capability of nodes has a profound impact on the phase transition in the emergence of percolating clusters, and that salient difference exists in upholding network integrity under random failures and intentional attacks. The results provide a theoretical framework for quantitatively understanding the self-healing phenomenon in varied complex systems.

Robustness Regions for Dichotomous Decisions.

ERIC Educational Resources Information Center

Vijn, Pieter; Molenaar, Ivo W.

1981-01-01

In the case of dichotomous decisions, the total set of all assumptions/specifications for which the decision would have been the same is the robustness region. Inspection of this (data-dependent) region is a form of sensitivity analysis which may lead to improved decision making. (Author/BW)

Robust co-regulation of tyrosine phosphorylation sites on proteins reveals novel protein interactions†

PubMed Central

Naegle, Kristen M.; White, Forest M.; Lauffenburger, Douglas A.; Yaffe, Michael B.

2012-01-01

Cell signaling networks propagate information from extracellular cues via dynamic modulation of protein–protein interactions in a context-dependent manner. Networks based on receptor tyrosine kinases (RTKs), for example, phosphorylate intracellular proteins in response to extracellular ligands, resulting in dynamic protein–protein interactions that drive phenotypic changes. Most commonly used methods for discovering these protein–protein interactions, however, are optimized for detecting stable, longer-lived complexes, rather than the type of transient interactions that are essential components of dynamic signaling networks such as those mediated by RTKs. Substrate phosphorylation downstream of RTK activation modifies substrate activity and induces phospho-specific binding interactions, resulting in the formation of large transient macromolecular signaling complexes. Since protein complex formation should follow the trajectory of events that drive it, we reasoned that mining phosphoproteomic datasets for highly similar dynamic behavior of measured phosphorylation sites on different proteins could be used to predict novel, transient protein–protein interactions that had not been previously identified. We applied this method to explore signaling events downstream of EGFR stimulation. Our computational analysis of robustly co-regulated phosphorylation sites, based on multiple clustering analysis of quantitative time-resolved mass-spectrometry phosphoproteomic data, not only identified known sitewise-specific recruitment of proteins to EGFR, but also predicted novel, a priori interactions. A particularly intriguing prediction of EGFR interaction with the cytoskeleton-associated protein PDLIM1 was verified within cells using co-immunoprecipitation and in situ proximity ligation assays. Our approach thus offers a new way to discover protein–protein interactions in a dynamic context- and phosphorylation site-specific manner. PMID:22851037

A reliability study on brain activation during active and passive arm movements supported by an MRI-compatible robot.

PubMed

Estévez, Natalia; Yu, Ningbo; Brügger, Mike; Villiger, Michael; Hepp-Reymond, Marie-Claude; Riener, Robert; Kollias, Spyros

2014-11-01

In neurorehabilitation, longitudinal assessment of arm movement related brain function in patients with motor disability is challenging due to variability in task performance. MRI-compatible robots monitor and control task performance, yielding more reliable evaluation of brain function over time. The main goals of the present study were first to define the brain network activated while performing active and passive elbow movements with an MRI-compatible arm robot (MaRIA) in healthy subjects, and second to test the reproducibility of this activation over time. For the fMRI analysis two models were compared. In model 1 movement onset and duration were included, whereas in model 2 force and range of motion were added to the analysis. Reliability of brain activation was tested with several statistical approaches applied on individual and group activation maps and on summary statistics. The activated network included mainly the primary motor cortex, primary and secondary somatosensory cortex, superior and inferior parietal cortex, medial and lateral premotor regions, and subcortical structures. Reliability analyses revealed robust activation for active movements with both fMRI models and all the statistical methods used. Imposed passive movements also elicited mainly robust brain activation for individual and group activation maps, and reliability was improved by including additional force and range of motion using model 2. These findings demonstrate that the use of robotic devices, such as MaRIA, can be useful to reliably assess arm movement related brain activation in longitudinal studies and may contribute in studies evaluating therapies and brain plasticity following injury in the nervous system.

Accurate quantification of chromosomal lesions via short tandem repeat analysis using minimal amounts of DNA

PubMed Central

Jann, Johann-Christoph; Nowak, Daniel; Nolte, Florian; Fey, Stephanie; Nowak, Verena; Obländer, Julia; Pressler, Jovita; Palme, Iris; Xanthopoulos, Christina; Fabarius, Alice; Platzbecker, Uwe; Giagounidis, Aristoteles; Götze, Katharina; Letsch, Anne; Haase, Detlef; Schlenk, Richard; Bug, Gesine; Lübbert, Michael; Ganser, Arnold; Germing, Ulrich; Haferlach, Claudia; Hofmann, Wolf-Karsten; Mossner, Maximilian

2017-01-01

Background Cytogenetic aberrations such as deletion of chromosome 5q (del(5q)) represent key elements in routine clinical diagnostics of haematological malignancies. Currently established methods such as metaphase cytogenetics, FISH or array-based approaches have limitations due to their dependency on viable cells, high costs or semi-quantitative nature. Importantly, they cannot be used on low abundance DNA. We therefore aimed to establish a robust and quantitative technique that overcomes these shortcomings. Methods For precise determination of del(5q) cell fractions, we developed an inexpensive multiplex-PCR assay requiring only nanograms of DNA that simultaneously measures allelic imbalances of 12 independent short tandem repeat markers. Results Application of this method to n=1142 samples from n=260 individuals revealed strong intermarker concordance (R²=0.77–0.97) and reproducibility (mean SD: 1.7%). Notably, the assay showed accurate quantification via standard curve assessment (R²>0.99) and high concordance with paired FISH measurements (R²=0.92) even with subnanogram amounts of DNA. Moreover, cytogenetic response was reliably confirmed in del(5q) patients with myelodysplastic syndromes treated with lenalidomide. While the assay demonstrated good diagnostic accuracy in receiver operating characteristic analysis (area under the curve: 0.97), we further observed robust correlation between bone marrow and peripheral blood samples (R²=0.79), suggesting its potential suitability for less-invasive clonal monitoring. Conclusions In conclusion, we present an adaptable tool for quantification of chromosomal aberrations, particularly in problematic samples, which should be easily applicable to further tumour entities. PMID:28600436

Design and analysis of tilt integral derivative controller with filter for load frequency control of multi-area interconnected power systems.

PubMed

Kumar Sahu, Rabindra; Panda, Sidhartha; Biswal, Ashutosh; Chandra Sekhar, G T

2016-03-01

In this paper, a novel Tilt Integral Derivative controller with Filter (TIDF) is proposed for Load Frequency Control (LFC) of multi-area power systems. Initially, a two-area power system is considered and the parameters of the TIDF controller are optimized using Differential Evolution (DE) algorithm employing an Integral of Time multiplied Absolute Error (ITAE) criterion. The superiority of the proposed approach is demonstrated by comparing the results with some recently published heuristic approaches such as Firefly Algorithm (FA), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) optimized PID controllers for the same interconnected power system. Investigations reveal that proposed TIDF controllers provide better dynamic response compared to PID controller in terms of minimum undershoots and settling times of frequency as well as tie-line power deviations following a disturbance. The proposed approach is also extended to two widely used three area test systems considering nonlinearities such as Generation Rate Constraint (GRC) and Governor Dead Band (GDB). To improve the performance of the system, a Thyristor Controlled Series Compensator (TCSC) is also considered and the performance of TIDF controller in presence of TCSC is investigated. It is observed that system performance improves with the inclusion of TCSC. Finally, sensitivity analysis is carried out to test the robustness of the proposed controller by varying the system parameters, operating condition and load pattern. It is observed that the proposed controllers are robust and perform satisfactorily with variations in operating condition, system parameters and load pattern. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Measures of phylogenetic differentiation provide robust and complementary insights into microbial communities.

PubMed

Parks, Donovan H; Beiko, Robert G

2013-01-01

High-throughput sequencing techniques have made large-scale spatial and temporal surveys of microbial communities routine. Gaining insight into microbial diversity requires methods for effectively analyzing and visualizing these extensive data sets. Phylogenetic β-diversity measures address this challenge by allowing the relationship between large numbers of environmental samples to be explored using standard multivariate analysis techniques. Despite the success and widespread use of phylogenetic β-diversity measures, an extensive comparative analysis of these measures has not been performed. Here, we compare 39 measures of phylogenetic β diversity in order to establish the relative similarity of these measures along with key properties and performance characteristics. While many measures are highly correlated, those commonly used within microbial ecology were found to be distinct from those popular within classical ecology, and from the recently recommended Gower and Canberra measures. Many of the measures are surprisingly robust to different rootings of the gene tree, the choice of similarity threshold used to define operational taxonomic units, and the presence of outlying basal lineages. Measures differ considerably in their sensitivity to rare organisms, and the effectiveness of measures can vary substantially under alternative models of differentiation. Consequently, the depth of sequencing required to reveal underlying patterns of relationships between environmental samples depends on the selected measure. Our results demonstrate that using complementary measures of phylogenetic β diversity can further our understanding of how communities are phylogenetically differentiated. Open-source software implementing the phylogenetic β-diversity measures evaluated in this manuscript is available at http://kiwi.cs.dal.ca/Software/ExpressBetaDiversity.

Multiobjective robust design of the double wishbone suspension system based on particle swarm optimization.

PubMed

Cheng, Xianfu; Lin, Yuqun

2014-01-01

The performance of the suspension system is one of the most important factors in the vehicle design. For the double wishbone suspension system, the conventional deterministic optimization does not consider any deviations of design parameters, so design sensitivity analysis and robust optimization design are proposed. In this study, the design parameters of the robust optimization are the positions of the key points, and the random factors are the uncertainties in manufacturing. A simplified model of the double wishbone suspension is established by software ADAMS. The sensitivity analysis is utilized to determine main design variables. Then, the simulation experiment is arranged and the Latin hypercube design is adopted to find the initial points. The Kriging model is employed for fitting the mean and variance of the quality characteristics according to the simulation results. Further, a particle swarm optimization method based on simple PSO is applied and the tradeoff between the mean and deviation of performance is made to solve the robust optimization problem of the double wishbone suspension system.

Linear, multivariable robust control with a mu perspective

NASA Technical Reports Server (NTRS)

Packard, Andy; Doyle, John; Balas, Gary

1993-01-01

The structured singular value is a linear algebra tool developed to study a particular class of matrix perturbation problems arising in robust feedback control of multivariable systems. These perturbations are called linear fractional, and are a natural way to model many types of uncertainty in linear systems, including state-space parameter uncertainty, multiplicative and additive unmodeled dynamics uncertainty, and coprime factor and gap metric uncertainty. The structured singular value theory provides a natural extension of classical SISO robustness measures and concepts to MIMO systems. The structured singular value analysis, coupled with approximate synthesis methods, make it possible to study the tradeoff between performance and uncertainty that occurs in all feedback systems. In MIMO systems, the complexity of the spatial interactions in the loop gains make it difficult to heuristically quantify the tradeoffs that must occur. This paper examines the role played by the structured singular value (and its computable bounds) in answering these questions, as well as its role in the general robust, multivariable control analysis and design problem.

Quality by Design: Multidimensional exploration of the design space in high performance liquid chromatography method development for better robustness before validation.

PubMed

Monks, K; Molnár, I; Rieger, H-J; Bogáti, B; Szabó, E

2012-04-06

Robust HPLC separations lead to fewer analysis failures and better method transfer as well as providing an assurance of quality. This work presents the systematic development of an optimal, robust, fast UHPLC method for the simultaneous assay of two APIs of an eye drop sample and their impurities, in accordance with Quality by Design principles. Chromatography software is employed to effectively generate design spaces (Method Operable Design Regions), which are subsequently employed to determine the final method conditions and to evaluate robustness prior to validation. Copyright © 2011 Elsevier B.V. All rights reserved.

Robust model predictive control for constrained continuous-time nonlinear systems

NASA Astrophysics Data System (ADS)

Sun, Tairen; Pan, Yongping; Zhang, Jun; Yu, Haoyong

2018-02-01

In this paper, a robust model predictive control (MPC) is designed for a class of constrained continuous-time nonlinear systems with bounded additive disturbances. The robust MPC consists of a nonlinear feedback control and a continuous-time model-based dual-mode MPC. The nonlinear feedback control guarantees the actual trajectory being contained in a tube centred at the nominal trajectory. The dual-mode MPC is designed to ensure asymptotic convergence of the nominal trajectory to zero. This paper extends current results on discrete-time model-based tube MPC and linear system model-based tube MPC to continuous-time nonlinear model-based tube MPC. The feasibility and robustness of the proposed robust MPC have been demonstrated by theoretical analysis and applications to a cart-damper springer system and a one-link robot manipulator.

Robust Magnetotelluric Impedance Estimation

NASA Astrophysics Data System (ADS)

Sutarno, D.

2010-12-01

Robust magnetotelluric (MT) response function estimators are now in standard use by the induction community. Properly devised and applied, these have ability to reduce the influence of unusual data (outliers). The estimators always yield impedance estimates which are better than the conventional least square (LS) estimation because the `real' MT data almost never satisfy the statistical assumptions of Gaussian distribution and stationary upon which normal spectral analysis is based. This paper discuses the development and application of robust estimation procedures which can be classified as M-estimators to MT data. Starting with the description of the estimators, special attention is addressed to the recent development of a bounded-influence robust estimation, including utilization of the Hilbert Transform (HT) operation on causal MT impedance functions. The resulting robust performances are illustrated using synthetic as well as real MT data.

Robust estimation of fractal measures for characterizing the structural complexity of the human brain: optimization and reproducibility

PubMed Central

Goñi, Joaquín; Sporns, Olaf; Cheng, Hu; Aznárez-Sanado, Maite; Wang, Yang; Josa, Santiago; Arrondo, Gonzalo; Mathews, Vincent P; Hummer, Tom A; Kronenberger, William G; Avena-Koenigsberger, Andrea; Saykin, Andrew J.; Pastor, María A.

2013-01-01

High-resolution isotropic three-dimensional reconstructions of human brain gray and white matter structures can be characterized to quantify aspects of their shape, volume and topological complexity. In particular, methods based on fractal analysis have been applied in neuroimaging studies to quantify the structural complexity of the brain in both healthy and impaired conditions. The usefulness of such measures for characterizing individual differences in brain structure critically depends on their within-subject reproducibility in order to allow the robust detection of between-subject differences. This study analyzes key analytic parameters of three fractal-based methods that rely on the box-counting algorithm with the aim to maximize within-subject reproducibility of the fractal characterizations of different brain objects, including the pial surface, the cortical ribbon volume, the white matter volume and the grey matter/white matter boundary. Two separate datasets originating from different imaging centers were analyzed, comprising, 50 subjects with three and 24 subjects with four successive scanning sessions per subject, respectively. The reproducibility of fractal measures was statistically assessed by computing their intra-class correlations. Results reveal differences between different fractal estimators and allow the identification of several parameters that are critical for high reproducibility. Highest reproducibility with intra-class correlations in the range of 0.9–0.95 is achieved with the correlation dimension. Further analyses of the fractal dimensions of parcellated cortical and subcortical gray matter regions suggest robustly estimated and region-specific patterns of individual variability. These results are valuable for defining appropriate parameter configurations when studying changes in fractal descriptors of human brain structure, for instance in studies of neurological diseases that do not allow repeated measurements or for disease-course longitudinal studies. PMID:23831414

Genetic variation and dopamine D2 receptor availability: a systematic review and meta-analysis of human in vivo molecular imaging studies.

PubMed

Gluskin, B S; Mickey, B J

2016-03-01

The D2 dopamine receptor mediates neuropsychiatric symptoms and is a target of pharmacotherapy. Inter-individual variation of D2 receptor density is thought to influence disease risk and pharmacological response. Numerous molecular imaging studies have tested whether common genetic variants influence D2 receptor binding potential (BP) in humans, but demonstration of robust effects has been limited by small sample sizes. We performed a systematic search of published human in vivo molecular imaging studies to estimate effect sizes of common genetic variants on striatal D2 receptor BP. We identified 21 studies examining 19 variants in 11 genes. The most commonly studied variant was a single-nucleotide polymorphism in ANKK1 (rs1800497, Glu713Lys, also called 'Taq1A'). Fixed- and random-effects meta-analyses of this variant (5 studies, 194 subjects total) revealed that striatal BP was significantly and robustly lower among carriers of the minor allele (Lys713) relative to major allele homozygotes. The weighted standardized mean difference was -0.57 under the fixed-effect model (95% confidence interval=(-0.87, -0.27), P=0.0002). The normal relationship between rs1800497 and BP was not apparent among subjects with neuropsychiatric diseases. Significant associations with baseline striatal D2 receptor BP have been reported for four DRD2 variants (rs1079597, rs1076560, rs6277 and rs1799732) and a PER2 repeat polymorphism, but none have yet been tested in more than two independent samples. Our findings resolve apparent discrepancies in the literature and establish that rs1800497 robustly influences striatal D2 receptor availability. This genetic variant is likely to contribute to important individual differences in human striatal function, neuropsychiatric disease risk and pharmacological response.

Meta-analyses and p-curves support robust cycle shifts in women's mate preferences: reply to Wood and Carden (2014) and Harris, Pashler, and Mickes (2014).

PubMed

Gildersleeve, Kelly; Haselton, Martie G; Fales, Melissa R

2014-09-01

Two meta-analyses evaluated shifts across the ovulatory cycle in women's mate preferences but reported very different findings. In this journal, we reported robust evidence for the pattern of cycle shifts predicted by the ovulatory shift hypothesis (Gildersleeve, Haselton, & Fales, 2014). However, Wood, Kressel, Joshi, and Louie (2014) claimed an absence of compelling support for this hypothesis and asserted that the few significant cycle shifts they observed were false positives resulting from publication bias, p-hacking, or other research artifacts. How could 2 meta-analyses of the same literature reach such different conclusions? We reanalyzed the data compiled by Wood et al. These analyses revealed problems in Wood et al.'s meta-analysis-some of which are reproduced in Wood and Carden's (2014) comment in the current issue of this journal-that led them to overlook clear evidence for the ovulatory shift hypothesis in their own set of effects. In addition, we present right-skewed p-curves that directly contradict speculations by Wood et al.; Wood and Carden; and Harris, Pashler, and Mickes (2014) that supportive findings in the cycle shift literature are false positives. Therefore, evidence from both of the meta-analyses and the p-curves strongly supports genuine, robust effects consistent with the ovulatory shift hypothesis and contradicts claims that these effects merely reflect publication bias, p-hacking, or other research artifacts. Unfounded speculations about p-hacking distort the research record and risk unfairly damaging researchers' reputations; they should therefore be made only on the basis of firm evidence. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Multiplex pyrosequencing of InDel markers for forensic DNA analysis.

PubMed

Bus, Magdalena M; Karas, Ognjen; Allen, Marie

2016-12-01

The capillary electrophoresis (CE) technology is commonly used for fragment length separation of markers in forensic DNA analysis. In this study, pyrosequencing technology was used as an alternative and rapid tool for the analysis of biallelic InDel (insertion/deletion) markers for individual identification. The DNA typing is based on a subset of the InDel markers that are included in the Investigator ® DIPplex Kit, which are sequenced in a multiplex pyrosequencing analysis. To facilitate the analysis of degraded DNA, the polymerase chain reaction (PCR) fragments were kept short in the primer design. Samples from individuals of Swedish origin were genotyped using the pyrosequencing strategy and analysis of the Investigator ® DIPplex markers with CE. A comparison between the pyrosequencing and CE data revealed concordant results demonstrating a robust and correct genotyping by pyrosequencing. Using optimal marker combination and a directed dispensation strategy, five markers could be multiplexed and analyzed simultaneously. In this proof-of-principle study, we demonstrate that multiplex InDel pyrosequencing analysis is possible. However, further studies on degraded samples, lower DNA quantities, and mixtures will be required to fully optimize InDel analysis by pyrosequencing for forensic applications. Overall, although CE analysis is implemented in most forensic laboratories, multiplex InDel pyrosequencing offers a cost-effective alternative for some applications. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Emotional dysregulation is a primary symptom in adult Attention-Deficit/Hyperactivity Disorder (ADHD).

PubMed

Hirsch, Oliver; Chavanon, MiraLynn; Riechmann, Elke; Christiansen, Hanna

2018-05-01

Clinical observations suggest that adults have more diverse deficits than children with Attention Deficit/Hyperactivity Disorder (ADHD). These seem to entail difficulties with emotionality, self-concept and emotion regulation in particular, along with the cardinal symptoms of inattention, impulsivity, and hyperactivity for adult patients. Here, we probed a model that explicitly distinguished positive and negative affect, problems with self-concept and emotion regulation skills as distinct but correlating factors with the symptom domains of inattention, hyperactivity, and impulsivity. Participants were 213 newly diagnosed adults with ADHD (62.9% male, mean age 33.5 years). Symptoms were assessed via self-report on the Conners' Adult ADHD Rating Scales, a modified version of the Positive and Negative Affect Scale and the Emotion Regulation Skill Questionnaire. A confirmatory factor analysis with the R package lavaan, using a robust Maximum Likelihood estimator (MLR) for non-normal data, was conducted to test our new non-hierarchical 7-factor model. All calculated model-fit statistics revealed good model-fit (χ 2 /df ratio = 2.03, robust RMSEA = .07). The SRMR in our model reached .089, indicating an acceptable model fit. Factor loadings on the postulated factors had salient loadings ≥ .31 except for one item on the hyperactivity factor. Latent factor associations were especially salient between emotional dysregulation and problems with self-concept, and also partially with impulsivity/emotional lability. The three models of ADHD and emotion regulation as suggested by Shaw et al. (2014) could not be disentangled in this study, though the overall results support the model with shared neurocognitive deficits. Further, we did not separately analyze ADHD with or without comorbid disorders. As our sample of clinical cases with ADHD is highly comorbid (47.9%), other disorders than ADHD might account for the emotion regulation deficits, though a sensitivity analysis revealed no such differences. Our model adequately characterizes the relations between and among clinically and therapeutically relevant symptoms in adult ADHD, thus potentially informing future therapeutic interventions by targeting the successful and flexible use of adaptive emotion regulation skills. Copyright © 2018 Elsevier B.V. All rights reserved.

Reengineering of a Corynebacterium glutamicum L-arginine and L-citrulline producer.

PubMed

Ikeda, Masato; Mitsuhashi, Satoshi; Tanaka, Kenji; Hayashi, Mikiro

2009-03-01

Toward the creation of a robust and efficient producer of L-arginine and L-citrulline (arginine/citrulline), we have performed reengineering of a Corynebacterium glutamicum strain by using genetic information of three classical producers. Sequence analysis of their arg operons identified three point mutations (argR123, argG92(up), and argG45) in one producer and one point mutation (argB26 or argB31) in each of the other two producers. Reconstitution of the former three mutations or of each argB mutation on a wild-type genome led to no production. Combined introduction of argB26 or argB31 with argR123 into a wild type gave rise to arginine/citrulline production. When argR123 was replaced by an argR-deleted mutation (Delta argR), the production was further increased. The best mutation set, Delta argR and argB26, was used to screen for the highest productivity in the backgrounds of different wild-type strains of C. glutamicum. This yielded a robust producer, RB, but the production was still one-third of that of the best classical producer. Transcriptome analysis revealed that the arg operon of the classical producer was much more highly upregulated than that of strain RB. Introduction of leuC456, a mutation derived from a classical L-lysine producer and provoking global induction of the amino acid biosynthesis genes, including the arg operon, into strain RB led to increased production but incurred retarded fermentation. On the other hand, replacement of the chromosomal argB by heterologous Escherichia coli argB, natively insensitive to arginine, caused a threefold-increased production without retardation, revealing that the limitation in strain RB was the activity of the argB product. To overcome this, in addition to argB26, the argB31 mutation was introduced into strain RB, which caused higher deregulation of the enzyme and resulted in dramatically increased production, like the strain with E. coli argB. This reconstructed strain displayed an enhanced performance, thus allowing significantly higher productivity of arginine/citrulline even at the suboptimal 38 degrees C.

Developing robust recurrence plot analysis techniques for investigating infant respiratory patterns.

PubMed

Terrill, Philip I; Wilson, Stephen; Suresh, Sadasivam; Cooper, David M

2007-01-01

Recurrence plot analysis is a useful non-linear analysis tool. There are still no well formalised procedures for carrying out this analysis on measured physiological data, and systemising analysis is often difficult. In this paper, the recurrence based embedding is compared to radius based embedding by studying a logistic attractor and measured breathing data collected from sleeping human infants. Recurrence based embedding appears to be a more robust method of carrying out a recurrence analysis when attractor size is likely to be different between datasets. In the infant breathing data, the radius measure calculated at a fixed recurrence, scaled by average respiratory period, allows the accurate discrimination of active sleep from quiet sleep states (AUC=0.975, Sn=098, Sp=0.94).

A robust optimization model for distribution and evacuation in the disaster response phase

NASA Astrophysics Data System (ADS)

Fereiduni, Meysam; Shahanaghi, Kamran

2017-03-01

Natural disasters, such as earthquakes, affect thousands of people and can cause enormous financial loss. Therefore, an efficient response immediately following a natural disaster is vital to minimize the aforementioned negative effects. This research paper presents a network design model for humanitarian logistics which will assist in location and allocation decisions for multiple disaster periods. At first, a single-objective optimization model is presented that addresses the response phase of disaster management. This model will help the decision makers to make the most optimal choices in regard to location, allocation, and evacuation simultaneously. The proposed model also considers emergency tents as temporary medical centers. To cope with the uncertainty and dynamic nature of disasters, and their consequences, our multi-period robust model considers the values of critical input data in a set of various scenarios. Second, because of probable disruption in the distribution infrastructure (such as bridges), the Monte Carlo simulation is used for generating related random numbers and different scenarios; the p-robust approach is utilized to formulate the new network. The p-robust approach can predict possible damages along pathways and among relief bases. We render a case study of our robust optimization approach for Tehran's plausible earthquake in region 1. Sensitivity analysis' experiments are proposed to explore the effects of various problem parameters. These experiments will give managerial insights and can guide DMs under a variety of conditions. Then, the performances of the "robust optimization" approach and the "p-robust optimization" approach are evaluated. Intriguing results and practical insights are demonstrated by our analysis on this comparison.

Guaranteeing robustness of structural condition monitoring to environmental variability

NASA Astrophysics Data System (ADS)

Van Buren, Kendra; Reilly, Jack; Neal, Kyle; Edwards, Harry; Hemez, François

2017-01-01

Advances in sensor deployment and computational modeling have allowed significant strides to be recently made in the field of Structural Health Monitoring (SHM). One widely used SHM strategy is to perform a vibration analysis where a model of the structure's pristine (undamaged) condition is compared with vibration response data collected from the physical structure. Discrepancies between model predictions and monitoring data can be interpreted as structural damage. Unfortunately, multiple sources of uncertainty must also be considered in the analysis, including environmental variability, unknown model functional forms, and unknown values of model parameters. Not accounting for these sources of uncertainty can lead to false-positives or false-negatives in the structural condition assessment. To manage the uncertainty, we propose a robust SHM methodology that combines three technologies. A time series algorithm is trained using "baseline" data to predict the vibration response, compare predictions to actual measurements collected on a potentially damaged structure, and calculate a user-defined damage indicator. The second technology handles the uncertainty present in the problem. An analysis of robustness is performed to propagate this uncertainty through the time series algorithm and obtain the corresponding bounds of variation of the damage indicator. The uncertainty description and robustness analysis are both inspired by the theory of info-gap decision-making. Lastly, an appropriate "size" of the uncertainty space is determined through physical experiments performed in laboratory conditions. Our hypothesis is that examining how the uncertainty space changes throughout time might lead to superior diagnostics of structural damage as compared to only monitoring the damage indicator. This methodology is applied to a portal frame structure to assess if the strategy holds promise for robust SHM. (Publication approved for unlimited, public release on October-28-2015, LA-UR-15-28442, unclassified.)

Robustness analysis of non-ordinary Petri nets for flexible assembly/disassembly processes based on structural decomposition

NASA Astrophysics Data System (ADS)

Hsieh, Fu-Shiung

2011-03-01

Design of robust supervisory controllers for manufacturing systems with unreliable resources has received significant attention recently. Robustness analysis provides an alternative way to analyse a perturbed system to quickly respond to resource failures. Although we have analysed the robustness properties of several subclasses of ordinary Petri nets (PNs), analysis for non-ordinary PNs has not been done. Non-ordinary PNs have weighted arcs and have the advantage to compactly model operations requiring multiple parts or resources. In this article, we consider a class of flexible assembly/disassembly manufacturing systems and propose a non-ordinary flexible assembly/disassembly Petri net (NFADPN) model for this class of systems. As the class of flexible assembly/disassembly manufacturing systems can be regarded as the integration and interactions of a set of assembly/disassembly subprocesses, a bottom-up approach is adopted in this article to construct the NFADPN models. Due to the routing flexibility in NFADPN, there may exist different ways to accomplish the tasks. To characterise different ways to accomplish the tasks, we propose the concept of completely connected subprocesses. As long as there exists a set of completely connected subprocesses for certain type of products, the production of that type of products can still be maintained without requiring the whole NFADPN to be live. To take advantage of the alternative routes without enforcing liveness for the whole system, we generalise the concept of persistent production proposed to NFADPN. We propose a condition for persistent production based on the concept of completely connected subprocesses. We extend robustness analysis to NFADPN by exploiting its structure. We identify several patterns of resource failures and characterise the conditions to maintain operation in the presence of resource failures.

Mapping the natural variation in whole bone stiffness and strength across skeletal sites.

PubMed

Schlecht, Stephen H; Bigelow, Erin M R; Jepsen, Karl J

2014-10-01

Traits of the skeletal system are coordinately adjusted to establish mechanical homeostasis in response to genetic and environmental factors. Prior work demonstrated that this 'complex adaptive' process is not perfect, revealing a two-fold difference in whole bone stiffness of the tibia across a population. Robustness (specifically, total cross-sectional area relative to length) varies widely across skeletal sites and between sexes. However, it is unknown whether the natural variation in whole bone stiffness and strength also varies across skeletal sites and between men and women. We tested the hypotheses that: 1) all major long bones of the appendicular skeleton demonstrate inherent, systemic constraints in the degree to which morphological and compositional traits can be adjusted for a given robustness; and 2) these traits covary in a predictable manner independent of body size and robustness. We assessed the functional relationships among robustness, cortical area (Ct.Ar), cortical tissue mineral density (Ct.TMD), and bone strength index (BSI) across the long bones of the upper and lower limbs of 115 adult men and women. All bones showed a significant (p<0.001) positive regression between BSI and robustness after adjusting for body size, with slender bones being 1.7-2.3 times less stiff and strong in men and 1.3-2.8 times less stiff and strong in women compared to robust bones. Our findings are the first to document the natural inter-individual variation in whole bone stiffness and strength that exist within populations and that is predictable based on skeletal robustness for all major long bones. Documenting and further understanding this natural variation in strength may be critical for differentially diagnosing and treating skeletal fragility. Copyright © 2014 Elsevier Inc. All rights reserved.

Mapping the natural variation in whole bone stiffness and strength across skeletal sites

PubMed Central

Schlecht, Stephen H.; Bigelow, Erin M.R.; Jepsen, Karl J.

2016-01-01

Traits of the skeletal system are coordinately adjusted to establish mechanical homeostasis in response to genetic and environmental factors. Prior work demonstrated that this `complex adaptive' process is not perfect, revealing a two-fold difference in whole bone stiffness of the tibia across a population. Robustness (specifically, total cross-sectional area relative to length) varies widely across skeletal sites and between sexes. However, it is unknown whether the natural variation in whole bone stiffness and strength also varies across skeletal sites and between men and women. We tested the hypotheses that: 1) all major long bones of the appendicular skeleton demonstrate inherent, systemic constraints in the degree to which morphological and compositional traits can be adjusted for a given robustness; and 2) these traits covary in a predictable manner independent of body size and robustness. We assessed the functional relationships among robustness, cortical area (Ct.Ar), cortical tissue mineral density (Ct.TMD), and bone strength index (BSI) across the long bones of the upper and lower limbs of 115 adult men and women. All bones showed a significant (p < 0.001) positive regression between BSI and robustness after adjusting for body size, with slender bones being 1.7–2.3 times less stiff and strong in men and 1.3–2.8 times less stiff and strong in women compared to robust bones. Our findings are the first to document the natural inter-individual variation in whole bone stiffness and strength that exist within populations and that is predictable based on skeletal robustness for all major long bones. Documenting and further understanding this natural variation in strength may be critical for differentially diagnosing and treating skeletal fragility. PMID:24999223

Simulated discharge trends indicate robustness of hydrological models in a changing climate

NASA Astrophysics Data System (ADS)

Addor, Nans; Nikolova, Silviya; Seibert, Jan

2016-04-01

Assessing the robustness of hydrological models under contrasted climatic conditions should be part any hydrological model evaluation. Robust models are particularly important for climate impact studies, as models performing well under current conditions are not necessarily capable of correctly simulating hydrological perturbations caused by climate change. A pressing issue is the usually assumed stationarity of parameter values over time. Modeling experiments using conceptual hydrological models revealed that assuming transposability of parameters values in changing climatic conditions can lead to significant biases in discharge simulations. This raises the question whether parameter values should to be modified over time to reflect changes in hydrological processes induced by climate change. Such a question denotes a focus on the contribution of internal processes (i.e., catchment processes) to discharge generation. Here we adopt a different perspective and explore the contribution of external forcing (i.e., changes in precipitation and temperature) to changes in discharge. We argue that in a robust hydrological model, discharge variability should be induced by changes in the boundary conditions, and not by changes in parameter values. In this study, we explore how well the conceptual hydrological model HBV captures transient changes in hydrological signatures over the period 1970-2009. Our analysis focuses on research catchments in Switzerland undisturbed by human activities. The precipitation and temperature forcing are extracted from recently released 2km gridded data sets. We use a genetic algorithm to calibrate HBV for the whole 40-year period and for the eight successive 5-year periods to assess eventual trends in parameter values. Model calibration is run multiple times to account for parameter uncertainty. We find that in alpine catchments showing a significant increase of winter discharge, this trend can be captured reasonably well with constant parameter values over the whole reference period. Further, preliminary results suggest that some trends in parameter values do not reflect changes in hydrological processes, as reported by others previously, but instead might stem from a modeling artifact related to the parameterization of evapotranspiration, which is overly sensitive to temperature increase. We adopt a trading-space-for-time approach to better understand whether robust relationships between parameter values and forcing can be established, and to critically explore the rationale behind time-dependent parameter values in conceptual hydrological models.

Diagnostics of Robust Growth Curve Modeling Using Student's "t" Distribution

ERIC Educational Resources Information Center

Tong, Xin; Zhang, Zhiyong

2012-01-01

Growth curve models with different types of distributions of random effects and of intraindividual measurement errors for robust analysis are compared. After demonstrating the influence of distribution specification on parameter estimation, 3 methods for diagnosing the distributions for both random effects and intraindividual measurement errors…

Robust MOE Detector for DS-CDMA Systems with Signature Waveform Mismatch

NASA Astrophysics Data System (ADS)

Lin, Tsui-Tsai

In this letter, a decision-directed MOE detector with excellent robustness against signature waveform mismatch is proposed for DS-CDMA systems. Both the theoretic analysis and computer simulation results demonstrate that the proposed detector can provide better SINR performance than that of conventional detectors.

Meta-proteomic analysis of protein expression distinctive to electricity-generating biofilm communities in air-cathode microbial fuel cells.

PubMed

Chignell, Jeremy F; De Long, Susan K; Reardon, Kenneth F

2018-01-01

Bioelectrochemical systems (BESs) harness electrons from microbial respiration to generate power or chemical products from a variety of organic feedstocks, including lignocellulosic biomass, fermentation byproducts, and wastewater sludge. In some BESs, such as microbial fuel cells (MFCs), bacteria living in a biofilm use the anode as an electron acceptor for electrons harvested from organic materials such as lignocellulosic biomass or waste byproducts, generating energy that may be used by humans. Many BES applications use bacterial biofilm communities, but no studies have investigated protein expression by the anode biofilm community as a whole. To discover functional protein expression during current generation that may be useful for MFC optimization, a label-free meta-proteomics approach was used to compare protein expression in acetate-fed anode biofilms before and after the onset of robust electricity generation. Meta-proteomic comparisons were integrated with 16S rRNA gene-based community analysis at four developmental stages. The community composition shifted from dominance by aerobic Gammaproteobacteria (90.9 ± 3.3%) during initial biofilm formation to dominance by Deltaproteobacteria , particularly Geobacter (68.7 ± 3.6%) in mature, electricity-generating anodes. Community diversity in the intermediate stage, just after robust current generation began, was double that at the early stage and nearly double that of mature anode communities. Maximum current densities at the intermediate stage, however, were relatively similar (~ 83%) to those achieved by mature-stage biofilms. Meta-proteomic analysis, correlated with population changes, revealed significant enrichment of categories specific to membrane and transport functions among proteins from electricity-producing biofilms. Proteins detected only in electricity-producing biofilms were associated with gluconeogenesis, the glyoxylate cycle, and fatty acid β-oxidation, as well as with denitrification and competitive inhibition. The results demonstrate that it is possible for an MFC microbial community to generate robust current densities while exhibiting high taxonomic diversity. Moreover, these data provide evidence to suggest that startup growth of air-cathode MFCs under conditions that promote the establishment of aerobic-anaerobic syntrophy may decrease startup times. This study represents the first investigation into protein expression of a complex BES anode biofilm community as a whole. The findings contribute to understanding of the molecular mechanisms at work during BES startup and suggest options for improvement of BES generation of bioelectricity from renewable biomass.

Designing Phononic Crystals with Wide and Robust Band Gaps

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jia, Zian; Chen, Yanyu; Yang, Haoxiang

Here, phononic crystals (PnCs) engineered to manipulate and control the propagation of mechanical waves have enabled the design of a range of novel devices, such as waveguides, frequency modulators, and acoustic cloaks, for which wide and robust phononic band gaps are highly preferable. While numerous PnCs have been designed in recent decades, to the best of our knowledge, PnCs that possess simultaneous wide and robust band gaps (to randomness and deformations) have not yet been reported. Here, we demonstrate that by combining the band-gap formation mechanisms of Bragg scattering and local resonances (the latter one is dominating), PnCs with widemore » and robust phononic band gaps can be established. The robustness of the phononic band gaps are then discussed from two aspects: robustness to geometric randomness (manufacture defects) and robustness to deformations (mechanical stimuli). Analytical formulations further predict the optimal design parameters, and an uncertainty analysis quantifies the randomness effect of each designing parameter. Moreover, we show that the deformation robustness originates from a local resonance-dominant mechanism together with the suppression of structural instability. Importantly, the proposed PnCs require only a small number of layers of elements (three unit cells) to obtain broad, robust, and strong attenuation bands, which offer great potential in designing flexible and deformable phononic devices.« less

Designing Phononic Crystals with Wide and Robust Band Gaps

DOE PAGES

Jia, Zian; Chen, Yanyu; Yang, Haoxiang; ...

2018-04-16

Here, phononic crystals (PnCs) engineered to manipulate and control the propagation of mechanical waves have enabled the design of a range of novel devices, such as waveguides, frequency modulators, and acoustic cloaks, for which wide and robust phononic band gaps are highly preferable. While numerous PnCs have been designed in recent decades, to the best of our knowledge, PnCs that possess simultaneous wide and robust band gaps (to randomness and deformations) have not yet been reported. Here, we demonstrate that by combining the band-gap formation mechanisms of Bragg scattering and local resonances (the latter one is dominating), PnCs with widemore » and robust phononic band gaps can be established. The robustness of the phononic band gaps are then discussed from two aspects: robustness to geometric randomness (manufacture defects) and robustness to deformations (mechanical stimuli). Analytical formulations further predict the optimal design parameters, and an uncertainty analysis quantifies the randomness effect of each designing parameter. Moreover, we show that the deformation robustness originates from a local resonance-dominant mechanism together with the suppression of structural instability. Importantly, the proposed PnCs require only a small number of layers of elements (three unit cells) to obtain broad, robust, and strong attenuation bands, which offer great potential in designing flexible and deformable phononic devices.« less

Designing Phononic Crystals with Wide and Robust Band Gaps

NASA Astrophysics Data System (ADS)

Jia, Zian; Chen, Yanyu; Yang, Haoxiang; Wang, Lifeng

2018-04-01

Phononic crystals (PnCs) engineered to manipulate and control the propagation of mechanical waves have enabled the design of a range of novel devices, such as waveguides, frequency modulators, and acoustic cloaks, for which wide and robust phononic band gaps are highly preferable. While numerous PnCs have been designed in recent decades, to the best of our knowledge, PnCs that possess simultaneous wide and robust band gaps (to randomness and deformations) have not yet been reported. Here, we demonstrate that by combining the band-gap formation mechanisms of Bragg scattering and local resonances (the latter one is dominating), PnCs with wide and robust phononic band gaps can be established. The robustness of the phononic band gaps are then discussed from two aspects: robustness to geometric randomness (manufacture defects) and robustness to deformations (mechanical stimuli). Analytical formulations further predict the optimal design parameters, and an uncertainty analysis quantifies the randomness effect of each designing parameter. Moreover, we show that the deformation robustness originates from a local resonance-dominant mechanism together with the suppression of structural instability. Importantly, the proposed PnCs require only a small number of layers of elements (three unit cells) to obtain broad, robust, and strong attenuation bands, which offer great potential in designing flexible and deformable phononic devices.

The comparison of robust partial least squares regression with robust principal component regression on a real

NASA Astrophysics Data System (ADS)

Polat, Esra; Gunay, Suleyman

2013-10-01

One of the problems encountered in Multiple Linear Regression (MLR) is multicollinearity, which causes the overestimation of the regression parameters and increase of the variance of these parameters. Hence, in case of multicollinearity presents, biased estimation procedures such as classical Principal Component Regression (CPCR) and Partial Least Squares Regression (PLSR) are then performed. SIMPLS algorithm is the leading PLSR algorithm because of its speed, efficiency and results are easier to interpret. However, both of the CPCR and SIMPLS yield very unreliable results when the data set contains outlying observations. Therefore, Hubert and Vanden Branden (2003) have been presented a robust PCR (RPCR) method and a robust PLSR (RPLSR) method called RSIMPLS. In RPCR, firstly, a robust Principal Component Analysis (PCA) method for high-dimensional data on the independent variables is applied, then, the dependent variables are regressed on the scores using a robust regression method. RSIMPLS has been constructed from a robust covariance matrix for high-dimensional data and robust linear regression. The purpose of this study is to show the usage of RPCR and RSIMPLS methods on an econometric data set, hence, making a comparison of two methods on an inflation model of Turkey. The considered methods have been compared in terms of predictive ability and goodness of fit by using a robust Root Mean Squared Error of Cross-validation (R-RMSECV), a robust R2 value and Robust Component Selection (RCS) statistic.

Characterizing uncertain sea-level rise projections to support investment decisions.

PubMed

Sriver, Ryan L; Lempert, Robert J; Wikman-Svahn, Per; Keller, Klaus

2018-01-01

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions.

Characterizing uncertain sea-level rise projections to support investment decisions

PubMed Central

Lempert, Robert J.; Wikman-Svahn, Per; Keller, Klaus

2018-01-01

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions. PMID:29414978

Death Competence: An Ethical Imperative

ERIC Educational Resources Information Center

Gamino, Louis A.; Ritter, R. Hal, Jr.

2012-01-01

The authors argued that death competence, defined as specialized skill in tolerating and managing clients' problems related to dying, death, and bereavement, is a necessary prerequisite for ethical practice in grief counseling. A selected review of the literature tracing the underpinnings of this concept reveals how a robust construct of death…

How Augmented Reality Enables Conceptual Understanding of Challenging Science Content

ERIC Educational Resources Information Center

Yoon, Susan; Anderson, Emma; Lin, Joyce; Elinich, Karen

2017-01-01

Research on learning about science has revealed that students often hold robust misconceptions about a number of scientific ideas. Digital simulation and dynamic visualization tools have helped to ameliorate these learning challenges by providing scaffolding to understand various aspects of the phenomenon. In this study we hypothesize that…

Robustness of the Sequential Lineup Advantage

ERIC Educational Resources Information Center

Gronlund, Scott D.; Carlson, Curt A.; Dailey, Sarah B.; Goodsell, Charles A.

2009-01-01

A growing movement in the United States and around the world involves promoting the advantages of conducting an eyewitness lineup in a sequential manner. We conducted a large study (N = 2,529) that included 24 comparisons of sequential versus simultaneous lineups. A liberal statistical criterion revealed only 2 significant sequential lineup…

Fathead Minnow Steroidogenesis: In Silico Analyses Reveals Tradeoffs Between Nominal Target Efficacy and Robustness to Cross-talk

EPA Science Inventory

This paper presents the formulation and evaluation of a mechanistic mathematical model of fathead minnow ovarian steroidogenesis. The model presented in the present study was adpated from other models developed as part of an integrated, multi-disciplinary computational toxicolog...

Whole genome sequencing reveals an outbreak of Salmonella Enteritidis associated with reptile feeder mice in the United Kingdom, 2012-2015.

PubMed

Kanagarajah, Sanch; Waldram, Alison; Dolan, Gayle; Jenkins, Claire; Ashton, Philip M; Carrion Martin, Antonio Isidro; Davies, Robert; Frost, Andrew; Dallman, Timothy J; De Pinna, Elizabeth M; Hawker, Jeremy I; Grant, Kathie A; Elson, Richard

2018-05-01

Analysis of whole genome sequencing data uncovered a previously undetected outbreak of Salmonella Enteritidis that had been on-going for four years. Cases were resident in all countries of the United Kingdom and 40% of the cases were aged less than 11 years old. Initial investigations revealed that 30% of cases reported exposure to pet snakes. A case-control study was designed to test the hypothesis that exposure to reptiles or their feed were risk factors. A robust case-definition, based on the single nucleotide polymorphism (SNP) profile, increased the power of the analytical study. Following univariable and multivariable analysis, exposure to snakes was the only variable independently associated with infection (Odds ratio 810 95% CI (85-7715) p < 0.001). Isolates of S. Enteritidis belonging to the outbreak profile were recovered from reptile feeder mice sampled at the retail and wholesale level. Control measures included improved public health messaging at point of sale, press releases and engagement with public health and veterinary counterparts across Europe. Mice destined to be fed to reptiles are not regarded as pet food and are not routinely tested for pathogenic bacteria. Routine microbiological testing to ensure feeder mice are free from Salmonella is recommended. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Quantitative proteomics reveals dynamic responses of Synechocystis sp. PCC 6803 to next-generation biofuel butanol.

PubMed

Tian, Xiaoxu; Chen, Lei; Wang, Jiangxin; Qiao, Jianjun; Zhang, Weiwen

2013-01-14

Butanol is a promising biofuel, and recent metabolic engineering efforts have demonstrated the use of photosynthetic cyanobacterial hosts for its production. However, cyanobacteria have very low tolerance to butanol, limiting the economic viability of butanol production from these renewable producing systems. The existing knowledge of molecular mechanism involved in butanol tolerance in cyanobacteria is very limited. To build a foundation necessary to engineer robust butanol-producing cyanobacterial hosts, in this study, the responses of Synechocystis PCC 6803 to butanol were investigated using a quantitative proteomics approach with iTRAQ - LC-MS/MS technologies. The resulting high-quality dataset consisted of 25,347 peptides corresponding to 1452 unique proteins, a coverage of approximately 40% of the predicted proteins in Synechocystis. Comparative quantification of protein abundances led to the identification of 303 differentially regulated proteins by butanol. Annotation and GO term enrichment analysis showed that multiple biological processes were regulated, suggesting that Synechocystis probably employed multiple and synergistic resistance mechanisms in dealing with butanol stress. Notably, the analysis revealed the induction of heat-shock protein and transporters, along with modification of cell membrane and envelope were the major protection mechanisms against butanol. A conceptual cellular model of Synechocystis PCC 6803 responses to butanol stress was constructed to illustrate the putative molecular mechanisms employed to defend against butanol stress. Copyright © 2012 Elsevier B.V. All rights reserved.

Multi-locus phylogenetic analysis reveals the pattern and tempo of bony fish evolution

PubMed Central

Broughton, Richard E.; Betancur-R., Ricardo; Li, Chenhong; Arratia, Gloria; Ortí, Guillermo

2013-01-01

Over half of all vertebrates are “fishes”, which exhibit enormous diversity in morphology, physiology, behavior, reproductive biology, and ecology. Investigation of fundamental areas of vertebrate biology depend critically on a robust phylogeny of fishes, yet evolutionary relationships among the major actinopterygian and sarcopterygian lineages have not been conclusively resolved. Although a consensus phylogeny of teleosts has been emerging recently, it has been based on analyses of various subsets of actinopterygian taxa, but not on a full sample of all bony fishes. Here we conducted a comprehensive phylogenetic study on a broad taxonomic sample of 61 actinopterygian and sarcopterygian lineages (with a chondrichthyan outgroup) using a molecular data set of 21 independent loci. These data yielded a resolved phylogenetic hypothesis for extant Osteichthyes, including 1) reciprocally monophyletic Sarcopterygii and Actinopterygii, as currently understood, with polypteriforms as the first diverging lineage within Actinopterygii; 2) a monophyletic group containing gars and bowfin (= Holostei) as sister group to teleosts; and 3) the earliest diverging lineage among teleosts being Elopomorpha, rather than Osteoglossomorpha. Relaxed-clock dating analysis employing a set of 24 newly applied fossil calibrations reveals divergence times that are more consistent with paleontological estimates than previous studies. Establishing a new phylogenetic pattern with accurate divergence dates for bony fishes illustrates several areas where the fossil record is incomplete and provides critical new insights on diversification of this important vertebrate group. PMID:23788273

Risk, Robustness and Water Resources Planning Under Uncertainty

NASA Astrophysics Data System (ADS)

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.

Relationship of cranial robusticity to cranial form, geography and climate in Homo sapiens.

PubMed

Baab, Karen L; Freidline, Sarah E; Wang, Steven L; Hanson, Timothy

2010-01-01

Variation in cranial robusticity among modern human populations is widely acknowledged but not well-understood. While the use of "robust" cranial traits in hominin systematics and phylogeny suggests that these characters are strongly heritable, this hypothesis has not been tested. Alternatively, cranial robusticity may be a response to differences in diet/mastication or it may be an adaptation to cold, harsh environments. This study quantifies the distribution of cranial robusticity in 14 geographically widespread human populations, and correlates this variation with climatic variables, neutral genetic distances, cranial size, and cranial shape. With the exception of the occipital torus region, all traits were positively correlated with each other, suggesting that they should not be treated as individual characters. While males are more robust than females within each of the populations, among the independent variables (cranial shape, size, climate, and neutral genetic distances), only shape is significantly correlated with inter-population differences in robusticity. Two-block partial least-squares analysis was used to explore the relationship between cranial shape (captured by three-dimensional landmark data) and robusticity across individuals. Weak support was found for the hypothesis that robusticity was related to mastication as the shape associated with greater robusticity was similar to that described for groups that ate harder-to-process diets. Specifically, crania with more prognathic faces, expanded glabellar and occipital regions, and (slightly) longer skulls were more robust than those with rounder vaults and more orthognathic faces. However, groups with more mechanically demanding diets (hunter-gatherers) were not always more robust than groups practicing some form of agriculture.

Using Robust Variance Estimation to Combine Multiple Regression Estimates with Meta-Analysis

ERIC Educational Resources Information Center

Williams, Ryan

2013-01-01

The purpose of this study was to explore the use of robust variance estimation for combining commonly specified multiple regression models and for combining sample-dependent focal slope estimates from diversely specified models. The proposed estimator obviates traditionally required information about the covariance structure of the dependent…

The Robustness of LISREL Estimates in Structural Equation Models with Categorical Variables.

ERIC Educational Resources Information Center

Ethington, Corinna A.

1987-01-01

This study examined the effect of type of correlation matrix on the robustness of LISREL maximum likelihood and unweighted least squares structural parameter estimates for models with categorical variables. The analysis of mixed matrices produced estimates that closely approximated the model parameters except where dichotomous variables were…

IMPLICATIONS OF USING ROBUST BAYESIAN ANALYSIS TO REPRESENT DIVERSE SOURCES OF UNCERTAINTY IN INTEGRATED ASSESSMENT

EPA Science Inventory

In our previous research, we showed that robust Bayesian methods can be used in environmental modeling to define a set of probability distributions for key parameters that captures the effects of expert disagreement, ambiguity, or ignorance. This entire set can then be update...

Robust watermarking scheme for binary images using a slice-based large-cluster algorithm with a Hamming Code

NASA Astrophysics Data System (ADS)

Chen, Wen-Yuan; Liu, Chen-Chung

2006-01-01

The problems with binary watermarking schemes are that they have only a small amount of embeddable space and are not robust enough. We develop a slice-based large-cluster algorithm (SBLCA) to construct a robust watermarking scheme for binary images. In SBLCA, a small-amount cluster selection (SACS) strategy is used to search for a feasible slice in a large-cluster flappable-pixel decision (LCFPD) method, which is used to search for the best location for concealing a secret bit from a selected slice. This method has four major advantages over the others: (a) SBLCA has a simple and effective decision function to select appropriate concealment locations, (b) SBLCA utilizes a blind watermarking scheme without the original image in the watermark extracting process, (c) SBLCA uses slice-based shuffling capability to transfer the regular image into a hash state without remembering the state before shuffling, and finally, (d) SBLCA has enough embeddable space that every 64 pixels could accommodate a secret bit of the binary image. Furthermore, empirical results on test images reveal that our approach is a robust watermarking scheme for binary images.

Enhanced robustness of evolving open systems by the bidirectionality of interactions between elements.

PubMed

Ogushi, Fumiko; Kertész, János; Kaski, Kimmo; Shimada, Takashi

2017-08-01

Living organisms, ecosystems, and social systems are examples of complex systems in which robustness against inclusion of new elements is an essential feature. A recently proposed simple model has revealed a general mechanism by which such systems can become robust against inclusion of elements with totally random interactions when the elements have a moderate number of links. The interaction is, however, in many systems often intrinsically bidirectional like for mutual symbiosis and competition in ecology. This study reports the strong reinforcement effect of the bidirectionality of the interactions on the robustness of evolving systems. We show that the system with purely bidirectional interactions can grow with twofold average degree, in comparison with the purely unidirectional system. This drastic shift of the transition point comes from the reinforcement of each node, not from a change in structure of the emergent system. For systems with partially bidirectional interactions we find that the regime of the growing phase gets expanded. In the dense interaction regime, there exists an optimum proportion of bidirectional interactions for the growth rate at around 1/3. In the sparsely connected systems, small but finite fraction of bidirectional links can change the system's behaviour from non-growing to growing.

Worst-Case Flutter Margins from F/A-18 Aircraft Aeroelastic Data

NASA Technical Reports Server (NTRS)

Lind, Rick; Brenner, Marty

1997-01-01

An approach for computing worst-case flutter margins has been formulated in a robust stability framework. Uncertainty operators are included with a linear model to describe modeling errors and flight variations. The structured singular value, micron, computes a stability margin which directly accounts for these uncertainties. This approach introduces a new method of computing flutter margins and an associated new parameter for describing these margins. The micron margins are robust margins which indicate worst-case stability estimates with respect to the defined uncertainty. Worst-case flutter margins are computed for the F/A-18 SRA using uncertainty sets generated by flight data analysis. The robust margins demonstrate flight conditions for flutter may lie closer to the flight envelope than previously estimated by p-k analysis.

On the robustness of a Bayes estimate. [in reliability theory

NASA Technical Reports Server (NTRS)

Canavos, G. C.

1974-01-01

This paper examines the robustness of a Bayes estimator with respect to the assigned prior distribution. A Bayesian analysis for a stochastic scale parameter of a Weibull failure model is summarized in which the natural conjugate is assigned as the prior distribution of the random parameter. The sensitivity analysis is carried out by the Monte Carlo method in which, although an inverted gamma is the assigned prior, realizations are generated using distribution functions of varying shape. For several distributional forms and even for some fixed values of the parameter, simulated mean squared errors of Bayes and minimum variance unbiased estimators are determined and compared. Results indicate that the Bayes estimator remains squared-error superior and appears to be largely robust to the form of the assigned prior distribution.

Position Accuracy Analysis of a Robust Vision-Based Navigation

NASA Astrophysics Data System (ADS)

Gaglione, S.; Del Pizzo, S.; Troisi, S.; Angrisano, A.

2018-05-01

Using images to determine camera position and attitude is a consolidated method, very widespread for application like UAV navigation. In harsh environment, where GNSS could be degraded or denied, image-based positioning could represent a possible candidate for an integrated or alternative system. In this paper, such method is investigated using a system based on single camera and 3D maps. A robust estimation method is proposed in order to limit the effect of blunders or noisy measurements on position solution. The proposed approach is tested using images collected in an urban canyon, where GNSS positioning is very unaccurate. A previous photogrammetry survey has been performed to build the 3D model of tested area. The position accuracy analysis is performed and the effect of the robust method proposed is validated.

Reciprocity Between Robustness of Period and Plasticity of Phase in Biological Clocks

NASA Astrophysics Data System (ADS)

Hatakeyama, Tetsuhiro S.; Kaneko, Kunihiko

2015-11-01

Circadian clocks exhibit the robustness of period and plasticity of phase against environmental changes such as temperature and nutrient conditions. Thus far, however, it is unclear how both are simultaneously achieved. By investigating distinct models of circadian clocks, we demonstrate reciprocity between robustness and plasticity: higher robustness in the period implies higher plasticity in the phase, where changes in period and in phase follow a linear relationship with a negative coefficient. The robustness of period is achieved by the adaptation on the limit cycle via a concentration change of a buffer molecule, whose temporal change leads to a phase shift following a shift of the limit-cycle orbit in phase space. Generality of reciprocity in clocks with the adaptation mechanism is confirmed with theoretical analysis of simple models, while biological significance is discussed.

New robust statistical procedures for the polytomous logistic regression models.

PubMed

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.

Robustness of reduced-order multivariable state-space self-tuning controller

NASA Technical Reports Server (NTRS)

Yuan, Zhuzhi; Chen, Zengqiang

1994-01-01

In this paper, we present a quantitative analysis of the robustness of a reduced-order pole-assignment state-space self-tuning controller for a multivariable adaptive control system whose order of the real process is higher than that of the model used in the controller design. The result of stability analysis shows that, under a specific bounded modelling error, the adaptively controlled closed-loop real system via the reduced-order state-space self-tuner is BIBO stable in the presence of unmodelled dynamics.

LL-37 Recruits Immunosuppressive Regulatory T Cells to Ovarian Tumors

DTIC Science & Technology

2009-11-01

receptor. Western blot analysis of MSC lysates showed that ERK-1 and -2 are robustly phosphorylated beginning 10 minutes after LL-37 treatment and...Carretero, Escamez et al. 2008; von Haussen, Koczulla et al. 2008). Western blot analysis of LL-37-treated SK-OV-3 cell lysates showed the robust...mesenchymal stem cells in the treatment of gliomas ." Cancer Res 65(8): 3307-18. Studeny, M., F. C. Marini, et al. (2004). "Mesenchymal stem cells: potential

Robust analysis of an underwater navigational strategy in electrically heterogeneous corridors.

PubMed

Dimble, Kedar D; Ranganathan, Badri N; Keshavan, Jishnu; Humbert, J Sean

2016-08-01

Obstacles and other global stimuli provide relevant navigational cues to a weakly electric fish. In this work, robust analysis of a control strategy based on electrolocation for performing obstacle avoidance in electrically heterogeneous corridors is presented and validated. Static output feedback control is shown to achieve the desired goal of reflexive obstacle avoidance in such environments in simulation and experimentation. The proposed approach is computationally inexpensive and readily implementable on a small scale underwater vehicle, making underwater autonomous navigation feasible in real-time.

Feasible logic Bell-state analysis with linear optics

PubMed Central

Zhou, Lan; Sheng, Yu-Bo

2016-01-01

We describe a feasible logic Bell-state analysis protocol by employing the logic entanglement to be the robust concatenated Greenberger-Horne-Zeilinger (C-GHZ) state. This protocol only uses polarization beam splitters and half-wave plates, which are available in current experimental technology. We can conveniently identify two of the logic Bell states. This protocol can be easily generalized to the arbitrary C-GHZ state analysis. We can also distinguish two N-logic-qubit C-GHZ states. As the previous theory and experiment both showed that the C-GHZ state has the robustness feature, this logic Bell-state analysis and C-GHZ state analysis may be essential for linear-optical quantum computation protocols whose building blocks are logic-qubit entangled state. PMID:26877208

Feasible logic Bell-state analysis with linear optics.

PubMed

Zhou, Lan; Sheng, Yu-Bo

2016-02-15

We describe a feasible logic Bell-state analysis protocol by employing the logic entanglement to be the robust concatenated Greenberger-Horne-Zeilinger (C-GHZ) state. This protocol only uses polarization beam splitters and half-wave plates, which are available in current experimental technology. We can conveniently identify two of the logic Bell states. This protocol can be easily generalized to the arbitrary C-GHZ state analysis. We can also distinguish two N-logic-qubit C-GHZ states. As the previous theory and experiment both showed that the C-GHZ state has the robustness feature, this logic Bell-state analysis and C-GHZ state analysis may be essential for linear-optical quantum computation protocols whose building blocks are logic-qubit entangled state.

Local Orthogonal Cutting Method for Computing Medial Curves and Its Biomedical Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiao, Xiangmin; Einstein, Daniel R.; Dyedov, Volodymyr

2010-03-24

Medial curves have a wide range of applications in geometric modeling and analysis (such as shape matching) and biomedical engineering (such as morphometry and computer assisted surgery). The computation of medial curves poses significant challenges, both in terms of theoretical analysis and practical efficiency and reliability. In this paper, we propose a definition and analysis of medial curves and also describe an efficient and robust method for computing medial curves. Our approach is based on three key concepts: a local orthogonal decomposition of objects into substructures, a differential geometry concept called the interior center of curvature (ICC), and integrated stabilitymore » and consistency tests. These concepts lend themselves to robust numerical techniques including eigenvalue analysis, weighted least squares approximations, and numerical minimization, resulting in an algorithm that is efficient and noise resistant. We illustrate the effectiveness and robustness of our approach with some highly complex, large-scale, noisy biomedical geometries derived from medical images, including lung airways and blood vessels. We also present comparisons of our method with some existing methods.« less

Robust demarcation of basal cell carcinoma by dependent component analysis-based segmentation of multi-spectral fluorescence images.

PubMed

Kopriva, Ivica; Persin, Antun; Puizina-Ivić, Neira; Mirić, Lina

2010-07-02

This study was designed to demonstrate robust performance of the novel dependent component analysis (DCA)-based approach to demarcation of the basal cell carcinoma (BCC) through unsupervised decomposition of the red-green-blue (RGB) fluorescent image of the BCC. Robustness to intensity fluctuation is due to the scale invariance property of DCA algorithms, which exploit spectral and spatial diversities between the BCC and the surrounding tissue. Used filtering-based DCA approach represents an extension of the independent component analysis (ICA) and is necessary in order to account for statistical dependence that is induced by spectral similarity between the BCC and surrounding tissue. This generates weak edges what represents a challenge for other segmentation methods as well. By comparative performance analysis with state-of-the-art image segmentation methods such as active contours (level set), K-means clustering, non-negative matrix factorization, ICA and ratio imaging we experimentally demonstrate good performance of DCA-based BCC demarcation in two demanding scenarios where intensity of the fluorescent image has been varied almost two orders of magnitude. Copyright 2010 Elsevier B.V. All rights reserved.

Analysing the impact of nucleo-cytoplasmic shuttling of β-catenin and its antagonists APC, Axin and GSK3 on Wnt/β-catenin signalling.

PubMed

Schmitz, Yvonne; Rateitschak, Katja; Wolkenhauer, Olaf

2013-11-01

The canonical Wnt signalling pathway plays a critical role in development and disease. The key player of the pathway is β-catenin. Its activity is mainly regulated by the destruction complex consisting of APC, Axin and GSK3. In the nucleus, the complex formation of β-catenin and TCF initiates target gene expression. Our study provides a comprehensive analysis of the role of nucleo-cytoplasmic shuttling of APC, Axin, and GSK3 and the inactivation of β-catenin by the destruction complex in Wnt/β-catenin signalling. We address the following questions: Can nucleo-cytoplasmic shuttling of APC, Axin and GSK3 increase the [β-catenin/TCF] concentration? And, how is the [β-catenin/TCF] concentration influenced by phosphorylation and subsequent degradation of nuclear β-catenin? Based on experimental findings, we develop a compartmental model and conduct several simulation experiments. Our analysis reveals the following key findings: 1) nucleo-cytoplasmic shuttling of β-catenin and its antagonists can yield a spatial separation between the said proteins, which results in a breakdown of β-catenin degradation, followed by an accumulation of β-catenin and hence leads to an increase of the [β-catenin/TCF] concentration. Our results strongly suggest that Wnt signalling can benefit from nucleo-cytoplasmic shuttling of APC, Axin and GSK3, although they are in general β-catenin antagonising proteins. 2) The total robustness of the [β-catenin/TCF] output is closely linked to its absolute concentration levels. We demonstrate that the compartmental separation of β-catenin and the destruction complex does not only lead to a maximization, but additionally to an increased robustness of [β-catenin/TCF] signalling against perturbations in the cellular environment. 3) A nuclear accumulation of the destruction complex renders the pathway robust against fluctuations in Wnt signalling and against changes in the compartmental distribution of β-catenin. 4) Elucidating the impact of destruction complex inhibition, we show that the [β-catenin/TCF] concentration is more effectively enhanced by inhibition of the kinase GSK3 rather than the binding of β-catenin to the destruction complex. © 2013 Elsevier Inc. All rights reserved.

Acute social stress-induced immunomodulation in pigs high and low responders to ACTH.

PubMed

Bacou, Elodie; Haurogné, Karine; Mignot, Grégoire; Allard, Marie; De Beaurepaire, Laurence; Marchand, Jordan; Terenina, Elena; Billon, Yvon; Jacques, Julien; Bach, Jean-Marie; Mormède, Pierre; Hervé, Julie; Lieubeau, Blandine

2017-02-01

Pig husbandry is known as an intensive breeding system, piglets being submitted to multiple stressful events such as early weaning, successive mixing, crowding and shipping. These stressors are thought to impair immune defences and might contribute, at least partly, to the prophylactic use of antibiotics. Robustness was recently defined as the ability of an individual to express a high-production potential in a wide variety of environmental conditions. Increasing robustness thus appears as a valuable option to improve resilience to stressors and could be obtained by selecting piglets upon their adrenocortical activity. In this study, we aimed at depicting the consequences of an acute social stress on the immune capacity of piglets genetically selected upon divergent hypothalamic-pituitary-adrenocortical (HPA) axis activity. For this purpose, we monitored neuroendocrine and immune parameters, in high- (HPA hi ) and low- (HPA lo ) responders to ACTH, just before and immediately after a one-hour mixing with unfamiliar conspecifics. As expected, stressed piglets displayed higher levels of circulating cortisol and norepinephrine. Blood cell count analysis combined to flow cytometry revealed a stress-induced leukocyte mobilization in the bloodstream with a specific recruitment of CD8α + lymphocytes. Besides, one-hour mixing decreased LPS-induced IL-8 and TNFα secretions in whole-blood assays (WBA) and reduced mononuclear cell phagocytosis. Altogether, our data demonstrate that acute social stress alters immune competence of piglets from both groups, and bring new insights in favour of good farming practices. While for most parameters high- and low-responders to ACTH behaved similarly, HPA hi piglets displayed higher number of CD4 + CD8α - T cells, as well as increased cytokine production in WBA (LPS-induced TNFα and PIL-induced IL-8), which could confer them increased resistance to pathogens. Finally, a principal component analysis including all parameters highlighted that overall stress effects were less pronounced on piglets with a strong HPA axis. Thus, selection upon adrenocortical axis activity seems to reduce the magnitude of response to stress and appears as a good tool to increase piglet robustness. Copyright © 2016 Elsevier Inc. All rights reserved.

Vortex line topology during vortex tube reconnection

NASA Astrophysics Data System (ADS)

McGavin, P.; Pontin, D. I.

2018-05-01

This paper addresses reconnection of vortex tubes, with particular focus on the topology of the vortex lines (field lines of the vorticity). This analysis of vortex line topology reveals key features of the reconnection process, such as the generation of many small flux rings, formed when reconnection occurs in multiple locations in the vortex sheet between the tubes. Consideration of three-dimensional reconnection principles leads to a robust measurement of the reconnection rate, even once instabilities break the symmetry. It also allows us to identify internal reconnection of vortex lines within the individual vortex tubes. Finally, the introduction of a third vortex tube is shown to render the vortex reconnection process fully three-dimensional, leading to a fundamental change in the topological structure of the process. An additional interesting feature is the generation of vorticity null points.

Phenotypic Diagnosis of Lineage and Differentiation During Sake Yeast Breeding

PubMed Central

Ohnuki, Shinsuke; Okada, Hiroki; Friedrich, Anne; Kanno, Yoichiro; Goshima, Tetsuya; Hasuda, Hirokazu; Inahashi, Masaaki; Okazaki, Naoto; Tamura, Hiroyasu; Nakamura, Ryo; Hirata, Dai; Fukuda, Hisashi; Shimoi, Hitoshi; Kitamoto, Katsuhiko; Watanabe, Daisuke; Schacherer, Joseph; Akao, Takeshi; Ohya, Yoshikazu

2017-01-01

Sake yeast was developed exclusively in Japan. Its diversification during breeding remains largely uncharacterized. To evaluate the breeding processes of the sake lineage, we thoroughly investigated the phenotypes and differentiation of 27 sake yeast strains using high-dimensional, single-cell, morphological phenotyping. Although the genetic diversity of the sake yeast lineage is relatively low, its morphological diversity has expanded substantially compared to that of the Saccharomyces cerevisiae species as a whole. Evaluation of the different types of breeding processes showed that the generation of hybrids (crossbreeding) has more profound effects on cell morphology than the isolation of mutants (mutation breeding). Analysis of phenotypic robustness revealed that some sake yeast strains are more morphologically heterogeneous, possibly due to impairment of cellular network hubs. This study provides a new perspective for studying yeast breeding genetics and micro-organism breeding strategies. PMID:28642365

First freshwater member ever reported for the family Bathycoccaceae (Chlorophyta; Archaeplastida) from Argentinean Patagonia revealed by environmental DNA survey.

PubMed

Lara, Enrique; Fernández, Leonardo D; Schiaffino, M Romina; Izaguirre, Irina

2017-08-01

We characterized molecularly the first freshwater member ever reported for the family Bathycoccaceae in Lake Musters (Argentinean Patagonia). Members of this family are extremely numerous and play a key ecological role in marine systems as primary producers. We cloned a fragment comprising the SSU rRNA gene+ITS region from environmental DNA using specific mamiellophyte primers. The unique SSU rRNA gene sequence obtained clustered robustly with Bathycoccus prasinos. Analysis of the two-dimensional structure of the ITS region showed the presence of a typical supplementary helix in the ITS-2 region, a synapomorphy of Bathycoccaceae, which confirmed further its phylogenetic placement. We finally discuss the possible causes for the presence of this organism in Lake Musters. Copyright © 2017 Elsevier GmbH. All rights reserved.

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

PubMed

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.

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

NASA Technical Reports Server (NTRS)

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.